PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 7, 2026Results in Engineering0 citationsOpen Access

Modeling and Optimization of Grain Loss in the Threshing, Separation and Cleaning (TSC) Unit of a Straw-Chopper Combine Harvester Using Response Surface Methodology

View Full Paper
IHIsa Hazbawi

Key Points

  • The aim is to model and optimize grain loss in the threshing, separation, and cleaning unit of combine harvesters.
  • Used response surface methodology to analyze the effects of independent variables.
  • Investigated variables included spike density, forward speed, and cutting height.
  • Applied desirability-based optimization for operational adjustments.
  • High desirability optimization model reduced wheat grain loss to 1.61%.
  • Increased spike density and forward speed resulted in more grain loss.
  • Optimal cutting height minimized non-grain load.

Abstract

• Cutting height increase reduced non-grain load and wheat grain loss. • Optimization model predicted ideal combine settings accurately. • Response Surface Method optimized wheat grain loss at 1.61%. • Higher spike density and forward speed increased non-grain load and grain loss. • Field-based optimization supports sustainable wheat harvesting efficiency. Wheat, as a strategic crop for food security, is affected by harvesting losses, and the widespread use of straw-chopper combine harvesters has altered the pattern of these losses. In these harvesters, the presence of two separate tanks for grain and straw increases the load of material other than grain (MOG) and turns the cleaning unit into the most critical section regarding grain loss. The objective of this study was to model and optimize the effects of spike density, forward speed, and cutting height on grain loss in the threshing, separation, and cleaning (TSC) system of a straw-chopper combine harvester and to determine the optimal operating conditions. The response surface methodology (RSM) combined with a desirability-based optimization approach, was employed to analyze system behavior and evaluate single- and scenario-based operational trade-offs. The independent variables included spike density (340-440 spikes m -2 ), forward speed (1-3 km h -1 ), and cutting height (5-15 cm). Optimization results indicated that the model, with high desirability, was capable of predicting the optimal combination of variables, under which the minimum wheat grain loss in the TSC was 1.61 %. Analysis of the variables revealed that increasing spike density and forward speed intensified grain loss by elevating the TSC load, whereas higher cutting heights mitigated losses by reducing MOG influx. These findings provide a better scientific understanding of the TSC system's response and, from an applied perspective, offer a basis for optimal combine harvester adjustment and the reduction of grain loss in post-harvest wheat management.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Isa Hazbawi (2026) studied this question.

synapsesocial.com/papers/69fbe382164b5133a91a2c0ehttps://doi.org/10.1016/j.rineng.2026.110861
Ask AI
Helpful
Bookmark
Share
View Full Paper