Application for the detection of physiopathologies in blueberry crop

Abstract

Mexico is the 6th. worldwide producer of blueberry with 48,999 tons; where Guanajuato contributes 11% of the national total, ranking 7th. producer of the country (Secretariat of Agrifood and Rural Development, 2020). One of the main physiopathies that occurs in blueberry plants is root suffocation, which limits the ability of plants to breathe through the roots (Generalitat Valencia, 2022). Identifying the severity of the damage caused by physiopathies is essential for timely treatment and the prevention of its transmission; however, it is complex due to the lack of classification criteria. In this context, an application was developed whose purpose is to detect the level of affectation by physiopathies in blueberry leaves, calculating the percentage of damage severity, using artificial intelligence (AI). The results allow us to conclude that AI provides an easy and incremental progression as it is applied to different varieties of physiopathies, through the analysis of photographs. The application is useful for blueberry farmers and greenhouse owners, providing convenient information for the prevention and spread of crop diseases and improving decision-making

Plant phenotyping relevance

ブルーベリー葉の生理障害による損傷重症度を写真とAIで定量推定するアプリケーション開発であり、植物状態の取得・抽出が中心的な方法貢献である。

Code and data availability

The paper describes the P-Search application with over 600 blueberry leaf images and a KNN classifier, but provides no public dataset, code, model, or supplement deposit; the only URLs are cited references, not authors' asset releases.

No evidence-backed public reproduction asset is currently recorded.