Peroxidase Activity in Tomato Leaf Cells under Salt Stress Based on Micro-Hyperspectral Imaging Technique

Salt stress has become a major problem in the tomato planting process, of which peroxidase (POD) activity is an important parameter reflecting the antioxidant capacity of plants. In order to explore the dynamic changes of catalase in leaves under different concentrations of NaCl stress, it is necess...
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Autor*in:	Longguo Wu [verfasserIn] Qiufei Jiang [verfasserIn] Yao Zhang [verfasserIn] Minghua Du [verfasserIn] Ling Ma [verfasserIn] Yan Ma [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	microscopic hyperspectral imaging technique tomato leaf salt stress peroxidase activity

Übergeordnetes Werk:	In: Horticulturae - MDPI AG, 2017, 8(2022), 9, p 813
Übergeordnetes Werk:	volume:8 ; year:2022 ; number:9, p 813

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/horticulturae8090813

Katalog-ID:	DOAJ034087257

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520			\|a Salt stress has become a major problem in the tomato planting process, of which peroxidase (POD) activity is an important parameter reflecting the antioxidant capacity of plants. In order to explore the dynamic changes of catalase in leaves under different concentrations of NaCl stress, it is necessary to establish a rapid detection technology for changes of POD activity in micro-areas of leaves. In this study, a total of 139 microscopic images were obtained under different concentrations of salt stress (0 g/L, 1 g/L, 2 g/L, 3 g/L) in the spectral range of 400–1000 nm. Regions of interest were extracted according to the reflectance of the samples, and the model was established by combining POD activity. Various spectral pre-treatment combined with partial least-squares regression models was compared to original spectrum combined with partial least-squares regression model. The characteristic wavelength was extracted by four methods, and partial least-squares regression (PLSR) and principal component regression (PCR) were established according to the characteristic wavelength. The results show that multiple scattering correction (MSC) is optimized as the pre-treatment method. The partial least-squares regression model based on the interval variable iterative space contraction method is the best, and the coefficient of determination and root mean square error of prediction set (RMSEP) are 0.66 and 18.94 U/g·min, respectively. The results show that it is feasible to detect the peroxidase activity in tomato leaves by micro-hyperspectral imaging combined with stoichiometry.
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spelling	10.3390/horticulturae8090813 doi (DE-627)DOAJ034087257 (DE-599)DOAJdb5fd8a8be5b4c3f8d56f7186d6c4a06 DE-627 ger DE-627 rakwb eng SB1-1110 Longguo Wu verfasserin aut Peroxidase Activity in Tomato Leaf Cells under Salt Stress Based on Micro-Hyperspectral Imaging Technique 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Salt stress has become a major problem in the tomato planting process, of which peroxidase (POD) activity is an important parameter reflecting the antioxidant capacity of plants. In order to explore the dynamic changes of catalase in leaves under different concentrations of NaCl stress, it is necessary to establish a rapid detection technology for changes of POD activity in micro-areas of leaves. In this study, a total of 139 microscopic images were obtained under different concentrations of salt stress (0 g/L, 1 g/L, 2 g/L, 3 g/L) in the spectral range of 400–1000 nm. Regions of interest were extracted according to the reflectance of the samples, and the model was established by combining POD activity. Various spectral pre-treatment combined with partial least-squares regression models was compared to original spectrum combined with partial least-squares regression model. The characteristic wavelength was extracted by four methods, and partial least-squares regression (PLSR) and principal component regression (PCR) were established according to the characteristic wavelength. The results show that multiple scattering correction (MSC) is optimized as the pre-treatment method. The partial least-squares regression model based on the interval variable iterative space contraction method is the best, and the coefficient of determination and root mean square error of prediction set (RMSEP) are 0.66 and 18.94 U/g·min, respectively. The results show that it is feasible to detect the peroxidase activity in tomato leaves by micro-hyperspectral imaging combined with stoichiometry. microscopic hyperspectral imaging technique tomato leaf salt stress peroxidase activity Plant culture Qiufei Jiang verfasserin aut Yao Zhang verfasserin aut Minghua Du verfasserin aut Ling Ma verfasserin aut Yan Ma verfasserin aut In Horticulturae MDPI AG, 2017 8(2022), 9, p 813 (DE-627)820684155 (DE-600)2813983-5 23117524 nnns volume:8 year:2022 number:9, p 813 https://doi.org/10.3390/horticulturae8090813 kostenfrei https://doaj.org/article/db5fd8a8be5b4c3f8d56f7186d6c4a06 kostenfrei https://www.mdpi.com/2311-7524/8/9/813 kostenfrei https://doaj.org/toc/2311-7524 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 8 2022 9, p 813
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language	English
source	In Horticulturae 8(2022), 9, p 813 volume:8 year:2022 number:9, p 813
sourceStr	In Horticulturae 8(2022), 9, p 813 volume:8 year:2022 number:9, p 813
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	microscopic hyperspectral imaging technique tomato leaf salt stress peroxidase activity Plant culture
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container_title	Horticulturae
authorswithroles_txt_mv	Longguo Wu @@aut@@ Qiufei Jiang @@aut@@ Yao Zhang @@aut@@ Minghua Du @@aut@@ Ling Ma @@aut@@ Yan Ma @@aut@@
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callnumber-first	S - Agriculture
author	Longguo Wu
spellingShingle	Longguo Wu misc SB1-1110 misc microscopic hyperspectral imaging technique misc tomato leaf misc salt stress misc peroxidase activity misc Plant culture Peroxidase Activity in Tomato Leaf Cells under Salt Stress Based on Micro-Hyperspectral Imaging Technique
