Smart Farming: New Technology Maximises Productivity

Smart Farming: New Technology Maximises Productivity

3 June 2011

AgResearch at the New Zealand National Agricultural Fieldays 2011

Smart Farming: New technology enables easier, accurate pasture measurements that maximise productivity

Funded by the Pastoral 21 feed programme (a joint investment by DairyNZ, Fonterra, Beef + Lamb New Zealand and the Ministry of Science and Innovation), a team of researchers led by Dr Robyn Dynes, Senior Scientist at AgResearch Lincoln, has been working to improve both pasture mass estimation techniques and real-time pasture quality measurements by developing what her colleague Dr Warren King calls "useful tools that could drive farm production by improving both the value and utilisation of pastures." This research will feature at the AgResearch exhibit at the National Agricultural Fieldays at Mystery Creek on 15-18 June 2011.

To estimate pasture mass, a technology called the C-Dax Pasture Meter has recently been introduced to provide more accurate and rapid measurements than could be achieved using previous devices. One of the key drivers of pasture productivity is grazing management, and how much and how often the pasture is grazed has a direct impact on both pasture production and quality.

The Pasture Meter is a commercially available tow-behind attachment for a quad bike, which enables rapid measurement over a large area. It continuously measures pasture height as the bike moves, and a calibration equation is then used to convert height into pasture mass. The calibrations used to make this conversion have, until recently, been based on restricted field data.

To address this issue, Dr Dynes' team began a project to develop customised calibrations to improve the accuracy of the C-Dax Pasture Meter. The team selected a range of paddocks in regions across New Zealand, and each month they measured the grass height and then cut, dried and weighed the grass to develop a set of calibrations converting grass height into pasture mass.

These measurements were repeated for a year so that the customised calibrations could be calculated for each region on a daily basis. The calculations were done for a number of dairy farms, as well as for beef and sheep farms in a reduced number of regions.

The calibrations should give farmers greater confidence in their ability to measure pasture mass, and now that the calculations have been included in the C-Dax Pasture Meter package, it is even easier for farmers to use them.

In addition to improved pasture mass estimation, Dynes' team has also focused on improving pasture quality measurements. In collaboration with Prof Ian Yule at Massey University, the researchers are developing new methods that can measure pasture quality parameters in real time, which will enable farmers to respond to diurnal and seasonal changes in nutrients such as protein and carbohydrates.

In the past, to get measurements of pasture quality parameters such as protein, carbohydrate, minerals and fibre, farmers would have to cut a sample of grass and send it off to a laboratory for analysis. They would then wait anywhere from three days to three weeks to get the results, by which time pasture conditions had changed and the measurements were no longer relevant to farm management.

Real-time measurements would enable farmers to react to, and thus take advantage of, short-term changes in nutrient levels. For example, when protein in pasture grass is too high relative to its carbohydrate content, leading to sub-optimal animal production, farmers could feed animals supplemental carbohydrates in the shed, thereby improving their productivity.

In addition, such feeding could also improve environmental performance. When animals ingest too much protein, they excrete the excess in their urine, which is a primary source of nitrogen leaching into groundwater and nearby waterways. High carbohydrate supplementary feed can reduce excreted nitrogen.

A second example of how pasture quality measurements can be used to drive both increased production and environmental performance is by using real-time measurements of nitrogen content in pasture to determine whether fertilisers are needed, and to develop a finely tuned, more efficient system for applying fertilisers, rather than just using a simple calendar schedule. Such a system could improve pasture production, reduce fertiliser costs and limit nitrogen losses to the environment.

Although currently no affordable devices are available for farmers to measure pasture quality in real time, such a device could be available in the future. The device will likely also operate as a tow-behind attachment on a quad bike.

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