The objectives of this project are to:
- undertake a proof of concept for the use of spectral analysis to determine bud fruitfulness
- demonstrate the feasibility of predicting bud fruitfulness prior to pruning, using a portable hand-held sensor
The ability to predict bud fruitfulness early in the season is a high priority for the Australian wine sector.
Currently yield prediction requires destructively sampling canes from the vine, then an expert carrying out bud dissections under a microscope. This is both time consuming and expensive.
Spectroscopy offers advantages in terms of speed and simplicity for routine analysis.
Providing a proof of concept, followed by development of a portable hand-held device to allow scanning of buds in the vineyard will provide pruning decision support to vineyard managers and help to alleviate the effects of excessively high or low yielding years.
This project will gather the foundation data to assist in developing a method for rapid, early prediction of yield in grapevines.
The research will be underpinned by traditional bud dissection methods, coupled with new technology for imaging the contents of intact buds.
This will initially be done by confocal 3D Raman mapping, followed by laboratory based FT-NIR spectroscopy and then portable UV-Vis-NIR spectroscopy in the field.
A predictive model using multivariate analysis will be developed to allow simple scanning of buds to provide yield forecasts prior to budburst.
The data will be used to develop an App for use with a specific instrument and software with relevant calibration, to allow informed pruning decisions to be made in the vineyard.
Findings from this study have the potential to assist growers in making informed pruning decisions resulting in an improved ability to reach target yields.
The digital tool will provide greater accuracy in yield prediction and reduce economic losses due to late season bunch removal or reduced prices due to excessively high yields.
This project is supported by funding from the Australian Government Department of Agriculture and Water Resources as part of its Rural R&D for Profit programme.