纸巾细菌总数检测加入氯化三苯四氮唑(TTC)方法的探讨

目的 探讨一种能精确检测纸巾细菌总数的方法。方法 在细菌总数检测时加入氯化三苯四氮唑(TTC)试剂，TTC在细菌脱氢酶的作用下变为红色。结果 细菌菌落着红色，被检样品不着色。使细菌菌落与样品中的絮状颗粒及气泡明显区分开来。结论 本方法在纸巾细菌总数检测中操作简便，结果准确，易于推广。     

用TTC琼脂培养基测定食品中细菌总数的应用

食品中细菌总数的测定，国标法是采用普通琼脂倾注平皿培养计数法。在实际工作中，常遇到样品残渣微粒（特别是一些较难溶食品如糕点等）与细菌菌落难以区分的问题，影响了细菌计数的准确性。近年来不少学者在普通琼脂培养基中加入氯化三苯甲基四氮唑（ＴＴＣ），使菌落着色，从而将菌落与样品残渣微粒区分开来，以提高判数结果的准确性和可靠性。本文将９６份食品用此法和国标法进行细菌总数测定对照试验，结果报告如下：１材料和方法１．１材料 干燥营养琼脂：江苏省宜兴市万石培养基厂出品。 １％ＴＴＣ溶液：商品名为红四氮唑，由上海前…     

TTC－指示剂在菌落计数中应用的探讨

作者对在营养琼脂中加入TTC-指示剂进行食品菌落计数进行了探讨。同时还对TTC倾注法与标准方法(普通营养琼脂倾注法)、TTC涂抹法进行了比较，TTC—倾注法检出率显著高于标准法和TTC—涂抹，而TTC—涂抹法与标准法无显著差异。     

氯化三苯四氮唑对金黄色葡萄球菌抑制性的实验观察

在细菌检验工作中,菌落总数测定是用于检验样品被污染程度的一项基本指标。我国的食品检验国家标准采用普通琼脂倾注法,但是,在实际工作中,往往会因为被检验样品中含有沉渣（食品中的碎屑、化妆品中的颗粒等）,其形态类似细菌,给菌落计数工作造成一定的困难。我国的化妆品国家标准《化妆品卫生规范》2007版中介绍：在每100mL卵磷脂吐温80营养琼脂培养基中可加入0．5％氯化三苯四氮唑（TIC）溶液1mL用于菌落总数的测定的实验方法拉,其原理是检样中如有细菌存在,培养后细菌在脱氢酶的作用下,TTC接受氢而变成红色,使细菌着色,而检验样品中如存在碎屑或颗粒无颜色变化,便于菌落计数。     

检样稀释至倾注平板时间对食品中菌落总数测定结果的影响

菌落总数是用来判定食品被细菌污染的程度及其卫生质量的指标，它反映食品是否符合卫生要求，以便对被检食品做出适当的卫生学评价。在测定过程中每一步的操作均影响到菌落总数测定的准确性，一般认为较为关键的是样品的处理和稀释。     

Small and Medium Enterprises’ Perspectives on Food Fortification Amid the Growing Burden of Malnutrition

The need for a profound food system transformation has never been greater. The growing burden of malnutrition has become the new normal, with two billion people who are overweight, over 140 million children under five who are stunted and over two billion people affected by hidden hunger. Food fortification has been recognized as a cost-effective strategy to address micronutrient deficiencies. Small and medium enterprises (SMEs) play a strategic role in the food supply chain in low- and middle-income countries, accounting for over 80% of food sales. It is therefore critical to create an enabling environment to facilitate SMEs’ involvement in food fortification practices as a potential solution to tackle all forms of malnutrition. This review highlights SMEs’ relevance as agents of change in the food system through food fortification practices and their indirect yet key role in producing nutritious, tasty and affordable foods. It discusses their challenges (e.g., access to long-term finance, sustainable technical assistance, limited capacity), presents solutions and discusses how different actors can help SMEs to overcome these challenges. Furthermore, it presents a relevant public–private partnership case study to demonstrate how SMEs can address the growing burden of malnutrition through food fortification practices, nutrient profiling schemes and demand generation.     

食醋中菌落总数检验样品前处理方法的改进

目前,检测食醋的方法采用国标法[1],需先用20%~30%的灭菌无水碳酸钠溶液将食醋pH值调至中性,然后再折算样品稀释浓度,这个步骤既费时又烦琐。还容易造成样品的污染。对食醋菌落总数测定的前处理虽有报道[2],但此方法由于取样量太少,稀释度太大,不能反映样品的代表性,加之食醋本身又具有杀菌能力,所以更不易检出菌落总数。为此,我们将原调pH值的方法进行了改进,直接用碳酸钠盐水溶液进行自动调pH值。报道如下。1材料与方法1.1碳酸钠盐水溶液称取8 g碳酸钠,8.5 g氯化钠,水1 000ml溶解后装瓶,每瓶225 ml,经121℃,15 min灭菌。1.2实验方法1.2.…     

