How did precision ag start?
How Did Precision Ag Start? It began with a seed. Some thousands of years ago, the first seed was intentionally planted. And from it came what we now call farming. Ancient civilizations used farming to feed, clothe, and sustain massive kingdoms – much like we do today.
What is pre-Cision agriculture?
Precision agriculture is usually done as a four-stage process to observe spatial variability: Precision agriculture uses many tools but here are some of the basics: tractors, combines, sprayers, planters, diggers, which are all considered auto-guidance systems.
What happened to pre-precision farming?
Precision farming wasn’t overly utilized for the first few decades of its existence. In the early days, farmers were either unconvinced of the benefits of PA or lacked the funds to install the system. Various renovations and changes were made to precision agriculture equipment to ensure ease of use, financial profit, and long-term applications.
Are small farms adopting precision agriculture in the US?
In the U.S., larger farms are increasing their use of precision agriculture and overcoming technology barriers to implement practices. But very few small farms in the U.S., which make up greater than 85 percent of U.S. farm totals, have adopted precision agriculture. Our work is specifically focused on small farmers and tractor guidance systems.
When was precision agriculture invented?
1980sWhat Year Did Precision Agriculture Begin? Precision ag was initially theorized in the 1980s by Dr. Pierre Robert, the father of modern precision farming. He came up with the concept while in college and spent many years studying and pioneering precision farming principles.
When did Smart Farming begin?
1 Introduction. Climate Smart Agriculture (CSA ) is an approach to guide the management of agriculture in the era of climate change . The concept was first launched in 2009, and since then has been reshaped through inputs and interactions of multiple stakeholders involved in developing and implementing the concept.
When was GPS first used in tractors?
1996In 1996 John Deere’s first production GPS receiver, nicknamed “green eggs and ham,” brought the possibility of satellite control to the tractor cab. In 1996 John Deere’s first production GPS receiver, nicknamed “green eggs and ham,” brought satellite control to the tractor cab.
How old is modern day precision agriculture?
The concept of precision farming can be traced back to America in the 1980s but took more than 10 years for other well-developed nations with a strong agricultural presence, like the UK, France and other major European countries, to latch on to its potential.
Who created precision agriculture?
Pierre RobertPierre Robert is often regarded as the father of precision farming because of his active promotion of the idea and organization of the first workshop, “Soil Specific Crop Management,” during the early 1990s.
When did farmers start using satellites?
And by the late 1900s, farmers had started using satellite imagery in the planning of their agricultural activities. The so-called precision farming technologies were designed to facilitate and optimize the management of different processes.
When was the first autonomous tractor made?
1940driverless tractor appears as early as 1940, but has really come to fruition in the last few years. The tractors use GPS and other wireless technologies to farm land without the need of a driver.
Are John Deere’s reliable?
Are John Deere tractors reliable? According to CarLogos.com, John Deere tractors are among the best and most reliable. In fact, some say these tractors are the most reliable tractors of all. But no matter how reliable a brand becomes in terms of its reputation among consumers, problems still arise.
What GPS does John Deere use?
StarFireStarFire is a wide-area differential GPS developed by John Deere’s NavCom and precision farming groups.
Which is first stage of implementing precision farming?
i) Assessing variability Assessing variability is the critical first step in precision farming. Since it is clear that one cannot manage what one does not know. Factors and the processes that regulate or control the crop performance in terms of yield vary in space and time.
How has precision agriculture changed farming?
By leveraging precision agriculture technologies, farmers have accomplished the following: 4% increase in crop production. 7% reduction in fertilizer use. 9% reduction in herbicide use.
What is the main purpose of precision agriculture?
Precision agriculture (PA) is an approach to farm management that uses information technology (IT) to ensure that crops and soil receive exactly what they need for optimum health and productivity. The goal of PA is to ensure profitability, sustainability and protection of the environment.
Who started climate smart agriculture?
