Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy
The feasibility of using visible and near-infrared spectroscopy technology combined with multivariate analysis to discriminate cv. ‘Big Top’ and cv. ‘Diamond Ray’ nectarines has been studied. These varieties are very difficult to differentiate visually on the production line but show important diffe...
| Autores principales: | , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
| Publicado: |
2018
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| Acceso en línea: | http://hdl.handle.net/20.500.11939/6034 http://www.sciencedirect.com/science/article/pii/S0925521417303721 |
| _version_ | 1855492005689294848 |
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| author | Cortés, Victoria Cubero, Sergio Aleixos, Nuria Blasco, José Talens, Pau |
| author_browse | Aleixos, Nuria Blasco, José Cortés, Victoria Cubero, Sergio Talens, Pau |
| author_facet | Cortés, Victoria Cubero, Sergio Aleixos, Nuria Blasco, José Talens, Pau |
| author_sort | Cortés, Victoria |
| collection | ReDivia |
| description | The feasibility of using visible and near-infrared spectroscopy technology combined with multivariate analysis to discriminate cv. ‘Big Top’ and cv. ‘Diamond Ray’ nectarines has been studied. These varieties are very difficult to differentiate visually on the production line but show important differences in taste that affects the acceptance by final consumers. The relationship between the diffuse reflectance spectra and the two nectarine varieties was established. Five hundred nectarine samples (250 of each variety) were used for the study. Tests were performed by using a spectrometer capable of measuring in two different spectral ranges (600–1100nm and 900–1700nm). These spectral ranges were used to develop two accurate classification models based on linear discriminate analysis (LDA) and partial least squares discriminate analysis (PLS-DA). Later, selection techniques were applied to select the most effective wavelengths. The results showed that the PLS-DA model achieved better accuracy and less latent variables than LDA model, and specifically, good results with 100% classification accuracy were obtained using only the 600–1100nm spectral range for the two models and eight selected wavelengths. These results places visible and near-infrared spectrocopy as an accurate classification tool for nectarine varieties with a very similar appearance but different tastes that could be potentially used in an automated inspection system. " |
| format | Artículo |
| id | ReDivia6034 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| record_format | dspace |
| spelling | ReDivia60342025-04-25T14:45:58Z Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy Cortés, Victoria Cubero, Sergio Aleixos, Nuria Blasco, José Talens, Pau The feasibility of using visible and near-infrared spectroscopy technology combined with multivariate analysis to discriminate cv. ‘Big Top’ and cv. ‘Diamond Ray’ nectarines has been studied. These varieties are very difficult to differentiate visually on the production line but show important differences in taste that affects the acceptance by final consumers. The relationship between the diffuse reflectance spectra and the two nectarine varieties was established. Five hundred nectarine samples (250 of each variety) were used for the study. Tests were performed by using a spectrometer capable of measuring in two different spectral ranges (600–1100nm and 900–1700nm). These spectral ranges were used to develop two accurate classification models based on linear discriminate analysis (LDA) and partial least squares discriminate analysis (PLS-DA). Later, selection techniques were applied to select the most effective wavelengths. The results showed that the PLS-DA model achieved better accuracy and less latent variables than LDA model, and specifically, good results with 100% classification accuracy were obtained using only the 600–1100nm spectral range for the two models and eight selected wavelengths. These results places visible and near-infrared spectrocopy as an accurate classification tool for nectarine varieties with a very similar appearance but different tastes that could be potentially used in an automated inspection system. " 2018-05-09T16:30:57Z 2018-05-09T16:30:57Z 2017 article acceptedVersion Cortes, V., Cubero, S., Aleixos, N., Blasco, J., Talens, P. (2017). Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy. Postharvest Biology and Technology, 133, 113-120. 0925-5214 http://hdl.handle.net/20.500.11939/6034 10.1016/j.postharvbio.2017.07.015 http://www.sciencedirect.com/science/article/pii/S0925521417303721 en Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ electronico |
| spellingShingle | Cortés, Victoria Cubero, Sergio Aleixos, Nuria Blasco, José Talens, Pau Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy |
| title | Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy |
| title_full | Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy |
| title_fullStr | Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy |
| title_full_unstemmed | Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy |
| title_short | Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy |
| title_sort | sweet and nonsweet taste discrimination of nectarines using visible and near infrared spectroscopy |
| url | http://hdl.handle.net/20.500.11939/6034 http://www.sciencedirect.com/science/article/pii/S0925521417303721 |
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