应用Weibull Hazard Analysis方法预测食品货架寿命

本实验以市售灭菌乳为研究对象,应用Weibull模型通过对食品非感官指标的分析,预测食品的货架期。灭菌乳分别在25、30、35、40℃环境下恒温储藏,并定期随机抽样进行感官检验和测定酸度、细菌总数。应用Weibull Hazard Analysis(WHA)方法分析非感官实验数据来预测样品货架期,并与采用寿命加速方法ASLT和文献WHA方法得到的预测结果进行了比较。     

寿命可靠性计算在食品货架期分析中的初步应用

以市售灭菌乳为研究对象,应用Weibull Hazard Analysis(WHA)方法,通过对食品品质指标的分析,预测食品的货架期;同时,探讨寿命加速试验线性无偏估计法在灭菌乳货架期可靠性分析方面的初步应用,分别在25、30、35、40℃环境下恒温贮藏,并定期随机抽样进行感官检验和测定酸度。     

应用脂肪酶预测UHT乳货架期的研究

以市售UHT乳为研究对象,应用Arrhenius模型对脂肪酶进行分析,预测UHT乳的货架期.UHT乳分别在25、45℃环境下恒温储藏,并定期随机抽样,进行感官检验和脂肪酶含量测定.应用Arrhenius方法分析脂肪酶含量,来预测样品货架期,并建立了模型.     

应用游离氨基氮预测UHT乳货架期的研究

以市售UHT乳为研究对象,应用Arrhenius模型通过对游离氨基氮的分析,预测UHT乳的货架期.UHT乳分别在25℃和45℃环境下恒温储藏,并定期随机抽样进行感官检验和游离氨基氮质量浓度测定.应Arrhenius方法分析用游离氨基氮质量浓度来预测样品货架期,并建立了模型.     

威布尔分析法在青稞发酵酒货架期预测中的应用

利用威布尔危险值分析法(Weibull Hazard Analysis WHA),通过对不同贮存温度下青稞发酵酒跟踪感官评价,最终建立货架期预测数学模型,将预测货架期与实际货架期进行比较,预测数据的误差在-3.33%～4.86%,误差波动相对较小,预测模型应用效果较好。     

基于Arrhenius模型预测无乳糖超高温乳的货架期

采用电子眼、电子鼻、电子舌等感官评价技术,结合货架期加速实验(ASLT)的阿伦尼乌斯公式(Arrhenius)模型,建立无乳糖超高温灭菌乳(UHT乳)的货架期预测模型。将无乳糖UHT乳分别贮存于37、27、4℃下,以色泽、气味、滋味为主要指标,在不同的贮存温度下,综合分析无乳糖UHT乳品质与贮存时间之间的变化,并应用Arrhenius公式建立货架期模型。结果表明:37、27℃下贮存的无乳糖UHT乳色泽的发生显著性变化(P<0.05)的时间为24、33 d;苦味发生显著性变化(P<0.05)的时间为24、27 d;而贮存60 d气味无显著性变化(P>0.05)。4℃下贮存60 d的无乳糖UHT乳色泽、气味、滋味均无显著性差异(P>0.05)。以苦味为指标,利用Arrhenius公式拟合的货架期模型为:t=0.109×e-5.1882。选取37、27℃验证模型准确性,与实际货架期之间的误差分别为9.5%、12.5%,误差较小。用此公式计算4℃下无乳糖UHT乳货架期为71 d。因此,以感官指标为依据建立货架期预测模型可预测无乳糖UHT乳的货架期。     

基于感官与理化指标的椪柑果酒货架期预测模型

通过对不同贮藏温度下椪柑果酒的感官、理化(挥发酸)和微生物(细菌总数)指标的变化分析,将感官威布尔危害分析(Weibull Hazard Analysis,WHA)模型和动力学模型分别结合Arrhenius方程,建立2种指标下椪柑果酒的货架期预测模型,并验证结果。研究结果表明,基于感官评价指标,在25,30,35,40℃温度下的货架期预测终点分别是620,436,310,222d,相对误差为-5.48%~5.52%;基于挥发酸评价指标,在25,30,35,40℃温度下的货架期预测终点分别是633,450,319,227d,相对误差为-2.74%~8.96%。椪柑果酒的贮藏温度与细菌总数相关性不显著,不作为具体参考指标。基于感官评价指标的货架期预测模型性能较优,可用于椪柑果酒的货架期终点预测。     

