The Agricultural Revolution: Beyond Precision

Randhir Chauhan, MD, NetafimWith more than 20 years of experience in the micro-irrigation sector, Randhir has handled cross-functional profiles of sales, marketing & operations for Netafim.

Mangesh is sipping morning tea in his home in Maharashtra's sugarcane belt, while a farm instrument installed on the field is cognizant of the soil moisture, weather trends, and recent rainfall and gives consistent data on his smartphone. Mangesh just opens his phone, checks the data and feeds a new irrigation schedule and moves on. A satellite is taking images of Mangesh's crops for pest prediction & yield estimation and feeds the data back to Mangesh, input companies, prospective buyers, credit organizations and relevant stakeholders. For many, this may still seem to be a scene from a science fiction movie set in 2118 and not something that in reality is happening in 2018. This is the effect of digitalization combined with artificial intelligence.

Is precision agriculture combined with advanced data analytics ready to transform the 10,000-year-old sector in the next 10 years? The answer to the question is already showing results in the field with the use of precision agriculture and digital technologies and as with all the technological development, every 10-year block is becoming better than the previous one with newer and advanced technologies. Commercially, the market is growing at a breakneck pace. A recent report pegged the artificial intelligence (AI) in agriculture market value at $432.2 million in 2016 and which is expected to be valued at $2,628.5 million by 2025, at a CAGR of 22.5 percent during the forecast period.

AI, Not Just Artificial, but Advanced Intelligence
In 1990s, India, an average farmer took a decision on farming, irrigation and pest control-based on available resource and limited observable data. In just 20 years, the average farmer is now moving towards effective products and resources to get more productivity from the similar or even lesser available resources and wealth of data to make informed decisions. It is often said that ‘Data is the new oil of the economy’, and the same has been helping in agricultural transformation across the world.
Artificial intelligence (AI) is a technology of low-cost prediction and discovery. It exploits the new resource of the digital age (the precious data) to identify patterns and make predictions. In countries like India that lack required human capital in fields like agricultural science and lower coverage of adequate information, AI presents an opportunity to bridge the gap and deliver sustainable results.

Bringing the Confidence in Uncertainty
Newest AI-led applications and technologies are disrupting the agricultural space every day and creating a platform for better preventive measures, yield productivity, and resource utilization. We can categorize the current applications based on the solutions into four major categories. In crop and soil monitoring segment, image analytics, soil variability measurement, deep learning algorithms are being leveraged by companies for processing captured data and offering accurate solutions in a relatively short period. The automated irrigation segment has shown disruptive advancements by enabling AI and data-driven automated irrigation, fertilizer application with irrigation (Fertigation) and crop protection. Innovative products capable of monitoring, analysing, and controlling the irrigation backed by AI have already been introduced in the market with the consistent addition of advanced features. With irrigation as the most important input to any crop and 70 percent of the world's freshwater used for agriculture, the ability to better manage how it's used will also have a huge impact on the world's water supply and not just limited to agriculture.

Predictive analytics covers an entire solution range that made guesses about the future of farming, not a magic dependent, but a data science-based one. Infield sensors, remote sensing inputs, and several data points help to take a well-informed decision much easier. Machine learning models and algorithms based on past & present factors in the field, along with environmental factors help to make an accurate prediction of each step of farming. Many technological organizations are already assisting farming at right sowing time, right irrigation schedule, expected pest attack and various other factors through predictive analytics. This is now being explored in improving supply chain efficiencies in agriculture as well. Agricultural Robotics segment backed by sturdy hardware and software alignment is currently used, and proponents of the robotics market are developing and programming offerings that are equipped with the intelligence to handle essential agricultural tasks and operate in unstructured and dynamic agricultural environments.

Precision Farming & AI a Necessity
A Global Harvest Initiative report pointed-out that at the current rate of agricultural productivity growth in India, domestic production will only meet 59 percent of the country's food demand by 2030. That means around 600 million people will be dependent on imports or will face minimal food availability. The variability in farming due to external factors is on an exponential increase with the change in weather patterns, rainfall variability, and new pest attacks. It needs an exponentially developing technology like AI to counter the effects and led to a sustainable environment of growth and productivity improvement in agriculture. Food and water, two of the most important constituents of earth sustainable life, are under severe stress ­ World needs to double our food production by 2050 to match the population growth, and 20 percent of the world population faces water shortages today as per the UN report (India is under severe water stress category). With depleting resources.