Quantum-Enhanced Artificial Intelligence Models for Sustainable Agriculture and Climate-Resilient Crop Production

Abstract: This study investigates quantum-enhanced artificial intelligence (QEAI) models for climate-resilient crop production and sustainability-oriented decision support in agriculture. The framework integrates agroclimatic signals (rainfall, temperature, evapotranspiration, heatwave and dry-spell indicators, and vapor-pressure deficit) with sensor-derived crop-state variables (soil moisture, canopy temperature, and vegetation indices) to estimate yield and to identify robust management levers