ANALYSIS - Agriculture and livestock farming needs to target better what it is putting into production in order to achieve improved yields.
Dr Pete Berry from agricultural advisors ADAS, speaking at the Smart Agriculture conference in Birmingham, UK, said that the improved targeting needed to be in both time and space – field by field, metre by metre.
By concentrating on targeting inputs into production, the farmer can reduce input costs and improve yields while at the same time ensuring compliance with regulations.
At present the farming sector has practiced and proven technology that is already helping to improve production and target more precisely the work and inputs on the farm, including GPS guidance, auto steer, accurate tramlines and automated record keeping.
There is also new technology in the development phase that will help improve farming practices including variable cultivation and seed rate, variable rate fertiliser and targeted herbicides.
However, there are also technologies for the future that will help the farmer including variable plant growth regulators, pest targeting and variable rate fungicides.
Dr Berry said that there are limitations in the current technology that are holding back the use of smart agriculture as at present agronomic understanding is not sufficiently quantitative, as, for example, it does not give sufficient information about how to manage different soil types.
He added that new technologies also do not always provide correct data.
Dr Berry told the conference that there is a need to develop ways of using existing information or to develop new technologies to measure the correct data.
He said there is a need for accurate weather forecasting and accurate yield prediction and efficient ways of integrating different data types have to be found.
There is an information gap in the knowledge of field validation such as knowing precisely the nitrogen needs in fertilisers, he said, as some fields will require different quantities as the nitrogen content of the soil varies from place to place.
He said that there are other areas of production that also require increased input of information including identifying yield limitation factors.
However, he said that new systems are being produced, such as the Agronomics system, designed to address these new demands and challenges.
He said that Smart Agriculture can help solve key challenges with better input targeting helping to bridge the yield gap. “Smart Agriculture relies on sound agronomic principles,” he said.
And he added that it is important to be able to test Smart Agriculture ideas and products on farms and to provide opportunities for farmers and scientists to work together more closely.
Where is Smart Agriculture heading in future?
Dr Berry described areas for development, including improving quantitative agronomic understanding and the provision of better physiological models for yield prediction.
To help in these areas he said that developments are needed in integrating remote sensing information and providing more reliable weather forecasting.
He said that Smart Agriculture will require focussed data collection and technology to identify yield limiting factors.
He said there is a need for software and web platforms to integrate different technologies and data sources into a single tool.
In the near future sensing data will be more readily and cheaply available, Dr Berry said and all data will be held in the cloud and accessible by smart phone.
However, he added that interpretation will be key and he predicted that there will be a thriving marketplace for reliable algorithms in the agricultural and livestock sectors to produce better understanding of the crop and animal.
He said that new technology developments will mean continual sensing of crop or animal status.
“The key decisions for farmers will be what ideas to test and how to act on the results,” he said
“There will be a wider range of farming systems and management optimised for specific region, farm, field and metre environments.”