Study On Inhibition Of Compound Natural Preservatives Against Spoilage Separated From Salted Goose And Establishment To Predictive Growth Model In The Shelf Life

In this paper,low-temperature salted goose was used as an object.First of all,three strain microorganisms was classified from salted goose by the streaked plate,then they were identified by using physiological and biochemical test and 16S rDNA sequence analysis.The results indicated that the three strains in salted goose were Bacillus cereus,B.c,Pseudomonas fluorescens,P.f and Pantoea agglomerans,P.a.Then,compound of natural preservatives were carrried on screening against dominant spoilage bacteria isolated from salted goose by antibacterial experiments to obtain a significant inhibitory effect of several natural preservative,and optimum complex ratiowas 0.03%Nisin+0.6%chitosan+0.025%?-polylysine+3%2:1:1fructus mume,clove,licorice complex solution by orthogonal test.And then,the optimum proportion was 0.03%Nisin+0.6%chitosan+0.025%?-polylysine+3%2:1:lfructus mume,clove,licorice complex solution.And its applied research in salted goose was studied,taking total bacteria counts,pH value,TVB-N value,TBARS value,water loss and sense organ evaluation as the index to appraise its anticorrosion effect.The results showed that the compound antiseptic could prolong the shelf-life of salted goose 21 days,and have significantly(P<0.05)antimicrobial effect compared with the control.At last,The growth characteristics of the major spoilage bacteria(Bacillus cereus,B.c)in salted goose was studied by using the method of predictive microbiology.The Baranyi model was found to fit with representation of experimental curves.Then two growth parameters(growth rate and lag time)of the growth curves calculated.Under combined condition including temperature(10?30 ?),NaCl concentration(1?10%)and pH value(5?7),two mathematical models are set up by using growth parameters of putrefying bacteria(Bacillus cereus,B.c).They were RBF(Radial Basis Function)model and SVM(Support Vector Machines)model.Also,by comparing their relative error between predictive value and practical value,"SVM" model has better predictive capability and accuracy than "RBF" model in predicting food shelf life.