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

Abstract

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.

Plant phenotyping relevance

UAVマルチスペクトル情報と空間補間・回帰モデルを統合し、柑橘樹の茎水ポテンシャルという生理状態を地図化する方法を開発・精度評価しており、植物フェノタイピング手法が中心である。

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