March 23, 2021 at 6:42 pm | Updated March 23, 2021 at 6:42 pm | 8 min read
Producing food sustainably for an ever-increasing population is one of the greatest single challenges of our time. This challenge has been compounded in recent years by plateauing profits and production, as well as serious environmental concerns posed by traditional methodologies. Precision farming can improve both yield and profits by using fewer resources, while at the same time making agriculture more sustainable and less polluting. Any farmer can adopt this data and technology-based approach. Let’s dive into how it works –
What is Precision Farming?
In traditional industrial agriculture, growers apply the same rate of fertilizers, irrigation, or pest control at prescribed times and frequencies. These are general recommendations for a cultivar or a region.
However, every farmer knows there are differences within a field. Some parts give better yield, while the other patches give very little. This can be due to differences in soil, slope, and shade.
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Micro-differences in physical, chemical, and biological features of soil will affect fertility and nutrient availability. While slope can affect water retention in soil, biological stress can still vary. Weeds tend to occur in the same spot because they are spread by tubers or seeds. The same pattern can also be seen in soil diseases. Hence, the growing conditions for any crop will not be uniform across a growing area.
When farmers do not consider these inherent differences and provide nutrients and treatment uniformly, they are providing too many resources to the good patches and not enough resources to the poor patches. Moreover, by adding fertilizers and treatment chemicals at prescribed rates, they are overusing them and unnecessarily adding to the cost of their operations.
Precision farming optimizes output by targeting the fine spatial differences in a farm.
The idea that differentiates precision farming from traditional methods is Variable-Rate Application (VRA). Inputs are given in amounts needed, where needed, and when needed.
All stages of agriculture can be optimized through precision farming, which will increase yield while keeping costs low for the following areas at the same time:
- Soil sampling
- Pest, weed, and disease control
- Planning harvesting and logistics
- Post-season benchmarking
Precision Farm Management
To be able to apply the VRA method, growers need detailed and spatial data about their farms and different Variable-Rate Technology (VRT) at each stage. The following are important steps in precision farming:
- Data collection
- Analysis of data
- Decision making based on analyzed data
- Managing field operations based on the decisions
Data Collection with Variable-Rate Technology
It is necessary to collect data about the field conditions, crop growth, and yield in different parts of a farm. This can be collected at the field level or through remote sensing.
The following new precision farming technologies are useful at different scales and mostly provide data about spatial differences:
- Geospatial technologies—such as remote sensing, Global Positioning Systems (GPS), and satellite imagery—provide information on differences in soils or crop health and performance on regional scales and weather.
- Multispectral imagery captures images of land in visible, near-infrared, and red edge bands of light. When analyzed by vegetative indices it provides information of the inner physiology of a crop to spot problems before we can see them. These can be collected by satellites, airplanes, or robotic drones.
- Small instruments or sensors, can be used on the farm to give information about soil moisture and temperature, root response to supplements, ripeness/ maturity of fruits, etc. Many of them use geo-referencing and IoT. These instruments have accompanying software that is immediately capable of predictive analysis and can be calibrated for specific crops or varieties and regions.
Data collection is a continuous process as the crop is monitored throughout its life cycle, as shown in Figure 1.
Figure 1: “Information process flow of Precision Agriculture,” Abdullahi, 2017. (image credits: http://www.jmest.org/wp-content/uploads/JMESTN42352362.pdf)
Data Analytics in Precision Agriculture
Before farmers can take action, the collected data must be analyzed to determine field and crop conditions.
Remote sensed imagery is often analyzed by third-party software analytic firms to give actionable insights. Many of them combine field and weather data to make the insights more accurate. The result is a report with simple statistics and an analyzed map.
These analytics use artificial intelligence (AI) algorithms and machine learning to analyze the enormous quantities of data generated by imagery and IoT sensors. They use several vegetative indices and models to spot stress due to diseases, nutrient deficiency, etc. The fields are also analyzed for water content to identify flooding or drought.
Today, AI and machine learning applications are growing rapidly.
