Wiley, Annals of Applied Biology, 3(184), p. 278-287, 2023
DOI: 10.1111/aab.12881
Full text: Unavailable
AbstractTwo plots (10 ha each) of Triticum aestivum L. wheat crop were analysed, one with a phosphorus‐solubilizing bioinoculant (bioinput) and another without the bioinput (control). Traditional physical–chemical variables and four enzymes were analysed: arylsulfatase (AS), β‐glucosidase (β‐G), acid phosphatase (AP), and N‐acetyl‐β‐d‐glucosaminidase (NAG). These variables were considered by Hierarchical Cluster Analysis (HCA) and partial least squares‐discriminant analysis (PLS‐DA). The HCA separated 100% correctly the control and bioinput samples along the wheat phenological stages (Feekes‐Large scale). The PLS‐DA model was constructed with seven latent variables and obtained 100% accuracy, explaining a variance of 97.05% in calibration and 93.13% in cross‐validation. The control soil had a productivity of 57.8 bags per hectare, while the soil with bioinput had a productivity of 60.8 bags per hectare. Furthermore, soil with the bioinput presented higher concentrations of the enzymes AS, β‐G, and AP in the final phenological stages.