蜂蜜中糖类的高效液相色谱测定及其在蜂蜜品质控制中的应用研究

蜂蜜营养价值丰富,糖类是其最主要的成分,约占总量的百分之七十五以上。利用高效液相色谱示差折光检测器法检测3个品种、9个产地来源的真蜂蜜和两种掺假蜂蜜中果糖、葡萄糖、蔗糖、麦芽糖和乳糖的含量。然后,基于定量检测结果,利用“简单聚类”分析方法进行蜂蜜产地溯源和掺假鉴别研究。试验结果表明:蜂蜜中糖类含量最高的为果糖,其次是葡萄糖和蔗糖,麦芽糖和乳糖含量较低。掺假蜂蜜以及不同品种、不同产地的真蜂蜜中糖类的含量具有明显差异性,为其产地溯源和掺假鉴别研究奠定基础。基于蜂蜜中糖类的定量结果,来自不同产地的3种蜂蜜都得到了很好的区分,且对于果葡糖浆掺假蜂蜜和真蜂蜜区分效果也令人满意,该方法可行有效,适用于推广使用。     

枣花蜜蛋白质的电泳行为及其荧光光谱分析

以枣花蜜为试材,分析了不同产地的枣花蜜蛋白质的电泳行为及其荧光光谱特征。结果表明:不同地区枣花蜜的蛋白质含量存在明显差异,在供试样品中陕西佳县蛋白质含量最高(1 468.18μg/g),而富平蛋白质含量最低(719.03μg/g);SDS-PAGE分析发现,陕西省不同地区枣花蜜蛋白质主要电泳谱带差异不大,但不同省份的枣花蜜蛋白质电泳谱带差异较大,表现出特有的蛋白质谱带;荧光光谱分析发现,不同地区枣花蜜蛋白质的最大荧光吸收峰和强度存在明显差异,说明枣花蜜蛋白质组成和结构存在一定的差异。     

不同花源蜂蜜蛋白质组分及提取方法的比较

比较中国不同花源蜂蜜蛋白质组分及提取方法的差异。以枣花蜜、荆条蜜、龙眼蜜、土蜂蜜、洋槐蜜和油菜蜜为研究对象,比较6种蜂蜜蛋白质电泳行为差异;采用超滤法和硫酸-钨酸钠沉淀法提取蜂蜜蛋白,分析2种蛋白质提取方法的适用性及分离效果。6种不同花源蜂蜜蛋白质相对分子质量集中在14. 4～97. 4 k Da,但蛋白质组成和含量在品种间差异明显,而枣花蜜、龙眼蜜和土蜂蜜在> 97. 4 k Da存在较多高分子质量蛋白;超滤法适合提取枣花蜜、荆条蜜、洋槐蜜和油菜蜜蛋白质,而龙眼蜜和土蜂蜜适合用硫酸-钨酸钠沉淀法分离,2种方法获得的6种蜂蜜蛋白在SDS-PAGE和RP-HPLC图谱中呈现明显的分子质量和疏水性差异。这为基于蛋白质差异构建蜂蜜花源鉴别技术奠定理论基础。     

真假蜂蜜理化指标的分析

针对蜂蜜掺假和造假问题,对所选蜂蜜的主要理化指标:还原糖含量、酸度、蔗糖含量、淀粉酶值、费氏反应等进行测定。同时研究储存温度(10、37、45℃)和时间(0、10、20、30d)对蜂蜜淀粉酶值和蛋白质含量的影响,比较真假蜂蜜的淀粉酶值和蛋白质含量的变化。并且对纯正蜂蜜进行不同浓度蔗糖与不同浓度淀粉的掺假处理,分析掺假对蜂蜜淀粉酶值的影响。从而为辨别蜂蜜掺假方法提供相关依据。     

利用同工酶技术检测蜂蜜品质的新方法

本文尝试选择蜂蜜淀粉酶作为检测对象,通过对两种天然蜂蜜与掺假所用的工业淀粉酶的同工酶电泳比较,发现天然蜂蜜的淀粉酶同工酶酶谱和工业淀粉酶的同工酶酶谱存在不同。所以,可以通过淀粉酶同工酶电泳的方法来检测蜂蜜产品质量、以及蜂蜜掺假。     

