Specialty Pumpkin: Laying the Groundwork for an Emerging Crop and Lucrative Products

Progress report for LS21-360

Project Type: Research and Education
Funds awarded in 2021: $399,999.00
Projected End Date: 03/31/2024
Grant Recipients: University of Florida; University of Puerto Rico ; University of Georgia
Region: Southern
State: Florida
Principal Investigator:
Dr. Geoffrey Meru
University of Florida
Co-Investigators:
Dr. Carlene Chase
University of Florida
Dr. Andrew MacIntosh
University of Florida
Dr. Angela Ramírez
University of Puerto Rico
Dr. Jorge Ruiz-Menjivar
University of Florida
Andre da Silva
Auburn University
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Project Information

Abstract:

Specialty pumpkins such as the tropical pumpkin or calabaza (Cucurbita moschata) fulfill lucrative emerging markets for the crop in the U.S. The desirable characteristics of the fruit include high soluble solids for the brewing industry; deep orange/non-stringy flesh for canning/ novel food-ingredient; and a favorable combination of flavor, fruit size, flesh texture/color for the fresh-cut market. Additionally, quality seeds are required by the snack food industry, and for pumpkin seed butter, which are non-allergenic and nutritious alternatives to nuts and nut butters. Organically grown produce is a priority for many restaurants, community supported agriculture, and for baby food. Optimized organic and conventional cropping systems will be needed to maximize profitability for growers supporting these industries. We propose a two-year, multi-institutional, transdisciplinary, regional project with University of Florida as the lead institution, in collaboration with University of Puerto Rico and University of Georgia. Our systematic approach includes Social Science research that will engage growers, industry stakeholders, and consumers to assess potential risks and benefits of specialty pumpkin production, as well as barriers to acceptance. Our breeders will provide germplasm that will be evaluated in Florida, Georgia, and Puerto Rico to select those most suitable for release as cultivars for organic and conventional systems. The suitability of the germplasm for food applications will be addressed by our food scientists who will also examine the functional attributes of the fruit and processed products. Additionally, our horticulturists will assess germplasm suitability for a conservation tillage, organic system based on summer cowpea and winter rye cover crops grown in sequence. This system will offer a sustainable, no plastic mulch approach that has the potential to suppress weeds and plant-pathogenic nematodes while improving soil health and soil fertility. We will monitor for pest and beneficial arthropods in all cropping systems to garner information that allows for the development of cultural and biological control tactics for arthropod pest management. We will conduct a thorough study of the potential acceptance of specialty pumpkin with key players in the production system from farm to consumer. This will include interviews with farmers and operators of sales points conducted through video conferencing. We will also conduct a nationwide consumer acceptance study. These three components will allow us to identify and address barriers to acceptance and take advantage of opportunities to build demand. Farmer engagement throughout the project is an important component of this project. We will work with growers to conduct on-farm trials based on treatments of their choice, grower assessments of on-station research, and an industry advisory panel that provides oversight of the overall progress of the project and makes recommendations to improve outcomes. The development of specialty pumpkin cultivars will improve environmental sustainability with a resilient, adapted crop in which pests, pathogens, and weeds will be managed with an integrated suite of physical, cultural, and biological methods. Farmer economic sustainability is also expected to improve since our systems approach will yield results that will overcome barriers to crop adoption and will identify lucrative products that are desired by consumers. 

Project Objectives:
  1. Assess potential risks/benefits of specialty pumpkin production and barriers to acceptance.
  2. Evaluate pumpkin germplasm lines and cultivars for use as flesh, seeds, and as product ingredients.
  3. Determine yield, fruit quality and disease resistance of tropical pumpkin cultivars in the Southeastern U.S. and Puerto Rico in organic and conventional cropping systems and determine phenotypic relationships among nutrition, flavor and fruit size traits in select germplasm.
  4. Develop cropping systems for sustainable organic and conventional specialty pumpkin production.
  5. Monitor arthropod pests and beneficial insects in specialty pumpkin to design cultural and biological control tactics for organic and conventional systems.

Cooperators

Click linked name(s) to expand/collapse or show everyone's info
  • Keith Anderson - Producer
  • Dr. Alex Bolques (Researcher)
  • Dr. Oscar Liburd (Researcher)
  • Dr. Gabriel Maltais-Landry (Researcher)
  • Margie Pikarsky - Producer
  • Dr. Amy Simonne (Researcher)
  • Dr. Marilyn Swisher (Researcher)
  • Dr. Chris Worden - Producer

Research

Materials and methods:

Objective 1: Assess potential risks/benefits of specialty pumpkin production and barriers to acceptance.

Team: Jorge Ruiz-Menjivar, Ph.D. | Assistant Professor of Consumer Economics | Family, Youth, and Community Sciences. Marilyn E. Swisher, Ph.D. | Professor of Sustainable Agriculture | Family, Youth and Community Sciences & Center for Sustainable and Organic Food Systems. Yong Liu, Ph.D | Research Assistant | Family, Youth and Community Sciences Kaylene Sattanno | Research Coordinator | Center for Sustainable and Organic Food Systems​

 

Activity 1: Consumer survey to understand consumer perceptions, preferences and willingness to pay for specialty pumpkin based on country of origin, certification labels other food product attributes.

 

Institutional Review Board approval. We obtained IRB approval to collect data with 450 American consumers via Qualtrics (IRB202000525)

  1. We reviewed the literature to identify social, economic, and psychological factors that affect the purchase decision-making of fruits and vegetables. In addition, identifying these factors led to a study where we conducted a formal bibliometric on the changes in eating habits and dietary patterns amid the COVID-19 pandemic. The coronavirus disease 2019 (COVID-19) pandemic altered and disrupted consumers’ daily routines, including food consumption behavior. Data for this global bibliometric study were collected from the Scopus database, resulting in a sample of 497 peer-reviewed articles published between 2020 and 2022.

 

Survey Development.

  • Informed by the extant literature on food preference for new food products, native foods, and consumerdemand for fresh produce. ​
  • Conceptual model guided by the Theory of Planned Behavior-TPB (Attitude, Subjective norm, Perceivedbehavioral control, and Behavioral intention)​
  • Design of Discrete Choice Experiments (DCE) with five attributes.

 

    Structure: (a) Informed consent and inclusion criteria Q's; (b) cooking Q's, food neophobiascale, consumer trust scales, TPB Q's; (c) Importance of Calabaza attributes and (d) Discrete Choice (DC) experiment. 

•	Structure: (a) Informed consent and inclusion criteria Q's; (b) cooking Q's, food neophobia scale, consumer trust scales, TPB Q's; (c) Importance of Calabaza attributes and (d) Discrete Choice (DC) experiment.

We used scales such as the Food Neophobia Scale (Rabadán, & Bernabéu, 2021), validated instruments measuring Food Agency, Skills and Confidence (Wolfson et al., 2020), and Trust (farmer, retailer, and government and supply food system).

Rabadán, A., & Bernabéu, R. (2021). A systematic review of studies using the Food Neophobia Scale: Conclusions from thirty years of studies. Food Quality and Preference, 93, 104241.

Wolfson, J. A., Lahne, J., Raj, M., Insolera, N., Lavelle, F., & Dean, M. (2020). Food agency in the United States: associations with cooking behavior and dietary intake. Nutrients, 12(3), 877.

Data collection. We collected data from 450 American consumers in February 2022.

Sample: 450 American consumers​

  • Nationally representative panel accessed via Qualtrics XM (Predetermined quotas: Gender (F: 52%; M:48%), Age (18-34: 30%; 35-54: 32%; 55+: 38%), Race (White: 75%; Non-White: 25%), and Ethnicity (Hispanic/Latino: at least 30%). ​
  • Compensation: $9.26 per respondent.​
  • Inclusion criteria: U.S. Adults 18+ and must have consumed/ purchased fresh pumpkins or butternutsquash for cooking purposes within the last two months.​
  • Cross-check questions (Birth year and Age) and Survey completions under 5 minutes were not deemed

 

Analysis.  Descriptive statistics and Partial Least Squares Structural Equation Modeling (PLS-SEM).

  1. A subsample of 300 consumers will be recruited to evaluate the effect of socio-psychologicalfactors (i.e., food agency, cooking, and food skills, cooking confidence, perceived behavioral control, subjective norms, attitude, food neophobia, consumer trust and certification label) on purchase intention of fresh calabaza and fresh produce. The results of the bibliometric search informed the data collection instrument for phase II of our consumer study. The instrument was developed based on the extant literature related to food preference for new food products, native foods, and consumer demand for fresh produce. Also, we employed the Theory of Planned Behavior-TPB (Attitude, subjective norm, perceived behavioral control, and behavioral intention) to guide the development of our instrument, research questions, and hypotheses. Data will be analyzed via Partial Least Squares Structural Equation Modeling (PLS-

Activity 2: Interviews with actors in the distribution system and sales points ranging from farmers’ markets to traditional commercial outlets, to identify key bottlenecks and opportunities to market in a variety of venues. ​

  1. We developed a 22-question interview instrument and obtained IRB approval (IRB 202102464) to conduct interviews with produce managers in the Southeast. Interviews will be completed in English or Spanish, as needed.  We will identify traits of importance to grocers as barriers or as incentives, such as:
    1. Seasonal availability​
    2. Size of the squash​
    3. Color of the squash rind and flesh​
    4. In-store perishability​
    5. Size of standard shipping units (e.g., bin vs. 50 box)​
    6. Value of the Fresh from Florida identity for calabaza​
    7. Value of country-of-origin labeling​
    8. Information about how to prepare the squash, including recipes.
  2. Our target sample is general managers, produce managers and others who make decisions about produce stocked at international specialty markets that typically carry calabaza. This includes a focus on points of sale in venues serving Latinx, Afro-American and Afro-Caribbean and other clientele groups who have a food culture heritage of consuming calabaza.
  • We will complete 30 interviews throughout the Southeast in 2023.

 

Activity 3: Interviews with farmers to identify key barriers, opportunities and research priorities for specialty pumpkin production. 

 

  1. We developed an interview instrument and obtained IRB approval (IRB 202102464) to conduct interviews with farmers in the Southeast. Interviews will be completed in English or Spanish, as needed.
  2. We are assessing grower interest in producing calabaza among non-producers​ and interest in increasing calabaza production ​among current producers. Our target sample includes producers that serve Latinx, Afro-Caribbean, Afro-American, and other clientele groups who have a food culture heritage of consuming calabaza.
  • We will complete 30 interviews throughout the Southeast in 2023. We have completed seven to-date.

Activity 4: Assessments of field research to identify most and least promising calabaza breeding lines currently under evaluation.

  1. We developed a research assessment instrument and obtained IRB approval (IRB 202102464) to conduct assessments in Florida and Puerto Rico. Assessments in Puerto Rico will be completed in Spanish.  Participants will identify their favorite and least favorite calabaza breeding lines currently under evaluation in this project.  They will also identify which traits are of greatest importance when selecting favorite and least favorite calabaza breeding lines.
  2. Our target sample is current calabaza producers, farmers interested in adding calabaza to their production system, and technical advisors that consult with farmers that grow calabaza.
  • We will conduct three research assessments during this project. We scheduled a research assessment in February 2023 but had to cancel due to a faculty strike at the University of Puerto Rico.  We will reschedule and conduct assessments in Florida and Puerto Rico in 2023 and 2024.

Activity 5: Advisory council meetings to review biological research and consult in the development of future calabaza research.

  1. We obtained IRB approval (IRB 202102464) and recruited eight panel members to attend annual or bi-annual meetings totally up to three hours per year. The advisory council is a permanent governing body for the project's duration that assesses overall results, discusses progress and impacts, and determines if the project plan requires adjustments.
  2. Our panel consists of four calabaza farmers from Florida, one calabaza farmer and one Extension faculty member from Puerto Rico, and one calabaza farmer and one Extension faculty member from Alabama. We extended invitations to an Extension faculty member from Florida and two calabaza farmers from Puerto Rico and Alabama, respectively.  We hope to add those additional members in 2023/2024.
  3. We hosted our first advisory council meeting in January 2023. Seven panel members were in attendance.  We will host additional meetings in 2023 and 2024.

 

Objective 2: Evaluate pumpkin germplasm lines and cultivars for use as flesh, seeds, and as product ingredients.

Team: Andrew MacIntosh and Amy Simonne

Activity 1: Comparative analysis of qualitative attributes for selection of calabaza genotypes adapted to subtropical climates

Materials and methods:

Calabaza Germplasm

A total of eight winter squash genotypes including five new germplasm hybrids and three commercial cultivars were evaluated (Table 3-1).

Table 3-1.  Pedigree of calabaza hybrids and cultivars used in the study.

 

Entry

Pedigree

Parental Internode

Waltham Butternut

Open pollinated

medium vine

UFTP 8

E-5 x TP331

long x short

UFTP 22

TP331 x TP411

short x short

UFTP 24

G38-2-38 x JP5

short x long

UFTP 38

TP331 x Fairytale

short x long

UFTP 42

Soler* x TP331

long x short

‘Soler’

Open pollinated

long

‘La Estrella’

G38-2-38 x ‘La Primera’

short x long

Fifteen seeds each for the eight squash genotypes were sowed on March 15, 2022, in a greenhouse in plastic seedling trays containing potting mix and starter fertilizer in Gainesville, FL. At two-weeks old, the seedlings of each germplasm line were transplanted on March 31, 2022, into a single plot in the field at the University of Florida, Plant Science Research and Education Unit in Citra, FL, USA.  Weekly pest and fertilizer management was conducted following the recommendations for pumpkins in the Vegetable Production Handbook of Florida (Dittmar, 2022). On July 1, 2022 (91 growing days), the mature tropical pumpkin and butternut squash genotypes were manually harvested and labeled. Fruit maturity was determined by a combination of expected rind-color and rind firmness using the thumb pricking technique. If light pressure from a thumb nail on the skin of the fruit was able to leave a slight indentation which is then fully recovered instantaneously, the fruit was deemed ripe for harvest. Conversely, if the light pressure from a thumb nail on the skin leaves an indent that does not recover, the fruit was not harvested. The fruits were wiped clean and labeled with germplasm line numbers directly on the fruit. A representative sample of 10–15 calabaza fruits per genotype were used for analysis. Using the United States Department of Agriculture (USDA) recommended storage conditions for curing and long-term storage (Gross, 2016), after harvest, calabaza were stored in a 75º F/24º C and 65% relative humidity (RH) room to cure for 7 days. This was performed to ensure that the respiration rate of the pumpkins did not escalate, resulting in weight loss and fruit degradation (Adeeko, 2020).  The cured pumpkins were transferred into a permanent storage cooling room at 10º C and 60% RH room as described by Gross (2016) for 7 days until processing. Each fruit was initially weighed, then cut in half, peeled, and de-seeded then weighed again. The peeling was done using a household peeler until no visible skin and white flesh were present. For de-seeding, a large serving spoon was used to remove all seeds and strings of fibers until uniform flesh was achieved. All flesh was cubed using a ½-inch cuber (Nemco N55450, Hicksville, USA) to achieve ½-inch (12.7 mm) samples. A uniform sample of each germplasm line was created by combining all cubes from 10-15 calabaza for random analysis. For texture analysis, ideal cubes (squares that were ½ -inch by ½ -inch by ½ -inch) were separated from the miscellaneously shaped samples. The ideal cubes were used for texture analysis to ensure as much uniformity in pressure of the sample. Miscellaneously shaped samples were used for all other analyses, as they involved blending. All samples were stored in single layer vacuum sealed bags at 4º C for up to 1 week until analyzed.  

  Flesh Yield 

To determine the flesh yield, each calabaza fruit was initially weighed. Each fruit was cut in half and labeled on both halves before de-seeding and peeling. After de-seeding and peeling, the two halves were reweighed together to determine the fruit yield shown in Eqn. 3-1. This was done to all 10-15 C. moschata fruit for the 8 cultivars of interest.

Where the edible portion of the fruit was calculated as ratio with the final weight being the edible flesh after processing and initial weight being the weight of one unadulterated tropical squash.

Where the edible portion of the fruit was calculated as ratio with the final weight being the edible flesh after processing and initial weight being the weight of one unadulterated tropical squash.

Color  

The color of the pumpkin flesh was evaluated immediately after being cut in half (within 5 minutes) using a tristimulus color analyzer (Konica Minolta, C4-400, Tokyo, Japan) equipped with an 8-mm diameter measuring area following the methods of Itle, with slight variation (Itle, 2009). This color system measures the L* (100 = white; 0 = black), a* (+, red; -, green) and b* (+, yellow; -, blue) values of a sample. These can be used to calculate Chroma (C*) (Equation 3-2) and hue angle (h*) (Equation 3-3), which are used to compare and contrast color samples for food (Pathare, 2012). Chroma represents the colorfulness of a sample and differentiates between this color and a grey color of the same lightness.

Fruits were cut vertically, and three measurements were taken per fruit, with 5 fruits representing each germplasm line. The three locations of flesh measurement are shown in Figure A-1, being right below the stem, mid-way down the fruit (equator), and right above the base, avoiding the seed cavity and peel (≈10 mm) for the most comprehensive sampling per fruit (Itle, 2009). 

Peroxidase (POD) 

The POD of the flesh was determined following the methods of Sampedro and Zhou, with slight modifications (Sampedro, 2014; Zhou, 2017). Samples (20 g) were blended with 20 mL of 4% polyvinyl polypyrrolidone (PVPP) in 0.2M aqueous phosphate buffer (pH = 6.5) for 2.5 minutes. Blended samples were held at 4ºC for 1.5 hours. The samples were then centrifuged at 12000 rpm using a centrifuge (Beckman J2-21, Palo Alto, CA, USA) for 20 minutes at 4ºC. The supernatant was vacuum filtered using 9.0 mm filter paper and gathered in a test tube for POD activity.  

A 0.1 mL aliquot of sample extract was added to 0.2 mL of 1.5% H2O2 and 3.0 mL 1.0% (v/v) guaiacol (dissolved in 0.2 M phosphate buffer, pH 6.5) in a test tube. The contents were vortexed for 5 seconds to achieve an even mixture and placed in a 30°C water bath for 20 seconds. The sample was poured into a quartz cuvette and the absorbance was measured using a UV spectrophotometer (Shimadzu, UV-1900, Kyoto, Japan) every half second for 120 seconds. Enzyme activity of POD (Abs/min) was determined using the slope from the linear portion of the reaction curve at Δ470 nm. 

Texture (Double Compression) 

The texture profile of the flesh was determined using a double compression test following Marian, with some variation (Marian, 2020). The flesh collected for analysis was only from the mid-section (labeled II) of the pumpkin at a distance of 4 mm from the skin for uniformity, as shown in Figure A-2. Due to the curvature of the calabaza, the axis of the square samples was perpendicular to the surface of the skin. 

Ideal cubes (1/2-inch or 12.7 mm) with vertical fiber grain orientation underwent a double compression test. A Texture Technologies TA.XTPlus Connect (Hamilton, MA, USA) texture analyzer outfitted with a 25 mm diameter cylindrical probe was used. The speed of the measuring head in each cycle was 0.83 mm·min−1. The probe descended until 50% of the sample height (6.35 mm) compression was achieved. The time interval between the first and second compression was 5 seconds. Analysis was performed on 12 cubes from each representative germplasm sample. Parameters measured for double compression include firmness/hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, and resilience.

 

Total Soluble Solids (Brix) 

Brix for calabaza fruit samples (200 g) was determined by blending the flesh until homogeneous. Samples were then centrifuged at 12000 rpm using a centrifuge (Beckman J2-21, Palo Alto, USA) for 20 minutes at 20ºC. The supernatant was vacuum filtered using 9.0 mm filter paper and measured using a benchtop refractometer with water bath temperature correction set for 20ºC (LeicaAbbe Mark ii refractometer, model 13104800, Buffalo, NY, USA) (USDA, 2020). 

Titratable Acidity (TA), pH, and Malic Acid 

Titratable acidity was determined following Papanov and AOAC methods with slight modifications (Papanov, 2021; AOAC, 2000). A total of 200 g of calabaza was blended until homogeneous. Samples were then centrifuged at 12000 rpm using a centrifuge (Beckman J2-21, Palo Alto, CA, USA) for 20 minutes at 20ºC. The supernatant was vacuum filtered using 9.0 mm filter paper and collected. The titratable acidity was expressed as a percentage of malic acid. This was determined through titration of 25 mL of pumpkin juice plus 3 drops of 1% phenolphthalein in 95% ethanol as an indicator with 0.1 M NaOH to a pH value of 8.1. pH was determined using a pH probe (Fisher Scientific, Accumet AB15 basic, Waltham, MA, USA) after calibrating with buffer solutions of pH 4.0, 7.0, and 10.0 following the operational instructions of the instrument.

Yeast Fermentable Extract (YFE) 

Yeast fermentable extract was determined following the American Society of Brewing Chemists (ASBC) WORT 5 method (ASBC, 2010). A 600 g sample of calabaza was blended until homogeneous. Samples were then centrifuged at 12000 rpm using a centrifuge (Beckman J2-21, Palo Alto, CA, USA) for 20 minutes at 20ºC. The supernatant (100 mL) was added to 2 g of lager yeast (Saccharomyces pastorianus) and 3 drops of defoamer (Atmos 300K) in 250 mL Erlenmeyer flasks for fermentation. Flasks were placed into a shaker water bath to ferment for 48 hours at 25ºC. Fermented samples (50 mL) were added to 0.5 g of sparkaloid (clarification agent) and filtered using 9.0 mm filter paper. This filtrate was further filtered using 0.45 µm syringe filter until 12 mL of sample was collected. Samples were placed in a sonicator (Branson ultrasonic cleaner B-52 240 Watts, Brookfield, WI, USA) for 30 seconds to remove any CO2 bubbles and run through an alcohol and extract meter (ALEX 500 – Anton-Paar, Houston, TX, USA) for a beer sample.  

Statistical Analysis 

All tested parameters were analyzed using a one-way ANOVA with Duncan separation in Statistical Analysis Systems™ 9.4 (SAS Inst. Inc., Cary, NC) to distinguish significant differences at α = 0.05 between each calabaza germplasm for the following parameters: L*, a*, b*, chroma, hue angle, pH, TA, malic acid, Brix, POD, YFE, hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, and resilience. Each parameters mean was then used to run a Pearson Correlation in Microsoft Excel to describe the relationship between all tested parameters. 

