Agriculture includes producing food and non-food from forest products, aquaculture, crops, and livestock. The nation’s core industry is agriculture. Agriculture is the origin of both food and livestock. The major contribution of the economy to the nation is agriculture. In this article, you should know about the top 6 applications of artificial intelligence in agriculture. Let’s get started!
It performs a vital role in global trade, including import and export agreements. It offers employment opportunities for both rural agricultural and non-agricultural workers. Agriculture is the main resource for food security, raising wages, and reducing poverty for the 80% population, and it is also the main occupation for the people who mostly live in rural areas.
Adopting effective agricultural technologies to increase productivity on limited land is challenging due to the world’s expanding population and rising food demand.
The usage of artificial intelligence in agriculture is increasing day by day, and AI-powered technologies are developing farming. Agriculture was based on soil nutrients, moisture, crop rotation, rainfall, temperature, and many other factors. Artificial intelligence tools have the features to analyse agricultural productivity. It is also used in developing the agriculture-related functions of the entire food supply chain.
Role Of Artificial Intelligence In Agriculture
1. Weather prediction
Weather plays an important role in farming. Unexpected weather may affect the crops. It affects the farmer’s hard work, profit, and also the country’s economy. So it is important to know about the weather, but we cannot predict the weather like rainfall, temperature, and humidity. Because of pollution, climate may change rapidly, making it difficult for farmers to harvest, plant seeds, and prepare soil. AI provides weather prediction according to the area. The AI will collect all the previous weather information about a particular area and give the present weather prediction. This technology helps farmers estimate the best time for planting, harvesting, and pesticide.
2. Crop and soil monitoring
Soil is the major component of agriculture. The plants and crops grow based on the soil. All soils are not suitable for every crop. There are several types of soils; each soil contains unique nutrients that are helpful for a healthy crop. Soil should have good nutrients and humus for plant growth. Some minor diseases that affect crops are invisible to farmers. Framers can’t monitor the crop and soil every time. AI will help you to monitor and analyse the soil and crop. It gives us details about the nutrients, humus, and moisture levels of the soil. It also gives details about the crop’s health and its growth with the help of drones and sensors. Through crop and soil monitoring through AI, farmers can take preventive steps before it becomes a major problem.
3. Water management
Watering huge crops may be difficult sometimes for farmers. Water capacity may rise or decrease when watering. Farmers find it difficult to stand in the sun while watering. Water management uses artificial intelligence to assess data on weather, soil quality, and crop development to maximize irrigation timings and reduce water wastage. It helps the farmers with water usage and identifies the best time for watering the crop. AI technology gives the details of the best time for watering and how much watering is needed for crops. This technology reduces water waste and helps farmers determine when to water. Some AI tools are available for watering the plants; these are connected like pipes and water the crops whenever the soil requires water.
4. Weed and pest detection
Farmers should always be aware of weeds and pests. This problem should be detected in the beginning, or else it becomes a major problem. This tool has a fixed camera with AI technology to detect the weeds and pests in the crop. This technology is helpful for farmers in reducing pesticide usage by identifying problems before they damage crops. By detecting weeds and past damage, farmers can make decisions on cropping and managing their fields.
5. Accurate farming
Accurate farming indicates the “right place, time, and products.” It is a significantly more reliable and regulated way of doing repetitive tasks than labour-intensive farming. Accurate farming also includes observing stress levels in plants. This can be performed by analysing high-resolution pictures and other data collected by AI technology from plants. The sensor data is subsequently integrated into a machine-learning model for stress recognition.
6. Agriculture Robotics
AI companies are developing robots for agricultural purposes. These robots are designed to do multiple tasks in farming. It reduces the manpower and makes the work more efficient.
- Harvesting: AI-powered robots are used for harvesting. They can harvest the crop efficiently and reduce man-labour. This technology helps the farmer save time. It gives quality work.
- Drones and sensors: These tools are used to analyse information about the crop and soil. Every drone has a camera fixed to it to capture every detail about the crop, plant growth, pest detection, and water management.
Robotics are used for each purpose in agriculture. They are used for harvesting, detecting, and cropping. These robots work faster than humans.
Conclusion
AI technology and AI robots are used in agriculture. These technologies can increase productivity, reduce cost, and optimise crops. AI is used for weather prediction, soil monitoring, crop monitoring, disease detection, pollination, crop forecasting, weed, and pest detection. There are many changes in the agriculture industry with the help of AI. It creates a future of sustainable and efficient agriculture. AI can help farmers by resolving complex issues that humans cannot identify. Developing farming solutions is challenging in the early stages, but farming is evolving. Many countries are implementing AI technology and AI-based farming solutions to reduce human labour, manual labour, and farmer time.
Also Check: Who Is Father of Artificial Intelligence?
