New Technology Applications for Agriculture: Going Beyond Awareness

Whether you are a student, farmer, corporate person, or policy maker, you are most likely aware that the Earth is changing, and not always for the better. Take the rise of the Earth’s global surface temperature since 1880 through today as an example. Our Earth is “redder” and “most of the warming has occurred in the past 35 years” (NASA, 2017).

Five-Year Global Temperature Anomalies from 1880 to 2016 (NASA, 2017)

Whilst global warming is the “big picture” on how the Earth is changing, our day-to-day life is also being affected, in terms of what we consume. For most of us, our food comes from the local market or food vendors. However, its main source is derived from farms that are facing climate-related challenges such as extreme weather events, pests and diseases, which require quick adaptations. And if farms cannot adapt, our food supply chain may be disrupted.


Thus, since 2012, the Vineyard of the Future (VoF), has aimed to establish a fully-instrumented vineyard using the Internet of Things (IoT) such as Unmanned Aerial Vehicles (UAVs), remote sensors, and apps. It has also acted as a test-bed for new technology applications and investigated the potential effects of climate change in different agricultural fields. To date, the VoF has worked on practical solutions such as:

  • The free VitiCanopy App that analyses the leaf area index and canopy porosity of grapevines, whereby its parameters can be related to berry quality parameters such as anthocyanin content and polyphenols.
  • Precision viticulture using UAVs for data collection on how grapevines are affected by abiotic factors (post-effect) such as frosts (Baofeng et al., 2016).
  • Biological sensors (dogs) to detect different compounds of interests, and pests such as phylloxera in viticulture (Fuentes & De Bei, 2016).
  • Robotic pourers and computer vision techniques to assess the quality traits of sparkling wines/beers based on foamability and bubble dynamics (Fuentes & De Bei, 2016).
  • The BIOSENSORY app that decodes consumer behaviour using facial biometrics, as our physiological response to stimuli is before our verbalisation of it.

In addition, new technology applications are also being developed for specific monitoring, and these include:

  • The early (pre-effect) detection on frost damage assessments in vineyards.
  • A pilot app for apples to detect sunburn risks and model final fruit-size during harvest time.
  • The detection of smoke contamination in vineyards, whereby the smoke-related compound guaiacol glycoconjugates results in undesirable aromas and flavours in wine (Fuentes & Tongson, 2017).
  • The use of non-invasive remote sensing to assess meat quality, whereby biometrics such as breathing patterns, body temperature, and heart-rate, are used to quantify the stress levels of cows.

As such, this list provides a snapshot of the VoF’s main projects in viticulture, fruit production, sensory science and animal science. Nevertheless, the end-goal remains, and that is for these solutions to be transferable to all fields of agriculture.

Remote Sensing Figure 3
A diagram representing how UAVs and remote sensing can be used to detect smoke contamination in vineyards (Fuentes & Tongson, 2017).


Baofeng, S., Jinru, X., Chunyu, X., Yulin, F., Yuyang, S. and Fuentes, S., 2016. Digital surface model applied to unmanned aerial vehicle based photogrammetry to assess potential biotic or abiotic effects on grapevine canopies. International Journal of Agricultural and Biological Engineering, 9(6), p.119.

Fuentes, S. and De Bei, R., 2016. Innovations and technology: Advances of the Vineyard of the Future initiative in viticultural, sensory science and technology development. Wine & Viticulture Journal, 31(3), p.53.

Fuentes, S. and Tongson, E., 2017. Vinyard technology: Advances in smoke contamination detection systems for grapevine canopies and berries. Wine & Viticulture Journal, 32(3), p.36.

NASA, 2017. Scientific Visualization Studio. [Online] Available at: [Accessed 11 December 2017].



The Vineyard of the Future is flying with Qantas!

Be it during takeoff, in the lounge, or online, with Qantas’ Qbusiness coverage on “wine boffins” this month, all you need is five good minutes to understand what The Vineyard of the Future is doing for the wine industry.