Many large organizations, universities, and governments are making their collected data freely available. The growth of Big Data, or Open Data as it is called, is making vital information open access. Universities are sharing publicly-funded agricultural research on data analytics and computation with the food and agriculture industry to speed up the development of analytics for the benefit of growers.
Smart Farming using Data-Driven Decisions
When growers get their reports, they can make data-driven management decisions. The reports subdivide a larger farm into smaller homogeneous zones based on variations in crop performance. These zones can be used to provide correct and optimum levels of inputs.
For example, using biomass analysis can check for emergence success. The software divides the field based on the percentage of emergence and uses color codes to demarcate the farm, so a grower can identify areas that need replanting and the extent of investment they have to make. By replanting only where necessary, they cut costs.
Similarly, when the analysis shows stress, the farmer knows which area to scout to identify the cause. Once that is done, they can prepare prescription maps and apply treatments where necessary using VRA.
This ensures that input use is optimized and costs are cut at each stage of the crop cycle.
Using New and Existing Machinery
In large fields, application of decisions will take place with the help of machinery or drones with GPS. Small farms can handle the application of treatments manually.
Agricultural machinery made for VRA application, like tractors, come equipped with satellite receivers to use prescription maps. For older machines, there are small devices that can be added retrospectively to access satellite signals to guide agricultural activities on the field, like plowing or application of treatments.
Applying Variable-Rate Technology
Precision farming involves using technology and data at one or more of the many stages of farming to benefit from levelling the variability in farms.
Fertilizer application – Some of the crucial steps in precision farming are determining the right amounts and timing for fertilizer application. This can improve crop yield and nutritional quality, reduce fertilizer use and cost, and result in less nutrient pollution.
- There are small and large devices for this purpose. Many tractors are fitted with devices that scan crop conditions in real time to regulate the amount of fertilizers added.
- Small devices such as the minirhizotrons, CI-600 In-Situ Root Imager, and CI-602 Narrow Gauge Root Imager can provide images of roots to see the response to fertilizers and other supplements provided so the application can be altered later.
Irrigation regimes can be adjusted to supply required amounts of water when necessary by using a wide range of tools, such as IoT soil probes, and minirhizotrons like CI-600 In-Situ Root Imager and CI-602 Narrow Gauge Root Imager.
Weed detection and chemical application can be regulated by devices attached to tractors. This step can reduce weedicides’ use by 80% by avoiding spraying on bare ground or neighbouring vegetation. This not only reduces the costs of weedicides but also maintains biodiversity by not killing non-target plants.
Micro-scale analysis for pest and disease control is also possible:
- There are devices, like the CI-710s SpectraVue Leaf Spectrometer, which use near-infrared (NIR) based technology to detect changes in above-ground plant parts due to diseases.
- Root diseases can be detected before symptoms manifest above-ground through handheld devices such as the CI-600 In-Situ Root Imager and CI-602 Narrow Gauge Root Imager.
Overall plant performance – You can monitor the overall crop health with NIR based technology, like the CI-710s SpectraVue Leaf Spectrometer and the CI-340 Handheld Photosynthesis System.
Harvesting – Unlike grains, deciding when to harvest fruits and vegetables can be challenging. Grains are harvested when dry and can be stored for months and years without being spoiled; however, fresh produce sometimes last only a few weeks, so fruits and vegetables must be plucked when they are ripe or mature enough to meet consumer taste preferences, but early enough to extend transport and storage time.
Affordable handheld devices, such as Felix’s F-750 Produce Quality Meter, use dry matter content, brix, titratable acidity, and internal color to decide harvesting time for a wide range of fruits and vegetables. The F-751 series is based on the F-750 and there are devices customized for Avocados, Mangoes, and Kiwis.
Post-harvest – During transport and storage, fresh produce needs to be monitored so that the rooms holding them have the optimum levels of ethylene, oxygen (O2), carbon dioxide (CO2), temperature, and humidity. Decision making requires precise data, which can be provided by the following cost-effective handheld tools produced by Felix Instruments:
Advantages of Precision Farming
Precision farming offers several advantages–economic, social, and environmental–over traditional methods:
- Increases ROI, by reducing inputs use and increasing yield amounts and quality.
- Reduces soil, water, and air pollution by decreasing the use of chemical fertilizers and pesticides.
