How AI Can Address Challenges in the Indian Agriculture Sector

Here is an article by Mr Nilesh Jahagirdar, VP Marketing [x]cube LABS wriitten for SMEStreet in which he explained the used-case of AI technologies for Agriculture sector.

SMEStreet Edit Desk
Aug 05, 2022 10:26 IST
New Update
Nilesh Jahagirdar

Agriculture is the backbone of every nation. While earlier, it was driven by conventional methods, farmers and industry players now have tech solutions at their disposal. 

Owing to the growing population, the demand-supply gap is significant. However, the farmers' traditional techniques currently cannot meet the demand. This has created much room for innovation, and in recent years, technological improvements have offered some hope for improved yields and more effective agricultural practices. This is how AgriTech has come into existence and is growing rapidly. Amongst the new-age technologies gaining popularity, AI receives a special mention. 

The growing prominence of AI in agriculture

Artificial Intelligence takes over complex and repetitive tasks and works on three main objectives: learning, reasoning, and perception. It is revolutionizing the agriculture industry and is reshaping conventional practices. The technology protects the industry from several concerns, including food safety, population increase, climate change, and job issues. Thanks to AI, modern agriculture has advanced to a new level.


As per Markets and Markets’ study, it is predicted that the market for Artificial Intelligence in agriculture is projected to grow from $1.0 billion in 2020 to $4.0 billion by 2026 and will grow at a CAGR of 25.5%. The research further points out that the rising usage of sensors and aerial photography for crop monitoring, the enhancement of crop production through deep learning technology, and government support for implementing modern agriculture methods are the key factors that will be driving the market's growth. 


AI: One-stop solution for farmers’ grievances 

Similar to conventional farming methods, farmers would face numerous challenges. AI is commonly used in this sector to address these issues. Due to Artificial Intelligence, farmers gain from healthier crop production, pest management, soil monitoring, and many other benefits. 


The industry is turning to Artificial Intelligence technology to improve a wide range of agriculture-related tasks throughout the food supply chain. This new-age tech not only helps produce healthier crops, control pests, monitor soil, and growing conditions but also helps organize data for farmers, reduce workload, and organize pests. 


There are various applications of AI in the agriculture industry that render various benefits to the market- 


Weather Forecasting for seed plantation

Due to the changing climate and rising pollution, farmers find it challenging to choose the ideal time for seeding. Farmers can plan the type of crop that can be cultivated and when seeds should be sown by utilizing weather forecasting and artificial intelligence to examine weather conditions. Particularly in the case of seasonal crops, since they cannot be grown yearly, they rely heavily on forecasts. The farmers must follow certain time constraints and weather requirements. The weather forecasting models developed by AI applications have tremendously benefited the more extensive agricultural lands and farms and the smaller farms. 


Best time to sow

With AI, farmers can process and gather more data than without it. A simple data point about the timing of seed sowing can make the difference between a successful year and a failing one. To avoid this, scientists deploy a predictive analytics method to determine the exact time to plant the seeds to get the most yield. In addition to a 7-day weather forecast, it also provides information on the health of the soil and fertilizer suggestions.


Crop yielding and price forecast

The variation in the crop's price is a significant source of concern for many farmers. They can never set a specific production pattern because of fluctuating prices. This issue is widespread for crops like tomatoes, which have a short shelf life. To deal with this challenge, companies examine the land and continuously monitor crop health using satellite imagery and weather data. Big data, AI, and Machine Learning technologies enable businesses to identify pest and disease infestations, calculate tomato output and yield, and forecast prices. They also guide farmers and the government on future pricing trends, demand levels, the best crops to plant for optimum profit, pesticides use, and other key areas. 


Monitoring soil health

The kind and nutrition of soil have a significant impact on crop quality. However, it is challenging to assess soil quality because of the daily decline brought on by the rate of deforestation. Various AI-based applications help detect nutrient deficits in soil and plant pests and diseases. This way, they provide farmers with the knowledge they need to use the appropriate fertilizer to increase the quality of their yield. With picture recognition-based technology, the farmers can use smartphones to take photos of the plants. This way, they can also view soil restoration methods along with advice and come up with other alternatives for a better yield of crops. 


Analyzing crop health by drones

Drone-based ariel imaging solutions for agricultural health monitoring have been made possible by technology. Based on AI, these devices collect data from fields sent by a USB drive to a computer for expert analysis. Even the photographs collected using the algorithms are analyzed to gather insights into the state of the farm. They further assist in identifying pests and microorganisms, enabling farmers to implement pest control measures and other techniques when necessary.


Precision farming

‘Right place, time, and goods’ are the three pillars of precision farming. The labor-intensive aspect of agriculture required to execute repeated chores can be replaced by precision farming technology, which is considerably more precise and controlled. The measurement of plant stress levels is one instance of AI-enabled precision farming. High-resolution photos and various plant sensor data can be used to obtain this. The machine learning model can further be used for stress recognition and then fed with sensor data as input for obtaining results.


Intelligent Spraying

Weed can be quickly and easily recognized with AI sensors, which can also identify weed-affected locations. Herbicides may be precisely applied in these locations after locating them, reducing the need for herbicides and saving time and crop. Various AI firms are developing robots with computer vision that can precisely spray weeds. Using AI, sprayers can significantly reduce the number of pesticides needed to be applied to fields, improving crop quality and reducing costs.


AI resolving the issue of workforce shortage

One of the most prevalent issues in agriculture is workforce shortage. It can be resolved with the help of Artificial Intelligence. They are affordable solutions that take over repetitive tasks. They are accurate, have a longer shelf life, and are less prone to errors. 


Robotics is widely employed in many industries, primarily manufacturing, to carry out challenging jobs. Currently, numerous AI companies are creating robots for use in the agriculture industry. These AI robots are designed so that they can handle a variety of farming activities.AI enabled robots are also taught to inspect crops for quality, spot and control weeds, and harvest crops more quickly than humans. They are also utilized for laborious tasks like trimming lettuce and gathering fruits and vegetables. 


Driverless tractors, intelligent irrigation and fertilization systems, smart spraying, vertical farming software, and AI-based harvesting robots are other examples of AI applications in agriculture.


Summing up!

With the help of Artificial Intelligence, farmers may automate their routine jobs while switching to careful cultivation for improved crop quality and production while consuming fewer resources. As technology advances, businesses that work to improve machine learning or Artificial Intelligence-based goods or services like training data for agriculture, drones, and automated machine manufacturing will be able to offer more beneficial applications to this industry, assisting the world in addressing issues related to food production for the expanding population.


The adoption of AI solutions will have a significant impact on the future of AI in farming. With the rising complexity of modern agriculture, the technology will emerge as a potent instrument that may assist industry players and farmers in coping with the shortage of resources and labor along with impacting product quality and quantity.

#AI #Agriculture Sector #Agro tech