ARTICLES

 

Winery On-site Assessment of Grapevine Bunch Rot: In Pursuit of Sustainable Practices

 

 

Cornelissen R.J.^{I, III}; Aleixandre Tudo J.L.^{II, IV}; Nieuwoudt H.H.^{I, *}

^ISouth African Grape and Wine Research Institute, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa
^IIDepartment of Viticulture and Oenology, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa
^IIINamaqua Wines, P.O. Box 75, Vredendal, 8160, South Africa
^IVInstituto de Ingeniería de Alimentos para el Desarrollo (IIAD), Departamento de Tecnología de Alimentos (DTA), Unversitat Politecnica de Valencia (UPV), Valencia, Spain

 

 

---

ABSTRACT

Producer wineries are responsible for processing 75 % of South Africa's annual wine grape production. A characteristic of producer wineries is the processing of large volumes of wine grapes, thus incorporating enormous variability in grape quality, which includes the presence of grapevine bunch rots. Grapevine bunch rots are detrimental to grape and wine quality. The "Introduction" provides background information on the industrial working conditions at producer wineries and the economic effect of rot on wine production. The next two sections discuss the principal reasons for bunch rot being an inevitable part of grape production, namely cultivar susceptibility and climatic conditions. The challenges regarding grapevine bunch rot assessment, specifically concerning producer wineries or wineries processing large amounts of grapes, are set out in "Assessing rot intensity". Representative sampling, mechanical harvesting of grapes and visual evaluation are discussed from an industrial perspective. The last section of this review focuses on the quest for sustainable appraisal of grapevine bunch rot. Infrared spectroscopy (IR) could provide a sustainable option for objectively assessing rot on-site at producer wineries. However, even with the availability of plenty of spectroscopic methods and the demonstrated potential of IR spectroscopy for rapid assessment of grapevine bunch rot, these methods are yet to be applied routinely under industrial working conditions.

Keywords: Producer winery, botrytis rot, sour rot, wine quality, rot assessment, severity, winery intake, sustainability, infrared spectroscopy

---

 

 

INTRODUCTION

Industrial scenarios at large producer wineries

Currently, South Africa has 43 producer wineries responsible for processing 75 % or 1 094 000 tonnes of South Africa's annual wine grape production (SAWIS, 2021). A producer winery, also referred to as a producer cellar, is defined as "a role player or entity where grapes are received and processed on behalf of a group of wine grape producers, its members, into wine grape products and the marketing thereof as packaged or bulk" (SAWIS, 2021). Globally, producer wineries account for one-quarter to one-third of global wine production, with well-known winery examples in France, Italy, Spain, Germany, and South Australia (Bezuidenhout, 2014).

A unique characteristic of producer wineries is the scale of production associated with processing large volumes of wine grapes. Thirty-two of South Africa's producer wineries process more than 10 000 tonnes per annum (SAWIS, 2021), but processing could amount to as much as 60 000 tonnes per annum at a single premise. Producer wineries arguably have advantages in the cost-effectiveness of operational costs due to economy of scale and market competitiveness by guaranteed volume supply to retail. However, the production of large volumes of grapes by many grape growers from commercial vineyards spread out over large surface areas creates significant logistical challenges, primarily related to grape quality control and resulting wine quality.

The producer winery's operational structure usually includes the advisory service of viticulturists, aiming to provide input on vineyard management practices at the farm level and thus manage grape quality according to desired wine style. Reviewed by Steel et al. (2013), the detrimental effect of grapevine bunch rots on grape berry composition and eventual wine quality is well-researched.

Thus, rot assessments are imperative to grape quality control at producer wineries. Constraints in terms of time, cost, and trained assessors required for in-field rot assessments justify consideration of alternatively assessing grape quality at the point at which grapes are delivered on-site at the winery, also referred to as grape or winery intake. Assessing individual grape loads at winery intake would also encompass in-vineyard variability, often overlooked by in-field assessments. It is long known that rot can exist as "pockets" in vineyard blocks (Seem, 1984). Grape (load) assessment at winery intake would also be advantageous if grape transportation by road from farm to winery is needed. Extended travel time and exposure to high temperatures during transport could significantly increase the microbial activity in grape loads (Swanepoel, 2006). In the instance where microbial rot pathogens are already present on the grapes in the vineyard, these travelling conditions could further deteriorate grape quality.

Currently, the parameters assessed at winery intake include sugar concentration (°Brix), pH, total titratable acidity (TA, measured in g/L), temperature (°C) and visual assessment of grape loads for rot and matter other than grapes (MOG). These parameters are limited since they do not account for the detrimental chemical compositional changes in the grape berries brought about by rot. Furthermore, the reported subjectivity and biased nature of visual rot assessments (Hill et al., 2014) often have led to disputes between grape growers and wineries (Longbottom et al., 2013). Logistical challenges during harvest require that producer wineries often employ seasonal workers with minimal knowledge of/or training in the visual assessment of rot in grape loads delivered to the winery. Furthermore, assessments must be done fast and not slow down harvest-related operations, which are hectic at large producer wineries.

Considering that this final grape quality evaluation at winery intake will ascertain grape growers' income, wineries are responsible for ensuring that quality assessment is objective and accurate. However, the presence of rot also has an impact on winery profits.

Economic implications of rot on wine quality

The wide variety of grapevine bunch rots was discussed in a large body of recently published literature (Jackson, 2014; Ioriatti et al., 2015; Steel et al., 2016; Hall et al., 2018; Steel et al., 2018; Gao et al., 2020; Crandall et al., 2022; Kellner et al., 2022). Regarding the economic impact of rot on wine production, it is especially botrytis rot and sour rot that are of concern (Ky et al., 2012; Hall et al., 2018; Molitor et al., 2018). Thus, this review focuses on the deleterious botrytis rot, also referred to as grey rot and sour rot.

The economic impact of rot can already be observed during the early stages of wine production by the significant decrease injuice yield obtained from rot-affected compared to healthy grapes. Sour rot-affected Cabernet Sauvignon grapes with 30 % severity could lead to as much as a 25 % decrease in the volume of grape juice recovered for fermentation (Barata et al., 2011b). Calculating a theoretical scenario: One tonne of healthy grapes provides an average juice yield of 770 L (Price Waterhouse Cooper, 2013), compared to rot-affected grapes, which could decrease the volume of juice recovered per tonne of grapes by as much as 25 %. This would mean that a winery could incur an estimated loss of as much as 40 % in South African rand (ZAR) value for each tonne of rot-affected grapes received compared to healthy grapes (Table 1).

In addition, rot increases wine production costs with specific interventions needed to mitigate the effect of rot on the grape must and wine matrix. For example, the presence of laccase in grape must and wine poses a serious threat to the quality of wine produced. Laccase is an oxidising enzyme produced by Botrytis cinerea, the causative fungi responsible for botrytis rot. Uncontrolled oxidative reactions of phenolic compounds, catalysed by laccase, cause browning and premature ageing of wine (Claus et al., 2014). Processing strategies to reduce laccase activity include short heat treatment of grape must and application of oenological tannins as early as crushing (AWRI, 2023; Vignault et al., 2019, Claus, 2020).

Another processing difficulty with a consequent increase in production costs caused by rot, is the early clogging of filter membranes. Wine filtration removes unwanted particles from the wine and enhances its stability. Decreased filterability is associated with the increased presence of β-glucans in wines (Francioli et al., 1999). Botrytis cinerea produces β-glucans responsible for botrytis rot in wine grapes (Jackson, 2014). Remedial actions include the addition of enzymes responsible for the hydrolysis of glucans to improve the filterability of wines (Jadhav & Gupta, 2016; Espejo, 2021).

However, the detrimental effect of rot on wine quality is primarily associated with the negative impact on wines' sensory properties. Rot could have a detrimental impact on the aroma of grape must and wine due to the following reactions: The laccase-induced oxidation of phenolic aroma compounds, as earlier discussed, the production of detrimental flavours, and the hydrolysis of aromatic grape components. The latter two complications are discussed in the following paragraphs.

