This study investigates relationships between wheat productivity and soil nitrogen, suggesting machine learning models can enhance soil health evaluation.
Coverage of the components of causal dependencies of crop productivity mediated by N-, C-chemical, biological indicators of soil (sizes of pools of relevant available forms, enzymatic activities) in the context of theoretical aspects of resource turnover in it is potentially significant for the design of systems of evaluation criteria for soil health using machine learning (ML) models. The purpose of this study was to find statistically valid and meaningful coordination and causal relationships of grain weight per sown area with available forms of N, C (inorganic and easily hydrolysed N – NIN, NEH; C of labile humus – CLH), in situ proteolytic PA, in vitro urease UA activity in association with the concepts of the turnover of these organogens in the soil under winter wheat under prototypical environmentally friendly fertiliser systems. The following methods were employed: field, in situ, laboratory-analytical chemical and biochemical, morphometric, statistical, ML-modelling. With a high probability, the increase in GM was caused by an additive increase in NIN, NEH, and a simultaneous decrease in in situ PA, in a way that mediated the effect of in situ PA on GM by the listed forms of N. Statistically less valid was the mediation of the effect of the ratio of NEH to NIN on GM through in situ PA with possibly mutually complementary predispositions of N forms, which, however, provided the basis for substantiating the simultaneous mutually opposite determination of GM by these N forms and in situ PA. It is plausible that CLH and in vitro UA were not involved in the development of GM under these experimental conditions, but it is possible that the latter of these variables may have a more significant effect on the variation of the former than vice versa. Studies in this vein will develop a discourse of theoretical predictions regarding the improvement of the structure of soil quality indices towards revealing aspects of the laws of promoting the balance between the characteristics of agro-ecosystem services, considering the chemical and biochemical properties of N and C turnover in the soil, and crop bioproductivity necessary for the development of sustainable agriculture
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Stasiv et al. (2025) studied this question.
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