Mohammadamin Kashiha

Different stressors elicit different responses in the salivary biomarkers cortisol, haptoglobin, and chromogranin A in pigs

Most commonly, salivary cortisol is used in pig stress assessment, alternative salivary biomarkers are scarcely studied. Here, salivary cortisol and two alternative salivary biomarkers, haptoglobin and chromogranin A were measured in a pig stress study. Treatment pigs (n = 24) were exposed to mixing and feed deprivation, in two trials, and compared to untreated controls (n = 24). Haptoglobin differed for feed deprivation vs control. Other differences were only found within treatment. Treatment pigs had higher salivary cortisol concentrations on the mixing day (P < 0.05). Chromogranin A concentrations were increased on the day of refeeding (P < 0.05). Haptoglobin showed a similar pattern to chromogranin A. Overall correlations between the salivary biomarkers were positive. Cortisol and chromogranin A were moderately correlated (r = 0.49, P < 0.0001), correlations between other markers were weaker. The present results indicate that different types of stressors elicited different physiological stress responses in the pigs, and therefore including various salivary biomarkers in stress evaluation seems useful.

Discerning Pig Screams in Production Environments

Pig vocalisations convey information about their current state of health and welfare. Continuously monitoring these vocalisations can provide useful information for the farmer. For instance, pig screams can indicate stressful situations. When monitoring screams, other sounds can interfere with scream detection. Therefore, identifying screams from other sounds is essential. The objective of this study was to understand which sound features define a scream. Therefore, a method to detect screams based on sound features with physical meaning and explicit rules was developed. To achieve this, 7 hours of labelled data from 24 pigs was used. The developed detection method attained 72% sensitivity, 91% specificity and 83% precision. As a result, the detection method showed that screams contain the following features discerning them from other sounds: a formant structure, adequate power, high frequency content, sufficient variability and duration.

Automatic identification of marked pigs in a pen using image pattern recognition

Individual identification in pigs is a key point for management. Many behaviors such as resting, activity, feeding and drinking are better to be monitored individually. The purpose of this work was to investigate feasibility of an automated method to identify marked pigs in a pen in experimental conditions and for behavior-related research by using image processing. First, ellipse fitting algorithms were employed to localize pigs. Second, individual pigs could be identified by their respective paint pattern using pattern recognition techniques. In total, pigs could be identified with an average accuracy of 89.4%. It was also shown that behaviors such as resting can be monitored using the presented technique.