Participatory breeding of high-value wheat for the Northeast

Final Report for GNE15-107

Project Type: Graduate Student
Funds awarded in 2015: $14,996.00
Projected End Date: 12/31/2016
Grant Recipient: Cornell University
Region: Northeast
State: New York
Graduate Student:
Faculty Advisor:
Dr. Heather Darby
University of Vermont Extension
Faculty Advisor:
Dr. Mark Sorrells
Cornell University
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Project Information

Summary:

This grant has developed 41 new populations of spring wheat and 63 populations of winter wheat, and dozens of early-stage breeding material of emmer and einkorn to meet organic farmers’ needs in the Northeast United States. Ten organic and biodynamic farmers in New York, Pennsylvania, Maine, and Vermont developed a total of 42 populations of wheat and einkorn tailored to their farming operations. Using rigorous plant breeding techniques at Cornell University, we have developed elite lines of winter wheat suited to the needs of organic growers in the Northeast. These lines outperform the varieties currently used by organic growers. Developed varieties are on the path to broader testing and variety release.

243 individuals attended workshops, presentations, and field days to learn about developed varieties. Journalists reached an unknown amount of other individuals by reporting on grant activities. By actively involving farmers, millers, and bakers in the breeding process, stakeholders are enthusiastic to adopt varieties developed through this grant. The farmers who participated in selection have gained new knowledge in plant improvement and become seed stewards for their developed varieties.

Results show that organic farmers were effective at improving their #1 priority trait of interest in spring wheat: weed-competitive ability. On average, four farmers in the northeast United States enhanced competitive ability of selected genotypes by 11.46%. Developed populations also showed evidence of local adaptation. There was a mean 9.35% increase in weed-competitive ability when lines were grown on the farms where they were selected. This study concludes that weed-competitive ability and its correlated trait of early vigor show local adaptation, and can benefit from decentralized breeding in the Northeast United States.

Introduction:

Small grains are important components of organic and local food systems. The fibrous root systems and high carbon plant residues of small grains can improve soil health by rapidly building organic matter (Snapp et al. 2005). Diversifying rotations with small grains mitigates two primary challenges of organic agriculture identified by Cavigelli et al. (2008): weed competition and nitrogen supply. Beyond agronomic benefits, small grains bolster the economic stability of farms and rural communities. In a meta-analysis by Crowder and Reganold (2015), organic cereals (along with oil and fiber crops) provided the greatest financial benefit-to-cost ratio when compared with conventional production. The long processing chains required for small grains also invigorate regional economies, providing entrepreneurial opportunities for millers, bakers, pasta makers, and restaurants to sell locally produced grain (Halloran 2015).

Despite its benefits, wheat underperforms in organic food systems. Worldwide meta-analyses show that wheat (along with barley and potato) has the lowest organic-to-conventional yield ratios in comparison with other crops (Ponisio et al. 2014; Seufert et al. 2012). Wheat genetics that underperform in organic systems may be reducing the crop’s potential.

Improved wheat genetics can boost grower adoption of small grains and sustainability of organic rotations. This grant focused on breeding wheat, emmer, and einkorn for organic production in the Northeast United States. The breeding program focused on selection traits prioritized by organic farmers in the region, including weed-competitive ability, Fusarium head blight resistance, straw production/tall height, lodging resistance, high protein, and free threshing. A participatory wheat breeding program enabled the identification, selection, and adoption of superior genotypes for organic production.

Project Objectives:

All objectives were accomplished

  1. Conduct participatory breeding of wheat, spelt, and einkorn on farms and research stations according to traits that are most important to farmers;
  2. Breed free-threshing populations of emmer, einkorn, and spelt;
  3. Test homozygous F7 farmer-selected wheat populations for performance throughout the Northeast, and compare selected populations for local vs. broad adaptation;
  4. Develop a roadmap with farmers and the seed industry to release top-performing varieties.

