SIH26111
Smart Al-Enabled Rapid Feed and Silage Quality Testing System for Dairy Farmers
Metadata & Specs
Department
Department of Animal Husbandry & Dairying
Category
Software
Theme
Agriculture, FoodTech & Rural Development
Deadline
20 September 2026
Submitted ideas
0/500
Problem Description & Statement Details
- Background Animal nutrition directly affects milk production, animal health, reproductive performance, and dairy profitability. Dairy farmers often face challenges due to poor-quality cattle feed,adulterated feed ingredients, fungal contamination, toxin presence, and low-quality silage.Conventional feed testing laboratories are expensive and inaccessible for many rural farmers.There is a need for rapid, portable, affordable, and digitally enabled feed quality assessment systems.Emerging technologies such as Al, loT, spectroscopy, computer vision, and biosensors can help create real-time feed testing and advisory systems for dairy farmers.
- Description Participants are required to develop a rapid digital testing solution capable of:
- Assessing nutritional quality of cattle feed and silage;
- Detecting adulteration and contamination;
- Providing instant farmer advisories and feed recommendations;
- Monitoring feed storage and silage conditions.
The solution may include
- Portable testing devices;
- Smartphone-enabled feed analysis;
- Al-powered nutritional prediction;
- Cloud dashboards;
- QR-based authenticity systems.
The system may detect
- Crude protein
- Moisture
- Fiber
- Energy value
- Mineral deficiencies
- Urea adulteration
- Sand/silica contamination
- Aflatoxins and mycotoxins
- Fungal contamination Silage monitoring may include:
- pH
- Fermentation quality
- Moisture
- Spoilage indicators
- Mould growth
- Expected Solution The expected solution should:
- Provide testing results within minutes;
- Be low-cost and portable;
- Support multilingual farmer interfaces;
- Work offline in rural areas;
- Generate nutritional and storage advisories;
- Enable cloud-based monitoring and traceability.
- Expected technologies
- AI/ML
- loT sensors
- NIR spectroscopy
- Mobile applications
- Computer vision
- Cloud analytics
- Predictive advisory systems
- Insert Table Here*
Similar Problem StatementsSame Theme or Organization
Ministry of Fisheries, Animal Husbandry & Dairying · Software · Deadline 20 September 2026