Project 3.3.2

Digital solutions for grape quality measurement and management

Project summary

Currently, subjective (visual) methods are used to quantify grape condition at the weighbridge. Defects may reduce the price paid to the grower or result in rejection of the fruit. This subjective assessment can cause mistrust for the grape supplier about the load assessment process. Conversely, if a defect such as bunch rot is present in the load but not observed, the resultant wine may have a lower value (50-70% of potential). The development of a process to objectively measure bunch rot and matter other than grapes (MOG) will provide greater transparency of the assessment process and help prevent the production of poor quality wine. This project will build on past work relating to objective measures of grape quality, in particular measurement of the degree of fungal rot infection through the use of spectral methods and chemometrics. Commercially available Visible-NIR hyperspectral imaging systems will be used at the weighbridge to provide objective data on the degree of infection by fungal rots and subsequent deterioration of fruit quality. Hyperspectral imaging is an emerging technique used in food manufacture but has mainly been used in the wine industry for assessing vineyard variability through aerial imaging. If hyperspectral imaging is unsuccessful, spectroradiometer probes will be used for the assessment of both fungal rot and MOG. The project will provide viticulturists and winemakers with tools to help optimise grape production towards desired quality targets, preferred wine styles and premium price points, as described in strategy 3 of the Wine Australia strategic plan.

Latest information

Assessment of Botrytis in berries

Hyperspectral imaging is an emerging technique used in food manufacture and so far has mainly been used in the wine industry for assessing vineyard variability through aerial imaging. Individual berries offer the simplest system as proof of principle for hyperspectral imaging of Botrytis. Figure 13 shows an RGB (red, green and blue) image and a false colour overlay of individual berries where the Botrytis infection has been identified. In this case the image analysis system was trained using Colombard berries grown in the Riverland that were either clean or infected with Botrytis in the laboratory, and was then able to identify and discriminate between Adelaide Hills Sauvignon Blanc berries that were clean or had a wild Botrytis infection. The hyperspectral imaging could also easily identify matter other than grapes. Analysis of the hyperspectral images of individual berries was also able to discriminate damaged Botrytis-infected berries from healthy damaged berries, shrivelled berries from sound berries and berries infected with sour rot from berries infected with Botrytis. The small mis-identified areas on the Sauvignon Blanc berries are likely the consequence of reflection from shiny berry skins. This highlights one of the challenges of this technique: the lighting is critical and needs to be set up so that it prevents shadows which can lead to false identification, while still avoiding reflections from the fruit surface.


Project Contact

Paul Petrie

This project is supported by Wine Australia, through funding from the Australian Government Department of Agriculture and Water Resources as part of its Rural R&D for Profit program and The Australian Wine Research Institute.