Francisco Rovira Más
Agricultural Robotics Laboratory (ARL), Polytechnic University of Valencia, Spain

The sustainability of agricultural production in the twenty-first century, both in industrialized and developing countries, benefits from the integration of farm management with information technology such that individual plants, rows, or subfields may be endowed with a singular “identity.” This approach approximates the nature of agricultural processes to the engineering of industrial processes. In order to cope with the vast variability of nature and the uncertainties of agricultural production, the concept of crop biometrics is defined as the scientific analysis of agricultural observations confined to spaces of reduced dimensions and known position with the purpose of building prediction models. This presentation explains the principles of crop biometrics, discussing the selection and quantization of biometric traits, and analyzing the mathematical relationships among measured and predicted traits. In addition, the idea of crop biometric maps will be applied to the particular case of a wine-production vineyard, taking into account such biometric traits as vegetative vigor, relative altitude in the field, soil compaction, berry size, grape yield, juice pH, and grape sugar content.