Agricultural and Biological Research

EfficientNetB0 technique of CNN for disease and health identification of soybean plant

Nitesh Rastogi* and Priya R. Swaminarayan

Recently, there has been a significant accumulation of data focused on predicting and preventing soybean infections. The methodologies and development stages of these approaches differ, but they share a common goal: To improve crop and product management. This study evaluates various models for disease detection and pod counting in soybean plants. Two specific models, CNN and EfficientDet B0, have been developed to identify healthy and diseased leaves and accurately count pods. Tensor flow, a versatile tool for numerical computation, was utilized in this research. It proves particularly useful in controlled farm environments, where it can quickly detect early signs of disease on plant leaves.