Precise farming ( PA ), satellite farming or site-specific crop management ( SSCM ) is a concept of agricultural management based on observation, measurement and response to variability between and in the field in plants. The purpose of precision agricultural research is to define decision support systems (DSS) for overall agricultural management with the aim of optimizing the return of inputs while maintaining resources.
Among the many approaches is the phytogeomorphological approach that links the stability/growth characteristics of multi-year crops to topological topology attributes. The interest in the phytogeomorphological approach stems from the fact that geomorphological components usually determine the hydrology of agriculture.
Precision farming practices have been made possible by the emergence of GPS and GNSS. The ability of farmers and/or researchers to locate their precise position in the field allows for the creation of a map of the spatial diversity of as many measurable variables as possible (eg yields, terrain features/topography, organic matter content, moisture level, nitrogen content, pH, EC, Mg, K, and others). Similar data is collected by the arrangement of sensors mounted on a combined harvester equipped with GPS. This array consists of real-time sensors that measure everything from chlorophyll levels to plant water status, along with multispectral images. This data is used in conjunction with satellite imagery by variable level technologies (VRT) including cleaners, sprays, etc. To distribute resources optimally.
Precision farming has also been activated by unmanned aerial vehicles such as the Phantom DJI which is relatively inexpensive and can be operated by novice pilots. This system, commonly known as drone, can be equipped with a hyperspectral or RGB camera to take many field shots that can be processed using photogrammetric methods to create orthophotos and NDVI maps.
Video Precision agriculture
History
Precision farming is a key component of the third wave of modern agricultural revolutions. The first agricultural revolution came during the rise of mechanization, from 1900 to 1930. Each farmer produced enough food to feed about 26 people during this time. The 1990s encouraged the Green Revolution with new genetic modification methods, which caused each farmer to feed about 155 people. It is expected that by 2050, the global population will reach about 9.6 billion, and food production must effectively double from the current levels to feed every mouth. With the advancement of new technology in the agricultural revolution of precision agriculture, every farmer will be able to feed 265 people on the same land.
Maps Precision agriculture
Overview
The first wave of the precision agricultural revolution will come in the form of satellite and air imagery, weather prediction, variable rate fertilizer application, and plant health indicators. The second wave will collect machine data for more precise cultivation, topographic mapping, and soil data.
Precision farming aims to optimize field-level management with regard to:
- cutting science: by matching farming practices closer to crop needs (eg fertilizer input);
- environmental protection: by reducing environmental risks and agricultural footprint (eg limiting nitrogen leaching);
- economy: by increasing competitiveness through more efficient practices (eg improvements in the management of fertilizer use and other inputs).
Precision farming also provides farmers with abundant information to:
- make a note of their farm
- improve decision making
- cultivate greater traceability
- improve the marketing of agricultural products
- improve lease arrangements and relationships with landlords
- improve the quality of inherent agricultural products (eg, protein levels in wheat bread)
Prescriptive planting
Prescriptive planting is a type of agricultural system that provides planting advice based on data that can determine the rate of planting variables to accommodate different conditions in one area, to maximize yield. It has been described as "Big Data on the farm." Monsanto, DuPont, and others are launching this technology in the US.
Tools
Precision farming is usually done as a four-stage process for observing spatial diversity:
Data collection
Field geolocation allows farmers to coat the information gathered from soil and residual nitrogen analysis, and information on prior crops and soil resistivity. Geolocation is done in two ways:
- The fields are depicted using the GPS receiver in the vehicle as the farmer moves the tractor around the field.
- This field is depicted on a base map that comes from aerial or satellite imagery. The base image must have an appropriate level of resolution and geometric quality to ensure accurate geolocation.
Variables
Intra and inter-field variability can be generated from a number of factors. These include climatic conditions (hail, drought, rain, etc.), soils (texture, depth, nitrogen level), cropping (weedless agriculture), weeds and disease. Permanent indicators - especially land indicators - give farmers information about major environmental constants. The point indicator allows them to track the status of the plant, ie to see if the disease develops, if the plant is suffering from water stress, nitrogen pressure, or lodging, whether it is damaged by ice and so on. This information may come from weather stations and other sensors (ground electrical resistivity, detection with the naked eye, satellite imagery, etc.). Soil resistivity measurements combined with soil analysis make it possible to measure moisture content. Soil resistivity is also a relatively simple and inexpensive measurement.
Strategy
Using land maps, farmers can pursue two strategies to match field input:
- Predictive approach: based on analysis of static indicators (soil, resistivity, field history, etc.) during the plant 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: measurement parameters such as temperature (air/ground), humidity (air/ground/leaf), wind or trunk diameter is possible thanks to Wireless Sensor Networks
- proxy-detection: the in-vehicle sensor measures leaf status; this requires farmers to get around the whole field.
- remote sensing of air or satellites: multispectral images obtained and processed to obtain maps of plant biophysical parameters, including disease indicators. Air instruments can measure the number of plant cover and distinguish between crops and weeds.
Decisions can be based on decision support models (plant simulation models and recommendation models), but in the final analysis it is up to the farmer to decide on business value and impact on the environment.
It is important to realize why PA technology is or is not adopted, "for the adoption of PA technology to occur farmers should view technology as useful and easy to use.This may not be enough to have positive external data about the economic benefits of PA technology as a farmer's perception should reflect consideration this economy. "
Implementing practice
New information and communication technologies (NICT) make field-level crop management more operational and more accessible to farmers. Crop management decision application calls for agricultural equipment that support variable-rate technology (VRT), eg various seed densities along with application-rate variables (VRA) of nitrogen and phytosanitary products.
