Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system
Tomatoes have different water requirements in each growing period. Excessive water use or insufficient water supply will affect the growth and yield of tomato plants. Therefore, precise irrigation control is necessary during cultivation to increase crop productivity. Traditionally, the soil moist...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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ASABE
2022
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/7149/1/J14156_b00ba3d32b05a48804d88da2e78ec6f7.pdf |
| _version_ | 1825710323851591680 |
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| author | h Tung, Chih Tung Ping, Lang Yen Chao-Yin Tsai1,, Yin Tsai Pauline Ong, Pauline Jer-Wei Lin1, Wei Lin Yung, Huei Chang Chen, Suming |
| author_facet | h Tung, Chih Tung Ping, Lang Yen Chao-Yin Tsai1,, Yin Tsai Pauline Ong, Pauline Jer-Wei Lin1, Wei Lin Yung, Huei Chang Chen, Suming |
| author_sort | h Tung, Chih Tung |
| collection | UTHM |
| description | Tomatoes have different water requirements in each growing period. Excessive water use or insufficient water
supply will affect the growth and yield of tomato plants. Therefore, precise irrigation control is necessary during cultivation
to increase crop productivity. Traditionally, the soil moisture content or leaf water potential has been used as an indicator
of plant water status. These methods, however, have limited accuracy and are time-consuming, making it difficult to be put
into practice in tomato production. This study developed an online hyperspectral imaging system to measure the leaf water
potential of tomato nondestructively. Linear Discriminant Analysis was utilized to automatically and quickly extract the leaf
images, with the recognition accuracy of 94.68% was achieved. The mathematical processing of Standard Normal Variate
scattering correction was used to remove the spectral variations caused by the defocused leave images. The developed leaf
water potential prediction model based on the spectral image information attained using the developed system achieved the
standard error of calibration of 0.201, coefficient of determination in calibration set of 0.814 and standard error of cross�validation of 0.230, and one minus the variance ratio of 0.755. The obtained performance indicated the feasibility of apply�ing the developed online hyperspectral imaging system as a real-time non-destructive measurement technique for the leaf
water potential of tomato plants. |
| first_indexed | 2024-03-05T21:55:52Z |
| format | Article |
| id | uthm.eprints-7149 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:55:52Z |
| publishDate | 2022 |
| publisher | ASABE |
| record_format | dspace |
| spelling | uthm.eprints-71492022-06-14T02:09:05Z http://eprints.uthm.edu.my/7149/ Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system h Tung, Chih Tung Ping, Lang Yen Chao-Yin Tsai1,, Yin Tsai Pauline Ong, Pauline Jer-Wei Lin1, Wei Lin Yung, Huei Chang Chen, Suming T Technology (General) Tomatoes have different water requirements in each growing period. Excessive water use or insufficient water supply will affect the growth and yield of tomato plants. Therefore, precise irrigation control is necessary during cultivation to increase crop productivity. Traditionally, the soil moisture content or leaf water potential has been used as an indicator of plant water status. These methods, however, have limited accuracy and are time-consuming, making it difficult to be put into practice in tomato production. This study developed an online hyperspectral imaging system to measure the leaf water potential of tomato nondestructively. Linear Discriminant Analysis was utilized to automatically and quickly extract the leaf images, with the recognition accuracy of 94.68% was achieved. The mathematical processing of Standard Normal Variate scattering correction was used to remove the spectral variations caused by the defocused leave images. The developed leaf water potential prediction model based on the spectral image information attained using the developed system achieved the standard error of calibration of 0.201, coefficient of determination in calibration set of 0.814 and standard error of cross�validation of 0.230, and one minus the variance ratio of 0.755. The obtained performance indicated the feasibility of apply�ing the developed online hyperspectral imaging system as a real-time non-destructive measurement technique for the leaf water potential of tomato plants. ASABE 2022 Article PeerReviewed text en http://eprints.uthm.edu.my/7149/1/J14156_b00ba3d32b05a48804d88da2e78ec6f7.pdf h Tung, Chih Tung and Ping, Lang Yen and Chao-Yin Tsai1,, Yin Tsai and Pauline Ong, Pauline and Jer-Wei Lin1, Wei Lin and Yung, Huei Chang and Chen, Suming (2022) Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system. Applied Engineering in Agriculture, 38 (2). pp. 273-282. https://doi.org/10.13031/aea.14800 |
| spellingShingle | T Technology (General) h Tung, Chih Tung Ping, Lang Yen Chao-Yin Tsai1,, Yin Tsai Pauline Ong, Pauline Jer-Wei Lin1, Wei Lin Yung, Huei Chang Chen, Suming Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system |
| title | Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system |
| title_full | Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system |
| title_fullStr | Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system |
| title_full_unstemmed | Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system |
| title_short | Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system |
| title_sort | nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/7149/1/J14156_b00ba3d32b05a48804d88da2e78ec6f7.pdf |
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