|Authors: ||A.M. Cavaco, M.D. Antunes, R. Guerra, M. Rosendo, R. Pires, A. Brázio, L. Silva, A.M. Afonso, T. Panagopoulos|
|Keywords: ||Algarve citrus, precision agriculture, geostatistics, geographic information system, optimal harvest date|
Producers, retailers, authorities and consumers need to be able to trace back and to authenticate food products to meet the food safety and food quality requirements.
This comprises time-consuming destructive analysis on a daily basis and it does not provide the orchard representative sampling of maturation index (MI), fruit quality parameters (QP) and optimal harvest date (OHD). Prediction maps of crop parameters are an important tool for the delineation of within-field management zones.
The objective of this research was to develop a novel approach to optimize crop management in precision agriculture based on the development of a geographical information based decision support system for the prediction of OHD. A non-invasive, low-cost, fast and reliable method based on optical spectroscopy provided accurate and extensive records of both MI and other QP, combined to predict specific-site fruit OHD in two edaphoclimatic conditions of Citrus sinensis (L.) Osbeck 'Newhall' orchards.
Overall, we expect to contribute to the state of art in non-invasive technology applied to precision agriculture at non-climacteric fruit by setting up a reliable forecast system for OHD that will optimize crop management, trace back harvested fruit and benefit economically in supply chain.
Prediction maps of fruit quality will provide a general pattern of crop distribution and deliver insight into the spatial heterogeneity within a field.
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