An adapted Weibull function for agricultural applications

The Weibull function is applied extensively in the life sciences and engineering but underused agriculture. was consequently adapted to include parameters metrics that increase its utility for characterizing agricultural processes. included initial final dependent variables (Y 0 Y F, respectively), independent variable (x ), a scale constant (k), shape (c). primary mode, integral average, domain, skewness, kurtosis. Nested within are Mitscherlich Rayleigh functions where c fixed at 1 2, respectively. At least one of three models provided an excellent fit six example datasets, as evidenced by large adjusted coefficient determination (R A 2 ≥ 0.9266), small normalized mean bias error (MBE N ≤ 1.49%), standard regression (SER 8.08%). most probable (P X ) representation corn (Zea mays L.) yield M = 87.2%); soil organic carbon depth profile R 96.4%); seedling emergence W 100%), nitrous oxide emissions nitrogen mineralization 58.4%), water desorption 100%). data also equivalent those well-established van Genuchten Groenevelt–Grant models. It concluded has good potential widespread informative application