Precision Farming - Modern Agricultural Revolution

Precision Farming and the third modern agricultural revolution

The world is at the edge of the third modern farming revolution and precision farming is an important part of it. The first farming revolution that occurred from 1900 to the 1930s, mechanized agriculture leaving each farmer able to produce enough for 26 people. Long after that, it was the 1990s when the second revolution known as the Green revolution took place. Due to scientific progression genetically modified newer sets of crops that are pest resistant and need less water were introduced, leaving each farmer able to feed 155 people. The global population is expected to reach 9.6 billion by 2050 and food production must be double the current levels to feed every person. Advanced analytical capabilities and constantly improving IoT capabilities, like precision agriculture drones, will be key elements in the third revolution.

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What is Precision Farming?

Understanding the definition of precision farming in its true sense is crucial for farmers as well as their associated brands. Precision Farming is a farm management concept that revolves around the process of observing, measuring, and responding to various inter-and intra-field variability inputs for modern agriculture.

Popular definitions of Precision Agriculture (PA), Satellite Farming, or Site-Specific Crop Management (SSCM) describe the term as ‘a technology-enabled approach to farming management that observes, measures, and analyzes the needs of individual fields and crops’. According to McKinsey, the Precision farming invention is shaped by two trends: Big Data and Advanced Analytics Capabilities, and Robotics — aerial imagery, sensors, and sophisticated local weather forecasts. In simple words farming that collects and uses data from plots for managing and optimizing the production of crops is known as predictive farming.

Predictive farming is analogous to taking a pill to target an ailment. The solutions are highly tailored from the type of crop suitable for a plot to the use of pesticides in targeted regions only. Adopting precision agriculture and modern farming reduces the production cost and wastage, as the tailored needs of each plot are catered to. Precision farming is practiced by adopting analytical software and the use of technical equipment. Rigorous data collection is done on soil testing, plot measurement, weather pattern analysis, and crop analysis through sensor-equipped devices placed on the fields. The data is calibrated to devise conclusions and based upon those results a very detailed and precise set of practices can be adopted.

Climate Change and Precision farming

Agri-businesses are highly vulnerable to climate change. Farming is becoming increasingly challenging in many areas due to decreased yields and increased frequency of extreme weather events like drought or flood. Climate change is expected to diminish global agricultural production by 17 percent by 2050, according to a study by the National Academy of Science (NAS).

Precision agriculture, according to NAS, should play a big role in making farming more sustainable, without compromising production or farmer earnings. With precision agriculture, the World Economic Forum believes world food production could rise 10-15 percent by 2030 and greenhouse gas emissions and water consumption would decrease by 10 to 20 percent, respectively, if 15 to 25 percent of farms adopted the technology.

Site-specific field management and variable-rate application (VRA) technologies are two of the most commonly discussed aspects of precision agriculture. These measures are essential to reducing the environmental effect of agriculture.

Making Precision Farming feasible through farm digitization

In developing economies, 32% of food losses occur during food production as analyzed by McKinsey on FAO data.

Conventional farming practices are area-centric. There is a general set of crops cultivated throughout an area. All the farmers in that area follow the same procedures with respect to the sowing, nourishing, irrigation, and harvesting period. What these practices result in is: unpredictability, overuse of resources, and uncontrolled waste production.

Before the use of tech in agriculture, a farmer’s probability of yielding good produce was as good as tossing a coin and wishing for heads. Since farmers had no information on their farms, there was no way of learning the causes of crop loss. This practice pushed the farmers towards losses and debt. Advancements in big data analytics, IoT, and accessible satellite imagery created optimism for the agriculture sector, thereby combating the issue of unpredictability.

Key advantages of Precision Farming

Since details of areas in a single farm can be traced, precision farming benefits farmers in several ways. Discussed below are some of the key advantages of precision farming:

  • A refined set of cultivation practices and choice of crops based on suitability of land
  • Elimination of volatility and risk
  • Waste management
  • Reduced production costs
  • Minimum environmental impact
  • Optimized use of fertilizers
  • Water management

Scope of Precision Farming

Precision farming examples include the adoption of highly precise set of practices that uses smart farming technologies to cater to the needs of individual plots and crops. Big data analytics software such as Cropin or robots such as drones can be used to get detailed information on the plot, soil type, suitable crops, irrigation, and fertilizer needs. The information obtained is used to tailor a very unerring selection of crops, fertilizer quantity, and watering needs. Precision agriculture helps farmers live a debt-free life as production costs and losses are reduced and overall environmental impact is also minimized.

The Future of Agriculture

Role of AI and ML in Precision Farming

Precision agriculture and modern farming focus on reducing production cost and wastage, as it is tailored to the needs of each plot. It centers on data collection and analysis of farm pIots which comprises sensors, drones, and robots for recording the data, and software as a service (SaaS) can be used to adapt to precision farming systems.

Although IoT is still at a nascent stage, the governments of agriculture-dominant economies do invest in other cutting-edge technologies like artificial intelligence and machine learning (AI/ML) to make smarter agriculture solutions. In countries like India, the implementation of IoT in agriculture has its own set of unique benefits and challenges.

