Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy
Early control of fruit quality requires reliable and rapid determination techniques. Therefore, the food industry has a growing interest in non-destructive methods such as spectroscopy. The aim of this study was to evaluate the feasibility of visible and near-infrared (NIR) spectroscopy, in combinat...
| Autores principales: | , , , , , , , , |
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| Formato: | acceptedVersion |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2017
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.11939/5727 http://www.sciencedirect.com/science/article/pii/S0260877417300626 |
| _version_ | 1855032324675076096 |
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| author | Cortés, Victoria Rodríguez-Ortega, Alejandro Blasco, José Rey, Beatriz Besada, Cristina Cubero, Sergio Salvador, Alejandra Talens, Pau Aleixos, Nuria |
| author_browse | Aleixos, Nuria Besada, Cristina Blasco, José Cortés, Victoria Cubero, Sergio Rey, Beatriz Rodríguez-Ortega, Alejandro Salvador, Alejandra Talens, Pau |
| author_facet | Cortés, Victoria Rodríguez-Ortega, Alejandro Blasco, José Rey, Beatriz Besada, Cristina Cubero, Sergio Salvador, Alejandra Talens, Pau Aleixos, Nuria |
| author_sort | Cortés, Victoria |
| collection | ReDivia |
| description | Early control of fruit quality requires reliable and rapid determination techniques. Therefore, the food industry has a growing interest in non-destructive methods such as spectroscopy. The aim of this study was to evaluate the feasibility of visible and near-infrared (NIR) spectroscopy, in combination with multivariate analysis techniques, to predict the level and changes of astringency in intact and in the flesh of half cut persimmon fruits. The fruits were harvested and exposed to different treatments with 95 % CO2 at 20 ºC for 0, 6, 12, 18 and 24 h to obtain samples with different levels of astringency. A set of 98 fruits was used to develop the predictive models based on their spectral data and another external set of 42 fruit samples was used to validate the models. The models were created using the partial least squares regression (PLSR), support vector machine (SVM) and least squares support vector machine (LS-SVM). In general, the models with the best performance were those which included standard normal variate (SNV) in the pre-processing. The best model was the PLSR developed with SNV along with the first derivative (1-Der) pre-processing, created using the data obtained at six measurement points of the intact fruits and all wavelengths (R2=0.904 and RPD=3.26). Later, a successive projection algorithm (SPA) was applied to select the most effective wavelengths (EWs). Using the six points of measurement of the intact fruit and SNV together with the direct orthogonal signal correction (DOSC) pre-processing in the NIR spectra, 41 EWs were selected, achieving an R2 of 0.915 and an RPD of 3.46 for the PLSR model. These results suggest that this technology has potential for use as a feasible and cost-effective method for the non-destructive determination of astringency in persimmon fruits. |
| format | acceptedVersion |
| id | ReDivia5727 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | ReDivia57272025-04-25T14:44:40Z Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy Cortés, Victoria Rodríguez-Ortega, Alejandro Blasco, José Rey, Beatriz Besada, Cristina Cubero, Sergio Salvador, Alejandra Talens, Pau Aleixos, Nuria Diospyros kaki, fruit internal quality, soluble tannins, near-infrared spectroscopy, chemometrics Early control of fruit quality requires reliable and rapid determination techniques. Therefore, the food industry has a growing interest in non-destructive methods such as spectroscopy. The aim of this study was to evaluate the feasibility of visible and near-infrared (NIR) spectroscopy, in combination with multivariate analysis techniques, to predict the level and changes of astringency in intact and in the flesh of half cut persimmon fruits. The fruits were harvested and exposed to different treatments with 95 % CO2 at 20 ºC for 0, 6, 12, 18 and 24 h to obtain samples with different levels of astringency. A set of 98 fruits was used to develop the predictive models based on their spectral data and another external set of 42 fruit samples was used to validate the models. The models were created using the partial least squares regression (PLSR), support vector machine (SVM) and least squares support vector machine (LS-SVM). In general, the models with the best performance were those which included standard normal variate (SNV) in the pre-processing. The best model was the PLSR developed with SNV along with the first derivative (1-Der) pre-processing, created using the data obtained at six measurement points of the intact fruits and all wavelengths (R2=0.904 and RPD=3.26). Later, a successive projection algorithm (SPA) was applied to select the most effective wavelengths (EWs). Using the six points of measurement of the intact fruit and SNV together with the direct orthogonal signal correction (DOSC) pre-processing in the NIR spectra, 41 EWs were selected, achieving an R2 of 0.915 and an RPD of 3.46 for the PLSR model. These results suggest that this technology has potential for use as a feasible and cost-effective method for the non-destructive determination of astringency in persimmon fruits. 2017-08-04T13:56:51Z 2017-08-04T13:56:51Z 2017 acceptedVersion Cortés V, Rodríguez A, Blasco J, Rey B, Besada C, Cubero S, Salvador A, Talens P, Aleixos N (2017). Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy. Journal of Food Engineering, 204, 27-37. http://hdl.handle.net/20.500.11939/5727 10.1016/j.jfoodeng.2017.02.017 http://www.sciencedirect.com/science/article/pii/S0260877417300626 en Info:eu-repo/grantAgreement/MINECO/Programa Nacional de Investigación Fundamental/RTA2012-00062-C04-01 Info:eu-repo/grantAgreement/MINECO/Programa Nacional de Investigación Fundamental/RTA2012-00062-C04-03 Info:eu-repo/grantAgreement/MINECO/Programa Nacional de Investigación Fundamental/RTA2013-00043-C02 This work has been partially funded by the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria de España (INIA) through research projects RTA2012-00062-C04-01, RTA2012-00062-C04-03 and RTA2013-00043-C02 with the support of European FEDER funds and by the Conselleria d' Educació, Investigació, Cultura i Esport, Generalitat Valenciana, through the project AICO/2015/122. Elsevier electronico |
| spellingShingle | Diospyros kaki, fruit internal quality, soluble tannins, near-infrared spectroscopy, chemometrics Cortés, Victoria Rodríguez-Ortega, Alejandro Blasco, José Rey, Beatriz Besada, Cristina Cubero, Sergio Salvador, Alejandra Talens, Pau Aleixos, Nuria Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy |
| title | Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy |
| title_full | Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy |
| title_fullStr | Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy |
| title_full_unstemmed | Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy |
| title_short | Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy |
| title_sort | prediction of the level of astringency in persimmon using visible and near infrared spectroscopy |
| topic | Diospyros kaki, fruit internal quality, soluble tannins, near-infrared spectroscopy, chemometrics |
| url | http://hdl.handle.net/20.500.11939/5727 http://www.sciencedirect.com/science/article/pii/S0260877417300626 |
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