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topic_title	SB1-1110 Peroxidase Activity in Tomato Leaf Cells under Salt Stress Based on Micro-Hyperspectral Imaging Technique microscopic hyperspectral imaging technique tomato leaf salt stress peroxidase activity
topic	misc SB1-1110 misc microscopic hyperspectral imaging technique misc tomato leaf misc salt stress misc peroxidase activity misc Plant culture
topic_unstemmed	misc SB1-1110 misc microscopic hyperspectral imaging technique misc tomato leaf misc salt stress misc peroxidase activity misc Plant culture
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title	Peroxidase Activity in Tomato Leaf Cells under Salt Stress Based on Micro-Hyperspectral Imaging Technique
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title_full	Peroxidase Activity in Tomato Leaf Cells under Salt Stress Based on Micro-Hyperspectral Imaging Technique
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author_browse	Longguo Wu Qiufei Jiang Yao Zhang Minghua Du Ling Ma Yan Ma
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title_sort	peroxidase activity in tomato leaf cells under salt stress based on micro-hyperspectral imaging technique
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title_auth	Peroxidase Activity in Tomato Leaf Cells under Salt Stress Based on Micro-Hyperspectral Imaging Technique
abstract	Salt stress has become a major problem in the tomato planting process, of which peroxidase (POD) activity is an important parameter reflecting the antioxidant capacity of plants. In order to explore the dynamic changes of catalase in leaves under different concentrations of NaCl stress, it is necessary to establish a rapid detection technology for changes of POD activity in micro-areas of leaves. In this study, a total of 139 microscopic images were obtained under different concentrations of salt stress (0 g/L, 1 g/L, 2 g/L, 3 g/L) in the spectral range of 400–1000 nm. Regions of interest were extracted according to the reflectance of the samples, and the model was established by combining POD activity. Various spectral pre-treatment combined with partial least-squares regression models was compared to original spectrum combined with partial least-squares regression model. The characteristic wavelength was extracted by four methods, and partial least-squares regression (PLSR) and principal component regression (PCR) were established according to the characteristic wavelength. The results show that multiple scattering correction (MSC) is optimized as the pre-treatment method. The partial least-squares regression model based on the interval variable iterative space contraction method is the best, and the coefficient of determination and root mean square error of prediction set (RMSEP) are 0.66 and 18.94 U/g·min, respectively. The results show that it is feasible to detect the peroxidase activity in tomato leaves by micro-hyperspectral imaging combined with stoichiometry.
abstractGer	Salt stress has become a major problem in the tomato planting process, of which peroxidase (POD) activity is an important parameter reflecting the antioxidant capacity of plants. In order to explore the dynamic changes of catalase in leaves under different concentrations of NaCl stress, it is necessary to establish a rapid detection technology for changes of POD activity in micro-areas of leaves. In this study, a total of 139 microscopic images were obtained under different concentrations of salt stress (0 g/L, 1 g/L, 2 g/L, 3 g/L) in the spectral range of 400–1000 nm. Regions of interest were extracted according to the reflectance of the samples, and the model was established by combining POD activity. Various spectral pre-treatment combined with partial least-squares regression models was compared to original spectrum combined with partial least-squares regression model. The characteristic wavelength was extracted by four methods, and partial least-squares regression (PLSR) and principal component regression (PCR) were established according to the characteristic wavelength. The results show that multiple scattering correction (MSC) is optimized as the pre-treatment method. The partial least-squares regression model based on the interval variable iterative space contraction method is the best, and the coefficient of determination and root mean square error of prediction set (RMSEP) are 0.66 and 18.94 U/g·min, respectively. The results show that it is feasible to detect the peroxidase activity in tomato leaves by micro-hyperspectral imaging combined with stoichiometry.
abstract_unstemmed	Salt stress has become a major problem in the tomato planting process, of which peroxidase (POD) activity is an important parameter reflecting the antioxidant capacity of plants. In order to explore the dynamic changes of catalase in leaves under different concentrations of NaCl stress, it is necessary to establish a rapid detection technology for changes of POD activity in micro-areas of leaves. In this study, a total of 139 microscopic images were obtained under different concentrations of salt stress (0 g/L, 1 g/L, 2 g/L, 3 g/L) in the spectral range of 400–1000 nm. Regions of interest were extracted according to the reflectance of the samples, and the model was established by combining POD activity. Various spectral pre-treatment combined with partial least-squares regression models was compared to original spectrum combined with partial least-squares regression model. The characteristic wavelength was extracted by four methods, and partial least-squares regression (PLSR) and principal component regression (PCR) were established according to the characteristic wavelength. The results show that multiple scattering correction (MSC) is optimized as the pre-treatment method. The partial least-squares regression model based on the interval variable iterative space contraction method is the best, and the coefficient of determination and root mean square error of prediction set (RMSEP) are 0.66 and 18.94 U/g·min, respectively. The results show that it is feasible to detect the peroxidase activity in tomato leaves by micro-hyperspectral imaging combined with stoichiometry.
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title_short	Peroxidase Activity in Tomato Leaf Cells under Salt Stress Based on Micro-Hyperspectral Imaging Technique
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