A method for soil management assessment in an unreplicated commercial field
2022
Lee, Juhwan | Plant, Richard E.
Context Unreplicated trials are common in agriculture. However, statistical inferences differ from those of traditional experiments based on small, replicated plots. Aims To present a method to assess management effects on soil carbon (C) storage from unreplicated, side-by-side field trials. Methods Two estimates of means with spatially correlated errors are compared using a corrected t -statistic. Then causal inference is made by analysing a significant difference between the means (P Key results The results show that crop C yield did not differ between the fields when using the same tillage practice but was greater in the tilled than the no-till field. The results also suggest that total and particulate organic matter-C contents depend on tillage history. For comparative purposes, the data were also analysed using standard mixed model analysis with a semivariogram model for spatial autocorrelation among the residuals. The mixed model results were generally similar to those of the corrected t -statistic method. The mixed model was often, but not always, less conservative than the corrected t -statistic model. Conclusions The method allows analysis of whole-field data and improves our understanding of soil C processes in commercial fields, where agricultural assessment cannot involve replication due to agronomic and economic constraints. Implications The method complements observational data analyses and can offer a direction towards whole-field management.
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