## 4 Discussion  
Until now, yeast diversity analysis by culture-dependent techniques has been performed using 5.8S-ITS-RFLP analysis and/or 26S rDNA D1/D2 domain sequencing [4; 6; 15; 49; 50; 51]. This approach based on PCR analysis and DNA sequencing is time-consuming. Recently, MALDI-TOF MS has been demonstrated to be a rapid and cost-effective tool for the identification of wine yeast at the species level [26; 29; 33]. In this study, species identification by MALDI-TOF MS was validated for 66% of wine yeast isolated at the prefermentary or beginning of alcoholic fermentation stages, in comparison with 26S rDNA sequencing. These first results revealed that it was necessary to enrich the MALDI-TOF MS Biotyper database not only with missing wine yeast species, such as _Starmerella bacillaris_, but also to add wine strains for some species, such as _S. cerevisiae_ or _H. urarum_, to improve identification. Different authors [28; 52] have already highlighted the importance of enriching the yeast database from standard spectra of isolates originated from the oenological environment. In the present study, the Biotyper database was extended by an oenological laboratory-specific database (43 new additional strains corresponding to 17 different species specific to the wine environment). [PERSON] et al. (2017) [28] reported the successful identification of 95.4% of yeast isolates after optimization of the preanalytical steps and the development of an in-house MS database. By using standard procedures for colony extraction (without optimization of the preanalytical steps) and an oenological laboratory specific extended data base, we were able to obtain the same identification rate with 95% of the isolates successfully identified. Our results confirmed that MALDI-TOF MS is a promising and robust method for wine yeast identification at the species level. However, this method does not currently allow differentiation at strain level in the oenological context, especially for _Saccharomyces cerevisiae_[28; 32]. The second aim of the study was to consider a mix of two non-_Saccharomyces_ yeasts as bioprotection (_Toruslospora delbrueckii_ and _Metschnikowia pulcherrina_) during the prefermentary stages without sulfur dioxide addition at the industrial scale. The MALDI-TOF MS method was used to assess the yeast diversity of the grape juice compared with different commonly-used methods and to monitor the implantation of both bioprotective species. First, the population dynamics of _Toruslospora delbrueckii_, _Metschnikowia pulcherrina_, and _Hanseniospora_ sp. were analyzed using Q-PCR. By targeting known species in the must ecosystem, this technique has the major advantage of establishing their population dynamics with a low detection level. Its major drawback lies in an overestimation that may be caused by the lack of discrimination between live and dying microorganisms. In the present work, this method allowed us to quantify population levels and to confirm the effective implantation of _Toruslospora delbrueckii_ and _Metschnikowia pulcherrina_ in the bioprotection treatment during the prefermentary stages. DNA metabarcoding is a method that is increasingly being used to characterize and quantify biodiversity in environmental samples. Illumina metabarcoding generates shorter reads but achieves deeper sequencing than 454 metabarcoding approaches [53]. This \begin{table}
\begin{tabular}{c c c} \hline \hline
**Stage** & **Treatment** & **Shannon** \\ \hline \multirow{3}{*}{Vatting} & 0 & 1.34 \\  & SO\({}_{2}\) & 1.21 \\  & BP & 0.68 \\ \hline \multirow{3}{*}{24 h of maceration} & 0 & 1.24 \\  & SO\({}_{2}\) & 1.16 \\  & BP & 0.52 \\ \hline \multirow{3}{*}{48 h of maceration} & 0 & 1.24 \\  & SO\({}_{2}\) & 1.58 \\ \cline{1-1}  & BP & 0.5 \\ \hline \hline \end{tabular}  
0: without any treatment; SO\({}_{2}\): 50 mg/L applied in must after crushed; BP: 50 mg/L of bioprotection applied on grapes and without SO\({}_{2}\).  
\end{table}