Precision agriculture
Precision agriculture (PA) is a farming management strategy based on observing, measuring and responding to temporal and spatial variability to improve agricultural production sustainability.[2] It is used in both crop and livestock production. Precision agriculture often employs technologies to automate agricultural operations, improving their diagnosis, decision-making or performing.[3][4] The goal of precision agriculture research is to define a decision support system for whole farm management with the goal of optimizing returns on inputs while preserving resources.[5][6]
Among these many approaches is a phytogeomorphological approach which ties multi-year crop growth stability/characteristics to topological terrain attributes. The interest in the phytogeomorphological approach stems from the fact that the geomorphology component typically dictates the hydrology of the farm field.[7][8]
The practice of precision agriculture has been enabled by the advent of
Precision agriculture has also been enabled by
History
Precision agriculture is a key component of the third wave of modern
Overview
The first wave of the precision agricultural revolution came in the forms of satellite and aerial imagery, weather prediction, variable rate fertilizer application, and crop health indicators.[16] The second wave aggregates the machine data for even more precise planting, topographical mapping, and soil data.[17]
Precision agriculture aims to optimize field-level management with regard to:
- crop science: by matching farming practices more closely to crop needs (e.g. fertilizer inputs);
- environmental protection: by reducing environmental risks and footprint of farming (e.g. limiting leaching of nitrogen);
- economics: by boosting competitiveness through more efficient practices (e.g. improved management of fertilizer usage and other inputs).
Precision agriculture also provides farmers with a wealth of information to:
- build up a record of their farm
- improve decision-making
- foster greater traceability
- enhance marketing of farm products
- improve lease arrangements and relationship with landlords
- enhance the inherent quality of farm products (e.g. protein level in bread-flour wheat)
Prescriptive planting
Prescriptive planting is a type of farming system that delivers data-driven planting advice that can determine variable planting rates to accommodate varying conditions across a single field, in order to maximize yield. It has been described as "
Principles
Precision agriculture uses many tools but here are some of the basics: tractors, combines, sprayers, planters, diggers, which are all considered auto-guidance systems. The small devices on the equipment that uses GIS (geographic information system) are what makes precision agriculture what it is. You can think of the GIS system as the “brain.” To be able to use precision agriculture the equipment needs to be wired with the right technology and data systems. More tools include Variable rate technology (VRT), Global positioning system and Geographical information system, Grid sampling, and remote sensors.[20]
Geolocating
- The field is delineated using an in-vehicle GPS receiver as the farmer drives a tractor around the field.
- The field is delineated on a basemap derived from aerial or satellite imagery. The base images must have the right level of resolution and geometric quality to ensure that geolocation is sufficiently accurate.
Variables
Intra and inter-field variability may result from a number of factors. These include climatic conditions (
Strategies
Using soil maps, farmers can pursue two strategies to adjust field inputs:
- Predictive approach: based on analysis of static indicators (soil, crop cycle.
- Control approach: information from static indicators is regularly updated during the crop cycle by:
- sampling: weighing biomass, measuring leaf chlorophyll content, weighing fruit, etc.
- remote sensing: measuring parameters like temperature (air/Wireless Sensor Networks[22] and Internet of things(IoT)
- proxy-detection: in-vehicle sensors measure leaf status; this requires the farmer to drive around the entire field.
- aerial or satellite remote sensing: multispectral imagery is acquired and processed to derive maps of crop biophysical parameters, including indicators of disease.[23] Airborne instruments are able to measure the amount of plant cover and to distinguish between crops and weeds.[24]
Decisions may be based on decision-support
It is important to realize why PA technology is or is not adopted, "for PA technology adoption to occur the farmer has to perceive the technology as useful and easy to use. It might be insufficient to have positive outside data on the economic benefits of PA technology as perceptions of farmers have to reflect these economic considerations."[25]
Implementing practices
New information and communication technologies make field level crop management more operational and easier to achieve for farmers. Application of crop management decisions calls for agricultural equipment that supports variable-rate technology (
Precision agriculture uses technology on agricultural equipment (e.g. tractors, sprayers, harvesters, etc.):
- GPSreceivers that use satellite signals to precisely determine a position on the globe);
- geographic information systems(GIS), i.e., software that makes sense of all the available data;
- variable-rate farming equipment (seeder, spreader).
