What question did this study set out to answer?

The study aims to identify the most influential climate predictors affecting mango crop yield in Tamil Nadu.

April 4, 2026Sustainable FuturesOpen Access

Identifying the most influential climate predictors for crop yield using advanced statistical and machine learning models: A case study for mango crop in India

View Full Paper

Ask AI

Bookmark

Authors

Identifies key climate predictors of mango yield in India, suggesting improvements for risk management tools.

The study aims to identify the most influential climate predictors affecting mango crop yield in Tamil Nadu.
Utilized d-vine copula regression and random forest statistical models
Analyzed climate data from the TerraClimate datasets for 31 districts
Employed stepwise selection for predictor identification and Mean Decrease Accuracy for variable ranking
Consistent climate variables identified include PDSI, minimum temperature, and actual evapotranspiration
PDSI was a key predictor across all mango phenological stages
Variations in predictor rankings were noted between the d-vine and random forest models

Nguyen-Huy et al. (2026) studied this question.

View Full Paper

Ask AI

Bookmark