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- W3004037650 abstract "Abstract The aim of the present study was to investigate whether the primarily positive affective state of fattening pigs influences various behavioral and physiological parameters such as the pigs’ playing behavior, way of behaving in behavioral tests, body language signals, or diameter, and astroglia cell numbers of hippocampi, salivary immunoglobulin A (IgA) content, or salivary protein composition. Additionally, the suitability of the variables mentioned was examined to assess the pigs’ positive affective state in practice, which still constitutes a latent variable not itself measurable. For this, a dataset including behavioral and physiological data of 60 fattening pigs from 3 different farms with different housing systems was analyzed by the partial least squares structural equation modeling (PLS-SEM) method. A hierarchical component model (HCM) was used including the pigs’ positive affective state as a higher-order component (HOC) and the behavioral and physiological parameters as lower-order components (LOC). Playing behavior, body language signals, and behavioral tests were revealed, in this order, to be most influenced by the pigs’ positive affective state since these resulted in the corresponding path coefficients (PC) of PC = 0.83, PC = 0.79, and PC = 0.62, respectively. Additionally moderate and weak R2-values occurred for the endogenous latent variables playing behavior (R2 = 69.8%), body language signals (R2 = 62.7%), and behavioral tests (R2 = 39.5%). Furthermore, the indicator of the “locomotor play” showed the highest indicator reliability (IR) (IR = 0.85) to estimate the latent variable of pigs’ positive affective state. The results of the present study supplement the comprehension and assessment of the pigs’ positive affective state in general." @default.
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- W3004037650 date "2020-01-30" @default.
- W3004037650 modified "2023-10-13" @default.
- W3004037650 title "Investigation of influence of growing pigs’ positive affective state on behavioral and physiological parameters using structural equation modeling" @default.
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- W3004037650 doi "https://doi.org/10.1093/jas/skaa028" @default.
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