CSA was developed by FAO as a unified approach to address the challenges of climate change. Ongoing FAO projects support work on CSA, for example, FAO’s Economics and Policy Innovations for Climate-Smart Agriculture (EPIC) programme and the Mitigation of Climate Change in Agriculture (MICCA) programme.
What are smart farms?
Smart Farms will focus on improving land management practices and biodiversity. It will also support agricultural systems to adapt to significant changes in climate, weather and markets.
Why do we need smart farming?
Benefits of smart farming Increasing control over production leads to better cost management and waste reduction. The ability to trace anomalies in crop growth or livestock health, for instance, helps eliminate the risk of losing yields. Additionally, automation boosts efficiency.
What is Gcsayn?
GCSAYN – Climate Smart Agriculture Youth Network Global.
Which country was the first to use precision agriculture?
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.
How has precision agriculture been enabled?
The practice of precision agriculture has been enabled by the advent of GPS and GNSS. The farmer’s and/or researcher’s ability to locate their precise position in a field allows for the creation of maps of the spatial variability of as many variables as can be measured (e.g. crop yield, terrain features/topography, organic matter content, moisture levels, nitrogen levels, pH, EC, Mg, K, and others). Similar data is collected by sensor arrays mounted on GPS-equipped combine harvesters. These arrays consist of real-time sensors that measure everything from chlorophyll levels to plant water status, along with multispectral imagery. This data is used in conjunction with satellite imagery by variable rate technology (VRT) including seeders, sprayers, etc. to optimally distribute resources. However, recent technological advances have enabled the use of real-time sensors directly in soil, which can wirelessly transmit data without the need of human presence.
How do drones help in agriculture?
These agricultural drones can be equipped with multispectral or RGB cameras to capture many images of a field that can be stitched together using photogrammetric methods to create orthophotos. These multispectral images contain multiple values per pixel in addition to the traditional red, green blue values such as near infrared and red-edge spectrum values used to process and analyze vegetative indexes such as NDVI maps. These drones are capable of capturing imagery and providing additional geographical references such as elevation, which allows software to perform map algebra functions to build precise topography maps. These topographic maps can be used to correlate crop health with topography, the results of which can be used to optimize crop inputs such as water, fertilizer or chemicals such as herbicides and growth regulators through variable rate applications.
How does precision agriculture improve the economy?
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.
How does precision agriculture help the environment?
Precision agriculture reduces the pressure by the 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.
What are the tools used in precision agriculture?
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 ag what it is.
Why is precision agriculture important?
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. Consequently, precision agriculture has become a cornerstone of sustainable agriculture, since it respects crops, soils and farmers.
What were the elements of precision agriculture?
Whether offered by small or large companies, these elements consisted of boundary making, recordkeeping, field notes, crop and pest scouting, field sampling in coordination with soil labs, variable-rate applications and other software tailored to crop-specific production practices. Nearly all companies staked out well-defined market geographies with little overlap. Some companies targeted growers while others worked through retailers, distributors, consultants and other entities who engaged growers.
What was the decade of pioneers?
The 1990s was the decade of pioneers. Small start-ups were introducing more accurate GPS units, yield monitors and software programs that assisted growers in the collection of field data and the interpretation of that data for production decisions.
What was the use of GPS in the 1990s?
The 1990s was the decade of pioneers. Small start-ups were introducing more accurate GPS units, yield monitors and software programs that assisted growers in the collection of field data and the interpretation of that data for production decisions. Most software was distributed on floppy disks but a few companies were taking advantage of the Internet with Web-based programs. Larger equipment companies were incorporating GPS units into their hardware so that the geographic positioning of material applications or harvested biomass could be tracked across a field. The 1990s saw the widespread use of laptop computers and handheld devices in the form of personal digital assistants (PDAs). Laptop computers and PDAs gave individuals mobility in the field. Software followed these mobile devices allowing participants in precision agriculture to trace a boundary, record a soil sample location and make crop and pest observations.
What was the first precision agriculture system?
