School of Agriculture, Food and Ecosystem Sciences - Theses
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ItemFinding the hidden smoke: Exploring the use of digital technologies for assessing grapevine smoke contamination and taint in grapes and wine( 2021)Grapevine smoke contamination and the subsequent development of smoke taint in wine has resulted in significant financial losses for winemakers throughout the world. Unfortunately, the incidence of grapevine smoke exposure is expected to rise as the number and intensity of wildfires increase due to the effects of climate change. Wines produced from smoke affected grapes are characterised by unpleasant smoky aromas, rendering them unpalatable and therefore unprofitable. Traditionally, chromatographic techniques such as gas chromatography-mass spectrometry (GC-MS) and high-performance liquid chromatography (HPLC) have been used for assessing the levels of smoke-derived volatile phenols and their glycoconjugates in grapes and wine. However, these methods are time consuming, expensive and require destructive sample preparation as well as the use of trained personnel. Furthermore, sensory evaluation of wine samples using human panels may be subject to bias due to individual variability of the participants, as well as being expensive and time consuming as large groups of participants must be recruited and trained. In addition to this, a number of methods have been identified for ameliorating smoke taint in wine such as the use of activated carbon and reverse osmosis. While effective at reducing levels of volatile phenols for smoke taint amelioration, they are unable to act on glycoconjugates, and therefore a gradual resurgence of smoky aromas may arise as these glycoconjugates are hydrolysed back into their free active forms over time. This research therefore investigated alternative methods for assessing the degree of grapevine smoke exposure and the level of smoke taint in wine using digital technologies coupled with machine learning (ML) modelling based on artificial neural networks (ANN), and whether the use of a cleaving enzyme prior to the addition of activated carbon could be effective at ameliorating smoke taint in wine. Near-infrared (NIR) spectroscopy was used to obtain a chemical fingerprint of grape berries, leaves, must and wine. These readings were then used as inputs to develop ANN models that showed high accuracy in the classification of berries and leaves according to the level of smoke exposure and degree of taint (97% – 98%), as well as predicting the levels of smoke-derived volatile phenols and their glycoconjugates in grapes, must and wine (R = 0.98 – 0.99). Additionally, models predicting consumer responses towards smoke tainted wines using NIR berry and wine spectral readings were created which displayed high accuracy in their predictive abilities (R = 0.97 – 0.98). The results demonstrated that NIR spectroscopy coupled with ML modelling can provide accurate, rapid and non-destructive tools for assessing grapevine smoke contamination and smoke taint in wine, in addition to predicting the sensory responses of consumers towards smoke tainted wines. Furthermore, the models developed can be used together to form an integrated smoke taint detection system that growers and winemakers can use in-field or in the winery to assess grapes and wine. A low-cost electronic nose (E-nose) was used to assess the aroma potential of smoke-tainted wines. Readings from the e-nose were used as inputs to develop ML models that showed high accuracy in predicting the levels of eight volatile aromatic compounds in wine (R = 0.99), the degree of smoke aroma intensity (R = 0.97). These two models may be used together with previously developed models that predict the levels of smoke-derived volatile phenols and their glycoconjugates and 12 wine descriptors to provide winemakers with a greater picture of the degree of smoke taint and the aroma profiles of smoke-tainted wines. In addition to this, the use of a cleaving enzyme (ZIMAROM, Enologica Vason) prior to treatment with activated carbon was found to be effective in ameliorating smoke taint and may help delay the resurgence of smoky aromas by hydrolysing glycoconjugates into their free volatile phenol forms which can then be removed by the addition of activated carbon. An ANN model displaying high accuracy (98%) was also developed using the readings from the e-nose to classify wine samples according to the type of smoke-taint amelioration treatment applied to assess their effectiveness. The model may offer winemakers a cost-effective, non-destructive, rapid, and accurate tool to assess the effectiveness of smoke taint amelioration treatment by activated carbon with/without the addition of a cleaving enzyme.
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ItemThe role of climate and tree nutrition on the occurrence of the southern greater glider (Petauroides volans) and its implications for conservation planning( 2021)The southern greater glider (Petauroides volans) is southeastern Australia’s largest gliding marsupial and widely distributed, but the species has recently experienced drastic declines in population numbers. Its association with hollow-bearing trees, used for nesting, has made it an important flagship species for the conservation of old-growth forest ecosystems. Stand replacing or altering wild- or planned fires and timber harvesting have been identified as major threats to the greater glider, but individuals and populations have over time disappeared from areas that have experienced neither, raising questions about the role of other factors in their decline. Habitat suitability is determined by three distinct factors: A narrow thermotolerance makes greater gliders vulnerable to high ambient temperatures. A specialised diet consisting entirely of nutrient-rich Eucalyptus leaves confines them to certain forest types and the need for multiple large tree hollows for denning confines populations to mature forests. Therefore, different spatial scales need to be considered when determining likelihood of occupancy and habitat suitability for greater gliders. Using high spatial and temporal resolution climate data, I identified that climate is driving greater glider occupancy across the landscape. At a stand scale, I developed new methods of remotely sensing feeding and nesting resources using field sampling and multispectral imagery collected by an unoccupied aerial vehicle (UAV). My findings have important implications for greater glider management and conservation of their habitat and associated forest types. At the landscape scale, I identified climatic refugia that may allow greater gliders to persist into a future under climate change if properly protected. At a stand scale, remotely sensed estimates of feeding and nesting resources may enable forest managers to better retain highly suitable habitat or assess remaining habitat suitability and likelihood of persistence after disturbance. The gathered knowledge enables us to spatially extrapolate field observations and model findings to test how different landscape, resource and disturbance configurations affect population density and persistence, which should further enhance our ability to protect southern greater gliders in southeastern Australia.