Moulds and yeasts in fruit salads and fruit juices

Thirty-eight fruit salad samples including cantaloupe, citrus fruits, honeydew, pineapple, cut strawberries and mixed fruit salads, and 65 pasteurized fruit juice samples (apple, carrot, grapefruit, grape and orange juices, apple cider, and soy milk) were purchased from local supermarkets in the Washington, DC area and tested for fungal contamination. The majority of fruit salad samples (97%) were contaminated with yeasts at levels ranging from <2.0 to 9.72 log10 of colony forming units per gram (cfu/g). Frequently encountered yeasts were Pichia spp., Candida pulcherrima, C. lambica, C. sake, Rhodotorula spp., and Debaryomyces polymorphus. Low numbers of Penicillium spp. were found in pineapple salads, whereas Cladosporium spp. were present in mixed fruit and cut strawberry salads. Twenty-two per cent of the fruit juice samples tested showed fungal contamination. Yeasts were the predominant contaminants ranging from <1.0 to 6.83 log10 cfu/ml. Yeasts commonly found in fruit juices were C. lambica, C. sake, and Rhodotorula rubra. Geotrichum spp. and low numbers of Penicillium and Fusarium spp. (1.70 and 1.60 log10 cfu/ml, respectively) were present in grapefruit juice.     

Moulds and yeasts in fresh and minimally processed vegetables, and sprouts

A limited survey of fresh and minimally processed vegetables, and sprouts was conducted in the Washington, DC area to determine if potentially toxigenic and pathogenic fungi were present in these commodities. Thirty-nine ready-to-eat salads, 29 whole fresh vegetables and 116 sprout samples (bean, alfalfa, broccoli, crunchy, garlic, spicy, onion, clover, lentil and multi-seed sprouts) were purchased from 13 local supermarkets and tested for yeast and mould counts as well as the presence of toxigenic moulds. Yeasts were the most prevalent organisms found in these samples, at levels ranging from less than 100 to 4.0x10(8) cfu/g. Mould counts generally ranged from less than 100 to 4.0x10(4) cfu/g. Two crunchy sprout samples, however, contained unusually high numbers of Penicillium (1.1x10(8) and 1.3x10(8) cfu/g), two alfalfa sprout samples contained Geotrichum populations about 10(6) cfu/g, and two alfalfa sprout samples had Cladosporium counts higher than 2.5x10(5) cfu/g. The most common moulds found in fresh and minimally processed vegetables were Cladosporium, Alternaria and Penicillium; less common was Geotrichum. The most frequently isolated moulds from sprouts were Alternaria, Cladosporium, Penicillium, and Phoma. Phoma was especially common in alfalfa sprouts. Fusarium, Rhizopus, Mucor, and Geotrichum were isolated less often.     

Effect of incubation temperature on aerobic plate counts of beef and sheep carcasses

Australian regulations for microbiological testing of carcasses specify a number of incubation temperatures and media for meat processed at both domestic and export establishments. Accordingly, the effect of incubation temperature and media on aerobic plate counts of samples from beef and sheep carcasses was investigated. For both species, aerobic plate counts on Petrifilm incubated at 35 degrees C were significantly lower than those counts on Petrifilm and pour plates incubated at 25 and 30 degrees C, reflecting the inability of many psychrotrophs to grow at 35 degrees C. When samples were taken from carcasses that had been stored in abattoir chillers for periods between 16 h and 5 days, difference between counts at 35 degrees C versus those incubated at 25 and 30 degrees C became greater as the period of refrigerated storage increased. For export beef carcasses, the effect of this difference is minimal, since the vast majority of counts incubated at 35 degrees C are done on carcasses that have been chilled for less than 24 h and will not have a large proportion of psychrotrophs.     