 

Activity 2: Chemical and physical properties of winter squash and their correlation with sensory attributes

The eight winter squash genotypes were grown at the Plant Science Research and Education Unit (PSREU) in Citra, Florida, as previously reported under activity 1. Each fruit was peeled, de-seeded, and cubed using a ½-inch cuber (Nemco N55450, Hicksville, USA). A uniform sample of each genotype was created by combining 10-15 whole cubed calabaza fruit for analysis. Ideal cubes (½ -inch by ½ -inch by ½ -inch) were used for texture analysis and sensory testing to ensure consistent pressure and cooking throughout the sample. Non-ideal shaped cube samples were used for all other analyses, as they involved blending. The uniform sample of  fruit cuts were then divided in half (roughly 35 lbs) and stored at 4º C or -20º in single layer vacuum bags (11″ by 12″) (Wevac 11″ by 150′, Hong Kong, China) until analysis.

Cooking

Microwave treatment was conducted using a GE JES1145SHSS microwave (Louisville, USA). Based on preliminary research, a 6-minute cook time with 60% efficiency and 30 cubes on a plate (Corelle, Vitrelle, Downers Grove, USA) was determined to be sufficient to cook the ½ -inch cubes to an internal temperature of 80º C, sustained for 3 minutes. To ensure cooking consistency, a uniform cube orientation from the rotating plate center was used (Figure 1).

Figure 1. Cube orientation on plate for microwave treatment

Figure 1. Cube orientation on plate for microwave treatment

Sensory

The consumer sensory evaluation took place at the University of Florida sensory lab. Eighty-nine untrained panelists were recruited for a two-day panel to taste four germplasm line samples per day with the fresh-cooked (fresh) panel being 1 month prior to the frozen-cooked (frozen) panel. Four genotypes from the first sensory panel evaluation were chosen at random and presented on the first day of the frozen panel evaluation. The sensory lab comprised of eighteen identical booths, each equipped with a computer and sliding door for sample. During the sensory evaluation, 2-3 cubes (12-18 g) were presented to panelists independently in a 4-ounce clear plastic cup with a three-digit code after being cooked and cooled for 2 minutes (serving temperature 22ºC). All possible orders of presentation were presented an equal number of times. Attribute questions were collected using a nine-point hedonic scale (1- extremely dislike; 9 – extremely like) and the attributes assessed included appearance liking, color liking, overall liking, flavor liking, sweetness liking, and texture liking. 

Color  

Color of cooked and cooled calabaza flesh was assessed using a tristimulus color analyzer (Konica Minolta, C4-400, Tokyo, Japan) equipped with an 8-mm diameter measuring area, following modified methods of Itle (2009). The color system measures the L* (100 = white; 0 = black), a* (+, red; -, green) and b* (+, yellow; -, blue) values, which can be used to calculate Chroma (C*)  and hue angle (h*), which have been used to compare and contrast color samples for food (Pathare, 2012). Chroma indicates the saturation of color for a sample. 

 The hue angle (h*) is determined based on the range of color values represented by a and b. A hue angle of 0 or 360 degrees indicates a red hue, while angles of 90, 180, and 270 degrees represent yellow, green, and blue hues respectively, as per the findings of Lopez (1997).

Peroxidase (POD) 

The POD activity of calabaza flesh was assessed according to the modified methods of Sampedro and Zhou (Sampedro, 2014; Zhou, 2017). A 20g sample of cooked calabaza flesh was blended with 20 mL of aqueous 4% polyvinyl polypyrrolidone (PVPP) in 0.2M phosphate buffer (pH = 6.5) for 2.5 minutes. After incubation at 4ºC for 1.5 hours, the samples were centrifuged at 12000 rpm for 20 minutes at 4ºC using a Beckman centrifuge (Beckman J2-21, Palo Alto, USA). The supernatant was vacuum filtered using 9.0 mm filter paper and gathered for POD activity.  

The filtered sample (0.1 mL extract) was mixed with 0.2 mL of 1.5% H2O2 and 3.0 mL 1.0% (v/v) guaiacol (dissolved in 0.2 M phosphate buffer, pH 6.5). The mixture was incubated in a water bath at 30°C for 20 seconds, poured into a quartz cuvette, and the absorbance was measured using a UV spectrophotometer (Shimadzu, UV-1900, Kyoto, Japan) at 470 nm every half second for 120 seconds. The enzyme activity of POD (Abs/min) was determined using the slope from the linear portion of the reaction curve with all germplasm lines run in triplicate. 

Texture (Double Compression) 

The flesh for texture analysis was prepared by using only the middle third of each fruit and a 4 mm from the skin (See Figure 2). Cubes of cooked flesh (1/2-inch or 12.7 mm) were assessed using a double compression test based upon the methods described by Marian (2020). A Texture Technologies TA.XT Plus Connect (Hamilton, MA, USA) texture analyzer with a 25 mm diameter cylindrical probe was used, with a probe descent rate of 0.83 mm/min. The sample had fiber grain oriented vertically and was compressed to 50% of their original height (6.35 mm) with a 5 seconds interval between the first and second compression. Texture analysis was performed on n=12 ideal cubes from each germplasm line to determine hardness, adhesiveness, cohesiveness, springiness, chewiness, resilience and gumminess.

Figure 2. Calabaza sampling location (A) and texture analysis sample size (B).

Figure 2. Calabaza sampling location (A) and texture analysis sample size (B).  

 Total Soluble Solids (Brix) 

For Brix analysis of calabaza fruit, 200 g of cooked fruit were homogenized using a blender. The samples were then centrifuged at 12000 rpm using a Beckman centrifuge (Beckman J2-21, Palo Alto, USA) for 20 minutes at 20ºC. The supernatant was vacuum filtered using 9.0 mm filter paper and measured using a benchtop refractometer with water bath temperature correction set for 20ºC (LeicaAbbe Mark ii refractometer, model 13104800, Buffalo, USA) (USDA, 2020). 

Titratable Acidity (TA), pH, and Malic Acid 

The titratable acidity of cooked calabaza was determined following modified Papanov and AOAC methods (Papanov, 2021; AOAC, 2000). A 200 g sample of cooked calabaza was homogenized and centrifuged at 12000 rpm using a Beckman centrifuge (J2-21, Palo Alto, USA) for 20 minutes at 20ºC. The supernatant was vacuum filtered using 9.0 mm filter paper. Titratable acidity was expressed as a percentage of malic acid and determined by titration of 25 mL of calabaza juice with 0.1 M NaOH using 3 drops of 1% phenolphthalein (in ethanol) as an indicator, until reaching a pH of 8.1. pH was measured using a pH probe (Fisher Scientific, Accumet AB15 basic, Walthan, USA) calibrated with buffer solutions (pH 4.0, 7.0, and 10.0) as per manufacturer’s instructions.

Statistical Analysis 

Sensory Analysis 

Two-way ANOVA followed by Duncan’s Multiple Range Test (MRT) was performed in Statistical Analysis Systems™ 9.4 (SAS Inst. Inc., Cary, NC) for all sensory parameters analyzed. Statistical significance was determined at α=0.05. Duncan’s (MRT) was used to denote significant differences between samples in overall liking, sweetness liking, flavor liking, appearance, color liking, texture liking, and perchance intention. 

Profile parameters 

One-way ANOVA followed by Duncan’s (MRT) was performed using Statistical Analysis Systems™ 9.4 (SAS Inst. Inc., Cary, NC) for all quality measurements. Statistical significance was determined at α=0.05. Duncan’s MRT was used to denote significant differences between samples in Brix, titratable acidity, L*, a*, b*, chroma, hue angle, hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, resilience, and POD. 

 Sensory results – Principal Component Analysis (PCA) plots 

Pearson correlation test and PCA were performed in Statistical Analysis Systems™ 9.4 (SAS Inst. Inc., Cary, NC) for both fresh and frozen qualitative and sensory attributes collected from the research conducted to determine statistical significance and correlation. Additionally, SAS was used to create a principal component analysis plot using a correlation matrix to visually represent the correlations amongst attributes.  

 

Activity 3: Determination of macronutrients and bioactive compounds of calabaza germplasm

Calabaza Samples

The eight winter squash genotypes were grown at the Plant Science Research and Education Unit (PSREU) in Citra, Florida, as previously reported under activity 1.

Calabaza Subsample Preparation

A metal borer with a 21 mm diameter was used to remove a single plug of mesocarp from the widest equatorial point of each sample calabaza fruit (Figure 3-1). Each plug was reduced to approximately 4 mm in length and approximately 2 grams in mass. The rind was removed from each plug and a handheld colorimeter (Konica Minolta Chroma Meter CR-400, Ramsey, NJ, USA) employing diffuse illumination, a 0° viewing angle, illuminant C, and the L* a* b* color space was used to measure L* a* b* values of the rind side of exposed mesocarp, in triplicate. Each sample fruit was then cut in half from stem to blossom end opposite the point from which the plug was drawn. The rind and seeds were discarded and mesocarp from the half fruit was blended in a food processor until it was similar in size to coarse sea salt.

Blended subsamples were randomly apportioned by assay, wrapped in aluminum foil, and vacuum sealed. For moisture content analyses, 2 grams of ground subsample were wrapped in foil and vacuum-sealed, while 20 grams of ground subsample were reserved for both carotenoid and phenolic analyses. Duplicate subsamples were preserved for each assay and the preparation repeated for each of the three samples from each of the nine experimental breeding lines and butternut squash. The remaining mesocarp was also wrapped in aluminum foil and vacuum sealed. Remaining mesocarp, moisture analysis subsamples, and subsamples preserved for carotenoid and phenolic analyses were held at -26 °C until the analyses were performed, approximately 1 – 6 months following preservation.

Each subsample of calabaza mesocarp reserved for ascorbic acid analysis was weighed (approximately 2 g) and its mass recorded before being submerged in 20 mL aqueous 3% meta-phosphoric acid held within conical plastic test tubes fitted with screw caps. The test tubes were then covered in aluminum foil and stored at -20 °C until the analysis was performed. Duplicate subsamples of calabaza mesocarp reserved for ascorbic acid were frozen at -26 °C without preservative. All frozen subsamples were brought to room temperature before being analyzed.

Determination of Moisture Content

The moisture content of the calabaza varieties was assessed using AOAC Official Method 930.15, in which a forced draft moisture oven was regulated to 135 ± 2 °C and 2 g ground subsamples (FDA 2021; Carvalho et al. 2011) were apportioned into moisture tins and dried for 2 hours ± 5 minutes or until the mass of the subsamples plateaued. Upon drying, covered moisture tins were placed in a desiccator to cool. Once cooled, the loss in weight on drying (LOD) was used to calculate the moisture content on a wet weight basis (wwb) 

Determination of Total Soluble Solids

Ground calabaza subsamples were pressed through cheesecloth and the liquid fraction applied to the sample well of a temperature-compensating refractometer (r2i300, Reichert Technologies, Depew, NY, USA). Total soluble solids were measured in triplicate, averaged, and reported in °Brix for each calabaza sample.

Determination of Carotenoids

A direct solvent extraction method based on the method used by Kimura et al. (2007) for sweet potatoes was used to extract carotenoids from the calabaza and butternut squash subsamples. Duplicate subsamples, weighing approximately 3 grams each, were homogenized (PowerGen 700D, Fischer Scientific, Waltham, MA, USA) in 0.001% butylated hydroxytoluene (BHT) in hexane (Fischer Chemical, Fair Lawn, NJ, USA) for two minutes at 8000 RPM. Homogenized subsamples were filtered into respective beakers through Whatman #2 filter paper-lined glass funnels until homogenate was free of mesocarp particulate. The homogenates were then filtered into new beakers through anhydrous sodium sulfate-filled Whatman #42 filter paper-lined glass funnels until solutions were no longer visibly turbid. Once clear, 200 μL of homogenate were transferred to a 96-well microplate and the absorbance of each subsample was measured at 450 nm at 30 °C. Calibration curves were constructed using β-carotene standards (Sigma Aldrich, St. Louis, MO, USA) in concentrations ranging from 0.6 μM to 3.0 mM. The concentrations of carotenoids extracted were reported as β-carotene equivalents (βCE). The following equation was used to convert β-carotene equivalents to retinol activity equivalents (RAE).

1 μg RAE = 12 μg β-carotene

 

Determination of Ascorbic Acid

This method was adapted from AOAC Method 967.21, AOAC Official Methods of Analysis 45.1.14 [2], and modified by Eitenmiller and Landen Jr (1999). This titrimetric method was performed in duplicate using subsamples from three calabaza fruit samples from each of the nine experimental breeding lines plus Waltham butternut squash, totaling 60 subsamples. To extract ascorbic acid, 2.0 g ground calabaza mesocarp were homogenized with 35 mL of 3% meta-phosphoric acid (w/v) using a high shear homogenizer (PowerGen 700D, Fisher Scientific, Waltham, MA, USA). The homogenate was filtered using fluted Whatman #2 filter paper.

The standard dye was prepared by dissolving 251 mg 2,6-dichloroindophenol (DCIP) sodium salt hydrate (Sigma-Aldrich, St. Louis, MO, USA) in 250 mL of deionized water containing 211 mg sodium bicarbonate (NaHCO3) (Fisher Chemical, Fair Lawn, NJ, USA). The DCIP solution was diluted to 1000 mL with deionized water. The dye was filtered through fluted Whatman #2 filter paper and stored under refrigeration (4 °C) in an amber glass bottle. To determine the equivalency factor of DCIP concentration to ascorbic acid concentration, 2 mL of ascorbic acid standard were added to 5 mL of the 3% meta-phosphoric acid extractant and titrated with DCIP solution until a light, rose pink color persisted for five seconds or longer. DCIP concentration was expressed as mg ascorbic acid equivalent per 1.0 mL dye solution. A blank was determined by titrating 7 mL of solvent containing water equal to the average volume of dye required to titrate the ascorbic acid standard.

Determination of Phenolic Content

This method was adapted from the Folin-Ciocâlteu assay of Singleton and Rossi (1965, as cited by Ainsworth and Gillespie, 2007) with modifications described by Ainsworth and Gillespie (2007) and Loayza Davila (2014). This method was performed in duplicate using three fruits from each experimental breeding line plus Waltham butternut squash, totaling 60 subsamples.  Approximately 0.4 g of ground calabaza mesocarp was homogenized with ice-cold 95% aqueous methanol for two minutes using a high shear homogenizer (PowerGen 700D, Fischer Scientific, Waltham, MA, USA). The homogenate was incubated at room temperature for 48 hours in the dark. Homogenate was then centrifuged at 13,000g for five minutes at room temperature. Then 100 μL each of sample supernatant, gallic acid standard solutions (ranging from 39 μM to 2.5 mM in 95% methanol), and 95% methanol (blank) were added to fresh microcentrifuge tubes. Next, 200 μL of 10% (v/v) Folin-Ciocâlteu reagent was added and the solution vortexed thoroughly. Following the addition of Folin-Ciocâlteu reagent, 800 μL of 700 mM sodium carbonate (Na2CO3) was added to each tube and left to incubate at room temperature for two hours. After incubation, the microcentrifuge tubes were, again, centrifuged for five minutes at 13,000g to pelletize sodium carbonate particulate. From the supernatant in each microcentrifuge tube 200 μL of either sample, standard, or blank were transferred to a clear 96-well microplate and the absorbance of each in each well was read at 765 nm. Gallic acid standards ranging from 39 μM to 2.5 mM concentrations were corrected using a blank and used to construct a calibration curve each time the analysis was performed to calculate the total phenolic compound concentration of each sample, reported as gallic acid equivalents (GAE).

Statistical Analysis

The results of each analysis were compared for statistically significant differences using Tukey’s Honest Significant Difference test performed in Prism (GraphPad software, San Diego, CA, USA) and in R (RStudio, Vienna, Austria, EUR). An alpha level of .05 was used.

 

Activity 4: Correlations between bioactive compound concentrations and tristimulus colorimetric values to approximate moisture, soluble solids, carotenoid content, ascorbic acid content, and phenolic content in calabaza mesocarp

Procedures for  subsample preparation, determination of moisture content, total soluble solids, carotenoids, ascorbic acid, phenolic content, and statistical analysis were the same as those in Activity 3.

 

 

Objective 3: Determine yield, fruit quality and disease resistance of tropical pumpkin cultivars in the Southeastern U.S. and Puerto Rico in organic and conventional cropping systems and determine phenotypic relationships among nutrition, flavor and fruit size traits in select germplasm.

Team: Geoffrey Meru, Angela Ramírez,  and Andre da Silva

Activity 1, 2 and 3 : Performance of calabaza germplasm in Florida (1); Performance of calabaza germplasm in Puerto Rico (2); Performance of calabaza germplasm in Alabama (3)

 

Materials and methods

In 2022, conventional and organic field trials were conducted for twenty calabaza cultivars and breeding lines in Florida, Puerto Rico and Alabama. In Florida, the trials were conducted at the UF/IFAS TREC in Redlands; in Puerto Rico at the UPRM Lajas Substation (conventional) or UPRM AES facilities (organic) and in Alabama at the E.V. Smith Research and Extension Center (conventional and organic). Seedlings were seeded in the greenhouse in a commercial planting mix and transplanted to the field after 14-21 days. The seedlings were arranged in a randomized complete block design with three replications at each production system, each plot with 5 plants. Seedlings were planted on raised beds (PR) or plastic mulch (UF and AL) and with drip irrigation. In-row spacing will be 3 ft, while 6ft between-row spacing was applied. Data was collected on growth habit (bush or vining), flowering time (days to male or female flowering), fruit size, fruit shape, plant vigor, vine length, disease/ insect tolerance, and yield (fruit and seed). At harvest, representative fruits per plot per cultivar were processed to determine fruit quality attributes including, flesh color, flesh thickness, seed-cavity size, and degree brix. Data was analyzed using the GLM procedure of SAS (SAS Institute Inc., Cary, NC).

 

 

Objective 4: Develop cropping systems for sustainable organic and conventional specialty pumpkin production.

Team: Carlene Chase and Gabriel Maltais-Landry; postdoctoral associates – Parmeshwor Aryal and Daniel Boakye

Materials and methods

Activity 1: Evaluation of spring-planted specialty pumpkin germplasm lines with roller-crimped rye mulch

 Trials were established on certified organic land at two field sites, the Plant Science Research and Extension Unit (PSREU), Citra, FL and the North Florida Research and Education Center – Suwannee Valley (NFREC-SV), Live Oak, FL. A reduced tillage system was initiated with the planting of cowpea (Vigna unguiculata) germplasm line US-1136 at 90 lb seeds/acre as a cover crop in Summer 2021 (June 30 at Citra and July 7 at Live Oak) and ‘Wrens Abruzzi’ rye (Secale cereale) was planted at 120 lb seeds/acre one week after roller-crimping cowpea on October 20 at Citra and October 27 at Live Oak. In Spring 2022, the rye cover crop was terminated by roller-crimping, drip tape was installed, and pre-plant fertilizer (Nature Safe 10:2:8) was applied at 90 lb N/acre at both sites. Two-week-old pumpkin seedlings of ten pumpkin/squash lines: UFTP46 (‘La Estrella’), UFTP8, UFTP22, UFTP24, UFTP38, UFTP42, UFTP45, Waltham Butternut squash, Fortuna UPR, and Verde Luz UPR) were transplanted at two weeks after roller-crimping rye on March 30 in Citra and April 8 in Live Oak. Two additional tilled treatments included ‘La Estrella’ evaluated with the rye incorporated and either left without mulch (UFTP46-Inc) or with raised beds covered with black plastic mulch (UFTP46-PM). The treatments were arranged as randomized complete block design with three replications. In each plot (18 ft long and 6 ft wide), 5 pumpkin/squash seedlings were transplanted in a single row with a 3-foot, within-row spacing. Pumpkin fruits were harvested at 80 days after transplanting (DAT) on June 14 in Citra. Marketable fruit number and weight, fruit flesh thickness, diameter, and flesh color were recorded. Two fruits per plot (if a plot has at least 2 fruits) were cut into half to determine fruit diameter, and flesh thickness. No data could be recorded at Live Oak as plants failed to produce flowers and fruits.

Prior to termination, rye biomass was sampled at both locations, dried, ground, and analyzed for nutrient concentrations. Upon termination of the rye cover crop, three treatments were established, all planted with cultivar UFTP46: mulched rye, rye mowed and incorporated without plastic mulch, and rye mowed and incorporated under plastic mulch. In each of these systems, soils were sampled and analyzed for inorganic N at sampling and N release using incubations with fresh soils. A soil subsample was air-dried and sieved, prior to analysis for carbon soil health indicators (permanganate oxidizable carbon [POXC], loss on ignition [LOI]). Pumpkins were planted and grown for spring and summer 2022. Upon pumpkin termination in late summer 2022, soils were sampled again for inorganic N, N release via incubations, and soil health carbon indicators. Soil extracts and air-dried soils that were preserved from this reporting period and the previous reporting period (i.e., fall 2020-summer 2021 growing season) were analyzed for inorganic N via colorimetry and for POXC and LOI using standard protocols. Data were validated, compiled, and analyzed to identify any effects of cover crop termination method on soil properties.

 

Activity 2: Evaluation of fall-planted specialty pumpkin germplasm lines with roller-crimped sorghum-sudangrass mulch

Sorghum-sudangrass (SSG) was planted as a summer cover crop in mid July 2022 at PSREU, Citra and terminated in fall (late September 2022) by roller crimping. Twelve pumpkin germplasm lines were evaluated in a reduced tillage system: UFTP8, UFTP22, UFTP38, UFTP42, UFTP45 (‘Soler’), UFTP46 (‘La Estrella’), UFTP47 (‘Taina Dorada’), UFTP57, UFTP58, Fortuna UPR, Verde Luz UPR and Waltham Butternut squash in Fall, 2022. A tilled strip along the center of each allowed for incorporation of pelleted organic fertilizer. The reduced tillage treatments were compared with UFTP46 where the SSG was incorporated (UFTP46-Inc) and UFTP46 with SSG incorporation and raised beds covered with black plastic mulch (UFTP46-PM). Three-week-old seedlings were transplanted on October 11, 2023 using within-row and between row planting spacings of 3 ft and 6 ft, respectively. The treatments were arranged in a randomized complete block design with three replications. The effect of the SSG mulch on weed suppression was assessed at 35 days after transplanting (DAT), which was followed by mechanical control of the weeds and volunteer SSG. Days to first male/female flowers after transplanting was recorded. Fruits were harvested at 70 DAT in advance of an early freeze. The data collected at harvest included number of fruits, fruit weight (immature fruits), fruit diameter, and shoot dry biomass.

 

Objective 5 Monitor arthropod pests and beneficial insects in specialty pumpkin to design cultural and biological control tactics for organic and conventional systems.

