GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 Machines and fire: developing a rapid detection system for grapevine smoke contamination using NIR spectroscopy and machine learning modelling

Machines and fire: developing a rapid detection system for grapevine smoke contamination using NIR spectroscopy and machine learning modelling

Abstract

Context and purpose of the study – Bushfires are a common occurrence throughout Australia and their incidence is predicted to both rise and increase in severity due to climate change. Many of these bushfires occur in areas close to wine regions, which receive different levels of exposure to smoke. Wine produced from smoke-affected grapes are characterised by unpalatable smoky aromas such as “burning rubber”, “smoked meats” and “burnt wood”. These smoke tainted wines are unprofitable and result in significant financial losses for winegrowers. This study investigated the use of near-infrared (NIR) spectroscopy and machine learning (ML) modelling for the rapid and non-destructive detection of grapevine smoke exposure by analysing grapevine leaves and/or grape berries.

Materials and methods – The trial was conducted during the 2018/2019 season at the University of Adelaide’s Waite campus in Adelaide, South Australia (34° 58’ S, 138° 38’ E) and involved the application of five different smoke and water misting treatments to Cabernet Sauvignon grapevines at approximately seven days post-veraison. Treatment vines were exposed to straw-based smoke for one hour under experimental conditions described previously by Kennison et al. (2008) and Ristic et al. (2011). Near-infrared (NIR) measurements were then taken from berries and leaves a day after smoking using the microPHAZIR TM RX NIR Analyser (Thermo Fisher Scientific, Waltham, USA) which has a spectral range of 1600-2396 nm. The NIR spectra were then used as inputs to train different ML algorithms, which resulted in two artificial neural networks (ANNs) with the best classification performance for either berry or leaf readings according to the different smoke treatments.

Results – Both ANN models found were able to correctly classify the leaf and berry spectral readings with high accuracy. The leaf model had an overall accuracy of 95.2%, 97.7% accuracy during training with a mean square error (MSE) 0.0082, 90.9% during validation with a MSE of 0.0353 and 88.1% during the testing stage with a MSE of 0.0386, while the berry model had an overall accuracy of 91.7%, 95.2% accuracy during training with a MSE of 0.0173, 86.4% during validation with a MSE of 0.0560 and 80.2% during the testing stage with a MSE of 0.0560. These results showed the potential of developing a rapid, non-destructive, in-field detection system for assessing grapevine smoke contamination following a bushfire using NIR spectroscopy and artificial neural network modelling.

DOI:

Publication date: September 28, 2023

Issue: GiESCO 2019

Type: Poster

Authors

Vasiliki SUMMERSON, Claudia GONZALEZ VIEJO, Damir TORRICO, Sigfredo FUENTES*

The University of Melbourne, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, Parkville 3010, Victoria, Australia

Contact the author

Keywords

bushfires, machine learning, smoke taint, climate change, non-destructive

Tags

GiESCO | GiESCO 2019 | IVES Conference Series

Citation

Related articles…

VineyardFACE: Investigation of a moderate (+20%) increase of ambient CO2 level on berry ripening dynamics and fruit composition

Climate change and rising atmospheric carbon dioxide concentration is a concern for agriculture, including viticulture. Studies on elevated carbon dioxide have already been on grapevines, mainly taking place in greenhouses using potted plants or using field grown vines under higher CO2 enrichment, i.e. >650 ppm. The VineyardFACE, located at Hochschule Geisenheim University, is an open field Free Air CO2 Enrichment (FACE) experimental set-up designed to study the effects of elevated carbon dioxide using field grown vines (Vitis vinifera L. cvs. Riesling and Cabernet Sauvignon). As the carbon dioxide fumigation started in 2014, the long term effects of elevated carbon dioxide treatment can be investigated on berry ripening parameters and fruit metabolic composition. The present study aims to investigate the effect on fruit composition under a moderate increase (+20%; eCO2) of carbon dioxide concentration, as predicted for 2050 on both Riesling and Cabernet Sauvignon. Berry composition was determined for primary (sugars, organic acids, amino acids) and secondary metabolites (anthocyanins). Special focus was given on monitoring of berry diameter and ripening rates throughout three growing seasons. Compared to previous results of the early adaptative phase of the vines [1], our results show little effect of eCO2 treatment on primary metabolites composition in berries. However, total anthocyanins concentration in berry skin was lower for eCO2 treatment in 2020, although the ratio between anthocyanins derivatives did not differ. [1] Wohlfahrt Y., Tittmann S., Schmidt D., Rauhut D., Honermeier B., Stoll M. (2020) The effect of elevated CO2 on berry development and bunch structure of Vitis vinifera L. cvs. Riesling and Cabernet Sauvignon. Applied Science Basel 10: 2486

Combining effect of leaf removal and natural shading on grape ripening under two irrigation strategies in Manto negro (Vitis vinifera L.)

