Turmeric plant disease prediction using hybrid deep learning-based feature extraction and classification models

Abstract For many farmers, particularly in areas like Tamil Nadu and Andhra Pradesh, turmeric is more than just a crop; it is a crucial source of revenue. Turmeric farming is important to rural economies because of its strong demand in international markets and reputation for medicinal benefits. However, the crop is susceptible to a number of diseases, particularly those that impact the rhizomes and leaves. These problems frequently go undetected until they have seriously harmed the crop, which lowers yield and quality. Farmers have historically relied on visual inspection and professional advice, but this approach can be unreliable and time-consuming, especially on large farms. The proposed work addresses this by presenting a hybrid deep learning-based disease prediction system that examines turmeric plant photos in order to identify problems early. The dataset contains both healthy samples and seven disease categories, including rhizome disease, leaf blotch, dry leaves, and aphid-infected leaves. This aids in the system’s ability to differentiate between various issues and recommend prompt solutions. The system can reduce the use of pesticides, protect yields, and minimize losses by providing farmers with early warnings. Turmeric farming can become more productive and sustainable with improved diagnostic and intervention tools. Numerous tests have demonstrated the accuracy and usefulness of this method, making it a viable option for practical application. The suggested approach achieves high classification performance, indicating its potential to support precision agriculture practices, according to extensive testing and evaluation. The system intends to boost turmeric crop productivity by facilitating early disease detection, which will enable farmers, agronomists, and other agricultural stakeholders to make well-informed decisions, implement prompt interventions, and so on. By minimizing crop losses, making the best use of inputs, and enhancing the general resilience and health of turmeric plantations, this method promotes sustainable farming.