Determinación de la textura en caqui "Rojo brillante" mediante imagen hyiperspectral Vis-NIR
Quality of persimmon cv 'Rojo Brillante' fruits can be affected by changes in texture during postharvest storage if storage conditions are not appropriate, which can impact consumer acceptance. Therefore, developing accurate tools to predict texture before marketing is of great interest. Hyperspe...
| Main Authors: | , , , , , , , , |
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| Format: | Objeto de conferencia |
| Language: | Español |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/20.500.11939/8879 |
| _version_ | 1855492578003124224 |
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| author | Castillo-Gironés, Salvador González-Muelas, Ángel Cubero, Sergio Rodríguez, Alejandro Munera, Sandra Salvador, Alejandra Guirao, Alberto Gómez-Sanchis, Juan Blasco, José |
| author_browse | Blasco, José Castillo-Gironés, Salvador Cubero, Sergio González-Muelas, Ángel Guirao, Alberto Gómez-Sanchis, Juan Munera, Sandra Rodríguez, Alejandro Salvador, Alejandra |
| author_facet | Castillo-Gironés, Salvador González-Muelas, Ángel Cubero, Sergio Rodríguez, Alejandro Munera, Sandra Salvador, Alejandra Guirao, Alberto Gómez-Sanchis, Juan Blasco, José |
| author_sort | Castillo-Gironés, Salvador |
| collection | ReDivia |
| description | Quality of persimmon cv 'Rojo Brillante' fruits can be affected by changes in texture
during postharvest storage if storage conditions are not appropriate, which can impact
consumer acceptance. Therefore, developing accurate tools to predict texture before marketing
is of great interest. Hyperspectral imaging is a non-destructive technology that has been proven
effective for predicting internal attributes. This study aimed to evaluate the usefulness of
hyperspectral images for predicting flesh firmness. A total of 3,340 persimmons were stored for
three months under different temperature conditions (0°C, 1°C, and 5°C) to induce varying
changes in flesh texture. Hyperspectral images were acquired at harvest and every month for
each storage condition. Flesh firmness was measured using a texturometer immediately after
image acquisition. Samples were clustered into three groups using k-Means based on their
firmness data and mean spectra was extracted from each persimmon. Samples were randomly
divided into training (70%) and test (30%) sets. Besides, wavelength reduction was performed using Partial Least Squares Discriminant Analysis (PLS) coefficients. The training data was used
to train PLS, Support Vector Machine, and Random Forest models using all spectra and selected
wavelengths. All models achieved high accuracies, indicating that even using a few
wavelengths, it is possible to accurately predict the flesh firmness of persimmon fruits. |
| format | Objeto de conferencia |
| id | ReDivia8879 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Español |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| record_format | dspace |
| spelling | ReDivia88792025-04-25T14:50:52Z Determinación de la textura en caqui "Rojo brillante" mediante imagen hyiperspectral Vis-NIR Castillo-Gironés, Salvador González-Muelas, Ángel Cubero, Sergio Rodríguez, Alejandro Munera, Sandra Salvador, Alejandra Guirao, Alberto Gómez-Sanchis, Juan Blasco, José N01 Agricultural engineering Diospyros kaki Spectral analysis Firmness Quality of persimmon cv 'Rojo Brillante' fruits can be affected by changes in texture during postharvest storage if storage conditions are not appropriate, which can impact consumer acceptance. Therefore, developing accurate tools to predict texture before marketing is of great interest. Hyperspectral imaging is a non-destructive technology that has been proven effective for predicting internal attributes. This study aimed to evaluate the usefulness of hyperspectral images for predicting flesh firmness. A total of 3,340 persimmons were stored for three months under different temperature conditions (0°C, 1°C, and 5°C) to induce varying changes in flesh texture. Hyperspectral images were acquired at harvest and every month for each storage condition. Flesh firmness was measured using a texturometer immediately after image acquisition. Samples were clustered into three groups using k-Means based on their firmness data and mean spectra was extracted from each persimmon. Samples were randomly divided into training (70%) and test (30%) sets. Besides, wavelength reduction was performed using Partial Least Squares Discriminant Analysis (PLS) coefficients. The training data was used to train PLS, Support Vector Machine, and Random Forest models using all spectra and selected wavelengths. All models achieved high accuracies, indicating that even using a few wavelengths, it is possible to accurately predict the flesh firmness of persimmon fruits. 2024-05-07T11:05:26Z 2024-05-07T11:05:26Z 2023 conferenceObject Castillo-Gironés, S., González-Muelas, A., Cubero, S., Rodríguez, A., Munera, S., Salvador, A., Guirao, A., Gómez-Sanchís, J., Blasco, J. (2023) Determinación de la textura en caqui ‘Rojo brillante’ mediante imagen hiperspectral Vis-NIR. XII Congreso Ibérico de Agroingeniería, Sevilla, p. 845-853 https://hdl.handle.net/20.500.11939/8879 es 2023-09-04 XII Congreso Ibérico de Agroingeniería Sevilla Este trabajo ha sido parcialmente financiado a través de los proyectos AEI PID2019- 107347RR-C31, C32 y C33 y fondos FEDER, y GVA CIPROM/2021/014. Salvador Castillo agradece a INIA por la beca FPI-INIA PRE2020-094491, con el apoyo de fondos FSE de la Unión Europea. Los autores agradecen a la Cooperativa Agrícola Ntra. Sra. Del Oreto Coop. V. (CANSO) por suministrar la fruta y por el apoyo técnico. Sandra Munera agradece el contrato postdoctoral Juan de la Cierva-Formación (FJC2021-047786-I) cofinanciado por el MICIN AEI/10.13039/501100011033 y la Unión Europea NextGenerationEU/PRTR. Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ openAccess electronico |
| spellingShingle | N01 Agricultural engineering Diospyros kaki Spectral analysis Firmness Castillo-Gironés, Salvador González-Muelas, Ángel Cubero, Sergio Rodríguez, Alejandro Munera, Sandra Salvador, Alejandra Guirao, Alberto Gómez-Sanchis, Juan Blasco, José Determinación de la textura en caqui "Rojo brillante" mediante imagen hyiperspectral Vis-NIR |
| title | Determinación de la textura en caqui "Rojo brillante" mediante imagen hyiperspectral Vis-NIR |
| title_full | Determinación de la textura en caqui "Rojo brillante" mediante imagen hyiperspectral Vis-NIR |
| title_fullStr | Determinación de la textura en caqui "Rojo brillante" mediante imagen hyiperspectral Vis-NIR |
| title_full_unstemmed | Determinación de la textura en caqui "Rojo brillante" mediante imagen hyiperspectral Vis-NIR |
| title_short | Determinación de la textura en caqui "Rojo brillante" mediante imagen hyiperspectral Vis-NIR |
| title_sort | determinacion de la textura en caqui rojo brillante mediante imagen hyiperspectral vis nir |
| topic | N01 Agricultural engineering Diospyros kaki Spectral analysis Firmness |
| url | https://hdl.handle.net/20.500.11939/8879 |
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