Visible Near-Infrared Spectroscopy and Pedotransfer Function Well Predict Soil Sorption Coefficient of Glyphosate

The soil sorption coefficient (Kd) of glyphosate mainly controls its transport and fate in the environment. Laboratory-based analysis Kd is laborious expensive. This study aimed to test feasibility visible near-infrared spectroscopy (vis–NIRS) as an alternative method for estimation at a country scale compare accuracy against pedotransfer function (PTF). A total 439 soils with wide range values (37–2409 L kg−1) were collected from Denmark (DK) southwest Greenland (GR). Two modeling scenarios considered predict Kd: combined model developed on DK GR samples individual models either or samples. Partial least squares regression (PLSR) artificial neural network (ANN) techniques applied develop vis–NIRS models. Results best technique validated using prediction set compared PTF each scenario. PTFs built texture, OC, pH, Feox, Pox. ratio performance interquartile distance (RPIQ) was 1.88, 1.70, 1.50 (ANN), validation models, respectively. obtained higher predictive ability than dataset, whereas resulted slightly better estimations However, differences between statistically insignificant. Considering multiple advantages vis–NIRS, e.g., being rapid non-destructive, it can provide faster easier estimating Kd.