Analyzing Early Growth Characteristics and Anchorage Force to Improve Cultivation Tolerance in Carrots

Progress report for GNE19-194

Project Type: Graduate Student
Funds awarded in 2019: $14,683.00
Projected End Date: 10/31/2022
Grant Recipient: University of Maine
Region: Northeast
State: Maine
Graduate Student:
Faculty Advisor:
Dr. Eric Gallandt
University of Maine
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Project Information

Project Objectives:
  1. Examine selected carrot cultivar early growth characteristics in the greenhouse and lab, including shoot height, shoot and root area, root to shoot area ratio, root branching, and shoot and root dry weights using a previously purchased WinRHIZO™ program (Regent Instruments, Québec, Canada).
  2. Determine carrot cultivar root anchorage force in the lab using a previously purchased Alluris® FMI-B150 Force Gauge.
  3. Assess carrot cultivar tolerance to mechanical cultivation by examining crop injury pre- and post-cultivation after use of either finger weeders, tine harrows, or hand-weeding with a stirrup hoe. 
  4. Compare carrot yields across tool treatments and compare to a hand-weeded control treatment.
  5. Perform correlation analyses between carrot early growth characteristics and field experiment results to determine “cultivation tolerance” and determine which growth traits may aid in cultivation tolerance.
Introduction:

The purpose of this project is to help identify early growth traits of carrot cultivars that make them more tolerant to mechanical cultivation. Organic vegetable production in the Northeast is growing, but small-seeded crops such as carrot often suffer significant yield and quality losses to weeds and mechanical cultivation because their slow early season growth and size make them less competitive and more prone to injury. Growth characteristics that may help a carrot better tolerate cultivation could help direct future plant breeding efforts and help organic vegetable farmers make more informed cultivar and tool selections. 

Cooperators

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Research

Materials and methods:

Seven popular commercial carrot cultivars were selected for early growth characteristic screening in 2019 to determine which cultivars and variables to assess in subsequent studies. Nine cultivars were selected in 2020 based on their known root and shoot growth to represent a range of carrot growth characteristics. Cultivars were arranged in the greenhouse in a factorial randomized block design with six replications. Each carrot cultivar had four growth stages tested: seed weight, and one, two, and four true leaves. Average seed weight was determined for each cultivar prior to sowing by weighing three samples each of 100 seeds. Root anchorage force, root and shoot biomass, and other selected root and shoot growth parameters were measured at each stage (Obj. 1-2). For each of the true leaf growth stages two carrots were seeded, one for anchorage force testing and one for analyzing the growth characteristics. Seeds were sown to a depth of 0.63 cm in ConeTainers (Stuewe & Sons, Inc., Tangent, OR) filled with coarse pool sand media using a dibble and watered as necessary. Cones were fertilized three times per week using Peter’s Professional 20-20-20 general purpose fertilizer to ensure growth in the sand media. Cone location in a tray was randomly selected for each cultivar and growth stage and labeled appropriately.

Carrot cultivar tolerance to physical weed control was assessed in a field trial with a factorial arrangement of six cultivars and three physical weed control treatments using a completely random design with four replications (Obj.3-4). Physical weed control treatments consisted of cultivation at two-true leaves with finger weeders or tine harrows, and a hand-weeded control using a stirrup hoe. Plots measured 3.0 m long by 0.5 m wide with two rows of carrots on 50 cm rows sown at a depth of 0.63 cm. Beds were formed using a cultipacker and carrots were sown using a Jang six-row tractor-mounted seeder using recommended seed rollers and calibrations. Beds were flame weeded six days after planting to minimize weed densities ahead of carrot emergence. 

 

Objective 1. Examine selected carrot cultivar early growth characteristics in the greenhouse and lab, including shoot height, shoot and root area, root to shoot area ratio, root branching, and shoot and root dry weights.

As true leaf growth stages were reached, plant shoot height (cm) was recorded and plants were destructively harvested, carefully washed, and placed in a tray for scanning using the WinRHIZO™ system (Regent Instruments, Québec, Canada) to quantify root and shoot area. Roots and shoots were separated, dried at 65ºC for at least three days in a lab drying oven, and weighed to determine dry root and shoot biomass. Root and shoot area data were pulled from WinRHIZO-generated scan files for analysis.  

