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UAS imaging-based decision tools for arid winter wheat and irrigated potato production management

机译:基于UAS影像的干旱冬小麦和灌溉马铃薯生产管理决策工具

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摘要

Small unmanned aerial systems (UAS) are gaining global attention for rapid image-based decision making in agricultural production. In this study, the aim was to evaluate UAS-based imagery for rapid assessment of wheat winter survival and spring stand in winter wheat production and crop necrosis in potato production. Both are critical aspects of field (arid) and row (irrigated) crop farming practices. Aerial images from 97 hard and 352 soft single nucleotide polymorphism winter wheat plots, and 32 potato field plots (with 1 and 2 years of green manure applications) were acquired using a multi-band imaging sensor integrated with UAS. The UAS-based imagery was useful in evaluating winter wheat plant winter survival and spring stand, with Pearson correlation coefficient (r) in the range 0.60-0.82 between imagery and ground reference data. Similarly, the image-based potato field necrosis assessment showed a strong relationship with ground reference data (r = 0.93 and 0.88 for 1 and 2 years of green manure application, respectively). Overall, UAS imagery provided quantifiable, timely, and unbiased field data with high spatial resolution (about 2.3 cm/pixel for images acquired at 100 m altitude) that can aid in field and row crop production decision making.
机译:小型无人机系统(UAS)在农业生产中基于图像的快速决策方面正受到全球关注。在这项研究中,目的是评估基于UAS的图像,以快速评估小麦的冬季存活率和春季小麦产量以及马铃薯生产中的作物坏死的春季林分。两者都是田间(干旱)和行(灌溉)作物种植实践的关键方面。使用集成有UAS的多波段成像传感器,可以获取来自97个硬和352个单核苷酸多态性冬小麦田地和32个马铃薯田地(应用1年和2年绿肥)的航拍图。基于UAS的图像可用于评估冬小麦植物的冬季存活率和春季林分,图像与地面参考数据之间的Pearson相关系数(r)在0.60-0.82范围内。同样,基于图像的马铃薯田间坏死评估显示与地面参考数据有很强的相关性(分别施用1年和2年绿肥,r = 0.93和0.88)。总体而言,UAS影像提供了可量化,及时且无偏差的田间数据,具有较高的空间分辨率(对于在100 m高度采集的图像,大约为2.3 cm /像素),可以帮助进行田间和行间作物生产决策。

著录项

  • 来源
    《International journal of remote sensing》 |2016年第2期|125-137|共13页
  • 作者单位

    Washington State Univ, Irrigated Agr Res & Extens Ctr, Ctr Precis & Automated Agr Syst, Prosser, WA 99350 USA|Washington State Univ, Dept Biol Syst Engn, Pullman, WA 99164 USA;

    Washington State Univ, Dept Biol Syst Engn, Pullman, WA 99164 USA;

    Washington State Univ, Dept Crop & Soil Sci, Pullman, WA 99164 USA;

    Washington State Univ, Dept Plant Pathol, Pullman, WA 99164 USA;

    Washington State Univ, Dept Crop & Soil Sci, Pullman, WA 99164 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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