Study of phenolic characterization of walnut wood extracts for potential use in oenology

Mestrado em Engenharia de Viticultura e Enologia (Double degree) / Instituto Superior de Agronomia. Universidade de Lisboa / Faculdade de Ciências. Universidade do PortoThe goal of this study is to identify the quantities of phenolic compounds that can be extracted from walnut wood extracts (Juglans regia), comparing them with those of oak wood extracts (Quercus petarea). These chips of the two different types of wood come in three different levels of toasting, light, medium and strong. The extracts were macerated in a known alcoholic solution for two different maceration times, respectively 15 and 30 days. All samples were replicated once to make this study statistically acceptable. After the two different maceration times, the samples were analyzed for 3 different compounds, total phenols, flavonoid phenols and non-flavonoid phenols, and for the color intensity of the solution. The results were statistically analyzed with two different methods, the first analyzes each sample by comparing it with the others at both maceration times, the second analyzes the samples for factors (type of wood, toasting and maceration time), studying their influence of individuals or interaction in pairs or all three. Walnut wood behaved differently from oak wood, having less influence on the content of phenolic compounds in the alcoholic solution, but resulted in a higher coloring intensity than oak. Toasting and maceration times also influence the content of phenolic compounds regardless of the type of woodN/

Comparison of parametric, orthogonal, and spline functions to model individual lactation curves for milk yield in Canadian Holsteins

Test day records for milk yield of 57,390 first lactation Canadian Holsteins were analyzed with a linear model that included the fixed effects of herd-test date and days in milk (DIM) interval nested within age and calving season. Residuals from this model were analyzed as a new variable and fitted with a five parameter model, fourth-order Legendre polynomials, with linear, quadratic and cubic spline models with three knots. The fit of the models was rather poor, with about 30%-40% of the curves showing an adjusted R-square lower than 0.20 across all models. Results underline a great difficulty in modelling individual deviations around the mean curve for milk yield. However, the Ali and Schaeffer (5 parameter) model and the fourth-order Legendre polynomials were able to detect two basic shapes of individual deviations among the mean curve. Quadratic and, especially, cubic spline functions had better fitting performances but a poor predictive ability due to their great flexibility that results in an abrupt change of the estimated curve when data are missing. Parametric and orthogonal polynomials seem to be robust and affordable under this standpoint

Method to establish average relationships among Holstein bull populations over time

Average relationship coefficients between groups of animals were calculated by repeating three calculation steps until convergence was reached. The first step was a stratified sampling of pedigrees. Second, relationships between animals in the sample were calculated, using the group relationships computed in a previous round for unknown parent relationships. Third, results were accumulated by group. Average relationship coefficients calculated in this way can be used for such purposes as to better understand the structure of a population, to more accurately calculate inbreeding coefficients, and to assign unknown parent groups using clustering methods. This method was applied to the pedigree data for the worldwide Holstein sire population. The data was derived from Interbull and North American pedigree databases. Groups were defined by year of birth, sex, and country. Average relationships between US and Canadian bulls increased across time from 0.02 in 1960 to 0.12 in 1999. The increase was continuous except for a plateau in 1992, followed by a slight decrease until 1995 when the trend to increase resumed. Average relationships across time comparing Canadian with European bulls and US with European bulls are quite similar. They increased from about 0 in 1963 to 0.10 in 1999. After a peak of 0.05 in 1966, the relationships dropped to 0.03 in 1976 before starting to increase again. For bulls born in 1996 in the US, Canada, and Germany (representing a typical European country), the average relationships were: 0.116 (CanadaCanada), 0.112 (Canada-USA), 0.1 (Canada-Germany), 0.101 (USA-USA), 0.101 (USAGermany) and 0.084 (Germany-Germany). These results demonstrate the recent dramatic increase in relationships and inbreeding in the worldwide Holstein population, and show the power of this method of calculating relationship coefficients

Effects of the timolol-dorzolamide fixed combination and latanoprost on circadian diastolic ocular perfusion pressure in glaucoma.

PURPOSE. To evaluate the effect of the timolol-dorzolamide fixed combination (TDFC) and latanoprost 0.005% on 24-hour intraocular pressure (IOP), systolic (SBP) and diastolic (DBP) blood pressure, and diastolic ocular perfusion pressure (DOPP) in patients with primary open-angle glaucoma (POAG). METHODS. This was an institutional, randomized clinical trial. After a 24-hour assessment without treatment, 27 previously untreated patients with POAG were randomized to 6 weeks’ treatment with twice-daily TDFC (8 AM and 8 PM) followed by once-daily latanoprost 0.005% (8 PM), or vice versa. One eye was analyzed per patient. The mean values of IOP, DBP, SBP, and DOPP (difference between DBP and IOP) were recorded at each time point, and the 24-hour data are the mean values of each patient’s measurements over the 24-hour period. The differences between the values of the first treatment period and the baseline and the second treatment period and washout were calculated and analyzed by means of an analysis of variance model that tested the effects of sequence and treatment. RESULTS. Both treatments significantly reduced 24-hour IOP (P <0.0001), but TDFC led to lower 24-hour pressure (mean ±SD: 15.4 ±1.9 vs. 16.7± 1.7 mm Hg; P=0.004). Latanoprost did not lead to any significant reduction in mean 24-hour SBP and DBP (SBP: P =0.952; DBP: P=0.831), but TDFC did (SBP and DBP: P < 0.0001). Both treatments significantly increased 24-hour DOPP (P < 0.0001), with no difference between the two medications (P=0.09). CONCLUSIONS. In previously untreated patients with POAG, TDFC, and latanoprost equally enhanced 24-hour DOPP: the former by counteracting the decrease in DBP with a substantial reduction in IOP and the latter by not affecting DBP and significantly reducing IO

