Fine-tuning Interpretations of the Cornell Soil Health Test in New York through Multivariate Analyses.

There is a growing demand from farmers and other stakeholders for an assessment tool that can provide information on directional changes in soil quality when specific management practices have been implemented. The Cornell Soil Health Test (CSHT) is a multiple indicator test that uses 15 biological, physical and chemical properties and was developed to guide Northeast USA growers in assessing the state of their “soil health” and to target management practices to address specific soil constraints. The CSHT is currently optimized for different soil textures; however, other important underlying factors may additionally be significant for result interpretation..

The CSHT was performed on 7 established long-term experiments located on Cornell University research facilities across New York, including different tillage and rotation systems. Principal component analysis was performed on the soil health variables and they were separated according to location, soil type, tillage method, management practices and soil texture.

From the projection of the cases on factor planes 1 and 2, unique groupings for management system, location, soil type, and soil texture were observed. Tillage did not group in any unique way. For most of the cases, the PCA of the factor plane 1 & 2 accounted for over 50% of the variation in the data. 

PCA groupings observed for location, soil type and soil texture were identical and this suggests that using texture as the basis for interpretation can account for both location and soil type differences observed in NY. Future work will focus on optimizing the CSHT for different management systems by possibly streamlining the indicators to minimize costs and shorten the turn-around period for laboratory analysis.