Multi-Parametric Approach to Management Zone Delineation in a Hazelnut Grove in Italy

Roberta Martelli, Vincenzo Civitarese, Lorenzo Barbanti (), Abid Ali, Giulio Sperandio, Andrea Acampora, Davide Misturini and Alberto Assirelli
Additional contact information
Roberta Martelli: Department of Agricultural and Food Sciences–DISTAL, University of Bologna, Viale Fanin 44, 40127 Bologna, Italy
Vincenzo Civitarese: Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, Monterotondo, 00015 Roma, Italy
Lorenzo Barbanti: Department of Agricultural and Food Sciences–DISTAL, University of Bologna, Viale Fanin 44, 40127 Bologna, Italy
Abid Ali: Department of Agricultural and Food Sciences–DISTAL, University of Bologna, Viale Fanin 44, 40127 Bologna, Italy
Giulio Sperandio: Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, Monterotondo, 00015 Roma, Italy
Andrea Acampora: Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, Monterotondo, 00015 Roma, Italy
Davide Misturini: Agrinnovazione, Via Prese 22a, Pescantina, 37026 Verona, Italy
Alberto Assirelli: Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, Monterotondo, 00015 Roma, Italy

Sustainability, 2023, vol. 15, issue 13, 1-12

Abstract: The increase in high-density hazelnut ( Corylus avellana ) areas drives the interest in practices of precision management. This work addressed soil apparent electrical conductivity (ECa), RGB aerial (UAV) images, proximal sensing, and field scouting in delineating and validating management zones (MZs) in a 2.96 ha hazelnut grove in Italy. ECa data were fitted to a semi-variogram, interpolated (simple kriging), and clustered, resulting in two MZs that were subjected to soil analysis. RGB imagery was used to extract tree canopies from the soil background and determine two vegetation indices (VIs) of general crop status: the Visible Atmospherically Resistant Index ( VARI ) and the Normalized Green-Red Difference Index ( NGRDI ). Then, plant growth parameters were manually assessed (tree height, crown size, etc.) and a proximal VI, the Canopy Index (CI), was determined with the MECS-VINE ® vertical multisensor. MZ1 was characterized by lower ECa values than MZ2. This was associated with a lower clay content (9% vs. 21% in MZ1 vs. MZ2) and organic matter content (1.03% vs. 1.51% in MZ1 vs. MZ2), indicating lower soil fertility in MZ1 vs. MZ2. Additionally, hazelnut trees had significantly smaller canopies (1.42 vs. 1.94 m 2 tree −1 ) and slightly lower values of VARI , NGRDI , and CI in MZ1 vs. MZ2. In conclusion, our approach used ECa to identify homogeneous field areas, which showed differences in soil properties influencing tree growth. This is the premise for differential hazelnut management in view of better efficiency and sustainability in the use of crop inputs.

Keywords: apparent electrical conductivity; hazelnut; management zones; multisensor; vegetation index (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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