ICCK

Paul Betiang Anyin

University of Cross River State, NG

Section 01

Academic Profile

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Section 02

ICCK Publications

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Open Access | Research Article | 24 August 2026
Model-Based Design and Evaluation of a Multi-Variable Hybrid Predictive Control Loop for Precision Fertigation Using Multi-Sensor Data Fusion
Digital Intelligence in Agriculture | Volume 2, Issue 3: 114-125, 2026 | DOI: 10.62762/DIA.2026.947445
Abstract
Efficient water and nutrient management remains a major challenge in modern agriculture due to rising fertilizer costs, global water scarcity, and environmental concerns such as groundwater contamination from nutrient leaching. Conventional fertigation typically relies on uniform application rates that neglect spatial and temporal root-zone variability, resulting in inefficient resource utilization. To address these limitations, this study proposes and evaluates an automated Multi-Variable Hybrid Predictive Control (HPC) framework for precision fertigation. The system captures the highly nonlinear dynamics of rapid soil moisture changes and slower nutrient transport using a multi-variable st... More >

Graphical Abstract
Model-Based Design and Evaluation of a Multi-Variable Hybrid Predictive Control Loop for Precision Fertigation Using Multi-Sensor Data Fusion