Lindahl Winther (vasefind3)

In Southern Italy, buffalo (Bubalus bubalis) milk is mostly intended for the manufacture of Mozzarella di Bufala Campana Protected Denomination of Origin (PDO) cheese. Despite the economic boost of the last 2 decades, the buffalo farming system should be improved to maximize the efficiency of the dairy industry, improve yield and quality of milk and cheese, and work toward better animal welfare. Milk somatic cell count (SCC) is used worldwide as an indicator of udder health in individual milk and is useful for monitoring farm hygiene in bulk milk. check details Mastitis data are currently not available on a large scale in Italy; thus, SCC is essential for identifying animals with suspected udder infection and inflammation. Moreover, high milk SCC is associated with altered composition and acidity, and poor technological properties of milk. However, payment systems of the PDO area are based simply on the delivered volume of milk rather than on quality characteristics. Hence, currently there are no penalties for elevated SCCels in the Italian buffalo population. In lactating dairy cattle, the corpus luteum (CL) is a dynamic endocrine tissue vital for pregnancy maintenance, fertility, and cyclicity. Understanding processes underlying luteal physiology is therefore necessary to increase reproductive efficiency in cattle. A common technique for investigating luteal physiology is reverse-transcription quantitative PCR (RT-qPCR), a valuable tool for quantifying gene expression. However, reference-gene-based RT-qPCR quantification methods require utilization of stably expressed genes to accurately assess mRNA expression. Historically, selection of reference genes in cattle has relied on subjective selection of a small pool of reference genes, many of which may have significant expression variation among different tissues or physiologic states. This is particularly concerning in dynamic tissues such as the CL, with its capacity for rapid physiologic changes during luteolysis, and likely in the less characterized period of CL maintenance during pregnancy. Thus, there is a clals alone were analyzed, CST3, HIF1A, and CD63 were also identified as more stable than ACTB and GAPDH. Identification of these new reference genes will aid in accurate normalization of RT-qPCR results, contributing to proper interpretation of gene expression relevant to luteal physiology. Furthermore, our analysis sheds light on the effects of luteolysis and pregnancy on the stability of gene expression in the bovine CL. This study explores the relationships between composition, hygienic quality, and color values of milk to evaluate whether colorimetry could be used as a valid predictor of the quality of raw milk and its coagulation. For this purpose, we performed analyses in 1,200 individual samples of Manchega sheep milk from 4 flocks from the region of Castilla-La Mancha, Spain. Based on the measured variables, we determined the differences and similarities between coagulating and noncoagulating samples using discriminant analysis techniques. The variables with a higher discriminant ability were lactose content, somatic cell score, pH, and the color values lightness (L*) and red/green value (a*). The model based on color values showed a predictive ability similar to that found in the model based on milk composition and hygienic quality. Canonical correlation analysis allowed us to explore the relationships between both sets of variables. Canonical correlations for the first and second pair of canonical values were 0.794 and 0.438, respectively. Both values were significant and represented 92.82% of the observed variability. The correlation structure showed that color values had a strong correlation with fat and protein content and with total solids, and they had a weak correlation with lactose content and somatic cell score. The 2 first combinations of standardized canonical variability could be considered a predictable measure of the composition and, to a le