SOIL ATTRIBUTES AS PREDICTORS OF CROP PRODUCTION UNDER STANDARDIZED CONDITIONS

To assess soil fertility or quality three controlling components - its physical, chemical and biological nature - have to be considered. In this study a broad spectrum of agricultural soils from Sweden were cro pped with ryegrass in pots under standardized conditions in climate ch ambers. Measurements of physical, chemical and biological attributes o f soil were used to predict C and N yields by simple correlation and t he multivariate calibration techniques, principal component analysis c ombined with multiple linear regression, and partial least squares (PL S) regression. The N yields were typically more accurately predicted t han the corresponding C yields. The best single predictor of yields wa s always total soil N, but estimates produced by multivariate models i ncluding organic C, total N, C/N ratio, coarse silt, potential denitri fication activity, N mineralization. substrate-induced respiration and sample site humidity were, in all cases, substantially more accurate. Coefficients of correlation bet it een predicted and measured C or N yields ranged between 0.61 and 0.80 with total N as predictor, and bet ween 0.69 and 0.97 with the multivariate models. Both quantitative and qualitative aspects of the organic matter were considered to be impor tant with respect to the predictive ability. Both these aspects were a ccounted for by the multivariate models. The multivariate technique, P LS regression, facilitated the classification of soils into categories of good, normal or poor fertility in relation to their organic matter content.