Meneguzzo et al. (2008) reported that Gewürztraminer wines made from rot-affected grapes differed significantly from healthy grapes due to the sensory detection of mould flavour and a dominating acetic character in rot-affected wines. Off-flavours regularly associated with rot-affected wines include earthy, mouldy, and fresh mushroom (Steel et al., 2013). Sweet-like honey off-flavours of ethyl phenylacetate and phenylacetic acid are associated with wine produced from sour rot-affected grapes (Barata et al., 2011a). Volatile markers reported for fungal rots include sesquiterpenes, 1,5-dimethylnaphthalene, 2-(4-hexyl-2,5-dioxo-2,5dihydrofuran-3-yl) acetic acid, m-cresol, γ-nonalactone (Schueuermann et al., 2019) and 2-trans-hexenal (Santos et al., 2022).

Besides producing unwanted sensory volatiles, rot can also induce wine aroma losses. Volatile organic compounds (VOCs) are the main contributor to wine aroma (Dudareva et al., 2013). Botrytis rot berry modifications could include the transformation of monoterpenes, the aromatic compounds responsible for the varietal aromas of Muscat cultivars, into less odorous compounds (Rienth et al., 2021). Furthermore, the disappearance of fruity aromas in young wines could be related to the hydrolysis of fatty acids' ethyl esters, which contribute to the fermentation aromas of wine by the esterase activity of Botrytis cinerea. Barata et al. (2011b) suggested that sour rot significantly affects the wine yeast's secondary metabolism, decreasing the levels of volatiles related to fatty acids and amino acid synthesis. Unwanted sensory properties in wine or the loss of varietal character could warrant wine quality downgrades with consequent economic implications for wineries (Table 1).

Furthermore, rot could also influence the food safety aspects of wine via the production of the mycotoxin, ochratoxin A (OTA) (Rousseaux et al., 2014; Welke, 2019; Ubeda et al., 2020). Classified by the International Agency for Cancer Research's (IARC) monographs (1993) in Group 2B as "possibly carcinogenic to humans", OTA levels in wine are regulated (European Commission, 2006). Selected winemaking practices could decrease OTA levels in wine, but these practices could be detrimental to the impact of wine's positive volatile compounds (Gambuti et al., 2005).

 

GRAPE CULTIVAR SUSCEPTIBILITY TO ROT

Over time, an extensive body of literature has developed on wine grape cultivars' natural differences in susceptibility to rot. As an example of ranking cultivars' susceptibility to rot, research by Paňitrur-De La Fuente et al. (2018) is discussed. Based on visual assessment, the in-field susceptibility of 13 wine grape cultivars naturally infected with botrytis rot was compared and classified in relation to fruit maturity under Chile and France's contrasting climate and vineyard practices. Despite differing climatic conditions and vineyard practices, cultivar susceptibility ranking on both sites was similar. High susceptibility to botrytis rot was associated with the cultivars Sauvignon blanc and Gewürztraminer, followed by Chardonnay and Pinot noir. Petit Verdot, Cabernet Sauvignon, Mourvèdre and Syrah were highly resistant to botrytis rot (Panitrur-De La Fuente et al., 2018).

Cultivar characteristics regularly reported as influencing susceptibility to rot include bunch compactness (Hed et al., 2009; Lisek & Lisek, 2021), berry skin traits such as physical berry resistance and cuticle thickness (Herzog et al., 2015). Grapevine breeders consider loose bunch architecture as the most important selection criterium to improve cultivars' resistance to botrytis rot (Herzog et al., 2022). Bunch compactness is defined as the tightness or the spatial arrangement of berries within a bunch (Tello & Ibáñez, 2018). Figure 1 illustrates an example of the difference in bunch compactness amongst cultivars.

Several factors contribute to dense bunches being more susceptible to rot. After flower dehiscent, compact bunches retain more flower debris between berries than more loose bunches leading to rot, for example, by harbouring Botrytis inocula (Hed et al., 2009). Insufficient development of berries' epicuticular wax between compact berries reduces resistance to pathogen attack (Marois et al., 1986). Berries in dense bunches press against each other as berry size increases towards maturity, which could lead to berry rupturing. This injury to the berry skin provides entry for secondary microorganisms while leaking grape juice supplies nutrients that stimulate microbial growth. Berry injuries are considered the primary source of sour rot (Hall et al., 2017; Ioriatti et al., 2018). The dense arrangement of berries could prevent fungicide spray from penetrating between berries and faster drying of bunches after rainfall, leaving a conducive environment for developing rot (Hed et al., 2009). However, Molitor et al. (2018) found that differences in clonal bunch compactness do not primarily explain the natural variation in botrytis rot susceptibility of nine White Riesling clones. The authors suggested that the general link between bunch compactness and rot susceptibility may not hold true within-cultivar, for example, for a group of clones from the same cultivar.

The berry skin is an important physical and mechanical barrier to rot. Thin-skinned cultivars are more prone to injury, providing entry for microbial colonisation and rot development. A recent study by Lisek & Lisek (2021) concluded that the resistance of cultivars to sour rot strongly correlated with increased berry skin thickness. For example, research has provided evidence that the berry skin of Ugni blanc (115 μm) is significantly thinner compared to the skins of Chardonnay (203 μπι) and Viognier (243 μm) (Jin et al., 2017). Thin-skinned berries are also more predisposed to rot in high temperatures and high visible light vineyard environments. These conditions more easily cause skin injury to thin-skinned berries compared to thicker-skinned cultivars (Steel et al., 2016; Lisek & Lisek, 2021).

Berry cuticle thickness and hydrophobic epicuticular waxes on the berry outer skin also influence cultivars' rot susceptibility (Herzog et al., 2015). The cuticle covers the outer surface of the berry skin. In-field evaluation of naturally infected grapes showed that a thicker cuticle associated with epicuticular waxes negatively correlates with susceptibility to botrytis rot, especially for compact-bunch cultivars (Herzog et al., 2015).

Considering reported differences in cultivar susceptibility to rot, it is conceivable that grape growers should be advised to plant rot-resistant cultivars and clones. However, cultivar choice is a long-term and strategic investment. Over time wineries build a relationship with the retail and clients, which could include the guaranteed volume supply of specific varietal wines. Furthermore, prominent wine regions in the world are characterised by cultivar-specific production; these include Merlot from Bordeaux, (Ky et al., 2012), Sauvignon blanc and Sémillon from Sauternes (Kallitsounakis & Catarino, 2020), Chenin blanc from the Loire Valley, France (Carbajal-Ida et al., 2016), and the sought-after, unique fruity Sauvignon blanc wines from Marlborough, New Zealand (Benkwitz et al., 2012). These cultivars are known to be susceptible to rot (Panitrur-De La Fuente et al., 2018), but due to being an economic driving force of these wine regions, they will continue to be planted for many years. Furthermore, even targeting cultivar and clone selection strategies associated with resilience to rot, climatic conditions still significantly influence the intensity of rot.

 

CLIMATIC INFLUENCES ON BOTRYTIS AND SOUR ROT OF GRAPEVINE BUNCHES

Botrytis rot can either manifest as unwanted grey rot, also called gray mold or just bunch rot, or as the special form of Botrytis cinerea infection, namely noble rot (Jackson, 2014). Noble rot is associated with the highly valued sweet white wine styles of Sauternes (Landrault et al., 2002) and Tokaj (Furdiková et al., 2019). Under controlled conditions, optimal botrytis rot development is observed at high relative humidity (> 90 %) and cool temperatures of 20°C to 25°C (Ciliberti et al., 2015). Very specific climatic conditions of humid nights, cool and foggy mornings, followed by dry, sunny, and windy afternoons are required for the development of noble rot (Furdíková et al., 2019). However, the occurrence of this rare botrytised noble rot grapes is geographically restricted (Kallitsounakis & Catarino, 2020), and under most conditions, botrytis rot is undesirable. Optimum conditions for the development of grey rot include temperatures of approximately 18°C to 22°C, high humidity (> 90 %), and prolonged wet conditions (Würz et al., 2020; Rienth et al., 2021). In contrast to the cool temperatures associated with botrytis rot, sour rot is favoured by hot summers (VanderWeide et al., 2020; Lisek & Lisek, 2021). Average monthly temperatures of approximately 18°C during berry ripening were reported by Lisek & Lisek (2021) for the vintages having severe sour rot. Significant to inducing sour rot is rainfall from veraison to harvest (VanderWeide et al., 2020; Lisek & Lisek, 2021). Rainfall during berry ripening could lead to grape berry splitting. Berry injuries are conducive to the development of sour rot by providing grape juice as a suitable substrate for yeast and acetic bacteria proliferation (Ioriatti et al., 2018).

