{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T20:59:59Z","timestamp":1777669199599,"version":"3.51.4"},"reference-count":25,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2019,7,30]],"date-time":"2019-07-30T00:00:00Z","timestamp":1564444800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["LP0989138"],"award-info":[{"award-number":["LP0989138"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Bushfires are becoming more frequent and intensive due to changing climate. Those that occur close to vineyards can cause smoke contamination of grapevines and grapes, which can affect wines, producing smoke-taint. At present, there are no available practical in-field tools available for detection of smoke contamination or taint in berries. This research proposes a non-invasive\/in-field detection system for smoke contamination in grapevine canopies based on predictable changes in stomatal conductance patterns based on infrared thermal image analysis and machine learning modeling based on pattern recognition. A second model was also proposed to quantify levels of smoke-taint related compounds as targets in berries and wines using near-infrared spectroscopy (NIR) as inputs for machine learning fitting modeling. Results showed that the pattern recognition model to detect smoke contamination from canopies had 96% accuracy. The second model to predict smoke taint compounds in berries and wine fit the NIR data with a correlation coefficient (R) of 0.97 and with no indication of overfitting. These methods can offer grape growers quick, affordable, accurate, non-destructive in-field screening tools to assist in vineyard management practices to minimize smoke taint in wines with in-field applications using smartphones and unmanned aerial systems (UAS).<\/jats:p>","DOI":"10.3390\/s19153335","type":"journal-article","created":{"date-parts":[[2019,7,30]],"date-time":"2019-07-30T11:15:56Z","timestamp":1564485356000},"page":"3335","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0377-5085","authenticated-orcid":false,"given":"Sigfredo","family":"Fuentes","sequence":"first","affiliation":[{"name":"School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia"}]},{"given":"Eden Jane","family":"Tongson","sequence":"additional","affiliation":[{"name":"School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia"}]},{"given":"Roberta","family":"De Bei","sequence":"additional","affiliation":[{"name":"School of Agriculture, Food and Wine, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9207-9307","authenticated-orcid":false,"given":"Claudia","family":"Gonzalez Viejo","sequence":"additional","affiliation":[{"name":"School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6056-9325","authenticated-orcid":false,"given":"Renata","family":"Ristic","sequence":"additional","affiliation":[{"name":"School of Agriculture, Food and Wine, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia"}]},{"given":"Stephen","family":"Tyerman","sequence":"additional","affiliation":[{"name":"School of Agriculture, Food and Wine, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6724-9837","authenticated-orcid":false,"given":"Kerry","family":"Wilkinson","sequence":"additional","affiliation":[{"name":"School of Agriculture, Food and Wine, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,30]]},"reference":[{"key":"ref_1","unstructured":"Hughes, L., and Alexander, D. (2019, July 10). Climate Change and the Victoria Bushfire Threat: Update 2017. Available online: http:\/\/www.climatecouncil.org.au\/uploads\/98c26db6af45080a32377f 3ef4800102.pdf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1038\/nclimate1417","article-title":"Earlier wine-grape ripening driven by climatic warming and drying and management practices","volume":"2","author":"Webb","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"99","DOI":"10.3354\/cr00740","article-title":"Climate change and winegrape quality in Australia","volume":"36","author":"Webb","year":"2008","journal-title":"Clim. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1111\/j.1755-0238.2007.tb00247.x","article-title":"Modelled impact of future climate change on the phenology of winegrapes in Australia","volume":"13","author":"Webb","year":"2007","journal-title":"Aust. J. Grape Wine Res."},{"key":"ref_5","first-page":"119","article-title":"Digital surface model applied to unmanned aerial vehicle based photogrammetry to assess potential biotic or abiotic effects on grapevine canopies","volume":"9","author":"Su","year":"2016","journal-title":"Int. J. Agric. Biol. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s40626-016-0054-x","article-title":"Impact of grapevine exposure to smoke on vine physiology and the composition and sensory properties of wine","volume":"28","author":"Ristic","year":"2016","journal-title":"Theor. Exp. Plant Physiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1111\/ajgw.12017","article-title":"Effect of leaf removal and grapevine smoke exposure on colour, chemical composition and sensory properties of Chardonnay wines","volume":"19","author":"Ristic","year":"2013","journal-title":"Aust. J. Grape Wine Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1007\/s00425-018-03079-x","article-title":"Accumulation of volatile phenol glycoconjugates in grapes following grapevine exposure to smoke and potential mitigation of smoke taint by foliar application of