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Smart agriculture, also known as precision agriculture, allows farmers to maximize yields using minimal resources such as water, fertilizer, and seeds. By deploying sensors and mapping fields, farmers can begin to understand their crops at a micro scale, conserve resources, and reduce impacts on the environment. Smart agriculture has roots going back to the 1980s when Global Positioning System (GPS) capability became accessible for civilian use. Once farmers were able to accurately map their crop fields, they could monitor and apply fertilizer and weed treatments only to areas that required it. During the 1990s, early precision agriculture users adopted crop yield monitoring to generate fertilizer and pH correction recommendations. As more variables could be measured and entered into a crop model, more accurate recommendations for fertilizer application, watering, and even peak yield harvesting, could be made.
In this article, we will explore how these sensing technologies have been woven into modern large agribusiness and discuss how progression of the technology both to small farms at home as well as globally can increase our capacity to feed the world.
A number of sensing technologies are used in precision agriculture, providing data that helps farmers monitor and optimize crops, as well as adapt to changing environmental factors including:
Location Sensors use signals from GPS satellites to determine latitude, longitude, and altitude to within feet. Three satellites minimum are required to triangulate a position. Precise positioning is the cornerstone of precision agriculture. GPS integrated circuits like the NJRNJG1157PCD-TE1 are a good example of location sensors.
Optical Sensors use light to measure soil properties. The sensors measure different frequencies of light reflectance in near-infrared, mid-infrared, and polarized light spectrums. Sensors can be placed on vehicles or aerial platforms such as drones or even satellites. Soil reflectance and plant color data are just two variables from optical sensors that can be aggregated and processed. Optical sensors have been developed to determine clay, organic matter, and moisture content of the soil. Vishay, for example, offers hundreds of photodetectors and photodiodes, a basic building block for optical sensors (Figure 1).
Figure 1: Vishay Photo IC Sensor
Electrochemical Sensors provide key information required in precision agriculture: pH and soil nutrient levels. Sensor electrodes work by detecting specific ions in the soil. Currently, sensors mounted to specially designed “sleds” help gather, process, and map soil chemical data.
Mechanical Sensors measure soil compaction or “mechanical resistance.” The sensors use a probe that penetrates the soil and records resistive forces through use of load cells or strain gauges. A similar form of this technology is used on large tractors to predict pulling requirements for ground engaging equipment. Tensiometers, like Honeywell FSG15N1A, detect the force used by the roots in water absorption and are very useful for irrigation interventions (Figure 2).
Figure 2: Honeywell Force Sensor
Agricultural Weather Stations are self-contained units that are placed at various locations throughout growing fields. These stations have a combination of sensors appropriate for the local crops and climate. Information such as air temperature, soil temperature at a various depths, rainfall, leaf wetness, chlorophyll, wind speed, dew point temperature, wind direction, relative humidity, solar radiation, and atmospheric pressure are measured and recorded at predetermined intervals. This data is compiled and sent wirelessly to a central data logger at programmed intervals. Their portability and decreasing prices make weather stations attractive for farms of all sizes.
Sensing technologies provide actionable data to be processed and implemented as need be to optimize crop yield while minimizing environmental effects. Here are a few of the ways that precision farming takes advantage of this data:
Yield Monitoring systems are placed on crop harvesting vehicles such as combines and corn harvesters. They provide a crop weight yield by time, distance, or GPS location measured and recorded to within 30cm.
Yield Mapping uses spatial coordinate data from GPS sensors mounted on harvesting equipment. Yield monitoring data is combined with the coordinates to create yield maps.
Variable Rate Fertilizer application tools use yield maps and perhaps optical surveys of plant health determined by coloration to control granular, liquid, and gaseous fertilizer materials. Variable rate controllers can either be manually controlled or automatically controlled using an on-board computer guided by real GPS location.
Weed Mapping currently uses operator interpretation and input to generate maps by quickly marking the location with a GPS receiver and datalogger. The weed occurrences can then be overlapped with yield maps, fertilizer maps, and spray maps. As visual recognition systems improve, the manual entry will soon be replaced by automated, visual systems mounted to working equipment.
Variable Spraying controllers turn herbicide spray booms on and off, and customize the amount (and blend) of the spray applied. Once weed locations are identified and mapped, the volume and mix of the spray can be determined.
Topography and Boundaries can be recorded using high-precision GPS, which allows for a very precise topographic representation to be made of any field. These precision maps are useful when interpreting yield maps and weed maps. Field boundaries, existing roads, and wetlands can be accurately located to aid in farm planning.
Salinity Mapping is done with a salinity meter on a sled towed across fields affected by salinity. Salinity mapping interprets emergent issues as well as change in salinity over time.