Different amounts and the distribution of rainfall, which lead to the increase in relative humidity and berry wetness duration, influence the intensity of rot (Becker & Knoche, 2012; Paňitrur-De La Fuente et al., 2018). Botrytis rot's potential infection occurrences under future European climatic conditions (2030 and 2050) were modelled using 15 years of temperature and leaf wetness duration data (Bregaglio et al., 2013). Mixed results emerged from the study, ranging from more than a 100 % increase in the occurrence of botrytis rot, maintaining similar levels of pressure compared to the current situation, or decreasing disease occurrences. The rise in botrytis rot relates to more humid conditions, favouring pathogen development. Bregagli et al. (2013) concluded that botrytis rot will remain a relevant problem to European wine production in the next 10 to 30 years. Using South African weather data from 1984 to 2015 and modelling plausible future conditions, similar heterogeneous climatic changes and conditions for the future were reported (Southey, 2022).

The published literature mainly focuses on the economic effect of a change in temperature on wine production (Ashenfelter & Storchmann, 2014). However, the effect of climate change relating to increased rainfall events during the summer months, i.e. the berry ripening period from veraison to harvest, is also of economic concern to the wine industry. These rainfall events would significantly impact the intensity of sour rot. An increase in the intensity of sour rot has already been observed in Europe (Hausinger et al., 2015; Lisek & Lisek, 2021). In-field observations of an increase in sour rot intensity could explain the series of recent studies on the etiology of sour rot (Ioriatti et al., 2015; Madden et al., 2017; Hall et al., 2018; Hall et al., 2019; Entling et al., 2019; Pinto et al., 2019; Gao et al., 2020).

Long-term strategies to lower the intensity of rot related to climatic conditions include site-specific plantings to avoid climatic conditions favourable to the development of rot. However, there is no strong indication in the literature that this strategy has been followed. For example, recent research suggests that new plantings are established under climatic conditions, knowing that botrytis rot will be problematic (Würz et al., 2020). Due to the dominant effect of climatic conditions on rot, it can be concluded that rot will inevitably be part of grape production.

Earlier literature reviews focused on the predisposing factors contributing to the development of rot, microorganisms associated with grapevine bunch rots, disease expression such as visual symptoms, the effect of rot on grape composition and wine chemistry, as well as vineyard management practices aimed at the control of rot (Mundy, 2008; Steel et al., 2013; Rousseaux et al., 2014; Latorre et al., 2015; Kallitsounakis & Catarino, 2020; Rienth et al., 2021; Crandall et al., 2022). However, grapevine bunch rot assessment from an industrial perspective has not been reviewed before. In the following sections, this review provides an industrial perspective on challenges specific to large or producer wineries concerning the assessment of grapevine bunch rots.

 

ASSESSING ROT INTENSITY

Before discussing the challenges relating to the accurate assessment of rot under industrial working conditions, a summary of relevant terms in the field of plant disease assessment is given. For a comprehensive glossary, the reader is referred to Bock et al. (2022a).

Plant disease assessment or phytopathometry concerns the visual estimation or instrument or sensor-based measurement of the amount of plant disease that usually is symptom-based (Bock et al., 2022a). Disease assessment focuses on detection, identification, quantification, or a combination of these objectives (Bock et al., 2022a). Disease intensity is a general term used to describe the amount of disease present in a population (Nutter, 1991). It can be defined by the terms prevalence, incidence, or severity (Bock et al., 2022a). In earlier research, prevalence, incidence, and frequency were often used as synonyms (Seem, 1984). However, incidence is the proportion or number of the whole of disease entities within a sampling unit, and prevalence is the proportion of diseased plots or fields in a defined area (Bock et al., 2022b). On the other hand, severity measures the quantity of disease within the sampling unit (Bock et al., 2022b).

Compared to prevalence or incidence, severity is more evident in research describing rot intensity on wine grape cultivars. The reason could be that as severity increases, the detrimental effect on wine quality also increases (Zoecklein, et al., 2000; Barata et al., 2011b; Steel et al., 2018). Globally, visual assessment is still the reference method to determine grapevine bunch rot intensity in-field, which could include visually estimating the percentage of berries infected per bunch, the percentage of tissue infected per bunch, or severity estimations according to scales (Hed et al., 2009; Hill et al., 2013; Molitor et al., 2020; Steel et al., 2020). Rot intensity assessment of grape loads at winery intake includes visual detection of rot-affected bunches, and/or calculating the severity by percentage of weight of rot in the sample. (Durgun, 2010). Bock et al. (2022a) strongly advised clearly defining how a disease assessment term is applied under specific industrial conditions. Wineries often impose a price penalty if rot intensity exceeds a certain threshold (Hill et al., 2014). Imposing price penalties could severely reduce grape growers' income; accordingly, rot intensity assessments must follow a standard protocol and ensure repeatability, objectivity, and accuracy. The next section will discuss three challenges concerning rot intensity assessment from an industrial perspective. These challenges include representative sampling, mechanical harvesting of grapes and visual assessment of rot.

Challenges relating to rot intensity assessment under industrial working conditions

Trustworthy assessment stems from representative samples (Wagner & Esbensen, 2015). The reality of variability within a vineyard is well-known (Bramley et al., 2011), which also applies to the variability of disease intensity within a single vineyard block. Clumping or pockets of rot within a single vineyard block is not uncommon, and rot intensity could differ between parts in the same vineyard block (Evans et al., 2010). Under industrial conditions, the sample size, and the spatial distribution from which the sample is collected, should be representative of the vineyard block if the assessment is executed at vineyard level; or the grape load which is assessed at winery intake. Non-representative sampling procedures may lead to invalid results.

Accuracy, or the lack thereof, in vineyard sampling comes with an increasing cost for both grape growers and wineries. Theoretically calculated, Hill et al. (2019) estimated that annual crop losses/ha could be as high as NZ$2 578 (approximately ZAR27 000/ha) due to incorrect estimates of botrytis rot severity in vineyards. The cost concerning the time spent and human resources needed to accurately assess many vineyard blocks in a large producer winery's setup could render in-vineyard assessment unsustainable. Interpolating vineyard blocks from small samples taken within the specific vineyard block was proposed by Hill et al. (2019) to reduce the amount of sampling. Assessing rot intensity at winery intake could provide an economical substitute for in-vineyard checks. However, mechanisation of the grape harvesting process confronts winery intake visual assessment with structural integrity loss of bunches (Durgun, 2010), which obscures the presence of rot.

When grapes are machine-harvested, mechanical actions are exerted on grapevines to remove the berries from the stalks. Grape bunches and berries lose their structural integrity due to the mechanical forces exerted on them. Grape loads delivered to the winery consist of a shapeless mass of juice, berry skins and pulps called grape mash; see Figure 2 for a visual demonstration of the effect of mechanical harvesting on grape bunches. However, regarding the sampling strategy of grape loads at winery intake, the sample size of machine-harvested grape loads could be smaller compared to hand-harvested loads. Marois et al. (1993) found that hand-harvest grape loads had a more aggregated distribution of Botrytis cinerea than machine-harvested grape loads, which had a more uniform distribution of Botrytis antigen.

In addition to the above two challenges, objective visual assessment proves to be difficult. For a review of the sources of error related to the visual assessment of plant diseases Bock et al. (2010) can be consulted. Under industrial working conditions, subjectivity can intensify by using seasonal employees without prior training or experience with visual rot assessments, as is often employed in large wineries. Several studies have demonstrated that experienced assessors estimate severity more accurately (Bock et al., 2022b).

