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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...

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Main Authors:	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
Format:	Article
Language:	English
Published:	ASABE 2022
Subjects:	T Technology (General)
Online Access:	http://eprints.uthm.edu.my/7149/1/J14156_b00ba3d32b05a48804d88da2e78ec6f7.pdf http://eprints.uthm.edu.my/7149/ https://doi.org/10.13031/aea.14800
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spelling	my.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
institution	Universiti Tun Hussein Onn Malaysia
building	UTHM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tun Hussein Onn Malaysia
content_source	UTHM Institutional Repository
url_provider	http://eprints.uthm.edu.my/
language	English
topic	T Technology (General)
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
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.
format	Article
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
title	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_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_sort	nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system
publisher	ASABE
publishDate	2022
url	http://eprints.uthm.edu.my/7149/1/J14156_b00ba3d32b05a48804d88da2e78ec6f7.pdf http://eprints.uthm.edu.my/7149/ https://doi.org/10.13031/aea.14800
_version_	1738581582619344896
score	13.223943

Nondestructive quantitative analysis of water potential of tomato leaves using online hyperspectral imaging system

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