Exploiting the successive projections algorithm to improve the quantification of chemical constituents and discrimination of botanical origin of Argentinean bee-pollen
Bee-pollen as a functional food is gaining importance throughout the world because of its composition and biological properties. The protein content is one of the main parameters to determine its nutritional value, but it makes accurate labeling difficult due its high variability related to the bota...
| Autores principales: | , , , , , |
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| Formato: | info:ar-repo/semantics/artículo |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2024
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12123/16419 https://www.sciencedirect.com/science/article/pii/S0889157523007998 https://doi.org/10.1016/j.jfca.2023.105925 |
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| author | Vallese, Federico Danilo Garcia Paoloni, María Soledad Springer, Valeria Fernandes, David Douglas de Sousa Diniz, Paulo Henrique Gonçalves Dias Pistonesi, Marcelo Fabián |
| author_browse | Diniz, Paulo Henrique Gonçalves Dias Fernandes, David Douglas de Sousa Garcia Paoloni, María Soledad Pistonesi, Marcelo Fabián Springer, Valeria Vallese, Federico Danilo |
| author_facet | Vallese, Federico Danilo Garcia Paoloni, María Soledad Springer, Valeria Fernandes, David Douglas de Sousa Diniz, Paulo Henrique Gonçalves Dias Pistonesi, Marcelo Fabián |
| author_sort | Vallese, Federico Danilo |
| collection | INTA Digital |
| description | Bee-pollen as a functional food is gaining importance throughout the world because of its composition and biological properties. The protein content is one of the main parameters to determine its nutritional value, but it makes accurate labeling difficult due its high variability related to the botanical origin. Thus, this work employed near-infrared (NIR) spectroscopy and chemometrics to perform the quality control of Argentinean bee-pollen. Compared to full spectrum models, the successive projections algorithm (SPA) for selection of intervals or individual variables always achieved the best results for quantitative and qualitative approaches. For moisture and total protein content determinations, SPA coupled with partial least squares (iSPA-PLS) and multiple linear regression (SPA-MLR) achieved relative errors of prediction (REP) of 3.53% and 3.93%, respectively. For the pollen classifications, in terms of total protein content (as a dietary supplement with a cut-off higher than 20 g/100 g) and botanical origin, discriminant analysis by iSPA-PLS-DA achieved the best predictive abilities, misclassifying only one sample in the test set for both studies. The overall accuracies were 97.2% and 96.1%, respectively. Therefore, NIR spectroscopy combined with chemometrics can be used as an effective, fast, and low-cost tool for screening the quality of bee-pollen. |
| format | info:ar-repo/semantics/artículo |
| id | INTA16419 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | INTA164192024-01-02T13:23:04Z Exploiting the successive projections algorithm to improve the quantification of chemical constituents and discrimination of botanical origin of Argentinean bee-pollen Vallese, Federico Danilo Garcia Paoloni, María Soledad Springer, Valeria Fernandes, David Douglas de Sousa Diniz, Paulo Henrique Gonçalves Dias Pistonesi, Marcelo Fabián Polen Calidad Análisis Multivariante Productos de la Colmena Argentina Pollen Apidae Quality Multivariate Analysis Hive Products Abejas Bees Bee-pollen as a functional food is gaining importance throughout the world because of its composition and biological properties. The protein content is one of the main parameters to determine its nutritional value, but it makes accurate labeling difficult due its high variability related to the botanical origin. Thus, this work employed near-infrared (NIR) spectroscopy and chemometrics to perform the quality control of Argentinean bee-pollen. Compared to full spectrum models, the successive projections algorithm (SPA) for selection of intervals or individual variables always achieved the best results for quantitative and qualitative approaches. For