Aside from the subjectivity and bias associated with visual assessment, this method does not fully capture the unseen chemical berry composition changes induced by rot. In the event of latent rot, visual symptoms would not yet have manifested, but chemical changes to the berry have already started to occur (Versari et al., 2008). It is also possible that an extended rot period increased the concentration of rot-associated grape berry metabolites compared to a shorter infection period. Still, visually berries are assessed with the same intensity (Fischer & Berger, 2007).

Since early investigations, such as Berg's et al. (1958) study into a practical grading system for defect detection at winery intake, efforts are still ongoing in the quest to improve the objectivity and speed of rot intensity assessments. The following section critically reviews the industrial application of sustainable rot assessment in the last 15 years, from 2007 to 2022.

 

THE QUEST FOR SUSTAINABLE ASSESSMENT OF GRAPEVINE ROT IN THE FOURTH INDUSTRIAL REVOLUTION

Sustainability has three core concepts, namely economic, environmental, and social sustainability (Contini & Peruzzini, 2022). Characteristic of the current fourth industrial revolution (Industry 4.0) is digitisation and automation in the manufacturing environment aiming to increase sustainability (Ortt et al., 2020; Hassoun et al., 2023). The vine and wine sectors also focus on digitisation to increase efficiency, productivity, transparency, value proposition and new business models, and sustainability (OIV, 2021).

Initiatives for sustainable development in the vine sector were launched in recent years. Examples of this inventiveness applied under industrial working conditions include the use of the normalised difference vegetation index (NVDI) that characterises in-vineyard variability (Best et al., 2015; Paňitrur-De la Fuente et al., 2020), and crop protection modelling (Molitor et al., 2020) which use meteorological conditions to predict the risk of rot.

Sustainable development in wine grape production also embraces replacing wet chemistry methods with non-destructive technologies such as infrared (IR) spectroscopy to quantify grape compounds rapidly (Swanepoel et al., 2007; Petrovic et al., 2020; Ferrer-Gallego et al., 2022). Infrared spectroscopy methods contribute to all three of the core sustainable concepts. Concerning the economic concept, accuracy, speed, and simplification of IR analysis methods can provide rapid results for actionable operational insights. Instrumentation and so-called global calibration models for the prediction of grape compounds are also available at a reasonable cost. Environmentally, IR methods reduce the use of harsh chemicals and thus also reduce chemical waste. Socially, since less or no chemicals are used during analysis, operators' health and safety are also considered. It is also possible for non-specialist operators to use spectroscopy instrumentation (Marcinkowska et al., 2019) as part of routine applications.

The above sustainable development initiatives indicate that the vine sector may be receptive to decision support using technological interventions. Infrared spectroscopy methods could provide options for sustainable rot assessment, and grape production can notably benefit from rot assessment decision support (Porep et al., 2014; Schmidtke et al., 2019). However, hurdles need to be cleared to achieve automated rot assessment including ensuring representative sampling, data analytics for actionable insights and winery decisions on sorting rot-affected grapes into different production streams.

Evaluating the progress towards this stance, published studies in the last 15 years, from 2007 to 2022, on the use of IR spectroscopy for grapevine bunch rot assessments in wine grapes are critically reviewed from an industrial perspective (Table 2).

Overview of published studies (2007 to 2022) using infrared (IR) spectroscopy for grapevine bunch rot assessment

Quantifying rot intensity was the focus of earlier IR studies (Versari et al., 2008; Durgun, 2010; Hill et al., 2014). In these studies, Fourier-transform mid-infrared (FTIR-MIR) showed an ability to predict severity (%) with R² = 0.8 (Versari et al., 2008) and R² > 0.9 (Durgun, 2010; Hill et al., 2014). Near infrared (NIR) spectroscopy also demonstrated potential for quantifying rot intensity (R² = 0.9). However, for the ease of in-field industrial application, Hill et al. (2014) recommended the use of digital image analysis instead of IR spectroscopy techniques. Digital image analysis does not require additional equipment for in-vineyard assessments and could save time. Still, emphasising the previously discussed challenges of rot assessment for producer wineries, the time implications of in-vineyard assessments are not sustainable. However, with an RPD of 2.5 and 2.0 for NIR and FTIR-MIR severity (%) predictions, respectively (Hill et al., 2014), these methods show potential for screening purposes at winery intake. Hill et al. (2014) noted that compared to visual assessments, both the beforementioned IR techniques appear to be more accurate at predicting severity > 50 %, and considerable non-linearity was observed in low severities of < 25 %.

Infrared spectroscopy techniques were especially explored for the detection of rot (Table 2). Detection of grapevine bunch rot could be achieved by following either of two strategies, namely detecting an increase in the concentration(s) of rot-associated disease marker(s) (Versari et al., 2008; Hausinger et al., 2015; Porep et al., 2015a; Porep et al., 2015b; Gelhken et al., 2022), or discriminating between rot-affected and healthy grapes (Beghi et al.,, 2017; Giovenzana et al., 2017; Giovenzana et al., 2018). The compounds in the beforementioned studies that were targeted to support the rapid detection of rot by increased concentrations include gluconic acid and glycerol (Versari et al., 2008; Hausinger et al., 2015; Porep et al., 2015a), acetic acid (Porep et al. 2015a), the fungal sterol, namely ergosterol (Porep et al., 2014; Porep et al., 2015b), as well as VOC's (Gelhken et al., 2022). Interestingly, the classification studies of Giovenzana et al. (2018) and Beghi et al. (2017) only aimed at discriminating between healthy and rot-affected grapes, which will be downgraded by the winery for high-quality vinification. From an industrial perspective, a two-class grading system could be limiting, especially in a year with extreme weather conditions conducive to rot development. A third group of "classified as infected, but in need of winemaking remedy" is probably a more realistic situation at a producer winery.

The identification of rot pathogens using IR spectroscopy has only recently been explored (Table 2). Although Giovenzana et al. (2018) did report visual spectral differences between grape must infected with botrytis compared to sour rot, no classification modelling was performed. Schmidtke et al. (2019) were the first to explore the use of IR techniques in combination with classification modelling for identifying rot pathogens in grape must. It should be noted that the latter study was conducted on a small sample set consisting of only 30 samples per pathogen. Furthermore, grape berries were inoculated with pure cultures; thus, identification of these rot pathogens will have to be tested with naturally infected berries (Schmidtke et al., 2019). Although the results from this study are promising for identifying rot pathogens, pathogen identification does not provide an answer to the amount of rot present. Knowing the intensity of rot is crucial to guide mitigation practices in wineries.

In addition, some of the reviewed studies listed in Table 2 lack industrial robustness, for example by using only a small sample size per parameter that was modelled. For optimal results with calibration modelling, more than 75 samples might be required (Versari et al., 2008). Furthermore, variation in the sample set must encompass different cultivars, vintages, climatic conditions and more than one type of rot. Rot rarely exhibits a single form under natural conditions. An example of lacking robustness for industrial application could be drawn from Durgun (2010) who explored the use of FTIR-MIR and Raman spectroscopy for rot quantification in the severity range of 0 % to 5 %. Even though this rot intensity range is likely to result in the downgrading of grapes at winery intake, it does not represent the observed in-field severities. Thus, this model would be limiting in sorting grapes into different production streams within the winery. Robust models can perform measurements in the various scenarios encountered under industrial conditions (Giovenzana et al., 2018).

Near-infrared spectroscopy features strongly in rot assessment studies (Table 2). Earlier studies did explore the potential of transmittance FTIR-MIR spectroscopy for rapid detection of rot (Versari et al., 2008; Durgun, 2010). However, the sample preparation requirements for transmission FTIR-MIR could be a drawback for rapid analysis at winery intake. Attenuated total reflectance mid-infrared (ATR-MIR) spectroscopy, which requires minimal or no sample preparation for analysis, could fulfil the requirements for routine application at winery intake. Schmidtke et al. (2019) is the only study exploring the potential use of ATR-MIR in rot assessments.

