Description

Precision agriculture is an umbrella term for using modern data-driven technologies for growing crops. Compared to traditional techniques, precision agriculture has many advantages. Implementing precision technologies can play a role in understanding local soil types, improving soil quality, making realistic crop choices, managing irrigation timing planting and harvest moments, planning and application of disease, pest and weed management, nutrient application, monitoring and yield prediction. Precision agriculture provides an improved understanding of the spatial demands of a particular agricultural area, which can be coupled with highly accurate decision support tools and early warning systems. Application of these tools prevents wasteful actions, and provides information for timely management. By optimising the use of water, chemicals and energy, precision agriculture reduces the sector’s vulnerability to climate change, especially considering droughts, extreme weather events and climate-related pests and diseases. Decisions about how much fertilizer, when to spray, when to water (and how much) can be made using decision support systems connected with the equipment in the field. This allows farmers to control important processes remotely, saving time, energy and resources. This will not only improve yield but could also impart predictive forecasting, which leads to appropriate and timely action. This allows for greater flexibility in adapting the entire harvest to extreme weather events as well since forecasting and other data-driven environmental factors can be formulated and updated in real time. 

The technologies used in precision agriculture are constantly evolving. The Internet of Things (IoT), Big Data analysis, artificial intelligence (AI), and machine learning could all be used, optimized and combined to make informed management decisions. In addition, increasing availability of high resolution (spatial, spectral and temporal) satellite images has promoted the use of remote sensing for agriculture as well. 

Precision agriculture techniques require the integration between software and hardware on three different spatial levels:  

  • Ground: this is where the physical actions are executed locally with agricultural machinery, irrigation equipment, or active or passive detection equipment. GPS (Global Positioning System)  is used with ground-based equipment to gather real-time location information allowing for maps of the irrigation system, fields, and surrounding landscape. It can also help localize problem areas (from flooding to pest outbreaks). GPS can also steer the tractor or provide specific seed or fertilizer application maps integrated with the appropriate equipment. 
  • Aerial: Unmanned aerial vehicles (drones) or crop dusters already used for irrigation, spraying or sowing, can be used for monitoring or detecting crop reflective properties by connecting a camera with multispectral, hyperspectral or thermal sensors. Crop reflective properties  indicate very common farming issues such as weed density, disease prevalence, nutrient deficiency, etc. 
  • Satellite: Similar to above, satellites can monitor larger landscape level patterns. This monitoring is usually on a larger spatial scale/ with lower resolutions than aerial drones, which can observe the earth’s properties and the regional weather patterns for forecasting, and detecting  vegetation indices. The data from satellites can be acquired from open sources and services such as the Copernicus Land Monitoring Service.   

Adaptation Details

IPCC categories
Social: Informational, Structural and physical: Technological options
Stakeholder participation

Generally, the farmer or landowner is directly involved in implementing new precision technologies with any associated technology companies. Precision agriculture also depends on the availability and accessibility of third-party datasets or satellite or weather data streams. Therefore, strong collaboration between farmers, farm advisory services (that provide farmers with knowledge and skills), researchers, and policymakers is needed. Often the implementation of this option may require a connection with a regional or national governmental program or association that provides land cover information and resources. Local solutions can also be implemented without external input but may be more costly or require in-house expertise.  

Success and Limiting Factors

Precision farming technology provides integrated tools for better decision-making in agriculture. Although farmers generally look to adopt precision technologies that reduce costs, precision farming has many benefits that can favour the success of this option. Precision agriculture can help make informed decisions about planting, managing and harvesting, help manage local fertilization, and irrigation quantities. With the right tools, precision techniques can steer machinery, locate and manage pest, diseases or drought and protect the soil from leaching or drying out, thereby saving costs, reducing wasted crops and fuel, and managing the workload. Initiatives that increase farmers’ awareness on these benefits, and knowledge of diverse techniques and skills can favour the actual implementation of this option. 

Despite the many benefits and wide array of precision tools available, precision agriculture still has a very low implementation rate. Some explanations for the low adoption rate have been identified, including high costs of investment and learning, extra work, cost/benefit ratio, doubts in the credibility of the technologies, farmer’s perception of usefulness, ease of use, farmer’s age and education level, and resource availability. The biggest issue/limitation for growers is knowing how to interpret all of the data collected and how to act on it. Results of the EU-funded Demeter project (H2020) revealed that data privacy could be a relevant concern for farmers, worried that third parties would gain ownership of their private data. Lack of resources and high implementation costs were reported as major barriers. Small operators may be left behind from this option without the resources or the proper knowledge, which may have implications for just resilience. 