Rockwell International Corp. , better known as a defense contractor, developed one of the first precision-agriculture applications. The Global Positioning System that precision agriculture relied on was primarily a military constellation, and Rockwell used its knowledge of military satellites to design its Vision System. Introduced in 1995, the system created detailed field maps. According to a report in the Los Angeles Times, the system’s computer attached to a combine and recorded the volume of crops harvested and paired those numbers with location data. The resulting map revealed which plots of land were more productive than others. Farmers could follow up with field tests to determine soil composition and apply targeted levels of fertilizer and insecticide the following planting season.
Where was Precision Farming located?
Fast forward to 1994, and John Deere’s Precision Farming group, in Moline, Illinois, was starting to explore a new concept in farming known as precision agriculture. Still in its infancy, precision agriculture had attracted the attention of a number of technology companies.
How much overlap does a farmer have when plowing a field without GPS?
When plowing a field without GPS, a farmer typically had almost one meter of overlap between rows. Reducing that overlap would mean spending significantly less time in the field and also using less fertilizer. Deere engineers partnered with engineers at Stanford University to develop an autonomous tractor controlled by GPS. Despite some successful demonstrations under idealized conditions, it was clear that they needed a GPS system that was more accurate and easier to use.
How much of the crop is self guided?
Self-guided systems now farm approximately 60 to 70 percent of the crop acreage in North America, 30 to 50 percent in Europe, and more than 90 percent in Australia.
When did John Deere start making GPS receivers?
Field Work: John Deere’s “green eggs and ham” GPS receiver, which went into production in 1997 as the StarFire, sits atop a tractor’s cab. Photo: Deere & Co.
Where did John Deere move from?
In the early 19th century, a blacksmith named John Deere moved from Vermont to Illinois, where he noticed that the farmers were having trouble. The sticky prairie soil accumulated on their traditional iron plows, forcing them to stop frequently to clean the blades.
What was the name of the plow that broke the plains?
Deere had an idea, and in 1837 he introduced his “self-scouring” steel plow. The blade cut through the tough, root-filled earth, and its curved shape allowed the soil to turn over. Deere’s invention became known as “the plow that broke the plains” and helped transform the Midwest into fertile farmland. His eponymous company became the largest plow manufacturer in the world.
What is the history of precision agriculture?
History of Precision Agriculture. First, a little bit of past history on adoption of technology within agriculture. It is interesting to note that major changes in agricultural technology have often been treated with derision and controversy. The change from horses to tractors was difficult for many people. Milk from a dairy farm was stored and …
When was GIS used?
In the 1960s and 1970s, GIS was used by research institutions, though it was still impractical for most commercial or educational uses. GIS provides the analysis tools needed for precision farming, but few people considered that as a possibility at the time.
Why was milk moved from single cross corn seed to hybrid seed controversial?
Moving from single cross corn seed to hybrid seed was controversial as some people argued that we were playing God with plants.
What is precision farming?
Precision farming allows a farmer to gather and see information about in real time. In the late 1990s the advent of GPS-based location-tracking technology and computer analysis launched an agricultural revolution. U.S. farmers began using the new technology to “see” bigger variations within their fields and animals than they had ever imagined.
Why did farmers use information?
U.S. farmers began using the new technology to “see” bigger variations within their fields and animals than they had ever imagined. Information became a new crop of the 21 st century, making farmers more efficient and sustainable but increasingly technologically dependent.
What was John Deere’s first GPS receiver?
John Deere’s first production GPS receiver, nicknamed “green eggs and ham,” brought satellite control to the tractor cab. Farmers eventually came to use GPS to steer their equipment, avoid spraying the same spot twice, and discover exactly which areas of a field produced the most.
What equipment does a farmer use to map their fields?
GPS receivers have become common on tractors, sprayers, combines, and farm equipment of all types. Farmers use satellite technology to guide their tractors, map their fields, control their planters and sprayers, and monitor their animals.
When did John Deere start using GPS?
should invest in GPS-based precision agriculture research. Company executives agreed, hoping to encourage farmers to buy new, more-efficient equipment. In 1996 , John Deere launched its GreenStar Precision Farming System. Their brochure predicted, “ Information is your new crop!”