Importantly, spectroscopy methods are coupled with multivariate data analysis (MVDA) techniques, such as partial least square (PLS) regression and partial least square discriminant analysis (PLS-DA) (Table 2). Spectroscopic methods lead to the generation of large volumes and a variety of data, also referred to as big data (Simsek et al., 2019). Although information-rich, this spectral data needs to be transformed into decision-support tools relevant for the problem at hand. The process of extracting information from these datasets is called data mining (Provost & Fawcett, 2013). However, the decision-support information needed for industrial implementation will be revealed only if MVDA data are combined with problem-specific interpretation (Esbensen & Julias, 2009). For an introduction to the MVDA methods coupled with spectroscopy in wine and grape analysis, the reader is referred to Cozzolino et al. (2009) and Musingarabwi et al. (2016).

 

CONCLUSIONS

Grapevine bunch rots are an inevitable part of grape production. They force attention to the unique challenges of producer wineries where large volumes of grapes need to be assessed for their health status in a relatively short harvest period. The need for rot assessment as part of grape quality evaluation relates to rot's detrimental effect on grape composition and wine quality. Inaccurate rot assessments lead to a loss in income, both for grape growers and wineries. Although grape cultivars naturally differ in susceptibility to rot, climatic conditions have overriding influences on the intensities of encountered infections.

From the published articles on the use of IR methods for grape rot assessments (Table 2), it is evident that the studies predominantly aimed at the detection of rot by rapid quantification of rot-associated disease markers. However, the first step towards the detection of rot at winery intake using rot-associated disease markers would require the identification of disease marker threshold values for rejection.

Infrared spectroscopy may provide sustainable options for rapid and objective rot assessment for routine application at producer wineries. The potential use of ATR-MIR for rapid detection and quantification of rot under industrial working conditions is unexplored. Furthermore, MVDA featuring discriminant analysis for quantifying the severity (%) has not been done before.

Compared to the fruit and vegetable sectors' use of decision support by automated analyses (Giovenzana et al., 2015), the vine and wine sector fail to keep pace. Creating an example for practical application and overcoming practical challenges would benefit sustainable practices in the wine industry.

However, the first step for industrial implementation would be based on having a standardised tool to assess rot at winery intake. As discussed by Hill et al. (2014), using a standardised alternative method for rot assessment would depend on the goal. The question arises whether the alternative method must predict severity (%) directly comparable to visually estimated severity (%)? Thus, to be used as a threshold level upon which penalties would be implied? Or is the goal to find an alternative assessment method that removes the subjectivity of visual assessment regardless of the variable used? The latter is a more generalised strategy and advantageous for implementation under different industrial working situations. The next step would be for wineries customising the assessment method for example, per cultivar and even per cultivar per quality goal. Following this stage, would be aligning process flows for an increase in the potential value of wine by sorting grapes according to health status into different production streams.

 

LITERATURE CITED

Ashenfelter, O. & Storchmann, K., 2014. Wine and climate change. American Association of Wine Economists (AAWE) Working paper, 152, 1-43.         [ Links ]

Australian Wine Research Institute (AWRI), 2023. Fact sheet: Managing Botrytis-infected fruit. https://www.awri.com.au Date of access: 06.04.2023.         [ Links ]

Barata, A., Campo, E., Malfeito-Ferreira, M., Loureiro, V., Cacho, J. & Ferreira, V., 2011a. Analytical and sensorial characterization of the aroma of wines produced with sour rotten grapes using GC-O and GC-MS: Identification of key aroma compounds. J. Agric. Food Chem. 59, 2543-2553.         [ Links ]

Barata, A., Pais, A., Malfeito-Ferreira, M. & Loureiro, V., 2011b. Influence of sour rotten grapes on the chemical composition and quality of grape must and wine. Eur. Food Res. Technol. 233(2), 183-194.         [ Links ]

Becker, T. & Knoche, M., 2012. Water induces microcracks in the grape berry cuticle. Vitis 51(3), 141-142.         [ Links ]

Beghi, R., Giovenzana, V., Brancadoro, L. & Guidetti, R., 2017. Rapid evaluation of grape phytosanitary status directly at the check point station entering the winery by using visible/near infrared spectroscopy. J. Food Eng. 204, 46-54.         [ Links ]

Benkwitz, F., Tominaga, T., Kilmartin, P.A., Lund, C., Wohlers, M. & Nicolau, L., 2012. Identifying the chemical composition related to the distinct aroma characteristics of New Zealand Sauvignon blanc wines. Am. J. Enol. Vitic. 63(1), 62-72.         [ Links ]

Berg, H.W., Alley, C.J. & Winkler, A.J., 1958. Investigation of defects in grapes delivered to California wineries: 1957. Am. J. Enol. Vitic. 9(1), 24-31.         [ Links ]

Best, S., Leon, L. & Quintana, R., 2015. Development of a differential grape harvesting methodology. Chem. Eng. Trans. 44, 295-300.         [ Links ]

Bezuidenhout, F., 2014. South African producer/co-operative wineries. Thesis, Cape Wine Masters, South Africa. Downloaded from https://icwm.co.za/members/bezuidenhout/ Date of access: 18.11.2022.         [ Links ]

Bock, C.H., Pethybridge, S.J., Barbedo, J.G.A., Esker, P.D., Mahlein, A.K. & Del Ponte, E.M., 2022a. A phytopathometry glossary for the twenty-first century: towards consistency and precision in intra- and inter- disciplinary dialogues. Trop. Plant Pathol. 47(1), 14-24.         [ Links ]

Bock, C.H., Chiang, K.S. & Del Ponte, E.M., 2022b. Plant disease severity estimated visually: a century of research, best practices, and opportunities for improving methods and practices to maximize accuracy. Trop. Plant. Pathol. 47(1), 25-42.         [ Links ]

Bock, C.H., Poole, G.H., Parker, P.E. & Gottwald, T.R., 2010. Plant disease severity estimated visually, by digital photography and image analysis, and by hyperspectral imaging. CRC. Crit. Rev. Plant Sci. 29(2), 59-107.         [ Links ]

Bramley, R.G.V., Trought, M.C.T. & Praat, J-P., 2011. Vineyard variability in Marlborough, New Zealand: Characterising variation in vineyard performance and options for the implementation of Precision Viticulture. Aust. J. Grape Wine Res. 17(1), 72-78.         [ Links ]

Bregaglio, S., Donatelli, M. & Confalonieri, R., 2013. Fungal infections of rice, wheat, and grape in Europe in 2030-2050. Agron. Sustain. Dev. 33(4), 767-776.         [ Links ]

Carbajal-Ida, D., Maury, C., Salas, E., Siret, R. & Mehinagic, E., 2016. Physico-chemical properties of botrytised Chenin blanc grapes to assess the extent of noble rot. Eur. Food Res. Technol. 242, 117-126.         [ Links ]

Ciliberti, N., Fermaud, M., Roudet, J. & Rossi, V., 2015. Environmental conditions affect Botrytis cinerea infection of mature grape berries more than the strain or transposon genotype. Phytopathology 105(8), 1090-1096.         [ Links ]

Claus, H., 2020. How to deal with uninvited guests in wine: Copper and copper-containing oxidases. Fermentation 6(38), 1-14.         [ Links ]

Claus, H., Sabel, A. & König, H., 2014. Wine phenols and laccase: An ambivalent relationship. In: El Rayess, Y. (eds.). Wine - Phenolic Composition, Classification and Health Benefits, (1^st ed.) pp 155-185.         [ Links ]

Contini, G. & Peruzzini, M., 2022. Sustainability and Industry 4.0: Definition of a set of key performance indicators for manufacturing companies. Sustainability 14, 1-37.         [ Links ]

Cozzolino, D., Cynkar, W.U., Shah, N., Dambergs, R.G. & Smith, P.A., 2009. A brief introduction to multivariate methods in grape and wine analysis. Int. J. Wine Res. 1, 123-130.         [ Links ]

Crandall, S.G., Spychalla, J., Crouch, U., Acevedo, F.E., Naegele, R.P. & Miles, T.D., 2022. Rotting grapes don't improve with age: Cluster rot disease complexes, management, and future prospects. Plant Dis. 106(8), 2013-2022.         [ Links ]