淀粉酶在真假蜂蜜中的区别

针对蜂蜜掺假和造假的问题,文中对真、假蜂蜜中的蛋白质含量、淀粉酶活性及淀粉酶同工酶谱带差异进行测定分析。结果表明,天然蜂蜜在低温条件下可以在近1个月的时间内保持其蛋白质含量和酶值基本不变,但是在高温的条件下,随着贮存时间的延长,其蛋白质含量和酶值就会明显下降。而假蜂蜜其蛋白质含量和酶值均没有明显的变化。同工酶凝胶电泳结果也表明,真、假蜂蜜中淀粉酶同工酶谱带明显不同。因此,通过跟踪测定蜂蜜中蛋白质含量、淀粉酶值变化、淀粉同工酶谱带可以检测蜂蜜的真假及其质量变化。     

液相色谱质谱技术在食品掺假中的应用

食品欺诈是食品安全风险防控领域中的重要方面, 其中食品掺假作为食品欺诈的一种类型, 因其掺假物的种类性质、方式等不同往往可能带来或者引入食品安全问题。针对全球性食品掺假行为, 本文综述了近年来液相色谱-质谱联用技术用于解决肉制品、牛奶、食用植物油、蜂蜜4类食品掺假问题, 总结了该4类食品的主要掺假行为, 其中肉制品掺假分为地理来源改变、肉种类替代、添加剂非法使用、过敏原引入、病死畜禽肉; 乳制品掺假主要有奶源产地改变、不同动物奶、添加富氮化合物、添加剂违规; 植物油掺假主要有油种类混合、掺入不可食用油、植物油产地改变、添加工业染料; 蜂蜜常见的掺假方式有蜂蜜产地、植物源、添加糖浆。对液相色谱-质谱鉴别食品真伪的前处理方法(液液萃取、固相萃取)也进行了总结, 以期为液相色谱-质谱联用技术在食品真实性技术鉴别应用提供有益参考。     

α-淀粉酶在检验真假蜂蜜中的应用

针对蜂蜜掺假和造假的问题,对真蜂蜜及耐高温α-淀粉酶中的蛋白质含量、淀粉酶活性进行测定分析.实验结果表明:天然蜂蜜在低温条件下可长期保持其酶值基本不变,但是在高温条件下,随着储存时间延长,其酶值就会明显下降.而耐高温α-淀粉酶酶值均没有发生明显变化.通过蜂蜜样品中的α-淀粉酶与耐高温α-淀粉酶酶学性质的比较为判别真蜂蜜与掺假蜂蜜提供依据.     

基于HPLC-ELSD和偏最小二乘判别分析法的蜂蜜掺假鉴别

为了实现蜂蜜掺假的简便、快速识别,应用高效液相色谱技术和化学计量学手段建立了一种蜂蜜掺假检测的新方法。该研究收集了中国不同品种、不同地域的典型天然蜂蜜样品,根据目前市场上常见的蜂蜜掺假手段、掺假物质及相对含量情况模拟制备系列掺假蜂蜜样品,利用HPLC-ELSD对样品中糖类物质进行分离测定,并采用PLS-DA统计学方法进行蜂蜜掺假识别研究。研究结果表明:掺入质量分数10%以上果葡糖浆和麦芽糖浆的掺假蜂蜜样品均能利用本方法予以鉴别,其校正集的正确判别率达到92.5%,验证集的正确判别率为100%。     

蜂蜜品种识别和掺假鉴别的研究进展

蜂蜜作为一种天然甜味剂,不仅营养价值高,而且还具备医疗功效,从而受到消费者青睐。市场上蜂蜜质量问题频繁发生,如混淆植物源和地理源,向蜂蜜中掺杂糖浆等。蜂蜜来源识别和掺假鉴别是中国乃至世界蜂业亟需解决的问题。因此,主要介绍仪器分析法在蜂蜜掺假、品种识别、产地鉴别方面研究进展,并对所有方法进行客观评价分析。对蜂蜜掺假和溯源从联合多种技术(掺假:碳同位素检测技术与色谱技术、光谱技术联合;溯源:其他技术和DNA技术联用)、化学计量学引入、构建蜂蜜数据库3个方面提出建议和展望。     

