Using surface soil layer depth for determining soil quality index for evaluating productivity of potato (Solanum tuberosum L.) in Hokkaido, Japan

ABSTRACT

A comprehensive quantification of soil quality is necessary for data-driven soil management, and numerous studies have sought to devise methods for determining the soil quality index (SQI) to assess soil productivity. However, most studies have focused on topsoil properties rather than deeper soil properties. Therefore, this study attempted to calculate the SQI by incorporating subsoil properties and surface soil layer depth and topsoil properties, targeting farms cultivating potatoes in Tokachi region, Hokkaido. The soil parent material in this region is primarily composed of a mixture of alluvial deposits, volcanic ash, and peat, which makes the comparison between the various soil properties difficult for evaluation by farmers. Principal component analysis (PCA) and regression analysis were used to select the minimum data set (MDS) representing the variance of the original data set: exchangeable Ca, K, pH, solid phase, and acid-soluble Cu in descending order of weight. Weights were allocated based on the eigenvalues of the principal components. This study selected MDS’s parameters from properties with soil diagnosis criteria based on past research on productivity evaluation. The selected parameters contained both physical and chemical properties, which indicated that the soil quality was evaluated from both aspects. For surface soil layer depth consideration, the corrected SQI was calculated by reducing more when the depth was shallower. SQI considering subsoil properties did not correlate with yield (r = 0.358), but SQI considering surface soil layer depth was significant (r = 0.515–0.518) regardless of the soil type (parent material) and cultivar. Correlations between SQI considering depth and yield were stronger when considering a single cultivar with the greatest number of sites (r = 0.620–0.641). A deeper surface soil layer depth would provide more macropores to plant roots and improve the availability of air, greatly affecting soil quality in the Tokachi region, where precipitation is high during the growth season. Therefore, this study reveals the importance of considering the surface soil layer depth to evaluate soil productivity using the SQI.

KEY WORDS:

• Surface soil layer depth
• multivariate analysis
• potato yield
• productivity
• soil quality index

Acknowledgments

The authors would like to thank Atsushi Yagioka of HARC/NARO for their support in soil N and C analyses. The authors also thank Takahiro Mikuni of HARC/NARO for their support with soil sampling. The authors thank Hikari Ogawa of the Tokachi Federation of Agricultural Cooperative Associations for obtaining permission from farmers to collect soil samples and schedule adjustments. This work was conducted as a joint research agreement ‘The research on utilization of agricultural data for the farming support in upland area’ between HARC/NARO and Tokachi Federation of Agricultural Cooperative Associations.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the joint research agreement ‘The research on utilization of agricultural data for the farming support in upland area’ between HARC/NARO and Tokachi Federation of Agricultural Cooperative Associations.