Yield Component Study of the USDA Pea Core Collection.
Clarice Coyne1, Allan Brown1, Chasity Watt1, Ruth Butler2, and Gail Timmerman-Vaughan2. (1) USDA-ARS-W.Regional Plt.Intro.Sta., 59 Johnson Hall, Washington State University, Pullman, WA 99164-6402, (2) New Zealand Institute for Crop and Food Research, Private Bag 4704, Christchurch, New Zealand
Cool season food legumes (peas, chickpeas, faba beans, and lentils) are excellent foods, low in fat and rich in protein, fibre, minerals and vitamins. Large-scale, cost-effective genome analysis techniques have been developed in model species (eg. Arabidopsis thaliana, yeast, Medicago truncatula) and the major food crops (soybean, maize, rice, wheat). These techniques can now be applied to other significant food crops, such as pea, to increase value and productivity through targeted addition of new positive gene variants (alleles) from germplasm collections yet previously undiscovered. This report is on the field study portion of a collaboration to apply of genomic tools (robotics, automated genotyping and sequencing, BAC libraries) to characterize an extensive germplasm collection using sequences targeted to traits of economic importance, primarily yield. The USDA refined pea core collection was grown in four environments, with each line replicated, plus a highly replicated check cultivar, using designs that allow for spatial analysis of any field trends in the large (1 ha and 0.8 ha) area of the experiments. Plants were sub-sampled from plots before harvest to assess plant height, nodes and yield components. At harvest, total harvest weight, total seed weight and 100 seed weight were measured. Each measurement was analysed by using a mixed modelling approach that included adjustments for any spatial trends, fitted with residual maximum likelihood (REML).