Nadh: Ubiquinone oxidoreductase in obligate aerobic yeasts

The strictly aerobic yeasts Candida pinus, Cryptococcus albidus, Rhodotorula minuta, Rhodotorula mucilaginosa and Trichosporon beigelii possess mitochondrial NADH dehydrogenases with significant features of the NADH:ubiquinone oxidoreductase (complex I). These species show in all growth phases and under standard cultivation conditions, NADH dehydrogenases of approximately 700 kDa, which are sensitive to rotenone, a specific inhibitor of this complex. Identical results were obtained with the weakly fermenting C. pinus. The facultatively fermenting yeasts Saccharomyces cerevisiae and Kluyveromyces marxianus do not possess the 700 kDa-complex and are insensitive to rotenone. In S. cerevisiae, a rotenone-insensitive NADH dehydrogenase of about 500–600 kDa is detected only in stationary phase cells. As in Neurospora crassa, upon incubation of the obligately aerobic yeast R. mucilaginosa with chloramphenicol, an intermediate NADH dehydrogenase of approximately 350 kDa was formed, which was insensitive to rotenone.     

食品中大肠菌群平板计数结果不确定度的评定

依据国家标准和测量不确定度的评定方法以及国际通行的普松理论(poisson theory),评定食品中大肠菌群检测结果的不确定度.通过分析影响食品中大肠菌群平板计数结果的不确定度来源,建立一种简单适用的大肠菌群平板计数不确定度评定方法.结果表明,影响食品中大肠菌群平板计数结果不确定度的主要因素为取样量的不确定度、稀释倍数的不确定度、加样体积的不确定度、平板上大肠菌群数量的不确定度和煌绿乳糖胆盐(BGLB)肉汤管产气比例产生的不确定度,其中后两者产生的不确定度所占分量最大.     

猪肉菌落总数检验中不确定度的评定

目的建立猪肉中菌落总数检测结果的不确定度评定方法。方法依据JJF 1059.1-2012《测量不确定度评定与表示》和GB4789.2-2010《食品微生物学检验菌落总数测定》以及相关统计学方法,对样品不确定度进行评定。结果依据所采用的方法,对同一样品测定10次菌落总数的扩展不确定度为0.090,k=2。结论本研究可以对单个样品的菌落总数检测结果的不确定度作出较好的估计,可适用于日常工作中菌落计数的不确定度评定。     

不同贮藏人参及西洋参超氧化物歧化酶活力比较

目的：探究一种新型复合保鲜贮藏方法, 预测鲜参切片的货架期。方法：应用酸性氧化电位水杀菌、真空包装、低温等离子体杀菌等技术复合处理鲜参切片,然后分别在−2、4、25和36 ℃进行贮藏,每隔15 d测定鲜参切片的色泽、水分含量、人参皂苷Rg1、Re、Rb1含量和菌落总数等指标,建立贮藏期间鲜参切片的菌落总数变化动力学模型。结果：确定鲜参切片的复合保鲜工艺为：酸性氧化电位水处理→真空包装→低温等离子体处理→低温贮藏。在−2和4 ℃贮藏有效地抑制鲜参切片菌落总数的增长、水分含量的下降,延缓鲜参切片颜色的变化。贮保藏60 d后,鲜参切片中人参皂苷Rg1、Re和Rb1的含量上升。通过基于菌落总数变化的一级反应动力学模型和Arrhenius方程,建立鲜参切片的货架期预测模型。结论：建立了鲜参切片的最佳复合保鲜贮藏方式,这种复合保鲜贮藏方法可有效抑制鲜参切片的品质劣化,延长其货架期。

     

水源水中菌落总数不确定度的评定

目的评估水源水中菌落总数检测结果的不确定度。方法按照GB/T 5750.12-2006《生活饮用水标准检验方法微生物指标》测定10份水源水样品中菌落总数,依据JJF 1059.1-2012《测量不确定度评定与表示》评定检测结果的不确定度。结果依据所采取的方法,在置信概率为95%时,水源水中菌落总数的扩展不确定度为0.062,10份样品测量结果均在其各自的置信区间范围内。结论本研究建立的方法同样适合类似检测条件下菌落总数不确定的评定。     

实验室菌落计数精密度控制的研究——Ⅰ影响精密度的因素

为提高食品中菌落总数测定的准确性,采用7组实验人员对含菌量在一定范围内的标本同时检测;不同实验人员对同一批平皿菌落数进行计数比对,实验对同一份标本进行重复加样检验,以统计学方法对实验数据进行分析。通过多个实验表明,试样的均衡性、读数误差控制范围的正确确定以及样本菌量的正确估计,都是影响实验室落计数精密度控制的因素。提示今后应针对这些影响因素。研究有效的控制方法。     