The increasingly frequent heat waves during grape ripening pose challenges for high quality wine grape production. Defoliation is a common practice that can improve the control of diseases in bunches, but also it increases the exposure to sunlight. Grapes exposed to solar radiation reach temperatures over the optimum for berry development and maturation. This makes the development of irrigation and canopy management techniques of great importance to maximize yield and grape quality. A field experiment was carried out during 2021 using Manto negro wine grapes to study the effect of applied irrigation and different light exposure levels on grape quality. Two irrigation treatments were imposed based on the frequency and amount of water doses in a four-block experimental vineyard at Bodega Ribas (Mallorca). Three light exposure treatments were randomly applied in each irrigation plot. The light treatments included exposed clusters from pea size, non-exposed clusters, and shaded clusters after softening. Leaf area index and canopy porosity was estimated every 2 weeks. Midday leaf water potential was measured weekly. Additionally, apparent electrical conductivity was measured between rows to estimate the soil water content variability. Light and temperature sensors were installed at the bunch level to quantify the differences in bunch temperature and light intensity among treatments. The effect of irrigation and cluster light exposure on berry weight, TSS, TA, malic acid, tartaric acid, K+, and pH were analysed at 5 moments along grape ripening. During different heat waves, the natural shading technique decreased the maximum bunch temperature around 10 °C respect to the exposed bunches in both irrigation strategies. The combination of defoliation and shading techniques after softening decreased TSS at harvest and affected most of the quality parameters during the last stages of ripening, showing an interesting technique to delay ripening in warm viticulture areas.

Late frost protection in Champagne

Probably one of the most counterintuitive impacts of climate change on vine is the increased frequency of late frost. Champagne, due to its septentrional position is historically and regularly affected by this meteorological hazard. Champagne has therefore developed a strong experience in frost protection with first experiments dating from the end of 19th century. Frost protection can be divided in two parts: passive and active. Passive protection includes all the methods that do not seek to modify the vine’s environment or resistance at the time of frost. The most iconic passive protection in Champagne is the establishment of the individual reserve. This reserve allows to stock a certain quantity of clear wine during a surplus year to compensate a meteorological hazard like frost during the following years. Other common passive methods are the control of planting area (walls, bushes, topography), the choice of grape variety, late pruning, or the impact of grass cover and tillage. Active frost protection is also divided in two parts. Most of the existing techniques tend to modify vine’s environment. Most of the time they provide warmth (candles, heaters, windmills, heating cables…), or stabilise bud’s temperature above a lethal threshold (water sprinkling). The other way to actively fight is to enhance the resistance of buds to frost (elicitors). The Comité Champagne evaluates frost protection methods following three main axes: the efficiency, the profitability, and the environmental impact through a lifecycle assessment. This study will present the results on both passive and active protection following these three axes.

A predictive model of spatial Eca variability in the vineyard to support the monitoring of plant status

[lwp_divi_breadcrumbs home_text="IVES" use_before_icon="on" before_icon="||divi||400" module_id="publication-ariane" _builder_version="4.19.4" _module_preset="default" module_text_align="center" module_font_size="16px" text_orientation="center"...

Influence of climatic conditions on grape composition of Tempranillo in La Mancha DO (Spain)

The aim of this work was to analyze the variability in grape composition of the Tempranillo cultivar related to climatic conditions, in La Mancha Designation of Origin. Grape composition (sugar content, total acidity, pH, malic acid, and total and extractable anthocyanins) recorded during ripening, were analysed for the period 2000-2019. The weather conditions at daily time scale, recorded during the same period, were also evaluated. The relationships between grape parameters with climatic variables related to temperature and to water deficits, referring different periods between phenological events along the growing cycle, were evaluated using regression analysis. High variability in grape composition was observed in the period analysed. Total acidity varied between 3.7 and 7.3 gL-1 while malic acid varied between 1.2 and 4 gL-1. The extractable anthocyanins ranged between 526 and 972 mgL-1, and total anthocyanins ranged between 922 and 1388 mgL-1, being the lowest values recorded in the hottest year (2017). Total acidity decreased 0.77 gL-1 for an increase of 100 GDD, while malic acid decrease in 0.42 gL-1 for the same GDD increase, being the period between veraison and harvest the one that seemed to have higher influence on acidity. In addition, it was confirmed that increasing water deficits decreased acidity. Total and extractable anthocyanins increased in about 210 and 105 mgL-1, respectively, with an increase of 100 GDD from veraison to harvest, and the increase in water deficits favour the increase of anthocyanins, both total and extractable anthocyanins. Total and extractable anthocyanins concentration increased in 35 and 22 mgL-1 per an increase of 10 mm in the water deficit. These results can be of interest to understand the potential changes that grapes composition may suffer under future warmer climates.