食品中蛋白质测定方法及样品消化过程的改进

蛋白质是食品检验中经常进行检测的项目。测定食品中蛋白质的含量，了解食品的质量，为合理配膳提供数据，保证不同人群对蛋白质的需要，掌握食品的营养价值和品质的变化，以达到合理利用食品资源。在蛋白质测定中常用的方法是《食品卫生检验方法》GB／T5009．5-2003中的第1法——凯氏定氮法。应用凯氏定氮法操作易出现失误造成结果偏差。为此，我们经过3年的实践探索总结了部分经验，在蛋白质的测定过程中，尤其在消化方而进行了改进，用三角烧瓶代替定氮瓶进行消化，取得了较为满意的结果，达到了易固定、消化时间缩短，定量方便，适用于大批样品消化的目的。现介绍如下，供同行们参考。     

有机磷农药残留检测的样品制备新技术

近年来,食品中有机磷农药残留分析的样品前处理技术发展了许多新方法,为此,重点概述了固相微萃取技术、超临界流体萃取技术、微波辅助萃取技术、单滴微萃取技术、压力液体萃取及亚临界水萃取在农药残留分析中的应用,同时对有关食品中有机磷农药残留分析技术的发展趋势方向进行了讨论。     

Food Neophobia,Familiarity with French Cuisine,Body Mass,and Restaurant Food Choices in a Sample of Polish Women

Food neophobia, a condition characterized by a reluctance or avoidance of unknown foods and meals, may influence food choice, and is also associated with body mass and familiarity with food items. This study aimed to analyze the associations between food neophobia, familiarity with French cuisine, body mass, and French restaurant menu food choices in a sample of 203 young Polish women. The Computer-Assisted Web Interview (CAWI) method was used in the study. The food choice questionnaire used for assessment was based on a model French restaurant menu, with dishes planned using a 2 × 2 factorial design for the components of neophobic potential (unfamiliar to Polish consumers) and animal-based components. Food neophobia, familiarity with French cuisine, and body mass were considered independent variables. The food neophobia scale (FNS) developed by Pliner and Hobden was used to assess food neophobia among respondents. The results showed an association between food neophobia and familiarity with French cuisine and French restaurant menu food choices (p ≤ 0.05), but no association with body mass was observed (p > 0.05). The respondents with a high level of food neophobia chose dishes with neophobic components (for soups and desserts) less often compared to those with a low neophobia level, and in the absence of such an association, they chose dishes with animal-based components (for starters and main courses) less often (p ≤ 0.05). The respondents who declared that they were familiar with French cuisine chose dishes with animal-based components (for starters and desserts) more often than those with no familiarity, but a reverse association was observed for soups (p ≤ 0.05). Based on the findings of the study, it may be concluded that food neophobia and familiarity with French cuisine may be important determinants of food choice within a French restaurant menu. The study did not show any association between body mass and the choice of dishes from the model French restaurant menu. The findings suggest that the presence of unfamiliar and animal-based ingredients may reduce the frequency of choosing specific dishes within a French restaurant menu, which may reduce the diversity of individuals’ diets.     

Food Choice Values and Food Literacy in a Nationwide Sample of Japanese Adults: Associations with Sex,Age, and Body Mass Index

This cross-sectional study of 2231 Japanese adults described food choice values and food literacy in relation to sex, age, and body mass index. We assessed eight food choice values (accessibility, convenience, health/weight control, tradition, sensory appeal, organic, comfort, and safety, using a 25-item scale), as well as food literacy, which was characterized by nutrition knowledge (using a validated 143-item questionnaire), cooking and food skills (using 14- and 19-item scales, respectively), and eight eating behaviors (hunger, food responsiveness, emotional overeating, enjoyment of food, satiety responsiveness, emotional undereating, food fussiness, and slowness in eating, using the 35-item Adult Eating Behavior Questionnaire). Females had higher means of all the variables than males, except for food fussiness. Compared to participants aged 19–39 and/or 40–59 years, those aged 60–80 years had low means of some food choice values (accessibility, convenience, sensory appeal, and comfort), nutrition knowledge, and all the food approach behaviors (hunger, food responsiveness, emotional overeating, and enjoyment of food) and high means of other food choice values (tradition, organic, and safety) and slowness in eating. Age was inversely associated with cooking and food skills in males, whereas the opposite was observed in females. The associations with body mass index were generally weak. These findings serve as both a reference and an indication for future research.     

Sample sizes for clinical trials with normal data

This article gives an overview of sample size calculations for parallel group and cross-over studies with Normal data. Sample size derivation is given for trials where the objective is to demonstrate: superiority, equivalence, non-inferiority, bioequivalence and estimation to a given precision, for different types I and II errors. It is demonstrated how the different trial objectives influence the null and alternative hypotheses of the trials and how these hypotheses influence the calculations. Sample size tables for the different types of trials and worked examples are given.     

Sample size for repeated measures studies with binary responses

We consider the sample size required for repeated measures studies when the response variable is binary. We propose the use of weighted least squares (WLS) for calculating the minimum sample size required to detect some minimum clinically important treatment effect. We provide tabulated values of the estimated sample sizes for a simple example and we discuss some practical considerations in determination of sample size with repeated binary responses.