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A machine learning framework for profit analysis: A case study on sustainable cocoa production in Ecuador
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DOI：10.1016/j.resconrec.2026.109075.png)
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Abstract
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• ML-based profit analysis: Predictive models assess organic vs. conventional cocoa farming profitability in Ecuador. • Key profit indicators: Quality of life, soil quality, planted area, and fertilizer use impact profitability. • Organic vs. conventional: Organic farming outperforms Fine Aroma cocoa; conventional farming is better for Ramilla variety. • Temporal trends: Organic farming faces land constraints; conventional farming increases chemical input reliance. • SHAP explainability: Machine learning identifies key economic and environmental drivers of profitability.
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