Developing a novel way of rapidly measuring agronomic treatment effects on grass growth

Measuring grass yield is time consuming and laborious because it either involves multiple measurements with a rising plate meter or counting and weighing silage trailers.

Recent studies have demonstrated that spectral reflectance of grass crops measured by satellite could be used to accurately measure grass yield. This method offers a much simpler and quicker method of measuring grass yield that would enable farmers to test the effect of different agronomic treatments in order to optimise their grass husbandry approach. Spectral reflectance imagery captured by drones can now also be used to measure grass growth which can produce finer resolution images however this relies on manual operation.

Three dairy farmers in Monmouthshire came together to investigate whether these new methods of measuring grass enabled them to measure grass yields reliably and quickly. 

Their hope was that the technology would allow them to measure the effects of different agronomic treatments (fertiliser treatments, grass varieties and the use of herbicide etc.) remotely on their own fields.

The two year project plan:

  • Across the three farms, five field-scale strip trials in grass and grass/clover fields in 2020 and 2021 testing a wide range of agronomic treatments including different grass and clover mixes, sulphur fertiliser rates, slurry, Smart Grass growth promoter, and biostimulant.
  • The control treatment was the farm standard treatment, which the treatments were trying to improve upon.
  • After the treatment had been applied, forage biomass were measured across the different trial plots using a rising plate meter, satellite and drone WDRVI (Wide Dynamic Range Vegetation Index) imagery.
  • The grass measurements from all three methods were then compared to test the effects the agronomic treatments had on grass yield.

Project Outcomes:

  • Analysis of the information from the drone and satellite technology showed it could detect significant differences in agronomic treatments applied on the farms as well as data that could not be picked up by plate meters.
  • The project also showed that the drone was able to detect the smallest treatment differences at a level two or three times smaller than the satellite used. 
  • This project had identified advantages and disadvantages of each grass measurement technique which allow farmers who wish to utilise this new technology to decide which technique would best suit their system.
  • These new methods could potentially provide a non-labour intensive method of accurately measuring grass which can improve farm viability and competitiveness.