Ruggeri, Roberta
(2024)
Advanced diagnostics for physiological characterisation of intrauterine growth-restricted pigs, [Dissertation thesis], Alma Mater Studiorum Università di Bologna.
Dottorato di ricerca in
Scienze e tecnologie agrarie, ambientali e alimentari, 36 Ciclo.
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Abstract
Intrauterine growth restriction (IUGR) affects up to 30% of piglets, leading to increased mortality and stunted growth. The lack of an accurate diagnostic method makes IUGR a challenge, limiting treatment development. This Ph.D. aimed to establish a model for the diagnosis of IUGR in newborn piglets and to characterise the IUGR subpopulation from a physiological perspective. The IUGR foetus increases blood flow towards the brain to survive when oxygen and nutrient supply through the placenta is limited. This mechanism results in a higher brain-to-liver weight ratio (BrW/LW) at birth. In this thesis, the BrW/LW was measured one day after birth with computed tomography or by weighing the organs, and compared with diagnosis based on head shape and birth weight (BtW). Moreover, pictures of the piglets were recorded to capture specific morphometric traits. Our findings revealed that identifying IUGR based on head morphology or BtW does not always align with an increased BrW/LW. Morphometric traits proved reliable indicators, allowing estimation of brain, liver weight, and BrW/LW with 6%, 17%, and 17% error, respectively. A higher BrW/LW correlated with extended time to reach market weight, negatively affecting growth from birth to slaughter, gain-to-feed ratio, and protein efficiency during the grower-finisher period, but without impacting fat and muscle mass at any stage. The BrW/LW affected the Beta diversity of faecal microbiota until the beginning of the finisher period. Plasma metabolome was unaffected by BrW/LW during lactation, and only asparagine was significantly lower in IUGR compared to normal pigs at the end of the starter period. Our research confirmed IUGR’s lasting impact on several physiological traits. An accurate and standardized diagnostic method is needed to further characterise the affected pigs and enable consistent comparisons across studies. The use of predictive models based on image analysis represents a promising tool for early identification of IUGR.
Abstract
Intrauterine growth restriction (IUGR) affects up to 30% of piglets, leading to increased mortality and stunted growth. The lack of an accurate diagnostic method makes IUGR a challenge, limiting treatment development. This Ph.D. aimed to establish a model for the diagnosis of IUGR in newborn piglets and to characterise the IUGR subpopulation from a physiological perspective. The IUGR foetus increases blood flow towards the brain to survive when oxygen and nutrient supply through the placenta is limited. This mechanism results in a higher brain-to-liver weight ratio (BrW/LW) at birth. In this thesis, the BrW/LW was measured one day after birth with computed tomography or by weighing the organs, and compared with diagnosis based on head shape and birth weight (BtW). Moreover, pictures of the piglets were recorded to capture specific morphometric traits. Our findings revealed that identifying IUGR based on head morphology or BtW does not always align with an increased BrW/LW. Morphometric traits proved reliable indicators, allowing estimation of brain, liver weight, and BrW/LW with 6%, 17%, and 17% error, respectively. A higher BrW/LW correlated with extended time to reach market weight, negatively affecting growth from birth to slaughter, gain-to-feed ratio, and protein efficiency during the grower-finisher period, but without impacting fat and muscle mass at any stage. The BrW/LW affected the Beta diversity of faecal microbiota until the beginning of the finisher period. Plasma metabolome was unaffected by BrW/LW during lactation, and only asparagine was significantly lower in IUGR compared to normal pigs at the end of the starter period. Our research confirmed IUGR’s lasting impact on several physiological traits. An accurate and standardized diagnostic method is needed to further characterise the affected pigs and enable consistent comparisons across studies. The use of predictive models based on image analysis represents a promising tool for early identification of IUGR.
Tipologia del documento
Tesi di dottorato
Autore
Ruggeri, Roberta
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
36
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
beta diversity, birth weight, body composition, computed tomography, head shape, image analysis, non-invasive diagnosis, predictive models, regression equations
URN:NBN
Data di discussione
11 Luglio 2024
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Ruggeri, Roberta
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
36
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
beta diversity, birth weight, body composition, computed tomography, head shape, image analysis, non-invasive diagnosis, predictive models, regression equations
URN:NBN
Data di discussione
11 Luglio 2024
URI
Gestione del documento: