Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Sensitive and highly specific quantitative real-time PCR and ELISA for recording a potential transfer of novel DNA and Cry1Ab protein from feed into bovine milk

To address food safety concerns of the public regarding the potential transfer of recombinant DNA (cry1Ab) and protein (Cry1Ab) into the milk of cows fed genetically modified maize (MON810), a highly specific and sensitive quantitative real-time PCR (qPCR) and an ELISA were developed for monitoring suspicious presence of novel DNA and Cry1Ab protein in bovine milk. The developed assays were validated according to the assay validation criteria specified in the European Commission Decision 2002/657/EC. The detection limit and detection capability of the qPCR and ELISA were 100 copies of cry1Ab microL(-1) milk and 0.4 ng mL(-1) Cry1Ab, respectively. Recovery rates of 84.9% (DNA) and 97% (protein) and low (<15%) imprecision revealed the reliable and accurate estimations. A specific qPCR amplification and use of a specific antibody in ELISA ascertained the high specificity of the assays. Using these assays for 90 milk samples collected from cows fed either transgenic (n = 8) or non-transgenic (n = 7) rations for 6 months, neither cry1Ab nor Cry1Ab protein were detected in any analyzed sample at the assay detection limits.

Concomitant lipopolysaccharide-induced transfer of blood-derived components including immunoglobulins into milk

During a mammary immune response, the integrity of the blood-milk barrier is negatively affected and becomes leaky. The aim of the present study was to demonstrate the blood origin, and to investigate changes in the concentration, of various constituents including immunoglobulins in blood and milk during the early phase of lipopolysaccharide (LPS)-induced mastitis. Five lactating dairy cows received continuous β-hydroxybutyrate (BHBA) clamp infusions to maintain elevated BHBA blood concentrations (1.5 to 2.0 mmol/L) from 48 h before and 8h after LPS administration. One udder quarter was infused with 200 μg of Escherichia coli LPS. A second quarter served as control. Milk and blood samples were taken hourly for 8h postchallenge (PC). The somatic cell count in LPS-challenged quarters was increased from 4h PC to the end of the experiment compared with control quarters. In LPS-challenged quarters, l-lactate, BHBA, lactate dehydrogenase (LDH), IgG(1), and IgG(2) were increased at 3h PC and remained elevated until the end of experiment (8h PC) compared with control quarters. In addition, the optical density values in milk in a nonquantitative ELISA for antibodies directed against bluetongue virus (used as a measure of nonspecific antibody transfer; all animals were vaccinated) increased and, thus, indicates an increase in these antibodies in response to LPS treatment. l-Lactate concentration also increased in blood 2h PC and in the milk of control quarters during the experiment from 3h PC. A second experiment was conducted in vitro to investigate a possible contribution from destructed milk cells to l-lactate concentration and activity of LDH in milk. Aliquots of milk samples (n=8) were frozen (-20°C) or disrupted with ultrasound, respectively. Freeze thawing and ultrasound treatment increased LDH in milk samples, but had no effect on l-lactate concentrations. Results suggest that intramammary infusion of LPS induces a systemic response, as evidenced by an elevation of blood l-lactate concentration. The concomitant changes of all investigated components suggest that they were blood derived. However, the increase in blood components in the milk is not necessarily supportive of the mammary immune system, and likely a side effect of reduced blood-milk barrier integrity.

Embryo transfer as a tool to disseminate k-casein BB genotype and improve milk clotting properties

Dairy industries are asked to be increasingly competitive and efficient. Despite the increasing trend in milk yield and protein content during the last decade genetic selection, milk coagulation ability has diminished and even if the absolute amount of cheese produced has increased, the relative cheese yield from a set amount of milk, has decreased. As casein content and variants, along with milk clotting properties (MCP) are determined to a large extent at DNA level, genetic selection and embryo transfer can provide efficacious tools to reverse this trend and achieve improvements. The aim of the proposed research was to determine how rapidly and to what extent milk coagulation properties could be improved by using embryo transfer (ET) as a tool to increase the frequency of k-casein BB genotype cattle and reducing A and E variants in an Italian Holstein herd with a low prevalence of the favourable genotype. In the effort to optimize superovulation protocols and results, synchronization of wave emergence was performed through manual transrectal ablation of the largest (dominant) ovarian follicle on days 7 or 8 of the cycle (estrus = day 0); different drugs and dosage for the superstimulation protocol were experimented trying to overcome the negative effects of stress and the perturbance of LH secretion in superovulated highly producing lactating cows and the use of SexedULTRA™ sex-sorted semen, for artificial insemination of superovulated cows was reported for the first time. The selection program carried out in this research, gave evidence and gathered empirical data of feasible genetic improvements in cheesemaking ability of milk by means of k-casein BB selection. In conclusion, in this project, selection of k-casein BB genotype markedly enhanced cheese-making properties of milk, providing an impetus to include milk coagulation traits in genetic selection and breeding programs for dairy cattle.

