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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 ripenessdoi:10.3390/horticulturae7090282 doaj:60a53d58958e451cadf3af519e6cf3c0 fatcat:uhgjpx6hwjg5pbpwrhyy5kozjm