Weibull模型在板鸭货架寿命预测中的应用

以重庆白市驿板鸭为研究对象,应用Weibull模型通过消费者对食品的接受性分析,来预测板鸭的货架寿命。板鸭分别在20、25、30℃下恒温连续贮藏,定期随机抽样进行感官和理化检验,应用危害分析对实验数据处理来得到预测模型,并对板鸭的货架寿命进行了预测。     

超高压灭菌技术在保障食品品质及安全性的 应用现状与展望

超高压灭菌技术能有效对食品进行杀菌和灭酶, 是食品加工业中的一种新型的非热力加工技术。本文综述了超高压灭菌原理、主要特点以及超高压处理对食品感官品质、酶活性、微生物、营养成分的影响, 并分析了超高压处理产品的安全性及其在食品加工业中的应用前景。     

应用ASLT法预测软面包的货架期

简要介绍食品储存期加速测试法,并采用该方法对某品牌软面包的货架期进行预测。通过检测食品的感官、理化和微生物指标,得到了47℃下的食品货架期为2d,37℃下的食品货架期为6d,由以上数据最后得到20℃下的软面包商业货架期为24d~39d。     

压缩饼干硬度临界值的确定以及加速试验条件下硬度的变化规律

压缩饼干是一种长货架期食品,理化指标和感官指标变化缓慢。为了阐明压缩饼干在贮藏过程中硬度变化规律,通常采用加速试验的方法。首先在50℃条件下采用感官可接受性评价和WHA(Weibull Hazard Analysis,威布尔危险分析)方法确定出压缩饼干硬度的感官可接受终点值以及以硬度作为指标的货架寿命预测模型。其次,分别将压缩饼干贮藏在40、60℃和70℃下进行加速试验,研究样品硬度变化与温度和贮藏时间之间的关系。结果表明:压缩饼干硬度的可接受临界值为290～330N;温度的增高明显地加快了压缩饼干变硬,温度越高压缩饼干达到硬度终点的时间越短。继续贮藏,硬度在一定范围内波动。     

青花椒酱的开发及其货架期预测

研究以青花椒为主要原料,辅以青椒和大蒜等原料,基于传统工艺开发了一种经超高压杀菌处理的花椒酱,对青花椒的护色方法进行优化,对超高压灭菌后的花椒酱进行了货架期预测。经过响应面优化护色剂使用量,发现青花椒经0.89 g/L抗坏血酸、0.1 g/L硫酸锌和2.62 g/L柠檬酸复配的护色液浸泡后护色效果显著。利用电子鼻对花椒酱的风味类型进行测定,结果表明青花椒酱中的风味类型主要由无机硫化物、烯萜类物质和氮氧化物风味成分组成。采用Q 10货架期预测模型对花椒酱的货架期进行预测。综合感官评价、色差、水分变化及菌落总数在花椒酱35℃和45℃贮藏条件下的变化情况得出:花椒酱在35℃贮藏条件下货架期为25 d;花椒酱在45℃贮藏条件下货架期为13 d。利用货架期模型预测花椒酱在4℃和25℃的货架期,结果表明花椒酱在贮藏温度为4℃时的货架期为189 d,在贮藏温度为25℃时的货架期为48 d。     

石榴风味乳饮料贮藏品质及货架期预测

以石榴汁和全脂奶粉为主要原料,添加低聚木糖,接种双歧杆菌（Bifidobacterium）进行发酵,制备石榴风味乳饮料。以不添加石榴汁和低聚木糖的普通乳饮料作为对照,分别考察4℃、25℃和35℃贮藏条件下乳饮料的品质变化。以酸度为评价指标,采用加速货架期实验（ASLT）法预测石榴风味乳饮料在4℃冷藏条件下的货架期。结果表明,石榴风味乳饮料在4℃、25℃和35℃条件贮藏期间酸度均逐渐增大,黏度和持水力均逐渐降低,双歧杆菌活菌数随着贮藏时间延长先升高后降低,且温度越高,变化幅度越大。石榴风味乳饮料在4℃冷藏条件下其酸度、黏度、持水力及双歧杆菌活菌数均优于对照乳饮料。经加速货架期实验预测,石榴风味乳饮料货架期可以达到24～40 d,优于市售的大部分酸乳的货架期21 d。     