From digital vineyards using drones and its MUASIP platform to monitor vast vineyard and other crop fields, to easy-to-use apps like VitiCanopy, that will instantly analyse canopy architecture, the effect of vineyard leaf canopies on the quality of grape and yields, the “holy grail for winemakers” is not out of reach (Nicholls, 2017). And if your vineyard happens to have a canine member, they could join you in the field to detect pests and diseases, as “man’s best friend” has the ability to sniff out the “bad” pheromones from insects up to 60 centimetres deep in the soil (Fuentes & De Bei, 2016).

But most importantly, as Dr Sigfredo Fuentes, Senior Lecturer in Wine Science at the School of Agriculture and Food, belonging to the Faculty of Veterinary and Agriculture from the University of Melbourne, has reiterated, “the end goal is the incorporation of technology in food security”, especially in the face of climate change.

Qantas_Wine boffin article
Qantas Spirit of Australia’s Qbusiness section on The Vineyard of the Future.


Nicholls, J. (2017). The Data Revolution – Wine Boffins. Qantas Spirit of Australia. [online] November 2017, p. 118. Available at: [Accessed 4 Nov. 2017].

Fuentes, S. and De Bei, R., 2016. Innovations and technology: Advances of the Vineyard of the Future initiative in viticultural, sensory science and technology development. Wine & Viticulture Journal, 31(3), p.53.


Networked Society Symposium 2017: Today for Tomorrow – Interdisciplinary research for a sustainable future

“The science of today is the technology of tomorrow.”

– Edward Teller

If you googled Teller, you would find some controversial facts. However, that aside, Teller did capture, in his quote, the “power” that science has in shaping the world we live in tomorrow. A world that is increasingly, or might I say, already, immersed in technology. But “with great power comes great responsibility”, and it is in this light that the Networked Society Symposium 2017 (NSS’17) kicked off.

Morning tea during the NSS’17. (Credit: Networked Society Symposium 2017)

The Digital Blue and Environmental Green

As individuals from different fields of research were seated in the B117 Theatre of the Melbourne School of Design, the stage was set for the “celebration” of interdisciplinary research. Interdisciplinary research that would have positive impacts and practical applications. As Professor Luciano Floridi, Director of the Digital Ethics Lab at Oxford Internet Institute, articulated, we, as the current generation, have the responsibility to build the foundations of a future society that future generations will be thankful for.

With the digital world, the features of our reality are being coupled, decoupled, and recoupled, or as we more commonly say, using the more “charged” term, disrupted. An example would be the decoupling of location and presence (Floridi, 2017). Whilst you physically enjoy a glass of Sauvignon Blanc at home, your interactions are with other users on a Facebook wine club page. Thus, your location is in Melbourne, but your presence is online, and your reach is global. This is just a simple example of how technology is “cleaving” at the features of our reality.

However, as we delved deeper “into the seeds of time”, it has not just been the clear-cut prediction of “which grain will grow and which will not” (Macbeth, 1.3.159-162). Instead, the “weeds’ of uncertainty and challenges have also surfaced. Predominantly, the deterioration of our environment in the face of climate change, and how we would shape our digital world with it. As such, how can we nurture the desirable and neutralise the undesirable?

Nurturing the desirable: Urban Green Spaces

With climate change, Australia is experiencing more frequent and hotter “hot days”, with heat waves increasing in duration, frequency, and intensity (CSIRO & Bureau of Meteorology, 2015). As such, Urban Green Spaces have become crucial in cooling urban heat islands and providing refuge against harmful air pollutants or the “concrete jungle” itself.

At NSS’17, interdisciplinary research on Urban Green Spaces involved technologies such as sensor networks, remote sensing cameras, and social media. Sensor networks were able to detect “microclimate” changes in temperature, humidity, and solar radiation, between grey (concrete) and green (greenery) areas. Furthermore, remote sensing cameras, mounted onto vehicles, yielded real-time thermal and visible images, that would be used in monitoring tree-health in city centres. And with social media, an analysis of positive and negative sentiments “tweeted” by Twitter users at existing Urban Green Spaces, indicated the influence of these spaces on human wellbeing. Thus, with these, the existence of Urban Green Spaces can be justified as beneficial, and the nurturing of desirable designs can be enhanced and propagated effectively alongside urbanisation.

