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Title: Superior EVOO Quality Production: An RGB Sorting Machine for Olive Classification
Authors: Violino, Simona
Moscovini, Lavinia
Costa, Corrado
Re, Paolo Del
Giansante, Lucia
Toscano, Pietro
Tocci, Francesco
Vasta, Simone
Manganiello, Rossella
Ortenzi, Luciano 
Pallottino, Federico
Journal: FOODS 
Issue Date: 2022
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.
ISSN: 2304-8158
DOI: 10.3390/foods11182917
Rights: Attribution 4.0 International
Appears in Collections:A1. Articolo in rivista

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