Precision agriculture: outlook and new applications
One of the most important challenges facing world agriculture in the coming decades is to increase food production, not only in quantity but above all by making it ever healthier for people and more sustainable for the environment. The FAO estimates that agri-food production will need to grow by at least 60% compared with the average of the last decade, to keep up with a world population expected to reach around 9 billion by 2050. Yet the global cultivated area will grow only marginally, so increasingly advanced farming systems will be needed to improve production and make the best use of available farmland. Precision Agriculture (PA) will undoubtedly play a major part in this.
In this article I will try to answer some key questions: what is Precision Agriculture? What are its goals? What benefits does it bring? How can it be put into practice? Enjoy the read!
What is precision agriculture?
Precision agriculture, also known as “precision farming”, can be seen as the set of technologies, principles and methods that allow farmers to work according to strategies for the best management of variability across fields and over time, also taking into account crop needs and the chemical and physical properties of the soil, with the aim of increasing yields while reducing costs.
There are several definitions of precision agriculture in the scientific literature. Perhaps the most complete is the one given by Pierce and Nowak (1999), who summed it up as “a system that provides the tools to do the right thing, in the right place, at the right time”, where “the right thing” means an agronomic operation. A more recent and broader definition describes precision agriculture as “farm management (agricultural, forestry and livestock) based on the observation, measurement and response to the set of quantitative and qualitative variables, between and within fields, that affect production. The aim is to define, after analysing site-specific data, a decision support system for the whole farm, in order to optimise returns with a view to advanced climate, environmental, economic, productive and social sustainability” (Casa and Sartori, 2015).
Managing variability in space and time
Within a field, production is very likely to be uneven: some areas yield more than others. This can be linked to many factors, for example incorrect application of inputs (such as fertiliser) or poorly executed sowing. Often, however, this variability is due to other elements that do not depend on the operator but are intrinsic to the field: differences in the physical and chemical composition of the soil, dips or low areas where water stagnates, or more compacted and therefore less porous zones. It is therefore essential to understand what causes variability, so as to find the most suitable ways to correct it where possible, or to adapt production to reduce waste. This can be considered the main goal of Precision Agriculture.
As we said, variability is not only spatial (this spot is different from that one) but also temporal (today is not like yesterday). Managing variability means that, once the necessary information has been gathered, production inputs are applied differently in time and space. For example, where we produced less we might decide to increase fertilisation to stimulate crop growth, or on the contrary reduce it if we think that the lower yield in that area is linked to characteristics that cannot be changed (soil texture). This is what doing the right thing, in the right place, at the right time means.
To do this you need specific technical skills and technologies able first to detect unevenness and then to apply crop inputs at variable rates within the field. Of course, techniques and inputs (tillage, fertilisation, treatments, sowing and so on) will always be applied according to crop needs, the chemical, physical and biological properties of the soil, the climate and weather, the history of the field and the experience of the person assessing it.
It is also worth remembering that precision agriculture can be adopted at different levels of complexity, from the most basic, such as assisted guidance, to the most complex, such as decision support systems (DSS), prescription maps and traceability systems. For a farm it is not an overnight change: it has to be done step by step, with the aim of improving production efficiency and reducing environmental impact, as part of sustainable agriculture.
The tools available
Today farms have many technologies available to improve the management of their fields. From a purely agronomic point of view, the best known and most widely used are:
- Monitoring tools. They detect and explain what is happening in the field through remote measurements (satellite maps) or proximal ones (drones, field surveys, soil analysis, weather stations, yield maps).
- Forecasting tools. They estimate what is happening in the field without direct measurement (estimates of irrigation or fertiliser needs, crop development and plant disease models).
- Decision and prescription tools for data-driven decisions, comparing and combining significant data (DSS, decision support systems).
- Application systems. They put decisions and prescriptions into practice in the field (parallel guidance, automatic steering, actuators, variable rate technology).
- Traceability systems. They track the life cycle of the product from field to consumer.
All these tools should work in a georeferenced way. Georeferencing is a now well-known technique that gives the exact position of the machine while it works (the level of precision depends on the reference system used), thanks to a receiver connected to satellite systems. We will look at this and other aspects, as well as Top Melon’s experience with precision agriculture, in a future article.
Photo: Agritaly
