Abstract

Global agriculture faces the dual challenge of ensuring food security while mitigating climate change, with soil degradation affecting nearly 70% of arable land worldwide. This review synthesizes current knowledge on engineering-integrated approaches for soil health optimization and carbon sequestration modeling within natural farming systems. Despite growing recognition of natural farming's potential for regenerative transitions, significant research gaps exist in quantifying carbon dynamics and optimizing bio-input technologies through computational approaches. This manuscript examines the convergence of agroecological principles, precision engineering interventions, and data-driven modeling frameworks to enhance soil organic carbon (SOC) storage while maintaining productivity in low-input systems. We present a conceptual framework integrating sensor-based soil diagnostics, process-based carbon models including DNDC and RothC, and emerging digital technologies such as machine learning and IoT monitoring systems. Major applications include field-level SOC enhancement under regenerative practices, engineering solutions for biochar incorporation and compost management, and digital decision-support tools for smallholder farmers. The findings demonstrate that engineering-integrated natural farming approaches can achieve carbon sequestration rates of 0.5–0.7 Mg C ha⁻¹ yr⁻¹ while improving soil biodiversity and water retention. Recent evidence from Vertisols in central India confirms that organic farming practices significantly increase soil organic carbon, enzymatic activity, and biochemical indices compared to conventional management [1]. Similarly, field applications in Uttar Pradesh, India, demonstrate that plant-derived biological inputs achieve 20–40% yield gains while reducing synthetic fertilizer use by up to 25%. This work establishes that translational pathways combining indigenous knowledge with precision agricultural engineering are essential for climate mitigation and sustainable rural development, particularly through carbon farming frameworks and verified monitoring, reporting, and verification systems.