Usage around the world
The concept of precision agriculture first emerged in the United States in the early 1980s. In 1985, researchers at the University of Minnesota varied lime inputs in crop fields. It was also at this time that the practice of grid sampling appeared (applying a fixed grid of one sample per hectare). Towards the end of the 1980s, this technique was used to derive the first input recommendation maps for fertilizers and pH corrections. The use of yield sensors developed from new technologies, combined with the advent of GPS receivers, has been gaining ground ever since. Today, such systems cover several million hectares.
In the American Midwest (US), it is associated not with sustainable agriculture but with mainstream farmers who are trying to maximize profits by spending money only in areas that require fertilizer. This practice allows the farmer to vary the rate of fertilizer across the field according to the need identified by GPS guided Grid or Zone Sampling. Fertilizer that would have been spread in areas that don't need it can be placed in areas that do, thereby optimizing its use.
Around the world, precision agriculture developed at a varying pace. Precursor nations were the United States, Canada and Australia. In Europe, the United Kingdom was the first to go down this path, followed closely by France, where it first appeared in 1997–1998. In
While digital technologies can transform the landscape of agricultural machinery, making mechanization both more precise and more accessible, non-mechanized production is still dominant in many low- and middle-income countries, especially in sub-Saharan Africa.[3][4] Research on precision agriculture for non-mechanized production is increasing and so is its adoption.[29][30][31] Examples include the AgroCares hand-held soil scanner, uncrewed aerial vehicle (UAV) services (also known as drones), and GNSS to map field boundaries and establish land tenure.[32] However, it is not clear how many agricultural producers actually use digital technologies.[32][33]
Precision livestock farming supports farmers in real-time by continuously monitoring and controlling animal productivity, environmental impacts, and health and welfare parameters.[34] Sensors attached to animals or to barn equipment operate climate control and monitor animals’ health status, movement and needs. For example, cows can be tagged with the electronic identification (EID) that allows a milking robot to access a database of udder coordinates for specific cows.[35] Global automatic milking system sales have increased over recent years,[36] but adoption is likely mostly in Northern Europe,[37] and likely almost absent in low- and middle-income countries.[38] Automated feeding machines for both cows and poultry also exist, but data and evidence regarding their adoption trends and drivers is likewise scarce.[3][4]
The economic and environmental benefits of precision agriculture have also been confirmed in China, but China is lagging behind countries such as Europe and the United States because the Chinese agricultural system is characterized by small-scale family-run farms, which makes the adoption rate of precision agriculture lower than other countries. Therefore, China is trying to better introduce precision agriculture technology into its own country and reduce some risks, paving the way for China's technology to develop precision agriculture in the future.[39]
In December 2014, the Russian President made an address to the Russian Parliament where he called for a National Technology Initiative (NTI). It is divided into subcomponents such as the FoodNet initiative. The FoodNet initiative contains a set of declared priorities, such as precision agriculture. This field is of special interest to Russia as an important tool in developing elements of the bioeconomy in Russia.[40][41]
Economic and environmental impacts
Precision agriculture, as the name implies, means application of precise and correct amount of inputs like water, fertilizer, pesticides etc. at the correct time to the crop for increasing its productivity and maximizing its yields. Precision agriculture management practices can significantly reduce the amount of nutrient and other crop inputs used while boosting yields.[42] Farmers thus obtain a return on their investment by saving on water, pesticide, and fertilizer costs.
The second, larger-scale benefit of targeting inputs concerns environmental impacts. Applying the right amount of chemicals in the right place and at the right time benefits crops, soils and groundwater, and thus the entire crop cycle.[43] Consequently, precision agriculture has become a cornerstone of sustainable agriculture, since it respects crops, soils and farmers. Sustainable agriculture seeks to assure a continued supply of food within the ecological, economic and social limits required to sustain production in the long term.
A 2013 article tried to show that precision agriculture can help farmers in developing countries like India.[44]
Precision agriculture reduces the pressure of agriculture on the environment by increasing the efficiency of machinery and putting it into use. For example, the use of remote management devices such as GPS reduces fuel consumption for agriculture, while variable rate application of nutrients or pesticides can potentially reduce the use of these inputs, thereby saving costs and reducing harmful runoff into the waterways.[45]
GPS also reduces the amount of compaction to the ground by following previously made guidance lines. This will also allow for less time in the field and reduce the environmental impact of the equipment and chemicals.
