The Effect of Climate Variability on Main Components of Cow Milk in Iran

The main purpose of this study is to assess the relationship between six bioclimatic indices for cattle (temperature humidity (THI), environmental stress (ESI), equivalent temperature (ESI), heat load (HLI), modified heat load (HLInew) and respiratory rate predictor(RRP)) and fundamental milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when cows use natural pasture, with possibility for cows to choose to stay in the barn or to graze on the pasture in the pasturing system. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty estimation through resampling in the confidence intervals. To find the relationships between climate indices (THI, ETI, HLI, HLInew, ESI and RRP) and main components of cow milk (fat, protein and yield), multiple liner regression is applied. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Cross validation is used to avoid over-fitting. Based on results of investigation the effect of heat stress indices on milk compounds separately, we suggest the use of ESI and RRP in the summer and ESI in the spring. THI and HLInew are suggested for fat content and HLInew also is suggested for protein content in the spring season. The best linear models are found in spring between milk yield as predictands and THI, ESI,HLI, ETI and RRP as predictors with p-value < 0.001 and R2 0.50, 0.49. In summer, milk yield with independent variables of THI, ETI and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. It is strongly suggested that new and significant indices are needed to control critical heat stress conditions that consider more predictors of the effect of climate variability on animal products, such as sunshine duration, quality of pasture, the number of days of stress (NDS), the color of skin with attention to large black spots, and categorical predictors such as breed, welfare facility, and management system. This methodology is suggested for studies investigating the impacts of climate variability/change on food quality/security, animal science and agriculture using short term data considering uncertainty or data collection is expensive, difficult, or data with gaps.

The 'rotiferologist' effect and other global correlates of species richness in monogonont rotifers

Global biodiversity patterns are often driven by diff erent environmental variables at diff erent scales. However, it is still controversial whether there are general trends, whether similar processes are responsible for similar patterns, and/or whether confounding eff ects such as sampling bias can produce misleading results. Our aim is twofold: 1) assessing the global correlates of diversity in a group of microscopic animals little analysed so far, and 2) inferring the infl uence of sampling intensity on biodiversity analyses. As a case study, we choose rotifers, because of their high potential for dispersal across the globe. We assembled and analysed a new worldwide dataset of records of monogonont rotifers, a group of microscopic aquatic animals, from 1960 to 1992. Using spatially explicit models, we assessed whether the diversity patterns conformed to those commonly obtained for larger organisms, and whether they still held true after controlling for sampling intensity, variations in area, and spatial structure in the data. Our results are in part analogous to those commonly obtained for macroorganisms (habitat heterogeneity and precipitation emerge as the main global correlates), but show some divergence (potential absence of a latitudinal gradient and of a large-scale correlation with human population). Moreover, the eff ect of sampling eff ort is remarkable, accounting for 50% of the variability; this strong eff ect may mask other patterns such as latitudinal gradients. Our study points out that sampling bias should be carefully considered when drawing conclusions from large-scale analyses, and calls for further faunistic work on microorganisms in all regions of the world to better understand the generality of the processes driving global patterns in biodiversity.

Effect of residual vanadyl ions on the spectroscopic analysis of humic acids: a multivariate approach.

In a study of the vanadyl (VO2þ)-humic acids system, the residual vanadyl ion suppressed fluorescence and specific electron paramagnetic resonance (EPR) and NMR signals. In the case of NMR, the proton rotating frame relaxation times (T1qH) indicate that this suppression is due to an inefficient H-C cross polarization, which is a consequence of a shortening of T1qH. Principal components analysis (PCA) facilitated the isolation of the effect of the VO2þ ion and indicated that the organic free radical signal was due to at least two paramagnetic centres and that the VO2þ ion preferentially suppressed the species whose electronic density is delocalized over O atoms (greater g-factor). additionally, the newly obtained variables (principal components ? PC) indicated that, as the result of the more intense tillage a relative increase occurred in the accumulation of: (i) recalcitrant structures; (ii) lignin and long-chain alkyl structures; and (iii) organic free radicals with smaller g-factors.