Dudareva, N., Klempien, A., Muhlemann, J.K. & Kaplan, I., 2013. Biosynthesis, function and metabolic engineering of plant volatile organic compounds. New Phytol. 198(1), 16-32.         [ Links ]

Durgun, H., 2010. Quantification of rot in wine grapes. https://scholarworks.calstate.edu/downloads/pz50gx20m?locale=en Date of access: 19.09.2022.         [ Links ]

Entling, W., Anslinger, S., Jarausch, B., Michl, G. & Hoffmann, C., 2019. Berry skin resistance explains oviposition preferences of Drosophila suzukii at the level of grape cultivars and single berries. J. Pest Sci. 92, 477-484.         [ Links ]

Esbensen, K.H. & Julius, L.P., 2009. 4.01 - Representative sampling, data quality, validation - A necessary trinity in chemometrics. In: Brown, S.D., Tauler, R. & Walczak, B. (eds). Comprehensive chemometrics, Chemical and biochemical data analysis, (1^st ed.) pp. 1-20.         [ Links ]

Espejo, F., 2021. Role of commercial enzymes in wine production: a critical review of recent research. J. Food Sci. Technol. 58, 9-21. https://doi.org/10.1007/s13197-020-04489-0        [ Links ]

European Commission, 2006. Commission regulation (EC) No. 1881/2006 of 19 December 2006. Setting maximum levels for certain contaminants in foodstuffs. Official Journal of the European Union, L364/5-L364/24 https://eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:364:0005:0024:EN:PDF Date of access: 15.11.2022.         [ Links ]

Evans, K.J., Dunne, K.J., Riches, D., Edwards, J., Beresford, R.M. & Hill, G.N. 2010. Effective management of botrytis bunch rot for cool climate viticulture. Grape and Wine Research and Development Corporation, Project Number: UT 06/01, University of Tasmania. https://www.wineaustralia.com/getmedia/3eb20c93-e535-4e1b-9989-7ebc16b3ce3c/UT-06-01 Date of access: 30.01.2022.         [ Links ]

Ferrer-Gallego, R., Rodríguez-Pulido, F.J., Toci, A.T. & García-Estevez, I., 2022. Phenolic composition, quality and authenticity of grapes and wines by vibrational spectroscopy. Food Rev. Int. 38(5), 884-912.         [ Links ]

Fischer, U. & Berger, T., 2007. Objective measurement of grape soundness. Focus 31(1), 18-21.         [ Links ]

Francioli, S., Buxaderas, S. & Pellerin, P., 1999. Influence of Botrytis cinerea on the polysaccharide composition of Xarel.Lo must and cava base wines. Am. J. Enol. Vitic. 50(4), 456-460.         [ Links ]

Furdíková, K., Machyňáková, A., Drtilová, T., Klempová, T., Ďurčanská, K. & Špánik, I., 2019. Comparison of volatiles in noble-rotten and healthy grape berries of Tokaj. LWT - Food Sci. Technol. 105, 37-47.         [ Links ]

Gambuti, A., Strollo, D., Genovese, A., Ugliano, M., Ritieni, A. & Moio, L., 2005. Influence of enological practices on ochratoxin A concentration in wine. Am. J. Enol. Vitic. 56(2), 155-162.         [ Links ]

Gao, H., Yin, X., Jiang, X., Shi, H., Yang, Y., Wang, C., Dai, X., Chen, Y & Wu, X., 2020. Diversity and spoilage potential of microbial communities associated with grape sour rot in eastern coastal areas of China. PeerJ 2020(6), 1-17.         [ Links ]

Gehlken, J., Pour Nikfardjam, M. & Zörb, C., 2022. Determination of aroma compounds in grape mash under conditions of tasting by on-line near-infrared spectroscopy. Eur. Food Res. Technol. 248(9), 2325-2337.         [ Links ]

Giovenzana, V., Beghi, R., Brancadoro, L. & Guidetti, R., 2017. Classification of wine grape based on different phytosanitary status by using visible/near infrared spectroscopy. Chem. Eng. Trans. 58, 331-336.         [ Links ]

Giovenzana, V., Beghi, R., Civelli, R. & Guidetti, R., 2015. Optical techniques for rapid quality monitoring along minimally processed fruit and vegetable chain. Trends Food Sci. Technol. 46(2), 331-338.         [ Links ]

Giovenzana, V., Beghi, R., Tugnolo, A., Brancadora, L. & Guidetti, R., 2018. Comparison of two immersion probes coupled with visible/near infrared spectroscopy to assess the must infection at the grape receiving area. Comput. Electron. Agric. 146, 86-92.         [ Links ]

Hall, M., Loeb, G. & Wilcox, W., 2017. Defining and development management strategies for sour rot. Res. Focus 2017-3 Cornell Viticulture and Enology 30, 1-7. https://grapesandwine.cals.cornell.edu/sites/grapesandwine.cals.cornell.edu/files/shared/Research%20Focus%202017-3.pdf Date of access: 04.01.2020.         [ Links ]

Hall, M.E., Loeb, G.M., Cadle-Davidson, L., Evans, K.J. & Wilcox, W.F., 2018. Grape sour rot: A four-way interaction involving the host, yeast, acetic acid bacteria, and insects. Phytopathology 108(12), 1429-1442.         [ Links ]

Hall, M.E., O'Bryon, I., Wilcox, W.F., Osier, M.V. & Cadle-Davidson, L., 2019. The epiphytic microbiota of sour rot-affected grapes differs minimally from that of healthy grapes, indicating causal organisms are already present on healthy grapes. PLoS One 14(3), 1-12.         [ Links ]

Hassoun, A., Jagtap, S., Garcia-Garcia, G., Trollman, H., Pateiro, M., Lorenzo, J.M., Trif, M., Rusu, A.V., Aadil, R.M., Šimat, V., Cropotova, J. & Câmara, J.S., 2023. Food quality 4.0: From traditional approaches to digitalized automated analysis. J. Food Eng. 337, 1-16.         [ Links ]

Hausinger, K., Lipps, M., Raddatz, H., Rosch, A., Scholten, G. & Schrenk, D., 2015. Automated optical grape-sorting of rotten grapes: effects of rot infections on gluconic acid concentration and glycerol/gluconic acid ratios in must and wine. J. Wine Res. 26(1), 18-28.         [ Links ]

Hed, B., Ngugu, H.K. & Travis, J.W., 2009. Relationship between cluster compactness and bunch rot in Vignoles grapes. Plant Dis. 93(11), 1195-1201.         [ Links ]

Herzog, K., Schwander, F., Kassemeyer, H.H., Bieler, E., Dürrenberger, M., Trapp, O. & Töpfer, R., 2022. Towards sensor-based phenotyping of physical barriers of grapes to improve resilience of Botrytis bunch rot. Front. Plant Sci. 12, 1-17.         [ Links ]

Herzog, K., Wind, R. & Töpfer, R., 2015. Impedance of the grape berry cuticle as novel phenotypic trait to estimate resistance to Botrytis cinerea. Sensors 15, 12498-12512.         [ Links ]

Hill, G.N., Evans, K.J., Beresford, R.M., & Dambergs, R.G., 2013. Near and mid-infrared spectroscopy for the quantification of botrytis bunch rot in white wine grapes. J. Near Infrared Spectrosc. 21(6), 467-475.         [ Links ]

Hill, G.N., Evans, K.J., Beresford, R.M., & Dambergs, R.G., 2014. Comparison of methods for the quantification of botrytis rot in white wine grapes. Aust. J. Grape Wine Res. 20(3), 432-441.         [ Links ]

Hill, G.N., Jackson, P., Sharp, J.M., Hunt, A.G. & Lewis, K.S.J., 2019. Investigating time and economic costs of botrytis bunch rot sampling using interpolated data. New Zeal. Plant Prot. 72, 166-175.         [ Links ]

International Agency for Research on Cancer, 1993. IARC Monographs on the identification of carcinogenic hazards to humans. https://monographs.iarc.who.int/list-of-classifications Date of access: 15.11.2022.         [ Links ]

