Digital Farming: The Future of Farming

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The farming community has spent several years defining an operational description for digital farming. In many cases, various solutions have been put forth, all claiming to be digital farming or digital agriculture. However. agriculture is a complex system that you can analyze. Most of the proposed solutions are weather, and imagery including many proprietary point solutions. 

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What is Digital Farming?

Digital farming is the use of digital technology to integrate agricultural production from the farmlands to the consumer. These digital technologies can provide tools and information to the agricultural industry. Consequently, one can make more informed decisions and improve productivity. It involves applying precision location methods and decision quality agronomic information. Consequently, it helps to forecast, and affect the continuity of cultivation issues across the farm.

Major Milestones in Advancement in Agriculture

Agriculture technologies have rapidly advanced in the second half of the 20th century and the starting of the 21st century. These developments have changed the way farmers work especially with the introduction of social media. Their agronomic knowledge has also increased.

The following are the significant milestones in the technological advances in farming over the past 50 years.

  • The 1960s – The Green Revolution

In the mid-1940s, Dr. Norman Borlaug started a growing process that allowed plants to flourish with new crop management and irrigation methods. By the 1960s, the benefits of this Green Revolution were apparent. It was a digital revolution. This was the time when successful new wheat varieties were made available in countries across the globe.

  • 1974 Release of First single active ingredient Roundup Herbicide

Roundup developed a new herbicide using glyphosate as the active ingredient. Farmers use these herbicides to control weeds in their crops. These branded herbicides also made their way into garden and lawn products. Consequently, it allowed landowners to kill weeds along sidewalks, driveways, gardens, and fences.

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  • 1975 Introduction of Rotary Combines 

Sperry-New Holland created the first twin-rotor system combine. This equipment allowed the crop to be cut and separated in one pass over the field. For corn, it not only divided the husk and ears but shelled the kernels and chopped the stalks.

  • 1982 Development of First GM Plant Cell

Scientists working at Monsanto became the first in the world to genetically modify a plant cell. The team of scientists used Agrobacterium to introduce a new gene into the petunia plant. Subsequently, they announced their success the following year. Within the next five years, researchers at Monsanto planted their first outdoor trials of a genetically modified crop – tomatoes. These tomato crops were resistant to Roundup agricultural herbicides, insects, or viruses.

  • 1994 Satellite technology advances farming

For the first time, farmers could use satellite technology to see their farms from overhead. Consequently, it allowed better tracking and planning.

  • 1996 – Commercial Availability of Monsanto’s first GMO crops.

Bollgard insect-protected cotton and Roundup Ready soybeans became the first genetically modified row crops available to farmers. The soybeans provided tolerance to the agricultural herbicide. The GM traits in cotton protected the cotton bollworm, tobacco budworm, and pink bollworm.

  • 2000 – Software and mobile devices help farmers have better harvests

The farmers started carrying mobile devices. Consequently, it allowed them to stay connected while in the field. Thus, they had access to data needed when they were on the move. They got the ability to place orders for fertilizer or seed at any time and any place.

  • 2015 Data revolutionizes Farming Potential

Farmers usually make decisions based on the information they have on hand. Therefore, the data has helped them utilize the power of information. Consequently, they could make better-informed decisions that allowed them to use resources in a sustainable manner. The digital platforms Climate Corporation’s Climate FieldView brings together data collection, agronomic modeling, and local weather monitoring. Consequently, farmers get a better understanding of their fields. These tools allow farmers to plan for better harvests and make decisions that are better for the planet.

Importance of Precision Location Methods in Digital Farming

Precision location methods deal with geolocation services associated with the GPS (Global Positioning System) and its extensions. These geolocation services overlay on a digital map for precision sensing, precision farming, identification, predictive decision-making, and action accordingly.

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Decision quality information is within the decision loop of the event and is timely delivered. Advanced sensors offer this decision quality information. These systems include descriptive models and predictive algorithms that provide critical insight into the agronomic issue.

Farming is a real time, end-to-end, continuous decision-making process. Additionally, it requires timely actions and decisions. It starts from the upstream of planting and ends with the downstream of harvest. Modern-day farming is about the knowledge and subjective observational powers of the individual. Tomorrow’s farming will be more about the sensed, objective, predictive power, and precision of the digital ecosystem.