Who developed the GPS system?
Image courtesy of the National Air and Space Museum. The satellite-based GPS system was first developed by the U.S. Departments of Defense in the 1970s. In the 1990s agricultural engineers began combining on-the-go crop yield readings with GPS tracking to create crop yield maps.
Who invented the yield monitor?
Al Myers invented an on-the-go crop yield monitor, a major step in making precision farming possible. Spot measuring the harvest gave farmers new information about the strongest and weakest portions of their fields. By linking the yield monitor data to GPS-plotted locations, farmers began creating detailed yield maps.
How is precision agriculture used?
Precision agriculture is a technology and information-based system used to manage farm inputs and to identify, analyze, and manage spatial and temporal variability in all aspects of agricultural production system within fields to maximize sustainability, profitability, and environmental safety (McBratney et al., 2005 ). N nutrition can be managed through precision farming methods using modern technological approaches and sensors. Local or remote N sensors could be helpful in sophisticated management practices to assess plant needs for supplemental N ( Schmidt et al., 2002 ). Precision agriculture that allows effective timing and precise application of N has the potential to save N and improves efficiency. Availability of several soil-crop simulation models paved the way to effective N management and assessment of NUE and N loss. These models integrate the effect of soil, weather, cultivar, pest, and other management practices on the growth and yield of crop. Site-specific nutrient recommendations are also made through the use of geographic information system (GIS) and global positioning system (GPS). N recommendation that takes into consideration of soil nitrate or any other N sources such as N credit by previous crop reduces the amount of needed N and improves efficiency. Other agronomic management practices that increase the yield and total N uptake can contribute to higher NUE of either indigenous or applied N sources as prescribed by simulation models. These management practices include insect and weed control, time of planting, planting density, supply of nutrients other than N, and selecting adapted cultivar or hybrid suited for the region and better N uptake.
What are the most rapidly adopted agricultural technologies?
Farmers, agricultural companies, and research institutions, especially in developed countries, are moving toward sustainable use of the Earth’s resources, conservation of water, and reducing, if not eliminating, soil erosion while continuing to increase production. Genetically modified crops , the most rapidly adopted agricultural technology ever developed (see Chapter 8 ), are the latest contribution of chemistry to the continuing transformation of agriculture that enables further progress toward, but alone cannot achieve, the ultimate goal of feeding all.
How can PLF technology be used in dairy cattle?
PLF technologies that have been developed for intensively-managed dairy cattle could, with some adaptation, be applied to intensify various aspects of sheep production, particularly for dairy sheep. Indeed, dairy sheep already benefit from EID-facilitated milk metering, individual feeding and automated sort gates. Oestrus detection systems based on behaviour monitoring (as discussed earlier) could facilitate artificial insemination to improve sheep genetics, and robotic milking systems could be adapted for use with dairy sheep. Neck and/or ear mounted accelerometers are also able to detect rumination and eating behaviour in cattle, and these should in principle work with sheep. Note that eating time is not very well correlated with food intake as animals spend variable amounts of time searching through mixed feeds as they select specific dietary components. However, time spent ruminating is closely linked with fibre intake, so can be used to help estimate intake. As well as helping to optimise feeding, these data can also help to detect the changes in behaviour such as a reduction in food intake associated with the early stages of many diseases. Leg-mounted accelerometers can detect changes in cow activity associated with the early onset of lameness in dairy cattle ( Thorup et al., 2015) and could be adapted to detect foot health problems in sheep. Physiological monitoring (e.g. boli to detect rumen pH) can also be used to help and optimise the diet and detect rumen disorders. However, PLF technologies could also be applied to more extensive sheep systems, not to make them more intensive but to make them more efficient, and these possibilities are covered in the remainder of this section.
What is PA in agriculture?
