Spatial variability analysis is fundamental in precision orchard management, yet non-uniform irrigation can distort the delineation of management zones (MZs), leading to sub-optimal operational decisions. This study investigates the impact of irrigation non-uniformity on MZ delineation in a 7-ha micro-irrigated pear orchard by integrating topographic information (Z), vegetation vigor (NDVI), soil apparent electrical conductivity (ECa), and emitter flow rates (Q). Geostatistical analyses show that elevation and ECa are the primary drivers of structured field variability, while Q reveals substantial hydraulic heterogeneity-most notably in the Carmen sector, which displays both the lowest average discharge and the greatest variability in emitter performance. Incorporating Q into fuzzy c-means clustering increases zoning complexity, leading to more MZs than classifications based solely on soil and vegetative indicators. When all variables (Z, NDVI, ECa, Q) are combined, the orchard is optimally divided into four management zones that more accurately reflect the interplay of hydraulic, topographic, and soil-related factors shaping crop response. These findings indicate that a lower distribution uniformity of the irrigation can introduce operational artefacts into spatial analyses, highlighting the value of optimising the irrigation layout and adopting zone-specific irrigation management to improve system performance and crop responsiveness.

Effect of irrigation uniformity on the delineation of homogeneous zones in a pear orchard

Bonzi L.;Carrara M.;Hamouda F.;Marasco S.;Massai R.;Puig Sirera A.;Remorini D.;Rallo G.
2026-01-01

Abstract

Spatial variability analysis is fundamental in precision orchard management, yet non-uniform irrigation can distort the delineation of management zones (MZs), leading to sub-optimal operational decisions. This study investigates the impact of irrigation non-uniformity on MZ delineation in a 7-ha micro-irrigated pear orchard by integrating topographic information (Z), vegetation vigor (NDVI), soil apparent electrical conductivity (ECa), and emitter flow rates (Q). Geostatistical analyses show that elevation and ECa are the primary drivers of structured field variability, while Q reveals substantial hydraulic heterogeneity-most notably in the Carmen sector, which displays both the lowest average discharge and the greatest variability in emitter performance. Incorporating Q into fuzzy c-means clustering increases zoning complexity, leading to more MZs than classifications based solely on soil and vegetative indicators. When all variables (Z, NDVI, ECa, Q) are combined, the orchard is optimally divided into four management zones that more accurately reflect the interplay of hydraulic, topographic, and soil-related factors shaping crop response. These findings indicate that a lower distribution uniformity of the irrigation can introduce operational artefacts into spatial analyses, highlighting the value of optimising the irrigation layout and adopting zone-specific irrigation management to improve system performance and crop responsiveness.
2026
Bonzi, L.; Carrara, M.; Hamouda, F.; Marasco, S.; Massai, R.; Puig Sirera, A.; Remorini, D.; Rallo, G.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1350867
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