Bharat in Betastartup field guide
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No. 1264Problem statementAgriculture and food

Quality assessment and grading of onions are often subjective and vary across procurement centers, resulting in disputes and inconsistencies.

Source

Source summary

The source asks for an AI mobile application that grades onions from images, identifies rot, damage, sprouting and undersized produce, estimates Grade A and URS proportions and creates an immediate quality report. It addresses inconsistent procurement-centre assessment; the short capture does not define the grade thresholds or validation dataset.

No. 1098Problem statementAgriculture and food

Mobile App for Direct Market Access for Farmers

Build a mobile marketplace connecting farmers directly with consumers and retailers. Let farmers list produce, negotiate prices and manage transactions through a simple interface. Reduced reliance on intermediaries and improved earnings are intended benefits, not established demand or income outcomes.

No. 1099Problem statementAgriculture and food

AI-Driven Crop Disease Prediction and Management System

Build mobile and web crop-disease prediction and management using crop images plus environmental data. Apply machine learning to identify possible diseases or outbreak risk and provide farmers with preventive and treatment guidance based on timely inputs. The source proposes decision support; diagnostic accuracy and loss reduction remain to be validated.

No. 1100Problem statementAgriculture and food

Sustainable Fertilizer Usage Optimizer for Higher Yield

Create an application recommending fertiliser types and quantities from soil-health information, crop choice and weather patterns. The source seeks more appropriate use to address soil degradation while supporting yield and income; it does not prescribe a specific model or establish that its recommendations will improve either outcome.