ARTIFICIAL INTELLIGENCE-BASED AGRICULTURE

1. Background

• Technology has redefined farming over the years and technological advances have affected the agriculture industry in more ways than one. 
• Agriculture is the mainstay occupation in many countries worldwide and with the rising population, which as per UN projections will increase from 7.5 billion to 9.7 billion in 2050, there will be more pressure on land as there will be only an extra 4% of the land, which will come under cultivation by 2050. 
• This means that farmers will have to do more with less. According to the same survey, food production will have to increase by 60% to feed an additional two billion people. 
• However, traditional methods are not enough to handle this huge demand. This is driving farmers and agro companies to find newer ways to increase production and reduce waste. 
• As a result, Artificial Intelligence (AI) is steadily emerging as part of the agriculture industry’s technological evolution. 
• The challenge is to increase global food production by 50% by 2050 to feed an additional two billion people.
• AI-powered solutions will not only enable farmers to improve efficiencies but will also improve the quantity, and quality and ensure faster go-to-market for crops.
• Artificial Intelligence-based agri-tech farm reforms have opened doors to private sector investments in agriculture.
• Agriculture and farming are one of the oldest and most important professions in the world. It plays an important role in the economic sector. Worldwide, agriculture is a $5 trillion industry.

2. The contemporary scenario in India

• In the financial year 2019-20, Indian agri-food tech start-ups raised more than $1 billion through 133 deals. 
• India’s exports of agricultural products rose to $37.4 billion in 2019 and with investments in the supply chain and better storage and packaging, this is set to increase further. All these steps will go a long way in ensuring remunerative prices for farmers and reducing agrarian stress.
• This growth in agricultural output and productivity is being further enhanced by investments in technology. 
• Disruptive technologies like AI are making big positive changes across Indian agriculture, and an increasing number of agri-tech startups in the country are working to develop and implement AI-based solutions. 
• Globally, AI applications in agriculture reached a valuation of $852.2 million in 2019 and this is estimated to grow to almost $8.38 billion by 2030, a nearly 25 per cent growth.
• The Indian agri-tech market, presently valued at $204 million, has reached just 1 per cent of its estimated potential of $ 24 billion.

3. Challenges faced by farmers in traditional Farming techniques

• In farming climatic factors such as rainfall, temperature and humidity play an important role in the agriculture lifecycle. Increasing deforestation and pollution result in climatic changes, so it’s difficult for farmers to make decisions to prepare the soil, sow seeds, and harvest.
• Every crop requires specific nutrition in the soil. There is 3 main nutrients nitrogen(N), phosphorus(P) and potassium(K) required in soil. The deficiency of nutrients can lead to poor quality of crops.
• As we can see from the agriculture lifecycle that weed protection plays an important role. If not controlled it can lead to an increase in production cost and also it absorbs nutrients from the soil which can cause nutrition deficiency in the soil.

5. The opportunity associated with the use of AI in Agriculture

• Use of technology in agriculture will improve farmers’ access to markets, inputs, data, advisory, credit and insurance. 
• Timely and accurate data coupled with analytics can help build a robust demand-driven efficient supply chain. 
• With the use of sensors, photographs through phones, IoT devices, drones and satellite images, agricultural data can be collected and matched with weather data, soil health card data, and mandi prices and help build predictive models that can greatly enhance decisions about seeds, fertilizers, pesticides that are of critical importance in both pre-harvest and post-harvest stages. 
• Most of these AI models are low-cost and affordable and can add a lot of value to the agriculture ecosystem.

6. Applications of AI in Agriculture

• The industry is turning to Artificial Intelligence technologies to help yield healthier crops, control pests, monitor soil, and growing conditions, organize data for farmers, help with the workload, and improve a wide range of agriculture-related tasks in the entire food supply chain.
• Use of weather forecasting: With the change in climatic conditions and increasing pollution it’s difficult for farmers to determine the right time for sowing seed, with help of Artificial Intelligence farmers can analyze weather conditions by using weather forecasting which helps they plan the type of crop can be grown and when should seeds be sown.
• Soil and crop health monitoring system: The type of soil and nutrition of soil plays an important factor in the type of crop grown and the quality of the crop. Due to increasing, deforestation soil quality is degrading and it’s hard to determine the quality of the soil.
• A German-based tech start-up PEAT has developed an AI-based application called Plantix that can identify the nutrient deficiencies in soil including plant pests and diseases by which farmers can also get an idea to use fertilizer which helps to improve harvest quality. This app uses image recognition-based technology. The farmer can capture images of plants using smartphones. We can also see soil restoration techniques with tips and other solutions through short videos on this application.
• Machine learning-based company that helps farmers to do a soil analysis to farmers. It helps farmers to monitor soil and crop health conditions and produce healthy crops with a higher level of productivity.
• Analyzing crop health by drones: Drone-based Ariel imaging solutions for monitoring crop health. In this technique, the drone captures data from fields and then data is transferred via a USB drive from the drone to a computer and analyzed by experts.
• Precision Farming and Predictive Analytics: AI applications in agriculture have developed applications and tools which help farmers inaccurate and controlled farming by providing them proper guidance to farmers about water management, crop rotation, timely harvesting, type of crop to be grown, optimum planting, pest attacks, nutrition management.
• While using the machine learning algorithms in connection with images captured by satellites and drones, AI-enabled technologies predict weather conditions, analyze crop sustainability and evaluate farms for the presence of diseases or pests and poor plant nutrition on farms with data like temperature, precipitation, wind speed, and solar radiation.
• Farmers without connectivity can get AI benefits right now, with tools as simple as an SMS-enabled phone and the Sowing App. Meanwhile, farmers with Wi-Fi access can use AI applications to get a continually AI-customized plan for their lands. With such IoT- and AI-driven solutions, farmers can meet the world’s needs for increased food sustainably growing production and revenues without depleting precious natural resources.
• In the future, AI will help farmers evolve into agricultural technologists, using data to optimize yields down to individual rows of plants
• Agricultural Robotics: AI companies are developing robots that can easily perform multiple tasks in farming fields. This type of robot is trained to control weeds and harvest crops at a faster pace with higher volumes compared to humans.
• AI-enabled system to detect pests: Pests are one of the worst enemies of the farmers and damage crops.AI systems use satellite images and compare them with historical data using AI algorithms and detect if any insect landed and which type insect has landed like locusts, grasshoppers, etc. And send alerts to farmers on their smartphones so that farmers can take required precautions and use required pest control thus AI helps farmers to fight against pests.

7. Infographic

8. Way forward

• Thanks to the diversity of its soil types, climate and topography, India provides a great opportunity for data scientists and AI experts to develop state-of-the-art AI tools and solutions for agriculture. Indian farms and farmers provide vast and rich data to help create AI solutions for not just the country but the world at large. And this is one of the factors that makes the opportunity for AI in Indian agriculture unparalleled.
• Artificial Intelligence in agriculture not only helps farmers to automate their farming but also shifts to precise cultivation for higher crop yield and better quality while using fewer resources.
• Companies involved in improving machine learning or Artificial Intelligence-based products or services like training data for agriculture, drone, and automated machine making will get technological advancements in the future and will provide more useful applications to this sector helping the world deal with food production issues for the growing population.