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

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

Multi-Angle Compound Imaging

This paper reports on a scanning technique, denoted multi-angle compound imaging (MACI), using spatial compounding. The MACI method also contains elements of frequency compounding, as the transmit frequency is lowered for the highest beam angles in order to reduce grating lobes. Compared to conventional B-mode imaging MACI offers better defined tissue boundaries and lower variance of the speckle pattern, resulting in an image with reduced random variations. Design and implementation of a compound imaging system is described, images of rubber tubes and porcine aorta are shown and effects on visualization are discussed. The speckle reduction is analyzed numerically and the results are found to be in excellent agreement with existing theory. An investigation of detectability of low-contrast lesions shows significant improvements compared to conventional imaging. Finally, possibilities for improving diagnosis of atherosclerotic diseases using MACI are discussed

Spoilage Potential of Contaminating Yeast Species <i>Kluyveromyces marxianus</i>, <i>Pichia kudriavzevii </i>and <i>Torulaspora delbrueckii</i> during Cold Storage of Skyr

This study investigated the spoilage potential of yeast strains Kluyveromyces marxianus (Km1, Km2 and Km3), Pichia kudriavzevii Pk1 and Torulaspora delbrueckii Td1 grown in skyr in cold storage. Yeast strains were isolated from skyr and identified by sequencing of the 26S rRNA gene. K. marxianus yeasts were grown in skyr to high numbers, generating large amounts of volatile organic compounds (VOC) associated with off-flavours, among them were alcohols (3-methyl-1-butanol, 2-methyl-1-propanol and 1-hexanol), esters (ethyl acetate and 3-methylbutyl acetate) and aldehydes (hexanal, methylbutanal and methylpropanal). Growth of P. kudriavzevii Pk1 led to moderate increases in several alcohols and esters (mostly, 3-methyl-1-butanol and ethyl acetate), whereas only minor shifts in VOCs were associated with T. delbrueckii Td2. The levels of the key aroma compounds, diacetyl and acetoin, were significantly decreased by all K. marxianus strains and P. kudriavzevii Pk1. In contrast to the other yeast species, K. marxianus was able to utilize lactose, producing ethanol and carbon dioxide. Based on the overall results, K. marxianus was characterised by the highest spoilage potential. The study revealed the differences between the yeast species in fermentative and spoilage activities, and clarified the role of yeast metabolites for off-flavour formation and quality defects in skyr during cold storage