Developing scoring functions based on soil texture to assess agricultural soil health in Quebec, Canada

Abstract

Adoption of soil health indicators to access physical, biological, and chemical properties involves adapting their interpretation for a specific region using scoring functions. Accordingly, we used data provided from 1166 soil samples distributed between fine, medium, and coarse-textured soils collected in agricultural areas across the province of Quebec, Canada, and analyzed for 15 soil health indicators. Scoring functions were calculated according to the means and standard deviations obtained for each soil health indicator by textural group. Three scoring types were used: “more-is-better”, “less-is-better”, and “optimum is best”. The results showed that 12 indicators were significantly influenced by soil texture and need separate scoring functions, except for wet aggregate stability, penetration resistance of the surface hardness (0-15 cm) and pH. This led to the development of one to three scoring functions for each soil health indicator. Correlation analysis between soil health indicators was also investigated to better understand relationships between soil physical, biological, and chemical properties. We observed that soil biological indicators were moderately to strongly correlated with each other (r = 0.59-0.74) and with soil physical indicators (r = 0.60-0.76). Overall, the results of this study led to the development of new scoring functions based on soil texture to interpret soil health indicators objectively and accurately for the benefit of Quebec farmers and agricultural stakeholders. The findings of this study demonstrated the need to adapt scoring functions to better account for the impact of regional factors on agricultural soils for the interpretation of soil health indicators.