Application of Predictive Model for Tractor Fuel Consumption in the Gezira Scheme, Sudan

Abstract

Fuel scarcity and rising energy costs are major challenges for mechanized agriculture in large-scale irrigated schemes such as the Gezira scheme, Efficient planning and allocation of diesel fuel are therefore critical for sustaining mechanized farming operations and maintaining productivity. This study aimed to apply a previously developed and validated predictive power model for tractor fuel consumption to support fuel requirement estimation, operational planning and economic analysis under real field conditions in the Gezira scheme. The model was used to estimate specific volumetric fuel consumption (SVFC), specific volumetric fuel efficiency (SVFE), fuel consumption per unit area (L/ha), unproductive fuel losses associated with off-road tractor movement, and total fuel requirements at farm and scheme levels. The application covered major crops grown in the Gezira scheme, namely cotton, wheat, groundnut and sorghum, under three farming systems: traditional, semi-mechanized, and fully mechanized. Fuel consumption for individual tractor–implement combinations was estimated using predicted hourly fuel consumption and effective field capacity, while unproductive fuel consumption was quantified based on tractor travel distance, speed and off-road fuel use. The model was further applied to estimate total seasonal and annual fuel demand and to assess fuel-related economic costs and potential savings. Results showed stable tractor fuel performance, with an average SVFC and SVFE values were 0.19 L/kW·h and 5.36 kW·h/L, respectively, indicating stable tractor fuel-use performance. Fuel consumption per hectare varied widely among implements, with unproductive fuel losses representing a significant share in high-capacity operations. Total fuel demand increased substantially with mechanization intensity, reaching a maximum under fully mechanized systems. Economic analysis revealed that fuel costs constitute a major component of production expenses, while a 10% reduction in fuel consumption could result in substantial financial savings at both farm and scheme levels. The findings demonstrate the practical applicability of the developed power model as a reliable decision-support tool for fuel budgeting and mechanization planning in large-scale irrigated agricultural systems.