A Visual Question Answering (VQA) dataset for crop disease diagnosis in smallholder farming contexts, built from the RAIL Crop Disease Dataset.Each image has three QA pairs — identification, action, prevention — grounded in an expert knowledge base and written in conversational farmer-friendly English with Twi translations.

Purpose: Fine-tune vision-language models (e.g., OWL-v2) to serve as AI crop disease assistants… See the full description on the dataset page: https://huggingface.co/datasets/toufiqmusah/GhanaAgricVQA-Dataset.