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 Magazinei-mk8

Download Full article by clicking here: IRScannerFuentes et alscan

 

 

 

 

 

 

 

The Vineyard of the Future initiative is a multinational project that aims to establish a fully instrumented vineyard using wireless connectivity and automated data gathering and analysis. It also aims to be a test-bed for new technology and a trial site for investigating the potential effects of climate change on viticulture in Australia, Chile, US and Spain. Researchers involved with the project have been developing an infrared scanner to assess plant water status at a fraction of the cost of infrared cameras and with the same comparable results.

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Water productivity Water

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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.

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
Workshop

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

 

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Figure 1: 3D model of the robotic pourer.

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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.

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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.

What grapevines do when everybody is sleeping?

Posted: March 30, 2014 by vineyardofthefuture in About the project, News, Research Paper

New study shows results of night-time water losses for grapevines.

By Sigfredo Fuentes

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Abstract:

Night-time water uptake (Sn) mainly corresponds to stem and organ rehydration and transpiration, the latter through stomata and cuticle. Nocturnal transpiration is uncoupled from photosynthesis, therefore it contributes to reduce water use efficiency (WUE). Night-time grapevine physiology was measured on field grown grapevines (cv. Shiraz) under partial root-zone drying (PRD) and deficit irrigation (Exp 1), on potted vines (cv. Tempranillo) (Exp. 2) and on potted vines (cv. Cabernet Sauvignon) on a progressive drought treatment in the glasshouse (Exp. 3). Sap flow probes using the compensated heat pulse method (cHP) were installed in vines (Exp. 1 and 3). Night-time gas exchange measurements were performed for Exp. 3. Other vine water status monitoring methods used were: midday stem water potential (Ψs) for all experiments, and abscisic acid (ABA) concentration monitored from leaf sap for Exp. 3. Results showed that Sn was parabolically correlated to Ψs measured on the previous day for all treatments and cultivars. Two distinct zones where vines exhibit different night-time behaviour within the Ψs vs Sn parabolic relationships were identified for all experiments. The differences between the two identified areas were related to the water status conditions of the vines:  i) non-water stress conditions (0 < Ψs < -1.0 MPa); ii) water stress conditions (-1.0 MPa < Ψs < -2.0 MPa). Furthermore, levels of water stress were negatively correlated to concentrations of leaf sap ABA, which helped to explain the parabolic curve found for cv. Cabernet Sauvignon.

Link to full article, click NighttimeVines

By: Sigfredo Fuentes

Presentation given at the Matlab tour 2013, Melbourne – Australia

To view proceedings CLICK HERE

MATLAB

 

 

 

 

 

 

 

 

 

 

 

 

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™.