Vol. 37 No. 1 (2023): Advances in Horticultural Science - Special issue Postharvest
Articles

Application of computer vision systems for assessing bergamot fruit external features

S. Benalia
Dipartimento di Agraria, Università degli Studi Mediterranea di Reggio Calabria, Località Feo di Vito, snc, 89122 Reggio di Calabria (RC), Italy.
V. Calogero
Dipartimento di Agraria, Università degli Studi Mediterranea di Reggio Calabria, Località Feo di Vito, snc, 89122 Reggio di Calabria (RC), Italy.
M. Anello
Dipartimento di Agraria, Università degli Studi Mediterranea di Reggio Calabria, Località Feo di Vito, snc, 89122 Reggio di Calabria (RC), Italy.
G. Zimbalatti
Dipartimento di Agraria, Università degli Studi Mediterranea di Reggio Calabria, Località Feo di Vito, snc, 89122 Reggio di Calabria (RC), Italy.
B. Bernardi
Dipartimento di Agraria, Università degli Studi Mediterranea di Reggio Calabria, Località Feo di Vito, snc, 89122 Reggio di Calabria (RC), Italy.

Published 2023-05-10

Keywords

  • Aspect ratio,
  • Citrus x bergamia Risso & Poiteau,
  • citrus colour index (CCI),
  • dimensions,
  • HunterLab,
  • imaging,
  • RGB
  • ...More
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How to Cite

Benalia, S., Calogero, V., Anello, M., Zimbalatti, G., & Bernardi, B. (2023). Application of computer vision systems for assessing bergamot fruit external features. Advances in Horticultural Science, 37(1), 111–116. Retrieved from https://oaj.fupress.net/index.php/ahs/article/view/13911

Abstract

Bergamot Citrus x bergamia Risso & Poiteau is an emblematic Citrus species of Reggio Calabria province (Southern Italy) where more than 90% of the global production thrives. The present work deals with the use of a non-destructive technique based on a computer vision systems to evaluate bergamot fruit peel colour, as well as dimensional features. To this purpose, experimental trials considered three bergamot cultivars, namely: ‘Femminello’, ‘Castagnaro’ and ‘Fantastico’. Bergamot fruit RGB images were taken using a laboratory inspection chamber equipped with a lighting system and a digital camera Nikon D5200 directly connected to a personal computer, to enable remote image acquisition. First, images were pre-processed according to a previously created colour profile. After that, bergamot fruit colour was analysed and expressed in terms of Hunter L, a, and b coordinates, which were used to calculate Standard Citrus Colour Index (CCI). In addition, dimensional features and shape descriptors were measured for each cultivar. Statistical data analysis, by applying the Kruskal-Wallis test at p<0.05 on CCI data highlighted significant differences between the assessed cultivars, and discriminant analysis (LDA) applied on CCI and dimensional features enabled a classification rate of 78.86% between cultivars, proving the reliability of computer vision techniques in assessing bergamot external features..