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Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer

This work aims to propose an alternative methodology to measure acidity index and chlorophyll content in ground soybean grains using an ultra-compact near-infrared (NIR) spectrometer. Experiment was conducted using 592 soybean samples for acidity index and 348 for chlorophyll content, harvested in s...

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Principais autores: dos Santos, Larissa da Rocha, Silva, Núbia Oliveira, Zangirolami, Marcela de Souza, Leme, Luiza Mariano, Valderrama, Patrícia, Março, Paulo Henrique
Formato: Artigo
Idioma: Inglês
Publicado em: Universidade Tecnológica Federal do Paraná (UTFPR) 2019
Acesso em linha: http://periodicos.utfpr.edu.br/rebrapa/article/view/12190
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spelling peri-article-121902021-01-18T16:48:25Z Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer dos Santos, Larissa da Rocha Silva, Núbia Oliveira Zangirolami, Marcela de Souza Leme, Luiza Mariano Valderrama, Patrícia Março, Paulo Henrique 5.07.01.06-1Avaliação e Controle de Qualidade de Alimentos fast analysis; ultra-compact NIR; PLS; chemometric methods; industrial improvements; food analysis. This work aims to propose an alternative methodology to measure acidity index and chlorophyll content in ground soybean grains using an ultra-compact near-infrared (NIR) spectrometer. Experiment was conducted using 592 soybean samples for acidity index and 348 for chlorophyll content, harvested in southern Brazil. A partial least squares (PLS) model was developed for both parameters, being optimized by outlier detection and validated through its merit figures. For the acid index model the root mean squared error for calibration (RMSEC) was 0.1974 and validation (RMSEP) 0.1694, correlation coefficient (Rcal) 0.8589. Moreover, residual prediction deviation for calibration (RPDcal; 1.7661) and validation (RPDval; 1.8525) were also determined. The results for chlorophyll content were RMSEC (623.2972 mg kg-1) and RMSEP (621.9778 mg kg-1), Rcal (0.8709), RPDcal (1.5956) and RPDval (1.6295). Results suggest that the NIR spectroscopy can be used to provide a suitable tool for the measurement of the acidity index and the chlorophyll content of the soybean, bringing a significant improvement mainly on the speed of analysis, what is an important goal to industrial routine purposes, besides advantages as non-invasively and non-destructive characteristics, exempt from waste generation and chemical reagents, being a potential alternative methodology for online monitoring in the soybean processing industries. Universidade Tecnológica Federal do Paraná (UTFPR) Capes e CNPQ 2019-12-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf http://periodicos.utfpr.edu.br/rebrapa/article/view/12190 10.3895/rebrapa.v10n4.12190 Brazilian Journal of Food Research; v. 10, n. 4 (2019); 1-17 Brazilian Journal of Food Research; v. 10, n. 4 (2019); 1-17 2448-3184 10.3895/rebrapa.v10n4 eng http://periodicos.utfpr.edu.br/rebrapa/article/view/12190/pdf Direitos autorais 2020 CC-BY http://creativecommons.org/licenses/by/4.0
institution Universidade Tecnológica Federal do Paraná
collection PERI
language Inglês
format Artigo
author dos Santos, Larissa da Rocha
Silva, Núbia Oliveira
Zangirolami, Marcela de Souza
Leme, Luiza Mariano
Valderrama, Patrícia
Março, Paulo Henrique
spellingShingle dos Santos, Larissa da Rocha
Silva, Núbia Oliveira
Zangirolami, Marcela de Souza
Leme, Luiza Mariano
Valderrama, Patrícia
Março, Paulo Henrique
Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer
author_sort dos Santos, Larissa da Rocha
title Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer
title_short Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer
title_full Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer
title_fullStr Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer
title_full_unstemmed Fast determination of acidity index and chlorophyll in soybean grains through an Ultra-Compact Near-infrared spectrometer
title_sort fast determination of acidity index and chlorophyll in soybean grains through an ultra-compact near-infrared spectrometer
description This work aims to propose an alternative methodology to measure acidity index and chlorophyll content in ground soybean grains using an ultra-compact near-infrared (NIR) spectrometer. Experiment was conducted using 592 soybean samples for acidity index and 348 for chlorophyll content, harvested in southern Brazil. A partial least squares (PLS) model was developed for both parameters, being optimized by outlier detection and validated through its merit figures. For the acid index model the root mean squared error for calibration (RMSEC) was 0.1974 and validation (RMSEP) 0.1694, correlation coefficient (Rcal) 0.8589. Moreover, residual prediction deviation for calibration (RPDcal; 1.7661) and validation (RPDval; 1.8525) were also determined. The results for chlorophyll content were RMSEC (623.2972 mg kg-1) and RMSEP (621.9778 mg kg-1), Rcal (0.8709), RPDcal (1.5956) and RPDval (1.6295). Results suggest that the NIR spectroscopy can be used to provide a suitable tool for the measurement of the acidity index and the chlorophyll content of the soybean, bringing a significant improvement mainly on the speed of analysis, what is an important goal to industrial routine purposes, besides advantages as non-invasively and non-destructive characteristics, exempt from waste generation and chemical reagents, being a potential alternative methodology for online monitoring in the soybean processing industries.
publisher Universidade Tecnológica Federal do Paraná (UTFPR)
publishDate 2019
url http://periodicos.utfpr.edu.br/rebrapa/article/view/12190
_version_ 1805450362950254592
score 10,814766

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