Agriculture ยท GS3
AI projects in agriculture
One line
The Agriculture Ministry reported AI projects for pest surveillance, weather advice, crop identification, insurance, scheme delivery, and governance analytics.
Summary
The release described the National Pest Surveillance System as using AI and machine learning to identify pest problems from images. It also reported BharatVistaar serving farmers with location-specific advice. The value lies in early information and targeted extension, but wrong advice can cause crop or financial loss.
PYQ pattern
UPSC agriculture questions often test technology through its effect on productivity, risk, markets, and inclusion. Use the official UPSC archive.
Core notes
- Image-based pest models need representative training data and local validation across crops, varieties, lighting, and disease stages.
- Weather advisories are useful when they are timely, location-specific, and connected to an action a farmer can take.
- AI can help scheme delivery and insurance assessment, but automated decisions need explanation, appeal, and human review.
- The release reported use by extension workers and farmers. Usage is not the same as measured yield improvement.
Prelims lens
- AI and machine learning are tools within the Digital Agriculture Mission context.
- Pest identification is different from pest control. A prediction must still lead to a suitable intervention.
- A model trained in one crop or region may not generalise to another.
MCQ 1
The National Pest Surveillance System uses AI or machine learning to:
- A. help detect pest infestation from crop images
- B. replace all agricultural universities
- C. issue currency notes
- D. measure ocean salinity only
Reveal answerHide answer
A
PIB described image-based pest identification as one use of the system.
MCQ 2
Consider the following statements:
- AI-based advice can be useful without any local validation.
- Human review and an appeal route are relevant when AI affects insurance or benefits.
- A. 1 only
- B. 2 only
- C. Both 1 and 2
- D. Neither 1 nor 2
Reveal answerHide answer
B
Agricultural conditions vary, so local validation matters. Automated decisions affecting entitlements need accountability and correction.
Mains
Question, 10 marks, 150 words: Assess the role of artificial intelligence in making Indian agriculture more resilient and productive.
Approach:
- Explain pest surveillance, weather advice, crop identification, insurance, and scheme delivery.
- Discuss early warning, lower information costs, multilingual extension, and targeting.
- Examine data bias, wrong diagnosis, connectivity, privacy, liability, and exclusion.
- Recommend human-in-the-loop systems, local validation, open evaluation, farmer consent, and offline access.