Evaluating functional diversity in an organic intercropping system

Final Report for GS11-108

Project Type: Graduate Student
Funds awarded in 2011: $10,000.00
Projected End Date: 12/31/2013
Grant Recipient: Texas A&M University
Region: Southern
State: Texas
Graduate Student:
Major Professor:
Dr. Astrid Volder
Texas A&M University
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Project Information


An incremental increase in functional crop diversity in an organic intercropping system has the potential of improving crop yield on a per acre basis. Land equivalent ratio data from year 2 of the study suggests there is an overall increase in productivity when incorporating a more complex intercropping combination using 3 or 4 functionally diverse species. Productivity on a per plant basis was also increased in some crops but was dependent upon planting date and competitive interactions with neighboring species. Additionally, weed dry biomass was significantly reduced and fruit quality does not appear to be adversely affected by multicropping treatments.


Intercropping is an agricultural practice that promotes biological interactions and diversifies crop production in order to introduce biodiversity into agroecosystems (Mohler and Stoner 2009). Biodiversity has evolved in order to fill the multiplicity of niches that exist in the worlds ecosystems (Koocheki et al. 2008) and, in turn, provides the foundations for nutrient cycling efficiency and natural pest and disease control (Altieri 1999) and counteracts the deterioration of genetic resources that have been found in many field crops by increasing the gene pool (Baudry 1989).
Some researchers have emphasized the importance of functional differences between species and the relationship between species in space and time rather than species richness per se on improving ecosystem functioning (Landis et al. 2000). Snapp et al. (2010) suggested that management strategies and intensity are responsible for enhancing soil health, not biodiversity. However, their study did not incorporate the concept of functional diversity, but only the number of species present. Thus, we proposed to choose crop species that add a specific function to the community, such as nitrogen fixation, pollinator attractant, herbivore repellant etc.

Small farmers in tropical forest areas have long utilized intercropping systems and have incorporated a variety of crops with different growth forms, which creates a complex multi-layered habitat that closely mimics nature (Denevan 1995). In agroforestry systems of the tropics, it has been observed that deep-rooted trees bring nutrients up from deeper soil layers, thereby increasing nutrient use efficiency and reducing leachate (van Noordwijk et al. 1996). The “three sisters” intercropping system of squash, bean and corn practiced by the Native Americans is another well documented example of a multi-layered agroecosystem (Mohler and Stoner 2009). In these types of systems, each crop occupies a functional group niche and contributes in a different way to the overall functioning of the ecosystem (Vitousek and Hooper 1993). In the case of the “three sisters”, squash suppresses weed growth (smother crop), bean as the nitrogen-fixer, and corn as structural support (Mohler and Stoner 2009).
Despite the rising popularity of intercropping in developed countries (Kahn 2010), multi-layer architecturally complex intercropping systems have not been studied extensively in the Southern United States. There are few studies that have quantitatively evaluated the role of functional diversity on ecosystem functioning, pest resistance and suppression, and yields in intercropping systems. We proposed to quantify and mechanistically explain the effects of a functionally diverse crop community on regulating pests, soil health, and on resource-use efficiency and plant productivity.

Project Objectives:

1. To evaluate the effectiveness of intercropping systems on sustaining or enhancing crop yield and quality
2. To determine how incremental increases in functional diversity affect weed suppression and disease incidence and severity


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  • Jose Franco


Materials and methods:

Experimental Design
In order to evaluate the relationship between plant functional diversity and crop yields, a plot-scale experiment was conducted on an approximately 0.1ha area on the Texas A&M University Horticulture Farm in 2011 and 2012. The study consisted of a randomized complete block design with 3 replicates. There were a total of 5 intercropping treatments and 5 controls. The controls were monocultures of five species; peanut (Arachis hypogaea L.), mini watermelon (Citrullus lanatus Thunb.), okra (Abelmoschus esculentus Moench.), hot pepper (Capsicum spp.), and cowpea (Vigna unguiculata L.). The 5 intercropping treatments were: a within-row intercropping system of peanut and watermelon (Ipw), a within-row intercropping system of peanut, watermelon, and okra (Ipwo), a within-row intercropping system of peanut, watermelon, okra, and cowpea (Ipwoc), a within-row intercropping system with all 5 control species (Iall), and a strip intercropping system of peanut and watermelon consisting of alternating single rows (Spw). Crops represented 4 different genera and were selected based on the following criteria: 1) heat tolerance, 2) desired architecture and functions, and 3) no known adverse effects on other component crops. The Texas A&M University (TAMU) mini watermelon was developed by the watermelon breeding program and was selected for its ability to tolerate tight spacing.

Plots measured 5 x 4m in area and crops were planted in 4m long double rows on 90cm wide raised beds with rows spaced approximately 30cm apart and beds spaced 45cm apart. Densities were kept constant across plots regardless of crop species and individual plants were spaced 30cm apart in a staggered row pattern so that each plant was neighbored by a plant of a different species and a legume crop. Spacing was based on the mean spacing requirement for all component crops. A 2m buffer was maintained between plots. Due to over-competition by watermelon in year 1, planting dates were altered in year 2.

