Yield mapping is one of the cheapest and most valuable Precision Ag technologies available. Being able to accurately measure crop performance on a farm, paddock and sub paddock scale, provides very powerful management information, however very few people are using this technology effectively.
Those who are, have demonstrated the ability to make significant cost savings by applying appropriate and targeted fertiliser rates, or improving crop yield from poor performing areas through targeted management to address constraints.
For those who are not using the technology effectively, the reasons are varied, with the consistent theme being a lack of willingness to put the time and effort into addressing minor issues, that limit accurate collection and processing of the data.
There are many causes of yield variability, some of which can be influenced by management, such as surface soil pH, soil Nitrogen, and soil Phosphorous. Managing these factors through varying application rates of inputs on a paddock zone level, can lead to a significant financial return to the business. Such returns, from better allocation of inputs or higher yield, can amount to thousands or even tens of thousands of dollars.
Other factors such as soil type, elevation and topography cannot be easily influenced. Whilst these might vary on a paddock zone level, management may be best to accept the limitation imposed and apply inputs to a more realistic target yield. Management may be less able to change the result in this case, but reducing inputs based on realistic yield targets can lead to cost savings.
In addition to paddock variability, quality yield maps can be used to record the performance of on-farm trials. Such trials may provide growers with the confidence to cut fertiliser rates, apply or not apply fungicides, change varieties, or spray out summer weeds earlier. Conclusive, relevant, on-farm data, can lead to better decisions and significant financial returns.
Collecting yield data does require some effort and attention to detail, but it’s not hard, if one is motivated to do so. Following are some considerations which can lead to better quality data:
- Calibrating the yield monitor – The single most important factor in achieving high quality data. Calibrated yield data should have a 1-3% variation from actual tonnes harvested, compared to uncalibrated data that can have 30 to 40% variation from actual tonnes harvested. If multiple headers are used, it is vital that they have a similar calibration, otherwise the data will be stripy, and this cannot be rectified during processing. Scaling of data using actual tonnes harvested can be used to adjust the average yield for reporting, however this does not rectify the spatial variation, which could lead to errors if applying variable rate inputs.
- Accurately label paddocks – Accurately and consistently labelling yield data is important, particularly where multiple headers are used and numerous years of data will be analysed to generate paddock zones. Making sure each paddock is labelled separately, will allow greater analysis at a paddock level compared to labelling blocks only.
- Set up Paddock Boundaries – The use of paddock boundaries makes allocating yield data to a specific paddock much easier, particularly if data labelling is not consistent. Boundaries are very useful in allocating yield data to the correct paddock, regardless of the initial label entered into the yield monitor. Other technologies which require accurate boundaries, include variable rate prescription maps and auto-turn technology. Generating paddock boundaries during sowing or cultivation operations, will provide the most accurate boundary.
- Contractors – It is vital to provide an empty USB stick prior to harvest and remove the stick before the header leaves. This will save having to follow the contractor up after harvest or missing out on the data altogether.
- Data Recording – Another common issue is that the yield data may not be recorded. The main causes are faulty connections/cables or incorrect monitor settings. Both of these are easily fixed at the beginning of harvest, once a recording issue is detected.
Without accurate yield maps, it is difficult to assess the outcome of decisions made during the cropping season and plan inputs for the coming season. With information provided by multiple years of yield data in conjunction with trial results, it is possible to match economically optimum input rates, to the yield potential of specific zones within each paddock.