Farmers make about fifty key decisions every cropping season. These choices are vital to the efficiency of the farm, and one poor decision can cost farmers as much as $50 per acre.(1) Precision farming assists the decision-making process by gathering and analyzing crop data. This data informs decisions regarding what type of seeds to plant and where fertilizer or crop protection products might need to be dispensed. This saves the farmer labour and supply costs, decreases environmental impacts, and increases yields.
Inputs—“resources that are used in farm production, such as chemicals, equipment, feed, seed, and energy.”(2)
The movement towards precision farming began in the 1980s with the introduction of Global Positioning System (GPS) technologies to the market.(3) The first satellite launched into space for agricultural purposes was the Landsat in 1972, but its poor quality and infrequent photographs did little for the industry. It wasn’t until 1999 that the Moderate Resolution Imaging Spectroradiometer (MODIS) was launched, providing daily updates to farmers with better quality images.(4)
Handheld devices also took off in the 1990s, sparking advancements. These devices allowed farmers to map boundaries, pinpoint soil sample locations, and monitor their crops. To assist with the collecting and processing of data, new Internet of Things (IoT) devices, such as sensors, drones, and smart phones with the ability to communicate and share information through the internet, were later invented.(4) When these data management technologies were paired with precision agriculture, smart farming was born.(5)
When further applied to robotics, variable rate technology (VRT) became possible. VRT is an example of site-specific management, which measures differences within each field and then pairs the recorded information with technology to dispense a targeted and controlled amount of inputs. VRT can adjust the amount of inputs it spreads as it goes without having to pass over a field more than once. Currently, 15 per cent of North American farms use VRT, but this number is expected to drastically increase over the next five years.(6) This technology is most often used in fertilizer application. With the cost of fertilizer ranging between 35 and 50 per cent of variable input costs,(7) limiting its use to only what is necessary can make the application more cost efficient for farmers, and prevent excess run-off of inputs into the surrounding environment.
Did You Know?
In 2013, farmers produced 262% more food with 2% fewer inputs (such as seeds, labour, and fertilizers) than they did in 1950.(8)
There are two different approaches to VRT: map-based and real-time (also known as sensor).(9) Map-based VRT uses previously collected data about the terrain and crop to create a multi-layered map called a prescription map. Yield-monitor and soil-sensor data, along with remote images from satellites or drones are input into a computer, where global information system (GIS) software is used to turn the data into a map. These maps show the current state of soil and plant health, alerting farmers to what sections of a crop require attention and treatment. If it is early in the season, the map can help determine which crops should be planted where.(10) The GPS in the farm machinery then interprets the maps and a controller is used to adjust the amount of input spread on the field.(9)
Real-time VRT (or sensor VRT) collects data as it goes and then immediately dispenses a solution based on its readings. Real-time VRT requires sensors to be incorporated into farm equipment like sprayers and seeders. As the machines move over the field, sensors detect the presence of weeds, pests, soil degradation, or drought, so the equipment and the farmer can make an immediate decision on what crop protection products or soil nutrients are needed. Alternatively, lasers can be used to zap weeds, replacing chemical inputs in both organic and conventional farming.
Sensors also assist the food supply chain in other settings, such as greenhouses and storage facilities like silos, grain bins, and refrigerators. The sensors monitor light, temperature, and humidity. Some sensors act as a switch, triggering when a certain threshold is breached, while others are more complex and can show continuous live readings. Should levels deviate from normal settings, alerts are provided with real-time information on the state of the commodities, allowing for quick action to solve a problem. This promotes crop health and produces higher yields in greenhouses while also preventing profit loss at the hands of spoilage when stored commodities like grain, produce, and meat aren’t kept at correct temperatures.
Commodity—“staple crops and animals produced or raised on farms or plantations. Most agricultural commodities such as grains, livestock, and dairy provide a source of food for people and animals across the globe.”(11)
Temperature sensors even have a place in tractors and other farming equipment. Some sensors detect overheating, while other sensors known as accelerometers catch changes in movement or vibrations, alerting the farmer to potential issues early.(12) This allows them to tune up equipment before it breaks down.
In the case of livestock farming, GPS sensors can track animals through special ID tags, keeping tabs on the movement of herds. With one on every animal, more advanced settings can even monitor health through the use of electronic collars.(13)
The future of precision farming will see a greater incorporation of autonomous robotics and artificial intelligence. AIs will become particularly useful in weather forecasting. Based on an intake of data, the algorithm can predict more accurately what weather farmers can expect. This includes temperature, precipitation, wind speed, and solar radiation.(14)
These predictions aid precision farming by allowing farmers to determine when to irrigate their crops and when they can count on the weather to keep them rain fed. This prevents unnecessary use of water resources, creating a healthier crop and a more sustainable farm. Weather information also assists farmers in determining the right time to harvest a crop before the first frost falls.
Precision farming is a growing movement, saving farmers money, protecting the environment, and helping produce enough food to feed a growing population. Soybean growers reported saving 15 per cent on input costs such as seed, fertilizer, and crop protection products through the use of precision agricultural technologies.(15) By 2025 the precision agriculture market is projected to reach $43.4 billion.(6)
For more information on agriculture technology explore our Nourishing Minds publications here.
1 Farmers Edge—How Big Data Can Mean Better Profit-Focused Decisions, 2016
2 Teach Me Finance—Farm Inputs
3 Global Market Insights—Industry Trends, 2019
4 MIT Technology Review—The Food Issue, 2021
6 AFN—What is Precision Agriculture?, 2017
7 Farmers Edge—Variable Rate: Why It’s Important Now, More Than Ever, 2020
8 Fact Retriever—67 Interesting Farming Facts, 2019
9 Sugar Research Australia—Variable-Rate Technology, 2014
10 Geospatial Word—How GIS is Enabling the Agricultural Sector, 2018
11 Commodity.com—Agricultural Commodities: Their Importance On The Global Market, 2020
12 Arrow—Agriculture Sensors: Top 5 Sensors Used in Agriculture, 2020
14 Customer Think—The Role of Artificial intelligence in Agriculture Sector, 2019
15 Precision Ag—Precision Agriculture: Higher Profit, Lower Cost, 2012