Year 1
In year 1, a chisel plow and middle buster were used to prepare the field in May 2011. The field was then irrigated and solarized for 1.5 months with clear greenhouse plastic to reduce weed pressure. Upon removal of plastic, a row-maker was utilized to make 3 1.5m long rows per replicate for a total of 9 rows. Drip tape was installed down the center of each row during the row-making process.

Peanut was direct seeded on August 1, 2011 and watermelon was direct seeded approximately one week later on August 7th. Okra and cowpea were direct seeded on August 14 and 15th, respectively. Three inch tall pepper plants were transplanted on August 18th. Peanut and cowpea were inoculated with Rhizobium during planting. Re-seeding continued through the end of August.

Year 2
In year 2, a chisel plow and middle buster were used to prepare the field in April 2012. Clear greenhouse plastic was laid on the field the second week of May for one month. A row-maker was then used to make 4 1.5m long planting rows per replicate for a total of 12 rows. Drip tape was installed down the center of each row during the row-making process. Due to low nutrient levels at the onset of year 2, rows were top dressed with 240lbs of chicken manure-based organic granular fertilizer (4-2-3) in mid-June (pre-planting).

Peanut and okra were direct seeded on June 21 and 22, 2012, respectively. Cowpea was direct seeded approximately one week later on June 27th. Peanut and cowpea were again inoculated with Rhizobium. Three-inch tall pepper plants were transplanted on July 3rd. Watermelon was direct seeded on July 12th. Re-seeding of peanut, okra, cowpea, watermelon, and pepper transplant replacements continued through the last week of July.

Objective 1: Fruit Yield and Quality
Crops were harvested as fruits matured throughout the growing season. Yields were then expressed per unit area and then used to compute Land Equivalent Ratio (LER), where the intercrop yield for each component crop was divided by the monocrop yield for that crop and then summed across all crops. An LER greater than 1 indicates a combined increase in yield compared to growing each component crop in monoculture, an LER below 1 indicates a combined decrease in yield compared to growing each component crop in monoculture. Quality measurements for watermelon included brix, rind thickness, weight, and flesh firmness. For okra and pepper quality measurements, individual fruit weight normalized based on fruit size and wall thickness measurements were collected. Pods per plant, peas per pod and 100ct weight were utilized as quality measures for cowpea. Peanut quality was only evaluated based on pods per plant and 100ct. Production was also calculated on a per plant basis in order to evaluate changes in individual plant production based on intercropping strategy.
Objective 2: Weed and Disease Suppression
Treatment effects on weed suppression were assessed by hand collecting above-ground weed biomass on a weekly basis through the end of harvest. Samples were oven-dried in order to calculate total dry weed biomass per plot.

Experimental plots were monitored for disease throughout the growing season. Disease occurrence was verified with the Texas Plant Disease Diagnostic Laboratory (TPDDL). Incidence was measured as the presence or absence of disease on each plant within each plot. Severity was expressed as the percentage of foliage per plant showing signs of disease.

Research results and discussion:

Objective 1: Fruit Yield and Quality
Due to late planting, peanut plants were not harvested in 2011. Therefore Land Equivalent Ratio’s (LER) were all below one, indicating a net decrease in per area production. However, ratios were as high as 0.87 and would have likely been well over 1 with peanut (Appendix Fig. 1). In 2012, LER’s were highest in the Ipwo and Ipwoc intercropping combinations at 1.17 and 1.20, respectively. LER was also above 1 when peanut and watermelon were strip intercropped, suggesting a complex within-row intercropping system with only watermelon and peanut may not be necessary to achieve maximum total yields on a per unit land area basis. In 2011, watermelon grew vigorously and, therefore, contributed the most to LER. However, in 2012, with the altered planting dates, okra outcompeted watermelon and contributed significantly to LER in those cropping combinations incorporating okra.

In 2011, watermelon production on a per plant basis was significantly improved in the more complex intercropping combinations of Ipwo, Ipwoc and Ipwocr at 3.7, 5.1 and 5.5 kg/plant respectively, compared to 2.1 kg/plant in monoculture (Appendix Fig. 2). Due to competition from okra and issues with downy mildew in 2012, however, production per plant dropped significantly across all treatments but was lowest at those same treatment combinations, 0.3, 0.2 and 0.3 kg/plant respectively compared to 0.9 k/plant in monoculture. We see a similar but reversed pattern in okra from 2011 to 2012. Okra production per plant was quite low in 2011 as it was outcompeted by watermelon with no significant differences between treatments. However in 2012 when okra seemed to have an advantage over watermelon in terms of planting date, production per plant increased overall but was significantly greater in the Ipwo, Ipwoc and Ipwocr treatments at 1.7, 2.5 and 2.3kg/plant respectively. These were all significantly greater than the okra monocrop which yielded 1.1 kg/plant. Cowpea had a reduction in per plant production in both 2011and 2012 in intercropping combinations containing watermelon when compared to cowpea monocrop suggesting it was also subject to over competition from watermelon. A similar trend was found in pepper production, with the pepper monocrop producing significantly greater amounts per plant. In 2011 production was 0.04 kg/plant in pepper monocrop versus 0.01 kg/plant in Ipwocr treatment combination. In 2012, pepper monocrop production was 0.16 kg/plant versus 0.07 in the Ipwocr treatment. Increased per plant productivity in 2012 when compared to 2011 for pepper also suggests that the changes in planting dates in 2012 allowed proper pepper establishment and reduced competition from watermelon. Peanut was only harvested in 2012, peanut production was improved in the Ipwo and Ipwoc intercropping combinations, 0.10 and 0.11 kg/plant, respectively, and was lowest in the Ipwocr and peanut-watermelon strip intercropping treatment (Spw) at 0.06 and 0.07 kg/plant respectively.

