作物
农学
粮食产量
环境科学
比例(比率)
排
产量(工程)
扎梅斯
农业工程
遥感
生物
计算机科学
地理
工程类
地图学
材料科学
数据库
冶金
作者
Jinshui Zhang,Bruno Basso,Richard F. Price,Gregory Putman,Guanyuan Shuai
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2018-04-20
卷期号:13 (4): e0195223-e0195223
被引量:35
标识
DOI:10.1371/journal.pone.0195223
摘要
Distance between rows and plants are essential parameters that affect the final grain yield in row crops. This paper presents the results of research intended to develop a novel method to quantify the distance between maize plants at field scale using an Unmanned Aerial Vehicle (UAV). Using this method, we can recognize maize plants as objects and calculate the distance between plants. We initially developed our method by training an algorithm in an indoor facility with plastic corn plants. Then, the method was scaled up and tested in a farmer's field with maize plant spacing that exhibited natural variation. The results of this study demonstrate that it is possible to precisely quantify the distance between maize plants. We found that accuracy of the measurement of the distance between maize plants depended on the height above ground level at which UAV imagery was taken. This study provides an innovative approach to quantify plant-to-plant variability and, thereby final crop yield estimates.
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