接种量对单增李斯特菌生长/非生长界面的影响

在4个水平(10~1,10~3,10~5,10~7 CFU/m L)接种浓度下,通过肉眼观察培养基浊度结合涂布TSA-YE平板,对TSB-YE肉汤中培养的单增李斯特菌在温度(0~30℃)、盐度(0.5%~8.5%)、pH(4.0~7.5)条件下的生长/非生长响应进行测定,结果表明:接种量影响单增李斯特菌生长/非生长界面的位置。通过对各种生长条件下单增李斯特菌生长/非生长数据的分析,用多项式逻辑回归模型,建立单增李斯特菌生长/非生长的界面模型,模型拟合的一致性为83.8%到89.6%,拟合结果较好。接种量对微生物生长的起点有重要影响,为微生物生长受初菌数的影响提供定量分析数据,也为建立实际产品中微生物的生长/非生长界面模型提供参考依据。     

接种量对单增李斯特菌生长期及生长界面的影响

为了初步了解接种量对单增李斯特菌生长状况及生长/非生长界面的影响,本实验对单增李斯特菌在0、4、10、25℃下通过培养菌液在600nm下的吸光光度值对其生长周期曲线分别进行了测定,并分析了不同接种量的单增李斯特菌菌液在25℃下的生长周期状况,探讨了纯培养条件下不同盐度和pH下,接种量对单增李斯特菌生长/非生长状况的影响。结果表明:不同的温度下,单增李斯特菌的生长周期有很大的差别;而在相同温度下,接种量对单增李斯特菌的生长周期有较大的影响,随着接种水平的降低,菌种生长所需的延滞时间越长,接种量为107CFU/mL时,其生长延滞期为0~4h,而当接种量减少为10CFU/mL时,其生长延滞期为0~16h;而对于单增李斯特菌的生长/非生长界面而言,接种量对其也有一定的影响,但其作用机制还有待进一步深入的研究。     

蜡样芽胞杆菌生长/非生长界面模型的建立和评价

蜡样芽胞杆菌是软烤虾仁产品的主要变质菌,它是一种条件致病菌,通过产生腹泻毒素和呕吐毒素导致食物中毒。该研究旨在建立一种概率模型来预测出蜡样芽胞杆菌的生长/非生长情况或者生长概率。用lo-gistic回归模型建立不同温度、水分活度和pH环境因子作用下蜡样芽胞杆菌的生长/非生长界面模型。实验结果表明蜡样芽胞杆菌在脑心浸液肉汤培养基中生长的最低温度为9.99℃,最低水分活度为0.931,最小pH值为4.5。在此基础上建立的蜡样芽胞杆菌生长/非生长界面模型的χ2=49.73,P<0.000 1。用logistic回归模型建立的生长/非生长模型拟合效果达到极显著水平。模型的预测值同时很好地量化了环境因子对蜡样芽胞杆菌的协同作用,为软烤虾仁产品中蜡样芽胞杆菌的生长/非生长界面模型的建立提供了参考。     

酵母菌促进单核细胞增生李斯特氏菌的生长

为了缩短单核细胞增生李斯特氏菌(单增李斯特氏菌)的前增菌时间,提升检测效率,本研究将酵母菌(ATCC9763)作为一种生长促进剂加入到单核细胞增生李斯特氏菌的前增菌培养基(LB1)中,结果表明添加适量的酵母菌可以使单增生李斯特氏菌的生长速度提升近100%,并且这种促进作用与培养过程中酵母菌的接种量、培养基的溶氧量以及培养方式密切相关。根据酵母菌的生长特性分析,这种促进作用产生的原因很有可能是由于酵母菌在生长过程中发酵分解了培养基中的糖类等营养物质,改善了单增李斯特氏菌的营养条件,从而提高了单增李斯特氏菌的繁殖速度。本研究为缩短单增李斯特氏菌检测的富集培养时间,提高检测效率奠定了很好的基础,同时也侧面提示我们要关注发酵类食品遭受单增李斯特氏菌污染的食品安全风险。     