There were no significant reductions in fruit quality in pepper, okra and peanut although okra individual fruit fresh weight was increased in the Ipwoc treatment combination. Cowpea pods per plant were significantly reduced in 2011 in the two intercropping combinations it was incorporated into, Ipwoc and Ipwocr, and was likely due to over competition from watermelon. No significant reductions in cowpea quality parameters were detected in 2012. There was a reduction in watermelon brix in 2012 in the Ipwoc treatment combination. However, it is unknown whether this reduction was caused by competition from okra (although no reductions were evident in other intercropping combinations with okra) or due to the downy mildew infestation.

Objective 2: Weed and Disease Suppression
Weed suppression in 2011 was significantly reduced in intercropping combinations with watermelon, suggesting watermelon served as an effective smother crop for weeds. Weed biomass remained below 160 kg/ha in watermelon monocrop and any combinations incorporating watermelon while pepper, peanut, okra and cowpea monocrops had weed biomass values of 576, 768, 1010 and 1299 kg/ha, respectively (Appendix Fig. 3). However, in 2012 with a reduction in watermelon biomass due to okra competition and downy mildew, its ability to act as a smother crop was minimal. Watermelon monocrop still had the lowest weed biomass at 266 kg/ha. This value increased to up to 695 kg/ha in the watermelon-peanut strip intercropping combination and was highest in the pepper monocrop at 1241 kg/ha. There were no significant differences between the cowpea, peanut and okra monocrops and intercropping combinations that contained watermelon.
Due to an extraordinarily dry year in 2011, no severe disease issues were observed in any of the component crops. However in the 2012, watermelon experienced a severe downy mildew infestation. Data on disease incidence and severity were recorded approximately 2 days after the infestation was observed. No significant differences in incidence and severity were observed between intercropping combinations, however.

Participation Summary

Educational & Outreach Activities

Participation Summary:

Education/outreach description:

Posters presenting this research were presented at the 2013 Society for Horticultural Sciences and the 2013 Ecological Society of America annual meetings. Further findings will be presented at the 2013 Soil Science Society of America’s annual meeting. Yield and quality findings are currently being prepared for manuscript submission to the Agroecology and Sustainable Food Systems Journal (formerly the Journal of Sustainable Agriculture).

Project Outcomes

Project outcomes:

Production data from both years suggest a net benefit to intercropping with functionally diverse species in terms of productivity per plant. Land Equivalent Ratios in 2012 also point to a benefit of these cropping systems, specifically when the number of competing species is kept to a minimum. LER values were highest in the Ipwo and Ipwoc intercropping combinations and began to decline significantly when pepper was added. It is possible that there is a threshold where the benefits of intercropping are maximized and where over competition leads to a decline in productivity. Another important aspect of this study was the difference in competitive/facilitative relationships between the two years, which highlights the importance of planting date as it relates to seedling establishment and competition for resources. Watermelon and okra appeared to be the most competitive species in these systems and influenced both yield and quality. Watermelon was an effective smother crop for weed suppression, but because of differences in planting dates and disease issues in 2012, watermelon was not as prolific and did not perform as effectively as a smother crop. As a result, the only crop that benefited from the weed-suppression effects of intercropping when compared to its monocrop was pepper. Initial results from both years suggest that introducing a functionally diverse cropping system and selecting appropriate planting dates could translate into a reduction in manual labor and costs for organic producers in the southern United States through weed suppression while increasing overall productivity on a per land area and per plant basis, provided the right cropping combinations are used. Additionally, disease issues with watermelon in 2012 highlight the importance of having a diverse cropping system such as the ones incorporated in this study that could assure producers would still have one or more cash crops to harvest when one component crop fails.

Economic Analysis

Although no data are available on the economic impact of incorporating a functionally diverse intercropping system, increasing production on a per acre basis with minimal inputs could increase profits for producers through a reduction in input costs and increase in yield revenue.

Farmer Adoption

No information is available regarding adoption of intercropping strategies to increase production and maximize resource-use efficiency.


Areas needing additional study

Future research regarding the incorporation of plant functional diversity in vegetable production should include a more detailed assessment of importance of planting date on competitive and facilitative interactions between component species. Additionally, more information is needed on how this type of system would react with deficit irrigation and varying levels of nutrient inputs. Belowground productivity and species interactions should be further studied in low-input intercropping systems.

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.