Ioriatti, C., Guzzon, R., Anfora, G., Ghidoni, F., Maxxoni, V., Villegas, T.R., Dalton, D.T. & Walton, V.M., 2018. Drosophila suzukii (Diptera: Drosophilidae) contributes to the development of sour rot in grape. J. Econ. Entomol. 111(1), 283-292.         [ Links ]

Ioriatti, C., Walton, V., Dalton, D., Anfora, G., Grassi, A., Maistri, S. & Mazzoni, V., 2015. Drosophila suzukii (Diptera: Drosophilidae) and its potential impact on wine grapes during harvest in two cool climate wine grape production regions. J. Econ. Entomol. 108(3), 1148-1155.         [ Links ]

Jackson, R.S., 2014. Botrytis. Encycl. Food Microbiol. Second Ed. (1), 288-296. http://dx.doi.org/10.1016/B978-0-12-384730-0.00042-2        [ Links ]

Jadhav, S.B. & Gupta, A., 2016. Studies on application of β-1,3 glucanase in the degradation of glucans produced by Botrytis cinerea and inhibition of fungal growth. Biocatal. Agric. Biotechnol. 7, 45-47.         [ Links ]

Jin, X., Wu, X., Liu, X. & Liao, M., 2017. Varietal heterogeneity of textural characteristics and their relationship with phenolic ripeness of wine grapes. Sci. Hortic. 216, 205-214.         [ Links ]

Kallitsounakis, G. & Catarino, S., 2020. An overview on botrytized wines. Cienc. e Tec. Vitivinic. 35(2), 76-106.         [ Links ]

Kellner, N., Antal, E., Szabó, A. & Matolcsi, R., 2022. The effect of black rot on grape berry composition. Acta Aliment. 51(1), 126-133.         [ Links ]

Ky, I., Lorrain, B., Jourdes, M., Pasquier, G., Fermaid, M., Gény, L., Rey, P., Doneche, B. & Teissedre, P.-L., 2012. Assessment of grey mould (Botrytis cinerea) impact on phenolic and sensory quality of Bordeaux grapes, musts and wines for two consecutive vintages. Aust. J. Grape Wine Res. 18(2), 215-226.         [ Links ]

Landrault, N., Larronde, F., Delaunay, J.C., Castagnino, C., Vercauteren, J., Merillon, J.M., Gasc, F., Cros, G. & Teissedre, PL., 2002. Levels of stilbene oligomers and astilbin in French varietal wines and in grapes during noble rot development. J. Agric. Food Chem. 50(7), 2046-2052.         [ Links ]

Latorre, B.A., Elfar, K. & Ferrada, E.E., 2015. Gray mold caused by Botrytis cinerea limits grape production in Chile. Cien. Inv. Agr. 42(3), 305-330.         [ Links ]

Lisek, J. & Lisek, A., 2021. Varietal response to sour rot bunch rot in polish grapevine genetic resources. Agronomy 11, 9-11.         [ Links ]

Longbottom, M., Simos, C., Krstic, M. & Johnson, D., 2013. Grape quality assessments: a survey of current practice. Wine Vitic. J. 28(3), 33-37.         [ Links ]

Madden, A.A., Boyden, S.D., Soriano, J.A.N., Corey, T.B., Leff, J.W., Fierer, N. & Starks, P.T., 2017. The emerging contribution of social wasps to grape rot disease ecology. PeerJ 5:e3223, 1-17.         [ Links ]

Marcinkowska, R., Namieśnik, J. & Tobiszewski, M., 2019. Green and equitable analytical chemistry. Curr. Opin. Green Sustain. Chem. 19, 19-23.         [ Links ]

Marois, J.J., Bledsoe, A.M., Ricker, R.W. & Bostock, R.M., 1993. Sampling for Botrytis cinerea in harvested grape berries. Am. J. Enol. Vitic. 44(3), 261-265.         [ Links ]

Marois, J.J., Nelson, J.K., Morrison, J.C., Lile, L.S. & Bledsoe, A.M., 1986. The influence of berry contact within grape clusters on the development of Botrytis cinerea and epicuticular wax. Am. J. Enol. Vitic. 37(4), 293-296.         [ Links ]

Meneguzzo, J., Miele, A., Rizzon, L.A. & Ayub, M.A.Z., 2008. Effect of bunch rot on the sensory characteristics of the Gewürztraminer wine. J. Int. des Sci. la Vigne du Vin 42(2), 107-11.         [ Links ]

Molitor, D., Baus, O., Didry, Y., Junk, J., Hoffmann, L. & Beyer, M., 2020. BotRisk: simulating the annual bunch rot risk on grapevines (Vitis vinifera L. cv. Riesling) based on meteorological data. Int. J. Biometeorol. 1571-1582.         [ Links ]

Molitor, D., Biewers, B., Jünglen, M., Schultz, M., Clementi, P., Permesang, G., Regnery, D., Porten, M., Herzog, K., Hoffmann, L., Beyer, M. & Berkelmann-Löhnertz, B., 2018. Multi-annual comparisons demonstrate difference in bunch rot susceptibility of nine Vitis vinifera L. 'Riesling' clones. Vitis - J. Grapevine Res. 57(1), 17-25.         [ Links ]

Mundy, D.C., 2008. A review of the direct and indirect effects of nitrogen on botrytis bunch rot in wine grapes. New Zeal. Plant Prot. 61, 306-310.         [ Links ]

Musingarabwi, D.M., Nieuwoudt, H.H., Young, P.R., Eyéghé-bickong, H.A. & Vivier, M.A., 2016. A rapid qualitative and quantitative evaluation of grape berries at various stages of development using Fourier-transform infrared spectroscopy and multivariate data analysis. Food Chem. 190, 253-262.         [ Links ]

Nutter, F.W., 1991. Disease assessment terms and concepts. Plant Dis. 75(11), 1187-1188.         [ Links ]

OIV - International Organisation of Vine and Wine, (2021). Digital trends applied to the vine and wine sector. A comprehensive study on the digitalisation of the sector. https://www.oiv.int/js/lib/pdfjs/web/viewer.html?file=/public/medias/8593/digital-trends-applied-to-the-vine-and-wine-sector.pdf Date of access: 06.09.2022.         [ Links ]

Ortt, R., Stolwijk, C. & Punter, M., 2020. Implementing Industry 4.0: assessing the current state. J. Manuf. Technol. Manag. 31(5), 825-836.         [ Links ]

Pañitrur-De La Fuente, C., Valdés-Gómez, H., Roudet, J., Acevedo-Opazo, C., Verdugo-Vásquez, N., Araya-Alman, M., Lolas, M., Moreno., Y. & Fermaud, M., 2018. Classification of winegrape cultivars in Chile and France according to their susceptibility to Botrytis cinerea related to fruit maturity. Aust. J. Grape Wine Res. 24(2), 145-157.         [ Links ]

Paňitrur-De La Fuente, C., Valdés-Gómez, H., Roudet, J., Verdugo-Vásquez, N., Mirabal, Y., Laurie, V.G., Goutouly, J.P., Acevedo-Opazo, C. & Fermaud, M., 2020. Vigor threshold NDVI is a key early risk indicator of botrytis bunch rot in vineyards. Oeno One 54(2), 279-297.         [ Links ]

Petrovic, G., Aleixandre-Tudo, J.L. & Buica, A., 2020. Viability of IR spectroscopy for the accurate measurement of yeast assimilable nitrogen content of grape juice. Talanta 206, 1-7.         [ Links ]

Pinto, L., Malfeito-Ferreira, M., Quintieri, L., Silva, A.C. & Baruzzi, F., 2019. Growth and metabolite production of a grape sour rot yeast-bacterium consortium on different carbon sources. Int. J. Food Microbiol. 296, 65-74.         [ Links ]

Porep, J.U., Erdmann, M.E., Körzendörfer, A., Kammerer, D.R. & Carle, R., 2014. Determination of ergosterol in grape mashes for grape rot indication and further quality assessment by means of an industrial near infrared/visible (NIR/VIS) spectrometer - A feasibility study. Food Control 43, 142-149.         [ Links ]

