Processing Quality Evaluation Of Wine Grape(Dry Red) Varieties And Construction Of DNA Fingerprinting

In this paper,red wine grapes and red wine were studied,and we detected the differences and similarities between sensory quality,nutritional quality and processing quality,respectively,and the predictive models and its standards of the quality evaluation on wine grapes were established according to wine grape quality indicators with sensory score of wine,aiming to establish a suitability evaluation system and providing a theoretical basis for the selection of wine grapes for brewing wine.DNA fingerprinting were construsted to select materials for the brewing wine,distinguish species and provide theoretical support on genetic breeding.Specific findings are as follows:1)All quality indicators(19)of red wine grapes were tested,and ANOVA was used to analysis the differences and Pearson correlation analysis was used to detect the relationships among these indicators.The results showed that there were many differences on CV among wine sensory quality of different varieties of red grapes,and skin color b*,H,skin quality got a big one,and there was a significant difference(p<0.05)different varieties among red wine grapes physicochemical qualities.Polyphenol oxidase activity(PPO),the anthocyanins(TA)exhibited the biggest difference to the smallest difference in pH value.2)36 single varieties of dry red wine were brewed using a small test vinification wine method,and the physical and chemical indicators(10)were detected.The difference of significant was discussed by ANOVA.The monomeric phenols contents and anthocyanin contents of typical dry red wines(15)were determined by HPLC,and the correlation between various indicators were analyzed.The results showed:there’re a significant difference(p<0.05)among the indicators of dry red wines;Yan 73,Seibel Noir,Crimpose,MaBpyд,Muscat Hamburg and Black Olympia were the dry red wines with high resveratrol content and antioxidant capacity(ARP).Different composition and contents of monomeric phenols were detected and classified into 7 categories(phenolic acids,coumarin,flavonols,flavanones,flavanols,flavonoids and non-flavonoids),and the phenolics acids contents was the bigges among these;Delphinidin 3-0-glucoside content was the highest in the 9 detected compounds and the Yan 73 held the highest contents of phenolic compounds(935.6 mg/L)and anthocyanin content(9.35 mg/L)in 15 wines,and it can be used to color other wines.There were differences among physical and nutritional indices of 36 kinds of red wine significantly,and resveratrol content and ARP of red wine can be used to evaluate the quality and classification of dry red wines.3)36 kinds of dry red wine were blindly tasted to get the sensory evaluation by OIV,and the sensory scores were analyzed by ANOVA and transferred by using replacement interval method to get a more effective sensory data because of less system errors.Grape varieties were classified into 4 categories(excellent,potential,qualified,bad)according to the different sensory scores of wine using K-means clustering method,There are 8 kinds(Cabernet Franc,Cabernet Sauvignon,Cabernet Gernischet,Pinot Noir,ect)in excellent carieties,and 14(Merlot、Seibel Noir、Muscat Hamburg、Ruby Cabernet,ect)potential ones,9(Carignan,Maspyд,ect)qualified wine grapes and 5 bad red wine grapes(Tayщ,Black Queen,ect).The converted sensory scores can be used for red wine grapes for quality classification.4)Quality indicators of red wine grape were screened using principal component analysis and stepwise regression methods,and a wine grape quality evaluation model was established with a better prediction results,while the wine grape quality evaluation criteria was build based on the weight of each indicator for predicting processing qualities of wine grapes and the K-means clustering method.The classification results using wine grape quality evaluation criteria on the wine grapes was similar to the sensory evaluation categories with a correct rate of 88.9%,which indicated that the wine grape quality evaluation model and its criteria was feasible.5)14 kinds of wine grape leaves DNA were extracted by the improved CTAB method,and 257 bands were PCR amplified and 96 alleles were detected by 10 pairs of SSR primers,the average alleles was 9.6 with a range from 4 to 14 and polymorphism was 100%.Comparison the PIC value of 10 SSR,the ability to distinguish Sort(descending order)was:VVS5、VrZAG67>、VVMD5、VMC4D4、SCU05VV、VMC4C6、VrZAG62、VrZAG79、VVS4、VMD27.6)The bands amplified by PCR were used to divided these 14 wine grapes into 4 categories by SimQual species similarity coefficient and UPGMA cluster tree diagrams,:category 1 contains 8 varieties;category 2 contains 2;category 3 has 3 varieties and category 4 contains only one species,the Black Queen.DNA fingerprinting of 14 red wine grapes were constructed using a SSR primer combination(VVS5,VRZAG67,VMC4C6),not a single SSR primer.