PA is an information and technology-based agricultural management system (e.g., using remote sensing, geographic information systems, global positioning systems, and robotics) to identify, analyze, and manage soil spatial and temporal variability within fields for optimum profitability, sustainability, and protection of the environment ( Bongiovanni and Lowenberg-Deboer, 2004; NRC, 1997; Gebbers and Adamchuk, 2010; Schrijver, 2016 ). PA is believed to be able to reduce the amount of inputs required, and better protect crops and soil.
What is the application cycle for spatial management?
The application cycle for PA is observation, evaluation, interpretation, targeted management, and observation.
Why are demonstration farms important?
Some works and reports ( Erickson and Widmar, 2015) have highlighted the essential role of demonstration ‘digital’ farms in promoting the appropriate adoption of precision farming by farmers . The role of these demonstration ‘digital’ farms is also essential to support farmers in making the appropriate technical choices and investments on their own farms. However, the establishment of such digital farms is not easy. Indeed, to maintain the trust of farmers, it cannot be a purely commercial showroom run only by a few companies. Farmers must also have a clear understanding of the specific contexts in which the demonstration farm operates and be able to assess the constraints they themselves face on their own farms (production profitability, interoperability with existing digital tools and services, employee skills and support, etc.) and be able to identify new commercialized solutions that are of potential interest. Meeting all these conditions is not easy and this is certainly why, to our knowledge, there are few examples of digital demonstration farms in the world.
How is remote sensing used in agriculture?
In agriculture, remote sensing has been in use since long for estimating land cover, land use, and crop biomass, and it has now been utilized to estimate the spatial crop N status in season ( Henebry et al., 2005; Osborne et al., 2002 ). For adjustment of N supply to meet crop requirement, use of proximal plant canopy sensors could also be a potential option. Schepers et al. (1992) proposed a need-based sensing tool to adjust N input according to the demand of maize in field conditions and to reduce the environmental contamination from excess nitrate. For this purpose, SPAD chlorophyll meter values are used to estimate crop N status against a standard color and then adjusting N application accordingly. The major problem of this technique is the physical collection of readings from many leaves and standardization of N-sufficient plants from N-deficient plants. Studies have confirmed a positive linear relationship between SPAD chlorophyll meter reading and chlorophyll content ( Sharma and Bali, 2017; Ulrich, 1952 ). Under precision agriculture, soil testing approach prior to crop planting, in-season nutrient management based on sensors, and split application of N fertilizers could be opted for improving NUE. For this purpose, sensor technologies and algorithm development need further research attention to develop more stable and reliable models.
What is precision agriculture?
Precision agriculture can be defined as “the application of modern information technologies to provide, process and analyze multisource data of high spatial and temporal resolution for decision making and operations in the management of crop production ” (National Research Council, 1997).
How can precision irrigation be used?
New uses relating to precision irrigation could include applications for mobile devices operating in the cloud to spatially monitor soil moisture, crop growth, and irrigation in real-time via in-field sensor arrays. Other cloud uses include providing data to refine planting and harvest operations, by integrating GPS and GIS data or managing equipment performance (pressures, flow rates, abstractions) at district or catchment scales. RFID tags, which automatically download data, are also becoming more widespread in agriculture. For example, tagging systems have been developed to collect data on the moisture content of straw bales, weight, and in-field position (GPS); in the future, similar cheap, possibly biodegradable, microtags could be deployed across fields to measure seasonal changes in soil moisture, organic content, crop canopy development, and canopy stress, or for monitoring and optimizing energy needs across pressurized irrigation distribution networks ( Carrillo Cobo et al., 2011 ). However, data security issues relating to confidentiality, integrity, availability, and accountability still need to be resolved before cloud technology can be fully integrated into precision irrigation.
What is the purpose of satellites in agriculture?
