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 rising population, which as per UN projections will increase from 7.5 billion to 9.7 billion in 20501, there will be more pressure on land as there will be only an extra 4% of land, which will come under cultivation by 2050. This means that farmers will have to do more with less. According to the same survey, the 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 the global food production by 50% by 20502 to feed an additional two billion people.AI-powered solutions will not only enable farmers to improve efficiencies but they will also improve quantity, quality and ensure faster go-to-market for crops.
Artificial Intelligence in Agriculture
Using AI for intelligent spraying of chemicals – Brings in cost savings
Every day, farms produce thousands of data points on temperature, soil, usage of water, weather condition, etc. With the help of artificial intelligence and machine learning models, this data is leveraged in real-time for obtaining useful insights like choosing the right time to sow seeds, determining the crop choices, hybrid seed choices to generate more yields and the like.
AI systems are helping to improve the overall harvest quality and accuracy – known as precision agriculture. AI technology helps in detecting disease in plants, pests and poor nutrition of farms. AI sensors can detect and target weeds and then decide which herbicide to apply within the region. This helps in reduced usage of herbicides and cost savings. Many technological companies developed robots, which use computer vision and artificial intelligence to monitor and precisely spray on weeds. These robots are able to eliminate 80% of the volume of the chemicals normally sprayed on the crops and bring down the expenditure of herbicide by 90%. These intelligent AI sprayers can drastically reduce the number of chemicals used in the fields and thus improve the quality of agricultural produce, and bring in cost efficiency.
Using AI-based robots for farm harvesting – Tackling the labor challenge
Have you ever wondered who actually picks the produce from the agricultural land? Well, in most cases, it is not the traditional farm worker but robotic machines that are capable of doing bulk harvesting with more accuracy and speed that are responsible for getting the produce on your kitchen table. These machines help improve the size of the yield and reduce waste from crops being left in the field.
Many companies are working on improving agricultural efficiencies. There are products like autonomous strawberry-picking machine1 and a vacuum apparatus that can harvest mature apples from trees. These machines use sensor fusion, machine vision and artificial intelligence models to identify the location of the harvestable produce and help pick the right fruits.
Agriculture is the second largest industry after Defense where service robots market have been deployed for professional use. The International Federation of Robotics estimates that as many as 25,000 agricultural robots have been sold —matching the number used for military purposes.
Using AI for predictive analytics – Enables right decision-making
Predicting the best time to sow
The difference between a profitable year and a failed harvest is just the timely information on a simple data point of timing of sowing the seed. To combat this, scientists of ICRISATused a predictive analytics tool to arrive at a precise date for sowing the seeds to obtain maximum yield. It even gives insights on soil health and fertilizer recommendations in addition to a 7-day weather forecast.
Crop yield predictions and price forecasts
For many farmers, the biggest worry is the price fluctuation of the crop. Due to unstable prices, farmers are never able to plan a definite production pattern. This problem is highly prevalent in crops like tomatoes that have very limited shelf time. Companies are using satellite imagery and weather data to assess the acreage and monitor crop health on a real-time basis. With the help of technologies like big data, AI and machine learning, companies can detect pest and disease infestations, estimate the tomato output and yield, and forecast prices. They can guide the farmers and governments on the future price patterns, demand level, type of crop to sow for maximum benefit, pesticide usage etc.
Innovative startups are using AI in the field of agriculture. A Berlin-based agricultural tech startup3developed a multi-lingual plant disease and pest diagnostic app, which uses various images of the plant to detect diseases; a smartphone collects the image that is matched with a server image and then a diagnosis of that particular disease is provided and applied to the crop using intelligent spraying technique. In this way, the application uses AI and ML to solve plant diseases. Over seven million farmers have downloaded this app and it has helped identify over 385 crop diseases among field crops, fruits, and vegetables.
To summarize, AI solves the scarcity of resources and labor to a large extent and it will be a powerful tool that can help organizations cope with the increasing amount of complexity in modern agriculture. It is high time that big companies invest in this space.
Can AI replace the knowledge that farmers have always had? The response is probably no for now- but definitely in the near future, AI will complement and challenge the way decisions are made and improve farming practices. Such technological interventions are likely to lead to better agricultural practices, yields, and qualitatively improve the lives of farmers.
References
[1] https://www.un.org/en/sections/issues-depth/population/
[2]http://www.fao.org/fileadmin/templates/wsfs/docs/expert_paper/How_to_Feed_the_World_in_2050.pdf
[3]http://www.fao.org/e-agriculture/ne...igence-help-improve-agricultural-productivity
[4]https://www.forbes.com/sites/cognit...-ai-is-transforming-agriculture/#5442e7ad4ad1
[5] https://www.sciencedirect.com/science/article/pii/S2589721719300182#bbb0025
[6] https://www.technologyreview.com/s/...g-farmers-and-babies-in-the-developing-world/
[7] https://analyticsindiamag.com/soon-...curately-determine-produce-yield-for-farmers/
About the author
RevanthPre Sales Solution Consultant
Revanth is a Pre Sales Consultant for HOLMES - Wipro’s Artificial Intelligence & Automation Platform. He works on various proposals by understanding the pain points in the customer IT environment and drives automation journey for various clients. He is an MBA from Indian Institute of Technology, Bombay.