Cooperators

Click linked name(s) to expand
  • Heather Darby
  • Michael Davis
  • Lisa Kissing Kucek
  • Mark Sorrells

Research

Materials and methods:
  1. Conduct participatory breeding of wheat, spelt, and einkorn on farms and research stations according to traits that are most important to farmers;

During the summers of 2015 and 2016, the graduate researcher facilitated farmer selection of superior winter wheat varieties. Five participating farmers from Oechsner Farms, Lakeview Organic Grain, Threshold Farms, Gleason Grains, and White Frost Farms planted bulked F3 biparental families from winter wheat and einkorn crosses in the fall of 2014. Each farm established two replicates of five biparental family plots and one check variety commonly grown by organic farmers in the region: ‘Warthog’. Plot sizes varied from 4.65 to 9m2, depending on the size of regional planting equipment. Farm-specific selection protocols facilitated the selection of phenotypes best suited to the priority traits of each farmer. With the help of the graduate investigator, the farmer visually separated each biparental family plot into four quadrants and selected the 10% of plants or spikes that best met priority traits in each quadrant. The graduate investigator also randomly collected the same number of spikes from each biparental family plot to form F3:F4 winter wheat and F4:F5 spring wheat baseline populations to track gains in selection. In addition to farmers selecting based on their priority traits in the field, we were able to select for protein content, which was the second highest rated trait by participating winter wheat farmer breeders. For farmers who selected protein as a priority trait, a single seed non-destructive Near-infrared spectroscopy (NIR) machine allowed the selection of 50% of spikes with highest protein. The graduate researcher calibrated the NIR instrument using a partial least squares model and a destructive nitrogen test (LECO TrueMac N). One hundred and ninety-two seeds each from six wheat varieties from a range of protein contents and color classes comprised the calibration set. The r2 of the calibration was high, at 0.87. This successful calibration allowed us to use the single seed NIR to advance of genotypes with highest protein content at an early stage in the breeding program, when seed is scarce. Using the NIR, we selected the 50% of farmer-selected wheat heads with the highest protein content. Selected seed was pooled from the two replicate plots of each biparental family and planted in 2016. Selection was repeated in 2016.

In tandem with on-farm selection, researchers selected biparental families on research stations for the most important regional traits. For winter wheat, research station selection protocols focused on traits of most importance to regional winter wheat farmers: Fusarium Head Blight (FHB) tolerance, high protein content, and desirable baking and sensory qualities. From the same winter wheat biparental families planted on farms, researchers evaluated 312 headrows of F2:F3 individuals and parental varieties at Freeville, NY and at a Fusarium head blight nursery in Ithaca, NY in 2015. At the disease nursery, headrows were inoculated at anthesis with Fusarium, and screened for FHB index (infection rate x severity). Other metrics of headrow evaluation included average height, leaf disease severity (1-9), glume blotch severity (0-3), and date at which 50% of heads emerged. Index selection provided a quantitative way to select the 30% best headrows from the field, weighted strongly against fusarium index, and to a lesser extent, against late heading, very tall height, leaf disease, and glume blotch (Equation 1). For baking and sensory quality, the third most important trait ranked by winter wheat farmers, the index added points to crosses with parents that have desirable quality characteristics. Researchers collected seed from 10 individual plants in each selected headrow. Eight seeds from each plant entered NIR evaluation for protein content. The 50% of plants with highest protein from each selected headrow, assed through NIR, advanced to the next year of selection. In 2016, 466 winter wheat F2:F4 individuals were assessed using the same method as 2015.

Equation 1. Index Score = IF(FHB index>10,-20,0)+(50/FHB index))+(IF(Heading Day after May1<38,0, Heading Day after May1*-0.5))+IF(Height<110,0,(Height*-1/20))+IF(RC(leaf disease<7,0,leaf disease*-1)+IF(leaf disease<5,(8/leaf disease),0)+IF(glume blotch=3,-5,IF(glume blotch=0,5,IF(glume blotch=1,3,0)))+(5 to 10 for parents with good qualities) (Excel 2013)

For spring wheat, researchers screened 210 headrows of F2:F3 individuals for the trait of most importance to spring wheat farmers in the region: weed competitive ability. Flagged plants and headrows with the highest early vigor (1-5) and leaf width (1-5) at third to fifth leaf stage advanced to the second year of selection in 2016. 90 headrows of F3:F4 individuals and F2:F4 individuals were grown in two locations in 2016. F4 lines were again ranked for early vigor (1-5) at Freeville, NY. Moreover, lines were inoculated in the Fusarium headblight nursery and scored for incidence and severity. Due to unprecedented drought conditions, the spring wheat F4 lines on research stations suffered greatly, and late season measurements were not feasible or representative of the crop. The best 30 individuals based on early vigor and FHB index were harvested.

