AI in Agriculture: Prospects vs Challenges

June 30, 2021

Artificial Intelligence (AI) is making tremendous strides in various industries, and agriculture is no exception. AI can make a significant impact on the agriculture industry by helping farmers increase their productivity, save resources, and efficiently manage their operations. However, with these benefits also come some challenges that need to be addressed.

Prospects of AI in Agriculture

Precision Farming

Precision farming is a farming management concept that uses modern technologies such as AI, IoT, and big data analytics to optimize crop yield and reduce waste. By using drones or other autonomous vehicles, farmers can collect data on the health status of crops, soil moisture, and nutrient levels, which can be used to make informed decisions. For example, this data can be used to determine the optimal planting time or to apply precise amounts of nutrients to crops.

A study conducted by MarketsandMarkets estimated that the precision farming market would reach $12.9 billion by 2027, growing at a CAGR of 12.7% between 2020 and 2027.

Disease and Pest Detection

Detecting crop diseases and pests early can be challenging, especially when it comes to large-scale farming. However, with AI-powered tools, farmers can detect the early signs of diseases or pests and take appropriate measures. AI algorithms can analyze images or other data collected from crops using drones or cameras, detecting potential diseases or pest damage.

A report by Meticulous Research suggests that the use of AI in agriculture for disease detection would grow at a CAGR of 24.6% between 2021 and 2028.

Farm Management and Planning

AI-powered farm planning tools can help farmers make informed decisions and optimize their operations. Farmers can use data-driven insights to manage their land, stock, and finances. By predicting market conditions and estimating crop yields, farmers can decide on the type of crops and the best time to plant or harvest.

According to ResearchandMarkets, the AI in agriculture market is expected to grow from $518.7 million in 2019 to $2.6 billion by 2025, at a CAGR of 25.5% between 2020-2025.

Challenges of AI in Agriculture

Data Management

AI systems require large amounts of data to make accurate predictions and recommendations. As a result, farmers must ensure that they collect and store data reliably and securely. In addition, they must also ensure that they have the necessary infrastructure to support data storage and processing.

Affordability

While AI has many benefits, it can be costly to implement, especially for small-scale farmers. The cost of acquiring AI-powered tools, such as drones or autonomous vehicles, can be significant, making it difficult for small-scale farmers to take advantage of these technologies. Besides, farmers may also need to invest in training and hiring personnel to operate these systems.

Reliance on Technology

While AI can provide significant benefits, farmers should not entirely rely on it. Human intuition and expertise are still essential in agriculture. Farmers should use AI-powered tools as aids to their decision-making processes and not depend on them entirely.

Conclusion

In conclusion, AI can offer many benefits to the agriculture industry. It can improve farming practices, increase productivity, and reduce costs. However, there are many challenges to implementing AI in agriculture, such as data management, affordability, and overreliance on technology. As the technology becomes more accessible, addressing these challenges will become increasingly critical.

References

  • MarketsandMarkets. (2020, August). Precision Farming Market by Technology (GSS, Telematics, VRT, Remote Sensing), Offering (Hardware-Sensing & Monitoring Devices, Software, Services), Application, Farm Size, Farmer's Type, Region - Global Forecast to 2025.
  • Meticulous Research. (2021, May). Artificial Intelligence in Agriculture Market by Type (Machine Learning, Computer Vision, Predictive Analytics), Offering, Technology (Sensors, Robotics, Drones), Application, Deployment Mode, Organization Size, and Geography - Global Forecast to 2028.
  • ResearchandMarkets. (2020, July). AI in Agriculture Market - Growth, Trends, and Forecasts (2020-2025).

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