Rapid Non-Destructive Detection of Rice Seed Vigor via Terahertz Spectroscopy

Jun Hu (), Sijie Xu, Zhikai Huang, Wennan Liu, Jiahao Zheng and Yuxi Liao
Additional contact information
Jun Hu: School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
Sijie Xu: School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
Zhikai Huang: School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
Wennan Liu: School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
Jiahao Zheng: School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China
Yuxi Liao: School of Mechatronics & Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China

Agriculture, 2024, vol. 15, issue 1, 1-19

Abstract: Rice seed vigor significantly impacts yield, making the selection of high-vigor seeds crucial for agricultural production. Traditional methods for assessing seed vigor are time-consuming and destructive. This study aimed to develop a rapid, non-destructive method for evaluating rice seed vigor using terahertz spectroscopy. Rice seeds with varying vigor levels were prepared through high-temperature and high-humidity aging and classified into high-, low-, and non-vigorous groups based on germination performance. Terahertz transmission imaging (0.1–3 THz) was conducted on 420 seeds, and spectral data were preprocessed using several advanced data processing techniques, including competitive adaptive reweighting (CARS), uninformative variable elimination (UVE), and principal component analysis (PCA). Three chemometric models, namely random forest (RF), K-nearest neighbors (KNN), and partial least squares–discriminant analysis (PLS-DA), were established. The model based on CARS-KNN after band selection achieved the highest prediction accuracy of 97.14%. The results indicate that terahertz spectroscopy combined with band selection methods provides a reliable, non-destructive approach for rice seed vigor assessment, offering significant potential for agricultural quality control.

Keywords: terahertz technology; crop seeds; band selection; random forest; partial least squares–discriminant analysis; K-nearest neighbors (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/15/1/34/pdf (application/pdf)
https://www.mdpi.com/2077-0472/15/1/34/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:15:y:2024:i:1:p:34-:d:1553963

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().