Immunological characterisation of barley polypeptides in lager foam

Eight monoclonal antibodies (mAb) recognising barley polypeptides have been identified from a library developed to wheat prolamins. The specificity or the mAb has been determined using enzyme-linked immunosorbent assay (ELISA) and immunoblotting. Six were of broad specificity, recognising D, B, C and γ-hordeins to varying degrees by both techniques. IFRN 0610 preferentially recognised γ-hordeins by ELISA but was highly specific for this hordein group by immunoblotting. Another mAb, IFRN 0624, bound to a M_r ∽ 18000 polypeptide belonging to the CM protein (trypsin/α-amylase inhibitor) family by immunoblotting. This, or a related protein, was detected by 0624 in all hordein fractions using ELISA. These mAb, together with two others described previously and found to recognise the repeat motif of C hordein, were used in ELISA and immunoblot analysis of Octyl-Sepharose fractions of lager foam. Hordein polypeptides were found in all foam fractions, indicating that much foam protein originates from the malt. The CM-like protein was found present in a virtually unmodified form. In contrast, the repeat motif of C hordein was not detected, indicating that it had either been destroyed or masked by other beer constituents. The foam stabilising agent, propylene glycol alginate (PGA), increased the apparent hydrophobicity of hordein fragments suggesting that at least part of the activity of PGA is mediated by interactions with the hordein components of foam.     

Mg2+ Selectively Isolates Gellan Gum from Dairy Products

Gellan gum was precipitated from the papain digest of dairy products by 5% MgSO₄. The precipitate was collected by centrifugation and washed with 2.5% MgSO₄ until the washings were negative to the phenol H_aSO₄ test. It was dispersed with hot 50% H₂SO₄ and the amount in the dispersion determined by the H₂SO₄-thiourea-cyste-ine-HCl reagent. Recovery from chocolate milk, yogurt, evaporated milk, ice cream, cream cheese, process cheese spread, flan and blue cheese (no oil) dressing ranged from 76–95%. Prior removal of fat and starch was unnecessary. Carrageenan, xanthan gum, alginate, pectin and other hydrocolloids did not interfere.     

Vitamin D Stability in Milk

A method was developed to determine vitamin D₃ in milk. It includes saponification, solid phase extraction and HPLC. Recovery of added vitamin D₃ was 93%. Vitamin D₃ concentrations in commercial milks were variable. Stability studies showed that on exposure to light, there was a slight loss of vitamin D₃ from fortified milk. Air exposure did not affect stability in milk. Upon standing there was some stratification of the vitamin in milk containers with slightly more vitamin D₃ in the top layer of milk than at the bottom.     

利用乳蛋白改善肉糜制品质量

乳蛋白是肉糜制品的优质乳化剂,它能与水和脂肪界面充分结合,形成较为稳定的水—蛋白质—脂肪系统,合理使用,可赋予成品良好的风味和口感及优良的物理性能.同时使用乳蛋白还可以尽量利用生产中的边角余料、低档肉,提高肉的利用率,降低生产成本.     

Listeria monocytogenes: Its importance in the dairy industry

Recent outbreaks of listeriosis associated with consumption of milk products contaminated with Listeria monocytogenes have focused attention on the importance of food-borne transmission of this disease. This review outlines current knowledge of the incidence of L monocytogenes in raw milk and its incidence in, and ability to survive, the manufacturing process for other dairy products—notably soft cheeses. Discrepancies in results obtained by researchers concerning growth of the organism at refrigeration temperatures and the bacterium's ability to survive pasteurisation are discussed.     

意大利WRAP300型纸箱包装机的技术改进

本文分析了意大利ＳＭＩ公司ＷＲＡＰ３００ 型纸箱包装机自身的结构问题,并对其关键部件进行了技术改进。通过实际使用,表明改进后的机器运行稳定、可靠,基本解决了原机存在的问题。     

啤酒大麦和麦芽微生物对啤酒质量的影响

叙述了啤酒大麦和麦芽微生物对啤酒质量的影响,同时讨论了其对人类健康的影响。     

影响啤酒苦味的因素

苦味是啤酒区别于其他酒类主要特征之一。作者针对啤酒苦味缺陷,从多酚物质、糖化用水、发酵泡盖、酵母自溶、氧等方面阐述了对啤酒苦味的影响,及改善啤酒苦味的工艺途径。     

基于循环取货的样品物流综合调度与管理系统

检验检疫样品物流综合调度与管理系统借鉴了现代物流理论中的循环取货原理,采用第三方物流服务进行集中统一的上门取样和递送检疫报告。系统综合运用了PDA手持终端、全球卫星定位系统(GPS)、地理信息系统(GIS),以及智能车辆路径规划算法等先进技术,能够达到提高送检效率,节约检验成本的目的。     

BP神经网络结合变量选择方法在牛奶蛋白质含量检测中的应用北大核心CSCD

牛奶中的蛋白质含量会影响牛奶的品质,利用高光谱图像的光谱特征信息研究对牛奶蛋白质含量预测的可行性。本文提出一种基于竞争性自适应重加权算法(competitive adaptive reweighted sampling, CARS)和连续投影算法(successive projections algorithm, SPA)结合多层前馈神经网络(back propagation, BP)的预测建模方法,实验以含有不同浓度蛋白质的牛奶为对象,利用可见光/近红外高光谱成像系统共采集到5种牛奶共计250组高光谱数据,通过实验对比选择采用标准化方法对获取到的吸收光谱预处理,然后采用CARS结合SPA筛选特征波长,得到18个特征波长,建立CARS-SPA-BP模型,经过试验,CARS-SPA-BP模型的训练集决定系数和测试集决定系数R;和R;分别达到0.971和0.968,训练集均方根误差(root mean square error of calibration,RMSEC)和测试集均方根误差(root mean square error of prediction,RMSEP)达到了0.033和0.034。研究发现,采用CARS结合SPA筛选的牛奶特征波长建立的多层前馈神经网络模型,其模型预测结果与全波长建模相比并没有明显降低,因此将CARS结合SPA用于波长筛选并且结合BP神经网络基本可以完成对牛奶蛋白质含量的预测。为验证CARS-SPA-BP模型的预测能力,在相同数据环境下,使用较为传统的偏最小二乘回归(partial least squares regression, PLSR)进行建模,实验结果表明,CARS-SPA-BP相较于PLSR,R;和RMSEP均有明显提升。研究表明,CARS-SPA-BP可充分利用牛奶光谱特征信息实现较高精度的牛奶蛋白质含量检测。