Correlation Analysis of Banana Leaf Colour and Texture Features with Chemically Determined Nutrient Concentrations

Correlation Analysis of Banana Leaf Colour and Texture Features with Chemically Determined Nutrient Concentrations examines the relationship between measurable colour and texture characteristics of banana leaves and their chemically determined nutrient concentrations. The study uses digital image processing to extract leaf features, including RGB colour values, colour intensity, texture patterns, and related statistical parameters. These image-based measurements are compared with laboratory-based nutrient analysis to identify significant correlations between optical features and nutrient levels. The research aims to determine whether leaf colour and texture can serve as reliable indicators of plant nutritional status. This approach may support the development of non-destructive, cost-effective, and efficient techniques for monitoring banana plant health. The findings can contribute to precision agriculture, improved nutrient management, and the advancement of image-based methods for crop assessment and agricultural research.

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Publication Details

Journal
International Journal of Emerging Technologies and Innovative Research
Published
2026-10-19
DOI
https://doi.org/10.5281/zenodo.23470857
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Correlation Analysis of Banana Leaf Colour and Texture Features with Chemically Determined Nutrient Concentrations

Anantjit Publication
International Journal of Emerging Technologies and Innovative Research
Smart Agriculture and AI
article

Correlation Analysis of Banana Leaf Colour and Texture Features with Chemically Determined Nutrient Concentrations

Anantjit Publication
article en

Abstract

Correlation Analysis of Banana Leaf Colour and Texture Features with Chemically Determined Nutrient Concentrations examines the relationship between measurable colour and texture characteristics of banana leaves and their chemically determined nutrient concentrations. The study uses digital image processing to extract leaf features, including RGB colour values, colour intensity, texture patterns, and related statistical parameters. These image-based measurements are compared with laboratory-based nutrient analysis to identify significant correlations between optical features and nutrient levels. The research aims to determine whether leaf colour and texture can serve as reliable indicators of plant nutritional status. This approach may support the development of non-destructive, cost-effective, and efficient techniques for monitoring banana plant health. The findings can contribute to precision agriculture, improved nutrient management, and the advancement of image-based methods for crop assessment and agricultural research.

International Journal of Emerging Technologies and Innovative Research
Openalex Percentile: Top 15%
Smart Agriculture and AI
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