Agriculture is essential for the survival of human civilization.  It plays an important role in the economic sector and several other industries also depend on agriculture for raw materials like cotton, and rubber. Working in the Agriculture research field I surveyed and visited several farms I closely watched the challenges they faced in farms. In this article, I will cover how Artificial Intelligence technologies help to improve crop yield, pest control, monitoring in soil, and crop growth, organize data for farmers, and assist with the workload, and a wide range of agriculture-related tasks in the whole food supply chain. AI is currently part of developing sustainable agriculture in the globally changing environmental conditions. 

Artificial Intelligence for spraying chemicals

Daily Farms generate data on soil, usage of water, weather condition, pest, diseases, etc. With the support of artificial intelligence and machine learning models, this data is leveraged in real-time for gaining valuable perceptions like selecting the precise time to sow seeds, defining crop selections, and hybrid seed selections to produce more quality yields.

AI technology can detect diseases in plants, pests, and poor nutrition in farms. AI sensors can identify and mark weeds and then select 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 images and artificial intelligence to monitor and precisely spray on weeds. These intelligent AI sprayers can hugely decrease the number of chemicals used in the fields and thus improve the quality of agricultural produce, and bring in cost efficiency.



Artificial Intelligence -based robots for agriculture practices and reduce dependence on manpower

 

In India, most of the agriculture practices are still done by laborers, lack of skilled labor makes the difficulty for to farmers do agricultural work in a timely. AI has the capacity to reduce the requirement for labor in farming.

AI-based machines are very useful that are capable of doing bulk harvesting with more accuracy and speed are responsible for getting the harvest 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 refining agricultural productivities. There are products like a self-sufficient strawberry-picking machine and a vacuum apparatus that can harvest matured apples from trees. These machineries uses sensor fusion, machine vision, and artificial intelligence models to identify the location of the harvestable produce and help pick the matured and sellable fruits. AI-based robots help in sowing, irrigation, harvest, and other agriculture practices and reduce the dependency on high cost and unavailability of manpower in the agriculture sector.



Artificial Intelligence for Forecasting and recommending the best time to sow and application of fertilizer

The modification between a profitable year and a failed harvest is just the well-timed information on a simple data point of the timing of sowing the seed. The Intelligent Agricultural Systems Advisory Tool (ISAT), developed by a collaboration of Microsoft, the Indian Meteorological Department (IMD), Acharya NG Ranga Agricultural University (ANGRAU), and ICRISAT, provides concise farm advisories to farmers on their phones. These messages are generated after analysis of local and global historical climate data, current and forecasted weather conditions, crop systems, and soil-related information. Use a predictive analytics tool to attain at an exact date for sowing the seeds to obtain the maximum yield.

Artificial Intelligence for Crop yield estimates, Market demand and supply evaluations

Another big challenge for farmers is the price instability of the crop and getting a good price for their produce. Due to unsteady prices, farmers are never capable to plot a final production pattern. This problem is highly prevalent in crops like tomatoes and leafy vegetables that have very limited shelf time. Companies are using satellite images, 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 identify pest and disease infestations, estimate tomato output and yield, and forecast prices. They can guide the farmers and governments on future price patterns, demand level, type of crop to sow for maximum benefit, pesticide usage, etc.

Market price analysis

Currently, every city in India has a ‘Market Yard’, which is a wholesale market for agricultural produce. This market yard publishes everyday data for the price of farm produce. AI can use this data for the selection of crops and supply to which market is best to get a better price for harvest than others.

Artificial Intelligence for Pest prediction

Pests are one of the important enemies of the farmers which damage crops. AI systems use satellite images and compare them with historical data using AI algorithms and detect if any insect has landed and which type of insect has landed like the locust, grasshopper, etc. And send alerts to farmers on their smartphones so that farmers can take mandatory precautions and use essential pest control. Several farmers are not able to detect which type of pesticide is best for pest control, AI helps in selecting the pesticide by analyzing previous data. Currently, in the market several types of chemicals are available but it confuses the farmers, AI can be useful in resolving this problem.

Artificial intelligence is today’s agricultural need in the global changing environmental conditions that are increasing challenges in farming. AI-based technology can resolve problems and reduce the burden on farmers. In India, most of the farmers are small landholders so technologies should be affordable and adaptable for small farming lands.