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Non-destructive analysis of germination percentage, germination energy and simple vigour index on wheat seeds during storage by Vis/NIR and SWIR hyperspectral imaging.
Spectrochim Acta A Mol Biomol Spectrosc. 2020 Oct 05; 239:118488.SA

Abstract

Two hyperspectral imaging (HSI) systems, visible/near infrared (Vis/NIR, 304-1082 nm) and short wave infrared (SWIR, 930-2548 nm), were used for the first time to comprehensively predict the changes in quality of wheat seeds based on three vigour parameters: germination percentage (GP, reflecting the number of germinated seedling), germination energy (GE, reflecting the speed and uniformity of seedling emergence), and simple vigour index (SVI, reflecting germination percentage and seedling weight). Each sample contained a small number of wheat seeds, which were obtained by high temperature and humidity-accelerated aging (0, 2, and 3 days) to simulate storage. The spectra of these samples were collected using HSI systems. After collection, each seed sample underwent a standard germination test to determine their GP, GE, and SVI. Then, several pretreatment methods and the partial least-squares regression algorithm (PLS-R) were used to establish quantitative models. The models for the Vis/NIR region obtained excellent performance, and most effective wavelengths (EWs) were selected in the Vis/NIR region by the successive projections algorithm (SPA) and regression coefficients (RC). Subsequently, PLS-R-RC models using selected wavebands (sixteen wavebands for GP, 14 wavebands for GE, and 16 wavebands for SVI) exhibited similar performance to the PLS-R models based on the full wavebands. The best R2 results obtained in the simplified models' prediction sets were 0.921, 0.907, and 0.886, with RMSE values of 4.113%, 5.137%, and 0.024, for GP, GE, and SVI, respectively. Distribution maps of GP, GE, and SVI were produced by applying these simplified PLS models. By interpreting the EWs and building prediction models, soluble protein and sugar content were demonstrated to have a relationship with spectral information. In summary, the present results lay a foundation towards the development of a significantly simpler, more comprehensive, and non-destructive hyperspectral-based sorting system for determining the vigour of wheat seeds.

Authors+Show Affiliations

Department of Plant Genetics and Breeding, College of Agriculture, China Agricultural University/Beijing Key Laboratory of Crop Genetic Improvement/The Innovation Center (Beijing) of Crop Seed Sciences Ministry of Agriculture, Beijing 100193, China. Electronic address: ztt_cau@outlook.com.Beijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China. Electronic address: fansx@nercita.org.cn.Department of Plant Genetics and Breeding, College of Agriculture, China Agricultural University/Beijing Key Laboratory of Crop Genetic Improvement/The Innovation Center (Beijing) of Crop Seed Sciences Ministry of Agriculture, Beijing 100193, China. Electronic address: xiangyingying@cau.edu.cn.Department of Plant Genetics and Breeding, College of Agriculture, China Agricultural University/Beijing Key Laboratory of Crop Genetic Improvement/The Innovation Center (Beijing) of Crop Seed Sciences Ministry of Agriculture, Beijing 100193, China. Electronic address: szhang@csu.edu.au.Department of Plant Genetics and Breeding, College of Agriculture, China Agricultural University/Beijing Key Laboratory of Crop Genetic Improvement/The Innovation Center (Beijing) of Crop Seed Sciences Ministry of Agriculture, Beijing 100193, China. Electronic address: wangjh63@cau.edu.cn.Department of Plant Genetics and Breeding, College of Agriculture, China Agricultural University/Beijing Key Laboratory of Crop Genetic Improvement/The Innovation Center (Beijing) of Crop Seed Sciences Ministry of Agriculture, Beijing 100193, China. Electronic address: sunqun@cau.edu.cn.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32470809

