Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit Zones
Accurate dry matter determination (DM) in Hass avocados is vital for optimal harvesting and ensuring fruit quality. Predictive models based on NIRS need to capture fruit DM gradient. This work aimed to determine the DM content in Hass avocado whole by NIRS scanning different fruit zones. Spectra wer...
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MDPI AG
2023-08-01
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| Series: | Plants |
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| Online Access: | https://www.mdpi.com/2223-7747/12/17/3135 |
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| author | Pablo Rodríguez Jairo Villamizar Luis Londoño Thierry Tran Fabrice Davrieux |
| author_facet | Pablo Rodríguez Jairo Villamizar Luis Londoño Thierry Tran Fabrice Davrieux |
| author_sort | Pablo Rodríguez |
| collection | DOAJ |
| description | Accurate dry matter determination (DM) in Hass avocados is vital for optimal harvesting and ensuring fruit quality. Predictive models based on NIRS need to capture fruit DM gradient. This work aimed to determine the DM content in Hass avocado whole by NIRS scanning different fruit zones. Spectra were recorded for each zone of the fruit: peduncle (P), equator (E), and base (B). The calibration and validation included fruit from different orchards in two harvest cycles. The results show a DM gradient within the fruit: 24.47% (E), 24.68% (B), and 24.79% (P). The DM gradient was observed within the spectra using the RMSi (root mean square) criterion and PCA. The results show that at least one spectrum per fruit zone was needed to represent the variability within the fruit. The performances of the calibration using the whole set of data were R<sup>2</sup>: 0.74 and standard error of cross-validation (SECV) = 1.18%. In the validation stage using independent validation sets, the models showed similar performance (R<sup>2</sup>: 0.75, SECV 1.15%) with low values of the standard error of prediction (SEP): 1.62%. These results demonstrate the potential of near-infrared spectroscopy for high-throughput sorting of avocados based on their commercial quality. |
| first_indexed | 2024-03-10T23:15:09Z |
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| id | doaj.art-3031909d85544d56897555c114367046 |
| institution | Directory Open Access Journal |
| issn | 2223-7747 |
| language | English |
| last_indexed | 2024-03-10T23:15:09Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
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| series | Plants |
| spelling | doaj.art-3031909d85544d56897555c1143670462023-11-19T08:41:49ZengMDPI AGPlants2223-77472023-08-011217313510.3390/plants12173135Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit ZonesPablo Rodríguez0Jairo Villamizar1Luis Londoño2Thierry Tran3Fabrice Davrieux4Research Unit ITAV: Innovaciones Tecnológicas para Agregar Valor a Recursos Agrícolas, Sector Llanogrande, Centro de Investigación La Selva, Corporación Colombiana de Investigación Agropecuaria-Agrosavia, km. 7, Vía Rionegro—Las Palmas, Rionegro-Antioquia 054048, ColombiaResearch Unit ITAV: Innovaciones Tecnológicas para Agregar Valor a Recursos Agrícolas, Sector Llanogrande, Centro de Investigación La Selva, Corporación Colombiana de Investigación Agropecuaria-Agrosavia, km. 7, Vía Rionegro—Las Palmas, Rionegro-Antioquia 054048, ColombiaInternational Center for Tropical Agriculture (CIAT), Valle del Cauca, Palmira 763537, ColombiaUMR Qualisud, Univ Montpellier, Avignon Université, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), Institut Agro, Institut de Recherche pour le Développement (IRD), Université de La Réunion, F-34398 Montpellier, FranceUMR Qualisud, Univ Montpellier, Avignon Université, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), Institut Agro, Institut de Recherche pour le Développement (IRD), Université de La Réunion, F-34398 Montpellier, FranceAccurate dry matter determination (DM) in Hass avocados is vital for optimal harvesting and ensuring fruit quality. Predictive models based on NIRS need to capture fruit DM gradient. This work aimed to determine the DM content in Hass avocado whole by NIRS scanning different fruit zones. Spectra were recorded for each zone of the fruit: peduncle (P), equator (E), and base (B). The calibration and validation included fruit from different orchards in two harvest cycles. The results show a DM gradient within the fruit: 24.47% (E), 24.68% (B), and 24.79% (P). The DM gradient was observed within the spectra using the RMSi (root mean square) criterion and PCA. The results show that at least one spectrum per fruit zone was needed to represent the variability within the fruit. The performances of the calibration using the whole set of data were R<sup>2</sup>: 0.74 and standard error of cross-validation (SECV) = 1.18%. In the validation stage using independent validation sets, the models showed similar performance (R<sup>2</sup>: 0.75, SECV 1.15%) with low values of the standard error of prediction (SEP): 1.62%. These results demonstrate the potential of near-infrared spectroscopy for high-throughput sorting of avocados based on their commercial quality.https://www.mdpi.com/2223-7747/12/17/3135dry matternear-infrared spectroscopyHass avocadofruit composition gradientfruit quality<i>Persea americana</i> |
| spellingShingle | Pablo Rodríguez Jairo Villamizar Luis Londoño Thierry Tran Fabrice Davrieux Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit Zones Plants dry matter near-infrared spectroscopy Hass avocado fruit composition gradient fruit quality <i>Persea americana</i> |
| title | Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit Zones |
| title_full | Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit Zones |
| title_fullStr | Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit Zones |
| title_full_unstemmed | Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit Zones |
| title_short | Quantification of Dry Matter Content in Hass Avocado by Near-Infrared Spectroscopy (NIRS) Scanning Different Fruit Zones |
| title_sort | quantification of dry matter content in hass avocado by near infrared spectroscopy nirs scanning different fruit zones |
| topic | dry matter near-infrared spectroscopy Hass avocado fruit composition gradient fruit quality <i>Persea americana</i> |
| url | https://www.mdpi.com/2223-7747/12/17/3135 |
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