蜂蜜中原蜜黄酮类化合物HPLC图谱比较分析

利用高效液相色谱比较分析不同蜂种、不同产地、加工与否以及不同蜜源蜂蜜中原蜜黄酮类化合物的种类及含量差异。结果表明,意大利蜜蜂油菜原蜜和中华蜜蜂油菜原蜜总峰数和峰形都比较相似,意大利蜜蜂油菜原蜜的总黄酮含量比中华蜜蜂油菜原蜜总黄酮含量高。不同产地的意大利蜜蜂油菜原蜜的图谱峰形整体相似,总黄酮含量和黄酮类化合物种类大致相同。加工后的商品蜜总黄酮含量减少,黄酮类化合物的种类也减少,商品蜜的高效液相色谱图显示其黄酮类化合物的出峰时间靠前,主要密集分布在水溶性的分离相中。3个不同蜜源蜂蜜原蜜黄酮类化合物高效液相色谱图的总峰数和峰形都有较大差异,油菜原蜜、洋槐原蜜及柑橘原蜜的总峰数分别为65、58、70个,柑橘原蜜的总黄酮含量最高,达161.62μg/100 g。单花蜂蜜原蜜黄酮类化合物的高效液相色谱图峰形具有一定的特异性,可以作为指纹图谱用于蜂蜜蜜源的鉴定。     

Floral Markers in Honey of Various Botanical and Geographic Origins: A Review

Abstract: In view of the expanding global market, authentication and characterization of botanical and geographic origins of honey has become a more important task than ever. Many studies have been performed with the aim of evaluating the possibilities to characterize honey samples of various origins by using specific chemical marker compounds. These have been identified and quantified for numerous honey samples. This article is aimed at summarizing the studies carried out during the last 2 decades. An attempt is made to find useful chemical markers for unifloral honey, based on the analysis of the compositional data of honey volatile compounds, phenolic acids, flavonoids, carbohydrates, amino acids, and some other constituents. This review demonstrates that currently it is rather difficult to find reliable chemical markers for the discrimination of honey collected from different floral sources because the chemical composition of honey also depends on several other factors, such as geographic origin, collection season, mode of storage, bee species, and even interactions between chemical compounds and enzymes in the honey. Therefore, some publications from the reviewed period have reported different floral markers for honey of the same floral origin. In addition, the results of chemical analyses of honey constituents may also depend on sample preparation and analysis techniques. Consequently, a more reliable characterization of honey requires the determination of more than a single class of compounds, preferably in combination with modern data management of the results, for example, principal component analysis or cluster analysis.     

单花蜂蜜多酚类物质的抗氧化活性

以5种中国单花原蜜,不同产地的42个样本通过Amberlite XAD-2吸附树脂得到的多酚提取物为原料,采用分光光度法,测定总酚酸和总黄酮含量、还原能力、抗氧化活性(清除DPPH自由基、O2－ ·能力),评估蜂蜜多酚类物质抗氧化活性及蜂蜜品种、颜色和地域差异对清除自由基的影响。结果表明：样本总黄酮含量为(9.41±0.18)～(92.76±0.13)mg/kg;总酚酸含量为(9.10±0.05)～(149.57±0.14)mg/100g;深色枣花蜜抗氧化能力最强,对DPPH自由基、O2－ ·清除作用分别为EC50＝(0.042±0.014)g/mL和EC50＝(0.038±0.009)g/mL。提示蜂蜜的多酚类物质影响抗氧化活性,酚酸、黄酮含量与抗氧化能力呈现正相关系;色深原蜜的酚酸、黄酮含量高于色浅原蜜,抗氧化能力也强于浅色原蜜。     

Honey Adulteration Detection Using Raman Spectroscopy

In this study, the Raman spectroscopy was used to detect honey adulterated with fructose (F), glucose (G), inverted sugar (IS), hydrolyzed inulin syrup (IN), and malt must (M). Thus, 56 samples of authentic honeys (acacia, sunflower, tilia, polyfloral, and honeydew) and 900 adulterated samples (with 5, 10, 20, 30, 40, and 50% fructose, glucose, inverted sugar, malt must, and hydrolyzed inulin syrup) were analyzed. The classification of honey authenticity has been made using the partial least square linear discriminant analysis (PLS-LDA), and a total accuracy of 96.54% (authentic honey vs. adulterated honey) was observed, while in the case of adulterated honey, a total accuracy of 90.00% was observed, respectively. The determination of the adulterant agent concentration has been made using partial least squares regression (PLSR) and principal component regression (PCR) methods. The proposed method can be considered easy and rapid for honey adulteration detection to provide continuous in-line information.     