Citation

Zhang, Tingting, et al. "Non-destructive Analysis of Germination Percentage, Germination Energy and Simple Vigour Index On Wheat Seeds During Storage By Vis/NIR and SWIR Hyperspectral Imaging." Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy, vol. 239, 2020, p. 118488.
Zhang T, Fan S, Xiang Y, et al. Non-destructive analysis of germination percentage, germination energy and simple vigour index on wheat seeds during storage by Vis/NIR and SWIR hyperspectral imaging. Spectrochim Acta A Mol Biomol Spectrosc. 2020;239:118488.
Zhang, T., Fan, S., Xiang, Y., Zhang, S., Wang, J., & Sun, Q. (2020). Non-destructive analysis of germination percentage, germination energy and simple vigour index on wheat seeds during storage by Vis/NIR and SWIR hyperspectral imaging. Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy, 239, 118488. https://doi.org/10.1016/j.saa.2020.118488
Zhang T, et al. Non-destructive Analysis of Germination Percentage, Germination Energy and Simple Vigour Index On Wheat Seeds During Storage By Vis/NIR and SWIR Hyperspectral Imaging. Spectrochim Acta A Mol Biomol Spectrosc. 2020 Oct 5;239:118488. PubMed PMID: 32470809.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Non-destructive analysis of germination percentage, germination energy and simple vigour index on wheat seeds during storage by Vis/NIR and SWIR hyperspectral imaging. AU - Zhang,Tingting, AU - Fan,Shuxiang, AU - Xiang,Yingying, AU - Zhang,Shujie, AU - Wang,Jianhua, AU - Sun,Qun, Y1 - 2020/05/16/ PY - 2020/01/27/received PY - 2020/04/26/revised PY - 2020/05/13/accepted PY - 2020/5/30/pubmed PY - 2021/5/15/medline PY - 2020/5/30/entrez KW - Distribution maps KW - Effective wavelengths KW - Hyperspectral imaging KW - SWIR KW - Seed vigour KW - Vis/NIR SP - 118488 EP - 118488 JF - Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy JO - Spectrochim Acta A Mol Biomol Spectrosc VL - 239 N2 - Two hyperspectral imaging (HSI) systems, visible/near infrared (Vis/NIR, 304-1082 nm) and short wave infrared (SWIR, 930-2548 nm), were used for the first time to comprehensively predict the changes in quality of wheat seeds based on three vigour parameters: germination percentage (GP, reflecting the number of germinated seedling), germination energy (GE, reflecting the speed and uniformity of seedling emergence), and simple vigour index (SVI, reflecting germination percentage and seedling weight). Each sample contained a small number of wheat seeds, which were obtained by high temperature and humidity-accelerated aging (0, 2, and 3 days) to simulate storage. The spectra of these samples were collected using HSI systems. After collection, each seed sample underwent a standard germination test to determine their GP, GE, and SVI. Then, several pretreatment methods and the partial least-squares regression algorithm (PLS-R) were used to establish quantitative models. The models for the Vis/NIR region obtained excellent performance, and most effective wavelengths (EWs) were selected in the Vis/NIR region by the successive projections algorithm (SPA) and regression coefficients (RC). Subsequently, PLS-R-RC models using selected wavebands (sixteen wavebands for GP, 14 wavebands for GE, and 16 wavebands for SVI) exhibited similar performance to the PLS-R models based on the full wavebands. The best R2 results obtained in the simplified models' prediction sets were 0.921, 0.907, and 0.886, with RMSE values of 4.113%, 5.137%, and 0.024, for GP, GE, and SVI, respectively. Distribution maps of GP, GE, and SVI were produced by applying these simplified PLS models. By interpreting the EWs and building prediction models, soluble protein and sugar content were demonstrated to have a relationship with spectral information. In summary, the present results lay a foundation towards the development of a significantly simpler, more comprehensive, and non-destructive hyperspectral-based sorting system for determining the vigour of wheat seeds. SN - 1873-3557 UR - https://www.unboundmedicine.com/medline/citation/32470809/Non_destructive_analysis_of_germination_percentage_germination_energy_and_simple_vigour_index_on_wheat_seeds_during_storage_by_Vis/NIR_and_SWIR_hyperspectral_imaging_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1386-1425(20)30467-4 DB - PRIME DP - Unbound Medicine ER -