Team: Oscar Liburd

Materials and methods

Activity 1: Effect of variety on insect pest complex of calabaza

From 20 Apr 2022 through 15 June 2022, in situ counts were conducted every other week to monitor for insect pests at both the UF Plant Science Research and Education Unit and the UF Live Oak research station. During the fall season, the same sampling technique was used weekly from 3 Nov to 8 Dec 2022 at the UF PSREU. For in situ counts, two plants per plot were examined using the leaf turn method. Two leaves per plant were turned over and pests and beneficial insects on the leaves were counted and recorded. Weekly squash silverleaf ratings were also conducted in the fall. Three plants per plot were rated for silverleaf on a scale of 0 to 5 where 0 is no silvering and 5 is completely silvered.

Activity 2: Effect of mulch type on insect pest complex of calabaza

A single cultivar of calabaza, UFPT46, was grown using 3 different mulch types: cover crop residue (control), cover crop residue incorporated into raised beds, and raised beds with black plastic mulch. The cover crop in the spring was rye while the cover crop in the fall was sorghum sudan grass. From 20 Apr 2022 through 15 June 2022, yellow sticky traps, clear pan traps, and in situ counts were used to monitor for insect pests at both the UF Plant Science Research and Education Unit and the UF Live Oak research station. During the fall season, the same sampling techniques, except for pan traps, were deployed from 3 Nov to 8 Dec 2022 at the UF PSREU. In situ counts were conducted as detailed above. Pan traps were filled with soapy water, which was changed weekly. Yellow sticky traps were deployed in each plot and collected after 48 h every other week in the spring and weekly in the fall. Weekly squash silverleaf ratings were also conducted in the fall as detailed above.

Research results and discussion:

Objective 1: Assess potential risks/benefits of specialty pumpkin production and barriers to acceptance.

Team: Jorge Ruiz-Menjivar and Marilyn Swisher

Activity 1: Consumer survey to understand consumer perceptions, preferences and willingness to pay for specialty pumpkin based on country of origin, certification labels other food product attributes.

 

  • The results showed that the impact of the COVID-19 pandemic on consumers’ dietary habits and food consumption was heterogeneous across countries, mainly depending on economic country conditions. Our findings indicated that in developed countries with higher purchasing power, there was a reduction in food waste and an increase in local food consumption. For example, studies conducted in these countries found that consumers demanded more “sustainable” food and procured food products using online delivery platforms. This paper will be presented at the 2023 Sociology of Consumption Conference (August 28th, Oviedo, Spain).
  • Taste, price, flesh color, size of calabaza, ease of preparation for cooking, and availability in nearby stores are all important factors reported by American consumers who had purchased calabaza and pumpkin varieties within the last two months.
  • Variety of calabaza, organic label, and packaging were not significant factors that appeared to influence consumers’ decision to purchase calabaza.
  • Based on our conceptual model informed by the Theory of Planned Behavior and using PL-SEM, we found that consumers trust (specifically, trust in food actors and confidence in the food safety system) were strong predictors of purchase intention for calabaza. Cooking habits and skills (as measured by food agency, skills, and confidence) were significantly related to purchase intention. Our results did not support a significant relationship between certification labels (i.e., organic products) and purchase intention.

Importance of Calabaza attributes

Figure: Importance of Calabaza attributes

Activity 2: Interviews with actors in the distribution system and sales points ranging from farmers’ markets to traditional commercial outlets, to identify key bottlenecks and opportunities to market in a variety of venues. ​

  • We developed a 22-question interview instrument and obtained IRB approval (IRB 202102464) to conduct interviews with produce managers in the Southeast.

Activity 3: Interviews with farmers to identify key barriers, opportunities and research priorities for specialty pumpkin production. 

 

  • We developed an interview instrument and obtained IRB approval (IRB 202102464) to conduct interviews with farmers in the Southeast.

Activity 4: Assessments of field research to identify most and least promising calabaza breeding lines currently under evaluation.

  • We developed a research assessment instrument and obtained IRB approval (IRB 202102464) to conduct assessments in Florida and Puerto Rico.

Activity 5: Advisory council meetings to review biological research and consult in the development of future calabaza research.

  • We obtained IRB approval (IRB 202102464) and recruited eight panel members to attend annual or bi-annual meetings totally up to three hours per year. The advisory council is a permanent governing body for the project's duration that assesses overall results, discusses progress and impacts, and determines if the project plan requires adjustments. Our panel consists of four calabaza farmers from Florida, one calabaza farmer and one Extension faculty member from Puerto Rico, and one calabaza farmer and one Extension faculty member from Alabama.  We extended invitations to an Extension faculty member from Florida and two calabaza farmers from Puerto Rico and Alabama, respectively.  We hope to add those additional members in 2023/2024. We hosted our first advisory council meeting in January 2023.  Seven panel members were in attendance. 

A summary of key points:

  • Growers were interested in trialing some of the calabaza germplasm on their farms. These seeds will be distributed to growers in 2023.
  • Growers wished to know how to protect the seedlings from bird and lizard damage. Netted shielding cages were suggested.
  • Growers were interested in earning how to measure sweetness of calabaza on their farms. Information was provided to a suitable equipment to use.
  • Consumer demand was highlighted as the main barrier to adopting calabaza as a new crop. Also resistant to pest and diseases was highlighted as important, especially for organic growers.
  • Growers provided input as to the main components to focus on in the marketing of calabaza e.g. providing information on nutrition, how to prepare for cooking, suggested recipes, change of name from calabaza to something more recognizable e.g. Bellevue butternut.

     

    Objective 2: Evaluate pumpkin germplasm lines and cultivars for use as flesh, seeds, and as product ingredients.

    Team: Andrew MacIntosh and Amy Simonne

    Activity 1: Comparative analysis of qualitative attributes for selection of calabaza genotypes adapted to subtropical climates

     

    Flesh Yield

    Flesh yield for the calabaza varies greatly among the squash genotype (Table 3-2) and are markedly distinguishable from the previously reported values on either extreme (Maynard, 2002). ‘Soler’ was much larger on average than any of the other cultivars (3.5 kg) while the Waltham Butternut cultivar was much smaller on average (0.72 kg). Generally, fruit size in Cucurbita is dependent on genotype but can also be influenced by the environment (Gaspera, 2016; Wetzel, 2019). In certain markets, smaller squash fruits are preferred by consumers due to convenience of handling, dish preparation, and less labor (Costa, 2003). Therefore, small fruit calabaza cultivars might be more desirable for a fresh market within the U.S. compared to large fruit cultivars (Carbonell, 1990).

    Fruit shape, Growth Habit, and Flesh Color

    The calabaza genotypes varied in fruit shape, growth habit and flesh color (Table 3-3). The fruit shapes observed spanned from globe shaped (UFTP 8, UFTP 22) to round shaped (UFTP 24, ‘La Estrella’) to oblate shaped (UFTP 38, UFTP 42, ‘Soler’) and Bell-shaped (Butternut). Calabaza fruit shapes are dependent on the parent lineage (Ferriol, 2003) and could be a factor affecting consumer preference (Carbonell, 1990).  Flesh yield for the calabaza, shown in Table 2, ranges greatly from previously seen values on either extreme (Maynard, 2002). The UFTP 45 germplasm line was much larger on average than any of the other lines (3.44 kg) while the ‘Waltham Butternut’ squash was much smaller on average (0.72 kg). It should be noted that convenience is also one of the major contributing factors in purchasing power due to many variables including but not limited to saving time, reduced cost, less skill required for complex dishes, and less labor (Costa, 2003). Therefore, smaller calabaza might be better for a fresh market within the U.S. compared to larger fruit.

    The flesh color was determined using the Hunter lab L*a*b* color scale. Statistically significant differences were observed among the squash genotypes in flesh color attributes, including lightness (L*), red/green (a*), and blue/yellow (b*) and are presented in Table 3-3. Interestingly, the values observed for the Waltham Butternut cultivar are different from values of those previously reported in literature. For example, Mashitoa, (2021) reported average L*, a*, b* values of 33.22, -7.45, and 10.61 in butternut, respectively (Mashitoa, 2021). However, the findings in the current study are within the range of those found in literature for other C. moschata cultivars (Men, 2020; Provesi, 2011; Itle, 2009). Silva (2019) found that cultivars with high a* and high b* (for an intense orange color) were preferred by panelists. Using this preference trend, UFTP 8, UFTP 22, and UFTP 24 would have the highest consumer color liking. The chroma and hue angle were determined using Equations 3-2 and 3-3, respectively (Table 3-4). These additional color indicators are also within ranges seen for various calabaza germplasm lines (Wessel-Beaver, 2006; Maynard, 1994).   Chroma value (color purity) was statistically the highest for UFTP 8 with UFTP 24 being the only other germplasm line that was not statistically significantly different. This color intensity would further support these germplasm lines’ higher consumer acceptability, as multiple studies have shown that appearance is a very important quality that consumers consider when buying a food (Silva, 2019; Trejo Araya, 2009). 

    Color parameters (a*b* and Chroma) were shown to be positively correlated with Brix and hardness, while lightness saturation parameters (L* and hue angle) were positively correlated with peroxidase as shown in Table 3-6. Helyes (2006) found that the relationship for color parameters (a*b* and Chroma) could be explained through the ripeness of the fruit, as color and Brix concentration naturally change throughout the fruit development process. The ripening process could also explain the positive correlation of Chroma, a*, and b* with hardness and many other texture parameters in squash fruits reflect an increase in hardness characteristics during the ripening process (Valenta, 2022). The L* value correlates with the lightness or darkness of a sample, with a positive L* value being lighter and a negative L* value being darker. Lightness (L*) and hue angle was shown to be positively correlated with POD. This is to be expected as POD is responsible for enzymatic browning on fruit. Therefore, when the concentration of the enzyme increases, color change will be evident – mainly changing to brown (Ndiaye, 2009). It should be noted that POD was negatively correlated with a*, (+, red;-, green), which is most likely due to the ripeness of the fruit being more of a red color than a green color. With POD making the overall color of the sample more brown, this would decrease the red hue resulting in an inverse relationship between these two attributes.  

    Peroxidase Enzyme (POD)

    Among the calabaza genotypes, there was a narrow range (1.5 - 1.8 abs/min) of observed POD activity, as seen in Table 3-4. The enzyme activity observed for these calabaza genotypes were relatively high when compared to values found in literature (0.9 - 1.1 abs/min) (Zhou, 2017; Jamali, 2018). This could be due to plant stress (Jaiswal, 2012), level of fruit maturity (Sharma, 2013), and days in storage (Suo, 2022). Peroxidase enzyme, unlike polyphenol oxidase, is primarily known for its browning effect on color (Tomás-Barberán, 2001; Toivonen, 2008). This relationship is supported with the finding shown in Table 3-6, where the primary correlations present were for color-based parameters. It should be noted that POD was also negatively correlated with “springiness”, a*, and SCC/TA. Springiness is defined as the ability of a food sample to recover its original height after being compressed between the first and second compression (Hanusz, 2018). Previous research on Cucurbita maxima shows that springiness is related to the moisture and fibrousness of the squash sample, which is also strongly correlated with ripeness (Corrigan, 2006). As previously described, a* is the color range from red (+) to green (-). With a* values being an indicator for fruit ripeness with the C. moschata species, a negative correlation with POD, would support the fact the the higher the concentration present, the lower the a* value and therefore undesirable fruit ripeness. 

    Brix

    The Brix values across the calabaza genotypes ranged between 6.2 and 12.2, with a mean of 9.9 (Table 3-4).  The observed values are within the range present in existing literature (6.3 – 15), affirming that the Brix measured is within an acceptable range (Iacuzzo, 2009; Abbas, 2020a; Jacobo-Valenzuela, 2011).  Notably, UFTP 22 had the highest Brix value (12.2), which may indicate this germplasm line has a higher perceived sweetness for consumers as °Brix is considered a reasonable measure of sugar content and the overall evaluation of fruit quality (Harrill, 1998). It should be noted that variation in Brix is primarily genetic (Akter, 2013); however, several other factors can influence this trait including growing conditions (Alam, 2001), and optically active compounds such as pectins, amino acids, fiber, and organic acids (Byrne, 1991; Li, 2021).

    Correlations between Brix and many other tested parameters are shown in Table 3-6 with positive correlations including TA, malic acid, a*, b*, chroma, hardness, cohesiveness, gumminess, chewiness, and resilience. Brix concentration in relation to organic acid concentration has been used as an indicator for fruit and vegetable ripeness for quite some time (Kuti, 1992). This would therefore support the strong correlation (0.78) between Brix and TA as well as Brix and malic acid.  

    Titratable Acidity and pH

    Previous studies have shown that the Butternut squash contains malic, citric, fumaric, ascorbic, and gallic acid (Nawirska-Olszańska, 2014; Pevicharova, 2017; Men, 2021), however, the most prevalent acid among these was malic acid (Papanov, 2021; Zhou, 2017). The reported malic acid concentration for C. moschata ranges from 0.16-0.28 mg/100 g (Table 3-4) (Zhou, 2017). This range is within that observed (0.05-0.17 mg/100 g) in the current study. The germplasm line UFTP 22 and the cultivars Waltham Butternut and La Estrella had the three highest TA values of 0.15, 0.17, and 0.13, respectively (Table 3-4). To account for the range and lower concentrations within this study, previous research has shown that the acid concentrations are expected to be influenced by the cultivar (Kim, 2012) and growing region (Pevicharova, 2017).  These higher TA concentrations strongly negatively impact the germplasm lines SSC/TA ratio (−0.84). However, the SSC/TA ratio is not a catch-all for consumer acceptability, as it has been shown to be cultivar-dependent (Crisosto, 2003). 

     Fruit pH is an important fruit -quality parameter due to its influences on color (Gliemmo, 2009), microbial growth (Gliemmo, 2013), and change during storage (Nawirska-Olszańska, 2014). Previous studies in C. moschata showed a pH range between 5.3-7.79. The values for pH observed in the current study (5.98 - 6.58) are within the range (5.3-7.79) of those previously reported for C. moschata (Provesi, 2011; Zhou, 2017; Papanov, 2021; Jacobo-Valenzuela, 2011).  

     Previous literature suggests that titratable acidity does not directly correlate to the pH of the sample in all cases (Marsh, 2006).  Papnov et al. (2021) previously showed that pH and TA (malic acid) had no correlation (0.04) while Zinash et al. showed a strong negative correlation (-0.86) between the two measurements (Papanov, 2021; Zinash, 2013). Based on the data presented in Table 4, TA (as malic acid equivalent) and pH were strongly negatively correlated for the fruits in this study. Acids in fruits of some species, such as tomatoes, have been shown to decrease acid concentration through respiration only (Anthon, 2011). This could mean that the germplasm lines, which are currently being compared could have varying degrees of ripeness. It should be noted that TA and pH should have a negative correlation as the increase of organic acids would lead to a decrease in pH values. Therefore, the variation in concentrations and inversely proportional relationship between pH and TA is to be expected. Additionally, pH was shown to be positively correlated with the SSC/TA ratio which follows the same logical reasoning as the negative correlation between pH and TA.

    Yeast Fermentable Extract (YFE)

    The YFE for the calabaza genotypes showed an initial extract range (6.1-12.4 ± 0.01) and a final extract range (1.1-3.2 ± 0.88) yielding a fermentable extract range of 60.5 - 78.5% (Table 3-4). The concentration of YFE for C. moschata has not been previously reported. However, this measurement is important to quantify as it reflects the amount of simple (fermentable) sugars affecting the consumer's perceived sweetness (Goldfein, 2015; Maicas, 2020).  Furthermore, YFE has been shown to be a reliable indicator for fermentability of produce (Moreno, 2022). It should be taken into account that yeast strain, fermentation temperature, enzymes, and yeast nutrients have all been shown to impact fermentation (Parcunev, 2012). Interestingly, UFTP 22 had the highest Brix values (12.2) but had one of the lowest YFE% of 60.8. Comparing this to UFTP 8 which had the highest YFE% of 78.5 with a relatively high Brix value of 11.6. This is supported by the correlation between Brix and YFE (0.23) not being significant. This distinction between Brix and YFE is important to assess as it can demonstrate the difference in market value potential between these germplasm lines for application-based purposes as described in the introduction. When comparing YFE to the Brix values within a germplasm line, one can extrapolate that the UFTP 8 contains the highest concentration of simple sugars and is therefore likely to be perceived as most sweet. The opposite is true for UFTP 42 and UFTP 22.

    Texture Profile

    The texture profile for each calabaza germplasm line was determined with average values and statistical differences for each textural attribute presented in Table 3-5. All textural measurements (hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, and resilience) showed some statistically significant differences between germplasm lines, but this range was not wide. This is most likely due to the genotypes similarity to one another but could also be due to storage time (Ratnayake, 2004), and sampling location (Marian, 2020). Firmness/hardness had statistically significant extremes with UFTP 8 having the highest firmness/hardness value (40,323 g) and UFTP 38 having the lowest firmness/hardness value (22,027 g). Gumminess was one of the most variable textural parameters with Soler having the lowest gumminess (ease of swallowing) but not being statistically significantly different than UFTP 38, and UFTP 42. As previously described, firmness/hardness is a strong indicator of fruit ripeness (Valenta, 2022); however, variation in texture parameters is to be expected based on genetics (Toivonen, 2008; Corrigan, 2006).  

    Concentration of compositional elements varied slightly, as seen in Table 3-4, but these ranges did not seem to impact or strongly correlate with textural parameters - excluding Brix and YFE - as seen in Table 3-6. YFE is a measurement of the amount of fermentable sugars present within a sample while Brix is a measurement of the total amount of soluble solids (I.e starch, sugar, and fiber) suspended in the blended sample. Therefore, it would be expected to see some similarities between Brix and YFE correlations as YFE is part of the Brix measurement.  

    Brix was positively correlated with all textural measurements except adhesiveness and springiness which have almost no correlation at (0.01 and 00.06 respectively) (Table 3-6). Adhesiveness is the amount of force required to remove the food sample from the probe it was in contact with, better known as stickiness (Chandra, 2014). Both adhesiveness and springiness are related to the amount of moisture within a food sample (Corrigan, 2006), which could decrease the concentration of sugars and other soluble solids impacting texture.  As previously discussed, hardness and many other texture parameters are impacted during the ripening process of fruits which corresponds with an increase in Brix (Valenta, 2022), supporting the strong correlations between Brix and all other textural measurements.  

    YFE was positively correlated with hardness and gumminess as seen in Table 3-6. Gumminess is determined by multiplying the hardness of a sample by its cohesiveness (Parcunev, 2012). Cohesiveness is a food sample’s ability to resist a second deformation compared to the first deformation due to compression (Chandra, 2014). With both textural parameters being positively correlated and related to hardness, it can be reasonably assumed that as the fruit ripens the sugar concentration and hardness parameters would increase. Additionally, springiness was negatively correlated with YFE. As previously described, both adhesiveness and springiness are related to the amount of moisture within a food sample (Corrigan, 2006), which could decrease the concentration of sugars and other soluble solids within a sample. As YFE is only the measurement of fermentable sugars, it would be more impacted by the dilution of sugars than Brix, resulting in this negative correlation. 

     

    Table 3-2.  Yield table for calabaza germplasm lines used in the study.

    Cultivar 

    Avg. Total Fruit Weight (kg)

    Avg Fruit Flesh (kg)

    Flesh Yield (%) 

    Butternut 

    0.72 d

    0.54 d

    75.17 c

    UFTP 8 

    1.62 c

    1.24 c

    76.55 bc

    UFTP 22 

    1.70 c

    1.36 c

    80.18 a

    UFTP 24 

    2.51 b

    1.99 b

    78. 36 abc

    UFTP 38 

    2.75 b

    2.14 b

    77.52 abc

    UFTP 42 

    2.58 b

    2.11 b

    79.88 ab

    ‘Soler’

    3.50 a

    2.77 a

    78.96 ab 

    ‘La Estrella ‘

    1.83 c

    1.38 c

    75.21 c

    n = 10-15 squash of each cultivar were measured to determine average values. Letters represent one-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per column.

    Table 3-3. Color (L*, a*, b*), chroma, hue angle, pictures of vine growth and cross section of Cucurbita moschata genotypes grown at the Plant Science Research and Education Unit in Citra, Florida (2022).

    Cultivar

    L*

    a*

    b*

    Chroma  

    Hue Angle

    Illustration (fruit and vine)

    Butternut

    69.13 bc

    22.37 b

    70.21 c

    73.93 c 

    72.41 cd

     

    UFTP 8

    67.90 cd

    25.23 a

    77.40 ab

    81.44 a 

    71.93 d

     

    UFTP 22

    69.93 ab

    22.72 b

    74.79 b

    78.21 b 

    73.15 cd

     

    UFTP 24

    68.63 bc

    20.10 c

    77.93 a

    80.52 ab 

    75.50 b

     

    UFTP 38

    66.41 d

    22.20 b

    59.92 e

    63.93 e 

    69.74 e

     

    UFTP 42

    69.70 abc

    20.66 b

    70.21 c

    73.20 c 

    73.62 c

     

    ‘Soler’

    71.18 a

    14.85 d

    67.51 d

    69.14 d 

    77.63 a

     

    ‘La Estrella’

    71.17 a

    19.00 c

    76.06 ab

    78.49 b 

    75.96 b

     

    N=5 squash were sampled per genotype, with 3 measurements taken per squash. Letters represent one-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per column.

     

    Table 3-4. Titratable acidity (TA) expressed as malic acid (g/100g), Brix/soluble solids content (g/L), SSC/TA ratio, peroxidase (POD) (abs/min), and yeast fermentable extract (YFE) for Cucurbita moschata germplasm lines grown at the Plant Science Research and Education Unit in Citra, Florida (2022). 

    Cultivar 

    Malic Acid (g/100g) 

    pH 

    Brix 

    (g/100 g) 

    SSC/TA 

    Ratio 

    POD (abs/min) 

    YFE 

    %

    Butternut 

    0.17 a 

    5.98 f 

    11.9 b 

    66.43 e

    1.71 a 

    66.19 bc 

    UFTP 8 

    0.09 d 

    6.58 a 

    11.6 c 

    127.83 bc

    1.59 a 

    78.47 a 

    UFTP 22 

    0.15 b 

    6.12 e 

    12.2 a 

    76.66 de

    1.49 ab 

    60.80 d 

    UFTP 24 

    0.08 e 

    6.16 d 

    10.7 e 

    134.29 ab

    1.70 a 

    67.19 b 

    UFTP 38 

    0.05 g 

    6.34 c 

    7.3 g 

    141.46 a

    1.26 b 

    62.19 d 

    UFTP 42 

    0.06 f 

    6.40 b 

    8.2 f 

    122.91 c

    1.55 a 

    60.53 d 

    ‘Soler’ 

    0.07 f 

    6.36 c 

    6.2 h 

    87.34 d

    1.76 a 

    67.81 b 

    ‘La Estrella’

    0.13 c 

    6.17 d 

    11.2 d 

     81.78 d

    1.76 a 

    64.72 c 

    Letters represent one-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per column.

