Mixed microorganism cultures are prevalent in the food industry. A variety of microbiological mixtures have been used in these unique fermenting processes to create distinctive flavor profiles and potential health benefits. Mixed cultures are typically not well characterized, which may be due to the lack of simple measurement tools. Image-based cytometry systems have been employed to automatically count bacteria or yeast cells. In this work, we aim to develop a novel image cytometry method to distinguish and enumerate mixed cultures of yeast and bacteria in beer products. Cellometer X2 from Nexcelom was used to count of Lactobacillus plantarum and Saccharomyces cerevisiae in mixed cultures using fluorescent dyes and size exclusion image analysis algorithm. Three experiments were performed for validation. (1) Yeast and bacteria monoculture titration, (2) mixed culture with various ratios, and (3) monitoring a Berliner Weisse mixed culture fermentation. All experiments were validated by comparing to manual counting of yeast and bacteria colony formation. They were highly comparable with ANOVA analysis showing p-value > 0.05. Overall, the novel image cytometry method was able to distinguish and count mixed cultures consistently and accurately, which may provide better characterization of mixed culture brewing applications and produce higher quality products.

中文翻译：

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一种基于图像的混合培养发酵中同时计数乳杆菌和酵母菌的新方法。

混合微生物培养物在食品工业中很普遍。在这些独特的发酵过程中使用了多种微生物混合物，以创造独特的风味特征和潜在的健康益处。混合文化通常没有很好的特征，这可能是由于缺乏简单的测量工具。基于图像的细胞计数系统已被用于自动计数细菌或酵母细胞。在这项工作中，我们旨在开发一种新颖的图像细胞计数方法来区分和计数啤酒产品中酵母和细菌的混合培养物。Nexcelom 的 Cellometer X2 用于使用荧光染料和尺寸排阻图像分析算法对混合培养物中的植物乳杆菌和酿酒酵母进行计数。进行了三个实验以进行验证。(1) 酵母和细菌单一培养滴定，(2) 不同比例的混合培养，以及 (3) 监测 Berliner Weisse 混合培养发酵。通过与酵母菌和细菌菌落形成的人工计数相比，所有实验均得到验证。它们与显示 p 值 > 0.05 的方差分析具有高度可比性。总的来说，新的图像细胞计数方法能够一致准确地区分和计数混合培养物，这可以更好地表征混合培养物酿造应用并生产更高质量的产品。