Satellite- and UAV-based applications of remote sensing in precision agriculture generally use multispectral measurements to estimate high-spatial resolution information related to soil properties, plant health, and crop yields. Reflectance spectra from soils provide information related to a variety of soil properties including soil moisture and organic matter content ( Ben-Dor et al., 2008 ). Depending on the spectral resolution of the instrument, specific constituents including clay minerals, calcium carbonates, and iron oxides that affect soil fertility and moisture holding capacity can also be measured ( Thomasson et al., 2001; Rossel et al., 2006 ). Each of these soil constituents have specific spectral regions where reflectance (or absorption) is strongest ( Ben-Dor, 2002; Ben-Dor et al., 2008 ), and narrowband or hyperspectral imagery, in combination with techniques such as spectral unmixing algorithms ( Huete and Escadafal, 1991) or derivative spectra ( Demetriadesshah et al., 1990; Li et al., 1993) are often required to identify these soil constituents. A key challenge in exploiting this capability is that current space-based instruments have limited spectral bands and resolution relative to the narrow and hyperspectral imagery used in many of the studies described earlier.
What factors influence crop yield?
One factor believed to influence crop yield is soil compaction, since it has a direct impact on soil hydraulic conductivity. As mentioned previously, the cone penetrometer is the soil-strength measuring device that is being used increasingly to map soil compaction level. Since it is a highly variable point measurement, numerous cone index values are needed to obtain proper representation of a field. This limitation of the cone penetrometer has led to the development of alternative devices that can measure and map soil strength in a continuous manner. One such device consists of a texture–soil-compaction sensing system that consists of a simple tine that is instrumented with a load cell to measure soil-cutting force. It also incorporates a dielectric-based soil-moisture sensor, because soil-moisture content influences soil-cutting force significantly. The soil-cutting force, F, is a function of soil bulk density, ρ, texture, ξ, and moisture content, θ, when the device is operated at a constant speed and operating depth; i.e.:
What is agricultural remote sensing?
Agricultural remote sensing is a big data source that can be used to monitor soil properties and crop stress. Agricultural remote sensing big data technology has been, since recently, gradually merging into precision agricultural schemes so that these big data can be analyzed rapidly in time for decision support in fertilization, irrigation, and pest management for crop production. Agricultural remote sensing is one of the backbone technologies for precision agriculture since it will produce spatially-varied data for subsequent precision agricultural operations. Agricultural remote sensing big data, which are acquired from different sensors and at different intervals and scales, have all the characteristics of big data. The acquisition, processing, storage, analysis, and visualization of these big data are critical to the success of precision agriculture.
How is remote sensing used in agriculture?
Large-scale data could discover the general trends, whereas the local data provides specific features of the farm and fields with the weather information. As a part of remote-sensing data supply chain management, agricultural remote-sensing big data architectures need to be built with the state-of-the-art technology of data management, analytics, and visualization. Real-time big data analytical architecture for precision agriculture are being developed. With the development of neural networks in deep learning, agricultural remote-sensing will use deep learning algorithms in remote-sensing data processing and analysis to develop unique research and development for precision agriculture.
What is cloud computing in agriculture?
Put simply, cloud computing involves using networks of remote servers hosted on the internet to store, manage, and process data, rather than hosting information and data on local servers. They generally rely on wireless data transfer and mobile web applications, in combination with other tools and spatial technologies including GPS and GIS. Cloud technology is well established within data-intensive industries, but only recently emerging in agriculture where various applications are being marketed. For example, in the USA, cloud services provide on-farm support from agribusinesses and consultants, for agrochemical application management. Other precision-related tools are now emerging.
What is precision farming?
Precision farming is generally defined as doing the right practice at the right location and time at the right intensity. Since its inception in the early 1980s, precision farming has been adopted on millions of hectares of agricultural cropland around the world. The objective of this chapter is to review the history of precision farming and the factors that led to its widespread popularity. The specific focus is on the following aspects of precision farming: soil sampling, geostatistics and Geographic Information Systems (GIS), farming by soil, variable rate fertilizer, site-specific farming, manage-ment zones, Global Positioning System (GPS), yield mapping, variable rate herbicides, variable rate irrigation, remote sensing, automatic tractor navigation and robotics, proximal sensing of soils and crops, and profitability and adoption of precision farming. For each topic, reference to key groups of researchers and the breakthroughs that helped propel precision farming onward are identified. The chapter concludes with a vision for the future of precision farming.
