Measuring particle-size distribution (psd) is so time-consuming and expensive that it is rarely affordable for systematic survey. In young soil dominated by silicate minerals the size fractions have characteristic elemental compositions, and so they might be predicted from geochemical analysis. We tested the feasibility of predicting the psd from concentrations of elements in samples of topsoil taken in surveys of two large regions in eastern England and on which the psd had been determined. Of the 35 elements measured we chose eight (a) from our general knowledge of mineral composition, (b) after a principal component analysis to avoid redundancy and (c) experience elsewhere. Of the eight elements, five were used (Al, Fe, Ni, Ti and Zr) to build multiple linear regression models for the predictions. The equations were assessed by their coefficients of determination, R2, and the effectiveness of their predictions, expressed as root-mean-square errors (RMSEs) on validation sets of data of known psd. The models accounted on average for 89% of the variance in the clay size-fraction and 82% for sand. The corresponding median RMSEs were 4.9% and 8.8% on medians of 17% and 58%, respectively. The silt size-fraction was less well predicted; R2 was only 0.58, and the median RMSE was 10.6% on a median of 22%. We judge our approach, in which the regression models may be regarded as pedotransfer functions, to have been moderately successful and to merit attention in similar circumstances in other regions.\ud \u
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