Machine Vision for Ripeness Estimation in Viticulture Automation

Eleni Vrochidou, Christos Bazinas, Michail Manios, George A. Papakostas, Theodore P. Pachidis, Vassilis G. Kaburlasos
2021 Horticulturae  
Ripeness estimation of fruits and vegetables is a key factor for the optimization of field management and the harvesting of the desired product quality. Typical ripeness estimation involves multiple manual samplings before harvest followed by chemical analyses. Machine vision has paved the way for agricultural automation by introducing quicker, cost-effective, and non-destructive methods. This work comprehensively surveys the most recent applications of machine vision techniques for ripeness
more » ... imation. Due to the broad area of machine vision applications in agriculture, this review is limited only to the most recent techniques related to grapes. The aim of this work is to provide an overview of the state-of-the-art algorithms by covering a wide range of applications. The potential of current machine vision techniques for specific viticulture applications is also analyzed. Problems, limitations of each technique, and future trends are discussed. Moreover, the integration of machine vision algorithms in grape harvesting robots for real-time in-field maturity assessment is additionally examined.
doi:10.3390/horticulturae7090282 doaj:60a53d58958e451cadf3af519e6cf3c0 fatcat:uhgjpx6hwjg5pbpwrhyy5kozjm