蜂蜜是一种天然性糖度剂，含有丰富的营养，既可直接食用又可广泛应用于各种饮料和食品的加工，同时蜂蜜具有一定的药物功效，深受人们喜爱。国际知名品牌Mannuka蜂蜜更是得益于其优越的抗炎功效而热销世界各地。蜂蜜产值高，营养功效好，随着食品加工，消费需求的增加，蜂蜜掺假尤其是糖浆掺假问题成为了制约蜂蜜市场健康发展的重要原因之一，建立快速可靠的适合于大批蜂蜜样品中的糖浆检测技术是应对产业发展和挑战的重要手段。在过去三十年中，已建立了多种分析方法用于蜂蜜中糖浆掺假的鉴别。在1970年晚期基于波层色谱（TLC）技术建立的分析方法被最早应用于蜂蜜中掺假糖浆的识别，随后C-同位素技术得到了发展并被特征性应用于高果糖浆的识别和检测。得益于高效离子色谱、超高效液相色谱、红外光谱、核磁、拉曼光谱等高精准度仪器设备的发展，目前已建立了碳同位素比率法、糖浆标志物检测法、高果糖淀粉糖浆薄层法、大米糖浆特异成分检测、外来酶法、光谱结合化学计量学模型识别法等10种检测方法，用于蜂蜜中玉米糖浆、大米糖浆、甜菜糖浆和菊粉糖浆等的掺假识别和含量检测。此外，Q-TOF-MS在近蜂蜜源糖浆如大米糖浆的掺假识别中得到了大力应用和发展，因为其可以灵敏反应蜂蜜和掺假糖浆的代谢组学差异，建立不同的指示物。Q-TOF-MS的使用有益于建立不同蜂蜜和掺假成分指示物的数据库，而基于代谢组学的检测技术将使蜂蜜中多组掺假成分的快速检测成为可能。

蜂蜜掺假问题严重已导致蜂蜜销量的严重下降，蜂农收入降低，进而放弃养蜂，造成蜂群数量减少而影响生态平衡。因此，应高度重视蜂蜜掺假问题，尽快建立多种掺假糖浆的快速检测方法和指示物信息。

本论文对于目前蜂蜜中不同掺假糖浆的现状，检测方法和指示物均做了详细的总结，相信对我国蜂蜜糖浆掺假识别和检测技术发展应用提供一定的思考和理论支撑。

内容如下：

Liming Wua, b, c, Bing Dua, Yvan Vander Heydend, Lanzhen Chena, b, c, Liuwei Zhaoa, Miao Wanga, b, c, Xiaofeng Xuea, b, c, , 

a Institute of Apiculture Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China

b Risk Assessment Laboratory for Bee Products Quality and Safety of Ministry of Agriculture, Beijing 100093, China

c Bee Product Quality Supervision and Testing Center, Ministry of Agriculture, Beijing 100093, China

d Department of Analytical Chemistry and Pharmaceutical Technology, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel-VUB, Brussels, Belgium

 

Highlights

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SCIRA differentiates honey adulterated by C3 plant adulterants.

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GC and HPAEC is an affordable, easy technique to detect HFCS.

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HPLC can detect C3 and C4 starch syrups and rice syrups.

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IR-based analysis, NMR, and Raman spectroscopy speed up the detection of honey adulterants.

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Q-TOF-MS for metabolomics-based detection is able to detect different adulterants simultaneously.

Abstract

Honey is a natural sweetening agent widely used in food products and as a daily diet ingredient, but it also has medicinal properties. An increase in the demand for honey has resulted in adulteration by different sugar syrups. Authentication is therefore important for consumer confidence. This comprehensive overview covers known syrup adulterants and the analytical methodologies adopted for their detection in honey. For instance, TLC is the oldest method for honey analysis. C-isotope methods such as SCIRA, which can differentiate adulterated honey from C3 plants, are explained. Common analytical techniques such as HPAEC, GC, and HPLC are discussed. Advanced techniques, including IR, NMR, and Raman spectroscopy, which enhance the analysis process for larger numbers of samples, are also presented. Finally, Q-TOF-MS is addressed as a metabolomics-based detection method, since it has recently gained momentum following the increase in different adulterants that make detection more difficult.

 

Keywords

Honey; Adulteration; Authenticity; Chemometrics; Metabolomics

Abbreviations

AFGP, 2-acetylfuran-3-glucopyranoside; ANN, artificial neural networks; ATR, attenuated total reflectance; BPN, back propagation network; C3, Calvin and Benson cycle; C4, Hatch–Slack cycle; CAM, Crassulaceanacid metabolism; CVA, canonical variate analysis; DAD, diode array detection; DFAs, difructose anhydrides; DP, degree of polymerization; DPLS, discriminant partial least squares; ECD, electrochemical detection; FTIR, Fourier transform infrared spectroscopy; FTMR, Fourier transform midinfrared spectroscopy; F/G, fructose/glucose; G2, maltose; G3, maltotriose; G4, maltotetraose; G5, maltopentaose; G6, maltohexaose; G7, maltoheptaose; GC, gas chromatography; GC/MS, gas chromatography coupled to mass spectrometry; GPC, gel permeation chromatography; HFCS, high-fructose corn syrup; HFIS, high fructose inulin syrups; HMF, hydroxy methyl furfural; HPAEC, high-performance anion exchange chromatography; HPLC, high-performance liquid chromatography; HPTLC, high-performance thin-layer chromatography; IR, infrared spectroscopy; kNN, k-nearest neighbors; LDA, linear discriminant analysis; LS-SVM, least squares support vector machine; MIR, mid-infrared; NIR, near infrared; NMR, nuclear magnetic resonance; PAD, pulsed amperometric detector; PCA, principal component analysis; PCR, principal component regression; PLS, partial least squares; Q-TOF-MS, quadrupole time-of-flight mass spectrometry; RBFN, radial basis function network; RID, refractive index detector; SCIRA, stable carbon isotopic ratio analysis; SIMCA, soft independent modeling of class analogy; TLC, thin-layer chromatography