Resumen

GOMEZ-CAMPEROS, July A.; JARAMILLO, Haidee Y.  y  GUERRERO-GOMEZ, Gustavo. Digital image processing techniques for detection of pests and diseases in crops: a review. Ing. compet. [online]. 2022, vol.24, n.1, e30110973.  Epub 30-Oct-2021. ISSN 0123-3033.  https://doi.org/10.25100/iyc.24i1.10973.

Proper detection of pests and diseases in crop production is essential to increase agricultural production in a sustainable way. For this reason, the term Agriculture 4.0 is incorporated, which integrates a set of technologies, devices, protocols, and computational paradigms to improve agricultural processes. Information on climatic conditions, soils, diseases, insects, seeds, fertilizers. It constitutes an essential contribution to the economic and sustainable development of this sector. Digital image processing techniques are a tool that allows early identification of pests or diseases in crops such as cereals, fruit trees, roots, leaves, and tubers mainly. In this way, mitigate economic losses in the agricultural sector. Globally, about 40% of crops are discarded by various diseases and pests. In most cases, crop diseases produce visible symptoms and characteristics during plant growth. Due to the scarcity of technologies used in crops, the diagnosis of diseases and pests is supported mainly by human inspection, generating errors caused by the subjectivity of individuals.

This literature review was carried out to identify different digital image processing techniques for pests and disease prevention in crops from different agricultural sectors. The results showed that the diagnostic system is composed of the acquisition of images, pre-image processing, segmentation, characteristics extraction, characteristics selection, and the subsequent classification of pests or diseases. Likewise, current trends and challenges on the subject are presented.

Palabras clave : agriculture; crop; disease; image processing; plague.

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