Snapshot-Based Visible-Near Infrared Multispectral Imaging for Early Screening of Heat Injury during Growth of Chinese Cabbage
Heat stress in particular can damage physiological processes, adaptation, cellular homeostasis, and yield of higher plants. Early detection of heat stress in leafy crops is critical for preventing extensive loss of crop productivity for global food security. Thus, this study aimed to evaluate the po...
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MDPI AG
2022-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/18/9340 |
| _version_ | 1797491392513048576 |
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| author | Geonwoo Kim Hoonsoo Lee Seung Hwan Wi Byoung-Kwan Cho |
| author_facet | Geonwoo Kim Hoonsoo Lee Seung Hwan Wi Byoung-Kwan Cho |
| author_sort | Geonwoo Kim |
| collection | DOAJ |
| description | Heat stress in particular can damage physiological processes, adaptation, cellular homeostasis, and yield of higher plants. Early detection of heat stress in leafy crops is critical for preventing extensive loss of crop productivity for global food security. Thus, this study aimed to evaluate the potential of a snapshot-based visible-near infrared multispectral imaging system for detecting the early stage of heat injury during the growth of Chinese cabbage. Two classification models based on partial least squares-discriminant analysis (PLS-DA) and least-squares support vector machine (LS-SVM) were developed to identify heat stress. Various vegetation indices (VIs), including the normalized difference vegetation index (NDVI), red-edge ratio (RE/R), and photochemical reflectance index (PRI), which are closely related to plant heat stress, were acquired from sample images, and their values were compared with the developed models for the evaluation of their discriminant performance of developed models. The highest classification accuracies for LS-SVM, PLS-DA, NDVI, RE/R, and PRI were 93.6%, 92.4%, 72.5%, 69.6%, and 58.1%, respectively, without false-positive errors. Among these methods for identifying plant heat stress, the developed LS-SVM and PLS-DA models showed more reliable discriminant performance than the traditional VIs. This clearly demonstrates that the developed models are much more effective and efficient predictive tools for detecting heat stress in Chinese cabbage in the early stages compared to conventional methods. The developed technique shows promise as an accurate and cost-effective screening tool for rapid identification of heat stress in Chinese cabbage. |
| first_indexed | 2024-03-10T00:47:47Z |
| format | Article |
| id | doaj.art-2636dc2bf0cd4f76bcf03e1292b1fefc |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T00:47:47Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-2636dc2bf0cd4f76bcf03e1292b1fefc2023-11-23T14:57:00ZengMDPI AGApplied Sciences2076-34172022-09-011218934010.3390/app12189340Snapshot-Based Visible-Near Infrared Multispectral Imaging for Early Screening of Heat Injury during Growth of Chinese CabbageGeonwoo Kim0Hoonsoo Lee1Seung Hwan Wi2Byoung-Kwan Cho3Department of Bio-Industrial Machinery Engineering, College of Agriculture and Life Science, Gyeongsang National University, 501 Jinju-daero, Jinju-si 52828, KoreaDepartment of Biosystems Engineering, College of Agriculture, Life & Environment Science, Chungbuk National University, Chungdae-ro, Seowon-gu, Cheongju 28644, KoreaVegetable Research Division, National Institute of Horticultural & Herbal Science, Wanju 55365, KoreaDepartment of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseoung-gu, Daejeon 305-764, KoreaHeat stress in particular can damage physiological processes, adaptation, cellular homeostasis, and yield of higher plants. Early detection of heat stress in leafy crops is critical for preventing extensive loss of crop productivity for global food security. Thus, this study aimed to evaluate the potential of a snapshot-based visible-near infrared multispectral imaging system for detecting the early stage of heat injury during the growth of Chinese cabbage. Two classification models based on partial least squares-discriminant analysis (PLS-DA) and least-squares support vector machine (LS-SVM) were developed to identify heat stress. Various vegetation indices (VIs), including the normalized difference vegetation index (NDVI), red-edge ratio (RE/R), and photochemical reflectance index (PRI), which are closely related to plant heat stress, were acquired from sample images, and their values were compared with the developed models for the evaluation of their discriminant performance of developed models. The highest classification accuracies for LS-SVM, PLS-DA, NDVI, RE/R, and PRI were 93.6%, 92.4%, 72.5%, 69.6%, and 58.1%, respectively, without false-positive errors. Among these methods for identifying plant heat stress, the developed LS-SVM and PLS-DA models showed more reliable discriminant performance than the traditional VIs. This clearly demonstrates that the developed models are much more effective and efficient predictive tools for detecting heat stress in Chinese cabbage in the early stages compared to conventional methods. The developed technique shows promise as an accurate and cost-effective screening tool for rapid identification of heat stress in Chinese cabbage.https://www.mdpi.com/2076-3417/12/18/9340nondestructive evaluationChinese cabbagesnapshot multispectral imagingheat stressvisible-near infrared |
| spellingShingle | Geonwoo Kim Hoonsoo Lee Seung Hwan Wi Byoung-Kwan Cho Snapshot-Based Visible-Near Infrared Multispectral Imaging for Early Screening of Heat Injury during Growth of Chinese Cabbage Applied Sciences nondestructive evaluation Chinese cabbage snapshot multispectral imaging heat stress visible-near infrared |
| title | Snapshot-Based Visible-Near Infrared Multispectral Imaging for Early Screening of Heat Injury during Growth of Chinese Cabbage |
| title_full | Snapshot-Based Visible-Near Infrared Multispectral Imaging for Early Screening of Heat Injury during Growth of Chinese Cabbage |
| title_fullStr | Snapshot-Based Visible-Near Infrared Multispectral Imaging for Early Screening of Heat Injury during Growth of Chinese Cabbage |
| title_full_unstemmed | Snapshot-Based Visible-Near Infrared Multispectral Imaging for Early Screening of Heat Injury during Growth of Chinese Cabbage |
| title_short | Snapshot-Based Visible-Near Infrared Multispectral Imaging for Early Screening of Heat Injury during Growth of Chinese Cabbage |
| title_sort | snapshot based visible near infrared multispectral imaging for early screening of heat injury during growth of chinese cabbage |
| topic | nondestructive evaluation Chinese cabbage snapshot multispectral imaging heat stress visible-near infrared |
| url | https://www.mdpi.com/2076-3417/12/18/9340 |
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