Prediction of oil yield in sunflower using deep learning regression algorithm under normal and drought stress conditions

Key Points

• Oil yield predictions demonstrate an accuracy of 85% under both normal and drought conditions, emphasizing the model's reliability.
• Feature importance analysis reveals water availability as a crucial factor affecting oil yield during drought.
• Analysis using a deep learning regression algorithm showcases comprehensive predictions across varying stress conditions.
• This highlights the potential of machine learning methods to enhance agricultural production, especially in changing climates.