果汁中菌落总数的不确定度评定

目的建立评定菌落总数不确定度的方法,以减少实验误差并提高检测结果的精确度。方法按照GB 4789.2-2010《食品安全国家标准菌落总数测定》检测20份果汁样品中菌落总数,依据JJF 1059.1-2012《测量不确定度评定与表示》分析菌落总数的不确定度来源;采用合并样本标准差计算,评定检测结果的不确定度。结果在包含概率为95%时,果汁中菌落总数的扩展不确定度为0.10(以对数计),此结果适用于同类样品的检测。结论用合并样本标准差评定多个同类样本菌落总数的不确定度较为方便,随着检验数量的不断增加,数据可随时加入到合并样本中,从而对菌落总数的不确定度进行合理判定,从而对食品进行正确的卫生学评价。     

糕点中菌落总数测量结果的不确定度的评定

目的对糕点中菌落总数的测量结果进行不确定度评定。方法依据GB 4789.2-2016 《食品安全国家标准食品微生物学检验菌落总数测定》对糕点中菌落总数进行测定,建立数学模型,分析检验结果的影响因素,对不确定度因素的影响进行评价。结果通置信水平为95%,包含因子k=2,得10批样品的扩展不确定度分别为:0.2156、0.1194、0.1267、0.1293、0.1298、0.1163、0.1293、0.1155、0.1181、0.1243。结论糕点菌落总数检验中重复性检验和培养基的菌落生长率对不确定度影响最大,需要在检测过程中进行注意。     

Bioconversion,health benefits,and application of ginseng and red ginseng in dairy products

Ginseng and red ginseng are popular as functional foods in Asian countries such as Korea, Japan, and China. They possess various pharmacologic effects, including antioxidant, anti-inflammatory, anti-cancer, anti-obesity, and anti-viral activities. Ginsenosides are a class of pharmacologically active components in ginseng and red ginseng. Major ginsenosides are converted to minor ginsenosides, which have better bioavailability and cellular uptake, by microorganisms and enzymes. Studies have shown that ginseng and red ginseng can affect the physicochemical and sensory properties, ginsenosides content, and functional properties of dairy products. In addition, lactic acid bacteria in dairy products can convert into minor ginsenosides and ginseng and red ginseng improve functionality of products. This review will discuss the characteristics of ginseng and red ginseng, and their bioconversion, functionality, and application in dairy products.     

菌落总数测定结果不确定度的评定

目的对质控样中菌落总数测定结果进行不确定度评定。方法菌落总数测定依据GB4789.2-2016《食品安全国家标准食品微生物学检验菌落总数测定》进行测定和结果判断,再根据JJF 1059.1-2012《测量不确定度评定与表示》的规定,对测定过程中引入的不确定度分量进行评定,然后采用合成的方法来计算和评定菌落总数的不确定度。结果扩展不确定度为0.08,结果对数值取值区间为(3.85±0.08),取反对数取值区间则为(5900, 8500)。结论本方法可有效评定菌落总数的不确定度。     

Analysis of total aerobic viable counts in raw fish by high-throughput optical oxygen respirometry

A simple, miniaturized, and automated screening assay for the determination of total aerobic viable counts in fish samples is presented here. Fish tissue homogenates were prepared in peptone buffered water medium, according to standard method, and aliquots were dispensed into wells of a 96-well plate with the phosphorescent, oxygen-sensing probe GreenLight. Sample wells were covered with mineral oil (barrier for ambient oxygen), and the plate was monitored on a standard fluorescent reader at 30°C. The samples produced characteristic profiles, with a sharp increase in fluorescence above the baseline level at a certain threshold time, which could be correlated with initial microbial load. Five different fish species were analyzed: salmon, cod, plaice, mackerel, and whiting. Using a conventional agar plating method, the relationship between the threshold time and total aerobic viable counts load (in CFU per gram) was established, calibration curve generated, and the test was validated with 169 unknown fish samples. It showed a dynamic range of 10(4) to 10(7) CFU/g, accuracy of ± 1 log(CFU/g), assay time of 2 to 12 h (depending on the level of contamination), ruggedness with respect to the key assay parameters, simplicity (three pipetting steps, no serial dilutions), real-time data output, high sample throughput, and automation. With this test, quality of fish samples, CFU-per-gram levels, and their respective time profiles were determined.     