Guidance Systems can accurately position a moving vehicle within 30cm or less using GPS. Guidance systems replace conventional equipment for spraying or seeding. Autonomous vehicles are currently under development and will likely be put into use in the very near future.
Large-scale farming gained an early foothold in the practice of precision farming. Expensive sensors, infrastructure, and processing equipment could only be realistically put to work by agribusinesses with sufficient capital available to invest. Those that invested in precision farming saw handsome paybacks in terms of crop yields.
In the United States, small farms—including organic and traditional—make up 91 percent of nearly 2 million farms. With a potential market of 1.8 million small farms in the United States alone, developers and designers have taken notice of the opportunities presented by integrating precision farming techniques on a smaller scale. Smartphone sensors and apps, as well as small-scale machinery, allow smaller farms to take advantage of precision agriculture technologies.Smartphone Tools
The smartphone alone has several tools that can be adapted to farming applications. For instance, crop and soil observations can be logged in the form of snapped pictures, pinpoint locations, soil colors, water, plant leaves, and light properties. Table 1 lists some in-phone tools that are useful for gathering data:
Table 1: Agricultural uses of existing smartphone tools.
Smart Farming Applications
Provides pictures of leaf health, lighting brightness, chlorophyll measurement, and ripeness level. Also used for measuring Leaf Area Index (LAI) and measuring soil organic and carbon makeup.
Provides location for crop mapping, disease/pest location alerts, solar radiation predictions, and fertilizing.
Helps with predictive maintenance of machinery.
Helps determine Leaf Angle Index. Also used as an equipment rollover alarm.
Detects equipment rollover.
Many smartphone applications have begun to incorporate Internet of Things (IoT) ideals, data aggregation, and speedy processing to bring up-to-date, actionable information to small farmers regarding seeding, weeding, fertilizing, and watering. These applications gather data from handheld sensors, remote sensors, and weather stations, creating in-depth analyses and valuable recommendations. Several applications have been developed specifically targeting the small-scale farmer:
Disease Detection and Diagnosis: Photos taken of suspect plants can be forwarded to experts for analysis.
Fertilizer Calculator: Soil sensors and leaf color can determine what nutrients are needed.
Soil Study: Capturing soil images, as well as pH and chemical data from sensors, allows farmers to monitor and adjust to changing soil conditions.
Water Study: Determining Leaf Area Index from photos and brightness logging can help farmers determine water needs.
Crop Harvest Readiness: Camera photos with UV and white lights accurately predict ripeness.
When specialized applications improve farm productivity by analyzing soil, crop, weed, and pest variables, as well as offer valuable feedback for agricultural decisions, the small farmer’s quality of life can noticeably improve.
Manufacturers are also looking at developing solutions specifically for small farms, such as the “Rowbot,” which can fertilize, mulch weeds, and sow seeds for cover crops. Much smaller and more nimble than traditional cultivating equipment, the Rowbot can fit between crop rows, does not compact soil, and can distribute micro-doses of fertilizer. Scaling up operations can be achieved by networking the machines into “flocks.”
In the developing world, roughly 500 million small farms produce more than 80 percent of the food consumed. Precision agriculture technology is becoming more widely accessible around the globe. New handheld devices can measure plant and soil health, giving farmers the information necessary to accurately calculate fertilizer requirements. Given that the United Nations projects worldwide demand for food will increase by 50 percent by 2050, precision agriculture technologies for farms of all sizes will be in demand.
Solving problems for farms both large and small and helping farmers meet ever-increasing food demands aren’t the only solutions smart, precision agriculture can provide. Smart farming offers a number of other benefits, such as:
Lowering fuel and energy consumption thus reducing carbon dioxide emissions
Reducing nitrous oxide released from soil by optimizing nitrogen fertilizer use
Reducing chemical use by pinpointing fertilizer and pest control needs
Eliminating nutrient depletion through monitoring and managing soil health
Controlling soil compaction by minimizing equipment traffic
Precision agriculture has grown to meet increasing worldwide demand for food using technologies that make it simpler and cheaper to collect and apply data, adapt to changing environmental conditions, and use resources most efficiently. Although large farms have been the first to adopt these technologies, smaller farms are now able to benefits as well, using tools built into smart phones, relevant applications, and smaller-sized machinery. What’s more, these technologies are contributing to solutions that extend beyond farms, including pollution, global warming, and conservation.
Future developments in precision agriculture will likely include increased autonomous farm vehicle use, as well as improved wireless data transmission and acquisition from smarter, smaller Unmanned Aerial and Unmanned Ground Vehicles (UAVs and UGVs, respectively). In addition to monitoring crop and soil conditions, these smaller vehicles can also monitor the status of farm equipment, allowing farmers to improve machine servicing and maintenance. In general, process improvements learned in the industrial manufacturing arena will continue to find their way into agriculture.
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