 

Costs and Benefits

The purchase cost of the precision agriculture infrastructure and services can be high due to the investments needed to  use of this technology on an individual/farm-based level and the fee associated with the specific service. Time and money are required for training and knowledge provision, expensive or highly specialised machinery or technologies, or a dedicated outsourced service provider. Small farmers in the current situation without common standards often prove unable to fix or adjust equipment, forcing them to risk delays and expenses when returning to manufacturers for appropriate technical support. Costs are associated with the deployment of the system (e.g. hardware and software, training, licensing) and operation (repair, maintenance). There are several known European incentives as precision agriculture, that can support the implementation of the Common Agricultural Policy.  

Some cost examples (Farm-europe) include:  

  • Weather stations require an investment of between €400 and €2,000.  
  • Decision support tools can be free of charge. Those that prescribe the quantities of inputs to be applied from sensors and satellite images of crops have a maximum cost of €20/ha/year.  
  • Precision sprayers can vary from €3,000 - €40,000.  
  • Machine Guidance (MG) and Controlled Traffic Farming (CTF) to gain in precision at the intra-plot scale:  cost varies from around €1,300 - €50,000  
  • Weeding robots cost between €25,000 and €80,000. 
  • Flow controllers for pivot irrigation systems are the most affordable starting at €1,300 and pivot control irrigation management systems can cost up to €35,000. Drip irrigation costs around €40/ha. 
  • Whatever the tool and its cost, training is necessary and can vary between €420 and €1,400. 

Additional costs for the maintenance of machineries and technologies, though not specifically reported, must be considered. 

Using precision technologies reduce environmental degradation and increases fuel efficiency resulting in lowering carbon footprints (synergy with mitigation aspects). Examples include reduced nitrate leaching in cropping systems, reduced groundwater contamination by extracting the spraying regimes and reduced erosion when precise tillage is conducted. The benefits for farmers are saving costs (machinery, inputs) and farm productivity and income. A reduction of wasted seeds and products is also expected. Environmental benefits include reduced eutrophication (due to lower use of nutrients) and pollution (due to lower use of pesticides).  

Moreover, precision agriculture allows for saving water and energy. For example, saving water in high-value fruit and vegetable crops with precision irrigation methods was found to save about €30/ha/year (Balafoutis et al., 2017). The largest potential is expected in drought prone areas as the Mediterranean region. 

Implementation Time

One year is needed for implementing most technologies, but sometimes training and partnerships between technology providers or services could take longer. The implementation time depends on the technology and budget available. Some technology options require more training or funding than others, but all require a certain training or start-up period before they become fully operational. Thoroughly researching, training and preparing can significantly reduce the implementation time, and work together with experienced users. 

Life Time

This option includes a wide range of possible techniques with different lifetimes. Precision farming tools are so varied that this depends on the type of hardware/software that is used. Whenever implemented correctly, the software can be adapted in real time and remains relevant as long as the hardware required for data collection remains functional. In this case, the lifetime is dependent almost entirely on the durability of the hardware used in the implementation. 

 

Reference information

Websites:
References:

Sishodia RP, Ray RL, Singh SK. Applications of Remote Sensing in Precision Agriculture: A Review. Remote Sensing. 2020; 12(19):3136. https://doi.org/10.3390/rs12193136 

Khanna, A., & Kaur, S. (2019). Evolution of Internet of Things (IoT) and its significant impact in the field of Precision Agriculture. Computers and electronics in agriculture, 157, 218-231. https://doi.org/10.1016/j.compag.2018.12.039 

Ullo SL, Sinha GR. Advances in IoT and Smart Sensors for Remote Sensing and Agriculture Applications. Remote Sensing. 2021; 13(13):2585. https://doi.org/10.3390/rs13132585 

Erion Bwambale, Zita Naangmenyele, Parfait Iradukunda, Komi Mensah Agboka, Eva A. Y. Houessou-Dossou, Daniel A. Akansake, Michael E. Bisa, Abdoul-Aziz H. Hamadou, Joseph Hakizayezu, Oluwaseun Elijah Onofua & Sylvester R. Chikabvumbwa | Stefania Tomasiello (Reviewing editor) (2022) Towards precision irrigation management: A review of GIS, remote sensing and emerging technologies, Cogent Engineering, 9:1, DOI: 10.1080/23311916.2022.2100573 

European Parliament. Precision agriculture in Europe. Legal, social and ethical considerations 

European Parliament. Precision agriculture and the future of farming in Europe. Scientific Foresight Study 

Precision agriculture: an opportunity for EU farmers – potential support with the CAP 2014-2020  

Published in Climate-ADAPT Mar 20, 2023   -   Last Modified in Climate-ADAPT May 17, 2024

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