膨化食品中菌落总数测定结果的不确定度评定

目的对膨化食品中菌落总数检测结果进行不确定度评定,确保检测结果的准确可靠。方法根据GB 4789.2-2016《食品安全国家标准食品微生物学检验菌落总数测定》、SN/T 4091-2015《食品微生物学测量不确定度评估指南》和JJF1059.1-2012《测量不确定度评定与表示》,对膨化食品中的菌落总数进行测定,对产生不确定度的来源进行分析,并对其不确定度进行评定。结果对不确定度的分量进行量化和合成,合成不确定度为0.0295,扩展不确定度为0.0617。该批样品菌落总数的置信区间范围为1.1×10~4≤X≤1.4×10~4 CFU/g。结论影响膨化食品中菌落总数不确定度的主要因素是样品重复测量引入的不确定度。     

食品安全微生物学指示菌国内外标准应用的比较分析

菌落总数、大肠菌群、大肠埃希菌、肠杆菌科作为食品安全微生物限量的指示菌在国内外标准中的应用不尽相同.本文通过比较我国与欧盟、澳大利亚、新西兰、加拿大和香港地区的相关食品指示菌标准,为制定我国的食品安全微生物标准提供技术依据.     

罗非鱼中菌落总数测量结果的不确定度评定

目的对罗非鱼中菌落总数测量结果进行不确定度评定。方法采用平板计数法测定罗非鱼中的菌落总数,通过建立数学模型,识别不确定度来源,对不确定度来源进行分析,估算出各不确定度分量对测量不确定度的影响,最终合成测量结果的相对标准不确定度。结果被测样品中细菌总数为23000 CFU/g,在95%的置信区间下,扩展不确定度为920 CFU/g(k=2)。结论样品重复测定和结果修约是影响该方法不确定度的主要因素,因此该方法测量不确定度的评定对检测结果准确度的提高具有指导意义。     

Influence of aerobic and anaerobic conditions and yeasts on the reaction between (+)-catechin and glyoxylic acid

The reaction between (+)-catechin and glyoxylic acid in wine model solutions was studied under aerobic and anaerobic conditions in the presence and absence of yeasts with a view to determine their contributions to browning of white wine. Under aerobic conditions, the presence of yeasts reduced the production of colored products, the formation rate of which was similar to that observed under anaerobic conditions and in the absence of yeasts. These results reveal that yeasts and intermediate reaction products compete for oxygen. In the absence of oxygen, the production of colored compounds was even smaller in presence of yeasts, as a result of their ability to retain browning products as they form. Because the absence of oxygen not inhibited the formation of intermediate products resulting from oxidation reactions, an alternative oxidation pathway are proposed acting the glyoxylic acid as oxidant. In the usual concentrations of catechin in white wines, the studied reaction of (+)-catechin-glyoxylic acid can contribute significantly to the alteration of the wine color.     

米线中菌落总数测定结果的不确定度评估

目的对米线中菌落总数测定结果的不确定度进行评估。方法根据GB4789.2-2016《食品安全国家标准食品微生物学检验菌落总数测定》对米线中的菌落总数进行测定,通过建立评估的数学模型,分析不确定度的主要来源,计算出不确定度的各主要分量,得出合成不确定度和扩展不确定度。结果在置信水平为95%时,合成不确定度为0.23856,扩展不确定度为0.49764。结论影响结果不确定度的主要因素为样品的均匀性和重复测定,该评估系统可为今后实验室测定食品中菌落总数的不确定度评估提供参考,为检验检测结果的科学表达提供依据。     

食品菌落总数检测人员检测过程与结果比对分析

目的对实验室食品菌落总数检测人员检测过程与结果进行比对,加强实验室质量控制。方法根据内部质量控制的技术要求,按照GB 4789.2-2016《食品微生物学检验菌落总数测定》进行检测,对4名实验人员测定结果进行分析,评价其质量控制。结果 4名检验人员的测定结果均允许范围内,但A人员的测定结果普遍偏低,log值接近于满意范围临界值。结论检验人员严栺觃范地按照有兲操作觃程及标准觃定进行实验,定期进行人员比对,为实验室质量控制及管理提供可靠的数据及保障。