Non-additive genetic effects for fertility traits in Canadian Holstein cattle (Open Access publication )

The effects of additive, dominance, additive by dominance, additive by additive and dominance by dominance genetic effects on age at first service, non-return rates and interval from calving to first service were estimated. Practical considerations of computing additive and dominance relationships using the genomic relationship matrix are discussed. The final strategy utilized several groups of 1000 animals (heifers or cows) in which all animals had a non-zero dominance relationship with at least one other animal in the group. Direct inversion of relationship matrices was possible within the 1000 animal subsets. Estimates of variances were obtained using Bayesian methodology via Gibbs sampling. Estimated non-additive genetic variances were generally as large as or larger than the additive genetic variance in most cases, except for non-return rates and interval from calving to first service for cows. Non-additive genetic effects appear to be of sizeable magnitude for fertility traits and should be included in models intended for estimating additive genetic merit. However, computing additive and dominance relationships for all possible pairs of individuals is very time consuming in populations of more than 200 000 animals

Fit of different functions to the individual deviations in random regression test day models for milk yield in dairy cattle

The shape of individual deviations of milk yield for dairy cattle from the fixed part of a random regression test day model (RRTDM) was investigated. Data were 53,217 TD records for milk yield of 6,229 first lactation Canadian Holsteins in Ontario. Data were fitted with a model that included the fixed effects of herd-testdate, DIM interval nested within age and season of calving. Residuals of the model were then fitted with the following functions: Ali and Schaeffer 5 parameter model, fourth-order Legendre Polynomials, and cubic spline with three, four or five knots. Result confirm the great variability of shape that can be found when individual lactation are modeled. Cubic splines gave better fitting pe4rformances although together with a marked tendency to yield aberrant estimates at the edge of the lactation trajectory

Usefulness of mid-infrared spectroscopy as a tool to estimate body condition score change from milk samples in intensively-fed dairy cows.

Directly measuring individual cow energy balance is not trivial. Other traits, like body condition score (BCS) and BCS change (ΔBCS) can, however, be used as an indicator of cow energy status. Body condition score is a metric used world-wide to estimate cow body reserves and the estimation of ΔBCS was, until now, conditional on the availability of multiple BCS assessments. The aim of the present study was to estimate ΔBCS from milk mid-infrared (MIR) spectra and days in milk (DIM) in intensively-fed dairy cows using statistical prediction methods. Daily BCS was interpolated from cubic splines fitted through the BCS records and daily ΔBCS was calculated from these splines. Body condition score change records were merged with milk MIR spectra recorded on the same week. The data set comprised 37,077 ΔBCS phenotypes across 9,403 lactations from 6,988 cows in 151 herds based in Quebec (Canada). Partial least squares regression (PLSR) and a neural network (NN) were then used to estimate ΔBCS from 1) MIR spectra only, 2) DIM only, or 3) MIR spectra and DIM together. ΔBCS data in both the first 120 DIM and 305 DIM of lactation were used to develop the estimates. Daily ΔBCS had a standard deviation of 4.40*10-3 BCS units in the 120-d data set and of 3.63*10-3 BCS units in the 305-d data set. 4-fold cross-validation was used to calibrate and test the prediction equations. External validation was also conducted using more recent years of data. Irrespective of whether based on the first 120 or 305 DIM, or when MIR spectra only, DIM only or MIR spectra and DIM were jointly used as prediction variables, NN produced the lowest root mean square error (RMSE) of cross-validation (1.81*10-3 BCS units and 1.51*10-3 BCS units, respectively, using the 120-d and 305-d data set). Relative to predictions for the entire 305 DIM, the RMSE of cross-validation was 15.4% and 1.5% lower in the first 120 DIM when using PLSR and NN, respectively. Predictions from DIM only were more accurate than those using just MIR spectra data but, irrespective of the data set and of the prediction model used, the combining DIM information with MIR spectral data as prediction variables reduced the RMSE compared with inclusion of DIM alone, albeit the benefit was small (the RMSE from cross-validation was reduced up to 5.5% when DIM and spectral data were jointly used as model features instead of DIM only). However, when predicting extreme ΔBCS records, the MIR spectral data was more informative than DIM. Model performance when predicting ΔBCS records in future years was similar to that from cross-validation demonstrating the ability of MIR spectra of milk and DIM combined to estimate ΔBCS, particularly in early lactation. This can be used to routinely generate estimates of ΔBCS to aid in day-to-day individual cow management