Artificial Intelligence in Agriculture: Using Modern Day AI to Solve Traditional Farming Problems

The global population is growing, expected to reach 10 billion by 2050, putting pressure on agriculture to produce more food. Two options to address food shortages have emerged: using more land for large-scale farming or using technology to enhance productivity on existing farmland. Modern agriculture faces limited land, labor shortages, climate change, and soil fertility issues. This has led to various innovative developments in farming. Technology keeps advancing each season to improve efficiency and harvests. Yet, many farmers and agribusinesses miss out on the benefits of artificial intelligence (AI) in agriculture. This article discusses the various applications of AI in the agricultural sector and how it is transforming traditional farming practices.

We’re at beginning of a golden age of AI. Recent advancements have already led to invention that previously lived in the realm of science fiction – and we have only scratched the surface of what’s possible

Jeff Bezos, Amazon CEO

Learning Objectives

• Learn about the various applications of AI technology in farming and crop management.
• Understand how AI helps in increasing agricultural production, and profitability.
• Gain knowledge about AI-powered smart farming techniques that transform traditional agricultural practices.
• Become aware of how the latest technologies such as robotics, drones, computer vision, and process automation are used in the agricultural industry.

This article was published as a part of the Data Science Blogathon.

What is the Role of AI in Agriculture?

AI is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the simplest to those that are even more complex. The goals of AI include learning, reasoning, and perception.

Some examples include vision-recognition systems on self-driving cars, recommendation engines that suggest products you might like based on what you bought in the past, speech and language recognition of the Siri virtual assistant on the Apple iPhone, and more.

AI is making a huge impact in all domains of the industry. Every industry is looking to automate certain jobs through the use of intelligent machinery. And a good online artificial intelligence course is all you need to break into any industry – even agriculture!

Agriculture and farming are one of the oldest and most important professions in the world. It plays an important role in the economic sector. Worldwide, agriculture is a $5 trillion industry.

As the world population is increasing, land, water, and other resources are becoming insufficient to continue the demand-supply chain. So, we need a smarter approach to become more efficient about how we farm and make it most productive.

Lifecycle of Agriculture

We can divide the process of agricultural cultivation into seven different phases: preparation of soil, sowing of seeds, adding fertilizers, irrigation, weed protection, harvesting, and storage of produce.

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 removing debris, such as sticks, rocks, and roots. Herbicides and organic matter (depending on the type of crop) are added in this stage to create an ideal ecosystem for crop growth.

Sowing of Seeds

This stage requires taking care of the distance between two seeds, and the depth for planting seeds. At this stage climatic conditions such as temperature, humidity, and rainfall play an important role. Soil conditions are also checked before sowing to ensure ideal crop growth.

Adding Fertilizers

It is important to maintain soil fertility so the farmer can continue to grow nutritious 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. The correct irrigation systems need to be out in place to ensure the right level of soil moisture.

Weed Protection

Weeds are unwanted plants that grow near crops or at the boundary of farms. Weed protection is important as weeds decrease yields, increase production costs, 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 in Using Traditional Methods of Farming

Here are some of the general challenges that exist in the agricultural domain:

• 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 make decisions to prepare the soil, sow seeds, and harvest.
• 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 crop quality.
• 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 AI 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.

Use of Weather Forecasting

With the change in climatic conditions and increasing pollution, it’s difficult for farmers to determine the right time for sowing seeds. With the help of AI, farmers can analyze weather conditions using weather forecasting which helps them plan the type of crop that can be grown and when the seeds should 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 startup 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 do soil analysis to farmers. Such apps help farmers 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 transfers the data 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 pest control and other methods to take required action.

Precision Agriculture and Predictive Analytics

Agri-based AI startups have developed applications and tools that help farmers with accurate and real-time farming advice. These apps provide them with proper guidance about soil health, water management, pesticide usage, sustainable farming techniques, and nutrition management. They also educate farmers on crop rotation, timely harvesting, the type of crop to be grown, and optimum planting, based on the different cropping seasons.

While using machine learning algorithms in connection with images captured by satellites and drones, AI-enabled technologies predict weather conditions and analyze crop sustainability. They also evaluate farms for the presence of diseases or pests and poor plant nutrition on farms, using 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 and new technologies 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 weeds with picking and packing of crops at the same time. These robots are also capable of fighting the 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 to detect any insect landings and the type of insect landed like the locust, grasshopper, etc. And send alerts to farmers on their smartphones so that farmers can take required precautions and use required pest control thus AI helps farmers to fight against pests.

Conclusion

Artificial intelligence has grown beyond machines and enterprises, to agriculture and maintaining the world’s food system. AI greatly assists farmers in data-driven decision-making and upgrading their farming practices. It guides them to shift to sustainable agriculture and precise cultivation for higher crop yield and better quality while using fewer resources.

Tech companies in the agricultural industry are working on improving AI tools or services that will provide more useful applications to farmers. AI will thus help the world deal with food production issues for the growing population.

Key Takeaways

• AI technology in agriculture helps farmers increase production and profitability through smart farming techniques.
• AI applications in agriculture include weather forecasting, soil and crop health monitoring, and drone-based crop analysis.
• Precision agriculture uses AI for real-time farming advice, improving soil health, water management, and sustainable farming practices.
• AI-enabled agricultural robots can control weeds, harvest crops efficiently, and handle quality control tasks.
• AI systems can detect pests early using satellite images, helping farmers take timely preventive measures.

Frequently Asked Questions