酱香型蓝莓利口酒贮存过程中品质稳定性研究

采用食品加速货架期测试法（ALST）对酱香型蓝莓利口酒的货架期进行预测,首先通过对其理化指标、微生物指标和感官品质的检测,得到了产品在55 ℃条件下的货架期为6 d,在45 ℃条件下的货架期为20 d。再利用Q10模型计算出Q10值为10/3,预测酱香型蓝莓利口酒在商业贮存温度（20 ℃）条件下的货架期约为406 d。     

Commercial application of high-pressure processing for increasing starter-free fresh cheese shelf-life

Different non-thermal technologies have been proposed to extend the shelf-life of solid food products, high-pressure processing (HPP) being one of the emerging technologies which has been most extensively studied. In this study, one of the first commercial industrial-scale applications of HPP on a starter-free fresh cheese, with the aim of increasing its shelf-life, is presented. The effect of 500 MPa (5 min, 16 °C) on physico-chemical, microbial, colour, microstructure, texture and sensorial characteristics of starter-free fresh cheeses during cold storage of 21 days was studied. The results showed that pressurised cheeses presented a shelf-life of about 19–21 days when stored at 4 °C, whereas control cheese became unsuitable for consumption on day 7–8. On the other hand, cheese treated at 500 MPa was firmer and more yellow than the untreated one. However, these changes, which were detected by instrumental and sensory analysis, did not affect the preference for pressurised cheese. These results may lead to practical applications of HPP in the food industry to produce microbiologically safe cheese with extended shelf-life and sensory quality.     

Shelf life of packaged sliced dry fermented sausage under different temperature

The aim of this study was to investigate the shelf-life of commercial sliced dry fermented sausage during storage at different temperatures. Different laminate composition was used for vacuum and nitrogen (100% N₂) packaging. The microbiological, physico-chemical and sensory parameters were analysed during 120 days storage at 4, 22 and 37 °C. Packaging materials were analysed for their barrier characteristic (oxygen permeability).     

Determination of shelf-life of homogenized apple-based beikost storage at different temperatures using Weibull hazard model

A shelf-life model based on the storage temperature was developed for a homogenized fruit-based baby food. Bottles of apple compote for infant feeding were collected from a food company and stored at three different temperatures (23, 30 and 37 °C) during 420 days. CIELAB color space parameters, vitamin C, 5-hydroxymethylfurfural were measured and sensory analysis (sensory attributes and overall acceptability) was carried out during the length of the study. Weibull Hazard Method was utilized to set the shelf-life end-point of the product at 37 °C according to overall acceptability score given by the sensory panel. Considering a 50% probability of panellists to find the product as being unacceptable, the end of shelf-life for the apple-based beikost stored at 37 °C was achieved after 346 days. The statistical analysis of the data enabled us to select the most adequate zero- and first-order kinetic equations for both physicochemical and sensory attributes in samples stored at 37 °C. Color CIELAB parameters, vitamin C and sensory attributes (color and taste) were selected as the critical parameters. Their rejection times at 23 and 30 °C storage temperatures were obtained by extrapolation of the results given by Weibull method at 37 °C. Finally, rejection times for critical parameters were used to propose a shelf-life equation that showed 4.5 and 3.4 years of shelf-life when stored at 20 and 23 °C, respectively.     

Quantifying the spoilage and shelf-life of yoghurt with fruits

The aim of the present study was to develop a predictive model to quantify the spoilage of yoghurt with fruits. Product samples were stored at various temperatures (5-20 °C). Samples were subjected to microbiological (total viable counts, lactic acid bacteria-LAB, yeasts and moulds) and physico-chemical analysis (pH, titratable acidity and sugars). LAB was the dominant micro-flora. Yeasts population increased at all temperatures but a delay was observed during the first days of storage. Titratable acidity and pH remained almost constant at low temperatures (5 and 10 °C). However, at higher temperatures (>10 °C), an increase in titratable acidity and reduction in pH was observed. Sugar concentration (fructose, lactose and glucose) decreased during storage. A mathematical model was developed for shelf-life determination of the product. It was successfully validated at a temperature (17 °C) not used during model development. The results showed that shelf-life of this product could not be established based only on microbiological data and use of other parameters such as sensory or/and physico-chemical analysis is required. Shelf-life determination by spoilage tests is time-consuming and the need for new rapid techniques has been raised. The developed model could help dairy industries to establish shelf-life predictions on yoghurt with fruits stored under constant temperature conditions.