Visual selection in fruits: systematic literature review




agriculture, algorithms, computing devices, fruits, image recognition, artificial vision


Artificial vision has an important participation in the agricultural sector due to the solutions it provides through the recognition of images of fruits considering their color and shape. The problem is the difficulty in evaluating the quality of the fruit, being carried out by people, errors are made when carrying out manual selection, since the subjective aspect and their perception abilities are involved. Being necessary to implement systems of this type, a systematic literature review was developed using the PRISMA methodology, which seeks to identify the current algorithms, techniques, computing devices, libraries or software that are used in artificial vision implementations for fruit. The results show 32 algorithms, 32 computer equipment, 25 models, 8 libraries or software that make it possible to carry out implementations for visual selection. In summary, artificial vision significantly impacts fruit selection and classification by improving efficiency, reducing manual work and accelerating selection time. This advance not only contributes to precise agriculture, but also promotes sustainability by optimizing processes and improving the quality of products, achieving an important role in the union of technology with agriculture.


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How to Cite

Parraga-Badillo, S. R., & Coral-Ygnacio, M. A. (2024). Visual selection in fruits: systematic literature review. Revista Científica De Sistemas E Informática, 4(1), e591.

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