Tractor Power Take-Off and Drawbar Pull Performance and Efficiency Evolution Analysis Methodology and Model: A Case Study

Previous studies on tractor performance and efficiency were conducted prior to the implementation of emission reduction technologies and the increased density and complexity of tractor portfolios. This study presents a robust methodology for forecasting specific fuel consumption based on public information, which incorporates physical attribute-based cohorts and technological generation groupings, alongside variables such as wheelbase, mass, and power take-off power. The proposed model significantly improves forecasting accuracy, enhancing the current R-squared (RSq) from 0.6091 to 0.8519 and reducing the root mean square error (RMSE) from 0.0098 to 0.0065. Additionally, the model provides accurate predictions of drawbar performance and efficiency. Its simplicity results in low cognitive and computational demands, making it accessible via widely available spreadsheet software on any computer or handheld device. This accessibility supports data-driven decision-making for tractor replacement strategies, ultimately promoting sustainable profitability in agricultural business operations.