     

    Table 3-5. Hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, and resilience for each calabaza germplasms using a double compression texture test (TA.XT). Plant Science Research and Education Unit in Citra, Florida.2022.

    Cultivar 

    Hard.

    Adhes.

    Spring.

    Cohes.

    Gum.

    Chew.

    Resilience

    Butternut 

    33009 bc 

    -47.74 bc 

    0.52 cd 

    0.21 d 

    9237 bcd 

    4885 bc 

    0.11 bc 

    UFTP 8 

    40323 a 

    -47.99 a 

    0.51 d 

    0.38 a 

    15792 a 

    8154 a 

    0.20 a 

    UFTP 22 

    32841 bc 

    -16.58 a 

    0.65 a 

    0.32 abc 

    10730 bc 

    7104 ab 

    0.16 ab 

    UFTP 24 

    35974 ab 

    -37.71 abc 

    0.50 d 

    0.35 ab 

    12725 ab 

    6420 ab 

    0.18 a 

    UFTP 38 

    22027 d 

    -47.99 bc 

    0.55 bc 

    0.24 cd 

    5628 de 

    3207 cd 

    0.11 bc 

    UFTP 42 

    26515 cd 

    -25.38 ab 

    0.58 b 

    0.25 bcd 

    7234 cde 

    4360 bcd 

    0.12 bc 

    ‘Soler’

    22541 d 

    -41.81 abc 

    0.52 cd 

    0.16 d 

    3665 e 

    1859 d 

    0.07 c 

    ‘La Estrella’ 

    36432 ab 

    -61.81 c 

    0.49 d 

    0.32 abc 

    11595 abc 

    5793 abc 

    0.16 ab 

    Letters represent one-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per column.

    Table 3-6. Pearson correlation coefficient for fresh calabaza quality parameters

    Parameter

    Brix

    pH

    TA%

    Malic

    Acid

    SSC/TA

    YFE

    L*

    a*

    b*

    Chroma

    Brix

    1.00

    -0.43

    0.78

    0.77

    -0.35

    0.23

    0.02

    0.62

    0.73

    0.80

    pH

    -0.43

    1.00

    -0.73

    -0.73

    0.63

    0.49

    -0.27

    0.11

    -0.10

    -0.08

    TA%

    0.78

    -0.73

    1.00

    1.00

    -0.83

    -0.09

    0.36

    0.25

    0.39

    0.41

    Malic Acid

    0.77

    -0.73

    1.00

    1.00

    -0.84

    -0.09

    0.36

    0.24

    0.38

    0.41

    SSC/TA

    -0.35

    0.63

    -0.83

    -0.84

    1.00

    0.18

    -0.71

    0.25

    -0.16

    -0.12

    YFE

    0.23

    0.49

    -0.09

    -0.09

    0.18

    1.00

    -0.18

    0.25

    0.41

    0.44

    L*

    0.02

    -0.27

    0.36

    0.36

    -0.71

    -0.18

    1.00

    -0.67

    0.34

    0.24

    a*

    0.62

    0.11

    0.25

    0.24

    0.25

    0.25

    -0.67

    1.00

    0.19

    0.33

    b*

    0.73

    -0.10

    0.39

    0.38

    -0.16

    0.41

    0.34

    0.19

    1.00

    0.99

    Chroma

    0.80

    -0.08

    0.41

    0.41

    -0.12

    0.44

    0.24

    0.33

    0.99

    1.00

    Hueangle

    -0.17

    -0.13

    0.00

    0.01

    -0.36

    0.02

    0.84

    -0.83

    0.39

    0.25

    Hard

    0.88

    -0.11

    0.49

    0.49

    -0.11

    0.55

    0.04

    0.50

    0.89

    0.93

    Adhes.

    0.01

    -0.04

    0.00

    0.00

    0.01

    -0.42

    0.06

    0.11

    0.06

    0.07

    Spring.

    0.06

    -0.09

    0.17

    0.17

    -0.14

    -0.57

    0.00

    0.26

    -0.15

    -0.12

    Cohes.

    0.68

    0.16

    0.11

    0.10

    0.33

    0.39

    -0.25

    0.61

    0.74

    0.80

    Gum.

    0.83

    0.04

    0.33

    0.32

    0.37

    0.56

    -0.15

    0.62

    0.84

    0.90

    Chewi.

    0.87

    -0.01

    0.41

    0.40

    0.52

    0.40

    -0.15

    0.70

    0.81

    0.88

    Resilien.

    0.75

    0.11

    0.19

    0.18

    0.24

    0.44

    -0.19

    0.60

    0.81

    0.87

    POD

    0.21

    -0.28

    0.34

    0.34

    -0.51

    0.32

    0.73

    -0.51

    0.57

    0.48

    1 Many physiochemical attributes were abbreviated including Hue (Hue angle), Hard (harndness), Adhes. (Adhesiveness), Spring. (Springiness), Cohes. (Cohesiveness), Gum. (Gumminess), Chewi. (Chewiness), and Resilien. (Resilience).

    2 Color values (L*, a*, and b*) are denoted with an asterisk.

     

    Table 3-6.  Continued

    Parameter

    Hue

    Hard.

    Adhes.

    Spring.

    Cohesiv.

    Gum.

    Chew.

    Resilien.

    POD

    Brix

    -0.17

    0.88

    0.01

    0.06

    0.68

    0.83

    0.87

    0.75

    0.21

    pH

    -0.13

    -0.11

    -0.04

    -0.09

    0.16

    0.04

    -0.01

    0.11

    -0.28

    TA%

    0.00

    0.49

    0.00

    0.17

    0.11

    0.33

    0.41

    0.19

    0.34

    Malic Acid

    0.01

    0.49

    0.00

    0.17

    0.10

    0.32

    0.40

    0.18

    0.34

    SSC/TA

    -0.36

    -0.11

    0.01

    -0.14

    0.33

    0.10

    0.04

    0.24

    -0.51

    YFE

    0.02

    0.55

    -0.42

    -0.57

    0.39

    0.56

    0.40

    0.44

    0.32

    L*

    0.84

    0.04

    0.06

    0.00

    -0.25

    -0.15

    -0.15

    -0.19

    0.73

    a*

    -0.83

    0.50

    0.11

    0.26

    0.61

    0.62

    0.70

    0.60

    -0.51

    b*

    0.39

    0.89

    0.06

    -0.15

    0.74

    0.84

    0.81

    0.81

    0.57

    Chroma

    0.25

    0.93

    0.07

    -0.12

    0.80

    0.90

    0.88

    0.87

    0.48

    Hue

    1.00

    0.03

    -0.04

    -0.31

    -0.18

    -0.12

    -0.20

    -0.13

    0.81

    Hard

    0.03

    1.00

    -0.19

    -0.27

    0.83

    0.97

    0.91

    0.89

    0.39

    Adhes.

    -0.04

    -0.19

    1.00

    0.85

    0.01

    -0.12

    0.11

    -0.01

    -0.29

    Spring.

    -0.31

    -0.27

    0.85

    1.00

    -0.03

    -0.19

    0.09

    -0.07

    -0.55

    Cohes.

    -0.18

    0.83

    0.01

    -0.03

    1.00

    0.93

    0.93

    0.99

    -0.06

    Gum.

    -0.12

    0.97

    -0.12

    -0.19

    0.93

    1.00

    0.96

    0.96

    0.19

    Chewi.

    -0.20

    0.91

    0.11

    0.09

    0.93

    0.96

    1.00

    0.96

    0.05

    Resilien.

    -0.13

    0.89

    -0.01

    -0.07

    0.99

    0.96

    0.96

    1.00

    0.04

    POD

    0.81

    0.39

    -0.29

    -0.55

    -0.06

    0.19

    0.05

    0.04

    1.00

    1 Many physiochemical attributes were abbreviated including Hue (Hue angle), Hard (harndness), Adhes. (Adhesiveness), Spring. (Springiness), Cohes. (Cohesiveness), Gum. (Gumminess), Chewi. (Chewiness), and Resilien. (Resilience).

    2 Color values (L*, a*, and b*) are denoted with an asterisk.

    Activity 2: Chemical and physical properties of winter squash and their correlation with sensory attributes

    Fresh Cooked – Quality Parameters 

    The genotypes differed significantly in physiochemical attributes, though the degree of separation varied (Table 1 and Table 2). Most notably, Brix, malic acid, and pH showed more separation between genotypes than hue angle, POD, and all texture profile measurements. The Brix measurements range found within this study (7.7 - 16.03°Bx) were higher than those previously reported by Gajewski (2008), Santos Jr. (2017), and Khanobdee (2001) for cooked C. moschata (3.0-13.6), and lower than reported by Amaro in 2017 (18.4°Bx). Variations in sugar levels are likely due to the maturity of the fruit, which is synonymous with a decline in starch and an increase in simple sugars (Irving, 1997). Other factors that commonly impact Brix levels include genetics (Akter, 2013) and growing conditions (Alam, 2001). Notably UFTP 8 had the highest Brix level (16.03°Bx) of the analyzed germplasms, while ‘Soler’ and ‘La Estrella’ had the lowest (7.73°Bx and 7.83°Bx, respectively).   

    Malic acid analysis showed UFTP 22 had the highest concentration (0.06 mg/100 g), while UFTP 38 had the lowest concentration (0.02 mg/100 g). This acidity range aligns with previous literature. However, it should be noted that winter squash acid dominance is cultivar-dependent (malic or citric acid) and variation between germplasm lines may cause this variation (Nawirska-Olszanska, 2014).   

    The average color values (L*, a*, b*) of the freshly cooked microwaved samples (50.98, 10.91, and 50.96 respectively) were higher than of microwaved samples previously reported , which averaged 38.22, 4.6, and 11.3 respectively (Silva, 2019). However, other means of cooking C. moschata show a range which encompasses the values shown in this study (Silva, 2019; Gajewski, 2008; de Almeida, 2019). Regarding L* value, UFTP 22 (56.74) was significantly higher than all other germplasm lines. This shows that the pulp from this genotype was lighter than all other lines. Many of the germplasm lines displayed an orange color with low a* values (red color) and high b* values (yellow color). UFTP 22 showed the highest average a* value (19.59) and b* value (65.77) which resulted in a more intense orange pulp color. This is further supported with UFTP 22 having the highest chroma value (68.69). The germplasm lines UFTP 38, ‘Soler’, and UFTP 42 were pale yellow/orange with the lowest chroma values. Hue angle defines the hue of the color of a sample without considering the lightness. This categorization of color ranged from 73.48 - 85.14, which encompasses a range from dark orange to yellow (Pathare, 2012).   

    A double compression texture profile was determined and slight statistical variations between germplasms were observed. These statistical differences are to be expected as all samples were cooked until an internal temperature of 80°C was maintained for 3 minutes as this was considered cooked, therefore, limited variation in texture between samples is to be expected. To account for the statistical differences reported, fruit development variation (Abbas, 2020) and genetic differences (Gomes, 2020) could explain the observed variation. Additionally, the values from this study are similar to those expressed within literature for winter squash (Theanjumpol, 2022; Rinaldi, 2020).  In summary, the measured physiochemical properties of fruit from this study fall within those reported in previous literature.

    Fresh Cooked – Consumers’ Acceptability 

    Demographic data was collected whereby 65.2% of panelists were women and 34.8% were men. This ratio aligns with findings from a prior study performed in the U.S. by Bowman (2006) which showed that 67% of meals were planned and prepared by women. This indicates that the results of this study may reflect the significance of women’s opinions on the characteristics of the genotypes, as they are frequent purchasers of food. Additionally, the majority of responses were from adults in the age range of 18 and 24 years old (43.5%), followed by those from 35 to 44 (33.9%), 25 to 34 (19.4%), and lastly over 45 (3.2%). It is noteworthy that age is a relevant factor of consumer acceptability due to dietary habits changing with developmental stages in life (Jaime et al., 2015). The panelists’ self-identified race was most often White (48.3%), followed by Asian (32.6%), then Hispanic (15.4%), and lastly African American (11.2%). Satterwaite et. al. (2010) showed that participants’ cultural habits and economic conditions influence their product consumption in their daily lives, which would therefore influence their product preference. 

    Appearance liking and color liking for the genotypes showed UFTP 38 and ‘Waltham Butternut’ as the most liked visually (Table 3). The overall liking comparison among samples, however, showed that UFTP 24 was statistically the highest performing variety. This indicates that other factors, such as taste and texture, greatly impacted the perception of a food, a finding supported by Anderson et al., (2019). When consumers rated their sweetness liking and flavor liking, UFTP 8 and UFTP 24 were statistically the most liked. In comparison, Brix values shown in Table 1 indicate UFTP 8 to be the highest, followed by UFTP 22. The discrepancy in Brix for UFTP 24 could be due to many reasons including varying concentrations of simple sugars (Godshall, 1995), and sweetness-contributing aromatic compounds (Schwieterman, 2014). Furthermore, sugar is one of the major factors affecting overall flavor perception (Godshall, 1995); understanding the composition and concentration of sugars is part of identifying consumer preferences (Beauchamp, 2011). In the case of the texture liking, there was less variation and no significant differences among the genotypes, however,  UFTP 38 and the ‘La Estrella’ were the least liked. The texture of produce is traditionally associated with sensory hardness which in turn is correlated with the presence or level of fibers (Kutle, 2021). The term ‘presence of fibers’ is frequently used, since it refers to the geometric properties of the food particles and is applied to fibrous materials (mainly materials containing hemicellulose and cellulose). These properties can be perceived during sensory analysis by chewing (Lillford, 2011) and are very important to solid vegetable foods. High fiber levels are typically undesirable in vegetable crops, since the consumer usually associates their presence with a lack of succulence in food (Laignier, 2021).  

    Fresh Cooked – Correlation 

    Data on physicochemical characteristics and sensory ratings were analyzed by Principal Component Analysis (PCA). In this analysis, attributes that presented statistically significant differences amongst other physicochemical characteristics in a correlation matrix were used. These included individual color values (L*, a*, b*), pH, malic acid, Brix, POD, hardness, adhesiveness, cohesiveness, springiness, chewiness, resilience, gumminess, overall liking, appearance liking, color liking, sweetness liking, flavor liking, texture liking, and price. The two components of the biplot PCA model explained 37.01% and 22.06%, respectively, for the total variability (59.07%) found in the original variables (Figure 3). The distance and the angle of the variables from one another using the origin as a vector indicates the positive or negative correlation those variables have. This angular interpretation is further explained with an acute angle indicating a positive correlation, an obtuse angle being a negative correlation and a 90° degree angle showing no correlation (Bro, 2014). Furthermore, the farther a variable is from the origin the more that component is impacting the model (Abdi, 2010).  

    Attributes that had a correlation with the primary components above 0.7 were considered important (Figure 3). The first principal component showed that many sensory profile attributes (overall liking, price, sweetness liking, and flavor liking), were strongly positively correlated, while appearance and color liking showed a strong negative correlation. For the second principal component, texture parameters including hardness, gumminess, and chewiness were positively correlated and negatively correlated to texture liking. PCA analysis confirmed genotype variation in physicochemical and sensory attributes (Figure 4). ‘Waltham Butternut’, ‘La Estrella’, UFTP 8, UFTP 22, and UFTP 24 placed on the right, whereas, on the left, were ‘Soler’, UFTP 38, and UFTP 42. Germplasm lines on the right that were negatively correlated with the second principal component had high overall liking, price, sweetness liking, and flavor liking for consumer acceptability; and high intensity for Brix. For the second principal component, germplasms ‘La Estrella’, UFTP 38, and UFTP 8 were above the axis indicating that these lines expressed more hardness, gumminess, and chewiness compared to other lines. 

    With respect to fresh microwaved pumpkin germplasms, Brix was strongly positively correlated with willingness to pay (0.79). This put UFTP 24 as the most liked genotype, overall. 

    Frozen Cooked– Quality Parameters 

    There was significant variation in the physiochemical composition among the genotypes when frozen fruit cuts were assayed (Table 4 and Table 5). Parameters which showed a great deal of statistical variation among the genotypes include Brix, malic acid concentration, and pH, whereas POD, hue angle, and texture composition showed the least variation. The UFTP 24 genotype had the lowest Brix values of 5.56 compared to UFTP 8 which had the highest at 12.53. The process of freezing involves the formation of ice crystals which damage the tissue and cells, thus resulting in softer foods (Van Buggenhout, 2006; Paciulli, 2015). This cell rupturing can cause leaching of nutrients including sugar and acids (Caliskan, 2017). However, Brix is considered a reasonable measure of sugar content and the overall evaluation of fruit quality (Harrill, 1998).

    Color values of frozen germplasm lines had L* values ranging from 53.5 – 60.5 indicating a light color for the samples. Additionally, some of the germplasm lines displayed a vibrant orange color with positive a* values (8.04 - 20.43) and b* values (49.93 - 65.72). The highest color values (L*, a*, b*) and chroma (68.88) were seen for UFTP 8 (60.50, 20.43, and 65.72) indicating a bright and highly saturated orange colored pumpkin. However, other genotypes including UFTP 22 and UFTP 24 were not statistically significantly different that UFTP 8 with regards to L* and b* values. Furthermore, the relationship between the chromatic parameters (a*, and b*) should be taken into account to interpret color. This is demonstrated with Soler and La Estrella which had the lowest a* values (8.04, and 8.48) and varying b* values (51.77, and 59.10). These a* and b* values for Soler and La Estrella resulted in the highest hue angle values of 81.5 and 82, respectively, indicating a yellow color. This is due to the difference between the a* and b* values and not just the b* value alone. The increase in chromatic values has previously been reported in salmon (Kono, 2017), cherries (Bilbao-Sainz, 2019), and papaya (Cano,1995) after freezing. Thus, freezing rate was shown to affect surface color.  

    Overall, the texture profile of the genotypes showed slight statistically significant separation amongst germplasm lines except for gumminess, and resilience (Table 5). These germplasm line differences are most likely due to several factors including starch gelatinization, pectin degradation, cell wall breakdown, and cell separation (Gallego-Castillo, 2018; van Dijk,2002). These phenomena translate into a release of water, which decreases tissue stiffness, hardness, and firmness and but increases adhesiveness, springiness, gumminess, and chewiness (Corrigan, 2006; Chandra, 2014). Freezing causes cell wall rupture, whereas just the cooking of fresh squash causes softening via cellular separation, without breakage, and leaving the structure of the cellular wall almost intact (Alvarez, 2005).  

    Frozen Cooked – Consumers Acceptability 

    Freezing fruits is a value-added process that aids in elongating shelf life and increasing value to fruits that otherwise would not have been used or wasted. Genotypes UFTP 8, UFTP24, and ‘Waltham Butternut’ had the highest overall liking scores (Table 6). Consumer acceptability for these genotypes was further supported by high flavor liking and sweetness liking ratings. As previously noted, consumers typically associate the term “overall liking” with “liking of taste” when compared to other sensory terms such as liking of appearance, odor, and texture (Andersen, 2019; Hellwig, 2022). Additionally, American consumers usually prefer sweeter foods on average (Barthes, 2012), demonstrating the correlation between sweetness and overall liking. 

    The appearance liking preference separated one half of the genotypes from the other with UFTP 8, UFTP 22, UFTP 42 and ‘Waltham Butternut’ being amongst the most preferred. When comparing this to the color liking, only UFTP 8, UFTP 22, and UFTP 42 were most preferred. This could be due to more prevalent shrinking, leading to higher rates of discoloration, or non-uniformity on the outside of the ‘Waltham Butternut’ samples. A clear, statistically significant difference in texture was observed among the genotypes. The four most liked samples- UFTP 8, UFTP 22, UFTP 24 and ‘Waltham Butternut’-were contrasted with UFTP 38 and ‘Soler’ as the least liked. This genotype preference was seen in the willingness to pay per pound of each sample, with the most liked samples being ‘Waltham Butternut’ at $1.40 and UFTP 8 at $1.44 per pound. As previously discussed, overall liking has been shown to be highly correlated with flavor liking and sweetness liking. These attributes were both lower for UFTP 24 (5.98- flavor liking) (6.00- sweetness liking) therefore decreasing the consumer acceptability of this genotype. Additionally, price ranged more with frozen samples (0.81-1.44) ) compared to fresh samples (1.21-1.53) indicating that the effects of freezing negatively affected some genotypes more than others. 

    Frozen Cooked – Correlation 

    Principal Component Analysis (PCA) was used to analyze physicochemical characteristics and sensory profile of frozen winter squash. Two components of the biplot PCA model explained 42.62% and 25.49% respectively, for the total variability (68.11%) found in the original variables (Figure 5). As previously stated, attributes with correlation to each axis >0.7 were considered important: sensory profile attributes (overall liking, price, sweetness liking, texture liking, and flavor liking) were strongly positively correlated to first principal component (C1), as were physicochemical characteristics (L*, a*, b*, and hardness). Visually, cohesiveness and adhesiveness were strongly negatively correlated (>-0.7) to C1 and with values at -0.68 and -0.65, respectively. This is an indication that texture in an important factor which influences the consumer perception of frozen samples. The second principal component (C2) supports the importance of texture, with texture profile characteristics (gumminess and resilience) and compositional characteristics (POD and pH) on either extreme.  

    The visualization of the PCA illustrates the components of consumer overall liking and willingness to pay (price). Flavor liking and overall liking have similar trends in correlations, with the latter being a better indicator for consumer acceptability (Andersen, 2019; Hellwig, 2022). Factors found to be strongly positively correlated with overall liking include L* and a* color values. This strong correlation (>0.7) for compositional characteristics in the frozen state is slightly different for price with L*, a*, and b* color values all being strongly positively correlated. It should also be noted that Brix no longer has a strong correlation with price, but sweetness liking is highly correlated (0.98). This could be due to other factors such as flavor overwhelming the consumers perception of the sample. As previously discussed, texture attributes were shown to impact consumer perception but were not strongly negatively correlated (>-0.7). However, for frozen samples, texture liking is strongly correlated with both overall liking (0.86) and price (0.91).  

