Identification and Classification of Buckwheat Grain by Microfocus Radiography and Hyperspectral Imaging Methods

IF 0.9 4区 材料科学 Q4 MATERIALS SCIENCE, CHARACTERIZATION & TESTING
Yu. T. Platov, S. L. Beletskii, D. A. Metlenkin, R. A. Platova, A. L. Vereshchagin, V. A. Marin
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Abstract

Classification of buckwheat grains is important because the absence of defective grains is a guarantee of yield and quality. Buckwheat grains were randomly selected from a batch with grains that varied in quality. The identification and classification of buckwheat grains according to the degree of fulfillment was carried out by a combination of microfocus X-ray and hyperspectral image analysis and multivariate analysis techniques. Using microfocus radiography, buckwheat grains were categorized into groups according to the degree of fulfillment. Hyperspectral image of buckwheat grains in the range of 935–1720 nm was acquired using a Specim FX17 camera. Using the polygon selection function, the averaged spectra were obtained and a data matrix of grain samples was generated. The bands of the spectrum contributing most to the grading of the grain samples by the degree of fulfillment were identified using the principal component analysis. The classification model of grading buckwheat grain into groups by the degree of fulfillment was constructed by partial least squares discriminant analysis method. The results showed that hyperspectral image is a potential tool for rapid and accurate identification of buckwheat grains, which can be used in large-scale grain classification and grain quality determination.

Abstract Image

Abstract Image

用微聚焦射线照相法和高光谱成像法对荞麦粒进行识别和分类
摘要 荞麦谷粒的分类非常重要,因为没有缺陷谷粒是产量和质量的保证。荞麦谷粒是从一批质量参差不齐的谷粒中随机挑选出来的。采用微焦 X 射线和高光谱图像分析以及多元分析技术,根据荞麦粒的合格程度对其进行鉴定和分类。利用微焦射线照相术,根据荞麦颗粒的饱满程度将其分为不同的组别。使用 Specim FX17 相机获取了荞麦粒在 935-1720 纳米范围内的高光谱图像。使用多边形选择功能获得了平均光谱,并生成了谷物样本的数据矩阵。利用主成分分析法确定了光谱中对谷物样品的饱满度分级贡献最大的波段。利用偏最小二乘法判别分析方法构建了荞麦谷物满足度分级模型。结果表明,高光谱图像是快速准确识别荞麦粒的潜在工具,可用于大规模谷物分类和谷物品质测定。
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来源期刊
Russian Journal of Nondestructive Testing
Russian Journal of Nondestructive Testing 工程技术-材料科学:表征与测试
CiteScore
1.60
自引率
44.40%
发文量
59
审稿时长
6-12 weeks
期刊介绍: Russian Journal of Nondestructive Testing, a translation of Defectoskopiya, is a publication of the Russian Academy of Sciences. This publication offers current Russian research on the theory and technology of nondestructive testing of materials and components. It describes laboratory and industrial investigations of devices and instrumentation and provides reviews of new equipment developed for series manufacture. Articles cover all physical methods of nondestructive testing, including magnetic and electrical; ultrasonic; X-ray and Y-ray; capillary; liquid (color luminescence), and radio (for materials of low conductivity).
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