Dataset & code for : "A machine learning approach for estimating forage maize yield and quality in NW Spain"

Data and Code for article: "A machine learning approach for estimating forage maize yield and quality in NW Spain". Code: Jupyter Notebooks for forage maize yields (Dry Matter, Crude Protein and UFL) 📙 Dry Matter forage maize yield predcitions using Machine Learning ensemble methods for NW of Spain 📙 UFL(Plant Lactation Total Energy) forage maize yield predcitions using Machine Learning ensemble methods for NW of Spain 📙 Crude Protein forage maize yield predcitions using Machine Learning ensemble methods for NW of Spain 📙 Dry Matter forage maize yield predcitions using Machine Learning ensemble methods and Bootstrapping for NW of Spain Dataset: (MS Excel File) The data file contains 1449 data for forage maize production covering 23 years from 2000 to 2022 and corresponds to 7 locations in NW of Spain (Grado, Barcia and Villaviciosa) in Asturias and (Ordes, Ribadeo, Sarria and Deza) in Galicia region. The production variables are: kg DM/ha, kilograms of Dry Matter by hectar UFL / ha, Unit of Forage milk by hectar kg CP / ha, kilograms of Crude Protein by hectar The input variables are 14: Location Year Cultivar Sowing date(Julian day) Elevation (m) WHC(mm) C(%) pH Tmax(ºC) Tmin(ºC) Radiation(MJ/m2 day) Precipitation(mm) Anthesis date(Julian day) Harvest date(Julian day)