    The C1 sample variation (Figure 6) revealed a separation between the most liked and least liked genotypes. The right side showed the most preferred germplasm lines: ‘Waltham Butternut’, UFTP 8, UFTP 22, and UFTP 24, while the left side included the lesser-liked germplasm lines: ‘Soler’, ‘La Estrella’, UFTP 38, and UFTP 42. ‘Waltham Butternut’ is strongly correlated with appearance and color liking compared to UFTP 8 which is strongly correlated with hardness, L*, and a* color values. Having the most preferred cultivars associated with factors strongly positively correlated with overall liking and price further support the use of these genotypes for the frozen American market. Conversely, UFTP 38 and ‘Soler’ were strongly correlated with cohesiveness and adhesiveness and were negatively correlated with overall liking and price. 

     


    Table 1. Freshly cooked compositional values including color values (L*a*b*), hue angle, chroma, titratable acidity (TA) (g/L), malic acid (g/100g), Brix/soluble solids content (g/L), peroxidase (POD) (abs/min), for Calabaza germplasms. Plant Science Research and Education Unit in Citra, Florida.2022. 

    Cultivar 

    L* 

    a* 

    b* 

    Hue Angle 

    Chroma 

     

    pH

    TA (g/L)

    Malic Acid (mg/100g) 

    SSC 

    (Brix) 

    POD (abs/min) 

    Butternut 

    53.37 b

    10.98 c

    54.01 c

    78.61 b

    55.25 c 

    6.86 f 

    0.08 c

     0.05 c

    14.80 c

    2.39 a

    UFTP 8 

    53.71 b

    15.96 b

    57.96 b

    74.68 c

    60.17 b 

    7.35 b 

    0.03 f

     0.02 f

    16.93 a

    0.56 b

    UFTP 22 

    56.74 a

    19.59 a

    65.77 a

    73.48 c

    68.69 a 

     6.70 g

    0.11 a

     0.06 a

    15.73 b 

    0.88 a

    UFTP 24 

    46.87 e

    8.66 cd

    47.16 d

    79.63 b

     47.98 d

     7.10 d

    0.05 e

     0.03 e

     14.37 d

    1.11 a

    UFTP 38 

    47.69 ed

    11.47 c

    41.63 e

    75.16 c

     43.54 e

     7.58 a

    0.02 h

     0.01 h

     10.57 e

    0.56 a

    UFTP 42 

    48.75 d

    7.32 d

    47.24 d

    81.25 b

     47.83 d

     7.28 c

    0.03 g

     0.02 g

     10.70 e

    0.71 b

    Soler

    49.47 ed

    4.07 e

    46.76 d

    85.14 a

     46.97 d

     6.85 f

    0.06 d

     0.03 d

     7.73 f

    0.91 b

    La Estrella  

    51.20 c

    9.25 cd

    47.14 d

    79.20 b

     48.29 d

     7.01 e

    0.09b

     0.06 b

     7.83 f

    1.97 a

    1 Letters represent one-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per row. n=10-15 fruits.

    Table 2. Freshly cooked texture profile (hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, and resilience) for each Calabaza germplasms using a double compression texture test (TA.XT). Plant Science Research and Education Unit in Citra, Florida.2022.

    Cultivar 

    Hardness (g) 

    Adhesiveness (g/sec) 

    Springiness

    Cohesiveness 

    Gumminess

    Chewiness

    Resilience 

    Butternut 

    313.73 bc

    -53.96 c

    0.20 a

    0.1454 a

    43.93 b

    8.80 ab

    0.0241 bc

    UFTP 8 

    393.46 abc

    -11.39 a

    0.22 a

    0.1424 ab

    58.49 ab

    14.63 ab

    0.0372 a

    UFTP 22 

    361.15 abc

    -18.56 ab

    0.18 a

    0.1151 c

    42.62 b

    8.14 ab

    0.0260 b

    UFTP 24 

    315.15 bc

    -25.50 b

    0.21 a

    0.1203 c

    36.84 b

    7.66 b

    0.0243 bc

    UFTP 38 

    418.94 ab

    -40.43 c

    0.18 a

    0.1170 c

    46.88 b

    8.43 ab

    0.0246 bc

    UFTP 42 

    274.08 c

    -48.43 c

    0.20 a

    0.1311 abc

    34.68 b

    6.91 b

    0.0210 bc

    Soler

    309.49 bc

    -40.15 c

    0.21 a

    0.1225 abc

    36.68 b

    8.03 ab

    0.0196 c

    La Estrella  

    480.82 a

    -19.62 ab

    0.20 a

    0.1423 ab

    73.38 a

    17.08 a

    0.0331 a

    1 Letters represent one-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per row. n=10-15 fruits. Texture characteristics n=12 and values are means ± 1 standard deviation.

     

    Table 3. Freshly cooked sensory rating using the 9-point hedonic ratings for overall liking, appearance liking, color liking, sweetness liking, flavor liking, and texture liking. A line scale for price was used ranging from $0.80 - 3.00 per pound.

    Cultivar

    Overall Liking

    Appearance Liking

    Color Liking

    Sweetness Liking

    Flavor Liking

    Texture Liking

    Price

    (Per pound)

    Butternut

    6.02 bc

    6.98 a

    7.10 ab

    6.10 bc

    6.10 b

    6.28 ab

    1.43 ab

    UFTP 8

    6.37 b

    6.04 c

    6.27 c

    6.38 ab

    6.54 ab

    6.08 abc

    1.46 b

    UFTP 22

    6.15 b

    5.82 cd

    6.10 c

    5.93 c

    6.25 b

    6.07 abc

    1.41 ab

    UFTP 24

    6.88 a

    6.02 c

    6.12 c

    6.63 a

    6.85 a

    6.44 a

    1.53 a

    UFTP 38

    5.37 d

    7.36 a

    7.17 a

    5.26 d

    5.43 c

    5.60 c

    1.18 d

    UFTP 42

    6.15 b

    6.45 b

    6.71 b

    5.78 c

    6.25 b

    5.96 abc

    1.34 c

    Soler

    5.61 cd

    6.54 b

    6.73 b

    5.01 d

    5.52 c

    6.02 abc

    1.21 cd

    La Estrella  

    5.97 bc

    5.52 d

    5.62 d

    5.88 c

    6.10 b

    5.87 bc

    1.31 bcd

    1 Letters represent two-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per row. n=10-15 fruits. Sensory panel N= 89 panelists and values are means ± 1 standard deviation.

     

    Figure 3. Principal component analysis for fresh microwaved sensory attributes and quality parameters

  • Figure 3. Principal component analysis for fresh microwaved sensory attributes and quality parameters

    Figure 4. Principal component analysis for fresh microwaved samples

    Figure 4. Principal component analysis for fresh microwaved samples

    Table 4. Frozen cooked compositional values including color values (L*a*b*), hue angle, chroma, titratable acidity (TA) (g/L), malic acid (g/100g), Brix/soluble solids content (g/L), peroxidase (POD) (abs/min), for Calabaza germplasms. Plant Science Research and Education Unit in Citra, Florida.2022. 

    Cultivar 

    L* 

    a* 

    b* 

    Hue Angle 

    Chroma 

     

    pH

    TA (g/L)

    Malic Acid (mg/100g) 

    SSC 

    (Brix) 

    POD (abs/min) 

    Butternut 

    55.82 cd

    14.75 b

    56.11 d

    75.26 c

     58.04 c

     5.66 f

    0.10 d

     0.06 d

    5.80 f 

    2.08 a

    UFTP 8 

    60.50 a

    20.43 a

    65.72 a

    72.77 d

     68.88 a

     6.14 ab

    0.12 b

     0.07 b

     12.53 a

    1.07 c

    UFTP 22 

    57.83 abc

    16.23 b

    61.45 abc

    75.28 c

     63.59 b

     6.03 c

    0.06 h

     0.04 h

     5.86 ef

    1.24 b

    UFTP 24 

    59.43 ab

    11.13 c

    63.24 ab

    80.16 b

     64.26 b

     6.10 b

    0.07 g

     0.04 g

     5.56 g

    1.25 b

    UFTP 38 

    55.12 cd

    13.71 b

    49.93 e

    74.80 c

     51.83 d

     5.92 d

    0.09 f

     0.05 f

     7.56 c

    1.35 b

    UFTP 42 

    57.11 bc

    15.62 b

    58.68 cd

    75.20 c

     60.74 bc

     5.95 d

    0.09 e

     0.06 e

     6.83 d

    1.36 b

    Soler

    53.49 d

    8.04 d

    51.77 e

    81.49 ab

     52.46 d

     5.88 e

    0.11 c

     0.07 c

     8.83 b

    1.21 bc

    La Estrella  

    55.40 cd

    8.48 d

    59.10 cd

    82.00 a

     59.77 bc

     6.15 a

    0.16 a

     0.10 a

     5.96 e

    1.34 b

     1 Letters represent one-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per row. n=10-15 fruits. Texture characteristics n=12 and values are means ± 1 standard deviation.

     

    Table 5. Frozen cooked texture profile (hardness, adhesiveness, springiness, cohesiveness, gumminess, chewiness, and resilience) for each Calabaza germplasms using a double compression texture test (TA.XT). Plant Science Research and Education Unit in Citra, Florida.2022.

    Cultivar 

    Hardness (g) 

    Adhesiveness (g/sec) 

    Springiness

    Cohesiveness 

    Gumminess

    Chewiness

    Resilience 

    Butternut 

    592.60 cd

    -66.83 c

    0.35 a

    0.1870 bc

    107.11 e

    38.01 c

    0.0308 e

    UFTP 8 

    2365.60 a

    -60.62 bc

    0.28 bc

    0.1569 c

    345.39 a

    92.93 a

    0.0429 dc

    UFTP 22 

    1127.00 bc

    -51.68 ab

    0.28 bc

    0.2049 b

    223.87 bc

    61.35 b

    0.0409 d

    UFTP 24 

    1425.90 b

    -63.96 bc

    0.27 bc

    0.2140 b

    297.53 ab

    78.91 ab

    0.0533 a

    UFTP 38 

    595.50 cd

    -52.67 ab

    0.30 b

    0.3256 a

    190.08 cd

    58.62 b

    0.0493 abc

    UFTP 42 

    638.20 cd

    -46.58 a

    0.27 bc

    0.2204 b

    128.88 de

    34.09 c

    0.0425 d

    Soler

    427.30 d

    -43.64 a

    0.25 c

    0.2977 a

    124.62 de

    31.04 c

    0.0437 bcd

    La Estrella  

    1592.90 b

    -64.84 bc

    0.30 b

    0.1923 bc

    280.80 ab

    83.07 a

    0.0499 ab

    1 Letters represent one-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per row. n=10-15 fruits. Texture characteristics n=12 and values are means ± 1 standard deviation.

     

    Table 6. Frozen cooked sensory rating using the 9-point hedonic ratings for overall liking, appearance liking, color liking, sweetness liking, flavor liking, and texture liking. A line scale for price was used ranging from $0.80 - 3.00 per pound.

    Cultivar

    Overall Liking

    Appearance Liking

    Color Liking

    Sweetness Liking

    Flavor Liking

    Texture Liking

    Price

    (Per pound)

    Butternut

    6.34 a

    6.72 abc

    6.77 bc

    6.62 a

    6.40 a

    6.00 a

    1.40 a

    UFTP 8

    6.40 a

    7.11 a

    7.14 ab

    6.56 a

    6.40 a

    6.32 a

    1.44 a

    UFTP 22

    5.62 bc

    7.11 a

    7.26 a

    6.00 b

    5.17 bc

    6.11 a

    1.17 b

    UFTP 24

    5.97 ab

    6.41 cd

    6.46 cd

    6.00 b

    5.98 ab

    5.84 a

    1.22 b

    UFTP 38

    5.09 d

    6.26 d

    6.24 d

    5.44 c

    5.26 d

    4.31 c

    0.90 e

    UFTP 42

    5.30 cd

    6.84 ab

    7.06 ab

    5.67 bc

    5.23 cd

    5.18 b

    1.07 c

    Soler

    4.41 e

    6.60 cd

    6.53 cd

    4.92 d

    4.43 e

    4.60 c

    0.81 e

    La Estrella  

    5.02 d

    4.84 e

    4.76 e

    5.50 c

    5.08 d

    5.17 b

    0.98 cd

    1 Letters represent two-way ANOVA with Duncan MRT results and mean separation to determine significant differences at α>0.05 per row. n=10-15 fruits. Sensory panel N= 90 panelists and values are means ± 1 standard deviation.

     

  •  

    Figure 5. Principal component analysis for fresh microwaved sensory attributes and quality parameters
    Figure 5. Principal component analysis for fresh microwaved sensory attributes and quality parameters

  • Figure 6. Principal component analysis for frozen microwaved samples
  • Figure 6. Principal component analysis for frozen microwaved samples

    Activity 3: Determination of macronutrients and bioactive compounds of calabaza germplasm

    Moisture Content and Total Soluble Solids Content

    The average moisture content of the calabaza varieties and butternut squash ranged from 76.30 to 94.4% on a wet weight basis, as shown in Table 3-2. UFTP45 was found to have the highest moisture content, while UFTP46 had the lowest observed moisture content. Samples from lines UFTP 8, UFPT22, UFTP38, UFTP48, and UFTP47 had significantly higher moisture content than samples from UFTP24 and UFTP57.  The butternut squash used as a control contained 87.6% moisture, with a standard deviation of 0.8, which did not significantly differ from the reported value for moisture content of butternut squash, 86.4% (USDA FDC).

    Total soluble solids of the calabaza varieties and butternut squash, reported in °Brix, ranged from 5.2 to 13.2 (Table 3-2). UFTP46 was found to have the highest soluble solids content among the calabaza varieties, while UFTP45 had the lowest concentration of soluble solids. This finding demonstrates the inversely proportional relationship between moisture and soluble solids concentrations within the mesocarp of the calabaza fruit and is in accordance with Loy’s (2004) claim that greater fresh weight, attributed to higher moisture, may be inversely proportional to consumer acceptability as it relates to sweetness of the edible portion of calabaza fruit. If 11% total soluble solids is to be considered the minimum threshold for consumer palatability, as determined by Loy (2004), then only one of the experimental varieties of calabaza would meet this standard, UFTP46 with 13.2% soluble solids, in addition to the butternut squash control which was found to have an average of 11.6% soluble solids. Average soluble solids were significantly higher in samples from lines UFTP8 and UFTP24 than in samples from lines UFTP22, UFTP47, and UFTP57. Along with average TSS in samples from UFTP45, average TSS in samples from lines UFTP38 and UFTP42 did not differ significantly.

    Carotenoid Concentration

    The average concentrations of carotenoids among the calabaza varieties, expressed as β-carotene equivalents, ranged from 17.4 to 73.5 micrograms per one gram of raw calabaza mesocarp on a wet weight basis (Table 3-3), 21.0 to 278 micrograms per gram on a dry weight basis. UFTP57 had the highest concentration of β-carotene equivalent carotenoids and, therefore, also retinol activity equivalents (RAE), but concentrations did not vary significantly from lines UFTP47, UFTP42, UFTP24, or UFTP8. UFTP45 had the lowest concentrations of β-carotene equivalent carotenoids but only varied significantly from two other lines, UFTP8 and UFTP57.

    The measured concentrations of β-carotene equivalent carotenoids for each calabaza variety, as well as the butternut squash control, fell within the range of β-carotene concentrations published by the USDA’s FoodData Central for raw winter squash (butternut), specifically 13.6 to 83.8 μg β-carotene per one gram of mesocarp. Concentrations of β-carotene equivalent carotenoids determined in this study were higher than those determined by Itle and Kabelka (2009); from six different varieties of Cucurbita moschata they found β-carotene concentrations ranging from 0.2 to 15.3 micrograms per gram on a wet weight basis using high-performance liquid chromatography. This could be because Itle and Kabelka (2009) determined β-carotene concentrations in Cucurbita moschata varieties exhibiting a wide range of mesocarp colors, from light yellow to orange-red, suggesting a wide range of β-carotene concentrations as β-carotene has already been associated with “deep orange flesh colour” (Robinson and Decker-Walters 1997). Using liquid chromatography analysis of lyophilized samples from different varieties of Cucurbita moschata, Azevedo-Meleiro and Rodriguez-Amaya (2007) and Kulcyński and Gramza-Michalowska (2019) determined concentrations of β-carotene to range from 56.7 to 66.7 micrograms per gram of dry matter from two sample C. moschata varieties and 12.9 to 52.6 micrograms per gram dry matter from six sample C. moschata varieties, respectively. This discrepancy between results of these studies and those of the study presented here can be explained by the methods of analysis chosen for each. Chromatography is a very precise and accurate primary method of chemical analysis that extracts and separates individual target compounds, such as β-carotene. Spectrophotometry is less precise as it measures absorbance and transmittance values at a given wavelength for all compounds extracted but not separated (e.g., total carotenoids). Therefore, the concentrations reported in this study are likely an overestimation of β-carotene in the calabaza samples. Though chromatographic methods of analysis are more precise and accurate than spectrophotometry, the latter is more cost-effective, less labor intensive, and more rapid, maintaining its status as a valuable secondary method of analysis.

    The dietary reference intakes (DRI) for RAE, based on the estimated average requirements (EAR) for humans based on their gender and age, are 210 μg RAE/day for male and female children aged 1 through 3 years, 275 μg RAE/day for male and female children aged 4 through 8 years, 445 μg RAE/day for males and 420 μg RAE/day for females aged 9 through 13 years, 630 μg RAE/day for males and 485 μg RAE/day for females aged 14 through 18 years, 625 μg RAE/day for males and 500 μg RAE/day for females aged ≥19 years (Institute of Medicine 2006). Table 3-4 shows the percentage of the DRI for retinol activity equivalents for each group specified previously that a single serving of each experimental calabaza variety and butternut squash would provide assuming that a serving size of calabaza is equal to 100 grams and that a negligible amount of β-carotene is lost during typical cooking (Kläui and Bauernfeind 1981).

    Samples from each breeding line, as well as samples of the butternut squash, would, on average, be considered “excellent” sources of retinol activity equivalents across every life stage and regardless of gender. An “excellent” source of a nutrient is defined as that which provides ≥ 20% of the respective DRI per reference amount customarily consumed (FDA 2022). Fruits from lines UFTP8, UFTP42, and UFTP57 were among the top samples consistently providing the highest percentages of the DRI for RAE at each life stage, though the carotenoid profile is complex and β-carotene is not the only carotenoid present.

    Ascorbic Acid Concentration

    Average ascorbic acid contents among the experimental varieties of calabaza varied significantly and ranged from 51.1 to 207 micrograms per single gram of raw mesocarp (Table 3-5). The highest concentrations of ascorbic acid were found in samples from breeding lines UFTP46 and UFTP24, while the lowest concentrations of ascorbic acid were observed in samples from breeding line UFTP45 and in samples of the butternut squash used as a control. Databases and literature values support ascorbic acid concentrations of 166 to 229 micrograms per gram of raw winter squash (butternut) on a wet weight basis (Hopp and Merrow 1963; USDA FDC; Roura et al. 2007).

    The DRIs for vitamin C (“ascorbic acid”), based on the EARs for humans at different life stages and by gender, are 13 mg/day for male and female children aged 1 through 3 years, 22 mg/day for male and female children aged 4 through 8 years, 39 mg/day for male and female children aged 9 through 13 years, 63 mg/day for males and 56 mg/day for females aged 14 through 18 years, 75 mg/day for males and 60 mg/day for females aged ≥19 years (Institute of Medicine 2006). Table 3-6 shows the percentage of the DRI for vitamin C (“ascorbic acid”) for each group specified previously that a single serving of each experimental calabaza variety and butternut squash would provide assuming that a serving size of calabaza is equal to 100 grams. It is important to note that ascorbic acid is sensitive to thermal treatments, such as those used in standard home cooking procedures. Roura et al. (2007) found that approximately 20% of the ascorbic acid content of fresh butternut squash was lost during a simulated cooking regime of 30 minutes at 95 ± 2 ºC.

    Each breeding line and butternut squash produced samples that, on average, would serve as “excellent” sources of vitamin C as a function of ascorbic acid content. A “good” source is one which provides 10 – 19% of a respective DRI per reference amount customarily consumed (FDA 2022). Samples from breeding lines UFTP22, UFTP38, UFTP45, UFTP47, and butternut squash produced samples that could be considered “good” sources of vitamin C as a function of ascorbic acid for children aged 9 through 13 years. Samples from lines UFTP8, UFTP24, UFTP42, UFTP46, and UFTP57 would serve as “excellent” sources of ascorbic acid. A single serving of calabaza from each experimental variety, and excluding butternut squash, could be considered a “good” source of ascorbic acid, with a few exceptions; samples from line UFTP45 would not be considered “good” sources of vitamin C as a function of ascorbic acid  for males aged 14 years and older, while samples from UFTP22 would not be considered “good” sources for males 19 years of age and older. Samples from lines UFTP24 and UFTP46 were most consistently found to be “excellent” sources of ascorbic acid across the life stages.

    Phenolic Compound Concentration

    The average concentration of phenolic content, expressed as gallic acid equivalents (GAE), among the experimental varieties of calabaza and the butternut squash control ranged from 168.4 to 526.6 micrograms GAE per gram of raw mesocarp (Table 3-7). Line UFTP46 produced samples with the significantly highest average concentration followed by samples from line UFTP24, while line UFTP38 produced samples with the lowest average concentrations.

    The USDA’s FoodData Central does not provide information on the total phenolic compound concentration of calabaza or any other related winter squash, raw or otherwise. Researchers have reported phenolic compound concentrations of 159.3 ± 5.7 micrograms GAE per gram of mesocarp in “pumpkin” (no species designation) on a wet weight basis using the Folin-Ciocâlteu method (Chun et al. 2005). Other researchers have also used the Folin-Ciocâlteu method to enumerate total phenolic concentrations, in C. moschata species specifically, and suggest a wide range of 69.7 to 974.3 micrograms GAE per gram of mesocarp on a wet weight basis (Deng at al. 2013; Mokhtar et al. 2021).

    There are no DRIs for total phenolic content, gallic acid, or antioxidants in general, save vitamins and minerals which also happen to confer biologically relevant antioxidant capacity (e.g., β-carotene, vitamin C).

    Figure 3-2 shows the average concentrations of each bioactive compound analyzed in this study between each breeding line and butternut squash. Samples from lines UFTP57 and UFTP8 showed the highest concentrations of β-carotene concentrations, but these concentrations did not vary significantly from those found in samples from lines UFTP24, UFTP42, and UFTP47. Samples from lines UFTP46 and UFTP24 were found to have the highest concentrations of ascorbic acid, though concentrations in UFTP24 did not significantly differ from several other lines. Calabaza from line UFTP46 was found to have a significantly higher concentration of phenolic content (GAE) than any other experimental line and butternut squash. This study found that, among the breeding lines analyzed, UFTP24 and UFTP46 stand to confer the most nutritional benefit to human health as it relates to the bioactive and antioxidant capacities of β-carotene, ascorbic acid, and total phenolic content.

