Journal article

Assessing wine grape quality parameters using plant traits derived from physical model inversion of hyperspectral imagery

L Suarez, P Zhang, J Sun, Y Wang, T Poblete, A Hornero, PJ Zarco-Tejada



Together with ensuring a stable yield, improving grape composition and aroma is the main goal of wine grape production management as it determines consumer acceptance and ultimately revenue. Understanding the triggers of the synthesis of aromatic components and finding methods to map their variability in the field can aid management practices during the season and planning selective harvest in views of maximizing benefit. Vegetation indices have been shown to track grape colour, sugar and acidity content but it has been demonstrated that aromatic components are the main drivers of the final palate of wine and are not correlated to sugar concentration. Leaf pigments such as chlorophyll, carot..

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Funding Acknowledgements

The authors would like to acknowledge Damien Sheehan and the team in Mt Langi Ghiran for allowing this research to be conducted there. Chemical analysis was partially funded by the Masters Major Project program at the School of Agriculture and Food, the University of Melbourne. Rafael Romero from QuantaLab-IAS-CSIC laboratory (Spain) for data processing, and Aaron Correra, Daniel Thomas and Luke Annels from XM2 Pursuit are also acknowledged for the image data collection and participation in the airborne campaigns.