Quantifying combine auto-adjusting capabilities in canola

Posted on 19.01.2023 | Last Modified 28.04.2023
Lead Researcher (PI): Lorne Grieger
Institution: Prairie Agricultural Machinery Institute
Total WGRF Funding: $56,679
Co-Funders: Saskatchewan Canola Development Commission
Start Date: 2022
Project Length: 1 Year

Quantify the change in conditions during a typical harvest day and effect on combine losses while harvesting canola. Measure the performance potential of combines with auto adjusting settings while harvesting canola.

Project Summary:

Canola is an essential crop in the Canadian Prairies, and canola losses are an unfortunate part of harvest that must be managed by producers. Canola losses can be categorized as either environmental losses, header losses, or combine losses. Environmental losses occur prior to cutting or gathering; header losses occur during swathing, swath pickup, or when straight cutting; and combine losses occur during harvesting and refer to grain lost (discarded with the chaff and straw) from the separation and cleaning systems. In 2019, the Prairie Agricultural Machinery Institute (PAMI) conducted a survey of canola losses in Western Canada to identify the harvest factors that impact canola harvest losses. This study found that weather conditions are a key factor influencing combine losses, and that combines should be set based on these conditions. It is important for producers to reassess their combine losses as conditions change both throughout the day and harvest season (PAMI, 2019). Auto-adjusting separation and cleaning systems being introduced by the major combine manufacturers may provide a daily opportunity for producers to retain more seed by automatically adjusting settings to reduce losses throughout a harvest day as environmental conditions change.

The objective of this project was to build on the study completed in 2019 and further investigate the effect of changing environmental conditions during a harvest day and the methods used to adjust “on-the-fly” to minimize losses. A total of 22 combines were tested (11 with auto-adjusting capabilities and 11 without).

The data collected and analyzed in this study found that mean daily temperature had a significant effect (P<0.05) on harvest yield loss while variation of temperature and humidity throughout the day (represented by standard deviation) did not appear to have a significant effect on the variability of percentage yield loss throughout the day.

Further, for the 22 combines tested, of which half had auto-adjusting capabilities, the auto-adjusting combines had slightly lower variation in yield loss compared to the manual adjusting capabilities, but this was not a significant difference, statistically. More importantly though, it was observed that the range of variation for the manual adjusting combine types was much lower than the auto-adjusting types. This indicates that auto-adjusting combine types still need calibration and monitoring to ensure that they are operating properly to respond to changing conditions and losses.

There is not a standard set of combine settings that can be attributed to specific losses. Each combine, operating in particular conditions for a specific crop, must be optimized for the given environment. Auto-adjusting capabilities in new combines have the potential to effectively respond to changing environmental conditions, but they cannot just be set and forgotten. They should be calibrated regularly, and it is important to regularly measure losses to ensure adjustments are made to properly optimize harvest yield by reducing combine losses. While it may allow more frequent adjustment to changing conditions without the inefficiencies of conducting loss measurements manually, auto-adjust feature does not negate the requirement to measure. Further, it can be said that any method to check for losses is better than not checking at all.

It should be noted that most data collected during this project was obtained directly from producers; therefore, the accuracy and consistency of this data greatly relied on the calibration methods used by each producer. This should be considered when assessing the results of this project.