GeoAI-Driven Crop Yield Prediction
Manually Counting Wheat Heads to Predict Wheat Yield
Problem Statement: Early, accurate estimation of crop yield can help farmers to plan harvest management, storage requirements, capital management, delivery estimates, and crop insurance assessments. However, crop yield prediction is extremely challenging. For farmers and growers, wheat yield estimation is often performed by randomly selecting and manually counting the number of harvestable heads from a specific length (e.g., 3 or 5 ft) of plant row in various locations around a field. By counting kernels on heads, determining the distance between rows and applying each measure to a formula, an approximate yield can be calculated. This method often has higher accuracy and lower cost than the crop yield prediction model, but is significantly time-consuming and unreliable due to subjective assessments.