Precision agriculture produces large quantities of varied sensing data which creates an opportunity to adapt and reuse such data for archaeology and heritage work, enhancing understanding of archaeology in contemporary agricultural landscapes.[46]
Emerging technologies
Precision agriculture is an application of breakthrough digital farming technologies. Over $4.6 billion has been invested in agriculture tech companies—sometimes called agtech.[15]
Robots
Agricultural robots, also known as AgBots, already exist, but advanced harvesting robots are being developed to identify ripe fruits, adjust to their shape and size, and carefully pluck them from branches.[50]
Drones and satellite imagery
Drone and satellite technology are used in precision farming. This often occurs when drones take high quality images while satellites capture the bigger picture. Aerial photography from light aircraft can be combined with data from satellite records to predict future yields based on the current level of field biomass. Aggregated images can create contour maps to track where water flows, determine variable-rate seeding, and create yield maps of areas that were more or less productive.[43]
The Internet of things
The Internet of things is the network of physical objects outfitted with electronics that enable data collection and aggregation. IoT comes into play with the development of sensors[51] and farm-management software. For example, farmers can spectroscopically measure nitrogen, phosphorus, and potassium in liquid manure, which is notoriously inconsistent.[43] They can then scan the ground to see where cows have already urinated and apply fertilizer to only the spots that need it. This cuts fertilizer use by up to 30%.[50] Moisture sensors[52] in the soil determine the best times to remotely water plants. The irrigation systems can be programmed to switch which side of tree trunk they water based on the plant's need and rainfall.[43]
Innovations are not just limited to plants—they can be used for the welfare of animals. Cattle can be outfitted with internal sensors to keep track of stomach acidity and digestive problems. External sensors track movement patterns to determine the cow's health and fitness, sense physical injuries, and identify the optimal times for breeding.[43] All this data from sensors can be aggregated and analyzed to detect trends and patterns.
As another example, monitoring technology can be used to make beekeeping more efficient. Honeybees are of significant economic value and provide a vital service to agriculture by pollinating a variety of crops. Monitoring of a honeybee colony's health via wireless temperature, humidity and CO2 sensors helps to improve the productivity of bees, and to read early warnings in the data that might threaten the very survival of an entire hive.[53]
Smartphone applications
Smartphone and tablet applications are becoming increasingly popular in precision agriculture. Smartphones come with many useful applications already installed, including the camera, microphone, GPS, and accelerometer. There are also applications made dedicated to various agriculture applications such as field mapping, tracking animals, obtaining weather and crop information, and more. They are easily portable, affordable, and have high computing power.[54]
Machine learning
Machine learning is commonly used in conjunction with drones, robots, and internet of things devices. It allows for the input of data from each of these sources. The computer then processes this information and sends the appropriate actions back to these devices. This allows for robots to deliver the perfect amount of fertilizer or for IoT devices to provide the perfect quantity of water directly to the soil.[55] Machine learning may also provide predictions to farmers at the point of need, such as the contents of plant-available nitrogen in soil, to guide fertilization planning.[56] As more agriculture becomes ever more digital, machine learning will underpin efficient and precise farming with less manual labour.
Conferences
- InfoAg Conference
- European conference on Precision Agriculture (ECPA) (biennial)
- International Conference on Precision Agriculture (ICPA) (biennial)
See also
- Agriculture – Cultivation of plants and animals to provide useful products
- Agricultural drones
- Automatic milking – Milking of dairy animals without human labour
- Geostatistics – Branch of statistics focusing on spatial data sets
- Integrated farming – Agricultural management system
- Integrated pest management – Approach for economic control of pests
- Landsat program – American network of Earth-observing satellites for international research purposes
- NDVI– Graphical indicator of remotely sensed live green vegetation
- Nutrient budgeting – Comparison between nutrients in soil and in crops
- Nutrient management – Management of nutrients in agriculture
- Phytobiome – Community of plants (phyto) situated in their specific ecological areas (biome)
- Precision beekeeping – Monitoring of individual bee colonies
- Precision fermentation– Biochemical process applied in industrial production
- Precision livestock farming
- Precision viticulture – Precision farming applied to optimize vineyard performance
- Satellite crop monitoring
- SPOT (satellites)– Commercial Earth-imaging satellite system operated by the French space agency CNES
- Variable rate technology– Precise use of a material in agriculture
Sources
This article incorporates text from a free content work. Licensed under CC BY-SA 3.0 (license statement/permission). Text taken from In Brief to The State of Food and Agriculture 2022 – Leveraging automation in agriculture for transforming agrifood systems, FAO, FAO.
Notes
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External links
Media related to Precision farming at Wikimedia Commons