The article "Artificial Intelligence: A Promising Tool for Application in Phytopathology" in Horticulturae, by Victoria E. González-Rodríguez et al., discusses the transformative role of AI in plant disease management and phytopathological research. It explores current applications and future directions of AI in agriculture, emphasizing its capabilities in disease detection and diagnosis through image recognition, surpassing human visual assessment. Additionally, forecasting models incorporating weather, soil, and crop data enable preventive interventions by predicting spatial-temporal outbreak risks accurately, reducing pesticide use. Precision agriculture powered by AI enhances data-driven, specific crop protection strategies, improving resilience. This approach underlines AI's efficiency in uncovering disease patterns in complex agricultural data, showcasing its potential to revolutionize decision-making, disease prevention, and precision management in the field.
Download here: The article "Artificial Intelligence: A Promising Tool for Application in Phytopathology" in Horticulturae, by Victoria E. González-Rodríguez et al., discusses the transformative role of AI in plant disease management and phytopathological research. It explores current applications and future directions of AI in agriculture, emphasizing its capabilities in disease detection and diagnosis through image recognition, surpassing human visual assessment. Additionally, forecasting models incorporating weather, soil, and crop data enable preventive interventions by predicting spatial-temporal outbreak risks accurately, reducing pesticide use. Precision agriculture powered by AI enhances data-driven, specific crop protection strategies, improving resilience. This approach underlines AI's efficiency in uncovering disease patterns in complex agricultural data, showcasing its potential to revolutionize decision-making, disease prevention, and precision management in the field. The article "Artificial Intelligence: A Promising Tool for Application in Phytopathology" in Horticulturae, by Victoria E. González-Rodríguez et al., discusses the transformative role of AI in plant disease management and phytopathological research. It explores current applications and future directions of AI in agriculture, emphasizing its capabilities in disease detection and diagnosis through image recognition, surpassing human visual assessment. Additionally, forecasting models incorporating weather, soil, and crop data enable preventive interventions by predicting spatial-temporal outbreak risks accurately, reducing pesticide use. Precision agriculture powered by AI enhances data-driven, specific crop protection strategies, improving resilience. This approach underlines AI's efficiency in uncovering disease patterns in complex agricultural data, showcasing its potential to revolutionize decision-making, disease prevention, and precision management in the field.