A new way to practice agriculture

Christel Kenou

Rather than treat a farm and crops as if every plant is the same, farmers can use precision agriculture to apply inputs only where and when they are needed.

Precision agriculture (PA) is a smart farming system that helps farmers collect information and data for better decision making. PA requires the use of inventive data on environmental and soil conditions. Then farmers use collected information to add precision to the quantity, quality, timing and location in the application and use of agricultural inputs. PA allows crop farmers to take into account the variation in the field and to apply variable rate treatments with a much finer degree of precision than was earlier possible.

PA is, therefore, an ICT-based farm management system that permits farmers to consider the field as a heterogenous entity and then to apply selective treatment, rather than seeing it as a homogenous entity where all is treated equally. The technology involves a process of data collection, data mapping and analysis, and site-specific treatment.

Conventionally, agronomic practices and treatments are applied in uniform fashion. For example, a plot is designed to operate at uniform depth and produce uniform results over a wide range of crop and soil conditions. Similarly, a sprayer will apply the same amount of solution containing either fertiliser or pesticide. In contrast, precision agriculture helps to meet site-specific needs. It involves better management of farm inputs, such as fertilisers, herbicides, seed and fuel by helping the farmer to employ the right management practice at the right place and the right time.


The first applications of PA around the world started in the early 1990s, mostly in developing countries, including some ACP nations. However, it was really only adopted at the end of the 1990s, with yield monitors and soil mapping, which remain important for PA. Techniques then progressed to site-specific crop management based on grid sampling and management zones. More recently there has been increasing emphasis on real-time on-the-go monitoring with ground-based sensors.

PA covers four key ICTs: location determination via GPS; GIS; computer-guided controllers for variable rate application (VRA) of crop inputs; and sensing technologies for automated data collection and mapping. The GPS and GIS technologies underpin the major PA practices that farmers have begun to adopt. One of these is nutrient management; it involves spatially referenced soil sampling, often linked to VRA fertiliser spreading. The other is yield monitoring, usually tied to yield mapping.

Yield monitors are mainly used in North America, Europe and Australia, but countries like Argentina, Brazil and some East Asian countries have also adopted these practices. The adoption of PA is related to socio-economic, agro-ecological, institutional, technological and behavioural factors, in addition to the sources of information and perception of the farmer.

Global applications

Remote sensing in PA includes using satellites, aircraft, balloons and helicopters, small unmanned aerial systems, or drones, and a variety of sensors, such as optical and near-infrared and radar. Drones could be a potential alternative to satellites and aircraft given their low cost. Farmers can use them to spray pesticides over their crops or for tracking livestock and crop monitoring. Other potential applications of remote sensing in PA include bare soil imaging for management zone delineation, weed mapping, nitrogen stress detection, crop yield mapping, and pest and disease detection.

Benefits and impacts

PA offers many benefits in terms of profitability, productivity, sustainability, crop quality, environment protection, on-farm quality of life, food safety and rural economic development. Indeed, it has the potential to increase crop yields and ensure food security. PA tools can help farmers save money by increasing efficiencies in broad acre cropping systems and it can improve crop productivity and farm profitability through the improved management of farm inputs.

As pests and disease cause huge losses to crops in ACP countries, remote sensing can help to detect even small areas troubled by pathogens. The application of fungicides can then therefore be optimally timed. Moreover, remote sensing combined with GIS and GPS can help in site-specific weed management.

In addition, PA benefits the environment from more targeted use of inputs that reduce losses from excess applications and from reduction of losses due to nutrient imbalances, weed escapes and insect damage, for example. Indeed, studies revealed that site-specific nutrient management reduced nitrogen fertiliser use in Vietnam and the Philippines by 14% and 10%, respectively. It also reduced total nitrogen losses from the soil by 25% to 27%. The variable rates of herbicide application reduced total herbicide use, and preserved surface and groundwater quality. As a result, soil and water contamination is minimised.

Society also benefits from PA as it creates technology jobs (computer hardware, computer software, machinery guidance, soil and crop sensors, information management, decision support systems) and mitigates environmental pollution from the over-application of agricultural fertilisers.

In a nutshell, farmers using PA can reduce their environmental impact while improving productivity and profits. In addition to reducing inputs through improved accuracy, the information from PA technologies allows farmers to produce more output with less input.


The challenge is to develop PA approaches that can provide customised management of farm inputs for individual plants by using data from field sampling, laboratory analyses, and proximal and remote sensors (for example, spectral, electrical, electromagnetic or radiometric measurements of soils or of plants) with different spatial and temporal scales.

For smallholder farmers, the amount of data may limit the adoption of this technology. Therefore, to spur adoption in ACP countries, the operational implementation of the technology and complete analysis of the costs need to be emphasised. In addition, the role of extension services and agricultural cooperatives are important to spread the use of these technologies.

Related resources

Adekunle, IO. (2013). Precision Agriculture: Applicability and Opportunities for Nigerian Agriculture, Middle-East Journal of Scientific Research 13(9): 1230-1237

Bongiovanni, R., & Lowenberg-DeBoer, J. (2004). Precision agriculture and sustainability. Precision agriculture, 5(4), 359-387

Lindblom, J., Lundström, C., Ljung, M., & Jonsson, A. (2017). Promoting sustainable intensification in precision agriculture: review of decision support systems development and strategies. Precision Agriculture, 18(3), 309-331. Daberkow, S.G., McBride, W.D. (2000). Adoption of Precision Agriculture Technologies by U.S. Farmers, 5th International Conference on Precision Agriculture, Bloomington, Minnesota, USA

Guo-Wei, X., Li-Nian, Y. Hao, Z., Zhi-Qin, W., Li-Jun, L & Jian-Chang, Y. (2008). Absorption and utilisation of nitrogen, phosphorus, and potassium in rice plants under site-specific nitrogen management and wheat-residue incorporation. Acta Agronomica Scienca. 34: 1424–1434

McBratney, A., Whelan, B., Ancev, T., & Bouma, J. (2005). Future directions of precision agriculture. Precision agriculture, 6(1), 7-23

Srinivasan, A. (2006). Handbook of precision agriculture: principles and applications. New York, NY, USA: Food Products Press

Stafford, J. V. (2000). Implementing precision agriculture in the 21st century. Journal of Agricultural Engineering Research, 76(3), 267-275

Zhang, C., & Kovacs, J. M. (2012). The application of small unmanned aerial systems for precision agriculture: a review. Precision agriculture, 13(6), 693-712 Zhang, N, Wang, M., Wang, N. (2002). Precision agriculture. A worldwide overview. Comput Electron Agric. 36: 113-132


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