Continental passive microwave-based rainfall estimation algorithm: Application to the Amazon Basin

This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations

The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

Nisin expression production from Lactococcus lactis in milk whey medium

BACKGROUND: Nisin is a commercially available bacteriocin produced by Lactococcus lactis ATCC 11454 and used as a natural agent in the biopreservation of food. In the current investigation, milk whey, a byproduct from dairy industries was used as a fermentation substrate for the production of nisin. Lactococcus lactis ATCC 11454 was developed in a rotary shaker (30 degrees C/36 h/100 rpm) using two different media with milk whey (i) without filtration, pH 6.8, adjusted with NaOH 2 mol L-1 and without pH adjustment, both autoclaved at 121 degrees C for 30 min, and (ii) filtrated (1.20 mu m and 0.22 mu m membrane filter). These cultures were transferred five times using 5 mL aliquots of broth culture for every new volume of the respective media. RESULTS: The results showed that culture media composed of milk whey without filtration supplied L. lactis its adaptation needs better than filtrated milk whey. Nisin titers, in milk whey without filtration (pH adjusted), was 11120.13 mg L-1 in the second transfer, and up to 1628-fold higher than the filtrated milk whey, 6.83 mg.L-1 obtained in the first(t) transfer. CONCLUSIONS: Biological processing of milk byproducts (milk whey) can be considered a profitable alternative, generating high-value bioproducts and contributing to decreasing river disposals by dairy industries. (C) 2008 Society of Chemical Industry.

Food energy content influences food portion size estimation by nutrition students

Background: Food portion size estimation involves a complex mental process that may influence food consumption evaluation. Knowing the variables that influence this process can improve the accuracy of dietary assessment. The present study aimed to evaluate the ability of nutrition students to estimate food portions in usual meals and relate food energy content with errors in food portion size estimation. Methods: Seventy-eight nutrition students, who had already studied food energy content, participated in this cross-sectional study on the estimation of food portions, organised into four meals. The participants estimated the quantity of each food, in grams or millilitres, with the food in view. Estimation errors were quantified, and their magnitude were evaluated. Estimated quantities (EQ) lower than 90% and higher than 110% of the weighed quantity (WQ) were considered to represent underestimation and overestimation, respectively. Correlation between food energy content and error on estimation was analysed by the Spearman correlation, and comparison between the mean EQ and WQ was accomplished by means of the Wilcoxon signed rank test (P < 0.05). Results: A low percentage of estimates (18.5%) were considered accurate (+/- 10% of the actual weight). The most frequently underestimated food items were cauliflower, lettuce, apple and papaya; the most often overestimated items were milk, margarine and sugar. A significant positive correlation between food energy density and estimation was found (r = 0.8166; P = 0.0002). Conclusions: The results obtained in the present study revealed a low percentage of acceptable estimations of food portion size by nutrition students, with trends toward overestimation of high-energy food items and underestimation of low-energy items.

Complementary filter design with three frequency bands: robot attitude estimation

This paper extents the by now classic sensor fusion complementary filter (CF) design, involving two sensors, to the case where three sensors that provide measurements in different bands are available. This paper shows that the use of classical CF techniques to tackle a generic three sensors fusion problem, based solely on their frequency domain characteristics, leads to a minimal realization, stable, sub-optimal solution, denoted as Complementary Filters3 (CF3). Then, a new approach for the estimation problem at hand is used, based on optimal linear Kalman filtering techniques. Moreover, the solution is shown to preserve the complementary property, i.e. the sum of the three transfer functions of the respective sensors add up to one, both in continuous and discrete time domains. This new class of filters are denoted as Complementary Kalman Filters3 (CKF3). The attitude estimation of a mobile robot is addressed, based on data from a rate gyroscope, a digital compass, and odometry. The experimental results obtained are reported.

