Optimisation of Performance Parameters of Farm Machinery for Economic Sustainability in Irrigation Scheme (A Case Study of Giriyan Irrigation Scheme, North Central Nigeria).

Abstract

The efficient utilization of farm machinery is key to strategic management for sustainable agricultural mechanization and economic sustainability. This study optimized agricultural input-output performance parameters of farm machinery for economic sustainability at Giriyan irrigation scheme, North Central Nigeria. A survey of structured questionnaires was adopted to obtain level of utilization of farm machinery in the scheme. Field data were obtained through soil analysis and real-time measurements of tractor performance using sensor-based instrumentation. An Artificial Neural Network (ANN) model was developed with nine input variables, two hidden layers (8–5nodes), and five output variables to evaluate utilization index, mechanization index, capacity utilization index, specific fuel consumption, and profitability index. The best topology structure for the ANN model developed was 9-8-5-5. The model achieved high prediction accuracy with coefficients of determination (R²) values of 0.9902, 0.9943, 0.9819, 0.9823 and 0.9979 for utilization index, mechanization index, capacity utilization index, specific fuel consumption, and profitability index respectively. The results revealed that operational cost, rated implement width, tractor power and tillage depth were the most influential parameters for optimizing specific fuel consumption and good profitability of farm machinery investment at Giriyan irrigation scheme of North Central Nigeria. The ANN model demonstrated strong predictive capacity, with training and testing errors of Mean Square Error (MSE) of 0.0528 and 0.0349 respectively. The ANN model provides a good decision-making support tool for farm managers and policy makers to improve farm machinery performance, optimize energy use, and promote sustainable agricultural mechanization in many irrigation schemes of North Central Nigeria.