C/C pattern of honey from Turkey and determination of adulteration in commercially available honey samples using EA-IRMS

Honey adulteration particularly by adding cheap sugars such as High Fructose Corn Syrup (HFCS) and cane sugar syrup into natural honey is widespread. This study reports (¹³C/¹²C, ‰) patterns of 31 authentic honey samples obtained from different sources and regions of Turkey as well as 43 commercial honey samples to determine the adulteration using mass spectrometer coupled to elemental analyzer (EA-IRMS). The analyses indicated that the ranges of (¹³C/¹²C, ‰) values of honey and protein fractions of Turkish honey are from −23.30 to −27.58‰ and −24.13 to −26.76‰, respectively. These values for commercial honey samples were determined to range from −11.28 to −25.54‰ and −19.35 to −25.61‰, respectively. The numbers of adulterated commercial honey samples were found to be 10, which corresponds to 23% of the total number of the samples. Diastase activity, HMF content, electrical conductivity and moisture content of honey samples were also determined. Method validation and uncertainty budget calculations were also reported.     

氢核磁共振结合正交偏最小二乘法对油菜蜜中果葡糖浆掺假的判别分析

利用氢核磁共振(1H nuclear magnetic resonance,1H NMR)谱图结合正交偏最小二乘(orthogonal partial least squares,OPLS)法对油菜蜂蜜和果葡糖浆掺假蜂蜜进行判别分析。采集了303个油菜蜜样品和180个按照不同比例配制的果葡糖浆掺假蜂蜜样品的1H NMR谱图,并对油菜蜜主要糖类成分和部分低含量化合物进行了信号归属。采用OPLS对训练集数据进行分析,建立蜂蜜果葡糖浆掺假判别模型。通过排列实验法对模型进行可靠性检验。结果显示,油菜蜜和果葡糖浆掺假蜂蜜样品在OPLS得分图中能明显区分。训练集和测试集样品的总体判别正确率分别为98.40%和98.24%。因此,1H NMR与OPLS相结合可以实现油菜蜜中果葡糖浆掺假的快速鉴别。该方法是基于对蜂蜜成分的整体分析,避免了仅仅分析个别成分指标的检验方法中存在的缺陷,为蜂蜜质量监控提供了一种新思路。     

蜂蜜用葡萄糖溶液掺假的近红外光谱检测

为实现蜂蜜用葡萄糖溶液掺假的快速检测,利用近红外光谱技术(NIRS)对真假蜂蜜样本进行了研究。121个真蜂蜜样本中取8个分别按5%、10%、15%、20%、25%、30%、35%、45%、55%和65%的质量比掺假,共得80个掺假样本。不同光谱预处理方法的模型结果表明最佳预处理方法为自归一化加一阶微分(真假判别)和中心化加一阶微分(掺假量分析)。利用CARS(Competitive adaptive reweighted sampling)法筛选变量,PLS-LDA模型对真假蜂蜜的判别准确率为100%,PLS模型对掺假量定量分析的交互验证均方差为3.137 7,预测均方差为2.980 0。结果表明NIRS能实现蜂蜜用葡萄糖掺假的检测。     

Immunological characterization of honey major protein and its application

Honey contains a small amount of proteins and we purified the major protein in honey produced by Apis cerana and by Apis mellifera, respectively. Each purified major protein was injected in rats and after repeated immunization; antibodies were obtained and verified with Western-blot. Although honey samples used in this study differ due to geographical variations, storage periods and botanical origins, each antibody was reacted specifically to its antigen with high affinity. These results showed that the major proteins in honey derived from A. cerana and from A. mellifera have different surface structures. This feature can be applied for discrimination of honey from different honeybee species and for detection of adulterated honey by ELISA with high sensitivity.     

Contribution of dynamic headspace GC–MS analysis of aroma compounds to authenticity testing of honey

The volatile profiles of 43 authentic honey samples of different botanical and geographical origins were obtained by means of gas chromatography–mass spectrometry. A qualitative analysis of the volatile compounds identified was performed in order to assess the marker compounds (if/when existing) for both botanical and geographical origin. The results seem to indicate the existence of certain marker compounds for the floral origins assessed (e.g. acacia, chestnut, eucalyptus, heather, lavender, lime, rape, rosemary and sunflower). Also such compounds for two geographical origins (e.g. Denmark and England) seem to exist and possible marker compounds could also be found for the honeys from The Netherlands, Spain and Portugal.