Low-cost system for multispectral image acquisition and its applicability to analysis of the physiological potential of soybean seeds

IF 1.2 4区 农林科学 Q3 AGRONOMY
Júlia Martins Soares, A. D. Medeiros, D. T. Pinheiro, J. Rosas, L. J. Silva, Daniel Lucas Magalhães Machado, D. Dias
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引用次数: 1

Abstract

The use of multispectral images has great potential to assess seed quality and represents a significant technological advance in the search for fast and non-destructive analysis techniques. However, the devices currently available are expensive. Thus, this study aimed to propose a low-cost method for acquisition and processing of multispectral images of soybean seeds and to evaluate their potential for rapid determination of seed physiological potential. The study was conducted in three steps: implementation of the multispectral image acquisition system, development of an algorithm for automatic image processing, and evaluation of the relationship between the data obtained through image analysis and the results of standard tests used to evaluate seed physiological potential. A total of 43 variables were assessed, eight related to seed physiological potential (germination and vigor) and 35 obtained from the analysis of the multispectral images. Of the variables obtained from multispectral images, 21 were related to pixel values in the images in the different bands evaluated (green, red, and infrared) and 14 associated with seed morphometric characteristics. The proposed system is efficient in obtaining multispectral images and the algorithm developed was efficient to extract morphometric characteristics and pixel information from the images. The parameters obtained from the NIR spectrum region showed a good relationship with the physiological potential of soybean seeds.
低成本多光谱图像采集系统及其在大豆种子生理潜能分析中的适用性
多光谱图像的使用在评估种子质量方面具有很大的潜力,并且代表了在寻找快速和非破坏性分析技术方面的重大技术进步。然而,目前可用的设备都很昂贵。因此,本研究旨在提出一种低成本获取和处理大豆种子多光谱图像的方法,并评估其在快速测定种子生理电位方面的潜力。研究分三步进行:实现多光谱图像采集系统,开发图像自动处理算法,评估通过图像分析获得的数据与用于评估种子生理潜能的标准测试结果之间的关系。共评估了43个变量,其中8个与种子生理势(发芽和活力)有关,35个来自多光谱图像分析。在多光谱图像中获得的变量中,21个与不同波段(绿色、红色和红外)图像中的像素值相关,14个与种子形态特征相关。该系统能够有效地获取多光谱图像,所开发的算法能够有效地提取图像的形态特征和像素信息。在近红外光谱区得到的参数与大豆种子的生理电位有很好的关系。
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来源期刊
Acta Scientiarum. Agronomy.
Acta Scientiarum. Agronomy. Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
2.40
自引率
0.00%
发文量
45
审稿时长
>12 weeks
期刊介绍: The journal publishes original articles in all areas of Agronomy, including soil sciences, agricultural entomology, soil fertility and manuring, soil physics, physiology of cultivated plants, phytopathology, phyto-health, phytotechny, genesis, morphology and soil classification, management and conservation of soil, integrated management of plant pests, vegetal improvement, agricultural microbiology, agricultural parasitology, production and processing of seeds.
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