Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in Fertilizer

The rise in population growth worldwide requires efficient management of agricultural lands through the correct determination of authentic fertilizers. In this current study, a rapid on-site detection technique was developed by using portable NIR spectroscopy in the wavelength range of 740–1070 nm t...

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Main Authors: Ernest Teye, Charles L. Y. Amuah, Kofi Atiah, Ransford Opoku Darko, Kwadwo Kusi Amoah, Emmanuel Afutu, Rebecca Owusu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Spectroscopy
Online Access:http://dx.doi.org/10.1155/2022/1412526
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author Ernest Teye
Charles L. Y. Amuah
Kofi Atiah
Ransford Opoku Darko
Kwadwo Kusi Amoah
Emmanuel Afutu
Rebecca Owusu
author_facet Ernest Teye
Charles L. Y. Amuah
Kofi Atiah
Ransford Opoku Darko
Kwadwo Kusi Amoah
Emmanuel Afutu
Rebecca Owusu
author_sort Ernest Teye
collection DOAJ
description The rise in population growth worldwide requires efficient management of agricultural lands through the correct determination of authentic fertilizers. In this current study, a rapid on-site detection technique was developed by using portable NIR spectroscopy in the wavelength range of 740–1070 nm together with optimum multivariate algorithms to identify fertilizer integrity (unexpired, expired, and adulterated) as well as quantify the levels (10–50%) of adulteration. NIR models were built based on support vector machine (SVM) and random forest (RF) for identification, while different types of partial least square regression (PLS, iPLS, Si-PLS, and GaPLS) were used for quantification purposes. The models were evaluated according to identification rate (Rt), coefficient of correlation in prediction (Rpre2), and root mean square error of prediction (RMSEP). For the identification of the integrity of the fertilizer, among the mathematical pretreatments used, the first derivative (FD) together with SVM gave above 99.20% identification rate in both calibration and prediction sets. For the quantification of the adulterants, Si-PLS was found to be superior and showed an excellent predictive potential of Rpre2 = 0.95–0.98 and RMSEP = 0.069–0.11 for the two fertilizer types used. The overall results indicated that a handheld NIR spectrometer together with appropriate algorithms could be employed for fast and on-site determination of fertilizer integrity.
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institution Kabale University
issn 2314-4939
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publishDate 2022-01-01
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spelling doaj-art-096093f09e09467cbee247875856f5262025-02-03T01:00:44ZengWileyJournal of Spectroscopy2314-49392022-01-01202210.1155/2022/1412526Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in FertilizerErnest Teye0Charles L. Y. Amuah1Kofi Atiah2Ransford Opoku Darko3Kwadwo Kusi Amoah4Emmanuel Afutu5Rebecca Owusu6University of Cape CoastUniversity of Cape CoastUniversity of Cape CoastUniversity of Cape CoastUniversity of Cape CoastUniversity of Cape CoastUniversity of Cape CoastThe rise in population growth worldwide requires efficient management of agricultural lands through the correct determination of authentic fertilizers. In this current study, a rapid on-site detection technique was developed by using portable NIR spectroscopy in the wavelength range of 740–1070 nm together with optimum multivariate algorithms to identify fertilizer integrity (unexpired, expired, and adulterated) as well as quantify the levels (10–50%) of adulteration. NIR models were built based on support vector machine (SVM) and random forest (RF) for identification, while different types of partial least square regression (PLS, iPLS, Si-PLS, and GaPLS) were used for quantification purposes. The models were evaluated according to identification rate (Rt), coefficient of correlation in prediction (Rpre2), and root mean square error of prediction (RMSEP). For the identification of the integrity of the fertilizer, among the mathematical pretreatments used, the first derivative (FD) together with SVM gave above 99.20% identification rate in both calibration and prediction sets. For the quantification of the adulterants, Si-PLS was found to be superior and showed an excellent predictive potential of Rpre2 = 0.95–0.98 and RMSEP = 0.069–0.11 for the two fertilizer types used. The overall results indicated that a handheld NIR spectrometer together with appropriate algorithms could be employed for fast and on-site determination of fertilizer integrity.http://dx.doi.org/10.1155/2022/1412526
spellingShingle Ernest Teye
Charles L. Y. Amuah
Kofi Atiah
Ransford Opoku Darko
Kwadwo Kusi Amoah
Emmanuel Afutu
Rebecca Owusu
Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in Fertilizer
Journal of Spectroscopy
title Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in Fertilizer
title_full Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in Fertilizer
title_fullStr Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in Fertilizer
title_full_unstemmed Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in Fertilizer
title_short Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in Fertilizer
title_sort feasibility study on the use of a portable nir spectrometer and multivariate data analysis to discriminate and quantify adulteration in fertilizer
url http://dx.doi.org/10.1155/2022/1412526
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