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How AI Can Help Agriculture Overcome Its Biggest Challenges

Context

The introduction of technology has led to a paradigm shift in how farmers cultivate their crops, advancing the agriculture sector. People must become more effective in boosting their productivity and farm yield as the world population continues to grow quickly and land becomes more scarce.

Relevance:

GS Paper-3: Science and Technology- Developments and their Applications and Effects in Everyday Life

Mains Question

How can artificial intelligence (AI) technologies help the agriculture sector overcome the most challenging hurdles in the sector? Discuss


AI’s potential in agriculture

  • The UN Food and Agriculture Estimate states that the global agricultural yield must increase by 70% by 2050 in order to feed the world’s growing population.
    • The $5 trillion global agriculture industry is moving toward artificial intelligence (AI) technologies to help farmers meet the rising demand for food.
    • By enhancing a variety of agriculture-related tasks crucial to the food chain, this aids farmers in adopting market-specific solutions for innovation, growth, and impact.

Agricultural industry implications of artificial intelligence (AI):

  • Analyzing farm data: Traditionally, farmers had to perform a wide range of manual tasks, such as pest control, soil monitoring, weather forecasting, etc.
    • Farmers found it difficult to daily analyse data points collected on the ground before AI integration.
    • Using AI has made it simpler to predict a variety of real-time factors, including weather, temperature, water usage, and soil conditions.
  • In order to produce more abundant yields, for example, AI empowers farmers to make better farming decisions at the planning stage.
  • Precision agriculture
    • Precision agriculture is made possible by AI-based technologies, which raises the standard and precision of farming. Data is analysed using artificial intelligence (AI) technology to find pests, diseased plants, and undernourished crops.
  • Identifying weeds and toxins: The sensors are essential for identifying weeds, pinpointing them, and selecting the best herbicides to use. This prevents the buildup of excess toxins and leads to the production of nutritious food.
  • Improved forecasting: Predictive models powered by AI assist farmers in predicting important factors affecting yield productivity. These models forecast future weather patterns to help farmers make decisions and achieve agricultural precision.
    • Seasonal and weather forecasting are essential in farming, especially on small farms where there is a lack of information and expertise and where farmers cannot afford to waste money on guesswork or experiments.
    • Small farms generate income for the majority of farmers and contribute to the agricultural economy. As a result, AI implementation is required to keep such farms running.
  • Monitoring: In addition, AI helps farmers keep a closer eye on their fields than ever before.
    • Farmers can more effectively monitor their fields in real-time with the data collected by drones flying over them.
    • Farmers can quickly identify problematic areas in bigger fields that are hard to monitor by humans using drone cameras with AI capabilities.

Combating labour shortages:

  • Automation: Agriculture, which traditionally required seasonal workers to harvest crops and maintain farms, is a labor-intensive activity.
  • Farmers are having trouble finding workers to maintain and increase the output of their farms as more people migrate from rural to urban areas.
  • Agriculture is not exempt from the automation that AI technology is bringing to every industry; it is also not immune from its willingness to assist farmers.
    • AI bots can be used in a variety of ways, such as to locate trouble spots in the field and harvest crops at a higher rate.
  • Information dissemination: Farmers can get technical support from AI chatbots. Numerous agritech start-ups are making efforts to give farmers the technical know-how of contemporary farming techniques.
    • As a result, they support farmers by providing answers to their questions as well as suggestions and advice.
  • Cost effectiveness: Farmers can become more cost-effective by using technology.
    • Automation has replaced a number of tedious and time-consuming human-oriented tasks.
  • Reducing labour and labour costs: Farmers can monitor their crops more precisely by doing away with tedious tasks, minimising mistakes, and lowering labour costs.
    • As a result, farmers can still increase yield productivity and efficiency while still supplying the world’s rising food demand.

Conclusion:

There will always be a fundamental need for food production. In fact, it will rise in response to the needs of the expanding population. Fortunately, AI will make it easier and less expensive for farmers to manage larger farms. They can produce food more productively with cognitive technologies.


February 2023
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