    Commercial Calabaza Cultivars

    Following experimentation, it was revealed that UFTP45 and UFTP46 are commercially available calabaza cultivars. The UFTP45 breeding line was revealed to be the cultivar ‘Soler’, released from the Agricultural Experiment Station at the University of Puerto Rico in 2004 (Wessel-Beaver 2005). Breeding line UFTP46 was revealed to be the cultivar ‘La Estrella’, developed by breeding programs at the University of Florida and released in 2002 (Maynard et al. 2002).

    In this study, these two cultivars performed vastly differently from each other compositionally. ‘Soler’ was among the lines with the highest moisture content (94.4%) and lowest soluble solids content (5.20 °Brix), while ‘La Estrella’ was among the lines with the lowest moisture content (76.3%) and highest soluble solids content (13.2 °Brix) (Table 3-2). ‘Soler’ exhibited one of the lowest concentrations of β-carotene equivalent concentrations among the lines analyzed in this study (17.4 μg βCE/g), while ‘La Estrella’ had approximately twice as much as ‘Soler’ (36.9 μg βCE/g), though it did not rank among the highest lines for β-carotene equivalent concentrations (Table 3-3). In a comparison of ascorbic acid content ‘Soler’ was found to have some of the lowest concentrations among the lines analyzed in this study (58.3 μg/g), while ‘La Estrella’ was found to have the highest concentration of ascorbic acid (207.4 μg/g) among all lines studied (Table 3-5). Among the breeding lines ‘Soler’ was found to have some of the lowest concentrations of phenolic content (193.6 μg GAE/g), while ‘La Estrella’ had the highest concentration of phenolics among all lines analyzed (526.6 μg GAE/g) (Table 3-7). Combining the results of these analyses, ‘Soler’ is associated with a less sweet-tasting mesocarp that has less health-promoting antioxidants than the sweeter-tasting ‘La Estrella’, which also boasts greater antioxidant capacity beneficial to human health.

    Applying nutrient content claims, as defined by the Food and Drug Administration, both ‘Soler’ and ‘La Estrella’ could be considered “excellent” sources of retinol activity equivalents because a single serving (approximately 100 grams) of either would provide at least 20% of the dietary reference intake for RAE across all life stages. ‘Soler’ could be considered a “good” source of vitamin C (10-19% DRI) across most life stages, with the exception of males 14 years of age and older (Table 3-5). In contrast, ‘La Estrella’ could be considered an “excellent” source of vitamin C across all life stages (Table 3-5). As previously stated, no DRIs have been established for phenolic content so nutrient content claims cannot be applied to ‘Soler’ or ‘La  Estrella’ in that regard.

     

    Table 3-2. Average moisture content  and °Brix of calabaza samples from each breeding line and samples from butternut squash.

    Breeding Line

    Moisture Contentwb (%)

    °Brix

    Waltham Butternut Squash

    87.6

    ±

    0.80ab

    11.6

    ±

    0.99ab

    UFTP8

    87.7

    ±

    1.90ab

    9.70

    ±

    0.68bc

    UFTP22

    91.5

    ±

    0.58ab

    7.96

    ±

    0.57cd

    UFTP24

    84.1

    ±

    1.29b

    10.2

    ±

    0.42bc

    UFTP38

    91.4

    ±

    2.20ab

    6.67

    ±

    0.90de

    UFTP42

    91.6

    ±

    1.15ab

    7.02

    ±

    0.59de

    UFTP45

    94.4

    ±

    1.55a

    5.20

    ±

    0.52e

    UFTP46

    76.3

    ±

    1.02c

    13.2

    ±

    1.80a

    UFTP47

    89.4

    ±

    2.86ab

    8.38

    ±

    0.83cd

    UFTP57

    86.5

    ±

    4.28b

    8.66

    ±

    0.35cd

    Average ± standard deviation; n = 3, except UFTP47 (n = 8) and UFTP57 (n = 9); Averages sharing the same letter do not differ significantly from one another.

     

    Table 3-3. Average β-carotene equivalent carotenoid concentrations (βCE) and calculated retinol activity equivalents (RAE) of calabaza samples from each breeding line and samples from butternut squash.

    Breeding Line

    Carotenoids (μg βCE/gwb)

    RAE (μg/gwb)

    Waltham Butternut Squash

    27.7

    ±

      6.87bc

    2.31

    ±

    0.57

    UFTP8

    54.9

    ±

    13.38ab

    4.58

    ±

    1.11

    UFTP22

    36.4

    ±

      4.64bc

    3.03

    ±

    0.39

    UFTP24

    44.4

    ±

    12.78abc

    3.70

    ±

    1.07

    UFTP38

    30.0

    ±

      8.94bc

    2.50

    ±

    0.75

    UFTP42

    48.4

    ±

      4.53abc

    4.04

    ±

    0.38

    UFTP45

    17.4

    ±

      9.78c

    1.45

    ±

    0.81

    UFTP46

    36.9

    ±

      9.48bc

    3.07

    ±

    0.79

    UFTP47

    35.6

    ±

    10.85abc

    2.97

    ±

    0.90

    UFTP57

    73.5

    ±

    27.35a

    6.13

    ±

    2.28

    Average ± standard deviation; n = 3; Averages sharing the same letter do not differ significantly from one another.

     

    Table 3-4. Percent Dietary Reference Intake (DRI) per life stage for retinol activity equivalents (RAE) provided by 100 grams raw calabaza.

     

    1 - 3 y

    4 - 8 y

    9 - 13 years

    14 - 18 years

    ≥19 years

    Breeding Line

    Males

    Females

    Males

    Females

    Males

    Females

    Waltham Butternut Squash

    110

    84

    52

    55

    37

    48

    37

    46

    UFTP8

    218

    166

    103

    109

    73

    94

    73

    92

    UFTP22

    144

    110

    68

    72

    48

    63

    49

    61

    UFTP24

    176

    135

    83

    88

    59

    76

    59

    74

    UFTP38

    119

    91

    56

    59

    40

    51

    40

    50

    UFTP42

    192

    147

    91

    96

    64

    83

    65

    81

    UFTP45

    69

    53

    33

    34

    23

    30

    23

    29

    UFTP46

    146

    112

    69

    73

    49

    63

    49

    61

    UFTP47

    141

    108

    67

    71

    47

    61

    47

    59

    UFTP57

    292

    223

    138

    146

    97

    126

    98

    123

     

    Table 3-5. Average ascorbic acid concentrations of raw calabaza samples from each breeding line and from the control, butternut squash.

    Breeding Line

    Ascorbic Acid (μg/gwb)

    Waltham Butternut Squash

    51.09

    ±

      3.92c

    UFTP8

    92.96

    ±

    11.87bc

    UFTP22

    66.79

    ±

     4.20bc

    UFTP24

    138.9

    ±

    10.74ab

    UFTP38

    72.39

    ±

      9.03bc

    UFTP42

    85.98

    ±

    18.08bc

    UFTP45

    58.26

    ±

      7.45c

    UFTP46

    207.4

    ±

    71.60a

    UFTP47

    73.42

    ±

    12.19bc

    UFTP57

    96.50

    ±

    29.73bc

    Average ± standard deviation; n = 3; Averages sharing the same letter do not differ significantly from one another.

     

     

     

     

     

    Table 3-6. Percent Dietary Reference Intake (DRI) per life stage for ascorbic acid (vitamin C) provided by 100 grams raw calabaza.

           

    14 - 18 years

    ≥19 years

    Breeding Line

    1 - 3 years

    4 - 8 years

    9 - 13 years

    Males

    Females

    Males

    Females

    Waltham Butternut Squash

    39**

    23**

    13*

    8

    9

    7

    9

    UFTP8

    72**

    42**

    24**

    15*

    15*

    12*

    15*

    UFTP22

    51**

    30**

    17*

    11*

    11*

    9

    11*

    UFTP24

    107**

    63**

    36**

    22**

    23**

    19*

    23**

    UFTP38

    56**

    33**

    19*

    11*

    12*

    10*

    12*

    UFTP42

    66**

    39**

    22**

    14*

    14*

    11*

    14*

    UFTP45

    45**

    26*

    15*

    9

    10*

    8

    10*

    UFTP46

    160**

    94**

    53**

    33**

    35**

    28**

    35**

    UFTP47

    56**

    33**

    19*

    12*

    12*

    10*

    12*

    UFTP57

    74**

    44**

    25**

    15*

    16*

    13*

    16*

    * denotes “good” source (10 -19% DRI); ** denotes “excellent” source (≥ 20% DRI).

    Table 3-7. Average total phenolic compound concentrations of raw calabaza samples from each breeding line and from the control, butternut squash.

    Breeding Line

    Phenolics (μg GAE/gwb)

    Waltham Butternut Squash

    265.83

    ±

    65.80bc

    UFTP8

    238.43

    ±

    37.58c

    UFTP22

    225.23

    ±

    20.16c

    UFTP24

    377.77

    ±

    44.96b

    UFTP38

    168.42

    ±

    33.58c

    UFTP42

    181.23

    ±

    22.71c

    UFTP45

    193.62

    ±

    14.74c

    UFTP46

    526.59

    ±

    84.44a

    UFTP47

    241.04

    ±

      8.82c

    UFTP57

    263.77

    ±

    20.06bc

    Average ± standard deviation; n = 3; Averages sharing the same letter do not differ significantly from one another.

     

     

     

     

     

    Figure 3-2. Average bioactive compound concentrations for each breeding line plus butternut squash samples.

    Figure 3-2. Average bioactive compound concentrations for each breeding line plus butternut squash samples.

    Activity 4: Correlations between bioactive compound concentrations and tristimulus colorimetric values to approximate moisture, soluble solids, carotenoid content, ascorbic acid content, and phenolic content in calabaza mesocarp

     

    Correlations between Colorimetric Values and Bioactive Compounds of Randomly Selected Calabaza Subsamples

    Significant correlations (Pearson, r) were observed between the measured L*, a*, and b* readings taken at a single point along the equatorial circumference of each calabaza sample, as well as the respective chroma value (C*) and hue angle (ha,b) calculations, and target compound concentrations within random subsamples of calabaza mesocarp from each fruit sample (Table 4-2). Weak correlations were observed between L* (lightness) and all target compounds analyzed, save total soluble solids content, which showed a moderately strong, positive, and statistically significant correlation with L*, r(28) = .42, p < .05. The measured colorimetric values for a* (redness-greenness) showed a strong, negative correlation with moisture content (r(64) = -.51, p < .0001) and strong, positive correlations with β-carotene equivalent concentrations (r(34) = .54, p < .001), ascorbic acid content (r(35) = .44, p < .01), and total soluble solids (r(28) = .64, p < .001). A moderately strong, positive correlation was observed between a* and total phenolic content extracted from the calabaza subsamples, but it was not statistically significant (p > .05). A statistically significant correlation was found between measured b* (yellowness-blueness) values and each target compound analyzed; moisture content showed a strong, negative correlation with b* (r(64) = -.56, p < .0001), while β-carotene equivalent concentration, ascorbic acid content, and total soluble solids showed strong, positive correlations with b* (r(34) = .56, p < .001, r(35) = .51, p < .01, r(28) = .60, p < .001, respectively). Though significant, total phenolics shared only a moderately strong, positive correlation with b* (r(28) = .41, p < .05).

    Chroma (C*) and hue angle (ha,b) were calculated from the L*, a*, and b* measurements and showed significant correlations with the analyzed compounds extracted from the calabaza subsamples. Moisture content exhibited a strong, negative correlation with C* (r(64) = -.57, p < .0001), while β-carotene equivalent concentration, ascorbic acid content, and total soluble solids showed strong, positive correlations with b* (r(34) = .57, p < .001, r(35) = .51, p < .01, r(28) = .62, p < .001, respectively). Total phenolic content showed a positive, moderately strong correlation with C* (r(28) = .41, p < .05). Moisture content showed a moderately strong, positive correlation with ha,b that was statistically significant (r(64) = .48, p < .0001). Beta-carotene equivalent concentrations and ascorbic acid content also demonstrated significant, moderate-strength correlations with ha,b, though negatively correlated (r(34) = -.48, p < .001, r(35) = -.40, p < .05, respectively). Total soluble solids showed a strong, negative correlation with ha,b (r(28) = -.64, p < .001). Finally, total phenolic content showed a negative, moderate-strength correlation with ha,b, but it was not found to be statistically significant (p > .05).

    These results suggest that as redness of the calabaza mesocarp increases, moisture content decreases, while also indicating that β-carotene equivalent concentrations, ascorbic acid content, and total soluble solids may be increased. Similar to redness and moisture, increased yellow pigmentation in calabaza mesocarp may indicate decreased moisture content. Increased yellowness may also indicate increased β-carotene equivalent concentrations, ascorbic acid, total soluble solids, and total phenolic compounds. Increased saturation of the hue of the mesocarp may indicate decreased moisture content; that is, a dull hued mesocarp is likely to have more moisture than a clear, brightly hued mesocarp. In contrast, increased saturation of hue may indicate increased concentrations of β-carotene equivalent concentrations, ascorbic acid, total soluble solids, and total phenolic compounds. Lastly, results show that an increased hue angle may indicate increased moisture, which is in accordance with other findings of this study that correlate yellowness and redness with decreased moisture. Since increased yellowness and redness were also found to be likely indicators of increased β-carotene equivalent carotenoid concentrations, ascorbic acid, total soluble solids, and total phenolic compounds, it should hold that these target compound concentrations should be decreased when hue angle is increased, which is supported by the inverse correlation found between these compound concentrations and hue angle.

    The directions of the correlations reported by Simonne et al. (1993) and Itle and Kabelka (2009) support the directions of correlations found in this study, however a discrepancy in the strengths of correlations may be attributed to the methods of analysis used in each study and, in the case of research conducted by Simonne et al. (1993), the use of a different color space (Hunter L a b vs. CIEL*a*b* used here).

    Significant correlations were also observed between L*, a*, and b* measurements, C* and ha,b calculations, and the phenotypic characteristics of the calabaza samples, specifically mass, widest circumference, and height measured from blossom end to stem beginning following a longitudinal cut through the middle of each fruit sample (Table 4-3). Weak, negative correlations were observed between L* and mass and L* and circumference while almost no correlation was observed between L* and fruit height. A weak, negative correlation was found between a* and mass of the sample fruits, but the association was not significant (p > .05). Equatorial circumference showed a significant, moderate-strength correlation with a*, negatively correlated (r(64) = -.34, p < .01), while fruit height also showed a significant, moderate-strength correlation with a*, positively correlated (r(64) = .24, p < .05). A significant, though weak, negative correlation was found between circumference and b* (r(64) = -.29, p < .05). A weak, negative correlation between mass and b* and a weak, positive correlation between height and b* were also observed, though neither were statistically significant (p > .05). Chroma exhibited one significant, negative correlation, though weak, with circumference (r(64) = -.28, p < .05). It also showed weak correlations with mass, negatively correlated, and height, positively correlated. Hue angle was found to have significant correlations, though only of weak to moderate strength, with circumference (r(64) = .34, p < .01) and height (r(64) = .25, p< .05).

    Moderate-strength correlations between a* and circumference and height of calabaza fruit may suggest that as fruits widen the redness of the mesocarp decreases. In contrast, redness may increase as fruit height increases. In general, though some of the correlations between color space values and calculations and phenotypic characteristics of calabaza fruit showed statistical significance, none of the correlations were particularly strong (-.50 < r  < .50) suggesting that phenotypic characteristics are not related to or good predictors of calabaza mesocarp colorimetric values.

    Significant correlations were also observed between proximate and bioactive compound concentrations extracted from random subsamples from each sample calabaza fruit (Table 4-4). Moisture content only weakly correlated with mass and height, with the latter practically not at all. A moderately strong, positive correlation was observed between moisture and circumference, and the correlation was statistically significant (r(64) = .32, p < .01). Moisture negatively correlated with target and bioactive compound concentrations within the subsamples of mesocarp; it was moderately correlated with β-carotene (r(34) = -.41, p < .05), strongly correlated with ascorbic acid (r(35) = -.84, p < .0001), strongly correlated with total soluble solids (r(28) = -.87, p < .0001), and strongly correlated with total phenolic compounds (r(28) = .88, p < .0001). Besides its correlation with moisture content, β-carotene concentration was only found to significantly correlate with ascorbic acid, and only moderately so (r(34) = .44, p < .01). Concentrations of β-carotene showed weak and negatively correlated associations with phenotypic characteristics of calabaza samples and weak and positively correlated associations with soluble solids content and total phenolics (p > .05). Like β-carotene concentrations, ascorbic acid content was only weakly and negatively associated with phenotypic characteristics of calabaza fruit; however, ascorbic acid did demonstrate a strong, positive correlation with total soluble solids content (r(28) = .65, p < .0001) and total phenolics (r(28) = .83, p < .0001). Strong, negative correlations were observed between total soluble solids and mass (r(28) = -.55, p < .01) and circumference (r(28) = -.66, p < .0001), but only a weak, positive correlation was observed between soluble solids and height (p > .05). There was a strong, positive correlation found between soluble solids and total phenolic content (r(28) = .81, p < .0001). Lastly, total phenolic content demonstrated moderate, negative correlations with mass and circumference of calabaza fruit, though neither association was statistically significant (p > .05), and almost no correlation with height of calabaza fruit.

    These results suggest that calabaza higher in moisture content may have lower concentrations of β-carotene equivalent carotenoids, ascorbic acid, soluble solids, and total phenolic compounds than calabaza fruits lower in moisture. This observed inverse relation of moisture with bioactive compounds and soluble solids concentrations within calabaza mesocarp, and to a lesser extent, the observed positive association of total soluble solids with bioactive compounds,  may be useful as a harvest index not only for fruit maturity, but also for phytonutrient density, especially with regard to total phenolic compound concentrations.

    A “fairly good” negative correlation was reported by Culpepper and Moon (1945) between mature fruit size and total solids content in Cucurbita spp. This supports the strong, negative correlation of TSS with mass and circumference observed in this study since TSS is a fraction of total solids. Results of this study are comparable to those of Kulczyński and Gramza-Michalowska (2019) who observed a significant, moderate strength, positive correlation between total carotenoid content and phenolic content (r = .44, p < .05) and phenolic content and ascorbic acid, reported as vitamin C (r = .42, p < .05)  in another cucurbit species, Cucurbita pepo. Unlike results of the present study, Kulczyński and Gramza-Michalowska (2019) found no statistically significant correlations between bioactive compounds when varieties of Cucurbita moschata were analyzed. Differences in the results of these studies may be attributed to the analytical methodology chosen; HPLC, a more precise method of analysis, was used to analyze carotenoids and vitamin C in Kulczyński and Gramza-Michalowska’s (2019) study.

    The strong, positive correlation between ascorbic acid and TPC is most likely due to the method for extraction of total phenolics used in this study; the Folin-Ciocâlteu method measures phenolic content, as well as other reducing agents found within a given substrate and, therefore, likely reflects the content of ascorbic acid. Attempts were made to mitigate this overlap by incubating samples for 48 hours, however future work may consider other FC protocols with different incubation periods better suited for phenolic extraction from calabaza, specifically.

    Correlations between Colorimetric Values and Bioactive Compounds of Non-randomized Calabaza Subsamples

    Significant correlations (Pearson, r) were observed between colorimetric readings and calculations and target bioactive compounds extracted from 2 gram, non-randomized plugs of calabaza subsamples (Table 4-5). Similar to the results reported in section 4.3.1, L* showed only weak correlations with β-carotene and ascorbic acid. In this experiment, L* also showed a weak correlation with total phenolic compound concentrations, but a moderate correlation with total soluble solids, though the correlation was not statistically significant (p > .05). Concentrations of β-carotene equivalent carotenoids and TPC concentrations showed moderately strong, positive correlations with a* colorimetric values, but were not statistically significant (p > .05), unlike correlations between a* and ascorbic acid (r(14) = .61, p < .05) and a* and TSS (r(13) = .65, p < .01) which were strong. Concentrations of β-carotene equivalent carotenoids and ascorbic acid demonstrated strong, positive correlations with b* colorimetric values (r(13) = .64, p < .05 and r(14) = .59, p < .05, respectively). A positive, moderate-strength correlation was observed between b* and TSS, while a weak but positive correlation was observed between b* and TPC. Neither correlation was found to be statistically significant (p > .05). Concentrations of β-carotene equivalent carotenoids and ascorbic acid were found to significantly correlate with calculated C* values (r(13) = .66, p < .01 and r(14) = .61, p < .05, respectively), both exhibiting a strong, positive relation. Chroma only moderately correlated with TSS and weakly correlated with TPC. Calculated ha,b showed a moderate-strength, negative correlation with β-carotene equivalent carotenoids and TPC, but neither correlation was found to be statistically significant (p > .05). There were strong, negative correlations observed between ha,b and ascorbic acid and TPC that were found to be statistically significant (r(14) = -.55, p < .05 and r(13) = -.67, p < .01, respectively).

    Results of this study further support that redness of calabaza mesocarp may indicate increased concentrations of ascorbic acid and total soluble solids, though results did not support redness as an indication of β-carotene equivalent carotenoid concentrations as they did in Section 4.3.1. Yellowness of calabaza mesocarp may be an indication of β-carotene equivalent carotenoid concentrations and ascorbic acid, as suggested previously (Section 4.3.1), but not of TSS or TPC. A bright, clear hue (denoted by increased C*) of calabaza mesocarp may indicate increased concentrations of β-carotene equivalent carotenoids and ascorbic acid, but there was insufficient evidence to support saturation of hue as an indication of increased TSS or TPC in this experiment. Similar to previous results, results from this experiment suggest that the farther away the color of mesocarp is from red and yellow along the a*, b* plane within the 3-dimensional CIEL*a*b* color space, the lower the concentrations of bioactive compounds, particularly ascorbic acid and TSS.

    Figure 4-1. Schematic illustrating triplicate colorimetric measurements (‘x’) taken from skin side of a plug of mesocarp subsample (skin removed). Opposite side of calabaza reserved for processing for subsequent moisture, soluble solids, β-carotene equivalent carotenoids, ascorbic acid, and total phenolic compound analyses.

    Figure 4-1. Schematic illustrating triplicate colorimetric measurements (‘x’) taken from skin side of a plug of mesocarp subsample (skin removed). Opposite side of calabaza reserved for processing for subsequent moisture, soluble solids, β-carotene equivalent carotenoids, ascorbic acid, and total phenolic compound analyses.