Simulation of humidity fields in concrete: experimental validation and parameter estimation

The moisture content in concrete structures has an important influence in their behavior and performance. Several vali-dated numerical approaches adopt the governing equation for relative humidity fields proposed in Model Code 1990/2010. Nevertheless there is no integrative study which addresses the choice of parameters for the simulation of the humidity diffusion phenomenon, particularly in concern to the range of parameters forwarded by Model Code 1990/2010. A software based on a Finite Difference Method Algorithm (1D and axisymmetric cases) is used to perform sensitivity analyses on the main parameters in a normal strength concrete. Then, based on the conclusions of the sensi-tivity analyses, experimental results from nine different concrete compositions are analyzed. The software is used to identify the main material parameters that better fit the experimental data. In general, the model was able to satisfactory fit the experimental results and new correlations were proposed, particularly focusing on the boundary transfer coeffi-cient.

Estimation of electronic coupling in π -stacked donor-bridge-acceptor systems: correction of the two-state model

Comparison of donor-acceptor electronic couplings calculated within two-state and three-state models suggests that the two-state treatment can provide unreliable estimates of Vda because of neglecting the multistate effects. We show that in most cases accurate values of the electronic coupling in a π stack, where donor and acceptor are separated by a bridging unit, can be obtained as Ṽ da = (E2 - E1) μ12 Rda + (2 E3 - E1 - E2) 2 μ13 μ23 Rda2, where E1, E2, and E3 are adiabatic energies of the ground, charge-transfer, and bridge states, respectively, μij is the transition dipole moments between the states i and j, and Rda is the distance between the planes of donor and acceptor. In this expression based on the generalized Mulliken-Hush approach, the first term corresponds to the coupling derived within a two-state model, whereas the second term is the superexchange correction accounting for the bridge effect. The formula is extended to bridges consisting of several subunits. The influence of the donor-acceptor energy mismatch on the excess charge distribution, adiabatic dipole and transition moments, and electronic couplings is examined. A diagnostic is developed to determine whether the two-state approach can be applied. Based on numerical results, we showed that the superexchange correction considerably improves estimates of the donor-acceptor coupling derived within a two-state approach. In most cases when the two-state scheme fails, the formula gives reliable results which are in good agreement (within 5%) with the data of the three-state generalized Mulliken-Hush model

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Estimation des coûts engendrés par l'occupation inappropriée des lits de soins aigus du CHUV par des patients en attente de placement

[Table des matières] 1. Pourquoi s'intéresser à l'occupation inappropriée des lits de soins aigus au CHUV ?. - 1.1. Etat des lieux. - 1.1.1. Les chiffres du CHUV. - 1.1.2. La cellule de gestion des flux de patients. - 1.1.3. L'unité de patients en attente de placement. - 1.1.4. La pénurie de lits dans les EMS vaudois. - 1.1.5. Le vieillissement de la population vaudoise. - 1.2. Evidences nationales et internationales. - - 2. Estimation des coûts. - 2.1. Coûts chiffrables. - 2.1.1. Perte financière directe. - 2.1.2. Coûts des transferts pour engorgement. - 2.1.3. Coût d'opportunité. - 2.2. Coûts non chiffrables. - 2.2.1. Patients. - 2.2.2. Personnel médical. - 2.2.3. CHUV. - - 3. Propositions. - 3.1. Prises en charge alternatives. - 3.1.1. Les réseaux intégrés de services aux personnes âgées. - 3.1.2. Les courts séjours gériatriques. - 3.1.3. Autres solutions. - 3.2. Prévention. - 3.2.1. Prévention des chutes. - 3.2.2. La prévention par l'information aux personnes âgées. - 3.2.3. La prévention par l'information à l'ensemble de la population

Radiative Heat Transfer in Boiler Furnaces

Better models are needed for radiative heat transfer in boiler furnaces. If the process is known better, combustion in the furnace can be optimized to produce low emissions. It makes the process to be environmental friendly. Furthermore, if there is a better model of the furnace it can more fully explain what is happening inside the furnace. Using of the model one can quickly and easily analyze how it operates with bio fuels, moist fuels or difficult fuels and improve the operation. Models helps with better estimation of furnace dimensions and result in more accurate understanding of operation. Key component lacking in these models is radiative heat transfer in particle laden gases. If there are no particles than radiative heat transfer can be calculated approximately. There are two problems with current models when used with flow modeling. The first one is a need to account for a particle laden gas and the second one is an absence of a fast algorithm. Fast calculation is needed if radiative heat transfer calculation is done for a large CDF model. Computations slow down if time is required for calculating radiative properties over and over again. This thesis presents a band model for radiative heat transfer in boiler furnaces. Advantage is a quickness of calculation and account of particles in the process.