Porep, J.U., Mattes, A., Pour Nikfardjam, M.S., Kammerer, D.R. & Carle, R., 2015a. Implementation of an on-line near infrared/visible (NIR/VIS) spectrometer for rapid quality assessment of grapes upon receival at wineries. Aust. J. Grape Wine Res. 21(1), 69-79.         [ Links ]

Porep, J.U., Mrugala, S., Por Nikfardjam, M.S. & Carle, R., 2015b. Online determination of ergosterol in naturally contaminated grape mashes under industrial conditions at wineries. Food Bioprocess Technol. 8(7), 1455-1464.         [ Links ]

Price Waterhouse Cooper, 2013. The South African wine industry insights survey 2013. www.pwc.co.za/wine-insights-survey Date of access: 03.12.2022.         [ Links ]

Provost, F. & Fawcett, T., 2013. Data science and its relationship to big data and data-driven decision making. Big Data 1(1), 51-59.         [ Links ]

Rienth, M., Vigneron, N., Walker, R.P., Castellarin, S.D., Sweetman, C., Burbidge, C.A., Bonghi, C., Famiani, F. & Darriet, P., 2021. Modifications of grapevine berry composition induced by main viral and fungal pathogens in a climate change scenario. Front. Plant Sci. 12, 1-12.         [ Links ]

Rousseaux, S., Diguta, C.F., Radoï-Matei, F., Alexandre, H. & Guilloux-Bénatier, M., 2014. Non-Botrytis grape-rotting fungi responsible for earthy and moldy off-flavors and mycotoxins. Food Microbiol. 38, 104-121.         [ Links ]

Santos, H., Augusto, C., Reis, P., Rego, C., Figueiredo, A.C. & Fortes, A.M., 2022. Volatile metabolism of wine grape Trincadeira: Impact of infection with Botrytis cinerea. Plants 11, 1-18.         [ Links ]

South African Wine Industry Information and Systems (SAWIS), 2021. SA Wine Industry 2021 Statistics, 46, 1-32. https://www.sawis.co.za/info/annualpublication.php Date of access: 02.10.2022.         [ Links ]

South African Wine Industry Information and Systems (SAWIS), 2022. Bulk wine and juice prices January - September 2022. https://www.sawis.co.za/info/priceranges_2022.php Date of access: 03.12.2022.         [ Links ]

Schmidtke, L.M., Schwartz, L.J., Schueuermann, C. & Steel, C.C., 2019. Discrimination of Aspergillus spp., Botrytis cinerea, and Penicillium expansum in grape berries by ATR-FTIR spectroscopy. Am. J. Enol. Vitic. 70(1), 68-76.         [ Links ]

Schueuermann, C., Steel, C.C., Blackman, J.W., Clark, A.C., Schwarz, L.J., Moraga, J., Collado, I.G. & Schmidtke, L.M., 2019. A GC-MS untargeted metabolomics approach for the classification of chemical differences in grape juices based on fungal pathogen. Food Chem. 270, 375-384.         [ Links ]

Seem, R.C., 1984. Disease incidence and severity relationships. Ann. Rev. of Phytopathol. 22, 133-150.         [ Links ]

Simsek, Z., Vaara, E., Paruchuri, S., Nadkarni, S. & Shaw, J., 2019. New ways of seeing big data. Acad. Manag. J. 62(4), 971-978.         [ Links ]

Southey, T., 2022. Presentation: Data-driven decision making tools: the Terraclim integrated data tool applied to Chenin scenarios. 2^nd Chenin blanc International Congress, 1-3 November 2022, Stellenbosch, South Africa.         [ Links ]

Steel, C.C., Blackman, J.W. & Schmidtke, L.M., 2013. Grapevine bunch rots: Impacts on wine composition, quality and potential procedures for the removal of wine faults. J. Agric. Food Chem. 61(22), 5189-5206.         [ Links ]

Steel, C.C., Savocchia, S. & Greer, L.A., 2016. Management of bunch rot diseases of grapes in subtropical vineyards in Australia. Acta Hortic. 1115, 265-271.         [ Links ]

Steel, C.C., Schwartz, L.J., Qiu, Y., Schueuermann, C., Blackman, J.W., Clark, A.C. & Schmidtke, L.M., 2020. Thresholds for Botrytis bunch rot contamination of Chardonnay grapes based on the measurement of the fungal sterol, ergosterol. Aust. J. Grape Wine Res. 26(1), 79-89.         [ Links ]

Steel, C.C et al., 2018. Report: Determination of thresholds for bunch rot contamination of grapes and techniques to ameliorate associated fungal taints, CSU13-01. Charles Sturt University, Wagga Wagga, NSW 100 pp. https://www.wineaustralia.com/getmedia/ad6cee75-3330-48ba-b2a9-bcc0b2fb6700/CSU-1301-Final-Report Date of access: 15.11.2022.         [ Links ]

Swanepoel, M., 2006. Monitoring the quality control chain from vineyard to wine: An industrial case study. Thesis, Stellenbosch University, Private Bag X1, 7602, Matieland (Stellenbosch), South Africa.         [ Links ]

Swanepoel, M., du Toit, M. & Nieuwoudt, H.H., 2007. Optimisation of the quantification of total soluble solids, pH and titratable acidity in South African grape must using fourier transform mid-infrared spectroscopy. South African J. Enol. Vitic. 28(2), 140-149.         [ Links ]

Tello, J. & Ibáñez, J., 2018. What do we know about grapevine bunch compactness? A state-of-the-art review. Aust. J. Grape Wine Res. 24(1), 6-23.         [ Links ]

Ubeda, C., Hornedo-Ortega, R., Cerezo, A.B., Garcia-Parrilla, M.C. & Troncoso, A.M., 2020. Chemical hazards in grape and wine, climate change and challenges to face. Food Chem. 314, 1-10.         [ Links ]

VanderWeide, J., Frioni, T., Ma, Z., Stoll, M., Poni, S. & Sabbatini, P., 2020. Early leaf removal as a strategy to improve ripening and lower cluster rot in cool climate (Vitis vinifera L.) Pinot Grigio. Am. J. Enol. Vitic. 71(1), 70-79.         [ Links ]

Versari, A., Parpinello, G.P., Mattioli, A.U. & Galassi, S., 2008.         [ Links ]

Determination of grape quality at harvest using Fourier-transform mid-infrared spectroscopy and multivariate analysis. Am. J. Enol. Vitic. 59(3), 317-322.         [ Links ]

Vignault, A., Pascual, O, Jourdes, M., Moine, V., Fermaud, M., Roudet, J., Canals, J.M., Teissedre, P.L. & Zamora, R., 2019. Impact of enological tannins on laccase activity. OENO One 53(1), 27-38.         [ Links ]

Wagner, C. & Esbensen, K.H., 2005. Theory of sampling: Four critical success factors before analysis. J. AOAC Int. 98(2), 275-281.         [ Links ]

Welke, J.E., 2019. Fungal and mycotoxin problems in grape juice and wine industries. Curr. Opin. Food Sci. 29, 7-13.         [ Links ]

Würz, D.A., Rufato, L., Bogo, A., Allebrandt, R., Pereira de Bem, B., Marcon Filho, J.L., Brighenti, A.F. & Bonin, B.F., 2020. Effects of leaf removal on grape cluster architecture and control of Botrytis bunch rot in Sauvignon Blanc grapevines in Southern Brazil. Crop Prot. 131, 1-6.         [ Links ]

Zoecklein, B.W., Williams, J.M. & Duncan, S.E., 2000. Effect of sour rot on the composition of White Riesling (Vitis vinifera L.) grapes. Small Fruits Rev. 1(1), 63-77.         [ Links ]

 

 

Submitted for publication: December 2022
Accepted for publication: May 2023

 

 

Acknowledgements: Funding of the research by South African Grape and Wine Research Institute (SAGWRI), Stellenbosch University, South Africa, the National Research Foundation (NRF) of South Africa, and Namaqua Wines, South Africa
R.J. Cornelissen: Current E-mail address: marina@namaquawines.com
* Corresponding author: E-mail address: hhn@sun.ac.za