Development of a Soil Quality Index:
Applications in California's Central Valley

SUSAN S. ANDREWS1, JEFF P. MITCHELL2*, DOUG L. KARLEN1*, CORNELIA BUTLER FLORA3,4,
STU PETTYGROVE5, TIM HARTZ2, KATE SCOW5, WILLIAM HORWATH5,
TOM LANINI2, KAREN KLONSKY6, AND DAN MUNK7

1USDA-ARS National Soil Tilth Laboratory
2Department of Vegetable Crops
Davis Campus

3North Central Regional Center for Rural Development
4Department of Sociology
Iowa State University

5Department of Soil and Biogeochemistry
6Department of Agricultural and Resource Economics
Davis Campus

7University of California Cooperative Extension
Fresno, CA

Summary

The intensification of high-value, large-scale crop production in the Central Valley of California has resulted in more frequent tillage, fewer additions of organic matter, and a perceived decline in soil quality. Producers, farm advisors, and other land managers may benefit from decision tools that identify management practices which sustain or enhance soil quality. An index of soil quality (SQI) is one such tool. We tested various methods for choosing a minimum data set (MDS), transforming the indicators, and calculating indexes, using data from two on-going research projects. In the San Joaquín Valley, the Biologically Integrated Farming Systems (BIFS) project examined the on-farm effects of alternative organic amendment practices, including cover crops, composts, and manure, on various soil quality indicators. In the Sacramento Valley, the Sustainable Agriculture Farming Systems (SAFS) project analyzed alternative vegetable production systems with varying rotations, manure applications, and pest control strategies. Data from both projects revealed a number of soil properties with significant differences among treatments, including soil organic matter (SOM), sodium adsorption ratio (SAR), Na, pH, microbial biomass C and N, Olsen-P, exchangeable K, and extractable Zn. The MDS components were chosen for the index, using expert opinion or principal components analysis (PCA). Multiple regressions of the MDS indicators against varying management goals showed no significant differences between the two selection techniques in their abilities to define variability within each sustainable management goal. For almost all indexing combinations, the organic system received significantly higher SQI values than the low-input or conventional treatments. For data from the SAFS project, the efficacy of the indices was tested by comparisons with individual indicators, varying management goals, and another multivariate technique for decision making that uses all available data rather than a subset (or MDS). Our results suggested that a small number of carefully chosen soil quality indicators, when used in a non-linearly scored index, adequately provided information needed in the selection of management practices. Further, indicator results pointed to the potential of a variety of practices that add organic matter, which improves soil quality even in the intensively-tilled, semi-arid environments of the Central Valley of California.