 

Objective 2. Determine carrot cultivar root anchorage force.

Additional plants were subjected to anchorage force testing using an Alluris® FMI-B150 Force Gauge. Plants were attached at the soil level to the force gauge hook using a metal clip and pulled straight up at a constant speed until all roots had been removed from the soil or the plant stem broke off from the roots. The maximum and average force (Newtons) required to remove a plant from the soil were recorded and data was pulled from the Alluris-generated Excel files for analysis.  

 

Objective 3. Assess carrot cultivar tolerance to cultivation events by examining crop injury pre- and post-cultivation. 

We measured crop mortality from cultivation with either finger weeders or tine harrows by recording the number of carrots pre- and post-cultivation in each of the two rows per plot. Post-cultivation data collection was performed approximately 24 hours after cultivation to ensure desiccation. Crop density was also recorded for hand-weeded treatments to determine if hand-weeding resulted in any crop mortality.

 

Objective 4. Compare carrot yields across tool treatments and compare to a hand-weeded control treatment.

Carrots were harvested by hand digging all carrots in each row. Carrots were removed from the soil using broad forks, dunked in two buckets of water to remove soil, and brought to the farm lab for processing. Carrots were divided into ‘marketable’ versus ‘unmarketable’ (very small or having major defects). Within each category, the number of carrots was recorded, as well as total fresh weight in grams. Carrot tops were removed using garden clippers, and carrot root fresh weight was recorded (grams). Carrot yields were analyzed in JMP 16 Pro and contrasts used to compare cultivated treatments to a hand-weeded control treatment to determine any differences.

 

Objective 5. Determine whether carrot early growth characteristics are related to “cultivation tolerance” and determine which growth traits may aid in cultivation tolerance.

Using JMP 16 Pro, early growth data including root and shoot biomass, root and shoot area, and shoot height were correlated with crop mortality and carrot yield data from the field trial. This analysis was used to determine if meaningful relationships exist between root and shoot morphology and crop mortality from mechanical cultivation. Based on this analysis, a “cultivation tolerance” table will be developed to help inform plant breeders and farmers about cultivar tolerances to physical weed control.

Research results and discussion:

The greenhouse trial was completed from June-September, and the field trial from July to October. Results to date are presented below, and final results are expected to be published in fall 2022. Below are tables and figures of data that has been summarized to date. Pictures from this year are also attached for reference.

 

Obj. 1-2-

Table 1. Greenhouse Trial Analysis of Variance results at α = 0.05. Year and block were included as random effects.

Source 

Shoot Ht 

Shoot Area 

Shoot Mass 

Root Area 

Root Mass 

Root:Shoot 

Tips

Forks

Max AF 

Avg AF

 

----------------------p-value----------------------

Cultivar (C) 

<0.0001

0.0001

0.001

0.0003

<0.0001

0.251

<0.0001

<0.0001

0.810

<0.0001

Growth Stage (G) 

<0.0001

<0.0001

<0.0001

<0.0001

<0.0001

0.040

<0.0001

<0.0001

0.997

<0.0001

Year (Y) 

0.520

0.617

0.514

0.502

0.604

0.495

0.916

0.736

0.331

0.078

C x G 

0.134

0.369

0.005

0.273

<0.0001

0.261

<0.0001

<0.0001

0.850

0.006

Y x C

0.018

0.116

0.146

0.018

0.032

0.558

0.069

0.024

0.796

0.028

Y x G

0.886

0.151

0.0001

0.004

<0.0001

<0.0001

<0.0001

<0.0001

0.996

0.114

Y x C x G

0.272

0.066

0.170

0.100

0.071

0.252

0.013

0.018

0.841

0.097

Block 

0.461

0.312

0.658

0.646

0.633

0.554

0.810

0.692

0.988

0.320

Figure 1. Mean root area (cm2) by cultivar, separated by a) one true leaf, b) two true leaves, and c) four true leaves. Data is pooled across years. Error bars represent standard error of the mean. Different letters indicate significant differences at α=0.05.

