美国食品企业检查员管理政策法规体系分析

以美国食品企业检查员为研究对象,从检查依据、检查员的构成及资质管理、检查员职责和任务、培训教育以及检查员的使用等方面,研究美国食品企业检查员的相关管理制度,分析其特点以及可供借鉴的经验,为探索建立我国食品企业检查员制度提供参考。     

Determination of Recognition Threshold and Just Noticeable Difference in the Sensory Perception of Pungency of Zanthoxylum bangeanum

Zanthoxylum bungeanum, also called the Szechuan pepper, is a pungent-flavored spice. Together with the chili pepper, it constitutes the typical flavor of famous Chinese Szechuan cuisine. With the worldwide popularity of Sichuan cuisine and pungent food, the research on sensory perception of pungency of Z. bungeanum becomes more important and necessary. This article first determined the sensory recognition threshold and just noticeable difference of pungency of Z. bungeanum. The pungent extract, containing hydroxyl α-sanshool (63.6%), hydroxyl β-sanshool (22.8%), and hydroxyl γ-sanshool (7.4%) from Z. bungeanum was used as the tested sample prepared in ethanol–water solution. Ten selected assessors participated in three sessions of sensory tests in standard sensory evaluation booths established according to ISO 8589 by following two-alternative forced choice procedure. The data showed that the recognition threshold was 0.036 mg pungent extract per 1 mL ethanol–water solution and just noticeable difference exponentially increased with the increase of the concentration of pungent extract solution. The response of pungency among assessors followed Weber’s Law with a stable Weber fraction (0.118) from 0.0360 to 0.500 mg pungent extract per 1 mL. Nevertheless, the fraction changed when the concentration of pungent extract solution was above 0.500 mg per 1 mL.     

干湿豆制浆模式下自制豆浆营养与感官品质分析

目的分析比较不同家用豆浆机干豆和湿豆2种模式下所制豆浆品质的差异方法以黄豆为原料选用国内外4个主流品牌的4款家用豆浆机分别采用干豆和湿豆2种模式制作豆浆,从营养品质(可溶性固形物、可溶性蛋白质、脂肪、还原糖含量)、物理性质(粘度、粒径)以及感官品质3个方面对豆浆品质进行比较和评价,分析干湿豆制浆模式和不同品牌豆浆机之间豆浆营养和感官品质的差异,探讨了不同制浆工艺对豆浆品质的影响。结果湿豆模式下所制得的豆浆在营养和感官品质上均优于干豆模式,不同品牌的豆浆机所制豆浆品质之间也存在较大差异。结论豆子经过浸泡后磨碎得更彻底,豆浆粒径更小,总营养物质溶出得更多。湿豆模式豆香味较浓郁,豆腥味淡,涩感弱,口感更绵滑。     

3种蜜源蜂蜜香气成分差异化信息分析研究

为挖掘不同蜜源蜂蜜香气成分差异,采用顶空固相微萃取-气质联用(GC-MS)法对油菜蜜、洋槐蜜以及椴树蜜3种蜜源蜂蜜香气成分进行了分析研究,并从蜂蜜香气成分种类构成、种类含量、特有成分分析了3种蜜源蜂蜜香气之间的差异。结果表明,油菜蜜、洋槐蜜香气成分种类构成相似,主要香气成分为醇类、酯类、酸类、醛类、烷烃类、酮类、呋喃和苯及其衍生物类,椴树蜜主要香气成分中除以上几大类外还含有一定的酚类、萜烯类物质,是椴树蜜特有类物质,但3种蜜源蜂蜜香气成分中各类物质含量相差较大,并且每种蜜源蜂蜜香气都有其特有的香气成分。油菜蜜、洋槐蜜、椴树蜜3种蜜源蜂蜜香气成分在种类构成、种类含量、特有成分上存有较大差异,特别是椴树蜜与油菜蜜和洋槐蜜之间的差异更为显著,这些差异性信息的分析研究为蜜源、掺假鉴别提供了理论依据和技术参考。     

Repurposing fish waste into gelatin as a potential alternative for mammalian sources: A review

Mammalian gelatin is extensively utilized in the food industry because of its physicochemical properties. However, its usage is restricted and essentially prohibited for religious people. Fish gelatin is a promising alternative with no religious and social restrictions. The desirable properties of fish gelatin can be significantly improved by various methods, such as the addition of active compounds, enzymes, and natural crosslinking agents (e.g., plant phenolics and genipin), and nonthermal physical treatments (e.g., ionizing radiation and high pressure). The aim of this study was to explore whether the properties of fish gelatin (gel strength, melting or gelling temperature, odor, viscosity, sensory properties, film-forming ability, etc.) could be improved to make it comparable to mammalian gelatin. The structure and properties of gelatins obtained from mammalian and fish sources are summarized. Moreover, the modification methods used to ameliorate the properties of fish gelatin, including rheological (gelling temperature from 13–19°C to 23–25°C), physicochemical (gel strengths from ∼200 to 250 g), and thermal properties (melting points from ∼25 to 30°C), are comprehensively discussed. The relevant literature reviewed and the technological advancements in the industry can propel the development of fish gelatin as a potential alternative to mammalian gelatin, thereby expanding its competitive market share with increasing utility.     

