High-Throughput UAV Image-Based Method Is More Precise Than Manual Rating of Herbicide Tolerance
作者机构：Department of Plant SciencesCollege of Agriculture and BioresourcesUniversity of Saskatchewan51 Campus DriveSaskatoonSKCanada
出 版 物：《Plant Phenomics》 (植物表型组学（英文）)
年 卷 期：2019年第1卷第1期
页 面：133-141页
核心收录：
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：The authors wouldalso like to acknowledge the Saskatchewan Pulse Growers Global Institute of Food Security(GIFS) and Canada First Research Excellence Fund (CFREF)for providing fundingfor this project
摘 要：The traditional visual rating system is labor-intensive,time-consuming,and prone to human *** aerial vehicle(UAV)imagery-based vegetation indices(VI)have potential applications in high-throughput plant *** study objective is to determine if UAV imagery provides accurate and consistent estimations of crop injury from herbicide application and its potential as an alternative to visual *** study was conducted at the Kernen Crop Research Farm,University of Saskatchewan in 2016 and ***(Vicia faba L.)crop tolerance to nine herbicide tank mixtures was evaluated with 2 rates distributed in a randomized complete block design(RCBD)with 4 *** trial was imaged using a multispectral camera with a ground sample distance(GSD)of 1.2 cm,one week after the treatment *** ratings of growth reduction and physiological chlorosis were recorded simultaneously with *** optimized soil-adjusted vegetation index(OSAVI)was calculated from the thresholded *** UAV-based vegetation index(OSAVI)produced more precise results compared to visual ratings for both *** coefficient of variation(CV)of OSAVI was~1%when compared to 18-43%for the visual ***,Tukey’s honestly significance difference(HSD)test yielded a more precise mean separation for the UAV-based vegetation index than visual *** significant correlations between OSAVI and the visual ratings from the study suggest that undesirable variability associated with visual assessments can be minimized with the UAVbased ***-based imagery methods had greater precision than the visual-based ratings for crop herbicide *** methods have the potential to replace visual ratings and aid in screening crops for herbicide tolerance.
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