期刊
SENSORS AND ACTUATORS B-CHEMICAL
卷 229, 期 -, 页码 534-544出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2016.02.015
关键词
Seed viability; Hyperspectral imaging; Partial least-squares discriminant analysis (PLSDA); Variable selection methods; Germination ability; Muskmelon seeds
资金
- Golden Seed Project, Ministry of Agriculture, Food and Rural Affairs (MAFRA)
- Ministry of Oceans and Fisheries (MOF)
- Rural Development Administration (RDA)
- Korea Forest Service (KFS)
- Technology Commercialization Support Program, Ministry of Agriculture, Food and Rural Affairs (MAFRA), Republic of Korea
- Institute of Planning & Evaluation for Technology in Food, Agriculture, Forestry & Fisheries (iPET), Republic of Korea [213002043SBY10, 113044033SB010] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
A near-infrared (NIR) hyperspectral imaging (HSI) system was used to predict viability and vigor (in term of germination periods) in muskmelon seeds. Hyperspectral images of muskmelon seeds were acquired using a NIR push-broom HSI system covering the spectral range of 948-2494 nm. After NIR spectra collection, all seeds underwent a germination test to confirm their viability and vigor. The spectra from seeds with 3 and 5 germination days and nongerminated seeds were further used for development of a classification model of partial least-squares discriminant analysis (PLSDA). Most effective wavelengths were selected using three model-based variable selection methods, i.e., variable important in projection (VIP), selectivity ratio (SR), and significance multivariate correlation (sMC), which selected 23, 18, and 19 optimal variables, respectively, from full set of 208 variables. The selected variables from different waveband selection methods were found genuine and significant for interpreting the prediction results of seed viability and vigor. Subsequently, the PLS-DA model was constructed using individual VIP-, SR-, or sMC-selected variables. The results demonstrated that the PLSDA model developed with the selected optimal variables from the different methods provided comparable results for the calibration set; however, the PLSDA-SR method afforded the highest classification accuracy (94.6%) for a validation set used to determine the viability and vigor of muskmelon seeds. The wavelengths selected by the different methods represents chemical components of the seed and the attribute of germination ability was chosen most often. (c) 2016 Elsevier B.V. All rights reserved.
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