Superior EVOO Quality Production: An RGB Sorting Machine for Olive Classification
Extra virgin olive oil (EVOO) is a commercial product of high quality, thanks to its nutritional and organoleptic characteristics. The olives ripeness and the choice of harvest time according to their color and size, strongly influences the quality of the EVOO. The physical sorting of olives with ma...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/11/18/2917 |
| _version_ | 1797488394692984832 |
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| author | Simona Violino Lavinia Moscovini Corrado Costa Paolo Del Re Lucia Giansante Pietro Toscano Francesco Tocci Simone Vasta Rossella Manganiello Luciano Ortenzi Federico Pallottino |
| author_facet | Simona Violino Lavinia Moscovini Corrado Costa Paolo Del Re Lucia Giansante Pietro Toscano Francesco Tocci Simone Vasta Rossella Manganiello Luciano Ortenzi Federico Pallottino |
| author_sort | Simona Violino |
| collection | DOAJ |
| description | Extra virgin olive oil (EVOO) is a commercial product of high quality, thanks to its nutritional and organoleptic characteristics. The olives ripeness and the choice of harvest time according to their color and size, strongly influences the quality of the EVOO. The physical sorting of olives with machines performing rapid and objective optical selection, impossible by hand, can improve the quality of the final product. The aim of this study concerns the classification of olives into two qualitative classes, based on the maturity stage and the presence of external defects, through an industrial RGB optical sorting prototype, evaluating its performance and comparing the results with those obtained visually by trained operators. EVOOs obtained from classified olives were characterized through chemical, physical-chemical analysis and sensory profile. For the first time, the optoelectronic technologies in an industrial system was tested on olives to produce superior quality EVOO. The selection allows late harvest, obtaining oils with good characteristics from fully ripe and unripe fruits together, separating defective olives with appropriate calibration and training. Optoelectronic selection creates the opportunity to blend the obtained oils destined to different applications according to the needs of the consumer or producer, using a vanguard technology at low cost. |
| first_indexed | 2024-03-10T00:01:32Z |
| format | Article |
| id | doaj.art-9ba673a4b3cf49a194de7912dce28221 |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-10T00:01:32Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-9ba673a4b3cf49a194de7912dce282212023-11-23T16:15:24ZengMDPI AGFoods2304-81582022-09-011118291710.3390/foods11182917Superior EVOO Quality Production: An RGB Sorting Machine for Olive ClassificationSimona Violino0Lavinia Moscovini1Corrado Costa2Paolo Del Re3Lucia Giansante4Pietro Toscano5Francesco Tocci6Simone Vasta7Rossella Manganiello8Luciano Ortenzi9Federico Pallottino10Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA)—Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA)—Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA)—Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Viale Lombardia C.da Bucceri, 65012 Cepagatti, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Viale Lombardia C.da Bucceri, 65012 Cepagatti, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Milano 43, 24047 Treviglio, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA)—Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA)—Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA)—Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA)—Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA)—Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Della Pascolare 16, 00015 Monterotondo, ItalyExtra virgin olive oil (EVOO) is a commercial product of high quality, thanks to its nutritional and organoleptic characteristics. The olives ripeness and the choice of harvest time according to their color and size, strongly influences the quality of the EVOO. The physical sorting of olives with machines performing rapid and objective optical selection, impossible by hand, can improve the quality of the final product. The aim of this study concerns the classification of olives into two qualitative classes, based on the maturity stage and the presence of external defects, through an industrial RGB optical sorting prototype, evaluating its performance and comparing the results with those obtained visually by trained operators. EVOOs obtained from classified olives were characterized through chemical, physical-chemical analysis and sensory profile. For the first time, the optoelectronic technologies in an industrial system was tested on olives to produce superior quality EVOO. The selection allows late harvest, obtaining oils with good characteristics from fully ripe and unripe fruits together, separating defective olives with appropriate calibration and training. Optoelectronic selection creates the opportunity to blend the obtained oils destined to different applications according to the needs of the consumer or producer, using a vanguard technology at low cost.https://www.mdpi.com/2304-8158/11/18/2917extra virgin olive oilinnovative classificationimage analysisqualityolive selection |
| spellingShingle | Simona Violino Lavinia Moscovini Corrado Costa Paolo Del Re Lucia Giansante Pietro Toscano Francesco Tocci Simone Vasta Rossella Manganiello Luciano Ortenzi Federico Pallottino Superior EVOO Quality Production: An RGB Sorting Machine for Olive Classification Foods extra virgin olive oil innovative classification image analysis quality olive selection |
| title | Superior EVOO Quality Production: An RGB Sorting Machine for Olive Classification |
| title_full | Superior EVOO Quality Production: An RGB Sorting Machine for Olive Classification |
| title_fullStr | Superior EVOO Quality Production: An RGB Sorting Machine for Olive Classification |
| title_full_unstemmed | Superior EVOO Quality Production: An RGB Sorting Machine for Olive Classification |
| title_short | Superior EVOO Quality Production: An RGB Sorting Machine for Olive Classification |
| title_sort | superior evoo quality production an rgb sorting machine for olive classification |
| topic | extra virgin olive oil innovative classification image analysis quality olive selection |
| url | https://www.mdpi.com/2304-8158/11/18/2917 |
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