     

    Figure 4-2. Subsample plugs of mesocarp, each measured for color (‘x’) on both sides of plug, in triplicate (skin removed) for a total of six colorimetric measures per plug. Each plug was designated for a specific analysis, either of β-carotene equivalent carotenoids, ascorbic acid, soluble solids, or total phenolic content.

     

    Figure 4-2. Subsample plugs of mesocarp, each measured for color (‘x’) on both sides of plug, in triplicate (skin removed) for a total of six colorimetric measures per plug. Each plug was designated for a specific analysis, either of β-carotene equivalent carotenoids, ascorbic acid, soluble solids, or total phenolic content.

    Table 4-1. Average mass, equatorial circumference, height, and color space values of (n = 3) calabaza samples from each breeding line, plus butternut squash samples; average ± standard deviation.

    Breeding

    Line

    Mass (kg)

    Equatorial Circumference

    (cm)

    Height (cm)

    L*

    a*

    b*

    Waltham Butternut

    0.429 ± 0.12

    24.39 ± 3.00

    14.34 ± 1.89

    71.84 ± 1.67

    17.07 ± 0.72

    70.31 ± 0.19

    UFTP8

    1.189 ± 0.02

    47.89 ± 1.51

    10.07 ± 0.45

    69.80 ± 0.46

    14.48 ± 3.69

    72.77 ± 1.80

    UFTP22

    1.300 ± 0.17

    45.35 ± 2.05

    12.53 ± 0.80

    76.19 ± 1.03

    12.49 ± 1.88

    72.66 ± 3.39

    UFTP24

    0.763 ± 0.36

    38.47 ± 0.48

    10.03 ± 0.35

    69.64 ± 4.38

    14.25 ± 2.21

    73.07 ± 2.76

    UFTP38

    1.797 ± 0.08

    54.77 ± 0.16

    12.37 ± 0.61

    70.45 ± 3.26

    8.72 ± 2.91

    63.93 ± 3.80

    UFTP42

    1.393 ± 0.29

    49.53 ± 5.01

    10.90 ± 0.61

    68.03 ± 2.70

    7.72 ± 7.19

    68.86 ± 5.56

    UFTP45

    2.236 ± 0.57

    64.61 ± 7.10

    10.60 ± 0.62

    68.79 ± 1.45

    -2.70 ± 3.14

    54.63 ± 2.70

    UFTP46

    1.248 ± 0.19

    44.56 ± 0.59

    11.83 ± 0.59

    74.94 ± 1.27

    11.35 ± 4.64

    74.69 ± 6.60

    UFTP47

    2.464 ± 0.52

    58.21 ± 4.65

    13.13 ± 0.35

    73.58 ± 6.98

    2.62 ± 4.23

    58.99 ± 8.84

    UFTP57

    1.707 ± 0.09

    49.64 ± 1.33

    13.73 ± 0.57

    73.91 ± 0.89

    15.95 ± 3.00

    79.26 ± 0.97

    Table 4-2. Pearson coefficients denoting strength and direction of linear correlations between target compounds and colorimetric values.

    Bioactive Compound

    L*

    a*

    b*

    C*

    ha,b (°)

    Moisture

    -.16

    -.51*

    -.56*

    -.57*

    .48*

    β-carotene

    .03

    .54*

    .56*

    .57*

    -.48*

    Ascorbic Acid

    .26

    .44*

    .51*

    .51*

    -.40*

    Total Soluble Solids

    .42*

    .64*

    .60*

    .62*

    -.64*

    Total Phenolics

    .33

    .32

    .41*

    .41*

    -.31

    * denotes statistically significant correlations.

     

     

     

     

     

     

    Table 4-3. Pearson coefficients denoting strength and direction of linear correlations between phenotypic characteristics of calabaza samples and colorimetric values.

    Phenotypic Characteristic

    L*

    a*

    b*

    C*

    ha,b (°)

    Mass

    -.13

    -.15

    -.18

    -.15

    .14

    Circumference

    -.23

    -.34*

    -.29*

    -.28*

    .34*

    Height

    .05

    .24*

    .19

    .21

    -.25*

    * denotes statistically significant correlations.

     

     

     

     

     

    Table 4-4.  Pearson coefficients denoting strength and direction of linear correlations between phenotypic characteristics and bioactive compound concentrations of calabaza samples.

     

    Moisture

    β-carotene

    Ascorbic Acid

    Total

    Soluble Solids

    Total Phenolics

    Mass

    .18

    -.20

    -.23

    -.55*

    -.31

    Circumference

    .32*

    -.19

    -.19

    -.66*

    -.34

    Height

    -.03

    -.15

    -.25

    .17

    -.06

    Moisture

    -

    -.41*

    -.84*

    -.87*

    -.88*

    β-carotene

    -.41*

    -

    .44*

    .20

    .13

    Ascorbic Acid

    -.84*

    .44*

    -

    .65*

    .83*

    Total Soluble Solids

    -.87*

    .20

    .65*

    -

    .81*

    Total Phenolics

    -.88*

    .13

    .83*

    .81*

    -

    * denotes statistically significant correlations.

     

    Table 4-5.  Pearson coefficients denoting strength and direction of linear correlations between bioactive compounds of non-random calabaza plugs and each plug’s colorimetric values.

    Bioactive Compound

    L*

    a*

    b*

    C*

    ha,b (°)

    β-carotene

    .18

    .44

    .64*

    .66*

    -.36

    Ascorbic Acid

    .11

    .61*

    .59*

    .61*

    -.55*

    Total Soluble Solids

    .42

    .65*

    .47

    .49

    -.67*

    Total Phenolics

    .19

    .33

    .20

    .22

    -.32

    * denotes statistically significant correlations.

Objective 3: Determine yield, fruit quality and disease resistance of tropical pumpkin cultivars in the Southeastern U.S. and Puerto Rico in organic and conventional cropping systems and determine phenotypic relationships among nutrition, flavor and fruit size traits in select germplasm.

Team: Geoffrey Meru, Angela Ramírez, Andre da Silva, and Carlene Chase

Activity 1: Performance of calabaza germplasm in Florida

The fruit weight varied across the germplasm evaluated and ranged from 0.85lb (JW6823 butternut) to 5.75 lb (Dickson) (Table 1). Similar results were observed for yield per plant which was highest in JW6823 butternut but least in Fortuna and UFTP25 (Table 1). However, the fruit weight and total weight/ acre was highest yield in UFTP42 followed by UFTP24, but least in Fortuna followed by WB butternut (Table 1). Fruit quality parameters varied significantly across the squash germplasm evaluated (Table 2). Flesh color was ranked highest in UFTP 1990 but least in Taina Dorada. On the other hand, the Brix index was highest in  JW6823 butternut but least in Dickson (Table 2). Fruit size also varied across the squash germplasm with the butternut cultivars having the least fruit length, fruit width, and flesh thickness. On the contrary these parameters were highest in Dickson pumpkin (Table 2).

 

TREC Yield 2022

Table 1: Fruit yield data for squash germplasm evaluated in Florida under conventional production system

Cultivar​

Fruit WT​

Fruit_plotcount​

Fruit yield per plant​

Fruit WT/ plant​

FT weight /acre​

No. 40 lb boxes​

$Value/acre​

Fortuna​

3.25​

1.33​

0.44​

1.44​

3466.67​

86.67​

1300.00​

WB​

0.95​

5.33​

1.78​

1.69​

4053.33​

101.33​

1520.00​

UFTP25​

4.86​

1.33​

0.44​

2.16​

5184.00​

129.60​

1944.00​

UFTP57​

4.13​

2.00​

0.67​

2.75​

6608.00​

165.20​

2478.00​

JW6823​

0.85​

10.00​

3.33​

2.83​

6800.00​

170.00​

2550.00​

Kakai​

2.09​

4.33​

1.44​

3.02​

7245.33​

181.13​

2717.00​

UFTP22​

2.63​

3.67​

1.22​

3.21​

7714.67​

192.87​

2893.00​

Taina Dorada​

4.04​

2.67​

0.89​

3.59​

8618.67​

215.47​

3232.00​

UFTP4​

2.33​

4.67​

1.56​

3.62​

8698.67​

217.47​

3262.00​

Verde​

3.95​

4.00​

1.33​

5.27​

12640.00​

316.00​

4740.00​

Soler​

5.00​

3.33​

1.11​

5.56​

13333.33​

333.33​

5000.00​

UFTP26​

5.00​

3.33​

1.11​

5.56​

13333.33​

333.33​

5000.00​

1990​

3.73​

5.33​

1.78​

6.63​

15914.67​

397.87​

5968.00​

UFTP32​

4.68​

4.33​

1.44​

6.76​

16224.00​

405.60​

6084.00​

La Estrella​

4.77​

4.33​

1.44​

6.89​

16525.60​

413.14​

6197.10​

UFTP8​

3.88​

5.33​

1.78​

6.90​

16554.67​

413.87​

6208.00​

UFTP81​

5.33​

4.00​

1.33​

7.11​

17056.00​

426.40​

6396.00​

UFTP34​

4.98​

4.33​

1.44​

7.19​

17264.00​

431.60​

6474.00​

UFTP80​

4.67​

4.67​

1.56​

7.26​

17423.47​

435.59​

6533.80​

UFTP44​

4.92​

4.67​

1.56​

7.65​

18368.00​

459.20​

6888.00​

Dickinson ​

5.75​

4.00​

1.33​

7.67​

18400.00​

460.00​

6900.00​

UFTP36​

5.10​

5.00​

1.67​

8.50​

20400.00​

510.00​

7650.00​

UFTP24​

5.22​

5.00​

1.67​

8.70​

20880.00​

522.00​

7830.00​

UFTP42​

5.38​

5.33​

1.78​

9.56​

22954.67​

573.87​

8608.00​

 

 

 

 

 

 

Table 2: Fruit quality of the squash germplasm evaluated in  Florida under conventional production system.

Cultivar

Flesh_Color

Brix_(%)

Fruit_lnth_(cm)

Flesh_Thickness_(mm)

Fruit_width_(cm)

 Fruit_width_(lb)

Dickinson

1.11

2.50

19.29

2.48

16.74

5.75

SS2256

0.95

2.69

14.73

3.64

19.04

5.65

UFTP38

1.54

2.83

14.30

2.88

20.35

6.69

UFTP42

1.36

2.83

12.75

3.67

18.49

5.38

SS2259

1.04

3.03

17.33

3.66

20.16

7.31

Soler

1.22

3.53

11.94

3.34

19.59

5.00

SS2257

1.46

3.58

15.60

2.44

15.08

3.33

Fortuna

1.75

3.75

10.80

3.23

17.93

3.25

UFTP57

2.00

4.13

14.49

2.90

15.85

4.13

Taina Dorada

0.92

4.22

11.86

3.49

17.58

4.04

UFTP44

1.72

4.47

11.63

3.91

19.19

4.92

UFTP25

2.00

4.75

14.60

3.78

17.08

4.86

Verde

1.50

4.75

9.63

2.95

16.52

3.95

UFTP10

1.83

4.83

13.23

3.53

18.51

5.24

UFTP81

2.00

4.97

13.21

3.21

18.26

5.33

UFTP22

1.92

5.00

11.99

2.76

13.72

2.63

UFTP34

2.08

5.00

14.85

3.25

16.83

4.98

1990

2.38

5.08

14.93

2.68

15.28

3.73

UFTP36

1.83

5.08

13.29

3.45

17.94

5.10

UFTP26

1.92

5.13

11.98

2.98

16.95

5.00

UFTP24

1.61

5.81

14.77

3.59

17.83

5.22

UFTP32

2.25

5.83

12.06

3.56

17.30

4.68

La Estrella

1.17

6.00

14.76

3.21

16.79

4.77

UFTP80

2.13

6.33

12.33

3.33

17.45

4.67

UFTP4

1.71

6.53

9.58

2.56

13.60

2.33

UFTP8

2.04

7.17

13.32

3.28

16.32

3.88

WB

2.33

7.25

14.01

1.42 c

8.84

0.95

JW6823

1.71

7.75

13.63

1.45 c

7.71

0.85

Kakai

1.00

.

12.60

2.00

15.13

2.09

 

 

Activity 2: Performance of calabaza germplasm in Puerto Rico

Horticultural traits evaluated like silverleaf, vigor, vine length, flowering male, and female) were statistically significant in the Spring trial. Means separation was performed using Tuckey (a= 0.05). Data on disease evaluation demonstrate that lines UFTP58 (Table 1) and Verde Luz were the only ones to show <10% of leaves symptoms for silverleaf.  Most lines under the conventional trial had silverleaf on >50-80% of the leaves (scores of 3.5 to 4). Genotypes Fortuna and Soler had higher (5) scores for silverleaf symptoms under the conventional trial. While under the organic trial genotypes UFTP58, Fortuna and Verde Luz had scores of Regarding powdery mildew (PM) evaluation, the only genotype showing PM symptoms was UFTP58 under both cropping systems. Under the horticultural evaluation lines UFTP34 and UFTP81 had excellent vigor (score of 5) under the conventional cropping system (Table 1) However, those genotypes did not have the same vigor under the organic trial. Genotypes UFTP38 and UFTP32 had the poorest vigor under the organic, while under the conventional those genotypes had scores of 4.6 and 4, respectively. Genotype UPFTP58 had the poorest vigor the conventional trial. In general, female flowering began at 38 after transplant (UFTP58), followed by UFTP4 (39 d), and the latest genotypes to have females flower was at 61 (Fortuna) days after transplanted under the conventional, while in the organic, genotype UPFT58 (34 d) was the earliest and UFPT10 and Soler was the latest (54 days). Considering male flowering under the organic started at 22 days (UFTP34) and the latest at 56 days (Fortuna). Under the conventional, the earliest male flower was in UFTP58 at 22 days after transplanting and UFPT22, UFPT26, and Fortuna (51 days) at the latest. Average male flowering regardless of the cropping system was at 44 days after transplanting. In general, most genotypes tended, under both cropping systems, to have small to medium vine lengths. Regarding yield, yield components (Table 2), the number of fruits per plot was 1 to 14 with a mean value of 8 for the conventional and 7 for the organic system. The number of marketable fruits in the plot was an average of 7 for both management systems (Table 2). The average fruit weight in the conventional system was 7.5 pounds and in the organic 6.6 pounds (Table 3), a small pumpkin and desirable size for some of the Puerto Rico vegetable markets. Most lines presented an orange color flesh with high sugar content (average of 8 Brix), average sweetness at consumption time and overall rating of 2 for both management growing systems (Table 4).  Some lines performed equally under both systems like UFPT 4, UFPT22, UFPT46 and Fortuna behave similarly in the downscale of yield, UFPT34 (C), UFTP42 and UFPT45 had the higher yield, however, this result was in one of the growing systems, non-showing consistent under both parameters. In general, a reduction of about + 6,000 kg ha-1 is observed in the others breeding lines when comparing yield under conventional versus organic, being the organic the one that have less production (Table 5). Promising lines are also observed under organic conditions (UFTP42, UFPT45) when compared to the conventional.

Table 1. Averages of the agronomic variables: days to male flower, days to female flower, vine length, plant vigor and silver leaf, of 22 genotypes of calabaza or pumpkin (Cucurbita moschata Duchesne), evaluated in experimental trials in the Lajas Agricultural Experimental Station from January to April in 2022.

 

 

Genotype

Days to male flower

Days to female flower

Vine length

1-4

Plant vigor

1-5

Silverleaf

1-5

 

Conventional

Organic

Conventional

Organic

Conventional

Organic

Conventional

Organic

Conventional

Organic

UFTP4

47 ab

45  bc

    39 a

 43 ab

1 a

1 a

     3 ab

3 ab

4 a

3  bc

UFTP8

48 ab

47  bc

    50   bcd

 49 ab

1  a

1 a

     4   bc

3 ab

4 a

3  bc

UFTP10

49 ab

46  bc

    50   bcd

 53   b

  2 ab

2 a

     4   bc

  4   bc

4 a

3  bc

UFTP22

51   b

49  bc

    58     c

  54   bc

1 a

1 a

     3 ab

  4   bc

3 a

3  bc

UFTP24

49 ab

44  bc

    44 ab

43 ab

 2 ab

2 a

     3 ab

  4   bc

4 a

3  bc

UFTP26

51   b

48  bc

    49   bc

46 ab

 2 ab

2 a

     4   bc

  4   bc

4 a

4    cd

UFTP32

47 ab

47  bc

    45 ab

45 ab

 2 ab

2 a

     5     c

  5     c

4 a

3  bc

UFTP34

47 ab

45  bc

    45 ab

43 ab

 3 ab

2 a

     5     c

  5     c

3 a

3  bc

UFTP36

48 ab

45  bc

    45 ab

44 ab

 2 ab

3 a

     5     c

  5     c

3 a

4    cd

UFTP38

      43 a

  40  b

    43 ab

42 ab

 2 ab

2 a

     4   bc

  4   bc

4 a

3  bc

UFTP42

      47 ab

48  bc

    45 ab

46 ab

 2 ab

2 a

     4   bc

  4   bc

4 a

4    cd

UFTP44

      47 ab

46  bc

    47 ab

49 ab

 2 ab

2 a

     4   bc

  5     c

4 a

3  bc

UFTP45

      51   b

  51    c 

    59        de   

   73      d

 3   b

3 a

     3 ab

 3 ab

5 a

5     d

UFTP46

      45 ab

  41  bc

    48 ab

    37 a

        1 a

2 a

     3 ab

 3 ab

4 a

3  bc

UFTP47

      48 ab

  46  bc

    50   bcd

 55   bc

  3   b

3 a

     3 ab

   4    bc

3 a

3  bc

UFTP57

      48 ab

  45  bc

    50   bcd

    46 ab

1 a

1 a

     3 ab

 3 ab

4 a

4    cd

UFTP80

      48 ab

  49  bc

    47 ab

    51 ab

 2 ab

1 a

     5     c

   4    bc

4 a

4    cd

UFTP81

      46 ab

  46  bc

    47 ab

    47 ab

 2 ab

1 a

     5     c

   4    bc

4 a

3  bc

Verde Luz

      45 ab

  51    c  

    46 ab

    48 ab

 2 ab

2 a

     3 ab

    2 a

1 b

1 a

Fortuna

      51   b

  21 a    

    61       e 

  68    cd

 3   b

2 a

     2 a

    3 ab

5 a

2 ab

TD

      47 ab

 44   bc

    46 ab

    47 ab

 2 ab

3 a

     3 ab

    3 ab

4 a

4    cd

Soler

      49 ab

  51     c

    49   bc

    53   b

 3    b

2 a

     4   bc

    3 ab

4 a

2 ab

Mean

47.79

46.75

    48.35

   49.30

1.94

1.97

     3.52

3.66

3.77

3.15

MSD

6.61

9.78

      9.84

   14.00

1.72

 2.05

     1.92

1.75

1.92

1.46

1/ Table 1 does not show data for the UFTP58 genotype, as it is very early compared to the other genotypes.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 2. Averages of the agronomic variables: number of plants in the plot, total de fruits in the plot, number of marketable fruits in the plot, total weight of marketable fruits in the plot, number of unmarket fruits in the plot and total weight of unmarket table fruits, in the plot of 22 genotypes of calabaza or pumpkin (Cucurbita moschata Duchesne), evaluated in experimental trials in the Lajas Agricultural Experimental Station from January to April in 2022.

 

 

Genotype

Number of plants in the plot

Total of fruits in the plot

Number of marketable fruits in the plot

Total weight of marketable fruits in the plot

Number of unmarket fruits in the plot

Total weight of unmarket table fruits in the plot

Conventional

Organic

Conventional

Organic

Conventional

Organic

Conventional

Organic

Conventional

Organic

Conventional

Organic

UFTP4

4

3

      5 ab

   4 a

  3 a

3 a

   10.74 a

9.40 a

2 a

1a

3.85 a

1.23 a

UFTP8

4

4

    12   b

10 a

 12    b

9 a

   75.39 ab

45.03 ab

0 a

1 a

0.60 a

1.20 a

UFTP10

5

4

    11 ab

  6 a

 11  ab

6 a

   66.39 ab

31.13 ab

0 a

0 a

3.17 a

0.00 a

UFTP22

5

4

      5 ab

  5 a

   5  ab

5 a

   16.86 a

 22.00 ab

0 a

0 a

0.65 a

0.00 a

UFTP24

5

5

      6 ab

  8 a

   6  ab

8 a

   54.98 ab

 66.88 ab

0 a

0 a

0.60 a

0.00 a

UFTP26

5

4

     5 ab

  8 a

   5  ab

8 a

   48.55 ab

 61.37 ab

0 a

0 a

0.00 a

0.00 a

UFTP32

5

5

   12   b

    10 a

  12  b

9 a

   74.80 ab

 68.81 ab

0 a

0 a

0.00 a

0.60 a

UFTP34

4

2

     9 ab

 5 a

    9 ab

5 a

   99.61   b

 41.00 ab

0 a

0 a

0.00 a

0.00 a

UFTP36

5

5

   11 ab

 9 a

 11  ab

9 a

   84.90  ab

 74.28 ab

0 a

0 a

0.00 a

0.00 a

UFTP38

4

5

     7 ab

 5 a

    7 ab

5 a

   57.74  ab

 55.46 ab

0 a

0 a

0.00 a

0.00 a

UFTP42

4

5

     7 ab

    10 a

    7 ab

  10 a

   60.14  ab

85.66 b

0 a

0 a

0.00 a

0.00 a

UFTP44

4

4

     9 ab

 8 a

    9 ab

8 a

   69.82  a

  66.35 ab

0 a

0 a

0.00 a

0.00 a

UFTP45

4

3

     9 ab

 8 a

    8 ab

8 a

   49.99  ab

  66.80 ab

1 a

0 a

4.00 a

3.10 ab

UFTP46

5

4

     5 ab

 6 a

    5 ab

6 a

   23.73  a

  30.35 ab

0 a

0 a

0.00 a

0.00 a

UFTP47

4

5

     6 ab

   10 a

    6 ab

   10 a

   51.80  ab

  79.27 ab

0 a

0 a

0.00 a

0.00 a

UFTP57

4

4

    5 ab

7 a

    5 ab

6 a

   32.92  ab

  26.20 ab

0 a

1 a

0.00 a

6.50 b

UFTP80

4

4

  12   b

7 a

  12   b

7 a

 102.85    b

   41.93 ab

0 a

0 a

0.00 a

0.00 a

UFTP81

5

5

    7 ab

7 a

    7 ab

7 a

   73.08  ab

   25.70 ab

0 a

0 a

0.00 a

0.00 a

Verde Luz

4

2

    8 ab

3 a

    6 ab

2 a

   36.17  ab

     10.07 a

2 a

0 a

2.03 a

0.53 a

Fortuna

3

2

         4 a

2 a

  4 a

2 a

  18.78  a

   11.07 ab

0 a

1 a

0.55 a

1.27 a

TD

3

4

         4 a

6 a

  4 a

6 a

  37.27  ab

   45.08 ab

0 a

0 a

0.00 a

0.00 a

Soler

5

3

   8 ab

5 a

    8 ab

5 a

  105.99  b

   48.71 ab

0 a

0 a

0.00 a

0.00 a

Mean

4.35

3.98

7.58

6.79

7.29

6.59

      56.93

   46.03

0.29

0.20

0.70

0.66

MSD

2.85

3.23

7.38

9.24

7.07

9.27

      74.35

  74.70

2.55

1.09

6.17

3.96

1/ Table 2 does not show data for the UFTP58 genotype, as it is very early compared to the other genotypes.

