利用激光传感器阵列测量农作物高度的可行性和可靠性

IF 7.7 Q1 AGRICULTURE, MULTIDISCIPLINARY
Pejman Alighaleh , Tarahom Mesri Gundoshmian , Saeed Alighaleh , Abbas Rohani
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引用次数: 0

摘要

作物高度测量被广泛用于分析和估计作物的整体状况和生物量产量。大规模的人工测量不仅耗时,而且不实用。此外,虽然有先进的设备,但它们需要技术技能,对小农户来说并不合理。本文研究了利用激光技术监测水稻和小麦作物高度的简单、低成本测量系统的可行性。经过设计和制造,该系统在实验室和农场进行了测试和评估。在实验室,测量了水稻的高度;在田间,高度检测系统测量了小麦的高度。结果表明,人工测量与高度检测系统测量之间的判定系数(R2),水稻为 0.96,小麦为 0.85。此外,在 5%的水平上,两个数据集之间没有明显差异。因此,该系统可以成为监测不同生长阶段作物高度的有用而准确的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feasibility and reliability of agricultural crop height measurement using the laser sensor array

Crop height measurement is widely used to analyze and estimate the overall crop condition and the amount of biomass production. Not only is manual measurement on a large scale time-consuming but also it is not practical. Besides, advanced equipment is available but they require technical skills and are not reasonable for smallholders. This article investigates the feasibility of a simple and low-cost measurement system that can monitor crops height of paddy rice and wheat using laser technology. After designing and fabricating, this system was tested and evaluated in both laboratory and farm sections. In the laboratory, paddy rice height was measured, and in the field section, the height detection system measured wheat height. The results showed that the coefficient of determination (R2) between manual measurement and height detection system measurement for paddy rice was 0.96 and for wheat was 0.85. Besides, there was no significant difference between the two datasets at the level of 5%. Hence, this system can be a useful and accurate tool to monitor crops height in different growing steps.

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来源期刊
Information Processing in Agriculture
Information Processing in Agriculture Agricultural and Biological Sciences-Animal Science and Zoology
CiteScore
21.10
自引率
0.00%
发文量
80
期刊介绍: Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining
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