How is precision farming influenced by technology?
The history of precision agriculture has shown that it is more strongly influenced by technological innovations rather than innovations in information analysis and decision support. For example, when first introduced, GPS and yield monitors were viewed as technological advances that could be added to existing farm equipment to add value. Later, agribusiness began embedding both GPS and yield monitors onto farm combines as part of the standard sales package. This combination of tech-nology is now widely adopted by farmers so that it is used by practitioners of precision farming as much as by practitioners of conventional farming. The addition of GPS to farm equipment enabled many other technological breakthroughs in precision farming, such as autosteer, and furthermore, machine location was essential for variable rate fertilizer application technology.
How does precision farming help the environment?
Precision farming allows for variation in the rate of applied fertilizer, manure, and pesticides to better match spatial patterns in soil fertility and pesticide adsorption, and to respond to changing temporal patterns in crop nutrient stress and infestations of weeds, insects, and disease. In addition, with autosteer technology, precision farming reduces overapplication of chemical inputs due to overlap between successive passes of chemical applicator machinery. All of these factors lead, con-ceptually, to improved environmental quality and sustainability (Larson et al. 1997; Bongiovanni and Lowenberg-DeBoer 2004).
What is site specific farming?
The philosophy of site-specific farming was distinct from farming by soil. Farming by soil pos-ited that fertilizer requirements varied across soil series but were homogeneous within a given soil series. Site-specific farming posited that variability within soil series boundaries was signifi-cant, and the only way to identify fertilizer requirements was by grid or transect soil sampling across soil series boundaries. Field investigations involving these two contrasting philosophies were partially motivated by the need to document the profitability of variable rate fertilizer appli-cations. To this end, Mulla and his colleagues from Cenex Land O’Lakes in Washington State established the first statistically rigorous field trials in 1987 comparing variable and uniform N and P fertilizer applications on commercial wheat farms (Mulla et al. 1992). Without GPS, they conducted long transect sampling at 15 m spacings across rolling landscapes, and used a manual controller to variably apply N and P according to a map developed by grouping and reclassifica-tion of soil fertility data from the transect sampling. While there were no statistically significant differences in crop yield between the uniformly and variably fertilized strips, the profitability of variable rate fertilizer was better than uniform management due to cost savings in fertilizer and improved protein content of wheat in the variably fertilized strips. Mulla introduced the concept of management zones into precision farming as a result of these and other early field trials on irrigated fields with variable rate fertilizer (Mulla 1991, 1993; Mulla et al. 1992). Management zones were relatively homogeneous regions within a larger field that differed from one another in fertilizer recommendations.
How is proximal sensing used in agriculture?
Proximal sensing has been widely used in precision farming to map spatial patterns in soil or crop properties. Early advances in proximal soil sensing were initially based on geophysical prospecting techniques that were used to discover mineral reserves buried deep in the earth (Parasnis 1973). Two categories of geophysical prospecting techniques have been adapted for proximal sensing of soil in precision farming: electrical resistivity/conductivity methods and electromagnetic induc-tion methods. Halvorson and Rhoades (1974) adapted electrical resistivity mapping methods to the problem of mapping soil salinity in agricultural fields based on the four-probe Wenner array devel-oped in the mining industry. Wenner array probes were simply metal spikes inserted in soil along a straight line at fixed spacing. A battery supplied current to the soil through two of the spikes, while the other two served as voltage probes. The depth of measurement could be controlled by varying the spacing between metal electrodes. Carter et al. (1993) built on the research by Halvorson and Rhoades (1974) to pioneer continuous mobile electrical conductivity measuring equipment for soil salinity mapping. The mobile apparatus consisted of a battery attached to four equally spaced chisel blades mounted on a tractor. This apparatus was the inspiration for the Veris electrical conductivity mapping system (Christy and Lund 1998) based on equally spaced electrode disks that is widely used in precision farming. Colburn (1991) patented a device for a resistivity-based sensor mounted behind a moving fertilizer spreader that was claimed to accurately vary fertilizer rate in response to differences in soil nitrate-N concentrations, soil cation exchange capacity, organic matter content, and soil moisture. This device, called Soil Doctor, was widely marketed for applications in precision farming, although many scientists were skeptical of its accuracy in the absence of rigorous scientific testing.
