Agricultural Technology in Climate-Smart Maize Systems: Integrating Digital, Agronomic, Biological, and Inclusive Innovations

Abstract

Agricultural technology is reshaping maize systems, yet its contribution to sustainable intensification depends less on the novelty of individual tools than on their integration across genetics, sensing, agronomy, ecology, institutions, and value chains. This structured critical review synthesizes 70 Scopus-indexed studies published from 2021 to 2025 to assess how recent technologies influence productivity, resource-use efficiency, climate resilience, environmental performance, and farmer welfare. The evidence shows rapid progress in unmanned aerial vehicle imaging, hyperspectral sensing, machine learning, crop modeling, variable-rate management, precision irrigation, and digital extension. These tools improve diagnosis and prediction, but their agronomic value is realized only when linked to actionable management rules. Conservation agriculture, subsurface drip fertigation, optimized nitrogen placement, controlled-release fertilizers, biochar-based amendments, microbial inoculants, and stress-targeted nanomaterials can raise yield or reduce environmental burdens, although performance is strongly conditioned by soil, climate, formulation, and management. Genomic prediction, high-density genotyping, gene editing, and high-throughput phenotyping are also converging toward environment-specific breeding. Across smallholder contexts, adoption is shaped by profitability, credit, market access, organizational membership, risk, and the compatibility of technologies as a package; information alone is rarely sufficient. Important trade-offs include microplastic accumulation from film mulching, nitrate displacement after ammonia-control interventions, uncertain nanoparticle safety, and digital model transferability. The review proposes an integrated framework in which sensing, prediction, intervention, verification, and institutional delivery operate as a closed decision loop. Future research should prioritize interoperable data, multi-location validation, whole-system environmental accounting, affordability, and co-designed technology bundles that deliver measurable gains under real farm constraints across diverse production regions.