摘要
Fruity esters are crucial in shaping wine aroma profile,but predicting their production is challenging,making it difficult to accurately control their concentration in wine.This study aimed to establish predictive models for wine fruity ester production based on the nitrogen profiles of initial grape juice.Synthetic must with recombined nitrogen contexts based on yeast nitrogen preference(preferred,non-preferred nitrogen sources,and Ehrlich amino acids)was used for alcoholic fermentation.Volatiles and amino acids were quantified with HPLC-PDA and HS-SPME-GC-MS,respectively.Multivariable linear regression(MLR)models of fermentation-derived volatile compounds were developed and validated in synthetic must and natural grape juices,respectively.Results indicated significant correlations between fruity ester yields and the initial nitrogen profiles.The MLR models showed that ethyl acetate and ethyl esters concentrations were significantly influenced by all three nitrogen source types,while higher alcohol acetates(HAAs)were affected by yeast-preferred nitrogen sources and Ehrlich amino acids.Higher alcohols were influenced only by Ehrlich amino acids.Validation in grape wine fermentation demonstrated high accuracy for the higher alcohol model,with relative errors within 17%in all conditions.The HAAs model showed good accuracy in wine grape must fermentations,with relative errors from 1.6%to 15.3%.The ethyl acetate and ethyl ester models were accurate only in white wine grape fermentations.In conclusion,the production of fruity esters is predictable based on the initial nitrogen profile,which is helpful for optimizing nitrogen management techniques to enhance aroma production in the winemaking process.
基金
supported by the Shaanxi Provincial Science and Technology Project for Innovation Team(2023-CX-TD-59)
the National Natural Science Foundation of China(32202213)
the Fundamental Research Funds of the Central Universities of Ministry of the Education of China(XYTD2023-12)
the Key Project for Experimental Technology Innovation of Northwest A&F University(A1070023104).