Figure 2. Mean shoot area (cm2) by cultivar, separated by a) one true leaf, b) two true leaves, and c) four true leaves. Data is pooled across years. Error bars represent standard error of the mean. Different letters indicate significant differences at α=0.05.

 

 

 

 

Obj. 3-5-

 

Table 2. Field trial Analysis of Variance results at α = 0.05. Year was included as random effect.

Source

Crop Mortality (%)

Hand Weeding Time (h ha-1)

Marketable Total Fresh Wt. (kg ha-1)

Marketable Root Weight (kg ha-1)

Unmarketable Total Fresh Wt. (kg ha-1)

Unmarketable Root Weight (kg ha-1)

 

-------------------- p-value --------------------

Cultivar (C)

0.995

0.352

<0.0001

<0.0001

0.113

0.006

Weed Treatment (T)

<0.0001

<0.0001

0.136

0.067

0.954

0.967

Year (Y)

<0.0001

0.532

0.731

0.594

<0.0001

<0.0001

C x T

0.287

0.493

0.672

0.322

0.884

0.706

Y x C

0.983

0.041

0.064

0.002

0.004

0.107

Y x T

0.009

0.388

0.667

0.137

0.428

0.681

Y x C x T

0.005

0.182

0.789

0.484

0.202

0.326

 

 

Table 3. Mean (±SE) crop mortality by cultivar and weed treatment in 2020. Different letters indicate significant differences at α=0.05.

 

Crop Mortality

Cultivar

Hand-Weeding

Finger Weeder 

Tine Harrow 

 

                                       ---------------%---------------

Bolero

-

3.77±2.38

16.70±4.23

Yellowstone

-

11.12±3.53

36.28±4.80

Dragon

-

13.62±3.12

20.17±3.11

SFF

-

  8.78±0.94

12.80±2.54

NB1

-

  7.05±1.40

18.37±2.01

NB2

-

  10.25±0.790

24.16±7.12

 

 

Table 4. Mean (±SE) crop mortality by cultivar and weed treatment in 2021. Different letters indicate significant differences at α=0.05.

 

Crop Mortality

Cultivar

Hand-Weeding

Finger Weeder

Tine Harrow

 

                                       ---------------%---------------

Bolero

-

10.57±3.24

7.22±3.46

Yellowstone

-

  8.43±0.84

6.01±1.10

Dragon

-

14.43±4.89

13.21±3.61

SFF

-

  9.20±3.62

12.08±1.06

NB1

-

  9.87±2.05

10.49±4.82

NB2

-

10.74±2.53

  7.62±1.73

 

Table 5. Mean (±SE) marketable versus unmarketable crop yield in 2020. Data is averaged across weed treatments. Different letters represent significant differences at α=0.05.

Cultivar

Marketable Total Fresh Wt.

Marketable Root Fresh Wt.

Unmarketable Total Fresh Wt.

Unmarketable Root Fresh Wt.

 

------------------kg ha-1------------------

Bolero

17432±1603 b

13249±1235 ab

1486±225

1019±148

Yellowstone

15500±1881 bc

8987±1075 c

2473±470

1356±274

Dragon

25005±1960 a

17370±1342 a

2796±349

1853±242

SFF

11631±1264 bc

    9507±1036 bc

2786±505

2237±410

NB1

   11242±751 c

  9109±623 bc

1777±221

1384±176

NB2

     4892±429 d

3752±338 d

2452±320

1841±249

 

 

 

 

 

 

 

 

Table 6. Mean (±SE) marketable versus unmarketable crop yield in 2021. Data is averaged across weed treatments. Different letters represent significant differences between cultivars at α=0.05.

Cultivar

Marketable Total Fresh Wt.

Marketable Root Fresh Wt.

Unmarketable Total Fresh Wt.

Unmarketable Root Fresh Wt.

