Obtaining reference values for nutrients in vineyard soils through boundary line approach using Bayesian segmented quantile regression on commercial farm data

Inefficient use of fertilizers in agriculture is a major issue in global food production as it hampers economic viability of farms and offers great risk of environmental pollution. Fertilizing recommendations are guided by plant nutritional assessments, which are compared to reference values so that decisions can be made regarding which nutrient and how much is to be supplied. Traditionally, these values are obtained by field trials that are particularly long and expensive for perennial crops such as grapevines. This research evaluated the use of boundary line (BL) approach and Bayesian segmented quantile regression (BSQR) in determining reference values for nutrients in vineyard soils using commercial farm data. Critical levels (CL) and sufficiency ranges (SR) of phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), copper (Cu), zinc (Zn), boron (B) and manganese (Mn) were estimated using datasets from a winery in the Campanha Gaucha region, Rio Grande do Sul, Brazil. Results indicated lower P and higher K, S, Zn and Mn levels, as compared to current state recommendations. Great inconsistencies were found in CL estimates for Cu and, to a lesser extend, Ca and Mg. Model assessments indicated that BSQR estimates were highly sensitive to quantile selection but poorly affected by changes in the prior. Data simulated using fitted models were consistently over-dispersed. Allowing for variable slopes and intercepts may partition data variability more properly, leading to better fit, higher parameter precision and greater accuracy of estimates. Despite current limitations, the BSQR model provides a flexible framework for BL analysis, enabling the use of commercial datasets in establishing reference values to support group-and site-specific recommendations, a valuable contribution to increase efficiency and sustain ability of grapevine fertilization.

Automated summary

This study evaluated the use of BL and BSQR approaches in determining reference values for nutrients in vineyard soils using commercial farm data. The results showed inconsistencies in current nutrient recommendations and highlighted the flexibility of the BSQR model in establishing reference values. The study emphasized the importance of increasing the efficiency and sustainability of grapevine fertilization.