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基于作物信号和多视角成像的大豆幼苗自动定位。

Automatic Localization of Soybean Seedlings Based on Crop Signaling and Multi-View Imaging.

机构信息

College of Engineering, China Agricultural University, Haidian, Beijing 100083, China.

出版信息

Sensors (Basel). 2024 May 11;24(10):3066. doi: 10.3390/s24103066.

Abstract

Soybean is grown worldwide for its high protein and oil content. Weeds compete fiercely for resources, which affects soybean yields. Because of the progressive enhancement of weed resistance to herbicides and the quickly increasing cost of manual weeding, mechanical weed control is becoming the preferred method of weed control. Mechanical weed control finds it difficult to remove intra-row weeds due to the lack of rapid and precise weed/soybean detection and location technology. Rhodamine B (Rh-B) is a systemic crop compound that can be absorbed by soybeans which fluoresces under a specific excitation light. The purpose of this study is to combine systemic crop compounds and computer vision technology for the identification and localization of soybeans in the field. The fluorescence distribution properties of systemic crop compounds in soybeans and their effects on plant growth were explored. The fluorescence was mainly concentrated in soybean cotyledons treated with Rh-B. After a comparison of soybean seedlings treated with nine groups of rhodamine B solutions at different concentrations ranging from 0 to 1440 ppm, the soybeans treated with 180 ppm Rh-B for 24 h received the recommended dosage, resulting in significant fluorescence that did not affect crop growth. Increasing the Rh-B solutions reduced crop biomass, while prolonged treatment times reduced seed germination. The fluorescence produced lasted for 20 days, ensuring a stable signal in the early stages of growth. Additionally, a precise inter-row soybean plant location system based on a fluorescence imaging system with a 96.7% identification accuracy, determined on 300 datasets, was proposed. This article further confirms the potential of crop signaling technology to assist machines in achieving crop identification and localization in the field.

摘要

大豆因其高蛋白和高油含量而在全球范围内种植。杂草为争夺资源而激烈竞争,这会影响大豆的产量。由于杂草对除草剂的抗性逐渐增强,以及人工除草成本的快速增加,机械除草正成为杂草控制的首选方法。由于缺乏快速、精确的杂草/大豆检测和定位技术,机械除草很难去除行间杂草。罗丹明 B(Rh-B)是一种系统作物化合物,可被大豆吸收,在特定的激发光下发出荧光。本研究旨在将系统作物化合物和计算机视觉技术结合起来,用于识别和定位田间的大豆。探讨了系统作物化合物在大豆中的荧光分布特性及其对植物生长的影响。荧光主要集中在经 Rh-B 处理的大豆子叶上。在比较了浓度范围为 0 至 1440 ppm 的 9 组 Rh-B 溶液处理的大豆幼苗后,发现用 180 ppm Rh-B 处理 24 小时的大豆接受了推荐剂量,产生了显著的荧光,而不会影响作物生长。增加 Rh-B 溶液会降低作物生物量,而延长处理时间会降低种子发芽率。荧光产生可持续 20 天,在生长初期可确保稳定的信号。此外,还提出了一种基于荧光成像系统的精确行间大豆植株定位系统,该系统在 300 个数据集上的识别准确率为 96.7%。本文进一步证实了作物信号技术有潜力帮助机器在田间实现作物识别和定位。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee90/11125097/a34c9c0a4547/sensors-24-03066-g001.jpg

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