Delineating citrus management zones using spatial interpolation and UAV-based multispectral approaches

The ability to delineate site-specific management zones is a key feature for precision agriculture applications. In this study, a novel methodological protocol for mapping the water status, i.e. the stem water potential (SWP), of citrus orchards was developed. Specifically, observed stem water potential (SWPobs) values and unmanned aerial vehicle multispectral information (i.e., vegetation indices, VIs, and spectral bands, SBs) were integrated to implement a twofold approach based on: (i) the spatial interpolation (SWPint) of the SWPobs, and (ii) the stepwise regression models (SWPproxy) between the SWPobs and the VIs (scenario 1) or between the SWPobs and the SBs (scenario 2). Then, the derived crop water status maps (SWPint and SWPproxy) were customized by applying an absolute (scientific-driven), a relative (quantile-driven), and an automated clustering (K-means) classification method. The accuracy of the proposed approach, evaluated by comparing SWPint and SWPproxy with SWPobs using linear regression models, showed reliable results, with average mean absolute error and root mean square error values ranging from 0.13 to 0.19 MPa and from 0.19 to 0.24 MPa, respectively. These results provide practical insights for identifying the spatial-temporal variability of the SWP of the citrus orchard under study. Additionally, the study highlights the importance of using a scientific-driven classification to support the adoption of precision irrigation criteria and decision-making process by non-expert users, as indicated by the assessment of the Silhouette index.