Advancements in neural network and fuzzy modelling approaches are transforming soil and crop management, offering highly adaptable computational frameworks to address the intricate challenges of ...

Crop yield can be maximized when the best genetic variety and most effective crop management practices are used for cultivation. Scientists have developed various machine learning models to predict ...

This research combines deep learning, visual question answering (VQA), and informed learning to bridge the gap between human-level understanding and machine-driven crop diagnostics. ILCD integrates a ...

Crop nutrition and quality formation are complex processes influenced by genotype, environment, and management practices.

• Background and Aims Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual ...

Agriculture currently accounts for approximately 70% of global freshwater withdrawals. Amid increasing challenges posed by ...