Precision farming

Farming is under pressure to produce more food, animal feed and fibre while using fewer chemicals. There is also a drive to use less energy and labour while at the same time improving the environmental management of land and water. One way to achieve these goals is through ‘precision farming’, the control of farm implements working the land, how they apply seeds, fertilisers and agrochemicals, and harvest the crop.

The recent Foresight report, Land Use Futures: Making the most of land in the 21st century, summed up these aspirations for the UK when it said “precision farming and technologies that monitor soil condition and water quality will enable farming to maintain high levels of productivity while reducing its environmental burden.” For this to happen, farmers have to know what is happening on their land, and the health of their crops from place to place throughout a field. Precision farming develops technologies that can locate and control the positions of farm vehicles with sensors that can analyse crops at the right scale.

Accurate location

Precision farming became possible in the early 1990s, when the US declassified the global positioning system (GPS), the network of satellites developed during the cold war for military navigation. GPS, a ubiquitous technology found in most smartphones, can locate and track a vehicle’s position with an accuracy of around 10 metres. This does not provide the accuracy and repeatability required for precise field machine operations, so many farm equipment suppliers use real time kinematic (RTK) systems which employ two or more GPS receivers, connected by radio, to refine positioning accuracy. With RTK, one GPS receiver operates as a base station while the other is on the moving vehicle. RTK can provide positioning accuracy down to a couple of centimetres.

In farming, one of the first sectors to utilise GPS, the development of the technology improved alongside the ability to collect data on the state of soil and crops. Knowing the location of agricultural machinery makes possible the production of yield maps by linking the position of a harvesting machine to instantaneous measurements of crop yield. Precision farming can then use these maps, along with other information, to control the application of agrochemicals, matching the distribution of fertilisers, herbicides and pesticides to the varying conditions in crops and fields.

Suppliers of tractors and agricultural machines can integrate GPS with machine guidance and automatic steering to maintain parallel pathways at the machine’s operating width across the field. Automated systems can also lift ploughs and other implements from the soil at a field’s headlands, steer a tractor into position and lower the implement in the right place for the next pass. This not only means that the equipment sticks to its intended path, but also reduces operator fatigue and increases safety: the operator can concentrate on the operation in hand rather than steering the machine.

GPS systems and automated farm machinery can also extend the working day. For example, the managers of large state farms in Heilongjiang in northeast China have reported that they achieved a 40% increase in machine productivity by allowing equipment to operate in poor light conditions and at night. As well as extending the operating period, this approach can also allow field operations to take place when the soil, crop and weather conditions are optimal, with the potential to improve crop yield and quality.

Farm vehicles that can follow an accurate and controlled route through crops can minimise the overlap between machine passes through a field, thereby avoiding the risk that some areas will receive a double dose of seeds, fertilizer and agrochemicals. By the same measure, productivity is improved by ensuring that there are no gaps where crops may not have been planted or have received the required agrochemical.

Soil compaction

Tractors and harvesters have increased dramatically in size and weight since the Second World War. Tractors of 15 to 25 tonnes, more than 10 times the weight of the classic Ferguson of the immediate post-war years, are not uncommon. Fully laden combine harvesters can weigh 30 tonnes, with sugar beet harvesters weighing as much as 50 tonnes. The latter often work through the winter, when the soil is soft and wet.

Traditional vehicles can be of varying widths, so wheel traffic has the potential to damage most of a field in a single season. If not managed correctly, this traffic can compact soil, leading to significant problems in subsequent years, reducing crop yield, increasing rainfall runoff and, in some circumstances, raising the risk of flooding and soil erosion.

One way to alleviate soil compaction is through controlled traffic farming (CTF) – see Wheels within fields. CTF separates the cropped and wheeled areas, with all fieldgoing operations on the same wheel tracks. By utilising GPS and automatic steering, CTF can reduce the field area damaged by wheels from as high as 85% of the field area to 15%, and increase yields by between 9% and 35%. It can also increase infiltration of rainfall into the soil by up to 400%, reducing runoff and flooding, and save fuel by increasing the efficiency of field machinery.

