Spatial Variability of Aroma Profiles of Cocoa Trees Obtained through Computer Vision and Machine Learning Modelling: A Cover Photography and High Spatial Remote Sensing Application
Sigfredo Fuentes, Gabriela Chacon, Damir D Torrico, Andrea Zarate, Claudia Gonzalez Viejo
Sensors | MDPI | Published : 2019
Cocoa is an important commodity crop, not only to produce chocolate, one of the most complex products from the sensory perspective, but one that commonly grows in developing countries close to the tropics. This paper presents novel techniques applied using cover photography and a novel computer application (VitiCanopy) to assess the canopy architecture of cocoa trees in a commercial plantation in Queensland, Australia. From the cocoa trees monitored, pod samples were collected, fermented, dried, and ground to obtain the aroma profile per tree using gas chromatography. The canopy architecture data were used as inputs in an artificial neural network (ANN) algorithm, with the aroma profile, con..View full abstract
This research was partially funded by the Ecuadorian government through the academic-award scholarships program granted to GC. This research was supported by the Digital Viticulture program funded by the University of Melbourne's Networked Society Institute, Australia.