啤酒酿造过程中的有害微生物及有机质残留检测与控制是防止微生物污染、保障啤酒质量的主要控制因素。该文以腺嘌呤核苷三磷酸(adenosine triphosphate, ATP)生物发光法为基础,建立啤酒酿造过程中微生物污染风险的快速评估方法。采用便携式ATP荧光检测仪对表面人工污染的短乳杆菌、梯度稀释的短乳杆菌菌悬液和啤酒有机质残留进行检测,分别对相对荧光单位(relative luciferase unit, RLU)和表面细菌总数、细菌浓度和啤酒有机质残留进行相关性分析,并建立预测模型。结果显示,表面细菌总数、水质细菌浓度和啤酒有机质残留预测模型的相关系数均>0.9(P<0.05),其中啤酒有机质残留预测模型的相关系数最高(R2=0.994)。基于便携式ATP快速荧光检测系统建立的表面短乳杆菌总数、水质短乳杆菌浓度和啤酒有机质残留预测模型,可对啤酒酿造过程中卫生学检验提供有效的实时监控,也为ATP生物发光法在食品质量安全的应用提供了理论支撑。
The detection and control of beer spoilage and organic matter residues in beer brewing process is one of the main effective methods to prevent microbial contamination and ensure beer quality. This study aimed to establish a rapid assessment method of microbial contamination risk during beer brewing based on the adenosine triphosphate (ATP) bioluminescence method. A portable ATP fluorescence detector was used to detect the contamination of Lactobacillus brevis on the surface, in the gradient diluted L. brevis suspension and the residual organic matter in beer. The correlation analysis of the relative fluorescence unit (RLU) and the total number of L. brevis on the surface, bacterial concentration in water and beer organic matter residues was conducted, respectively. Three kinds of different prediction models were established. The correlation coefficients of these “matched” combinations including total surface bacteria, bacterial concentration in water and beer organic matter residual prediction model, were all greater than 0.9 (P<0.05). Among them, beer organic matter residual prediction model was highly relevant to RLU (R2=0.994). The prediction model of total L. brevis on the surface, concentration of L. brevis in water and residual organic matter in beer was established based on the portable ATP fast fluorescence detection system, which can provide effective real-time monitoring for the hygiene inspection in the beer brewing process, and also provides theoretical support for the application of luminescence method in food quality and safety.
[1] 侯英,吴雪琼,王兴华. ATP生物发光原理及应用研究[J].中国医药导报, 2010,7(12):12-13;18.
[2] MOYER J D, HENDERSON J F. Nucleoside triphosphate specificity of firefly luciferase[J].Analytical Biochemistry,1983,131(1): 187-189.
[3] VIVIANI V R, OEHLMEYER T L, AMOLDI F G C, et al. A new firefly luciferase with bimodal spectrum: Identification of structural determinants of spectral pH-sensitivity in firefly luciferases[J].Photochemistry and Photobiology,2007,81(4):843-848.
[4] SELAN L,BERLUTTI F,PASSARIELLO C,et al. Reliability of a bioluminescence ATP assay for detection of bacteria[J].Journal of Clinical Microbiology,1992,30(7):1 739-1 742.
[5] 李春艳,霍贵成,王德国,等. ATP生物发光法快速测定生乳中微生物总数的研究[J].东北农业大学学报,2008,29(7):103-106.
[6] 李利霞,伍金娥,常超,等.优化的ATP生物发光法快速检测面粉中细菌总数[J].安徽农业科学,2011, 39(7):4 55-4 057.
[7] 胡雪莲,韩芳,侯玉柱,等. ATP生物发光法测定啤酒酿造过程中污染微生物变化规律的研究[J].啤酒科技,2012(5):24-26.
[8] 程金权,胡继贵.食品中菌落总数快速检测研究进展[J].食品与发酵科技,2014,50(6): 1-5.
[9] 田雨, 侯玉柱, 柯润辉,等.采用ATP生物发光法分析6株常见细菌ATP含量差异[J].食品与发酵工业,2015, 41(1):220-224.
[10] 侯玉柱,田雨,柯润辉,等. ATP生物发光法快速测定物体表面的菌落总数[J].食品与发酵工业,2015,41(2):217-220.
[11] LEE S J, PARK J S, IM H T, et al. A microfluidic ATP-bioluminescence sensor for the detection of airborne microbes[J].Sensors and Actuators B chemical, 2008, 132(2):443-448.
[12] 叶子豪.啤酒酿造过程中有害微生物污染因素及防治策略[J].现代农业科技,2011(9):370-371;376.
[13] NISHIKAWA S, SAKAI S, KARUBE I, et al. Dye-Coupled electrode system for the rapid determination of cell populations in polluted water[J].Applied and Environmental Microbiology, 1982, 43(4): 814-818.
[14] TENOVER F C. Rapid detection and identification of bacterial pathogens using novel molecular technologies: Infection control and beyond[J].Clinical Infectious Diseases, 2007, 44(1):418-423.
[15] VIALETTE M, PINON A, LEPORD B, et al. Meta-analysis of food safety information based on a combination of a relational database and a predictive modeling tool[J].Risk Analysis, 2010, 25(1):75-83.
