10 Use Cases of AI in the Agriculture Industry

If you're wondering how artificial intelligence may help solve global food crises and other agricultural issues, this blog is for you!

While food production is enough to support the world's population, almost one billion people continue to suffer from hunger and malnutrition as a result of food waste, climate change, and other causes.

With the world's population expected to reach 9. 7 billion by 2050, pressure is rising on the agriculture industry to produce more food while utilizing fewer resources and decreasing its environmental impact.

The good news is that integrating AI into agriculture has the potential to change food production and contribute to solving the global food issue.

AI-powered software can analyze data from multiple sources and help farmers make data-driven decisions, optimize resource usage, and reduce environmental impact.

According to the World Economic Forum, AI in agriculture could bring about a 60% decrease in pesticide usage and a 50% reduction in water usage.

This article will delve into how AI is used in the agriculture sector, from predicting crop yields to improving soil health, and how it can pave the way for a more sustainable and food-secure future.

What is AI in Agriculture?

AI in agriculture, sometimes called precision agriculture, is the use of artificial intelligence (AI) technologies in the agricultural industry.

The technique is used for field harvesting, health monitoring, weed and pest management, nutrient deficiency diagnosis in soil, and other applications.

The most recent market numbers show that businesses are interested in investigating and developing AI solutions for agricultural applications.

The overall value of artificial intelligence in the global agriculture market was estimated to be around 1.7 billion U.S. dollars in 2023 and is expected to grow to about 4.7 billion U.S. dollars by 2028.

Challenges That Farmers Face With Traditional Methods in Farming

Agriculture has been an integral part of our society for centuries, offering the necessary sustenance to the human population. However, with traditional farming techniques, farmers have faced challenges in recent years, some of them are:

» limited irrigation

» Soil degradation

» Variables that can't be controlled

» Pest and disease outbreaks

» Labor shortages

» Lack of access to markets

AI can mitigate many of these challenges, leading to better harvesting increased efficiency, and enhanced economic stability for farmers worldwide.

Recommended Read: 20 Best Agriculture Business Ideas To Use in India

How Artificial Intelligence Can Be Used in Agriculture?

There are many ways of leveraging AI in agriculture to enhance efficiency and productivity. Here are a few of the primary use cases of AI in the farming industry:

Analyzing Market Demand

Analyzing market demand is an important part of modern agriculture. AI can assist farmers in choosing the best crop to grow or sell. Descartes Labs is a New Mexico-based firm that provides an AI-powered platform to help farmers assess market demand.

The startup creates machine learning algorithms to analyze satellite photos and weather data, delivering vital insights on the ideal planting periods and crops to cultivate.

These types of firms can help forecast market demand for specific crops and assist farmers in increasing revenues by analyzing data patterns.

Managing Risk

Another key use case of AI in agriculture is risk management. Farmers can reduce their crop failure risk by using forecasting and predictive analytics.

For example, Intello Labs is a firm in India that employs artificial intelligence (AI) to assist farmers in analyzing the quality of their crops and reducing food waste.

The company creates AI applications that employ computer vision algorithms to analyze fruits and vegetables and provide information on quality, ripeness, and size.

These AI systems can also detect faults and diseases in crops, allowing farmers to take preventive steps before the crops are damaged.

Breeding Seeds

By gathering data on plant growth, AI can assist in the production of crops that are less susceptible to disease and better adaptable to environmental conditions.

Scientists can make use of AI in agriculture to select the best-performing plant kinds and crossbreed them into even superior hybrids. Yes, hybridization has been employed in agriculture for many years.

However, obtaining genetic information from seeds using AI technologies such as Seed-X can help accelerate the process and boost the likelihood of success.

Must Read: How Artificial Intelligence Can Be Used in the Finance Sector

Monitoring Soil Health

AI in agriculture can perform chemical soil studies and accurately predict lacking nutrients. Agrocares, a Dutch agritech startup, has developed AI-powered software.

One of its products, the Nutrient Scanner, takes data from soil samples and gives farmers precise estimates of missing nutrients and general soil health.

This enables farmers to adapt their fertilizer and irrigation operations to achieve optimal crop growth while minimizing environmental impact.

AgroCares also provides farmers with customized soil management recommendations, assisting them in maintaining the health of their soil over time.

Protecting Crops

When it comes to the role of AI in agriculture, the technology can monitor plant health to detect and anticipate illnesses, identify and eradicate weeds, and offer effective pest treatments.

Taranis, for example, is a precision agriculture firm that utilizes computer vision and machine learning to analyze high-resolution crop photos, delivering plant insights to detect stress or illness.

Their AI-powered solutions are highly accurate at detecting and classifying diseases and pests. It can also recommend the most efficient pest treatment, eliminating the need for broad-spectrum pesticides, which can kill beneficial insects and cause chemical resistance.

