Occurrence and Identification of Yeasts in Production of White-Brined Cheese

Abstract

The aim of this study was to reveal the sites of yeast contamination in dairy production and perform taxonomic characterization of potential yeast spoilers in cheese making. Occurrence of spoilage yeasts was followed throughout the manufacture of white-brined cheese at a Danish dairy, including the areas of milk pasteurization, curd processing, and packaging (26 sites in total). Spoilage yeasts were isolated from whey, old cheese curd, and air samples in viable counts of 1.48-6.27 log CFU/mL, 5.44 log CFU/g, and 1.02 log CFU/m³, respectively. Yeast isolates were genotypically classified using (GTG)₅-PCR fingerprinting and identified by sequencing of the D1/D2 region of the 26S rRNA gene. The largest yeast heterogeneity was found in old curd collected under the turning machine of molds, where 11 different yeast species were identified. The most frequently isolated yeast species were Candida intermedia, Kluyveromyces marxianus, and Pichia kudriavzevii. The less abundant yeast species included Candida auris, Candida parapsilosis, Candida pseudoglaebosa, Candida sojae, Cutaneotrichosporon curvatus, Cutaneotrichosporon moniliiforme, Papiliotrema flavescens, Rhodotorula mucilaginosa, Vanrija humicola, and Wickerhamiella sorbophila. The awareness on occurrence and taxonomy of spoilage yeasts in cheese production will contribute to a knowledge-based control of contaminating yeasts and quality management of cheese at the dairies.

Keywords: dairy production; spoilage yeasts; white-brined cheese; yeast taxonomy.

Figure 1

Schematic illustration of the white-brined cheese-production line, including (A) cheese vats, (B) mechanical tunnel, (C) draining room, (D,E) packaging areas. The sampling sites are denoted in boxes and described in Table 1 and Table 2.

Figure 2

Dendrogram of (GTG)₅-PCR fingerprints of yeast isolates collected from the production line of white-brined cheese. Clustering was based on Dice’s coefficient of similarity with the unweighted pair-group method with arithmetic average clustering algorithm (UPGMA). Numbers of nodes in the dendrogram denote the percentage of similarity between the clusters.