Predictive models for heat stress assessment in Holstein dairy heifers using infrared thermography and machine learning.

Heat stress is a condition that impairs the animal's productive and reproductive performance, and can be monitored by physiological and environmental variables, including body surface temperature, through infrared thermography. The objective of this work is to develop computational models for classification of heat stress from respiratory rate variable in dairy cattle using infrared thermography. The database used for the construction of the models was obtained from 10 weaned heifers, housed in a climate chamber with temperature control, and submitted to thermal comfort and heat wave treatments.

Using Thermal Signature to Evaluate Heat Stress Levels in Laying Hens with a Machine-Learning-Based Classifier.

Infrared thermography has been investigated in recent studies to monitor body surface temperature and correlate it with animal welfare and performance factors. In this context, this study proposes the use of the thermal signature method as a feature extractor from the temperature matrix obtained from regions of the body surface of laying hens (face, eye, wattle, comb, leg, and foot) to enable the construction of a computational model for heat stress level classification. In an experiment conducted in climate-controlled chambers, 192 laying hens, 34 weeks old, from two different strains (Dekalb White and Dekalb Brown) were divided into groups and housed under conditions of heat stress (35 °C and 60% humidity) and thermal comfort (26 °C and 60% humidity).

Synthesis and evaluation of a chitosan nanomaterial as efficient sorbent for determination of fungicide residues in waters and wine by liquid chromatography high resolution mass spectrometry.

In the present study a novel, cost-effective, environmentally friendly, and efficient analytical method was developed to analyze fungicide residues in water and wine. The method relies on the application of a newly developed sorbent nanomaterial named Nano-Cs-NAT, synthesized by modifying chitosan, a naturally occurring, low-cost polysaccharide, through grafting with two acrylic monomers and a cross-linker. Nano-Cs-NAT was introduced as analytical sorbent for Dispersive Micro Solid Phase Extraction (D-μ-SPE) before Liquid Chromatography-Orbitrap High-Resolution Mass Spectrometry (LC-Orbitrap HRMS) analysis of twelve fungicides commonly used in viticulture (among the others, triazoles, strobilurines and -substituted imidazoles).

The oral-gut-circulatory axis: from homeostasis to colon cancer.

The human microbiota is widely recognized as providing crucial health benefits to its host, specifically by modulating immune homeostasis. Microbial imbalance, known as dysbiosis, is linked to several conditions in the body. The oral cavity and gut host the two largest microbial communities playing a major role in microbial-associated diseases.

Three environmental dimensions of beef cattle in tropical feedlot: Water, nutrients and land.

This study aims to evaluate water, land, and nutrient efficiencies in a tropical beef feedlot system by providing artificial shading and considering local conditions and feed cultivation. The study was conducted at the Experimental Feedlot of Embrapa Southeast Livestock in Brazil. Forty-eight Nellore bulls were divided into two groups, with one group having shade (GS) and the other without shade (GWS).