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Full-Text Articles in Agriculture

Soybean Response To Water: Trait Identification And Prediction, Shawn Jenkins Feb 2020

Soybean Response To Water: Trait Identification And Prediction, Shawn Jenkins

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

The rising demand for soybean [Glycine Max (L.) Merrill] taken in consideration with current climatic trends accentuates the importance of improving soybean seed yield response per unit water (WP). To further our understanding of the quantitative WP trait, a multi-omic approach was implemented for improved trait identification and predictive modeling opportunities. Through the evaluation of two recombinant inbred line populations jointly totaling 439 lines subjected to contrasting irrigation treatments, informative agronomic, phenomic, and genomic associations were identified. Across both populations, relationships were identified between lodging at maturity (r = -0.58, H = 0.86), canopy to air temperature differential …


Wheat Growth Monitoring And Yield Estimation Based On Multi-Rotor Unmanned Aerial Vehicle, Zhaopeng Fu, Jie Jang, Yang Gao, Brian Krienke, Meng Wang, Kaitai Zhong, Qiang Cao, Yongchao Tian, Yan Zhu, Weixing Cao, Xiaojun Liu Jan 2020

Wheat Growth Monitoring And Yield Estimation Based On Multi-Rotor Unmanned Aerial Vehicle, Zhaopeng Fu, Jie Jang, Yang Gao, Brian Krienke, Meng Wang, Kaitai Zhong, Qiang Cao, Yongchao Tian, Yan Zhu, Weixing Cao, Xiaojun Liu

Department of Agronomy and Horticulture: Faculty Publications

Leaf area index (LAI) and leaf dry matter (LDM) are important indices of crop growth. Real-time, nondestructive monitoring of crop growth is instructive for the diagnosis of crop growth and prediction of grain yield. Unmanned aerial vehicle (UAV)-based remote sensing is widely used in precision agriculture due to its unique advantages in flexibility and resolution. This study was carried out on wheat trials treated with different nitrogen levels and seeding densities in three regions of Jiangsu Province in 2018–2019. Canopy spectral images were collected by the UAV equipped with a multi-spectral camera during key wheat growth stages. To verify the …