Exploratory inference of the ingestive behavior of pigs in the finishing phase in an air-conditioned environment.

The objective of this research is to apply exploratory analysis and modeling associated with abiotic factors, physiological and behavioral variables of swine in the semi-arid region. The experimental design used was completely randomized, in a 3 × 3 factorial scheme, randomly distributed in nine pens, with three animals. The behavior of the animals was recorded using images and analyzed within 10-min interval. The data analysis used was multivariate, using the clustering method (tree diagram) and principal component analysis (PCA), in order to establish the main predictors of swine ingestive behavior, using multiple linear regression models. The PCA showed satisfactory results, in which the lowest eigenvalue observed was 2.82 and the accumulated variance for the treatments ranged from 69.70 to 94% for the first two principal components. Through exploratory data analysis, it was possible to identify the relationship between biotic and abiotic factors with the ingestive behavior of pigs in the finishing phase. Based on the results of the multivariate analysis, the most promising predictor variables for estimating the regression models were determined. Adiabatic evaporative cooling associated with 18 h of light was the combination of factors with the best results, presenting models for eating and drinking behavior, i.e. a complete ingestive characterization.

Vaginal temperature modeling in Holstein cows and cluster analysis by the cophenetic correlation coefficient.

The objective was to establish a model for the prediction and characterization of vaginal temperature in Holstein cows, based on environmental predictors and thermal comfort indices, through cluster analysis, validation by the cophenetic correlation coefficient, and multiple regression analysis. The micrometeorological characterization of the site was carried out by recording the air temperature (Tair), the relative humidity (RH), the black globe temperature (BGT), the black globe temperature and humidity (BGHI), and dew point temperature (TDP). The recording of vaginal temperature (Tv) was performed in eight dairy cows using temperature sensors, equipped with data loggers, coupled with intravaginal devices. The data were analyzed using descriptive statistics and cluster analysis (CA) by using the hierarchical agglomerative method based on the value of the cophenetic correlation coefficient (CCC >0.70), in which representative physiological models were established, characterizing the Tv through multiple regression. In the afternoon the coefficient of variation (CV) was low for all variables, indicating homogeneity of the meteorological variables and efficiency of the ventilation system. The temperature and humidity index (THI) was mild only on the morning. There was a variation of 0.28 °C of Tv between shifts, sufficient to characterize the condition of comfort and stress of the animal, with values above 39 °C indicating animal stress. Tv showed strong correlation with BGT, Tair, TDP and RH, assuming that physiological variables, such as Tv, tend to have greater relationship with abiotic variables. Empirical models were established for estimating Tv based on the analyses performed in this study. Model 1 is recommended for TDP ranges of 14.00-21.00 °C and RH of 30-100%, while model 2 can be used for Tair situations up to 35 °C. The regression models for estimating Tv are promising for characterizing the thermal comfort of dairy cows housed in compost barn systems.

Bioclimatic Zoning for Sheep Farming through Geostatistical Modeling in the State of Pernambuco, Brazil.

The Intergovernmental Panel on Climate Change (IPCC) has pointed out the high vulnerability of developing countries to climate change, which is expected to impact food and income security. Sheep farming is one of the main animal productions among the families located in the most vulnerable regions of the semiarid region of Pernambuco state, a Brazilian territory known for its high temperatures, low relative humidity, and high net solar radiation. Therefore, the objective of this study was to identify different regions of Pernambuco that may be more suitable for different breeds of sheep, based on non-parametric statistics and kriging maps of the temperature and humidity index (THI). THI values were determined based on mean annual temperature and wind speed extracted from the TerraClimate remote sensing database. Pernambuco state presented THI values ranging from 66 to 79, with the hair breeds having a high potential for exploitation in almost all territories, including the main meat-producing breeds. The East Friesian breed, a high milk producer, would be well suited to the Agreste mesoregion, a territory that, like the Pajeú and Moxotó microregions, also proved favorable for the introduction of three wool breeds (Suffolk, Poll Dorset, and Texel) known as major meat producers. The kriging maps of the THI values successfully allowed the identification of strategic development regions of Pernambuco state with high potential for sheep breeding.