Ion composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array

This is the first study to develop an effective tool for plant sap analysis based on a solid-contact ion-selective electrode (SCISE) array, which has the advantages of on-site, direct and fast analysis. SCISEs are all-solid-state ion-selective electrodes with a conducting polymer for ion-to-electron...

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Autores principales:	Sheng-Feng Huang, Wei-Li Shih, Yi-Yi Chen, Yi-Min Wu, Lin-Chi Chen
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Solid-contact ion-selective electrode Sap analysis Pattern recognition Biotechnology TP248.13-248.65
Acceso en línea:	https://doaj.org/article/f44790d427bd4a81adcc13841a980c19
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spelling	oai:doaj.org-article:f44790d427bd4a81adcc13841a980c192021-11-24T04:34:05ZIon composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array2590-137010.1016/j.biosx.2021.100088https://doaj.org/article/f44790d427bd4a81adcc13841a980c192021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2590137021000248https://doaj.org/toc/2590-1370This is the first study to develop an effective tool for plant sap analysis based on a solid-contact ion-selective electrode (SCISE) array, which has the advantages of on-site, direct and fast analysis. SCISEs are all-solid-state ion-selective electrodes with a conducting polymer for ion-to-electron transduction. With the conducting polymer solid-contact, the electrodes perform high stability and short response time (<30 s) during potentiometric sensing. The developed SCISE array consists of potassium (SEN = 51.9 mV/decade), sodium (64.2 mV/decade), ammonium (59.3 mV/decade), calcium (32.1 mV/decade), and magnesium (33.0 mV/decade) selective electrodes. To verify the application, seven types of fresh crude vegetable leaf juices (ion concentration range: 10−3–10−4 M) were measured with the array, and the result was compared with ion chromatography. It was found that the array was able to obtain the unique, distinguishable ion composition profile as a radar plot of each vegetable sap, implying the fingerprint application of the present technology. Furthermore, applying principle component analysis (PCA) and K-means clustering, lettuces grown in different environments (deficiency either in potassium or in nitrate) are able to be discriminated. In summary, we demonstrate a tool for on-site, high-throughput and direct plant sap analysis based on SCISE array. Moreover, it could combine with pattern recognition and become a promising tools which could provide a diagnosis of the nutritive status of vegetables.Sheng-Feng HuangWei-Li ShihYi-Yi ChenYi-Min WuLin-Chi ChenElsevierarticleSolid-contact ion-selective electrodeSap analysisPattern recognitionBiotechnologyTP248.13-248.65ENBiosensors and Bioelectronics: X, Vol 9, Iss , Pp 100088- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Solid-contact ion-selective electrode Sap analysis Pattern recognition Biotechnology TP248.13-248.65
spellingShingle	Solid-contact ion-selective electrode Sap analysis Pattern recognition Biotechnology TP248.13-248.65 Sheng-Feng Huang Wei-Li Shih Yi-Yi Chen Yi-Min Wu Lin-Chi Chen Ion composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array
description	This is the first study to develop an effective tool for plant sap analysis based on a solid-contact ion-selective electrode (SCISE) array, which has the advantages of on-site, direct and fast analysis. SCISEs are all-solid-state ion-selective electrodes with a conducting polymer for ion-to-electron transduction. With the conducting polymer solid-contact, the electrodes perform high stability and short response time (<30 s) during potentiometric sensing. The developed SCISE array consists of potassium (SEN = 51.9 mV/decade), sodium (64.2 mV/decade), ammonium (59.3 mV/decade), calcium (32.1 mV/decade), and magnesium (33.0 mV/decade) selective electrodes. To verify the application, seven types of fresh crude vegetable leaf juices (ion concentration range: 10−3–10−4 M) were measured with the array, and the result was compared with ion chromatography. It was found that the array was able to obtain the unique, distinguishable ion composition profile as a radar plot of each vegetable sap, implying the fingerprint application of the present technology. Furthermore, applying principle component analysis (PCA) and K-means clustering, lettuces grown in different environments (deficiency either in potassium or in nitrate) are able to be discriminated. In summary, we demonstrate a tool for on-site, high-throughput and direct plant sap analysis based on SCISE array. Moreover, it could combine with pattern recognition and become a promising tools which could provide a diagnosis of the nutritive status of vegetables.
format	article
author	Sheng-Feng Huang Wei-Li Shih Yi-Yi Chen Yi-Min Wu Lin-Chi Chen
author_facet	Sheng-Feng Huang Wei-Li Shih Yi-Yi Chen Yi-Min Wu Lin-Chi Chen
author_sort	Sheng-Feng Huang
title	Ion composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array
title_short	Ion composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array
title_full	Ion composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array
title_fullStr	Ion composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array
title_full_unstemmed	Ion composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array
title_sort	ion composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/f44790d427bd4a81adcc13841a980c19
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_version_	1718415952875356160

Ion composition profiling and pattern recognition of vegetable sap using a solid-contact ion-selective electrode array

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