Nurturing the desirable: Digital Vineyards

Besides Urban Green Spaces, interdisciplinary research has also yielded how technology can transform the agriculture industry for the better. This is seen in the development of “digital vineyards” to combat smoke contamination in vineyards as a result of increased bush fires in Victoria, Australia. With bush fires now occurring from October to March, smoke contamination in vineyards are on the rise. And with the accumulation of smoke-related compounds, known as guaiacol glycoconjugates, in grapes, these compounds are resulting in undesirable aromas and flavours in wine, thereby reducing their value (Fuentes & Tongson, 2017).

Dr Sigfredo Fuentes putting the use of “digital vineyards” into context. (Credit: Networked Society Symposium 2017)

As such, by combining the use of Unmanned Aerial Vehicles (UAVs) and remote sensing with agricultural science, real-time Infrared Thermography Imaging (IRTI) would be able to recognise smoke contaminated vineyard canopies by detecting pattern changes in leaf conductance. The presence of smoke-related compounds in berries could also be detected using non-invasive Near Infrared Spectroscopy (NIR), which determines the composition of berries. Thus, as Dr Sigfredo Fuentes, Senior Lecturer in Wine Science at the University of Melbourne, presented, smoke-contaminated areas could be mapped and differential harvesting could occur.

Remote Sensing Figure 3
A diagram representing how UAVs and remote sensing can be used to detect smoke contamination in vineyards (Fuentes & Tongson, 2017).

Neutralising the undesirable: Getting it “right”

Whilst digital vineyards are viewed as a solution to bush fire smoke contamination, other areas of fundamental industries, such as law, are facing “warning signs” of undesirable outcomes. Particularly in “how” we will regulate the access to law without the actual access to lawyers. And with the adoption of open data, “how” we will adapt to the use of it, especially with increasing concerns over data privacy.

But if done “right”, in terms of enhancing the “human” in our digital projects, whereby the technologies we build are “open, tolerant, equitable, just, and supportive” for both humans and the environment to flourish, the digital world can be for the better (Floridi, 2017). And as I once asked an 83 year old man on “what not to do in life”, he quoted Charles Dickens’ “a heart that never hardens, a temper that never tires, and a touch that never hurts”. Perhaps what we need then, is technology that would never harden our humanity, nor tire ourselves from bettering our designs, and most importantly, technology that would never hurt ourselves. With this, the NSS’17 concluded with the mindset for design to be for the long-term sustainability of humans in the digital world.


Floridi, L. Philos. Technol. (2017) 30: 123.

CSIRO and Bureau of Meteorology 2015, Climate Change in Australia Information for Australia’s Natural Resource Management Regions: Technical Report, CSIRO and Bureau of Meteorology, Australia

Fuentes, S. and Tongson, E., 2017. Vineyard technology: Advances in smoke contamination detection systems for grapevine canopies and berries. Wine & Viticulture Journal, 32(3), p.36.

New Paper: Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and artificial neural networks modelling techniques


Claudia Gonzalez Viejo 1, Sigfredo Fuentes 1*, Damir Torrico1, Kate Howell1, and Frank R. Dunshea1.

1 University of Melbourne, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, VIC 3010, Australia

* Correspondence:; Tel.: +61 3 9035 9670

Journal of The Science of Food and Agriculture

Full Article: CLICK HERE


Beer quality is mainly defined by its color, foamability and foam stability, which are influenced by the chemical composition of the product such as proteins, carbohydrates, pH and alcohol. Traditional methods to assess specific chemical compounds are usually time-consuming and costly. This study used rapid methods to evaluate 15 foam and color-related parameters using a robotic pourer (RoboBEER) and chemical fingerprinting using near infrared spectrometry (NIR) from six replicates of 21 beers from three types of fermentation. Results from NIR were used to create partial least squares regression (PLS) and artificial neural networks (ANN) models to predict four chemometrics such as pH, alcohol, Brix and maximum volume of foam.


Why there are more and bigger bushfires?: Smoke Taint in Berries and Wine, What can we do about it?