Digital Farming – Complete Operational System

Digital Farming involves a complete operational system. Due to this reason, the requirements ensure the system will scale to millions of acres and deploy across multiple crops. It will provide end-to-end digital solutions will exist within an ecosystem. The system will support the diverse agronomic and economic needs of thousands of stakeholders simultaneously. It has to be much more than a curiosity for the scholarly intellectual. It must consistently serve the small grower up to the most prominent farmer.


Digital farming must organize, analyze, and arrange the timely delivery of information from data sources that constitute a field at the lowest level. It must break the area down into differentiable, geographically-located, and homogeneous units of productive assets. Each unit must be treated as a productive asset.

The precision location ensures that the collected information about the unit is measured, collected, analyzed, and actioned for the exact location. Moreover, it is differentiated from all of the other surrounding assets. It is individually homogeneous and identical in size, footprint, and depth so that the system can repeatedly analyze the same unit.

Trends driving Digital Farming 

The demand for food is all set to grow globally as the world’s population increases from seven billion to almost 10 billion over the next 30 years. A growing global middle class, particularly in Asia, is increasing food and fiber export growth prospects.

Although the demand is bound to grow, farmers are facing the following challenges of climate changes:

  • changes in rainfall patterns
  • reductions in water availability
  • frequent tornadoes, hurricanes, cyclones, and cloud bursts
  • increased temperatures
  • more frequent extreme weather events.

In this volatile environment, farmers must continue to innovate to maintain and improve productivity to meet the surge in demand.

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Digital technologies can provide farmers with the information and ability to meet these challenges and seize growth opportunities. Consequently, both home consumers, as well as overseas consumers, are now more informed and aware about the products they are buying. Therefore, they demand high-quality food and fiber. They want to know more about the source of their products. Thus, digital technologies enable improved traceability of agricultural products, provide peace of mind for consumers. Moreover, it increases farmers’ value.

Examples of Digital Farming

The enormous opportunities to lift productivity in the farming sector lie in new and emerging technologies such as:

  • robotics
  • new packaging material
  • geospatial monitoring
  • precision application of water and chemicals
  • animal monitoring
  • weather monitoring
  • biotechnology and digital and wireless technologies for data measurement


The introduction of robotics to the poultry, dairy, and beef farming industries is progressing at a rapid pace. Subsequently, the following applications are most impacted:

  • egg collection and sorting
  • autonomous feeding and milking
  • autonomous cleaning.

These technologies are assisting a lot in the early detection and treatment of health issues of animals.

Satellite imagery

The satellite imagery provides the moisture data. This data, coupled with the soil property, is used to program the agricultural equipment for variable seeding rates and depths. Consequently, it leads to higher yields and less wastage.

Digital infra-red light and heat sensors combined with geographic information system technology in drones. These drones are used for measuring crop health to inform decisions about:

  • harvesting
  • pest management
  • irrigation
  • fertiliser applications

Sensors and electronic identification

Integrated digital animal health biometric sensors and electronic identification devices enable farmers to respond to animal stress or disease cases rapidly. Consequently, it is helping in increasing livestock and agricultural production and improving livestock health.

Digital Farming Investment Scheme

Many countries have implemented Digital Agriculture Investment Scheme to assist farmers to transition to digital technology enables business.  Due to this strategy, they can improve productivity, resilience, and the long-term viability of their farms. Additionally, this strategy is to create a strong, innovative, and sustainable agriculture sector. Additionally, the process outlines the country’s plan to grow a thriving and globally competitive industry. Funds are being committed to the scheme to help farmers (farmers access) overcome the financial difficulty in investing (invest in digital) in digital agriculture technologies.


The essence of digital farming lies in generating value from data. Therefore, digital farming means going further beyond the presence and data availability. Thus, the main aim is to develop actionable intelligence and meaningful value addition from such data. Digital farming is the integration of both the concepts of smart farming and precision farming. 

For farmers, digital agriculture provides the opportunity to increase their farm’s production, Additionally, it saves costs in the long term and eliminates risks. Consequently, the majority of the experts have the view that digital farming is the future of the agricultural industry.

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