Artificial Intelligence: Detection of diseases in bean crops.
DOI:
https://doi.org/10.37533/cunsurori.v10i1.87Abstract
Today's agriculture faces great challenges, the little tenure of arable land extensions, the wear of soils, bad practices that degenerate the soil; Climate change and high input costs are leading us to a food crisis, which is why new technological proposals are demanded.
Precision Agriculture (Agriculture 4.0) maximizes the performance of time, inputs, the products are of better quality, and the intervening contaminants are intended be mitigated as much as possible.
Artificial Intelligence (A.I.) models achieve a rebound in the achievement of objectives in Agriculture 4.0, as a circularly sustainable activity. Use a variety of techniques, among which numerical analysis, decision-making in autonomous processes and visual detection of agricultural indicators stand out.
This study deals with a Deep Learning algorithm based on Visual Computing capable of early detection of nutritional principles of the bean plant, obtaining substantive results that assess the technique itself, the quality of the intervening inputs, and the degree of algorithmic effectiveness of the techniques, which are represented graphically.
The AI model locates diseases in the plant, yielding a scientifically typified diagnosis; this demonstrated a high percentage of assertiveness of 99%.
Key words: Artificial Intelligence, Agriculture 4.0, Environmental impact, Food crisis, Nutritional assessment techniques.
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Copyright (c) 2023 Samuel Saldaña Valenzuela
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