单增李斯特菌在生食鱼片中生长模型的建立

为研究生食鱼片中单增李斯特菌的生长规律,将单增李斯特菌接种到经冷杀菌后的3 种生食鱼片（三文鱼片、金枪鱼片、鲷鱼片）中,分别置于4、8、15、25、35 ℃环境下培养,间隔适当时间取出计数。用5 种常用的一级模型（Gompertz模型、Baranyi模型、Logistic模型、Richards模型和MMF模型）对实验数据进行拟合,通过比较相关系数R2和均方误差（mean square error,MSE）,确定最适一级模型为Gompertz模型。建立单增李斯特菌生长动力学参数（最大比生长速率μm和迟滞期λ）关于温度、pH值和水分活度的二级平方根扩展模型,并应用相关系数R2、偏差值Bf和准确值Af进行验证。结果表明,构建的二级模型能够很好地描述生食鱼片中单增李斯特菌的生长情况。     

鲜切结球莴苣中单增李斯特菌生长预测模型的建立

为建立不同温度下鲜切结球莴苣中单增李斯特菌生长模型,将单增李斯特菌接种到鲜切结球莴苣表面,并于不同温度下贮藏,获得其在4、8、16、24和32℃下的生长数据,选用Gompertz模型进行拟合,建立初级生长模型。在此基础上建立二级模型研究温度对初级模型中单增李斯特菌生长动力学参数的影响,并进行数学检验。结果表明,对最大比生长速率和延滞时间建立平方根模型,结果呈良好的线性关系,相关系数R2分别为0.977 2和0.984 7,所建立的预测模型能很好地描述不同温度下单增李斯特菌的生长动态。     

超高压协同温度处理对烟熏火腿中单增李斯特菌生长预测模型的建立

为了建立超高压协同温度处理烟熏火腿中单增李斯特菌生长预测模型。本研究分别以20、30、40、50℃结合600MPa对接种106cfu/g单增李斯特菌烟熏切片火腿进行5min的超高压处理,4℃贮藏条件下,每10d测定处理后样品中单增李斯特菌的数量。结果表明:当超高压协同处理的温度高于40℃时显著延长了单增李斯特菌在烟熏火腿修复生长的延滞期,所得生长曲线用修正的Gompertz模型进行了拟合,在35、45d进行验证,建立了烟熏火腿中单增李斯特菌在超高压协同温度处理后的生长预测模型,经验证其精确因子(Af)、偏差因子(Bf)、根平均方差(RMSE)和决定系数(R2)均在较好范围内,能较好的模拟单增李斯特菌的生长情况,为低温肉制品中单增李斯特菌的控制提供理论参考。     

鲜切雪莲果中单增李斯特菌生长动力学研究

为研究鲜切雪莲果中单增李斯特菌的生长规律,将4株单增李斯特菌混合接种至鲜切雪莲果表面,并分别置于4℃,10℃,16℃,20℃,25℃,30℃,37℃,40℃和43℃条件下培养,间隔时间取样计数,所得的生长数据分别代入Baranyi模型和Huang模型进行拟合,经综合比较2种初级模型的RMSE、RSE、AIC和生长速率,确定Baranyi模型和Huang模型均适合描述鲜切雪莲果中单增李斯特菌的生长,且具有等同的拟合效果。选取Huang平方根模型、Cardinal模型、Arrhenius-type模型描述温度对单增李斯特菌生长速率的影响,并通过Huang平方根模型和Cardinal模型估算单增李斯特菌的最低生长温度、最高生长温度,通过Cardinal模型估算单增李斯特菌的最适生长温度和最适生长速率,研究结果还表明Arrhenius-type模型能更准确地描述低温(4℃)条件下的单增李斯特菌的生长速率。建立的模型可为相关监管部门开展鲜切果蔬中单增李斯特菌的安全风险评估提供科学依据。     

