1,721,039 research outputs found
Effectiveness of two different at-line instruments for the assessment of cheese composition, major minerals and fatty acids content
No full textThe at-line performance of two different NIRS instruments to predict major and minor cheese nutritional traits was evaluated. For this purpose, 158 samples from dairy products were collected and analysed by reference methods. Spectra were acquired using a transmittance and a reflectance instrument. Predictive equations were developed on the whole dataset or dividing samples in groups. Samples clustering was performed using pairwise Mahalanobis distance and centroid linkage algorithm. Prediction models for protein, fat, saturated fatty acids and minerals showed good prediction performances (R2 > 0.80). Instrument configuration had a limited impact on prediction accuracy. Overall, clustering approach reduced prediction error but coefficient of determination also decreased. Prediction of minor compounds with models built from a large variety of cheeses could be useful for process control. Cluster approach is recommended for specific traits and cheese type, for the fine tuning of final product characteristics
Acute necrotizing encephalopathy: combined theraphy and favourable outcome in a new case
No full textBACKGROUND: Acute necrotizing encephalopathy (ANE) is a rare disease characterized by multiple, symmetrical brain lesions, affecting thalami, brainstem tegmentum, and cerebellar medulla; more inconstantly, other structures are involved, i.e., internal capsules, posterolateral putamen, and deep periventricular white matter.
FEATURES: The clinical picture consists of rapidly deteriorating acute monophasic encephalopathy preceded by prodromal febrile illness; the symptoms include hyperpyrexia, convulsions, recurrent vomiting, and coma within 24 h.
PROGNOSIS: The outcome is usually poor and approximately 70% of the patients die within a few days from the onset of fever. There is no specific therapy for ANE but, in some patients, the clinical status improved with steroid treatment
β-Casein variants differently affect bulk milk mineral content, protein composition, and technological traits
No full textDetailed milk protein composition has strong influence on milk quality. This study quantitatively investigated the effect of β-casein variants A1, A2 and B on composition, and technological traits of bulk milk. A total of 171 commercial herds located in northern and central Italy were visited, and 299 bulk milk samples were collected. Traditional milk quality traits, major minerals, milk coagulation properties were assessed. Detailed milk protein composition and β-casein genetic variants were determined by reversed-phase HPLC. Effects of β-casein variants were estimated by fitting a mixed model with variants concentration as a covariate. Results demonstrated that greater concentration of β-casein B is linked with greater protein, casein, and fat content. Likewise, greater concentration of variants A1 and B of β-casein had a significant positive effect on rennet coagulation time and curd firmness, and was linked to a greater amount of Ca and P content than was the A2 variant
Dissociating top-down and bottom-up temporal attention in Down syndrome: A neurocostructive perspective
Full text linkDevelopment of infrared prediction models for diffusible and micellar minerals in bovine milk
Full text linkMilk and dairy products are major sources of minerals in human diet. Minerals influence milk technological properties; in particular, micellar and diffusible minerals differentially influence rennet clotting time, curd firmness and curd formation rate. The aim of the present study was to investigate the ability of mid-infrared spectroscopy to predict the content of micellar and diffusible mineral fractions in bovine milk. Spectra of reference milk samples (n = 93) were collected using MilkoscanTM 7 (Foss Electric A/S, Hillerød, Denmark) and total, diffusible and micellar content of minerals were quantified using inductively coupled plasma optical emission spectrometry. Backward interval partial least squares algorithm was applied to exclude uninformative spectral regions and build prediction models for total, diffusible and micellar minerals content. Results showed that backward interval partial least squares analysis improved the predictive ability of the models for the studied traits compared with traditional partial least squares approach. Overall, the predictive ability of mid-infrared prediction models was moderate to low, with a ratio of performance to deviation in cross-validation that ranged from 1.15 for micellar K to 2.73 for total P
Effects of somatic cell score on milk yield and mid-infrared predicted composition and technological traits of Brown Swiss, Holstein Friesian, and Simmental cattle breeds
Full text linkHigh milk somatic cell count (SCC) influences milk production and quality; however, very little is known about the effect of low SCC on milk quality, especially in terms of mineral content and coagulation properties. Thus, the present study aimed to investigate the effects of somatic cell score (SCS), calculated as log2(SCC/100) + 3, on milk yield, composition (fat, crude protein, casein, lactose, milk urea nitrogen, protein fractions, and mineral contents), and coagulation properties of Brown Swiss, Holstein Friesian, and Simmental cows from multibreed herds. Milk composition and coagulation traits were predicted using mid-infrared spectroscopy. The data set comprised 95,591 observations of 6,940 cows in 313 multibreed herds, collected from January 2011 to December 2017. Observations were divided into 8 classes based on SCS. Statistical analysis was performed using a linear mixed model, which included breed, parity, stage of lactation, SCS class, and their interactions as fixed effects, and herd test day, cow, and residual as random effects. The probability that cows experienced SCS > 4.00 at 30 ± 5, 60 ± 5, or 90 ± 5 d after the observation test day was calculated for each SCS class, and odds ratios to the reference class (−1.00 4.00). Moreover, cows with SCS lower than −1.00 on a test day were about 7 times more likely to present high SCS within the following 90 ± 5 d than cows with SCS between −1.00 and 0.00. Breeds responded similarly to the increase of SCS, but the overall loss of fat and crude protein yields, and several minerals among Holstein Friesian were lower with increasing SCS. The best milk yield and quality were observed between SCS 0.00 and 1.00, but milk quality of Holstein Friesians started to decrease at lower SCS compared with milk quality of Brown Swiss and Simmental cows. Results suggest a breed-dependent optimum of SCS, and highlighted that very low SCS can be an indicator of udder health problems and, thus, may be used for early detection of mastitis
Mineral equilibrium in commercial curd and predictive ability of near-infrared spectroscopy
Full text linkCurd samples (n = 83) from 3 European dairy companies were analyzed for micellar and soluble mineral fractions content using inductively coupled plasma optical emission spectrometry as a gold standard method. The same curd samples were analyzed through 3 different near-infrared (NIR) instruments, and NIR spectra were merged with reference data. Prediction equations were developed using modified partial least squares analysis, and the accuracy of prediction was evaluated through leave-one-out cross validation. Overall, NIR spectroscopy was capable of predicting micellar and soluble mineral fractions in curd, but with differences among instruments. Fitting statistics showed that the visible NIR instrument in reflectance mode outperformed the NIR instrument in transmittance mode as well as the portable NIR instrument in reflectance mode. Prediction accuracies for most of the analyzed mineral fractions can be used for curd quality control in dairy companies and to aid in decision-making during the cheesemaking process
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