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Value-Added Einkorn for Organic Production in the Great Plains Region

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Value-Added Einkorn for Organic Production in the Great Plains Region 2017 Final Report to Ceres Trust for the project: Value-added Einkorn for Organic Production in the Great Plains Region submitted by Abdullah Jaradat USDA North Central Soil Conservation Research Laboratory Morris, MN, Dipak Santra UNL Panhandle Research Extension Center Scottsbluff, NE, Steve Zwinger NDSU Carrington Research Extension Center Carrington, ND, Joel Ransom NDSU Extension Fargo, ND, Frank Kutka Northern Plains Sustainable Agriculture Society Lamoure, ND INTRODUCTION: The purpose of this project was to identify einkorn accessions with desirable traits for performance within organic farming and marketing systems in the Northern Great Plains. Einkorn (Triticum monococcum), a wheat species with hulls like barley, was cultivated thousands of years before the development of modern wheat. However, there is a renewed interest in einkorn because of its apparent salinity and other stress tolerance, its high nutritional quality, and its usually impressive flavor. Finding superior varieties of high value crops, such as einkorn, is a key approach to improve nutritional quality for consumer health and to improve farm profitability and soil health across the Great Plains region. Given the relatively limited experience with einkorn in our region and low number of varieties currently available, extensive evaluation of varieties was required in order to find those that might provide real benefits to both organic farmers and consumers. This report summarizes our study of agronomic traits, nutritional traits, and salinity tolerance of einkorn accessions selected from the collection deposited at the USDA National Small Grains Collection, Aberdeen, Idaho and several available in the specialty seed trade. Figure 1. Einkorn grown organically in Carrington, North Dakota in 2014. ACTIVITIES AND OUTCOMES: Objective 1: Evaluate einkorn germplasm for adaptability to organic management Replicated field evaluation of einkorn accessions Our initial work in 2014 was a non-replicated screen of 100 accessions and varieties of einkorn at our three research locations (Scottsbluff, Morris, Carrington). Most of these were originally obtained from the USDA National Plant Germplasm System and increased previously as part of other research at the Carrington Research Extension Center. Several others were purchased from specialty seed houses in the USA and Canada that were selling small lots of einkorn for gardeners. After considering the initial data from the non- replicated screen, we identified nineteen accessions that appeared worthy of more intensive evaluation to see if our first impressions would hold up, and if some of the less obvious traits like higher nutritional quality might be present. Given the experience of specialty wheat research at the Carrington Research Extension Center, we chose the variety “TM23” (PI 355523) to be used as a check variety. TM23 has been getting some use by NPSAS Farm Breeding Club members who are increasing the seeds for larger scale production. In a change to our initial plan, we increased the seed of the twenty lines of einkorn at the NDSU Carrington Research Extension Center in 2015. Seeds for field evaluations were sent to the USDA North Central Soil Conservation Research Laboratory in Morris, MN and to the University of Nebraska Panhandle Research and Extension Center in Scottsbluff in 2016 and 2017. Four replicates of each line were planted out in an alpha design at each of these locations each spring. An Alpha design uses incomplete blocks as factors in order to better account for soil and other variation across the experiment. When the effect of these incomplete blocks is insignificant or small compared to the effect of complete replicates with all of the experimental varieties, the Alpha design conveniently reverts to the randomized complete block design (RCBD) with which most agronomists are familiar. Plot sizes were approximately 5’ x 25’ and four replicates were planted at each location each year at appropriate times for spring wheat establishment. In 2016 plugging in the plot planter resulted in mixed stands at the Nebraska location. The drought of 2017 also severely limited growth at Scottsbluff, and yields for most plots were scarcely more than a few bushels per acre. Therefore, the yield data analyzed and presented here were solely from Carrington, ND and Morris, MN. With twenty experimental entries (nineteen accessions and a check variety), four replicates, two locations and two years of evaluations, we