Artificial intelligence technology is supporting different sectors to boost productivity and efficiency. AI solutions are assisting to overcome the traditional challenges in every field. Likewise. AI in agriculture is helping farmers to improve their efficiency and reduce environmental hostile impacts. The agriculture industry strongly and openly embraced AI into their practice to change the overall outcome. AI is shifting the way our food is produced where the agricultural sector’s emissions have decreased by 20%. Adapting AI technology is helping to control and manage any uninvited natural condition.
Today, the majority of startups in agriculture are adapting AI-enabled approach to increase the efficiency of agricultural production. The Market study report stated that the global Artificial Intelligence (AI) in Agriculture market size is expected to reach 1550 million US$ by the end of 2025. Implementing AI-empowered approaches could detect diseases or climate changes sooner and respond smartly. The businesses in agriculture with the help of AI are processing the agricultural data to reduce the adverse outcomes.
Lifecycle of Agriculture
We can divide the Process of Agriculture into different parts:
Preparation of soil: It is the initial stage of farming where farmers prepare the soil for sowing seeds. This process involves breaking large soil clumps and remove debris, such as sticks, rocks, and roots. Also, add fertilizers and organic matter depend on the type of crop to create an ideal situation for crops.
Sowing of seeds: This stage requires taking care of the distance between two seeds, depth for planting seeds. At this stage climatic conditions such as temperature, humidity, and rainfall play an important role.
Adding Fertilizers: To maintain soil fertility is an important factor so the farmer can continue to grow nutritious crops and healthy crops. Farmers turn to fertilizers because these substances contain plant nutrients such as nitrogen, phosphorus, and potassium. Fertilizers are simply planted nutrients applied to agricultural fields to supplement the required elements found naturally in the soil. This stage also determines the quality of the crop
Irrigation: This stage helps to keep the soil moist and maintain humidity. Underwatering or overwatering can hamper the growth of crops and if not done properly it can lead to damaged crops.
Weed protection: Weeds are unwanted plants that grow near crops or at the boundary of farms. Weed protection is important to factor as weed decreases yields, increases production cost, interfere with harvest, and lower crop quality
Harvesting: It is the process of gathering ripe crops from the fields. It requires a lot of laborers for this activity so this is a labor-intensive activity. This stage also includes post-harvest handling such as cleaning, sorting, packing, and cooling.
Storage: This phase of the post-harvest system during which the products are kept in such a way as to guarantee food security other than during periods of agriculture. It also includes packing and transportation of crops.
Challenges faced by farmers by using traditional methods of farming
Listing down general challenges that exist in the agricultural domain.
1. 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 take decisions to prepare the soil, sow seeds, and harvest.
2.Every crop requires specific nutrition in the soil. There are 3 main nutrients nitrogen(N), phosphorous(P) and potassium(K) required in soil. The deficiency of nutrients can lead to poor quality of crops.
3.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.
Applications of Artificial Intelligence 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.
Weather forecasting: With the change in climatic condition 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 is 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.
Similarly, Trace Genomics is another machine learning-based company that helps farmers to do a soil analysis to farmers. Such type of app helps farmers to monitor soil and crop health conditions and produce healthy crops with a higher level of productivity.
Analyzing crop health by drones: SkySqurrel Technologies has brought 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.
This company uses algorithms to analyze the captured images and provide a detailed report containing the current health of the farm. It helps the farmer to identify pests and bacteria helping farmers to timely use of pest control and other methods to take required action
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.
These types of robots are trained to check the quality of crops and detect weed with picking and packing of crops at the same time. These robots are also capable to fight with challenges faced by agricultural force labor.
AI-enabled system to detect pests: Pests are one of the worst enemies of the farmers which damages crops.
AI systems use satellite images and compare them with historical data using AI algorithms and detect that if any insect has landed and which type of insect has landed like the locust, grasshopper, etc. And send alerts to farmers to their smartphones so that farmers can take required precautions and use required pest control thus AI helps farmers to fight against pests.
Artificial Intelligence in agriculture not only helping 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 advancement in the future will provide more useful applications to this sector helping the world deal with food production issues for the growing population.