Zhang Guozhi, Liu Yao, Luo Yaling, Zhang Cuiping, Li Shanshan, Zheng Huoqing, Jiang Xiasen, Hu Fuliang
College of Animal Sciences, Zhejiang University, Hangzhou 310058, China.
Engineering Technology Research Center of Anti-Aging Chinese Herbal Medicine of Anhui Province, Biology and Food Engineering School, Fuyang Normal University, Fuyang 236000, China.
Foods. 2024 Nov 23;13(23):3753. doi: 10.3390/foods13233753.
The chemical composition and quality of honey are influenced by its botanical, geographic, and entomological origins, as well as climatic conditions. In this study, the physicochemical characteristics, microbial communities, and hydrocarbon compounds of honey produced by , , , , and were elucidated. The physicochemical profile of the honey exhibited significant differences across species, including moisture content (18.27-23.66%), fructose (33.79-38.70%), maltose (1.10-1.93%), electrical conductivity (0.37-0.74 mS/cm), pH (3.36-3.72), diastase activity (4.50-29.97 diastase number), and color (37.90-102.47 mm). Microbial analysis revealed a significant abundance of lactic acid bacteria, particularly the genus in honey and the in honey, indicating significant probiotic potential. Chemometric methods, principal component analysis, hierarchical cluster analysis, and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to classify the honey samples based on the 12 beeswax-derived hydrocarbons. The OPLS-DA model demonstrated 100% accuracy in predicting the entomological origin of honey, indicating that specific hydrocarbons are reliable markers for honey classification.
蜂蜜的化学成分和质量受其植物来源、地理来源、昆虫学来源以及气候条件的影响。在本研究中，对由[具体蜜蜂种类1]、[具体蜜蜂种类2]、[具体蜜蜂种类3]、[具体蜜蜂种类4]和[具体蜜蜂种类5]所产蜂蜜的理化特性、微生物群落及碳氢化合物进行了阐释。不同种类蜂蜜的理化特征存在显著差异，包括水分含量（18.27 - 23.66%）、果糖（33.79 - 38.70%）、麦芽糖（1.10 - 1.93%）、电导率（0.37 - 0.74 mS/cm）、pH值（3.36 - 3.72）、淀粉酶活性（4.50 - 29.97麦芽糖酶值）以及色泽（37.90 - 102.47 mm）。微生物分析显示乳酸菌数量显著，尤其是[具体蜜蜂种类1]蜂蜜中的[具体乳酸菌属1]和[具体蜜蜂种类2]蜂蜜中的[具体乳酸菌属2]，表明具有显著的益生菌潜力。采用化学计量学方法、主成分分析、层次聚类分析和正交偏最小二乘法判别分析（OPLS - DA），基于12种源自蜂蜡的碳氢化合物对蜂蜜样本进行分类。OPLS - DA模型在预测蜂蜜的昆虫学来源方面准确率达100%，表明特定的碳氢化合物是蜂蜜分类的可靠标志物。
