Phenotypic and Genetic Modeling of Seasonal Growth in a Soft Red Winter Wheat Mapping Population Using NDVI.

Remote sensing has grown in popularity as a way to monitor crop growth and predict performance.  These tools can be especially useful in environments where abiotic stresses, such as severe drought, heat or waterlogging are limiting to crop yield.  In wheat, normalized difference vegetative index (NDVI) is commonly used to monitor crop nitrogen content as well as for predicting biomass and yield.  The goal of this study was to use NDVI to monitor seasonal growth in a soft red winter wheat (SRWW) mapping population and asses its utility in predicting early vegetative biomass, biomass at maturity and yield.  In addition, this data was used to identify quantitative trait loci (QTL) associated with NDVI accumulation throughout the season and the co-localization of these regions with QTL for biomass and grain yield.  A wheat recombinant inbred line (RIL) population consisting of 178 lines derived from a cross between Pioneer 26R61 (Pioneer Hi-Bred) and AGS2000 (University of Georgia) was used for this study.  Both cultivars are well adapted to the southeastern United States and have shown high yield and broad adaptation.  A dense genetic linkage map consisting of 895 DArT and SSR markers was developed for all 21 chromosomes in the wheat genome.  RILs and parental lines were grown at field locations in Fayetteville and Stuttgart Arkansas in 2011-2012 in a randomized incomplete block design with two replications per location.  Parental lines were replicated ten times within each complete block.  The two locations provided good contrast between ideal (Fayetteville) and drought stressed (Stuttgart) growing conditions.  NDVI measurements were taken monthly from four weeks post emergence until anthesis and bi-weekly from anthesis to physiological maturity using a Handheld Greenseeker.  Vegetative biomass samples were harvested at Feekes Stage 5, weighed fresh and re-weighed after drying.  At maturity, 50 spike bearing tillers were harvested at ground level and threshed to calculate final biomass and yield components.  At both locations, NDVI increased throughout the growing season until anthesis and decreased starting shortly after anthesis until physiological maturity.  NDVI measurements were highly correlated with each other, especially during winter and early spring growth (r=0.73 to 0.90), but this correlation decreased during rapid growth from node initiation to anthesis.  NDVI measurements were significantly lower in Stuttgart, which experienced severe drought stress starting from Feekes Stage 9 to mid-grain fill.  NDVI correlated strongly with fresh weight of biomass samples taken at Feekes Stage 5 (r=0.61) but only moderately with dry weight (r=0.36).  Preliminary QTL analysis shows a strong clustering of QTL for NDVI dependent on growth stage.  QTL regions identified on chromosomes 3A, 5A, 5BS, 5BL, 6B, and 7B co-localize for both NDVI and vegetative biomass.  Analysis of the phenotypic and genetic relationship between NDVI, biomass at maturity and yield are currently underway and will be presented.