巴氏杀菌奶中单增李斯特菌生长动力学模型的研究

为研究巴氏杀菌奶中单增李斯特菌的生长规律,将4株单增李斯特菌混合接种到巴氏杀菌奶中,并分别置于4、8、12、16、20、25、30、37、40、43℃条件下恒温培养,间隔时间取样计数。使用美国农业部开发的IPMP 2013软件,将4～43℃条件下得的生长数据分别代入Huang模型和Baranyi模型进行拟合,分析单增李斯特菌在不同温度下的生长动力学特征。在所有温度下均可以观察到单增李斯特菌的生长,所有生长曲线都显示出滞后期,指数期和稳定期。综合比较2种初级模型的RMSE、RSE、AIC和生长速率,确定Baranyi模型和Huang模型均适合描述巴氏杀菌奶中单增李斯特菌的生长,且具有等同的拟合效果。采用Ratkowsky平方根模型、Huang平方根模型和Cardinal模型描述温度对巴氏杀菌奶中单增李斯特菌生长速率的影响。研究表明:3种模型都能用于评价温度对其生长速率的影响。Ratkowsky平方根模型预测的单增李斯特菌的最低、最高温度为0.218℃和46.389℃,与文献报道的更为接近。因此,Ratkowsky平方根模型比Huang平方根模型和Cardinal模型更适合描述温度对单增李斯特菌生长的影响。建立的模型可为相关监管部门开展巴氏杀菌奶中单增李斯特菌的安全风险评估提供科学依据。     

生鲜猪肉中单增李斯特菌动态生长预测与数值模拟

构建生鲜猪肉中单增李斯特菌的动态生长预测模型。猪肉样品接种由3 株单增李斯特菌制备的混合菌液,并置于3 组波动温度（1～45 ℃）条件下培养,采用一步法对获得的生长数据进行分析,构建并比较由初级模型（Baranyi或Two-compartment模型）与二级模型（Cardinal模型）集成的组合模型。结果表明,Baranyi-Cardinal和Two-compartment-Cardinal模型均适合用于描述猪肉中单增李斯特菌的生长,由两者估计的猪肉样品中单增李斯特菌最低、最适、最高生长温度分别为0.94、38.37、45.36 ℃和1.03、37.96、45.58 ℃,最适生长速率分别为0.891 h－1和0.858 h－1,最大生长浓度分别为9.07（lg（CFU/g））和9.09（lg（CFU/g））;通过另设的4 组动态生长实验和3 组等温（4、20、37 ℃）生长实验对模型进行验证,分析表明,模型可以准确预测动态及等温条件下的单增李斯特菌的生长,预测曲线的均方根误差介于0.13～0.48 （lg（CFU/g））,残差服从均值为－0.02 （lg（CFU/g））、标准差为0.29（lg（CFU/g））的正态分布。最后,基于构建的模型开展生鲜猪肉家庭冰箱冷藏过程中单增李斯特菌的生长数值模拟,以证明模型潜在的应用性。本研究结果可用于猪肉中单增李斯特菌的生长预测及风险评估。     

三因子金黄色葡萄球菌生长/非生长模型构建

运用统计分析R软件,建立金黄色葡萄球菌在温度、pH、盐浓度3种环境因子影响下的生长/非生长模型,构建的回归模型参数值a_1、a_2、a_3、a_4、a_5、a_6值均低于0.01,具有高度显著的拟合效果。分析各因子不同取值得到的方程式曲线图得出:在温度为10~25℃,pH值为4.5~5.5,盐浓度为0.5%~14.5%时,单因子对金黄色葡萄球菌生长/非生长影响显著;其他选值范围,3种因子协同影响。     

软烤贻贝中蜡样芽孢杆菌生长/非生长界面模型建立与评价

建立软烤贻贝中蜡样芽孢杆菌标准菌株(ATCC49064与DSMZ 4312)在不同贮藏温度(T)、pH、水分活度(Aw)下生长/非生长界面模型,对其拟合情况和来自软烤贻贝蜡样芽孢杆菌(YB001)的验证情况进行分析和评价,并与已建立的脑心浸出液肉汤(BHI)中蜡样芽孢杆菌生长/非生长界面模型进行比较。所建模型总方程为Lopit(P)=-208.457-2.167·T+35.304·pH+705.573·Bw+1.117·T·pH-7.072·T·Bw-174.946·pH·Bw,其中R2-Nagelkerke=0.979和χ~2=0.019(df=8,P=1)显示拟合度较高,而且其预测一致率明显高于BHI培养基中建立的模型,表明该模型在预测软烤贻贝中蜡样芽孢杆菌的生长/非生长情况有很高的精确度和很好的适用性。此外,贮藏温度、水分活度、pH及其交互作用显著影响蜡样芽孢杆菌的生长/非生长(P0.05)。因此可以通过所建生长/非生长界面模型量化温度、水分活度、pH值等栅栏因子并结合其交互效应来确保软烤贻贝的高品质与安全性。     

