Choosing the proper interpolation method for grain loss mapping in combine harvester

Authors

1 Department of Biosystems Engineering, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran

2 Department of Biosystem Engineering, Faculty of Agriculture, University of Tabriz

Abstract

Wheat is one of the most important crops in the country and plays an essential role in meeting the food needs of the people.Wheat production is associated with waste, and most of this waste comes from the harvesting stage. The amount of this loss in Iran is more than the world's allowed amount and any effort to reduce this loss can be effective in improving the product's performance. If losses are evaluated using precision agriculture techniques on site-specific, corrective measures can be taken according to each location to reduce losses and increase efficiency. In the present study, an attempt was made to prepare a grain loss map with acceptable accuracy by using a suitable interpolation method. For this purpose, natural, head and rear losses were collected simultaneously with the change in combine settings during harvesting. Then, using kriging interpolation methods, inverse distance weighting and moving average, the mapping of grain losses was done in ArcGIS software. The results of cross-validation and comparison of the accuracy of the methods showed that the mean value of the loss prediction error in all the interpolation methods is close to each other. For example, the RMSE value in the header loss for the inverse weighting method was calculated as 0.006017, which is lower than the values calculated for the kriging and moving average methods, which were obtained as 0.006732 and 0.006095, respectively. According to the results, the inverse distance weighting method is the best interpolation method for creating grain loss maps.

Keywords

References

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Agricultural Mechanization
Volume 8, Issue 2
June 2023
Pages 55-64

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History

  • Receive Date: 06 August 2023
  • Revise Date: 11 September 2023
  • Accept Date: 19 September 2023

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