Assessing soil health in long-term crop rotations

Recently, via social media, they shared with us research that is closely related to soil health and therefore to the NOVASOIL project. This study, published in Geoderma, analyses soil health and key indicators in five long-term crop rotations with different fertility management practices. The research was carried out by Jingyu Zhang, Miles Dyck, Sylvie A Quideau and Charlotte E Norris at the University of Alberta, Canada.


Soil health is a crucial issue for sustainable agriculture as it affects productivity, environmental quality and plant and animal health. This study focused on assessing soil health under different long-term agricultural practices. The aim of this article is to present the main findings of the study, highlighting how crop rotation and fertility management practices affect soil health.


The authors of this valuable study identified several key objectives:

  • To assess soil health under different long-term agricultural practices.
  • Identify key soil health indicators (SHI) that are sensitive to management practices.
  • Develop a soil health score specific to the study site.

Study site location

The study was conducted at the University of Alberta’s Breton Plots, located approximately 100 km southwest of Edmonton, Alberta, Canada. This site has been used for crop rotation and fertility management experiments since 1929.


The research team used a Principal Component Analysis (PCA)-based approach to identify soil health keys. Soil samples were collected in 2019 and 2020, and a total of 168 soil health indicators, including chemical, biological and physical properties, were assessed.

Sampling procedure

  • Plot selection: Plots representative of five long-term rotations with different fertility management were selected.
  • Sampling: Soil samples were taken at different depths and analyzed in the laboratory to measure a range of SHIs.
  • Data analysis: PCA was used to reduce the large amount of data to a set of key indicators that explained most of the variability in soil health.


The analysis identified seven SHI keys that explain 86.8% of the total variability in the dataset. These indicators include

  • Autoclavable Citrate Extractable Protein (ACEP): Indicator of potentially available nitrogen.
  • Soil pH: Indicator of soil fertility and quality.
  • Mehlich 3 extractable phosphorus (M3-P): Indicator of nutrient availability.
  • Morgan modified extractable sodium (MM-Na): Indicator of soil structure and fertility.
  • Available Water Holding Capacity (AWHC): Indicator of the ability of the soil to hold water.
  • Total carbon in water stable aggregates (PTCA): Indicator of soil stability and carbon sequestration.
  • Phosphomonoesterase activity (PME): Indicator of organic phosphorus mineralization.


The study results underline the importance of crop rotation and fertility management practices for soil health. More diversified crop rotations and treatments with fertilizers and organic amendments were found to significantly improve soil health. The PCA-based approach proved to be an effective tool to identify key SHIs and to develop a specific soil health score.

Implications for the NOVASOIL project

This study provides a solid foundation for the NOVASOIL project and highlights the importance of monitoring and improving soil health through sustainable agricultural practices. The results can guide the implementation of soil management techniques that promote agricultural productivity and environmental sustainability.

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