Precision farming using technology in agricultural equipment (eg tractors, sprayers, harvesters, etc.):
- positioning system (eg a GPS receiver that uses satellite signals to precisely locate on the globe);
- geographic information system (GIS), that is, software that allows all available data;
- variable-rate farm equipment (seeder, spreader).
Worldwide use
The concept of precision agriculture first appeared in the United States in the early 1980s. In 1985, researchers at the University of Minnesota varied lime inputs in crop fields. At this point the practice of grid sampling (applying a fixed grid of one sample per hectare). Toward the end of the 1980s, this technique was used to obtain the first input map recommendations for fertilizers and pH correction. The use of sensor results developed from the new technology, combined with the arrival of a GPS receiver, has gained ground ever since. Currently, the system covers several million hectares.
In the US Midwest (USA), it is not related to sustainable agriculture but with major farmers trying to maximize profits by spending money only in areas that require fertilizer. This practice allows farmers to vary the fertilizer rate in the field according to the needs determined by GPS guided Grid or Zone Sampling. Fertilizers that will be dispersed in areas that do not need them can be placed in areas that do, thus optimizing its use.
Around the world, precision farming is growing at varying speeds. The precursor countries are the United States, Canada and Australia. In Europe, Britain was the first to go down this road, followed by France, where it first appeared in 1997-1998. In Latin America, the leading country is Argentina, where it was introduced in the mid-1990s with the support of the National Agricultural Technology Institute. Brazil established a state-owned company, Embrapa, to research and develop sustainable agriculture. The development of GPS and variable-level dissemination techniques help to anchor precision agricultural management practices. Currently, less than 10% of French farmers are equipped with a variable rate system. Wider GPS absorption, but this does not stop them from using precision farming services, which provide field-level recommendation maps.
One third of the global population is still dependent on agriculture to earn a living. Although more advanced precision farming technologies require large up-front investments, farmers in developing countries benefit from cellular technology. This service helps farmers with mobile payments and receipts to improve efficiency. For example, 30,000 farmers in Tanzania use cell phones for contracts, payments, loans, and business organizations.
Economic and environmental impact
Precise farming, as the name suggests, implies applying the right amount of precise and appropriate inputs such as water, fertilizers, pesticides, etc. At the right time for the plant to increase its productivity and maximize its yield. Practical agricultural management practices can significantly reduce the amount of nutrients and other plant inputs used while increasing yields. Farmers thus get a return on their investment by saving water, pesticides, and fertilizer costs. The second benefit, the larger scale of the targeting input - in terms of spatial, temporal and quantitative - concerns environmental impact. Applying the right amount of input in the right place and at the right time will benefit the harvest, soil and ground water, and thus the entire cycle of the plant. As a result, precision farming has become a cornerstone of sustainable agriculture, hence respecting crops, soil and farmers. Sustainable agriculture seeks to ensure a sustainable supply of food within the ecological, economic and social boundaries necessary to sustain production over the long term. Therefore, precision farming seeks to use high-tech systems to achieve this goal.
A recent article tries to show that precision farming can help farmers in developing countries like India.
New technology
Precision farming is a breakthrough digital agricultural technology application. More than $ 4.6 billion has been invested in agricultural technology companies - sometimes called agtech.
Robot
Self-steering tractors have been around for some time now, because John Deere's equipment works like a plane on autopilot. Tractors do most of the work, with farmers entering for emergencies. The technology advances into a GPS-driverless engine for spreading fertilizer or plowing land. Other innovations include solar-powered engines that identify weeds and precisely kill them with doses of herbicides or lasers. Agricultural robots, also known as AgBots, already exist, but sophisticated harvesting robots are being developed to identify the ripe fruit, adjust to their shape and size, and carefully pick it from the branch.
Drone and satellite imagery
Advances in drone and satellite technology benefit precision farming because drones take high-quality images, while satellite captures larger images. Light plane pilots can combine aerial photographs with data from satellite recordings to predict future results based on current field biomass levels. Combined images can create contour maps for tracking where the water flows, determining variable rate seeding, and making more or less productive area result maps.
Internet stuff
Internet stuff is a network of physical objects equipped with electronics that enable data collection and aggregation. IoT comes into play with the development of sensors and agricultural management software. For example, farmers can measure nitrogen, phosphorus, and potassium spectroscopy in liquid manure, which is notoriously inconsistent. They can then scan the ground to see where the cow is already urinating and provide fertilizer only to where it needs it. This cuts the use of fertilizer by up to 30%. The humidity sensors on the ground determine the best time for long-haul water plants. The irrigation system can be programmed to replace the sides of which tree trunks they water based on crop needs and rainfall.
Innovation is not just limited to plants - they can be used for animal welfare. Livestock can be equipped with internal sensors to track gastric acidity and digestive problems. External sensors track movement patterns to determine the health and fitness of cows, feel the physical injury, and identify the optimal time to breed. All of these data from sensors can be collected and analyzed to detect trends and patterns.
As another example, monitoring technology can be used to make bees more efficient. Honeybees have significant economic value and provide essential services for agriculture by fertilizing various crops. Monitoring the health of honey bee colonies through wireless temperatures, humidity and CO2 sensors helps increase bee productivity, and reads early warnings in data that may threaten the survival of the entire hive.
Conference
- InfoAg Conference
- European Conference on Precision Agriculture (ECPA) (biennial)
- International Conference on Precision Agriculture (ICPA) (biennial)
See also
- Drone farm
- Geostatistics
- Integrated farming
- Integrated pest management
- Landsat Program
- Nutritional budgeting
- Nutritional management
- Phytobiome
- Beekeeping
- Precious cattle farming
- Precise vitality
- Satellite crop monitoring
- SPOT (satellite)
Note
External links
Media linked to Precision farming on Wikimedia Commons
- Precision farming, IBM
Source of the article : Wikipedia
0 Comments