What is remote sensing in agriculture?
Remote sensing applications in precision agriculture are primarily based on reflectance of the sun’s visible and near-infrared light by soils or crops. Remote sensing does not require contact between the sensor and the soil or crop and is usually achieved using cameras mounted on satellites, air-planes, towers, or unmanned aerial vehicles. Proximal sensing, discussed in Section 1.13 below, differs from the traditional definition of remote sensing in that proximal sensing involves sensors placed on ground vehicles rather than aerial platforms.
What are some examples of precision agriculture?
Another example of a precision agriculture tool is variable rate technology , which allows crop producers to apply variable rates of fertilizer across a field. Similarly, yield monitoring systems record yield data (grain and grain moisture) on a combine during harvesting. Today’s yield monitoring systems provide operators with a user interface that includes a spatial map that displays the grain yield of the harvested portions of the field. Both these technologies provide farmers with additional farm-level information for managing risk and more precisely managing fertilizer, seed, and herbicide.
What is PO farming?
PO – Large farms tend to have larger fields with row crop agriculture. Small farms can vary from forages to orchards to specialty crops to row crops, so they may be extremely diverse. This diversity requires us to think about research and technology in a different way.
What is tractor guidance?
AA – Tractor guidance (also called autosteer) is a precision agriculture technology that uses GPS and can result in accuracy within one centimeter when planting, spraying herbicide, or applying fertilizer. This improved precision during field activities can result in fewer overlaps (areas in the field with double application) and gaps (or skipped areas in the field) and overall improved efficiencies (both economic and environmental).
How profitable is tractor guidance system?
AA – Tractor guidance systems can be profitable for small farms and improve efficiency gains by 20 percent. This technology can potentially improve environmental sustainability by reducing the over application of fertilizers, seed, and herbicide.
How does tractor guidance affect small farms?
Tractor guidance offers more spatially precise understanding of tractor operations, which lead to reduced operator fatigue, higher yield, and the ability to work longer workdays during inclement conditions. Altogether, these changes may significantly lessen a small farm’s fuel, labor, repair, and maintenance costs.
What is AA in agriculture?
AA – Precision agriculture is a general term to describe farming tools based on observing, measuring, and responding to within-field variability via crop management. It is made possible through the use of Global Positioning System (or GPS satellites) or Global Navigation Satellite System (GNSS), which enable farm managers to respond …
Do all agricultural sectors receive information on technology at the same rate?
Not all agricultural sectors receive information on technology at the same rate. There is a need for identifying potential adoption and appropriateness of technologies that can automate production while improving the economic and environmental impacts of production systems at all scales.
Precision agriculture (PA) is a farming management concept based on observing, measuring and responding to inter and intra-field variability in crops. The goal of precision agriculture research is to define a decision support system (DSS) for whole farm management with the goal of optimizing returns on inputs while preserving resources.
Precision agriculture is a key component of the third wave of modern agricultural revolutions. The first agricultural revolution was the increase of mechanized agriculture, from 1900 to 1930. Each farmer produced enough food to feed about 26 people during this time. The 1960s prompted the Green Revolution with new methods of genetic modification, which led to each farmer feeding about 156 people. It is expected that by 2050, the global population will reach about 9.6 billion, a…
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. The second wave aggregates the machine data for even more precise planting, topographical mapping, and soil data.
Precision agriculture aims to optimize field-level management with regard to:
Usage around the world
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. Farmers thus obtain a return on their investment by saving on water, pesticide, and fertilizer costs.
• InfoAg Conference
• European conference on Precision Agriculture (ECPA) (biennial)
• International Conference on Precision Agriculture (ICPA) (biennial)