Tramline trials used to test winter wheat nitrogen accuracy

An innovative set of trials has helped farmers test the accuracy of nitrogen (N) management in their winter wheat crops.

Wheat yields differed both between farms and within farms but the cause of most of the variation was deemed unlikely to be a result of N tactics.

The conclusions add weight to other research findings that show, if N rates are calculated using RB209 and a nutrient management plan is drawn up and followed, yield variation is most likely caused by other factors.

Large variations in wheat yields across farms and fields, and even within fields, often make people question their approach to N management.

The AHDB-funded ‘LearN’ project tested a radical new approach to help farmers work out whether they were applying too much, too little or just the right amount of N fertiliser.

The project recruited 18 highly engaged farmers, who already followed best nutrient management practice, to test their farms’ standard N rates in simple tramline trials.

The trials, which ran from 2014 to 2017, tested single replicates of two treatments (60kg/ha more and less than the farm standard rate of fertiliser N) in alternate tramlines.

A yield increase of 0.3t/ha was deemed necessary to pay for an additional 60kgN/ha – based on a wheat price of £140/t and fertiliser costs of £0.70/kg.

The average wheat yield (142 tramline experiments) was 11.43t/ha for the farm standard. On average, yields were reduced by 0.36t/ha for the minus 60kgN/ha treatment and increased by 0.36t/ha for the plus 60kgN/ha treatment.

Sajjad Awan, who manages nutrient management research at AHDB, said: “On balance, there was little, if any, economic incentive to deviate from the standard N rate on these farms.

“The benefits of tramline trials depend on the accuracy of the standard N rate, as well as the accuracy of the trial. If the accuracy is already there, then there’ll be little benefit of increasing or decreasing rates. However, the farmer does get peace of mind by knowing the current approach is right.”

Sajjad continued: “Across all experiments, none of the farms was applying too much or too little N consistently. This means that the large variation in yield, both across farms and fields, was probably the result of agronomic, genetic, chemical, soil or engineering factors. It is these factors that need to be addressed, if yields are to be improved significantly.

“The best way to optimise N applications is to follow RB209, develop a nutrient management plan and flex it in response to the season. LearN-type approaches are most useful to deploy in fields where N optima are uncertain.”

The full final report can be accessed via cereals.ahdb.org.uk/learn