Grouping Soils by Taxonomic Order to Improve Lime Recommendations

The success of a liming program is dependent upon the accuracy of the lime recommendation, which in turn depends on the quality of the underlying correlations and calibrations. Because of the expense, large-scale field calibration experiments are rarely conducted. The relatively low economic returns from pastures make it even more unlikely that a calibration experiment would be conducted, especially in West Virginia. Therefore, any improvements in lime recommendations have to be made from lime correlations. Moreover, it is unlikely that a single lime correlation can accurately identify appropriate lime rates for all soils. Hence, the objectives of this study were to improve the accuracy of lime recommendations by using quick tests that account for soil order and to develop lime correlations for acidic pasture soils of West Virginia. Twenty-five surface soil samples (0–7.5 cm) from the three major soil orders in the state (Alfisols, Inceptisols, Ultisols) were collected, most in cooperation with state soil scientists. Standard procedures for the determination of lime requirements by the Adams–Evans buffer (AEB), Mehlich single buffer (MB), and Shoemaker–McLean–Pratt single buffer methods (SMPB) were used. Statistically significant improvements in lime recommendations for target pH values of 6.5 and 5.5 were achieved by accounting for soil order. Mehlich single buffer recommendations were better for Alfisols and Ultisols than for Entisols to achieve pH 6.5. Lime correlations were developed for all three chemical buffers by multiple regression where the independent variables were target pH and soil-buffer pH. The AEB predicted lime rates better for target pH 5.5.