  1. Breed free-threshing populations of emmer, einkorn, and spelt;

In the spring of 2015, superior varieties ‘Lucille’, ‘ND Common’, and ‘Red Vernal’ were crossed with the free-threshing emmer variety, ‘Debra’, that is poorly adapted to the Northeast, in addition to a free-threshing emmer relative, Kamut®. In the greenhouse, F1 progeny were backcrossed to each parent during flowering. The seed from the BC1 generation were selected that threshed free of glumes. The plants were allowed to self to F2 and F3 and assessed for free threshing.

In the fall of 2014, einkorn and spelt seeds from various F3 biparental populations that most easily separated from the hull were selected. After rolling in a simple rubber tube, small portions of the hulled seed broke free of the glume. These seeds were planted in F2:F3 headrows at two sites for winter hardiness, heading date, height, and FHB tolerance. In the fall of 2015, we repeated this process, selecting the most easily dehulled seed from superior performing headrows. This selected seed was replanted as F2:F4 in the fall of 2015 for another year of agronomic evaluation. In the fall of 2015, the most easily dehulled F5 seed from top-performing headrows were selected and planted on a research station in Freeville, NY and on farm at Lakeview Organic Grain. After recognizing that our selection methods for free-threshing einkorn may not be producing the desired results, we sought germplasm of free-threshing einkorn to establish new breeding populations.

Free threshing einkorn lines were acquired from Canada, the USDA, and a breeding program in Germany.  These lines were grown in the field in 2016 to test their field performance.  Simultaneously, these free threshing einkorns were crossed with our top-performing agronomic F4 breeding lines from Lakeview Organic Grain and Cornell University.

  1. Test homozygous F7 farmer-selected wheat populations for performance throughout the Northeast, and compare selected populations for local vs. broad adaptation;

In preparation for yield testing during the summer of 2016, the graduate researcher sent the farmer-selected populations to an off-season nursery for seed increase. Unfortunately, the nursery that we chose to work with in California destroyed the majority of seed as a result of poor land management. We supplemented seed by planting 533 plants for seed increase in a greenhouse at Cornell University. One site (Willsboro, NY) was removed from the multienvironment trials due to lower than expected amounts of seed from the increase. 

In 2016, farmer-selected F7 populations of spring wheat and baseline randomly-collected F4:F7 populations were planted in split plot pairs to measure gains in selection at five research station locations (Old Town, ME; Borderview, VT; Fusarium Headblight Nursery in Ithaca, NY; Ketola in Ithaca, NY; Helfer in Ithaca, NY). Recorded data at Borderview and Old Town included yield at 12% moisture, test weight at 12% moisture, height, lodging (1 to 9), and early vigor between 4th and 5th leaf stage (1 to 9). At Old Town, ME, plots were overseeded with the surrogate weed Sinapsis alba cv. ‘Idagold’ using a Brillion seeder at a rate of 75 live seeds per m2. Weed and wheat biomass were measured in each plot by sampling two 0.25 m2 quadrats (0.5 m2 total sample size), separating out wheat from weed biomass, drying at 55°C, and weighing. At Ketola and Helfer, six-row one-meter miniplots were assessed by two to three evaluators for early vigor at 4th leaf stage (1 to 9). Ground cover was also assessed at Ketola and Helfer using a 16 Megapixel camera and Canopeo App (Patrignani and Ochsner 2015) at one meter height during 3rd, 4th, and 5th leaf stages. Due to errors incurred in the Canopeo processing software during high light conditions, shade cloth was added to camera equipment for the 4th and 5th leaf stages. A calibration trial was conducted to assess the consistency of visual early vigor genotype rankings among evaluators. Six graduate student evaluators were trained on visual rating of early vigor for five minutes, and then asked to rate 20 spring wheat genotypes for early vigor over three replicates. Through the package ‘lme4’ [version1.1-10] (Bates et al. 2015), the random effects of genotype, replicate, evaluator, and the interaction between genotype and evaluator were tested for variance in early vigor scores.

To determine if selection was effective, an F-test compared the fixed effect of population type (F7 and F4:F7) for WCA traits using R [version 3.2.2] (R Core Team 2015), package ‘lme4’ [version1.1-10] (Bates et al. 2015) (Equation 2). The model included family and farm where selection took place as fixed effects, and block as a random effect.