 

------------------kg ha-1-----------------

Bolero

9983±1460

5990±807

2013±324 b

1150±160 c

Yellowstone

    14660±961

8089±549

  2974±333 ab

1197±146 c

Dragon

15597±2122

  8731±1114

3192±432 a

  1586±208 bc

SFF

12823±1447

8799±834

3227±379 a

2162±237 a

NB1

10447±1566

6980±903

3117±349 a

  2085±220 ab

NB2

11435±1945

  7111±1124

2080±250 b

1238±143 c

 

 

Figure 3. Mean (±SE) total hand-weeding labor to achieve weed-free conditions for each weed control treatment. All treatments were hand weeded at one true leaf. Finger weeder and tine harrow treatments were hand weeded once 14 days after cultivation. The hand-weeding only treatment was weeded every 14 days for a total of three times after the initial hand weeding event. Data is pooled across years. Different letters represent significant differences at α=0.05.

 

 

Summary points-

Greenhouse (Obj. 1-2)-

  • No cultivar differences detected at first true leaf, but cultivars diverge in growth allocation thereafter.
  • “Top” category appears to put more growth allocation into shoot height after first true leaf.
  • Once fourth true leaf is reached, Bolero has greatest root and shoot area and mass.
  • “Bottom” category has lowest shoot and root area and mass at four true leaves- these cultivars tend to have slower emergence and put resources into roots and shoots equally.
  • Interestingly, red core Chantenay, which is considered to be in the “top” category, had lower root and shoot area and biomass in 2021. Regression tree analysis showed this cultivar to be similar to those in the “bottom” category. Growing conditions were similar from year to year, and germination test results were similar as well, suggesting that there may be other factors influencing the growth of this cultivar such as root and shoot width or tensile strength.
  • Root area has moderate correlation with average anchorage force, but not maximum anchorage force, suggesting that root morphology does play a role in anchorage force but the maximum force is also a factor of other variables (growing media, moisture, time of day?).

 

Field (Obj. 3-5)-

  • “Top” category prioritizes shoot growth first, but this resulted in greater crop mortality from tine harrows in 2020, which have more contact with carrot tops than finger weeders.
  • Finger weeders and tine harrows showed similar crop mortality in 2021 and lower overall mortality compared to 2020. The significant p-value in the model was due to differences in crop mortality between the hand-weeded control treatment versus the finger and tine harrow treatments, which was expected.
  • In 2021, 14-day post-cultivation biomass was analyzed to see if injury carried into final yield. Root biomass 14 d post cultivation was significantly different for cultivar but not weed treatment or their interaction. Shoot biomass was non-significant across model parameters.
  • Marketable yield was different between cultivars in 2020 but non-significant in 2021, indicating that carrots may likely be recovering from any root injury during cultivation that lowered 14 d root biomass.
  • Marketable total crop fresh weight graphs show a general trend of yields being similar across weeding treatments, but tine harrowing may have the ability to reduce yield in cultivars which prioritize shoot growth early in the season while cultivars that put resources equally into root and shoot growth may be able to recover well after damage from PWC.
  • Total hand weeding time (hours/acre) is higher for the hand-weeding control group, as expected, while hand weeding time is lower for the tine harrow treatment. The tine harrow is likely killing more weeds but comes with the tradeoff of greater crop loss.
  • Correlations performed to explore relationships between field and greenhouse data. Greenhouse root and shoot data have weak (<0.40) or negative correlations with crop mortality, hand weeding time, and marketable and unmarketable crop yield. This is similar in both years, suggesting that a multitude of factors contribute to field results where the environment is not as controlled as a greenhouse setting.

 

Pictures-

Participation Summary

Project Outcomes

Knowledge Gained:

Data collection began for this project in July 2020. During the duration of the experiment and data collection, my knowledge about carrot production and my skills in their production drastically changed. It is one thing to read literature and talk to farmers about their experience growing carrots, it is another thing to be the one in charge of every aspect of the production. I was in charge of everything from purchasing seed, to bed prep, planting, weeding, irrigating, and harvesting. I now have a much greater appreciation for the work that goes into growing carrots, and this further reinforces why the need for this research is so important for organic farmers. 

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.