The objective of this study was to screen probiotic lactic acid bacteria (LAB) with beneficial properties such as acid and bile salt tolerance, antibacterial activity, autoaggregation ability, and cholesterol‐lowering capacity from fermented Cornus officinalis fruits. Eleven probiotic LAB strains, identified as ten Lactobacillus plantarum and one Lactobacillus casei, were screened out and evaluated by in vitro tests. The results of principal component analysis (PCA) based on probiotic characteristics suggested that L. plantarum 2519, 3725, and 3735 were promising probiotic candidates, which were better than the probiotic reference strain, Lactobacillus rhamnosus GG. Among them, L. plantarum 2519 showed the hightest autoaggregation value of 94.62%, and L. plantarum 3725 showed a cholesterol assimilation percentage of 47.83% and remarkable antimicrobial activity against five foodborne pathogens with the cell number decrease from 3.68 to 4.60 log cfu/mL. These results indicate that these three LAB strains are good candidates as probiotic starters. Practical applications Cornus officinalis is known as a kind of medicinal plant with fruits having many pharmacological activities, such as improving liver and kidney function, potent hpyerglycemic and antioxidant effect. C. officinalis is rich in endophytes, and its pharmacological activities may be associated with the metabolic products of endophytic bacteria. Therefore, the exploitation of microbial resources in spontaneous fermented C. officinalis fruits is beneficial to select probiotics. Moreover, the fruits from a natural reserve should be an excellent resource, attributing to the low impact of antimicrobial contamination may guarantee non or low intensity of antibiotic activity of their endophytic bacteria.
Performance evaluation techniques of manufacturing systems are powerful decision support tools especially at system design stage. In this paper, an approximate technique based on decomposition method is proposed for performance evaluation of serial homogeneous transfer lines with unreliable machines and finite transfer-delay buffers. The characteristic of transfer-delay buffers means that it takes some transit time to transfer the parts through buffers, which increases the complexity of transfer lines. In order to address the problem, we firstly transform the initial transfer line into an equivalent transfer line, a serial non-homogeneous transfer line with unreliable machines and finite buffers. Then another transformation which replaces the equivalent line by an approximate homogeneous line is introduced. Finally, decomposition method is used to deal with the approximate model. The accuracy and efficiency of the method are validated by simulation results.
Process capability index (PCI) has been widely applied in manufacturing industry as an effective management tool for quality evaluation and improvement, whose calculation in most existing research work is premised on the assumption that there exists no bias. In this paper, the bias of gauge which exerts an effect on the calculation of PCI is indicated inevitable. The influence on PCI caused by the bias is analyzed by constructing a comparative ratio R between the empirical process capability index and the PCI. A confidence interval estimation method is proposed to solve the underestimation problem of PCI.
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