Equation 2.     Yijkl = µ + αi + βj + γk + dlijkl 

H0: µF7= µF4:F7; α≤0.05

yijkl: trait of interest for type i, family j, farmer k, and replicate l;

µ: overall mean response;

αi: fixed effect of type i (e.g. F7, F4:F7);

βj: fixed effect of family j;

γk: fixed effect of farmer k; dl: random effect of block l;

εijkl: experimental error associated with response i,j,k,l

 

To measure local adaptation of selected populations, the F7 populations were placed on four farms in a replacement experiment in 2016: Butterworks Farm (Westfield, VT), Grange Corner Farm (Lincolnville Center, ME), Essex Farm (Essex, NY), Adirondack Organic Grains (Westport, NY). Trials followed a randomized complete block design with three replicates. Each farmer grew the five to six “local” populations that he had selected in addition to three to four populations selected by each of the other farmers, for a total of 10 to 12 “introduced” comparison populations. Plots were screened for visual early vigor on a 1 to 9 scale, and visual measures of WCA. We were not able to seed a surrogate weed species on participating farms, due to concerns about increasing farm weed seedbanks. However, visual measures of WCA have been shown to correlate highly with biomass measurements (r=0.87), while saving considerable time and effort (Worthington et al., 2013). Measures of WCA varied by farm due to different levels of weed competition at each farm. At Essex and Adirondack, the visual ratio of wheat to weed biomass was measured. At Butterworks, intense natural weed competition prevented an accurate visual estimate of wheat to weed biomass, and heads of wheat were counted as a more reliable measure. At Grange Corner, where there was little to no weed presence, visual ratings of weed competition were not possible. An ANOVA with a random blocking factor tested differences in mean values of WCA between local and introduced populations using R [version 3.2.2] (R Core Team, 2015), package ‘lme4’ [version1.1-10] (Bates et al. 2015) (Equation 3). Data were plotted using ‘forestplot’ (Gordon 2014).

Equation 3.     Yijklm = µ + αi +βj + γk + dl(fm)+ εijklm

H0: µlocal = µintroduced; α≤0.05

yijklm: trait of interest for type i, family j, farm k, rep k, trial m;

µ: overall mean response;

αi: fixed effect of type i (local or introduced); βj: fixed effect of family j;

γk: fixed effect of farm where selected k;

dl(fm): random effect of rep l, nested in trial m;

εijklm: experimental error associated with response i,j,k,l,m

Seeding rates in all trials were adjusted based on germination rates and thousand kernel weight to obtain 376 viable seeds per square meter. Right-skewed responses were log transformed to obtain normal distributions for ANOVA models (e.g., data for the number of wheat heads at Butterworks and weed to wheat ratio at Old Town).

  1. Develop a roadmap with farmers and the seed industry to release top-performing varieties.

The graduate researcher collaborated with Cornell University, NOFA-NY, and Greenmarket-GrowNYC to host an event titled “Sowing the Future of Organic Wheat” on June 10th, 2016 (see Table 1). We collaborated with regional bakers to make varietal-specific breads and pastries for tasting.  Researchers provided a comprehensive overview of organic wheat research that has taken place up to this point in the Northeast.  Participants engaged in selecting wheat populations in the field.  To end the day, participants entered a focus group session to vision priorities, needs, and structure for releasing varieties and future breeding efforts.

Table 1. Agenda for “Sowing the Future of Organic Wheat”

12:30-1:00 Registration, tasting of Wegmans breads and varietal pastries

1:00-3:30 Review of regional grains research

Northern New England Bread Wheat Project – Heather Darby, University of Vermont


Value Added Grains for Local and Regional Food Systems – Lisa Kissing Kucek, Cornell University

Perennial Grains Update – Sandra Wayman, Cornell University

Regional Grain Marketing and Economics - June Russell, Greenmarket, GrowNYC


Restoring the Culture of Heritage Wheat – Eli Rogosa, Heritage Grain Conservancy

Hudson Valley Grain Research - Justin O’Dea, Cornell Cooperative Extension of Ulster County

3:30-4:00 Sample varietal breads made by Brookyln Bread Lab

4:00-5:00 Tour organic wheat breeding nurseries

Integrated Management of Fusarium Head Blight and Mycotoxins – Gary Bergstrom, Cornell University

Introduction to Organic Breeding Populations

Quality Seed for Organic Production – Phil Atkins, New York Seed Improvement Program

5:00-6:00 Focus group and listening session on the future of organic grains research

6:00-7:00 Celebration with wood fired pizza and regional beer sampling

Research results and discussion:
  1. Conduct participatory breeding of wheat, spelt, and einkorn on farms and research stations according to traits that are most important to farmers

Farmers were pleased with many of the lines that they selected. Some of these farmers have shown off their new wheat lines at field days in the region, indicating the pride and value they see in such varieties.

