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Guan X.,State Key Laboratory of Dairy Biotechnology | Guan X.,University of Shanghai for Science and Technology | Gu F.-Q.,University of Shanghai for Science and Technology | Liu J.,Shanghai Maritime University | Yang Y.-J.,Shanghai Institute for Food and Drug Control
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2013

Brand traceability of several different kinds of milk powder was studied by combining near infrared spectroscopy diffuse reflectance mode with soft independent modeling of class analogy (SIMCA) in the present paper. The near infrared spectrum of 138 samples, including 54 Guangming milk powder samples, 43 Netherlands samples, and 33 Nestle samples and 8 Yili samples, were collected. After pretreatment of full spectrum data variables in training set, principal component analysis was performed, and the contribution rate of the cumulative variance of the first three principal components was about 99.07%. Milk powder principal component regression model based on SIMCA was established, and used to classify the milk powder samples in prediction sets. The results showed that the recognition rate of Guangming milk powder, Netherlands milk powder and Nestle milk powder was 78%, 75% and 100%, the rejection rate was 100%, 87%, and 88%, respectively. Therefore, the near infrared spectroscopy combined with SIMCA model can classify milk powder with high accuracy, and is a promising identification method of milk powder variety. Source

Xu J.,Jiangnan University | Han M.,Jiangnan University | Han M.,State Key Laboratory of Dairy Biotechnology | Ren X.,Jiangnan University | Zhang W.,Jiangnan University
Biochemical Engineering Journal | Year: 2016

To develop an L-lysine high-yielding strain, the enzymes involved in the L-lysine biosynthetic pathway, including aspartokinase III (AK III) and dihydrodipicolinate synthetase (DHDPS) were investigated. Allosteric enzymes involved in L-lysine production from L-lysine producer Escherichia coli LATR11 were sequenced and showed that AK III with mutation T344M or DHDPS with mutation H56K is more conducive to L-lysine production than AK III with mutation M318I or E250K-M318I-G323D or DHDPS with mutation H118Y. Moreover, an L-lysine high-yielding strain was developed from E. coli LATR11 via overexpression of ppc, lysCT344M, asd, dapAH56K, dapB, and lysA combined with heterologous expression of Corynebacterium glutamicum ddh. The resulting strain LATR11/pWG-DCSMASMBHc.gLP showed high L-lysine production (37.2 ± 2.3 g L−1) with productivity (QP) of 1.16 g L−1 h−1 in shake flasks. In fed-batch fermentation, LATR11/pWG-DCSMASMBHc.gLP produced about 125.6 g L−1 of L-lysine with QP of 3.14 g L−1 h−1 and glucose conversion rate (α) of 58.97% after 40 h. From which we got the following conclusions: the enzyme with non-feedback control and high activity, and the high flux through biosynthetic pathway are beneficial to improve L-lysine production in E. coli. These results provide a definite theoretical foundation for breeding amino acid high-yielding strains via genetic engineering from classical producers. © 2016 Source

Guan X.,State Key Laboratory of Dairy Biotechnology | Guan X.,University of Shanghai for Science and Technology | Liu J.,Shanghai Maritime University | Huang Q.,Rutgers University | Li J.,Jiangsu Yurun Food Industry Group Co.
Journal of Food Protection | Year: 2013

To improve the performance of meat freshness identification systems, we present a new identification method based on quantum-behaved particle swarm optimization (QPSO) and the support vector machine (SVM). Fresh pork, beef, mutton, and shrimp samples were stored in a hypobaric chamber for several days, and the conventional indices of meat freshness, including total volatile basic nitrogen content, aerobic plate count, pH value, and sensory scores, were determined to achieve the identification of sample freshness. However, the experiments showed that it was difficult to obtain an ideal freshness assessment by any single physicochemical or sensory property. Therefore, SVM was introduced to use these data to build a freshness model. Furthermore, QPSO was proposed to seek the optimal parameter combination of SVM. The experimental results indicated that the hybrid SVM model with QPSO could be used to predict meat freshness with 100% classification accuracy. © International Association for Food Protection. Source

Xu J.,Jiangnan University | Han M.,Jiangnan University | Han M.,State Key Laboratory of Dairy Biotechnology | Zhang J.,OriGene Biotechnology Co. | And 3 more authors.
Journal of Chemical Technology and Biotechnology | Year: 2014

BACKGROUND: Corynebacterium glutamicum was engineered for improvement of L-lysine production and minimization of by-products synthesis by genetically engineering. RESULTS: The most promising recombinant strain C. glutamicum Lys9 produced 62.1 mmol L-1 L-lysine with substrate-specific yield (YP/S) of 0.28 mol per mol of glucose in shake flasks fermentation, whereas parental strain showed more than four times lower L-lysine production and more than 10 times lower biomass-specific yield (YP/X) than that of C. glutamicum Lys9. L-lysine production and cell growth were drastically decreased by isocitrate dehydrogenase (ICD) attenuation in aceE deletion strains, indicating that down-regulation of ICD activity in aceE deletion strains adversely affects L-lysine production. In fed-batch fermentation, C. glutamicum Lys9 produced 526 mmol L-1 L-lysine, i.e. 96.8 g L-1 L-lysine-HCl with high yield of 0.422 mol per mol of glucose and productivity of 2.69 g L-1 h-1. Corynebacterium glutamicum Lys9 was devoid of any detectable L-alanine and L-lactate synthesis. CONCLUSION: Superior to classical producers to some degree, C. glutamicum Lys9 is more adaptable for industrial L-lysine production. In addition to L-lysine, pyruvate, oxaloacetate (OAA) and L-valine were produced by C. glutamicum Lys9, suggesting further optimization to improve L-lysine production by engineering the L-lysine and/or NADPH biosynthetic pathway. © 2013 Society of Chemical Industry. Source

Wang Y.,State Key Laboratory of Dairy Biotechnology | Wang Y.,Shanghai Normal University | Li Y.,Shanghai Normal University | Liu Y.,Shanghai Normal University | And 2 more authors.
International Journal of Biological Macromolecules | Year: 2015

Se-polysaccharides from Se-enriched tea leaves were purified by DEAE-sepharose fast flow gel column (2.5×60cm) and three polysaccharide fractions (Se-TPS1, Se-TPS2, and Se-TPS3) were isolated and purified with yields of 6.5, 37.14, and 8.57%, respectively. The average sizes of Se-TPS1 and Se-TPS2 were determined by HPGPC system, with molecular weights of 1.1×105 and 2.4×105Da, respectively. Se-TPS3 was a polysaccharide polymer with two peaks with molecular weights of 9.2×105 and 2.5×105Da. Monosaccharide components analysis by ion chromatography revealed Se-polysaccharides were acidic polysaccharoses and different from each other in monosaccharide kinds and molar ratio. Elements of Se, C, H, N, S, and 14 kinds of mineral elements were analyzed by AFS, EA, and ICP-AES, respectively. Spectral analysis (IR and UV) indicated Se-polysaccharides were typical glycoproteins. Morphological analyses of the samples were determined by SEM and AFM. In addition, the DPPH and superoxide radicals scavenging activities were also discussed to assess antioxidant activities of the samples, and Se-polysaccharides showed higher antioxidant activities compared to the ordinary polysaccharides. © 2015. Source

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