Firstly, the farmers fear upgrading to agtech as they lack knowledge about the applicability of the technology in agriculture. Besides this, the sensors, robots, and drones are expensive, have high maintenance, and require technically trained labor to operate. Further, the captured data needs to be analyzed in a lab or using specialized instruments on the farm. Also, a variety of sensors are required for collecting data on different parameters, which need to be analyzed separately, hence driving operational costs higher. Therefore, the solution must be cost-effective and highly scalable, considering the various sizes of farms.

precision farming and man looking at field ph level.

The Precision Farming Solution

A more economical, scalable, and accurate solution is cloud-based SaaS (Software as a Service). SaaS solutions used in agriculture technology focus on providing advanced farming technologies that help farmers, agribusinesses, and other stakeholders to make smart decisions based on the analysis of data. Cropin is at the forefront of making agriculture smarter with the use of satellite imagery, weather analysis, and machine learning for monitoring, detection, analysis, and prediction. Cropin’s smart applications can be integrated with already installed software and sensors through APIs. The data gathered on soil or moisture levels, temperature changes, or crops can be processed using the capabilities of big data analytics and machine learning algorithms to provide actionable insights based on the accuracy of collected data.

Tools of precision farming

Anyone pursuing precision farming should be knowledgeable about the tools available. Computer-based applications are used to create precise farm plans, field maps, crop scouting, yield maps and to define the exact amount of inputs to be applied to fields. One benefit of this method is the ability to design a friendly agricultural strategy, which helps to lower costs and boost yields. But, because the obtained data cannot be integrated into other supporting systems, these applications offer limited value data that cannot be used for large-scale precision farming solutions. Let us dive into the tools needed for precision farming: 

1) Global positioning system

GPS is a set of satellites that identify the location of farm equipment of an actual site in the field. The GPS technology provides an accurate positioning system necessary for field implementation of variable rate technology in agricultural input management. The current internet enables the creation of a system for efficient remote sensing-based agricultural management.

2) Geographical information system (GIS)

A geographical information system (GIS) consists of a computer software database system used to input, store, retrieve, analyze and display, in map-like form, referenced geographical information.

3) Grid sampling

Grid sampling is a technique for segmenting fields into around 0.5–5 ha-sized units. Those grids' soil samples will be used to calculate the proper application rates for crop inputs Each grid has many samples collected, combined, and delivered to the lab for evaluation.

4) Variable-rate technology

Variable-rate technology (VRT) consists of farm field equipment with the ability to precisely control the rate of application of crop inputs that can be varied in their application including tillage, insect control, fertilizer, plant population and irrigation.

5) Yield monitors

Crop yield measuring tools fitted on harvesting machinery are called yield monitors. Along with the positioning data from the GPS device, the yield data from the monitor is recorded and saved. Utilizing the yield data, GIS software creates yield maps.

6) Yield maps

Data from an adapted combine harvester that has a GPS integrated with a yield tracking system is processed to create yield maps. Yield mapping includes tracking the actual moisture in the field and the crop flow through the combined harvest time.

7) Remote sensors

Remote sensors are generally categorized as aerial or satellite sensors. Changes in soil type, crop development, field boundaries, roads, water, etc., they can indicate differences in field color. Remote science in agricultural terms means viewing crops from overhead (from a satellite or low-flying aircraft) without coming into contact, recording what is viewed and displaying the image and providing the map to pinpoint the field problems earlier and more effectively. 

8) Auto-guidance systems

Farmers may keep their rows straight during farm operations and return to the same rows the next season thanks to an auto-guidance system. With these systems, they enable more accurate input applications.

9) Proximate sensors

Proximate sensors can be used to measure soil (N and pH) and crop properties as the tractor passes over the field. The soil sample is scooped, pressed against an electrode, a stabilization period of about 10-15 seconds allowed, and the reading taken.

10) Computer hardware and software

Computer support is required to analyze the data gathered by other components of precision farming technology and to make it accessible in formats such as maps, graphs, charts, or reports.

Sustainable Digitalization of Agriculture

The recent rapid digitalization has reduced the exhaustive paperwork in banks, hospitals, and most private and public sector organizations seem to diminish as their businesses move online. Digitization has reduced the manual work - which was time-consuming, error prone, and inefficient - thus saving millions for corporations. Digitization of the economy has broken the barriers and has successfully curtailed the fear of tech dependency, especially among the farming community. Digitalization is slowly also revolutionizing the vast and complex Agriculture sector.

precision farming and farm digitization

The recent and rapid digitalization has reduced the exhaustive paperwork burdening private and public sector organizations in diverse sectors, like finance and healthcare. Digitization has reduced the manual work, which was time-consuming, error-prone, and inefficient, thus saving millions for corporations. Digitalization of the economy has broken the barriers and has successfully curtailed the fear of tech dependency, especially among the farming community. It is also slowly revolutionizing the vast and complex agriculture sector.

The United Nations projects that by the year 2050 the population of the world will be 9.7 Billion. With the relevance of over 60% of the world population relying on agriculture for food, the pressure to increase crop production to meet demands doesn’t seem to ease. Coupled with climate change, which is leading to the rise in global temperatures, levels of greenhouse gases, and frequency of extreme weather events like droughts and floods, along with increasing labor costs, high production costs, and unpredictability, poses a major challenge to the future of agriculture. Hence, the goal is to increase productivity in a sustainable way.

Authored by Pragati Shah