Characterization of Soybean Seed Yield Using Optimized Phenotyping With Canopy Reflectance.

Genotyping and phenotyping technologies that increase the amount of genetic material in the breeding program and increase the efficiency of cultivar development are necessary to accomplish the genetic gains needed to meet food demand. Optimized phenotyping using canopy reflectance measurements may provide  a logical solution. The objectives of this study were: 1) to determine if canopy reflectance is useful in characterizing soybean seed yield; 2) to build yield estimation models for use as a screening tool; 3) to determine which wavebands contribute most to soybean yield estimation; and 4) to determine which spectral reflectance observations at specific growth stages contribute most to soybean seed yield. Canopy reflectance and seed yield were measured on 20 maturity group III (MGIII) and 20 maturity group IV (MGIV) soybean cultivars released from 1923 to 2010. Measurements were conducted on six irrigated and water-stressed environments in 2011 and 2012. Spectral band regions significantly contributing to seed yield prediction were selected through partial least squares regression, and yield estimation models were created using selected band regions through multiple linear regression. Significant differences in sources of variation for yield and band region were detected for genotypes, environments, and genotype x envionment interaction. Yield prediction models created using the red edge and portions of the near-infrared spectrum explained much of the variation in seed yield among genotypes. No significant trend was found for specific growth stages contributing more to yield estimation modeling or between water regimes. Yield estimation models using canopy reflectance measurements may be a useful selection tool in breeding programs.