Non-invasive smoke-taint detection in berries from grapevine (Vitis vinifera L.) using near infrared spectroscopy and machine learning models

I have been spending some whole nighters working on this topic due to recent news about extensive bush fires in Chile and in New South Wales, in January and February 2017 respectively. Both of these events have been named by the media as the biggest bush fire events in their respective histories. In Chile, the majority of the bush fires were in the central part of Chile, coincidentally to the majority of grapevine plantations. We do know that smoke taint has the biggest effect on berry contamination after veraison (7 days after on-set), which was about the timing of bushfires for a few cultivars for both Chile and NSW.



A recent report (February 2017) from the Victorian Government – Australia, has concluded that bush fires will increase severity and the window of opportunity due to climate change, specifically due to increases in temperature, increased frequency and intensity of heat waves and drought events.


So, what can we do about it?

As said before, I started to dig up some data from an ARC – Linkage project in which I worked as part of a team from The University of Adelaide. In that project we smoked artificially a number of cultivars to see the physiological effects of smoke contamination. From the canopy perspective and stomatal conductance, to be more specific, this effect can be explained through the chemical reaction between the main compounds found in smoke: carbon dioxide (CO2) and carbon monoxide (CO) and water. When getting in contact with stomata, smoke gases they can pass to the sub-stomata cavity, which is at 100% relative humidity. These compounds are then mixed with water forming carbonic acid (H2CO3) which reduced pH (acidic) hence close stomata.

This effect was reported in a poster in which I did a model to detect this effect on stomata conductance to discriminate canopies that have been contaminated or not with smoke. See posting by clicking here. The models worked really well for all the cultivars studied but Sauvignon blanc. I did attributed this effect to the morphology of leaves for this cultivar, which have high pubescence in the abaxial side. My hypothesis was that this offers a barrier to smoke, which can explain the inefficiency of the model based on the lack of stomatal conductance reduction.

I am currently working in the development of these models considering the top of canopies to apply them using infrared thermal imagery from Unmanned Aerial Vehicles (UAV), which can map a whole vineyard in the days after a bush fire event.

After the bush fires in Chile, I have revisited the Near Infrared (NIR) data from berries to see whether I was able to generate machine learning models to detect smoke taint in berries triggering the instrument around the skin and then measuring also in halved berries. The instrument that we used was a ASD FieldSpec® 3, Analytical Spectral Devices, Boulder, Colorado, USA. Which measures in the range of 350 – 1880 nm.


I have decided to concentrate the models in the700 – 1100 nm range using the second derivative of data, since it is the range of inexpensive NIR instrumentation. Also, after analysis of the rest of the wavelength range, the improvements of models obtained did not justified the jump in price of instrumentation from around $2,000 – $3000 to $38,000 – $65,000.

I did obtain three interesting models, the first was to detect whether the berries measured in a bunch have been contaminated or not using Artificial Neural Networks. I tried with data from whole and half berries and surprisingly I got better results with full berries. This is important since it renders the methodology as non-invasive. And makes sense when reading reports which found that the majority of glycocongugates are found in the skin of berries, which are higher than the pulp and higher that those found in seeds.


Then I tried models using machine learning fitting algorithms to see whether I could predict the levels of glycocongugates in the berries (whole):


And finally, whether I was able to predict smoke taint compounds in the wine made with contaminated and non contaminated berries, such as guaiacol, Syringol and cresols:



These are very exciting preliminary results which I am in the process of writing up for a peer review publication. The best thing is that if measurements made in the field are associated to GPS tagging, this could produce a contamination map using simple kriging interpolation techniques. This tool can support the decision making process towards differential harvest to avoid contaminating the whole production and salvaging fruit that has not been contaminated to the levels of spoilage. It offers also alternatives for winemaking to avoid excessive crushing and fermentation with skins that could contribute to the increase of smoke taint compounds in the final wine. Decisions can also be made by assessing the timing of ageing in barrels and whether it is required at all. And obviously, making non-contaminated wine using non-contaminated fruit. As can be seen in my preliminary results, the model for glycocongugates rendered a 10% error, which by quantifying the levels of smoke taint compounds does not make much difference in the final wine and it may contribute even to increased organoleptic characteristics with tones of leather, wood, bacon, etc

Something to look forward after all these tragedies.

Dr Sigfredo Fuentes

The University of Melbourne