Proposing the Mathematical Model of Combine Harvester Rear Losses in Soybean Harvesting

Document Type : Research Paper

Authors

1 Department of Agricultural Engineering & Technology, Faculty of Agriculture & Natural Resources Moghan, University of Mohaghegh Ardabili, Ardabil, Iran

2 M.S. in Engineering of Agricultural Mechanization, Moghan Agro-industrial & Livestock (MAIL) Co., Pars Abad Moghan, Iran

3 Department of Biosystems Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

Abstract

Abstract
Soybean is mostly harvesteds by conventional grain combine harvesters. Harvesting losses is one of the major issues in this way. Harvesting losses cannot be reduced to zero, but using the correct methods and proper equipments could reduce it to an acceptable level. Estimate of the losses rate in harvesting stage and recognition of effective factors in essentioal to decrease the losses. For reaching to a minimum loss, each one of harvesting processes (cutting, threshing, separation and …) must be optimized in operation. In this study the influence of forward speed, moisture content and plant density factors were used to make a mathematical model for John Deere 955 combine harvester rear losses. The experiments were conducted in soybean farms in Moghan plain, which is one of the major soybean prodcution areas in Ardabil province, Iran. For statistics a 3×3×3 factorial pattern based on randomized complete block design with 3 replications (in total 81 tests) was used. The effects of forward speed (in three levels of 1.8, 2.5 & 3.2 km h-1), moisture content (15, 19 & 23%) and soybean plant density  (40, 50 and 60 plant m-2) were tested again combine harvester rear losses (%). ANOVA results showed that the effects of all three factors with the double and triple interactions were significant at 1% probability level on rear losses. The losses were increased with increasing forward speed, plant density and moisture content. Linear regression was used to determine the relationship between dependent and independent parameters. The results of regression analysis of the model showed that 77% of the combine harvester rear losses is justified by the three variables studied in this study. The higher standardized coefficient of combine forward speed in the model make it the greatest effect on the rate of combine harvester rear losses.
 

Keywords

References

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Agricultural Mechanization
Volume 6, Issue 1
April 2021
Pages 31-38

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History

  • Receive Date: 10 July 2021
  • Accept Date: 10 July 2021

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