MEXICO DISTRITOFEDERAL: ANALISIS ESPACIAL DE ALGUNAS VARIABLES DE POBLACION, 1980

Este trabajo presenta el tratamiento estadístico de algunas variables de censo de población; y en general y en forma general se las represento en mapas, cartógrafas  formas de correlación y de explicación, tanto a nivel social como de su representación espacial. El trabajo se elaboró con las 15 delegaciones del Distrito Federal y con un mapa a base o escala 1.200.000. El análisis de los resultados es estadístico en la medida que se parte en un censo que resulta evidentemente una información de la situación, en un momento específico de la vida del Distrito Ciudad Federal Mexicana.   Considerando variables con el volumen y densidad de población; las características socioeconómicas de la fuerza de trabajo, la situación de la vivienda y el analfabetismo.   Para luego considerar el análisis dinámico con otras fuentes de información secundarios y otros censos, presentando un análisis de l crecimiento de la población y su movilidad espacial.

Effect of heat stress on milk production of goats from Alpine and Saanen breeds in Brazil.

The purpose of this bibliography review was to approach the thermal comfort rates on milk production of goats from Alpine and Saanen breeds in Brazil. The caloric stress caused by weather changes to which the animals are submitted, influence on the mechanisms of normal physiological processes of the body. Thus, the effect on the lactation process in goats can be mentioned, where it decreases the amount of water in the body with the consequent decrease in synthesis and milk ejection interfering in the production of hormone prolactin and growth hormone. The animal?s interaction with the environment must be considered when the aim in livestock farming is welfare, because the different responses of the animal to the peculiarities of each region are crucial for the success of the animal adaptation. So, the correct identification of the factors that influence the productive life of the animal, such as the stress caused by the seasonal fluctuations of the environment, allow production systems management, making it possible to make them sustainable and viable. The maintenance of these parameters in normal levels is very important, to the point of being used in the evaluation of climate adaptability of breeds to a certain environmental condition. In this way, the concerns about animal welfare and environmental comfort are due to the climatic variables and the behavioral, physiological and productive responses are prevailing when implementing the suitability of certain production systems.

MODELO DE SIG PARA EL ANALISIS DE PROPENSION AL DENGUE A PARTIR DE VARIABLES CLIMATICAS, SOCIOCULTURALES Y EPIDEMIOLOGICAS EN LOS CINCO DISTRITOS DEL CANTON DE POCOCI PARA EL AÑO 2010

Resumen

Combined effects of soil biotic and abiotic factors, influenced by sewage sludge incorporation, on the incidence of corn stalk rot.

Abstract: The objectives of this study were to evaluate the combined effects of soil bioticand abiotic factors on the incidence of Fusarium corn stalk rot, during four annual incorporations of two typesofsewagesludge intosoil ina 5-years field assay under tropical conditions and topredict the effectsof these variables on the disease. For each type of sewage sludge, the following treatments were included: control with mineral fertilization recommended for corn; control without fertilization; sewage sludge based on the nitrogen concentration that provided the same amount of nitrogen as in the mineral fertilizer treatment; and sewage sludge that provided two, four and eight times the nitrogen concentration recommended for corn. Increasing dosages of both types of sewage sludge incorporated into soil resulted in increased corn stalk rot incidence, being negatively correlated with corn yield. A global analysis highlighted the effect of the year of the experiment, followed by the sewage sludge dosages. The type of sewage sludge did not affect the disease incidence. Amultiple logistic model using a stepwise procedure was fitted based on the selection of a model that included the three explanatory parameters for disease incidence: electrical conductivity, magnesium and Fusarium population. In the selected model, the probability of higher disease incidence increased with an increase of these three explanatory parameters. When the explanatory parameters were compared, electrical conductivity presented a dominant effect and was the main variable to predict the probability distribution curves of Fusarium corn stalk rot, after sewage sludge application into the soil.

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.