- Builds up soil biodiversity and supports wildlife outside farms.
- Makes farming sustainable by reducing reliance on resources and water.
- Reduces carbon emissions from the agriculture sector.
Farm Size Doesn’t Matter
Precision farming is suitable for big farms, small family farms, and organizations working with many growers.
Not surprisingly, this method of farming is expected to increase by a CAGR of 12.6.0% from 2021 to reach 12.9 billion USD by 2026.
Small farms produce more than 80% of the world’s food, so it is important to use these smart farming practices at small scale as well. However, the tools that farmers use could be different depending on the size of the farm.
Compact handheld devices, smart sensors, mobile apps, and small drones can bring the benefits of precision farming even to small farmers. Often the benefits to small farmers can mean using just 20% of the fertilizers or pesticides, decreasing costs and improving profits significantly. In some cases, very little technology is needed.
Large farms use precision farming to help them scout and create field management zones for all or specific operations.
Organizations such as farmers’ cooperatives, input retailers, seed producers, food processors, and crop insurance companies who work on a massive, often multinational basis, are increasingly using precision farming. These sectors can benefit from the virtual field visibility and digital reports that precision farming provides. Due to the significant reduction in travel imposed by the COVID-19 pandemic, the virtual side of precision farming has been notably beneficial, and a continued trajectory of increased adoption rates is expected.
Level of Expertise Needed
Many of the tools are simple and easy to use, but some require a little expertise. They are essentials for crop consultants and agricultural centers; however, the network of support available for farmers who want to learn to use and implement these technologies themselves has grown immensely in recent years, making the process more effective than ever. The money and time invested in VRT tools has been shown to provide substantial returns in farms of all sizes, and consistent improvements are providing even greater returns with less input as time goes on.
Science Writer, CID Bio-Science
Ph.D. Ecology and Environmental Science, B.Sc Agriculture
Feature phopto courtesy of USDA.
Abdullahi, H.S. (2017). Advances of image processing in Precision Agriculture: Using deep learning convolution neural network for soil nutrient classification. http://www.jmest.org/wp-content/uploads/JMESTN42352362.pdf
Big Data. Retrieved from https://www.ifpri.org/topic/big-data
Businesswire (2021, February 16). Global precision farming Market (2021 To 2026) – Growth, Trends, COVID-19 impact, and forecasts – ResearchAndMarkets.com. Retrieved February 19, 2021, from https://www.businesswire.com/news/home/20210216005687/en/Global-Precision-Farming-Market-2021-to-2026—Growth-Trends-COVID-19-Impact-
DeJoia, A., and Duncan, M. (2015, February 27). What is “Precision Agriculture and why is it important”. Retrieved from https://soilsmatter.wordpress.com/2015/02/27/what-is-precision-agriculture-and-why-is-it-important/
European Global Navigation Satellite Systems Agency. (2017, October, 12). Precision farming becoming more and more important in modern agriculture. Retrieved from https://www.gsa.europa.eu/newsroom/news/precision-farming-becoming-more-and-more-important-modern-agriculture
Geospatial World. (2017, Nov 20). What is Precision Agriculture? What is the meaning of Precision Farming? Retrieved from https://www.youtube.com/watch?v=WhAfZhFxHTs
Shibusawa, S. (2002, August 01). Precision Farming Approaches to Small-Farm Agriculture.Food and Fertilizer Technology Center. Retrieved from http://www.fftc.agnet.org/library.php?func=view&id=20110726164350
The Open Ag Technology and Systems (OATS) Center. (n. d). Retrieved from https://oatscenter.org/
Van Vark, C. (2014, June 4). From agribusiness to subsistence: high-tech tools now available to all. Retrieved from https://www.theguardian.com/ global-development-professionals-network/2014/jun/04/subsistence-farming-precision-agriculture
Wigmore, I. Precision Agriculture. Retrieved from https://whatis.techtarget.com/definition/precision-agriculture-precision-farming
Yara International. (2013, Jan 11). Precision farming for sustainable agriculture. Retrieved byhttps://www.youtube.com/watch?v=nrixH9tFxoA
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