| Sumario: | Chemical analyses of plants for nutritional diagnoses are destructive, complex, and timeconsuming.
Fast and non-destructive alternatives based on optical sensors can perform the
nutritional status of plants in the field [1]. While data captured by spectral sensors can be used to
determine the nutritional status, the actual needs are influenced by other factors, such as the size of
the plant or growth evolution. Allometric measurements, such as height, diameter, or canopy volume,
along with the study of their temporal evolution, can provide valuable information. The use of 3D
sensors can optimise this process, with one of the most widely used sensors being LiDAR [2].
Another technique is photogrammetry, which generates a 3D model from photographs. The aim
was to develop non-destructive tools for determining allometric measurements of a persimmon crop
at various phenological stages using LiDAR and photogrammetry on a robotic platform.
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