 

 

Table 3. Averages of the agronomic variables: fruit total weight, fruit length, fruit width, flesh thickness, fresh color and brix, of 22 genotypes of calabaza or pumpkin (Cucurbita moschata Duchesne), evaluated in experimental trials in the Lajas Agricultural Experimental Station from January to April in 2022.

 

 

Genotype

Fruit total weight (lb)

Fruit length (cm)

Fruit width (cm)

Flesh thickness (mm)

Fresh color (1,2,3)

Brix

 

Conventional

Organic

Conventional

Organic

Conventional

Organic

Conventional

Organic

Conventional

Organic

Conventional

Organic

 

UFTP4

  4.89 ab

  2.22 a

  11.30 ab

   9.70 b

  17.33 ab

12.84  a

    31.34 a

   28.44 ab

2   b

2  ab

6.15  a

6.51  a

 

UFTP8

  5.94 abcd

  4.95 abcd

  14.50   bcde

 13.46   cdef

  18.65 ab

15.91 a

    33.95 abc

   32.44 abc

2   b

2  ab

8.69  a

8.24  a

 

UFTP10

  6.31 abcd

  5.36 abcde

  13.96 abcde

 12.91  bcde

   19.61 abc

17.99 a

    40.06 abcd

   33.99 abcd

2   b

3    b

7.66  a

 9.25 a

 

UFTP22

  3.29 a

  4.04 abc

  12.61 abcd

 13.88     def

      15.39 a

72.13 a

    31.80 a

   33.82 abcd

2   b

2  ab

7.85  a

12.57  a

 

UFTP24

  8.02 abcd

  8.74       def

  15.05     cde

 16.58       ef

   20.43 abc

21.83 a

    34.59 abcd

   35.93 abcd

2   b

2  ab

8.44  a

 8.29  a

 

UFTP26

  9.22 abcd

  7.38   bcdef

  15.07     cde

 13.90   cdef

  22.48   bc

20.44 a

    45.90 abcd

   39.03 abcd

2   b

2  ab

8.53  a

 8.10  a

 

UFTP32

  6.18 abcd

  7.77     cdef

  13.78  abcde

 13.88   cdef

18.89 ab

21.34 a

    39.64 abcd

   42.12 abcd

2   b

2  ab

9.14  a

11.21  a

 

UFTP34

 11.40    cd

  9.41         ef

  19.71           f    

 16.42      ef

   21.74 abc

21.40 a

    48.59       d

   47.94       d

 3     c

3    b

9.14  a

11.41  a

 

UFTP36

  7.92 abcd

  8.56       def

  15.48      cde 

 16.67        f

   20.87 abc

21.27 a

    40.72 abcd

   43.59   bcd

2   b

2  ab

9.96  a

  8.07  a

 

UFTP38

  8.85 abcd

10.51           g

  14.66    bcde

 16.50      ef

   22.11 abc

24.84 a

    37.92 abcd

   39.46 abcd

2   b

2  ab

6.31  a

  5.80  a

 

UFTP42

  8.95 abcd

  8.81      def

  14.19    bcde

 14.88    def

   21.72 abc

22.51 a

    43.19 abcd

   40.78 abcd

2   b

2  ab

7.34  a

   7.07 a

 

UFTP44

  7.80 abcd

  8.52      def

  12.24  abc

 12.13  bcd

   22.46   bc

22.62 a

    43.52 abcd

   46.90     cd

2   b

2  ab

8.75  a

 12.00 a

 

UFTP45

  6.67 abcd

  6.79   bcdef

  12.00  abc

 11.93  bcd

   20.16  abc

21.59 a

    36.43 abcd

   38.39 abcd

         1 a

   1  a

5.48  a

  5.58  a

 

UFTP46

  5.22 ab

  4.86 abcd

  14.47   bcde

 12.71  bcd

 17.51 ab

47.42 a

    35.62 abcd

   35.43 abcd

2   b

2  ab

7.53  a 

 8.78  a

 

UFTP47

  8.20 abcd

  7.93     cdef

  14.58   bcde

 13.52   cdef

  20.84 abc

21.67 a

    46.52   bcd

   47.84       d

2   b

2  ab

6.23  a

 6.98  a

 

UFTP57

  6.58 abcd

  4.67  abcd

  16.69         ef

 15.11     def

18.90 ab

16.61 a

    44.49 abcd

   34.54 abcd

2   b

3  b

6.88  a

 5.13  a

 

UFTP80

  9.18 abcd

  5.96  abcdef

  13.44  abcde

 13.18 bcdef

  22.59  bc

18.12 a

    47.23     cd

   40.67 abcd

2   b

3  b

9.37  a

 8.34  a

 

UFTP81

10.37   bcd

  3.67  abc

  15.16      cde

 11.47 bcd

  23.88  bc

16.25 a

    43.42 abcd

   27.43 a

2   b

2  ab

8.66  a

 6.28  a

 

Verde Luz

  5.71 abc

  3.31  ab

  11.82  abc

 10.26  bc

 18.89 ab

15.72 a

    39.73 abcd

   28.69 ab

2   b

2  ab

6.69  a

 8.05  a

 

Fortuna

  4.66 ab

  5.62  abcde

  10.39 a

   5.89 a

 18.47 ab

59.24 a

    32.84 abc

   29.19 ab

2   b

    1 a

7.58  a

 6.48  a

 

TD

  8.46 abcd

  7.29    bcdef

  16.31       def

 14.82     def

   21.75 abc

20.06 a

    43.67 abcd

   41.37 abcd

2   b

 2  ab

6.44  a

 6.88  a

 

Soler

  11.90    d

10.00           f

  15.17      cde

 14.50     def

   26.22     c

23.39 a

    44.93 abcd

   40.68 abcd

2   b

 2  ab

5.70  a

 6.65  a

 

Mean

      7.50

6.65

14.21

13.38

20.50

25.24

40.28

37.67

2.07

2.11

7.66

8.08

 

MSD

      6.04

4.36

3.74

3.67

6.80

82.12

15.07

15.21

0.87

1.25

4.52

8.46

 

1/ Table 3 does not show data for the UFTP58 genotype, as it is very early compared to the other genotypes.

 

 

Table 4. Averages of the variables of sweetness, flavor, texture and overall rating, of 22 genotypes of calabaza or pumpkin (Cucurbita moschata Duchesne), evaluated in experimental trials in the Lajas Agricultural Experimental Station from January to April in 2022.

 

 

Genotype

Sweetness (1-4)

Flavor

Texture (1-4)

Overall rating (1-4)

Conventional

Organic

Conventional

Organic

Conventional

Organic

Conventional

Organic

UFTP4

2

2

2

2

2

2

2

2

UFTP8

3

3

2

2

3

2

2

2

UFTP10

2

2

2

3

2

2

2

3

UFTP22

2

2

2

2

3

2

2

2

UFTP24

2

2

2

2

2

2

2

1

UFTP26

2

2

2

2

2

2

2

2

UFTP32

3

3

3

2

3

3

3

3

UFTP34

3

4

3

4

2

3

2

3

UFTP36

2

3

2

2

3

2

3

2

UFTP38

1

1

1

1

1

1

1

1

UFTP42

2

2

1

2

2

2

1

2

UFTP44

2

2

2

2

2

2

2

2

UFTP45

1

1

1

1

1

2

1

2

UFTP46

1

2

1

2

2

2

2

2

UFTP47

2

2

2

2

3

2

2

2

UFTP57

2

2

2

2

2

2

2

2

UFTP80

3

2

2

2

2

2

3

2

UFTP81

2

1

2

1

2

2

2

1

Verde Luz

2

2

2

2

2

2

2

2

Fortuna

2

2

2

2

2

1

2

2

TD

1

2

1

2

1

2

1

2

Soler

1

1

1

1

1

1

1

1

Mean

1.96

2.00

1.90

1.85

2.03

2.76

1.96

1.91

MSD

1.86

1.45

1.54

1.26

1.72

1.69

1.61

1.45

 

 

Table 5. Yield average of 22 genotypes of calabaza evaluated in experimental trials in the Lajas Agricultural Experimental Station from January to April in 2022.

 
 

Genotype

Yield kg ha -1

 

Conventional

Organic

 

UFTP4

12978.28 a

7527.78  a

 

UFTP8

       45202.46 abcd

28771.67  ab

 

UFTP10

      39291.38 abcd

20307.63  ab

 

UFTP22

  9165.61 a

13572.65  ab

 

UFTP24

      31293.21 abcd

39246.07  ab

 

UFTP26

    28737.24 abc

38837.90  ab

 

UFTP32

      40665.40 abcd

37409.05  ab

 

UFTP34

      69525.56       d

36495.76  ab

 

UFTP36

      46156.08 abcd

40380.90  ab

 

UFTP38

      35582.00 abcd

30149.77  ab

 

UFTP42

      38096.45 abcd

50206.13    b

 

UFTP44

      44914.18 abcd

45708.03  ab

 

UFTP45

      32575.57 abcd

47286.83    b

 

UFTP46

4189.22 a

18811.44  ab

 

UFTP47

     32600.64 abcd

43091.81 ab

 

UFTP57

  22370.41 ab

17803.91  ab

 

UFTP80

     63974.03    cd

27854.29  ab

 

UFTP81

     42512.84 abcd

13971.31  ab

 

Verde Luz

   25387.26  abc

10933.02  ab

 

Fortuna

                         15041.97  a

13560.57  ab

 

T. Dorada

   29217.90  abc

32700.46  ab

 

Soler

     60748.58    bcd

37779.33  ab

 

Mean

                            35,464.83

               29,654.83

 

LSD

40,011.00

               39,496.00

 

Activity 3: Performance of calabaza germplasm in Alabama

Weather conditions were optimum for crop production, trials in the conventional and organic site had no to a very low disease pressure. Only few plants were scouted with powdery mildew. Weed pressure was high under the organic trial, but weeds not measured at the conventional trial (Fig. 1). In general, fruit weight was higher for the conventional trial compared to organic trial. However, both trials and the grower trial achieve desired yields. Varieties under the breeding program performed better than commercial cultivars, indicating better adaptability to Alabama environmental conditions (Table 1 and 2). Nevertheless, commercial cultivars had a better performance in the sensorial evaluation compared to varieties under the breeding program (Table 3 and 4).

Figure 1. Conventional (left) and organic (right) trials.

Figure 1. Conventional (left) and organic (right) trials.

Table 1. Cultivar main effect on fruit weight, fruit length, fruit width, flesh thickness, brix, and flash color in the conventional trial.

Table 1. Cultivar main effect on fruit weight, fruit length, fruit width, flesh thickness, brix, and flash color in the conventional trial.

Table 2. Cultivar main effect on fruit weight, fruit length, fruit width, flesh thickness, brix, and flash color in the organic trial.

Table 2. Cultivar main effect on fruit weight, fruit length, fruit width, flesh thickness, brix, and flash color in the organic trial.

Table 3. Cultivar main effect on sweetness, flavor, texture, and overall rating in the conventional trial.

Table 3. Cultivar main effect on sweetness, flavor, texture, and overall rating in the conventional trial.

Table 4. Cultivar main effect on sweetness, flavor, texture, and overall rating in the organic trial.

Table 4. Cultivar main effect on sweetness, flavor, texture, and overall rating in the conventional trial.

Objective 4: Develop cropping systems for sustainable organic and conventional specialty pumpkin production.

Team: Carlene Chase and Gabriel Maltais-Landry; postdoctoral associates – Parmeshwor Aryal and Daniel Boakye

Activity 1: Evaluation of spring-planted specialty pumpkin germplasm lines with roller-crimped rye mulch

UFTP46-Inc had the highest marketable fruit yield (10,092 kg/ha) but was not significantly different from UFTP46-PM (6646 kg/ha) and UFTP38 (6161 kg/ha). There was no difference in yield among the germplasm lines grown with the roller-crimped rye mulch. No yield was obtained with UFTP22 and Fortuna UPR. The average fruit diameter ranged from 3.3 cm to 15.1 cm and flesh thickness ranged from 0.3 cm to 3 cm. Although significant differences among treatments were observed for days to male flowering, the difference in days to female flowering was not significant. Weed suppression was not as effective with the rye mulch as expected. Roller-crimping terminated the rye but did not kill emerged weeds. The emerged and germinating weeds were likely the min contributor to the lack of flowering and yield at Live Oak and relatively poor yields at Citra. It is possible that a rye cultivar that produces greater shoot biomass may be more effective at suppressing weed growth during the cover crop period and thus also provide a greater volume of residue for weed suppression during the cash crop.

The rye biomass was very low at both locations in spring 2022 (< 1000 kg ha-1 of dry biomass), several fold lower than in 2021, but it had a higher N concentration and lower C:N ratio in 2022 vs. 2021. This difference in biomass accumulation impacted how treatments affected soil properties. In 2021, there was greater N release when rye was incorporated vs. roller-crimped, but there was no effect of treatments in 2022. There were few differences in POXC among systems in 2022, and somewhat contradicting effects of cover crop termination treatments between locations in 2021. Results from 2021 suggest that cover crop termination method could impact both C and N cycling in these systems, but results from 2022 highlight that a minimum amount of biomass production is likely required to generate quantifiable effects.

 

Activity 2: Evaluation of fall-planted specialty pumpkin germplasm lines with roller-crimped sorghum-sudangrass mulch

The most common weedy plants were broadleaf weeds (53%), nutsedge (19.6%) and SSG volunteers (26.8%). Two-thirds of the pumpkin lines had says to first male and female flowers between 35 to 45 DAT while the remaining lines flowered later or not at all. All but one of the late flowering lines was germplasm of Puerto Rican origin. Although, the fruits were harvested at the immature stage, significant differences in yield were obtained. The highest yield was obtained with UFTP46-PM; however, this was not significantly different from the two other UFTP46 treatments, UFTP38, and UFTP42. Fortuna UPR produced the lowest yield of the lines that produced fruit. UFTP47 produced no flowers and no fruit, whereas UFTP45 produced male flowers at 55 DAT and female flowers at 53 DAT but also produced no fruits.

 

 

Objective 5 Monitor arthropod pests and beneficial insects in specialty pumpkin to design cultural and biological control tactics for organic and conventional systems.

Team: Oscar Liburd; 

Activity 1: Effect of variety on insect pest complex of calabaza

Insect pests in the spring included aphids, flower thrips, and squash bugs. Beneficial arthropods collected included minute pirate bugs, which prey on thrips, spider, lady beetles, rove beetles, and parasitoid wasps. In the spring, thrips numbers were much lower. Aphids were collected and whiteflies were a major pest. UFTP58, Verde Luz, and Waltham Butternut had low silverleaf ratings throughout the season while UFPT42 and UFPT45 had high ratings even after treatment for whiteflies. The other tested varieties recovered after treatment. Beneficial insects seen in the fall were similar to those seen in the spring. There were no differences in pest or beneficial numbers among varieties. 

Activity 2: Effect of mulch type on insect pest complex of calabaza

A single cultivar of calabaza, UFPT46, was grown using 3 different mulch types: cover crop residue (control), cover crop residue incorporated into raised beds, and raised beds with black plastic mulch. The cover crop in the spring was rye while the cover crop in the fall was sorghum sudan grass. From 20 Apr 2022 through 15 June 2022, yellow sticky traps, clear pan traps, and in situ counts were used to monitor for insect pests at both the UF Plant Science Research and Education Unit and the UF Live Oak research station. During the fall season, the same sampling techniques, except for pan traps, were deployed from 3 Nov to 8 Dec 2022 at the UF PSREU. In situ counts were conducted as detailed above. Pan traps were filled with soapy water, which was changed weekly. Yellow sticky traps were deployed in each plot and collected after 48 h every other week in the spring and weekly in the fall. Weekly squash silverleaf ratings were also conducted in the fall as detailed above.

 

Participation Summary

Educational & Outreach Activities

2 Consultations
1 Curricula, factsheets or educational tools
1 Journal articles
2 Online trainings
10 Tours
19 Webinars / talks / presentations

Participation Summary:

6 Farmers participated
Education/outreach description:

Carlene lab

  • Results were presented at the Southern Weed Science Society meeting and the TriScocieties meeting in 2021.
  • Maltais-Landry, G., A. Schmidt, P. Aryal, C.A. Chase, and G. Meru. 2022. Comparing How Termination Practices of a Winter Rye Cover Crop Affect Nitrogen Release and Permanganate-Oxidizable Carbon. Oral presentation, ASA-SSSA-CSSA International Annual Meeting, Baltimore (MD) – Nov. 2022.
  • Aryal, P., S. Willis, G. Maltais-Landry, G. Meru, and A. Chase. 2022. Evaluation of specialty pumpkin germplasm lines in a reduced tillage organic cropping system in Florida (abstr). HortScience 57(9):S48-49. Oral presentation at the American Society for Horticultural Science Annual Meeting, Chicago (IL) – Aug. 2022

Meru lab

  • Meru G. 2021: Grower education efforts through lectures (n = 2) in Miami-Dade county and Hernando County
  • Meru G. Online resource PowerPoint June 4, 2021 (126 views so far): This video provides information on growing calabaza pumpkin for home gardeners. https://www.youtube.com/watch?v=WNZ0EZRQNEk
  • Meru G. UF/IFAS Southeast Extension District (SEED): Feb & Oct 2021
  • Meru G. Squash Breeding and Genetics: Building Blocks for Success in a Genomics Era. Michigan State University. March 26, 2023.
  • Meru G. Advancing the Cucurbit industry through a genomics-enabled breeding and extension program. University of Florida. August 2022.
  • Prerna., S. Meru, G. et al. 2022. Yield and Horticultural Traits of Tropical Pumpkin in Florida. Cucurbitaceae 2022, Naples FL.
  • Prerna., S. Meru, G. et al. 2023. Yield and Horticultural Traits of Tropical Pumpkin in Florida. University of Florida/ TREC Seminar Series 2023. 
  • Prerna., S. Meru, G. et al. 2023. FSHS 2023 (June)- Evaluation of Tropical Pumpkin for Yield and Horticultural Traits in Florida

Andre lab

  • da Silva, A.L.B.R. Vegetable cultivar selection for Alabama. In Alabama Fruit and Vegetable Growers Association Conference 2023. Gulf Shores, USA.
  • da Silva, A.L.B.R. Pumpkin Varieties for Alabama. In Alabama Fruit and Vegetable Growers Association Conference 2023. Gulf Shores, USA.
  • da Silva, A.L.B.R., 2023. Variety Selection and Disease Management. Jackson County Meeting. (25 attendees)
  • da Silva, A.L.B.R., J. Kelley. 2022. Best management practices for vegetable production in Alabama. In Poarch Creek Field Day / Commercial Horticulture Team – Alabama Cooperative Extension System (9 attendees).
  • da Silva, A.L.B.R. and N. Kelly. 2022. Identifying challenges of vegetable production in southeastern Alabama. Dale County meeting / Commercial Horticulture Team – Alabama Cooperative Extension System (8 attendees).
  • Dorminey, A., L.B.R. da Silva, 2022. Organic transition for vegetable production. In Alabama Vegetable Crops Field Day from the Commercial Horticulture Team – Alabama Cooperative Extension System (89 attendees).

Andrew Lab

Talks/ scientific and extension presentations:

  • Kinsman, M., Simonne, A., Sargent S., Meru G., Chase A.A., MacIntosh A.J. (2023) Determination of Select Macronutrients and Bioactive Compounds Present in Winter Squash Utilizing Tristimulus Colorimetry. IFT FIRST Annual Event & Expo 2023.
  • Kinsman, M., Simonne, A., Sargent S., Meru G., Chase A.A., MacIntosh A.J. (2023) Key Quality Component and Bioactive Compound Analysis of Novel Calabaza Germplasm Lines. FSHS 2023 Annual Conference

Publications  

  • Skylar R Moreno, Masoud Yazdanpanah, Tianyi Huang, Charles A Sims, Carlene A Chase, Geoffrey Meru, Amarat Simonne, Andrew J MacIntosh (2023) Comparative Analysis of Qualitative Attributes for Selection of Calabaza Genotypes in the Southeast United States. Horticulturae 9(3): 409

Angela Lab

Publications  

  • Sarmiento, L. y A.M. Linares Ramírez. 2022. Evaluación de Genotipos de Calabaza en Sistemas de Producción Orgánica y Convencional en Lajas, Puerto Rico. 44a Reunión Científica Anual de la Sociedad Puertorriqueña de Ciencias Agrícolas. Coamo, PR

Learning Outcomes

2 Farmers reported changes in knowledge, attitudes, skills and/or awareness as a result of their participation

Project Outcomes

Project outcomes:

Growers have demonstrated interest in growing calabaza as evidenced by seed requests to our program. To-date more than 75 seed packets of calabaza have been distributed to growers.  Two local growers in south Florida have tested a few of the breeding lines at their farms at small scale and have sold their produce profitably (no empirical data available at this point). On-farm trials with grower cooperators later this year (2023) will provide a better understanding of the viability of calabaza production under both conventional and organic systems.

In both the Spring and the Fall, the cover crop used for generating the residue needed for weed suppression was not as effective as was intended and weed infestation was a major problem in both seasons and volunteer tillering of the SSG was an additional problem in Fall. Additionally, the December freeze abruptly ended the Fall trial. Therefore, utilizing a rye cultivar that produces greater biomass and better weed suppression will be explored in future work. Planting the Fall trial by late August will allow for adequate time to evaluate these pumpkin lines during fall prior to occurrence of a frost or freeze incident. Pearl millet will be evaluated as an alternative to SSG to allow for more effective termination with the roller-crimper. Avoiding use of a tilled strip for addition of fertilizer and placement of drip tape should also be avoided to limit the germination of weeds during transplant establishment.

Information Products

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.