It can take time for farmers to convert to CTF and to ensure that their vehicles have compatible axle widths. Despite these challenges, a growing number of farmers, accounting for more than 50,000 hectares in the UK, use CTF systems today.

Mapping fields and crops

As well as the ability to control the position and operation of equipment, precision farming relies on knowing what is going on where in a field, and how crops are responding to soil conditions, pests and diseases, and the weather. Linking the GPS position of the harvesting machine to a real-time record of the mass or volumetric flow of the crop during the harvesting process provides the information required to generate yield maps.

Variations in soil type, direction of the field slope and other factors can affect the growth and yield of a crop within a field. More critically, yield maps give farmers data on the magnitude of the differences in yield and their distribution throughout the field. Yield maps can be combined with other data, such as soil maps derived from the measurement of electrical conductivity – which senses variation in soil moisture, which in turn is related to the amount of sand, silt and clay in that part of the field. This can help in the creation of an application map to control the rate at which a fertilizer distributor, equipped with GPS applies fertilizer as it traverses the field.

The application of nitrogen is an example of how farmers have changed how they use data such as yield maps. Early management scenarios took the yield map from the previous season: if this showed an area of the field that did not perform well then farmers could apply more or less nitrogen to that area while more productive areas of the field received less, or increased amounts of, fertilizer. It soon became apparent that while planning nitrogen application maps from previous years gave a valuable insight into the variability of the field, this was not ideal. Planning how to apply nitrogen required real-time sensing of the crop’s condition.

In the UK, farmers currently measure the status of the crop canopy when, or just before, they apply nitrogen, typically at three growth stages in the development of the crop between February and May. By comparing the canopy size to that expected of a healthy crop, agronomists can produce application maps to match the spread of nitrogen to local plant conditions.

Agronomists currently use sensors on satellites, light aircraft or agricultural vehicles to map crop conditions by observing the crop’s red and near-infrared reflectance to determine the normalised difference vegetation index (NDVI). Remote sensing, though, has to contend with the weather, and the possibility that clouds will obscure the ground at crucial times.

The technology of crop monitoring has now reached a stage where farmers can buy crop monitoring as a service. For example, the precision farming company SOYL provides farmers with satellite images of crops as an aid to crop management. The company is also developing ways to control the application of agrochemicals. Pilot studies using satellite images have shown overall increases of 3% to 7% in wheat yield. Calculations of nitrogen balance based on Cranfield University’s data suggested an overall reduction in the nitrogen remaining in the soil after the harvest of approximately one third, hence improving the overall efficiency of nitrogen use and reducing nitrogen leaching.

More recently, small-unmanned aerial vehicles (UAVs), popularly known as drones, have gathered aerial data. UAVs can fly below clouds, quickly scanning fields and immediately transmitting the data. The challenge is to make sensors light enough so that small UAVs can cover a sufficiently large area in a single flight and carry the camera payload.

The company URSULA Agriculture uses UAVs to image crops. It can then provide growers with information on weed problems and can forecast yields for crops such as lettuce and onions. The company is also investigating disease mapping in potato crops and is trying to identify areas of persistent blackgrass in cereal crops. The objective is to deliver pesticides to their targets more effectively and to reduce the use of chemicals. URSULA Agriculture’s UAV data can also help farmers when they make decisions on which varieties to grow, as well as their choice of which machinery to use and rotation planning.

The ultimate advancement for crop analysis is to place sensors on tractors. These measurements are less prone to problems caused by adverse weather and provide the closest and most accurate real-time assessments of a crop’s state. However, unless data collection and nitrogen application can happen simultaneously, tractor-mounted sensors require additional, relatively slow field operations to gather data on the state of the crop. The fertiliser company Yara provides a commercial service using on-board algorithms to estimate the required application rate for fertiliser. The algorithm is programmed from the results of many field studies, and recent versions now permit the addition of local field knowledge that the farmer or the agronomist may wish to take into consideration.