The top 50 F5 lines selected on research stations showed excellent improvement and performance for farmer traits of interest, particularly Fusarium Head Blight (FHB) tolerance, high protein content, and low leaf disease. These lines performed better than varieties commonly grown by organic farmers in the region: ‘Arapahoe,’ ‘Red Fife,’ and ‘Warthog’. These promising breeding lines will be planted in replicated trials at Freeville, NY; Madison, Wisconsin; Danforth, Illinois; and the FHB nursery in Ithaca, NY to evaluate yield, test weight, heading date, and disease in 2017. These lines hold great promise for release to organic farmers in the coming years.

The top 15% of spring headrows were selected based on early vigor (1-9) and Fusarium Index. These lines will be grown again in 2017 due to drought conditions in 2016 preventing accurate assessment of field performance.

  1. Breed free-threshing populations of emmer, einkorn, and spelt;

The most commonly cited barrier for farmers in the Northeast to growing ancient grains is dehulling. We have attempted to introgress free threshing into the best performing ancient grains for farmers in the Northeast.

For emmer, we saw evidence of cross-compatibility issues with Kamut®. These lines are being carefully inspected for unsuccessful crosses that may have selfed during the initial cross. We have generated free threshing emmer types, but more testing is needed to ensure the reliability of these lines and the free threshing trait. We hope to plant these lines out in the field in 2017 or 2018, depending on seed availability, to assess agronomic quality.

For einkorn, we were able to successfully cross our top breeding lines with free threshing genotypes from around the world. The free threshing genotypes, however, show variable adaptation to the Northeast. Progeny among free threshing crosses will further tested for adaptation to the region.

Developing molecular markers to associated with free-threshing would be a valuable future project for improving the efficiency of breeding for this trait.

  1. Test homozygous F7 farmer-selected wheat populations for performance throughout the Northeast, and compare selected populations for local vs. broad adaptation;

Results show that organic farmers were effective at improving their #1 priority trait of interest in spring wheat: weed-competitive ability. On average, four farmers in the northeast United States enhanced competitive ability of selected genotypes by 11.46%. Developed populations also showed evidence of local adaptation. There was a mean 9.35% increase in weed-competitive ability when lines were grown on the farms where they were selected. This study concludes that weed-competitive ability and its correlated trait of early vigor show local adaptation, and can benefit from decentralized breeding in the Northeast United States.

To validate the effects of local adaptation, collaborators plan to complete another year of data collection on farms. In 2017, we are hoping for a less dry year that is more representative of Northeast conditions. Farmer-selected lines will also be tested for early vigor and yield performance at research stations in Ithaca and Willsboro, NY; Borderview, VT; and Orono, ME.

Visual estimation of early vigor showed consistency in varietal ratings among different evaluators, indicating its promise for use as a consistent field measurement tool. After six evaluators visually rated early vigor of 20 spring wheat genotypes over three replicates, 70% of the variance in early vigor was explained by genotype. Although evaluators did have slightly different rating scales, with 11% of the variance in early vigor explained by the evaluator, evaluators did not differ in their ranking of varieties for early vigor. Only 0.09% of variance in early vigor was explained by the interaction between evaluator and replicate. Consequently, visual estimation seems to be a reliable measure of early vigor among genotypes, even if different evaluators complete field measurements. Visual early vigor measurements were also correlated with canopy cover measurements using Canopeo (r=0.3238 at p<0.0001). However, canopy cover measurements and data processing took 408% more person-hours than visual estimates of early vigor. Worthington et al. (2013) found similar results, and recommended visual estimations of early vigor instead of ground cover imaging.

  1. Develop a roadmap with farmers and the seed industry to release top-performing varieties.

The event “Sowing the Future of Organic Wheat” was highly successful at engaging stakeholders and developing a roadmap for releasing wheat varieties. Thirty-eight farmers, millers, bakers, researchers, and journalists joined us for the event.

Farmers have decided to release their top-performing varieties under the Open Source Seed Initiative (OSSI, for details visit http://osseeds.org/).  After another year of testing farmer-selected lines in the Northeast, the top lines will be considered for release through OSSI.  Researchers have decided to release their top-performing varieties as Plant Variety Protected lines and through the Open Source Seed Initiative.

