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Irrigated pinto bean crop stress and yield assessment using ground based low altitude remote sensing technology

Information Processing in Agriculture 2019年第4期6卷 502-514页

作者： Rakesh Ranjan Abhilash KChandel Lav R.Khot haitham ybahlol Jianfeng Zhou Rick ABoydston Phillip NMiklas Department of Biological Systems Engineering Washington State UniversityPullmanWAUSA Center for Precision and Automated Agricultural Systems IARECWashington State UniversityProsserWAUSA USDA-ARS Grain Legume Genetics and Physiology Research Unit ProsserWA USA

The pinto bean is one of widely consumed legume crop that constitutes over 42%of the U.S dry bean ***,limited studies have been conducted in past to assess its quantitative and qualitative yield *** remote sensing technologies can help in such ***,this study evaluates the role of ground-based multispectral imagery derived vegetation indices(VIs)for irrigated the pinto bean stress and yield *** were eight cultivars of the pinto bean grown under conventional and strip tillage treatments and irrigated at 52%and 100%of required *** data was acquired using a five-band multispectral imager at early,mid and late growth *** used 25 broadband VIs were derived to capture crop stress traits and yield *** component analysis and Spearman’s rank correlation tests were conducted to identify key VIs and their correlation(rs)with abiotic stress at each growth *** difference vegetation index,nonlinear vegetation index(NLI),modified NLI and infrared percentage vegetation index(IPVI)were consistent in accounting the stress response and crop yield at all growth stages(rs>0.60,coefficient of determination(R2):0.50–0.56,P<0.05).Ten other VIs significantly accounted for crop stress at early and late ***,identified key VIs may be helpful to growers for precise crop management decision making and breeders for crop stress response and yield assessments.

关键词： Pinto bean Multispectral imaging Vegetation indices Stress assessment Yield potential

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