Observing Crop Maturity

Estimating crop growth and maturity is a time-consuming and difficult process for farmers, but using AI in agriculture farmers can do it quickly and accurately.

Farmers can identify and track crop changes using AI-powered software, such as sensors and image recognition tools, to make precise forecasts about when crops will mature.

According to studies, employing AI and farming to anticipate crop maturity yielded a greater accuracy rate than that of human observers. Increased precision can result in significant cost savings and higher earnings for farmers.

Also Read: What are Some Ethical Considerations When Using Generative AI?

Soil Monitoring

One of the key uses of AI in agriculture is soil monitoring. Farmers can correctly monitor how much water and nutrients are available in the soil by integrating sensors and artificial intelligence technologies.

Using sensors in soil monitoring could entail deploying equipment that assesses soil moisture, temperature, pH levels, and nutrient content.

These sensors feed data back to AI systems, which then analyze it and advise farmers on how to best manage their crops based on what they learn about soil conditions.

For example, the AI system may detect portions of the field where the soil is too dry or too moist and make recommendations on when and how much water to apply to maximize crop growth.

Similarly, the AI software may detect nutrient deficits in the soil and advise on the most appropriate types and amounts of fertilizer to use to increase yields.

Insect and Plant Disease Detection

Farmers can utilize AI in agriculture to detect insects and plant illnesses faster than people.

For example, an AI-powered device may identify an aphid infestation on a strawberry crop, send the data to the farmer's mobile phone, and then recommend the next course of action.

If a pesticide application is required, the system may even automate it using a connected sprayer.

Intelligent Spraying

Weed and pest control can be automated using AI for agriculture. Weeding robotics using computer vision is supposed to be astonishingly exact, leading to a 90% reduction in pesticide usage.

These solutions use data analytics to compute how much pesticide is required for each field depending on its history, soil status, and crop type.

Blue River Technology's flagship product, the "See and Spray" machine, has transformed traditional weed management methods.

The device uses computer vision and machine learning to distinguish between crops and weeds and then applies pesticides only where necessary. This could be cost-effective.

Chatbots for Farmers

Chatbots can be used to connect farmers with their consumers or distributors. Farmers can utilize conversational agents to answer questions about products or services, purchase supplies, and monitor inventory levels.

Moreover, the AI Chatbot can also help manage databases of agricultural and soil information. They operate as virtual farm assistants, carrying out farm activities.

Read Next: Which Business Case is Better Solved by Artificial Intelligence?

Future of AI in Agriculture

Artificial intelligence (AI) in agriculture is set to grow significantly in the upcoming years, as it has the potential to change the sector by enhancing crop production, reducing waste, and increasing efficiency.

One of the key benefits of AI in the agriculture market is collecting and analyzing large amounts of data.

Farmers can use this to make more informed decision-making and improve crop yields, essential for addressing the global food security challenge.

Moreover, AI can also be used to monitor soil conditions, crop growth, and climate changes. As a result, they will be able to spot diseases early and take the necessary preventive measures before a crop is destroyed.

AI for agriculture will also continue to help farmers foresee weather changes, allowing them to better plan their activities and take advantage of the best planting season.

While AI has significant benefits in agriculture, most farmers globally, particularly smallholder farmers, lack the resources to deploy these technologies.

Smallholder farmers often have little access to technical knowledge, making it difficult for them to properly use AI systems. Many people lack the financial resources to buy the equipment and software required for AI-based farming.

The use of AI in agriculture must be inclusive, taking into account the requirements and limits of smallholder farmers, who account for a sizable share of the worldwide agricultural workforce.

Initiatives that offer access to training and funding for these farmers to implement AI-based farming practices can help bridge the gap.

With this, farmers at all levels can take advantage of emerging technologies that the world needs to secure our food systems’s future.

Frequently Asked Questions

Q. How Artificial Intelligence can be used in Agriculture?

Ans. AI can be used in agriculture for various tasks like predicting crop yields, monitoring soil health, detecting pests and diseases, optimizing irrigation, and automating processes like harvesting.

Q. What are the benefits of artificial intelligence in agriculture?

Ans. AI can increase efficiency, reduce costs, improve yields, and make farming more sustainable by optimizing resource usage and minimizing environmental impact.

Q. How will AI replace farmers?

Ans. AI is not intended to replace farmers but to assist them in their tasks. It can automate repetitive and time-consuming tasks, freeing up farmers to focus on more strategic aspects of their work.

Q. When was AI first used in agriculture?

Ans. The early applications of AI in agriculture can be traced back to the 1980s, but its widespread adoption and integration into farming practices have become more prevalent in recent years.

Q. What are the disadvantages of AI in agriculture?

Ans. Some disadvantages of AI in agriculture include the high initial cost of implementation, the need for specialized expertise, and potential issues related to data privacy and security.