Identification of Weeds in Banana Crops (Musa × paradisiaca L.) Using NDVI
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Abstract
The purpose of this study was to identify, characterize, and classify weeds present in banana (Musa × paradisiaca L.) crops using the Normalized Difference Vegetation Index (NDVI) and spectral image analysis. An applied, descriptive, documentary, and field study was conducted at the Milagro University Campus “Dr. Jacobo Bucaram Ortiz,” where the most common weed species, their adaptive characteristics, and their degree of impact on the crop were recorded. The results showed a high prevalence of Cyperus rotundus (35%), Imperata cylindrica (30%), and Amaranthus sp. (20%), species known for their resistance and ability to spread. NDVI analysis allowed the crop areas to be categorized into four levels of infestation, identifying critical zones with values below 0.2, which exhibited sparse vegetation and high infestation. Likewise, the use of spectral images enabled the precise delineation of zones with higher weed density, facilitating decision-making for selective management. It is concluded that NDVI is an effective tool for monitoring, diagnosing, and planning sustainable weed control strategies in banana cultivation.
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