Feasibility analysis of NIR for detecting sweet corn seeds vigor |
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| Institution: | 1. Department of Physics and Astronomy, Catania University, Catania, Italy;2. Laboratori Nazionali del Sud, Istituto Nazionale di Fisica Nucleare, Catania, Italy;3. Facoltà di Ingegneria e Architettura, Università di Enna Kore, Enna, Italy;4. Department of Agriculture, Food and Environment, Catania University, Catania, Italy;1. China Agricultural University, 17 Tsinghua East Road, Beijing 100083, China;2. Accurate Agricultural Technology Integrated Research Base of Ministry of Agriculture (Fisheries), 17 Tsinghua East Road, Beijing 100083, China;3. Beijing Agricultural Internet of Things Engineering Research Center, 17 Tsinghua East Road, Beijing 100083, China;1. Department of Biological Engineering, Jinan University, Huangpu Road West 601, Tianhe District, Guangzhou 510632, China;2. Department of Optoelectronic Engineering, Jinan University, Huangpu Road West 601, Tianhe District, Guangzhou 510632, China |
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| Abstract: | This paper explores the feasibility of particle-based detection and grading of seed vigor based on a self-built seed single-granulation device using near infrared spectroscopy (NIRS). Sweet corn with uniform kernel size was used for this study. The seed samples were divided into three types, they were normal seeds, artificially aged seeds and heat-damaged seeds. A 2-part spectral acquisition of each seed were performed, one for the collection of seeds that fall into the detection zone within the separation pipe, another was on the static platform, whose collection was performed on 5 faces of each seed. Partial least squares discriminant analysis (PLS-DA) was used to classify the original data of the seeds. In the 2 parts, the discriminant results of the unprocessed normal seeds and the artificial accelerated aging seeds, the untreated normal seeds and the heat-damaged seeds showed that classification accuracy was higher than 98%. The research indicates that the spectral data of different positions of seeds can reflect their activity information, and it is feasible to detect and classify seeds in real time in the detection area of the separation pipeline. |
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| Keywords: | Corn seed Near infrared spectroscopy Vigor detection Discrimination NIRS"} {"#name":"keyword" "$":{"id":"kwrd0035"} "$$":[{"#name":"text" "_":"near infrared spectroscopy PLS"} {"#name":"keyword" "$":{"id":"kwrd0045"} "$$":[{"#name":"text" "_":"partial least squares PLS-DA"} {"#name":"keyword" "$":{"id":"kwrd0055"} "$$":[{"#name":"text" "_":"partial least squares discriminant analysis |
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