kaolin","volume":"249","author":"Munguia","year":"2019","journal-title":"Planta"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"S41","DOI":"10.1111\/j.1755-0238.2011.00148.x","article-title":"Amelioration of smoke taint in wine by reverse osmosis and solid phase adsorption","volume":"17","author":"Fudge","year":"2011","journal-title":"Aust. J. Grape Wine Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1111\/j.1755-0238.2012.00200.x","article-title":"Amelioration of smoke taint in wine by treatment with commercial fining agents","volume":"18","author":"Fudge","year":"2012","journal-title":"Aust. J. Grape Wine Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"S22","DOI":"10.1111\/j.1755-0238.2011.00147.x","article-title":"Comparison of methods for the analysis of smoke related phenols and their conjugates in grapes and wine","volume":"17","author":"Wilkinson","year":"2011","journal-title":"Aust. J. Grape Wine Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1016\/j.foodchem.2010.11.094","article-title":"Quantitative analysis of glycoconjugate precursors of guaiacol in smoke-affected grapes using liquid chromatography\u2013tandem mass spectrometry based stable isotope dilution analysis","volume":"126","author":"Dungey","year":"2011","journal-title":"Food Chem."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1021\/jf305025j","article-title":"Assessing the impact of smoke exposure in grapes: Development and validation of a HPLC-MS\/MS method for the quantitative analysis of smoke-derived phenolic glycosides in grapes and wine","volume":"61","author":"Hayasaka","year":"2012","journal-title":"J. Agric. Food Chem."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1021\/jf203849h","article-title":"Classification of smoke tainted wines using mid-infrared spectroscopy and chemometrics","volume":"60","author":"Fudge","year":"2011","journal-title":"J. Agric. Food Chem."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"7379","DOI":"10.1021\/jf800927e","article-title":"Smoke-derived taint in wine: The release of smoke-derived volatile phenols during fermentation of Merlot juice following grapevine exposure to smoke","volume":"56","author":"Kennison","year":"2008","journal-title":"J. Agric. Food Chem."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1007\/s00271-012-0375-8","article-title":"Computational water stress indices obtained from thermal image analysis of grapevine canopies","volume":"30","author":"Fuentes","year":"2012","journal-title":"Irrig. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2249","DOI":"10.1093\/jxb\/erf083","article-title":"Use of infrared thermography for monitoring stomatal closure in the field: Application to grapevine","volume":"53","author":"Jones","year":"2002","journal-title":"J. Exp. Bot."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/S0034-4257(97)00045-X","article-title":"Opportunities and limitations for image-based remote sensing in precision crop management","volume":"61","author":"Moran","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/S0168-1923(99)00030-1","article-title":"Use of infrared thermometry for estimation of stomatal conductance as a possible aid to irrigation scheduling","volume":"95","author":"Jones","year":"1999","journal-title":"Agric. For. Meteorol."},{"key":"ref_20","unstructured":"Beale, M.H., Hagan, M.T., and Demuth, H.B. (2018). Deep Learning Toolbox User\u2019s Guide, The Mathworks Inc."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Gonzalez Viejo, C., Torrico, D.D., Dunshea, F.R., and Fuentes, S. (2019). Development of Artificial Neural Network Models to Assess Beer Acceptability Based on Sensory Properties Using a Robotic Pourer: A Comparative Model Approach to Achieve an Artificial Intelligence System. Beverages, 5.","DOI":"10.3390\/beverages5020033"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1016\/j.scitotenv.2017.07.158","article-title":"Application of thermography for monitoring stomatal conductance of Coffea arabica under different shading systems","volume":"609","author":"Craparo","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.agwat.2017.03.030","article-title":"Assessing a crop water stress index derived from aerial thermal imaging and infrared thermometry in super-high density olive orchards","volume":"187","author":"Egea","year":"2017","journal-title":"Agric. Water Manag."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.compag.2018.06.035","article-title":"Automated grapevine cultivar classification based on machine learning using leaf morpho-colorimetry, fractal dimension and near-infrared spectroscopy parameters","volume":"151","author":"Fuentes","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2285","DOI":"10.1016\/j.proeng.2012.01.302","article-title":"Study on the best analysis spectral section of NIR to detect alcohol concentration based on SiPLS","volume":"29","author":"Wang","year":"2012","journal-title":"Procedia Eng."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/15\/3335\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:11:03Z","timestamp":1760188263000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/15\/3335"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,30]]},"references-count":25,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2019,8]]}},"alternative-id":["s19153335"],"URL":"https:\/\/doi.org\/10.3390\/s19153335","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,30]]}}}