ended up with three hundred and twenty total observations. As we did not find large differences between the results of the RCBD and the alpha design, for simplicity we present here the statistical analysis with the RCBD. The analysis of variance (ANOVA) of the RCBD used a simple model with treatments, replicates within environments, environments (site-years), and treatment by environment interaction as factors. For the grain yield data, the overall model had an F value of 13.41 and was significant at the p<0.001 level (Table 1), so we reject the null hypothesis that these factors do not have an influence on einkorn yield. Each of the factors in the model also had F values that were significant at the p>0.01 level given this large data set (Table 1). This suggests that observations were different among the four site-years, among the replicates within each of those environments, among the einkorn accessions, and that performance of these accessions interacted with the environments. This sort of interaction can make it more difficult to identify lines that are clearly superior across the region (broad adaptation), but it can still be possible to identify those that are superior at specific locations if the differences are striking (local adaptation). Table 1. Results of the analysis of variance (ANOVA) for a study of nineteen einkorn accessions and one experimental check variety conducted in Carrington, ND and Morris, MN in 2016 and 2017. Source DF Sum of Squares Mean Square F Value Pr>F Model 91 101616395.2 1116663.7 13.41 <0.0001 Env 3 86694989.18 28898329.73 347.04 <0.0001 Rep (Env) 12 3260312.31 271692.69 3.26 0.0002 Var 19 3966861.44 208782.18 2.51 0.0007 Env*Var 57 7694232.27 134986.53 1.62 0.0071 Error 228 18985749.0 83270.8 Corrected Total 319 120602144.2 Average yields for the nineteen accessions and check variety were largely similar (Table 2). When the yield data were ranked or standardized to percent of the average replicate yield, there were also significant differences among the einkorn lines (Table 2) and there was also significant interaction between the accessions and the environment. Ranking and other standardization techniques can be used to control or eliminate some environmental variation. These do not provide predictions of likely grain yield, but can give an indication of the likelihood of a variety ranking well or yielding better than average compared to other varieties. However, there was still enough variation in ranks to produce a good deal of noise in the data set and prevent the clear identification of a few superior varieties. The same held true when the data were standardized to replicate averages. Table 2. Average grain yield of nineteen einkorn accessions and one experimental check variety at Carrington, ND and Morris, MN in 2016 and 2017. Results are shown as kg/ha, ranked within replicates, and percent yield within replicates. An ANOVA was performed on the overall data so least significant differences are shown for those data. The best performer overall and at each location is highlighted in yellow. Those accessions that differ from the best performer using the LSD estimates are highlighted in red. Overall Carrington, ND Morris, MN Accession Yield Rank % Mean Yield Rank % Mean Yield Rank % Mean 94743 2495 10.8 100.1 1973 11.2 98.3 3018 10.4 101.9 119422 2408 11 95.2 1772 13.3 87.7 3044 8.8 102.8 119423 2513 9.4 102 2119 7.8 105.2 2907 11.1 98.8 167526 2377 13.3 95.3 1892 13.2 94 2861 13.4 96.6 170196 2552 10 102.3 1996 12 99.6 3108 8.1 105 191381 2633 8.1 105.3 2076 8.6 103.4 3191 7.7 107.3 237659 2586 7.9 104 2111 7.7 105 3062 8.3 103 254195 2505 10.8 101.4 2043 11 102 2968 10.5 101 326317 2533 9.5 103.2 2151 8.3 107.5 2916 10.8 99 428149 2702 6.6 108.4 2132 8 106.6 3273 5.4 110.3 428150 2470 10.9 99.4 2026 9.5 100.6 2915 12.3 98.4 428155 2508 9.7 100.7 2027 10.2 100.9 2990 9.3 100.5 428156 2300 15.5 90.7 1684 17.7 83.7 2916 13.4 97.8 428158 2415 11.9 96.6 1843 14.4 92.1 2988 9.4 101.3 428163 2533 8.6 104 2240 5.8 111.6 2827 11.4 96.5 428164 2490 9.6 101.7 2159 6.2 107.6 2821 13.1 95.9 428171 2447 11.8 99.1 1993 12.7 99.7 2902 10.9 98.5 428172 2172 16.2 88.4 1854 14.7 92.4 2490 17.8 84.5 428173 2514 9.6 101 2008 10 100 3020 9.2 102.1 TM23 2503 9.2 101.2 2069 8.8 102.6 2937 9.7 99.8 Average 2483 10.5 100 2008 10.6 100 2958 10.56 100 LSD 0.05 402 7.3 17.5 Accession PI 428149 had the highest yield of grain, the lowest average rank, and the highest percentage of average yields in the overall results (Table 2). Least significant difference tests show that the means of two other accessions (PI 428156 and PI 428172) were significantly lower, while the others were not significantly different.
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