Using physical processes to improve physicochemical and structural characteristics of fresh and frozen/thawed sheep milk

We assessed the impact of stirring (ST), high shear dispersing (HSD) and low (LPH, 3.5 MPa) and high pressure homogenization (HPH, 50 MPa) on physicochemical and structural characteristics of whole and skimmed sheep milk fresh or previously frozen and thawed (FT). Freezing affected the size of the fat globules, their interaction with caseins, reduced calcium solubility (10%) and buffering capacity (5–11%). Amongst the studied processes, HSD was the only one unable to improve the milk stability. The other ones reduced the size of the fat globules and increased fat and casein interactions, favoring milk stability and reducing the creaming occurrence (>22%). LPH and HPH also reduced the sedimentation in skimmed milk (>37%). Moreover, all processes recovered the buffering capacity of FT samples. The effectiveness of the processes can be ordered as ST < LPH < HPH, but the final choice will depend on the stability improvement required for milk vs. acquisition and operational equipment costs.Practical applicationSheep milk is normally not homogenized because it has a lower fat globule size than cow milk, which reduces the creaming occurrence. However, creaming happens in some instances and it can be intensified if the milk is preserved frozen (to accumulate enough volume) prior to the dairy production, causing defects in the final products (mainly yogurts). The studied physical processes can be strategically used to solve this problem, increasing the milk emulsion stability, reducing the sedimentation occurrence and changing the buffering capacity to reach the same value of fresh milk.     

基于麻味物质构成特征的红花椒高效液相色谱 指纹图谱建立研究

目的针对红花椒的麻味物质构成特征建立红花椒的高效液相指纹图谱。方法采用Diamonsil C_(18)色谱柱(250 mm×4.6 mm,5μm)进行梯度洗脱,流动相为甲醇-水系统,检测波长为268 nm,建立指纹图谱并对谱图进行相似度分析。通过高效液相色谱-质谱联用法(HPLC-MS)对共有指纹峰进行分析定性。结果建立了红花椒HPLC特征指纹图谱,确定13个共有峰,共有峰相对保留时间的相对偏差较小,均小于5%,相似度良好,HPLC-MS定性结果显示可知共有峰大部分为麻味物质。结论该分析方法简便、快速,且指纹图谱反映了红花椒麻味物质的主要构成特征,为红花椒的鉴定和质量评价提供了科学依据。     

New dimensionality reduction model (manifold learning) coupled with electronic tongue for green tea grade identification

Multivariate data analysis methods play a key role in extracting effective features to denote original tea samples. The most commonly used multivariate data analysis methods are principle component analysis and linear discriminant analysis. These methods are based on statistical learning theory and complete in mathematics. However, there is correlation and redundancy among multiple sensors of electronic tongue, and it cannot guarantee that the tea samples are linearly separable in the original data space. The aim of this study is to conduct new dimensionality reduction methods: manifold learning algorithms, to extract effective features from the responses of electronic tongue sensors, and the algorithm which gives the highest recognition accuracy is considered to be the best for tea quality gradation. Experimental results show that supervised nonlinear manifold learning algorithms outperform other methods and achieve the highest recognition accuracy for green tea with four quality grades.     

Artificial olfactory system with fault-tolerant sensor array

Numerous applications of artificial olfaction resulting from research in many branches of sciences have caused considerable interest in the enhancement of these systems. In this paper, we offer an architecture which is suitable for critical applications, such as medical diagnosis, where reliability and precision are deemed important. The proposed architecture is able to tolerate failures in the sensors of the array.In this study, the discriminating ability of the proposed architecture in detecting complex odors, as well as the performance of the proposed architecture in encountering sensor failure, were investigated and compared with the generic architecture. The results demonstrated that by applying the proposed architecture in the artificial olfactory system, the performance of system in the healthy mode was identical to the classic structure. However, in the faulty situation, the proposed architecture implied high identification ability of odor samples, while the generic architecture showed very poor performance in the same situation. Based on the results, it was possible to achieve high odor identification through the developed artificial olfactory system using the proposed architecture.