AI in Agriculture: Traditional Farming Challenges and Way Forward

Agriculture is the mainstay occupation in many countries worldwide. With the rising population, which as per UN projections will increase from 7.5 billion to 9.7 billion in 2050, the food demand is projected to increase between 35%—56%.

It means the pressure on land will rise and the extra 4% of the land will also come under cultivation by 2050. So, farmers will cultivate more on the existing land to meet the growing demands.

It, thus, lays emphasis on the need for the use of AI in agriculture to improve farming techniques.

Understanding Existing Agriculture Landscape

Weather factors such as Rainfall, temperature, and humidity play an important role. Due to pollution, sometimes the climate varies abruptly. Hence, it becomes difficult for farmers to make proper decisions for harvesting, sowing seeds, and soil preparation.

For a better crop, it is necessary that the soil should be productive. It must have the required nutrition, such as Nitrogen, Phosphorous, and Potassium. If these nutrients are not present in an effective way in the soil, then it may lead to poor-quality crops. But it is difficult to identify the soil quality in traditional ways.

In the agriculture life cycle, it is required that we save our crops from weeds. Else it may increase the production cost, and it also absorbs nutrients from the soil. But traditional ways don’t have an efficient way for the identification and prevention of crops from weeds.

To solve these issues, farmers leverage newer technologies like AI, machine learning and deep learning. It helps them leverage advanced technology for crop monitoring, soil assessment, disease detection, predictive analytics, etc.

As per Forbes’s report, global spending on “smart” agriculture, including AI and machine learning, will triple to $15.3 billion by 2025. Also, research suggests that the market size of AI in agriculture should expect a compound annual growth rate (CAGR) of 20%, reaching $2.5 billion by 2026.

What is AI?

Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence.

While AI is an interdisciplinary science with multiple approaches, advancements in machine learning and deep learning, in particular, are creating a paradigm shift in virtually every industry.

What is AI in Agriculture?

Artificial intelligence in agriculture refers to the use of AI to improve traditional farming. It aims to transform the agriculture industry by helping farmers get the most out of their efforts.

Using AI, farmers can increase crop yields, improve sustainability, and reduce costs. Here are a few effective ways in which AI is being used in agriculture:

Weather Forecasting

Due to changes in climate and rising pollution, it’s difficult for farmers to determine the right time for sowing and harvesting. But, with help of Artificial Intelligence, farmers can analyze weather conditions. They can use weather forecasting to plan the type of crop that can be grown and when should seeds be sown.

Precision Agriculture and Predictive Analytics

AI-powered sensors and drones help collect data on crop growth, soil moisture, and nutrient levels. Machine learning models use this data to generate insights that help farmers make more informed decisions. For example, it allows farmers to determine when and where to irrigate, fertilize, and apply pesticides. This can result in higher yields and more efficient resource use.

Crop Monitoring

AI algorithms can analyze satellite and drone imagery for effective crop monitoring. They can examine and identify issues that might otherwise go unnoticed by the naked eye. For example, they can detect signs of stress or disease in crops, allowing farmers to address potential problems before they become widespread.

Harvest Forecasting

Machine learning algorithms can analyze historical weather patterns, soil quality, and other factors to predict crop yields and harvest times. Thus AI can help farmers plan their operations more effectively.

Livestock Management

AI-powered sensors can monitor the health and behavior of livestock. In case of an abnormal situation, the system can alert farmers to potential health problems. Thus, helping them to improve breeding and production outcomes.

Food Safety

AI can identify potential contaminants and pathogens in food products. Thus they can help ensure that the food we eat is safe and healthy.

Agricultural Robotics

AI companies are developing robots that can easily perform multiple tasks in farming fields. These robots are designed to perform specific tasks. For example, they can control weeds or harvest crops at a faster pace with higher volumes compared to humans. Thus, they help fight with challenges faced by agricultural force labor.

Pest Detection

Pests are one of the worst enemies of the farmers which damage crops. AI systems use satellite images and compare them with historical data to detect if any insect has landed. They also identify which type of insect has landed like the locust, grasshopper, etc.

Accordingly, they send alerts to farmers on their smartphones. Farmers can then take required precautions and use required pest control to fight against pests.

By providing farmers with more precise and data-driven insights, AI is revolutionizing agriculture.

Challenges in Adopting AI Agriculture Solutions

Lack of familiarity: This is due to people not being familiar with AI-enabled solutions. If a basic support system is provided to farmers, this challenge can be resolved.

Lack of experience: Most of the time, farmers have not used agricultural technology before. So, farmers require training or the support of AI-skilled persons

Data Privacy and Security: Accessing and sharing data raises concerns and may lead to legal issues. Further troubles like cyber-attacks and data leaks can cause trouble for the farmers.

Way forward for AI in Agriculture

By using Big Data for informed decision-making, IoT sensors for capturing and analyzing data, and automation and robotics for minimizing manual work, AI will change everything in agriculture.

This reduces the considerable amount of manual effort involved in farming and also improves work efficiency and is comparatively lesser prone to errors.

We are working on a variety of projects in the agriculture domain. If you wish to collaborate or have any ideas for AI in agriculture, feel free to contact us. We would love to hear it from you