moisture and total protein content determinations, SPA coupled with partial least squares (iSPA-PLS) and multiple linear regression (SPA-MLR) achieved relative errors of prediction (REP) of 3.53% and 3.93%, respectively. For the pollen classifications, in terms of total protein content (as a dietary supplement with a cut-off higher than 20 g/100 g) and botanical origin, discriminant analysis by iSPA-PLS-DA achieved the best predictive abilities, misclassifying only one sample in the test set for both studies. The overall accuracies were 97.2% and 96.1%, respectively. Therefore, NIR spectroscopy combined with chemometrics can be used as an effective, fast, and low-cost tool for screening the quality of bee-pollen. EEA Hilario Ascasubi Fil: Vallese, Federico Danilo. Universidad Nacional del Sur. Departamento de Química. INQUISUR; Argentina Fil: Vallese, Federico Danilo. Consejo Nacional de Investigaciones Científicas y Técnicas. INQUISUR; Argentina Fil: Garcia Paoloni, María Soledad. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Hilario Ascasubi; Argentina Fil: Springer, Valeria. Universidad Nacional del Sur. Departamento de Química. INQUISUR; Argentina Fil: Springer, Valeria. Consejo Nacional de Investigaciones Científicas y Técnicas. INQUISUR; Argentina Fil: Fernandes, David Douglas de Sousa. Universidade Estadual da Paraíba. CCT. Departamento de Química; Brasil Fil: Diniz, Paulo Henrique Gonçalves Dias. Universidade Federal do Oeste da Bahia. Programa de Pós-Graduação em Química Pura e Aplicada; Brasil Fil: Pistonesi, Marcelo Fabián. Universidad Nacional del Sur. Departamento de Química. INQUISUR; Argentina Fil: Pistonesi, Marcelo Fabián. Consejo Nacional de Investigaciones Científicas y Técnicas. INQUISUR; Argentina 2024-01-02T13:20:03Z 2024-01-02T13:20:03Z 2024-02 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/16419 https://www.sciencedirect.com/science/article/pii/S0889157523007998 0889-1575 1096-0481 https://doi.org/10.1016/j.jfca.2023.105925 eng info:eu-repo/semantics/restrictedAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Argentina .......... (nation) (World, South America) 7006477 Elsevier Journal of Food Composition and Analysis 126 : 105925. (February 2024) |
| spellingShingle | Polen Calidad Análisis Multivariante Productos de la Colmena Argentina Pollen Apidae Quality Multivariate Analysis Hive Products Abejas Bees Vallese, Federico Danilo Garcia Paoloni, María Soledad Springer, Valeria Fernandes, David Douglas de Sousa Diniz, Paulo Henrique Gonçalves Dias Pistonesi, Marcelo Fabián Exploiting the successive projections algorithm to improve the quantification of chemical constituents and discrimination of botanical origin of Argentinean bee-pollen |
| title | Exploiting the successive projections algorithm to improve the quantification of chemical constituents and discrimination of botanical origin of Argentinean bee-pollen |
| title_full | Exploiting the successive projections algorithm to improve the quantification of chemical constituents and discrimination of botanical origin of Argentinean bee-pollen |
| title_fullStr | Exploiting the successive projections algorithm to improve the quantification of chemical constituents and discrimination of botanical origin of Argentinean bee-pollen |
| title_full_unstemmed | Exploiting the successive projections algorithm to improve the quantification of chemical constituents and discrimination of botanical origin of Argentinean bee-pollen |
| title_short | Exploiting the successive projections algorithm to improve the quantification of chemical constituents and discrimination of botanical origin of Argentinean bee-pollen |
| title_sort | exploiting the successive projections algorithm to improve the quantification of chemical constituents and discrimination of botanical origin of argentinean bee pollen |
| topic | Polen Calidad Análisis Multivariante Productos de la Colmena Argentina Pollen Apidae Quality Multivariate Analysis Hive Products Abejas Bees |
| url | http://hdl.handle.net/20.500.12123/16419 https://www.sciencedirect.com/science/article/pii/S0889157523007998 https://doi.org/10.1016/j.jfca.2023.105925 |
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