Control of growth and differentiation of the mammary gland by growth factors

Mammary gland development is a complex process regulated by various steroid and polypeptide hormones. Although the systemic importance of hormones, such as estrogen, progesterone, prolactin, and growth hormone, in the growth of the mammary gland has been well documented, these hormones are virtually incapable of stimulating mammary cell growth in vitro. Thus, the growth stimuli for mammary cells requires clarification. In recent years, a number of growth factors have been discovered; this has prompted interest in examining possible involvement of these biologically active agents in the process of mammary gland development. Results presented herein indicate that several growth factors including epidermal growth factor, transforming growth factor alpha and beta, basic fibroblast growth factor, insulin-like growth factor-I, and mesenchyme-derived growth factor participate in the regulation of mammary cell growth and differentiation.     

Effects of l-arginine on growth hormone and insulin-like growth factor 1

Food Science and Biotechnology - l-Arginine has been reported to promote cellular and organismal growth. In this study, the effects of l-arginine on the expression of growth hormone (GH) and...     

The boundary for growth of Zygosaccharomyces bailii in acidified products described by models for time to growth and probability of growth

Models to predict days to growth and probability of growth of Zygosaccharomyces bailii in high-acid foods were developed, and the equations are presented here. The models were constructed from measurements of growth of Z. bailii using automated turbidimetry over a 29-day period at various pH, NaCl, fructose, and acetic acid levels. Statistical analyses were carried out using Statistical Analysis Systems LIFEREG procedures, and the data were fitted to log-logistic models. Model 1 predicts days to growth based on two factors, combined molar concentration of salt plus sugar and undissociated acetic acid. This model allows a growth/no-growth boundary to be visualized. The boundary is comparable with that established by G. Tuynenburg Muys (Process Biochem. 6:25-28, 1971), which still forms the basis of industry assumptions about the stability of acidic foods. Model 2 predicts days to growth based on the four independent factors of salt, sugar, acetic acid, and pH levels and is, therefore, much more useful for product development. Validation data derived from challenge studies in retail products from the U.S. market are presented for Model 2, showing that the model gives reliable, fail-safe predictions and is suitable for use in predicting growth responses of Z. bailii in high-acid foods. Model 3 predicts probability of growth of Z. bailii in 29 days. This model is most useful for spoilage risk assessment. All three models showed good agreement between predictions and observed values for the underlying data.     

Regulation of ovarian follicular growth by somatotropin and insulin-like growth factors in cattle

Somatotropin (ST), insulin-like growth factor (IGF)-I, and IGF-II affect animal growth and lactation as well as animal reproduction. Understanding the effects of ST and the IGF on reproduction is important because ST and IGF-I undergo dynamic changes prior to the postpartum breeding period. In addition, administration of recombinant bovine somatotropin (rbST) to lactating cows is a common practice that increases blood concentrations of ST and IGF-I during the breeding period. In vivo, administration of rbST caused greater ovarian follicular development. The effects of rbST may represent direct actions of ST because ST receptors are found within granulosa cells as well as oocytes. Alternatively, the actions of ST may be indirectly mediated by increased IGF-I and (or) nutrient partitioning that occurs after rbST. Both IGF-I and IGF-II are synthesized within the ovary. Ovarian IGF are, therefore, a composite of IGF from both endocrine (liver) and autocrine and paracrine (ovary) sources. The IGF stimulate ovarian function by acting synergistically with gonadotropins to promote growth and steroidogenesis of ovarian cells. Actions of IGF-I and -II are restrained by a series of IGF binding proteins (IGFBP) that either originate from the blood or are synthesized locally within the follicle. Degradation and differential synthesis of IGFBP are important mechanisms regulating IGFBP amounts. The relative amounts of IGFBP may ultimately determine ovarian IGF action. Future studies of ST and IGFs should focus on the hormones, receptors, and binding proteins as well as the metabolic requirements for normal ovarian function in dairy cattle.     

