Different strategies for the rapid detection of Haze‐Forming Proteins (HFPs)

Abstract

Over the last decades, wine analysis has become an important analytical field, with emphasis placed on the development of new methodologies for characterization and elaboration control. Advances in wine chemistry knowledge allow the relation of specific wine faults or defects to the compounds responsible for those unpleasant characteristics. In most cases, those compounds are already naturally present in wine, but their effect does only become noticeable when their concentration exceeds the “sensory threshold”. 

Among the different instabilities that can occur, protein haze formation is a serious quality defect because consumers perceive hazy wines as “spoiled” [1]. Protein haze is caused by aggregation of residual grape pathogenesis-related proteins, particularly, thaumatin-like proteins and chitinases upon exposure to elevated temperatures during storage or transportation. Unfortunately, a specific method for the detection, or treatment, of such proteins in affected wines does not exist, and current practice is to use fining agents such as bentonite for their removal. On the one side, this might have a negative impact on wine quality, as not only haze forming proteins (HFPs) are being removed, but also other compounds that do impact on wine flavour/ aroma. On the other side, the lack of a specific method to quantify HFPs, tends to result in over-fining, which in turn has a more detrimental impact in wine quality, fining cost and waste generation. 

Herein we investigate on the development of an easy‐to‐use sensory device that allows to detect the presence of HFPs. To this aim, three different approaches have been explored. 

On the one hand, two different impedimetric biosensors based on screen-printed electrodes were developed, and their performance assessed towards standard solutions as well as wine samples. As an alternative, Fourier Transform Infrared (FT-IR) spectra were collected for different wine samples and chemometric tools such as discrete wavelet transform (DWT) and artificial neural networks (ANNs) were used to achieve the quantification of HFPs proteins. Detection of HFPs at the μg/L level has been achieved with both impedimetric biosensors in standard solutions, whereas the FT-IR-based approach allowed their quantification at the mg/L level in wine samples directly. 

[1] S.C. Van Sluyter, et al. J. Agr. Food Chem., 63 (2015) 4020-4030.