Link to full article:Research Gate: Sigfredo Fuentes
Archive for the ‘Projects’ Category
Tags: foam dynamics, image analysis, protein content, robotic pourer, sparkling wine, wine quality
Flight of the Viticopter II: Test flight for Viticopter belonging to VoF: The University of MelbournePosted: July 31, 2014 by vineyardofthefuture in News, Projects, Research Grant, Uncategorized
Flight of the Viticopter (VoF – The University of Melbourne)
Aircraft: Hexacopter, eAustralis hexacopter mark 2
Pilot: Jeff Hollingworth
Place: Dookie Campus (UoM)
Date: 31st July 2014
By: Sigfredo Fuentes
As the effects of climate change on Australian agriculture become more apparent, the importance of monitoring changing weather conditions and their diverse impacts will grow to paramount importance. Flexible and scalable processes for data analysis and modelling, particularly image and sensor data, are an essential part of how we monitor and respond to our changing environment. But more than that, we must foster a new generation of scientists and engineers who possess not only the technical skills to analyse this data, but the critical thinking and innovative aptitude to turn it into more sustainable outcomes for our economies, communities, and the entire planet. Full Article: ea Magazine
Download the full document by clicking the link above the picture.
This document was prepared by The University of Melbourne as part of its flagship innovation initiative, Carlton Connect (www.carltonconnect.com.au). An expert, strategic advisory committee, which contributed towards the methodology and content of this Blueprint, included representatives from the Bureau of Meteorology, the Commonwealth Environmental Water Office, Geosciences Australia, the National Water Commission and the Victorian Department of Environment and Primary Industries. The Murray Darling Basin Authority was also consulted as part of the process. However, the views expressed herein are the views of the University of Melbourne based on the consultation process and are not a reflection of any official policy or consensus amongst these organisations.
A Research and Development Advisory Committee provided many contributions to this report. This group included: Dr Margaret Ayre, Professor Snow Barlow, Dr Brian Cook, Dr Bob Farquharson, Dr Sigfredo Fuentes, Professor Lee Godden, Professor David Karoly, Professor John Langford, Dr Veronika Nemes, Associate Professor Ruth Nettle,
Dr Murray Peel, Dr Vincent Pettigrove, Associate Professor Ian Rutherfurd, Dr Dongryeol Ryu, Dr Khusro Saleem, Professor Peter Scales, Dr Dominic Skinner, Dr Mohsen Kalantari Soltanieh, Associate Professor Michael Stewardson, Dr Angus Webb, Professor Andrew Western and Associate Professor Erik Weyer.
The project team would like to sincerely thank those that readily gave their time to participate in online surveys and workshops.
An appropriate citation for this publication is:
Stewardson M.J., D. Skinner, M. Ayre, S. Barlow, B. Cook, B. Farquharson, S. Fuentes, L. Godden, D. Karoly,
J. Langford, V. Nemes, R. Nettle, M. Peel, V. Pettigrove, I. Rutherfurd, D. Ryu, K. Saleem, P. Scales, M.K. Soltanieh, A. Webb, A. Western, E. Weyer. 2014. Water Productivity Blueprint. The University of Melbourne, Melbourne.
Southern Hemisphere Water Productivity Workshop for the Agriculture of the Future (Santiago – Chile: 22nd May 2014)Posted: May 6, 2014 by vineyardofthefuture in About the project, Conference paper, News, Projects, Seminar presentation
Workshop in Chile, organised by The University of Melbourne, The University of Talca (Chile) and INIA (Chile).
In this opportunity it will be presented latest advances in robotics and UAV with a case study for The Vineyard of the Future (Melbourne – Australia)
Full Program: Workshop-full
What a Robot can tell you about the quality of your sparkling wine?: share a drink with FIZZeye-RobotPosted: April 22, 2014 by vineyardofthefuture in News, Projects, Research Grant
FULL TEXT, DOWNLOAD HERE: Research Gate: Sigfredo Fuentes
By Sigfredo Fuentes; Bruna Lima, Maeva Caron and Kate Howell
Article to come out in the May-June issue of the Wine and Viticulture Journal
Figure 1: 3D model of the robotic pourer.
