Genetic Variability of Growth and Development in Response to Nitrogen in Two Soft Winter Wheat Populations

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Virginia Tech


The use of nitrogen (N) fertilizers is both costly to farmers and contributes to environmental degradation. N applied to wheat accounts for 18% of N applied to farmland globally, making it a prime target for reducing and optimizing N application. Chapter I is a review on nitrogen use efficiency (NUE) in wheat, with emphasis on breeding efforts and genetic resources available to increase NUE. The concept of effective use of nitrogen (EUN) as yield per unit N applied as a measure of N use, is also introduced. Chapter II is a study using two bi-parental double haploid families to evaluate genetic variability of both the genetic main effects (intercept) and linear response to N (slope) and determine the feasibility of selection for EUN in wheat. Using cross validation, a genomic prediction accuracy of 0.68 for intercept and 0.50 for slope was found, indicating that EUN is under genetic control and can be selected for. The prospect of breeding for EUN under limited resources, i.e., using fewer N rates and fewer experimental plots, is also explored. It was found that two different N treatments can be used to produce accurate predictions of intercept and slope as high as 0.98 and 0.95, respectively. Chapter III uses the same population described in chapter II to further investigate feasibility of selection for EUN using a normalized difference vegetation index (NDVI) obtained from multi-spectral aerial images gathered throughout the growing season. Cumulative photosynthesis across the growing season was estimated by integration across the NDVI curve, and compared to grain yield estimates to determine the efficacy of aerial imaging to identify high EUN lines. NDVI values and the area under the NDVI curve were able to predict yield and had the strongest ability to predict yield in moderate to low N treatments, with R2 values as high as 0.81 and 0.78 respectively.



Triticum aestivum, wheat, nitrogen, nitrogen use efficiency, genomic selection, linkage mapping, marker-assisted selection, high-throughput phenotyping