Investigation of influence of growing pigs' positive affective state on behavioral and physiological parameters using structural equation modeling

Emotional "Contagion" in Piglets after Sensory Avoidance of Rewarding and Punishing Treatment

In the pig farming industry, it is recommended to avoid groups when treating individuals to reduce adverse reactions in the group. However, can this eliminate the adverse effects effectively? Piglets were assigned to the Rewarding Group (RG), the Punishing Group (PG), and the Paired Control Group (PCG). There were six replicates in each group, with two paired piglets per replicate. One piglet of the RG and PG was randomly selected as the Treated pig (TP), treated with food rewards or electric shock, and the other as the Naive pig (NP). The NPs in the RG and PG were unaware of the treatment process, and piglets in the PCG were not treated. The behavior and heart rate changes of all piglets were recorded. Compared to the RG, the NPs in the PG showed longer proximity but less contact behavior, and the TPs in the PG showed more freezing behavior. The percentage change in heart rate of the NPs was synchronized with the TPs. This shows that after sensory avoidance, the untreated pigs could also feel the emotions of their peers and their emotional state was affected by their peers, and the negative emotions in the pigs lasted longer than the positive emotions. The avoidance process does not prevent the transfer of negative emotions to peers via emotional contagion from the stimulated pig.

Invited review: Recursive models in animal breeding: Interpretation, limitations, and extensions

Structural equation models allow causal effects between 2 or more variables to be considered and can postulate unidirectional (recursive models; RM) or bidirectional (simultaneous models) causality between variables. This review evaluated the properties of RM in animal breeding and how to interpret the genetic parameters and the corresponding estimated breeding values. In many cases, RM and mixed multitrait models (MTM) are statistically equivalent, although subject to the assumption of variance-covariance matrices and restrictions imposed for achieving model identification. Inference under RM requires imposing some restrictions on the (co)variance matrix or on the location parameters. The estimates of the variance components and the breeding values can be transformed from RM to MTM, although the biological interpretation differs. In the MTM, the breeding values predict the full influence of the additive genetic effects on the traits and should be used for breeding purposes. In contrast, the RM breeding values express the additive genetic effect while holding the causal traits constant. The differences between the additive genetic effect in RM and MTM can be used to identify the genomic regions that affect the additive genetic variation of traits directly or causally mediated for another trait or traits. Furthermore, we presented some extensions of the RM that are useful for modeling quantitative traits with alternative assumptions. The equivalence of RM and MTM can be used to infer causal effects on sequentially expressed traits by manipulating the residual (co)variance matrix under the MTM. Further, RM can be implemented to analyze causality between traits that might differ among subgroups or within the parametric space of the independent traits. In addition, RM can be expanded to create models that introduce some degree of regularization in the recursive structure that aims to estimate a large number of recursive parameters. Finally, RM can be used in some cases for operational reasons, although there is no causality between traits.

Evaluating the influence of environmental variables on the length-weight relationship and prediction modelling in flathead grey mullet, Mugil cephalus Linnaeus, 1758

Fish stocks that are grown under diverse environmental conditions have different biometric relationships and growth patterns. The biometric length-weight relationship (LWR) is an essential fishery assessment tool, as fish growth is continuous and depends on genetic and environmental factors. The present study attempts to understand the LWR of the flathead grey mullet, Mugil cephalus Linnaeus, 1758, from different locations. The study area encompassed its distribution in the wild across freshwater location (one), coastal habitats (eight locations), and estuaries (six locations) in India to determine the relationship between various environmental parameters. Specimens (n = 476) of M. cephalus were collected from commercial catches and the length and weight of individual specimens were recorded. Monthly data from the study locations were extracted for nine environmental variables from the datasets downloaded from the Physical Oceanography Distributed Active Archive Center (PO.DAAC) and the Copernicus Marine Environment Monitoring Service (CMEMS) over 16 years (2002 to 2017) on the Geographical Information System platform. The parameters of the LWR, intercept 'a' and slope or regression coefficient 'b', varied from 0.005321 to 0.22182 and 2.235 to 3.173, respectively. The condition factor ranged from 0.92 to 1.41. The partial least squares (PLS) score scatter plot matrix indicated differences in the environmental variables between the locations. PLS analysis of the regression coefficient and environment parameters revealed that certain environment variables viz., sea surface temperature, salinity, dissolved oxygen, nitrate, and phosphate, played a positive role. However, chlorophyll, pH, silicate, and iron played a negative role in influencing weight growth across various locations. The results revealed that the M. cephalus specimens from three locations, Mandapam, Karwar, and Ratnagiri, possessed significantly higher fitness to their environment than those from the other six locations. The PLS model can be used to predict weight growth under the various environmental conditions of different ecosystems. The three identified locations are useful sites for the mariculture of this species considering their growth performance, the environmental variables, and their interactions. The results of this study will improve the management and conservation of exploited stocks in regions affected by climate change. Our results will also aid in making environment clearance decisions for coastal development projects and will improve the efficiency of mariculture systems.

Effects of long-term exposure to music on behaviour, immunity and performance of piglets

Context Music induces physiological responses in animals, and as an enriched environment, it may have a positive effect on behaviour and productivity. Aims This study aimed to determine the effects of different kinds of music on immunity, stress response and performance of piglets. Methods In total, 144 hybrid piglets (Yorkshire × Durac × Minpig) at the age of 7 weeks were divided into three treatment groups: slow-tempo string music (65 beats per min), fast-tempo wind music (200 beats per min), and control (i.e. no music). Exposure to music lasted for 42 days, from 8 to 14 weeks of age. During the experimental period, behavioural activities were observed, and physiological parameters, immune responses and growth performance were measured. Key results Results showed that long-term music exposure increased (P < 0.01) playing and tail-wagging behaviours compared with the control group, but had no effect (P > 0.05) on walking, lying, exploring, fighting or feeding behaviours. No effect (P > 0.05) was found on the levels of growth hormone, salivary cortisol, serum cortisol, adrenocorticotrophic hormone, β-endorphin or dopamine, or on the performance of growing pigs. However, the specific music type slow-tempo string significantly (P < 0.05) increased interleukin-4. Conclusions Long-term exposure to music does not affect stress response or growth performance in piglets. However, it promotes positive mood as indicated by increased playing and tail-wagging activities, and induces positive immunomodulation through increased interleukin-4 levels in piglets. Implications Exposure to music may be used to promote positive mood, and hence enhance welfare, in piglets.