纳米技术与非织造布产业

最近在巴尔的摩召开的由非织造布工业协会与世界纸浆、造纸和印染加工工业技术协会(INDA—TAPPI)举办的国际非织造布技术会议上，人们发现用于非织造布制造的技术种类越来越多，也越来越复杂。随着非织造布工业的发展，围绕非织造布生产的主要工艺流程和原材料的学术     

1993 Industry growth

According to industry tracker Technomic Inc., 1993 food purchases in noncommercial foodservice will increase only slightly, moving up a little less than 1%. While this is greater than the 1992 growth rate of 0.3%, it's still less than half as strong as that of the commercial market.     

Analysis of a novel class of predictive microbial growth models and application to coculture growth

In this paper, a novel class of microbial growth models is analysed. In contrast with the currently used logistic type models (e.g., the model of Baranyi and Roberts [Baranyi, J., Roberts, T.A., 1994. A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology 23, 277–294]), the novel model class, presented in Van Impe et al. (Van Impe, J.F., Poschet, F., Geeraerd, A.H., Vereecken, K.M., 2004. Towards a novel class of predictive microbial growth models. International Journal of Food Microbiology, this issue), explicitly incorporates nutrient exhaustion and/or metabolic waste product effects inducing stationary phase behaviour. As such, these novel model types can be extended in a natural way towards microbial interactions in cocultures and microbial growth in structured foods. Two illustrative case studies of the novel model types are thoroughly analysed and compared to the widely used model of Baranyi and Roberts. In a first case study, the stationary phase is assumed to be solely resulting from toxic product inhibition and is described as a function of the pH-evolution. In the second case study, substrate exhaustion is the sole cause of the stationary phase. Finally, a more complex case study of a so-called P-model is presented, dealing with a coculture inhibition of Listeria innocua mediated by lactic acid production of Lactococcus lactis.     

Interaction between lactose levels and antimicrobial growth promoters on growth performance of weanling pigs

In experiment 1, 224 pigs (initially 8.85 kg and 28 ± 2 days of age) were used in a 2 × 2 factorial arrangement of treatments to investigate the interaction between lactofeed (LF70) (860 g kg^?1 whey permeate, 140 g kg^?1 soya bean meal) level (175 g kg^?1 and 350 g kg^?1) and avilamycin (0 and 40 mg kg^?1) inclusion in piglet starter diets. Pigs were fed starter diets from day 0 to day 22 and a transition diet was fed from day 23 to day 39. The inclusion level of LF70 in the transition diet was 75 g kg^?1 and 150 g kg^?1. Pigs fed 350 g kg^?1 LF70 had a higher daily gain (ADG) (p < 0.01) and an improved feed conversion ratio (FCR) (p < 0.05) during the starter period than the pigs fed 175 g kg^?1 LF70. Pigs fed medicated diets had a higher ADG (p < 0.05) and an improved FCR (p < 0.05) than the non‐medicated fed pigs during the starter period. There was an increase in feed intake (AFI) (p < 0.05) during the transition period with increasing levels of LF70. There was an improvement in FCR during the transition period with the inclusion of avilamycin (p < 0.01). There was a significant interaction (p < 0.01) between LF70 and avilamycin for ADG during the transition period. The inclusion of avilamycin at 175 g kg^?1 LF70 inclusion had no effect (p > 0.05) on ADG. However at 350 g kg^?1 LF70 inclusion the pigs offered medicated diets had a higher ADG (p < 0.001) compared with non‐medicated diets. In experiment 2, 224 pigs (initially 8.85 kg and 28 ± 2 days of age) were used in a 2 × 2 factorial to investigate the interaction between LF70 level (175 g kg^?1 and 350 g kg^?1) and zinc oxide (ZnO) (0 and 3.1 g kg^?1) inclusion in piglet starter diets. The inclusion level of LF70 in the transition diet was 75 g kg^?1 and 150 g kg^?1 and of ZnO was 2 g kg^?1. There was a significant increase (p < 0.05) in ADG with increasing levels of LF70 during the starter period. The inclusion of ZnO during the starter period resulted in an increase in ADG (p < 0.001) and FCR (p < 0.05) compared with no ZnO inclusion. Neither the inclusion of zinc oxide not of LF70 had an effect (p > 0.05) on performance during the transition period. In conclusion the supplementation of starter diets with increasing levels of LF70, ZnO and avilamycin resulted in increased ADG and improved FCR. Copyright © 2004 Society of Chemical Industry