Figure 2: Inside and outside of actual pourer.
The Australian wine industry contributes strongly to the country’s economy (Lin, 2013). Australia is the sixth largest wine producer and the fourth largest wine exporter (WFA, 2013). Sparkling wine accounts for approximately 9% of the domestic wine sales and 13% of total wine imports in Australia (ABS, 2013). Wines with dissolved carbon dioxide are also economically important for several countries, France, Spain, Italy, USA, and Chile (IWSR, 2011; CIVC, 2013). Increase in temperature and carbon dioxide levels in the atmosphere have shown to affect flavour and aroma of wines (Johnson and Robinson, 2013), decrease protein concentration in plants (Högy et al., 2009; Azam et al., 2013; Mishra et al., 2013) and increase alcohol in wines (Howden and Stokes, 2009). Consequently, climate change is expected to influence the final quality of sparkling wine, since several compounds, including protein concentration and alcohol are related to foam stability and the ability of the wine to produce foam (Pozo-Bayón et al., 2009; Coelho et al., 2011).
Figure 3: Sparkling wine pouring
The quality of sparkling wine is visually assessed by its colour, bubble behaviour, appearance (bead) and foam persistence (mousse) (Liger-Belair, 2013). However, as discussed by a number of authors, these parameters are extremely variable and are affected by pouring, reception vessel shape and type as well as temperature (Cilindre et al., 2010; Liger-Belair et al., 2012; Liger-Belair et al., 2013). Robotics and chemometrics allows us to control and monitor these parameters, and thus repeatedly measure sparkling wine for quality assessment and to correlate it with traditional measures of quality. A robotic bottle pourer has been developed to standardise time and wine volume of pouring into a standardised vessel. Images are collected automatically with a digital camera attached to the pourer and transferred to a computer. These images are then evaluated by image analysis algorithms, which convey the information into bubble size and speed, foamability (ability of the wine to produce foam), foam persistence and stability, and collar stability.
Figure 4: Pourer in action in parallel to a sensory analysis at Moet Chandon, Yarra Valley, VIC – Australia.
As a result, this robotic pourer and image analysis algorithms, which simultaneously quantify both bubble’s individual behaviour and collectively as part of the foam, allows the development of a reproducible, easy and inexpensive method to measure sparkling wine quality. Results from this novel technology have been compared to chemometrics and sensory panel data using multivariate data analysis.
By: Sigfredo Fuentes
Presentation given at the Matlab tour 2013, Melbourne – Australia
To view proceedings CLICK HERE
Climate change related phenomena like higher temperatures, increased carbon dioxide concentration in the atmosphere, and more frequent and intensive climatic anomalies, such as heat waves and floods, have placed great pressure on agricultural production around the world. In this scenario, agriculture research and production requires more intensive spatial and temporal monitoring of critical variables to assess the effects of climate change on plant physiology, growth, and fruit quality. Image analysis is becoming an important component in modern agriculture and horticulture. It allows the use of inexpensive devices to acquire meaningful information on crop growth, water status, and quality. In the past, these kinds of technology and analysis were too expensive and required specific know how, which was not readily available to growers. This presentation describes the tools used to solve this problem, such as automated analysis of RGB images and video of plant material, scanned images, and infrared thermal images of canopies to assess plant growth and canopy architectural parameters, leaves and fruit development and plant water status. Results from proposed analysis tools have shown similar outcomes in accuracy and robustness compared to more established techniques. The presenter has developed automated image and video analysis codes using the following MATLAB tools: Image Acquisition Toolbox™, Image Analysis Toolbox™, and Statistical Toolbox™.