Catarina Pereira1, Davide Mendes2, Nuno Martins3, Raquel Garcia4, Marco Gomes da Silva2, Maria João Cabrita4
1 MED - Mediterranean Institute for Agriculture, Environment and Development. Instituto de Investigação e Formação Avançada, Universidade de Évora, Pólo da Mitra, Ap. 94, 7006-554 Évora, Portugal.
2 LAQV-REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal.
3 MED – Mediterranean Institute for Agriculture, Environment and Development, Universidade de Évora, Pólo da Mitra. Ap. 94, 7006-554 Évora, Portugal.
4 MED – Mediterranean Institute for Agriculture, Environment and Development, Departamento de Fitotecnia, Escola de Ciências e Tecnologia, Universidade de Évora, Pólo da Mitra. Ap. 94, 7006-554 Évora, Portuga
Email contact: ccd.pereira[@]campus.fct.unl.pt
As environmental issues come more to the fore, vineyards residues are being looked at as solutions rather than problems. Aiming to develop a sustainable methodology for musts acidity correction in the process of winemaking, much needed in warm regions, the present study was performed according to Circular Economy values. Four red wines from Aragonez grapes and six white wines from Antão Vaz grapes were produced using two different strategies for musts acidity correction: i) the addition of a mixture of organic acids (Mix) commonly used in winemaking; ii) the addition of previously produced unripe grape musts (UM) from the same grape varieties. Also, a testimonial (T) sample was produced in both wine varieties with no acidity correction. Oenological parameters, amino acid (AA) content and volatile composition of all wines produced were determined and evaluated.
The AAs composition was quantified by HPLC-DAD, after a derivatization step to obtain the aminoenone derivatives [1,2]. The volatile organic compounds (VOCs) were determined by GC/MS, after an HS-SPME extraction [3]. One-way analysis of variance with Fisher’s least significant difference (LSD) test at p<0.05 and Principal Component Analysis (PCA) were performed with SPSS24.0.
The Aragonez wines showed significant differences between the wines with acidity correction by the unripe musts addition (UM-A and UM-B), showing the higher amounts of AAs (640.08 mg/L and 630.33 mg/L, respectively), and the wines from Mix and T, with lowest amounts of AAs (546.24 mg/L and 562.51 mg/L, respectively). Also, for the volatile compounds significant differences were found for the UM-B wine, with the highest amount of VOCs, and T wine, with the lowest amount of VOCs. As for the Antão Vaz wines, significant differences were obtained between all wines, regarding AA content, with T wine showing the higher amounts of AA (4395.13 mg/L), and Mix wine the lowest content. (2948.41 mg/L). On the volatile results no significant differences were obtained among them.
Principal component analysis (PCA) obtained with combined data of AAs and volatile compounds, after normalization, for all wine samples, shows the separation obtained for the Aragonez red wines and Antão Vaz white wines according to the type of acidification under study...
Results obtained indicate that the use of unripe grape musts can be a strategy to increase musts acidity, without a negative impact on wine characteristics.
References:
[1] S. Gómez-Alonso, I. Hermosín-Gutiérrez, E. García-Romero, Simultaneous HPLC Analysis of Biogenic Amines, Amino Acids, and Ammonium Ion as Aminoenone Derivatives in Wine and Beer Samples, J. Agric. Food Chem 55 (2007) 608–613. https://doi.org/10.1021/jf062820m
[2] C. Pereira, D. Mendes, T. Dias, R. Garcia, M. Gomes da Silva, M. J. Cabrita, Revealing the yeast modulation potential on amino acid composition and volatile profile of Arinto white wines by a combined chromatographic-based approach, J. Chromatogr. A 1641 (2021) 461991. https://doi.org/10.1016/j.chroma.2021.461991
[3] N. Martins, R. Garcia, D. Mendes, A.M. Costa Freitas, M. Gomes da Silva, M. J. Cabrita, An ancient winemaking technology: Exploring the volatile composition of amphora wines, LWT - Food Science and Technology 96 (2018) 288– 295. https://doi.org/10.1016/j.lwt.2018.05.048