Research conclusions:

41 new populations of spring wheat, 63 populations of winter wheat, and 16 populations of winter einkorn have been developed by organic farmers from New York to Maine. After testing these populations in 2017, the superior varieties will be considered for variety release. Once released, these varieties can immediately boost performance, sustainability, and profitability of organic farms in the region. Moreover, the varieties will help build local grain economies that are emerging throughout the Northeast.

The development of free-threshing emmer and einkorn varieties can allow small farmers to incorporate high-value small grains in their rotations. Without the need for dehulling, these grains can be profitable for small farmers. These high-value grains would improve soils, reduce erosion, and reduce pests when incorporated in rotation with demanding high-value crops grown more commonly by small farmers, such as vegetables. Moreover, this product will help satisfy a booming consumer demand for these ancient wheat species, which are perceived to be less harmful for individuals with wheat sensitivity (Kissing Kucek et al. 2015).

There is little research evidence of local adaptation in plant breeding. This novel research quantified local adaptation of lines selected on diverse farmers in the Northeast. Moreover, this research adds to the literature substantiating participatory plant breeding as an effective method. Farmers were able to improve weed competitive ability in spring wheat by making selections on their farms.

This research actively engaged stakeholders in the wheat breeding process. Farmers, millers, and bakers were energized and enthusiastic to adopt varieties developed through this grant. The farmers who participated in selection have become seed stewards for their developed varieties, and have been seen showing off their new wheat lines at field days in the region. For a small seed market like organic wheat in the Northeast, this example of decentralized plant breeding and seed systems will help meet the diverse needs of growers.

Participation Summary

Education & Outreach Activities and Participation Summary

Participation Summary:

Education/outreach description:
  • Kissing Kucek, L, Darby, H, Atkins, P, Bergstrom, G, Russell, J, O’Dea, J, Rogosa, E, Wayman, S, Sowing the Future of Organic Wheat. Ithaca, NY, June 2016.

38 participants (including farmers, millers, bakers, journalists, and researchers) engaged in wheat breeding, seed improvement, wheat pathology, and selection.

50 farmers learned about organic wheat breeding

  • Kissing Kucek, L. et al. “Four Years of Ancient, Heritage, and Modern Wheat Research in the Northeast” Northern Plains Sustainable Agriculture Society Winter Conference. Aberdeen, SD, January 2016.  Also presented The Grounded Guide to Gluten: How Modern Genotypes and Processing Impact Wheat Sensitivity.

45 farmers learned about ancient grain variety trialing and breeding for free threshing

  • Kissing Kucek, L and Atkins, P “Small Grain Variety Selection and Seed Production Workshop” University of Maine. Orono, ME, July 2015.  Maine Selection Workshop

30 participants (primarily farmers) learned about the basics of small grain genetics and experimental design for on-farm breeding. Phil Atkins introduced the basics of seed certification and how to save quality seed on farm.

  • Kissing Kucek, L “Participatory Plant Breeding: Engaging farmers and gardeners to build resilient food systemsYale Food Systems Symposium. New Haven, CT, October 2015.  Yale Food Systems presentation

40 participants (including farmers, students, and food processors) learned about the coevolution of crops and humans, the importance of involving more people in breeding, and examples of participatory plant breeding.

  • Darby, H. et al. “Modern, Heirloom, and Ancient Grain Evaluation and Participatory Development of New Varieties for Our Region.” 2015 Growing Organic Farm Conference. Harrisburg, PA, December 2015. Methods and early results of the SARE grant were shared and exchanged with organic growers and researchers in PA.
  • The results of the local adaptation trials and farmer gains in selection for weed competitive ability was presented to 50 researchers and published as a dissertation chapter with Cornell University. The contents will be submitted to Crop Science, after collaborators complete another year of data collection to validate results.

Project Outcomes

Project outcomes:

NA

Farmer Adoption

243 individuals, including many farmers and seed company representatives, attended workshops, presentations, and field days to learn about breeding lines. Journalists reached an unknown amount of other individuals by reporting on grant activities. By actively involving farmers, millers, and bakers in the breeding process, stakeholders are enthusiastic to adopt varieties developed through this grant. The ten farmers who participated in selection have gained new knowledge in plant improvement and become seed stewards for their developed varieties.

Assessment of Project Approach and Areas of Further Study:

Areas needing additional study

Understanding the molecular mechanisms in free threshing of emmer and einkorn would greatly facilitate a rapid breeding program.

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.