Sarah Opeyemi Ajayi1, Qingwu Xue2, Nithya Rajan3, Amir M.H. Ibrahim3, Srirama Krishna Reddy4, Jackie C. Rudd2, Shuyu Liu4, Ruixiu Sui5 and Kirk E Jessup4, (1)Department of Soil and Crop Sciences, Texas A&M University, COLLEGE STATION, TX (2)Soil and Crop Science, Texas A&M University, Texas A&M AgriLife Research and Extension Center, Amarillo, TX (3)Soil and Crop Sciences, Texas A&M University, College Station, TX (4)Texas A&M AgriLife Research, Amarillo, TX (5)Crop Production Systems Research Unit, USDA-ARS, Stoneville, MS
Early growth stages in wheat can be influenced by factors, such as planting date, type of cultivar, water management or growing condition among others. It is essential to monitor the crop performance during the growing season by taking accurate measurements of crop growth parameters (such as ground cover) that can provide information to increase yield potential. Wheat production can be enhanced through the development of improved cultivars with wider genetic background, capable of producing better yield under various agro-climatic conditions and stresses. The process of monitoring plant stress, development and phenology contributes to better understanding the relationships between environmental conditions, vegetation health and productivity. Conventional methods can be time-consuming, labor-intensive and can cause large sampling errors. Remote sensing tools have provided easy and quick measurements of plant characteristics without destructive sampling. The objective of this study is to evaluate genetic variability in early growth and yield (not available due to hailstorm damage) of twenty wheat genotypes under two water regimes (rainfed and irrigated conditions), using GreenSeeker®, digital photography (percentage ground cover - %GC) and vegetation indices (VIs) estimated from aerial imagery. Field experiments were conducted at the Texas A&M AgriLife Research Station in Bushland, Texas during the 2014-2015 winter wheat growing season. Significant relationships (R2: 49%-95%) were recorded between VIs and %GC, also between observed and predicted %GC. Overall results of this study illustrated the potential use of aerial imagery for high-throughput phenotyping of wheat genotypes grown in the Texas High Plains under water-limited and optimum conditions for high-throughput phenotyping.