Herbicides

As well as knowing when and where to apply fertilisers, farming has to face the challenge of weed control and pressure to reduce the use of herbicides. Growers of field vegetable and salad crops, for example, try to minimise the use of herbicides for weed control, partly in response to customer pressure, but also because of crop resistance and environmental issues, such as groundwater contamination. Quality salad and leafy vegetable products do require high levels of weed control, however, so reducing the use of chemicals increases the need for other methods – see Weed control.

Precision farming can also help agriculture to adapt to the shrinking armoury of herbicides that farmers are allowed to use. Over the past decade, their introduction has been limited, due to the increasingly stringent regulatory requirements, the cost of development and the size of markets. As a result, controlling grass weeds in cereal crops is now a major issue for arable farmers. The weeds are resistant to the selective herbicides that have been the mainstay of weed control in arable crop rotations.

One technological approach to maintaining an acceptable level of weed control involves growing crops with a wider space between rows, typically 20 to 25cm rather than the traditional 10 to 24cm, and using precision guidance to deliver a non-selective herbicide to the area between rows. Machinery makers have developed commercial systems that use either computer vision to detect crop rows, and the gap between them, or RTK GPS to enable units to be positioned with accuracies in the order of 25mm. Here the technique used is to deploy specialised nozzle systems, shrouds and shields to protect crops from spray drift.

An underlying theme of these developments in precision farming is the need to know and control the position of the vehicles that are applying agrochemicals and removing weeds. Vehicles that can operate free of the controlling hand of the driver are already making inroads into agriculture. As with automobiles, we can expect to see driverless tractors in the not-too-distant future. These will use GPS, machine guidance and auto-steer technologies. These may eventually develop into fully autonomous vehicles.

However, farm vehicles can be very much larger and heavier than cars. The major concern for fully autonomous 15-tonne, 300hp tractors is the issue of liability should the control and fail-safe shutdown systems malfunction. A partial solution is the adoption of a ‘master and slave’ system, where one or more machines follow an operator-controlled lead machine. In the UK, smaller robotic field machines will probably find an initial application in crop protection, weed control and harvesting in horticultural and field vegetable production.

Next steps

Through developments like those described here, agricultural engineers can play an important part in feeding people more efficiently and with less damage to the environment. Engineering solutions such as those underlying precision farming systems can buy time until agriculture can reap the benefits of longer-term research into plant and animal genetics. Bettering the precision and efficiency in farming operations has already helped to increase crop yields, and to reduce inputs and labour. It has also brought environmental benefits by reducing residual nitrogen, and by reducing or replacing herbicides with spot and mechanical weed control. It has also improved the infiltration of rainfall into the soil, potentially reducing flooding risk and increasing the economic viability of agriculture.

We can expect to see further advances in agricultural engineering, with, for example, the rise of robotics. However, for this to happen, we need to understand the role that engineering can play in agriculture. As the Institution of Agricultural Engineers (IAgrE) said in its report Agricultural Engineering: a key discipline enabling agriculture to deliver global food security, “The contribution of engineering needs to be more widely recognised in meeting societal challenges in global food security and contributing to economic growth, and an engineering community addressing these issues needs to be established with effective links to the key stakeholders.”

The example of precision agriculture demonstrates the assertion in the IAgrE’s report that “Sophisticated sensing technologies like real-time computer-based image analysis can be used with confidence to control agricultural machines, and permit, for example, effective weed management with minimal pesticide.” With its long-standing and globally recognised tradition in agricultural engineering, the UK is well placed to lead the way.

The next few decades of population growth will place huge strains on the way we need to farm. Agricultural machinery, along with its associated products and services, will be key to providing new technology platforms for improved field management. To facilitate this, there will need to be wise leadership, sufficient investment and well-trained operators, as well as engineers and researchers in the field. In short, we need to protect our agricultural capital and develop our human capital.

***

The author would like to thank the following for their contributions to this article: Dr Tim Chamen (Controlled Traffic Europe), Dr Paul Miller (NIAB-TAG), Dr Nick Tillet (Tillet and Hague Technology Ltd), Professor Simon Blackmore (Harper Adams University) and Michael Kenward OBE.

This article has been adapted from "Precision farming", which originally appeared in the print edition of Ingenia 64 (September 2015).