Evaluador inteligente de daño fenológico en la planta de trigo.

Climate Change on the planet has affected the world wheat production and forecasts ensure that these changes and effects will be greater over time. Considering the importance of this cereal as a basic diet of human beings, this work proposes a new form of crop evaluation that allows to forecast probable damage by phenological stage, through an Artificial Neural Network trained with historical data of global climatic behavior and phenological impact. A results system interprets the output and constitutes the user interface. The proposal was validated, showed its generalization capacity and reached high precision of 84%, so it is considered adequate. [ABSTRACT FROM AUTHOR]