Bharat in Betastartup field guide
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No. 1340Problem statementAgriculture and food

Smart Al-Enabled Rapid Feed and Silage Quality Testing System for Dairy Farmers

Source

Source summary

The proposed portable feed/silage tester should provide results within minutes, work offline and offer multilingual nutrition/storage advice with cloud traceability. Possible analyses include protein, moisture, fibre, minerals, adulteration, toxins and fermentation/spoilage indicators. AI, NIR, biosensors, computer vision and IoT are possible methods, not proof that one sensor measures every hazard. The saved statement includes a missing table placeholder, and assay capability requires validation.

No. 1035Problem statementAgriculture and food

Smart Irrigation System for Precision Farming

Develop an IoT irrigation module combining soil-moisture sensors and weather information with a farmer-facing mobile app. Provide timely irrigation alerts and recommendations from real-time observations to support scheduling. Reduced water use and improved yield are intended benefits requiring field evaluation.

No. 1041Problem statementAgriculture and food

Rapid colorimetric and artificial intelligence-based methods for determining the microbial quality of raw milk, processed milk, and milk products

Develop a rapid, portable, cost-effective way to assess microbial quality of raw and pasteurised milk faster than the source's stated 4–6-hour MBRT process. For processed dairy products, freshness-indicating packaging is also proposed. Colour-based testing, AI or machine vision are avenues to explore rather than validated methods; the core requirement is practical quality assessment at reception, processing and chilling points.

No. 1075Problem statementAgriculture and food

Drone-Based Intelligent System for Apple Orchard Management in Himachal Pradesh

Develop drone-based apple-orchard management for Himachal Pradesh. Combine multispectral/thermal observations and AI analysis for tree health, moisture and stress, with targeted nutrient/pest/disease treatment and prediction using historical/environmental data. Estimate production from blossom/fruit imagery and pre-harvest surveys to support storage, logistics and marketing. Include farmer training, drone-footage virtual tours and promotional content; the source also proposes blockchain traceability covering origin, quality and the apples’ journey.