PREDICTION OF STILLBORN PIGLETS FROM MULTIPAROUS SOWS

<p><strong>Background:</strong> Assisting sows during parturition reduces the number of stillborn piglets caused by anoxia. However, in industrial settings with a large number of animals, the capacity for assistance is limited. The development of predictive models based on existing data can enable farms to anticipate stillbirths in sows. <strong>Objective: </strong>To develop a predictive model to identify factors affecting the presence of stillborn piglets (PSbP), estimate the probability of their occurrence, and establish a classification criterion accordingly. <strong>Methodology:</strong> Data from 2 415 farrowings in 822 sows (Landrace, Yorkshire, and their crossbreeds) were analyzed. Five variables relating to the current farrowing and five variables related to the preceding one were examined. Our study used cross-validation (groups = 5), modeling the response variable (PSbP, 1: presence, 0: absence). <strong>Results:</strong> The only factor shown to have a negative effect (p<0.01) on PSbP was litter weight at birth, while litter size at birth and parity (number of farrowings) were seen to have a positive effect (p<0.01). PSbP prevalence during training and testing were 0.297 and 0.296 respectively. The model's estimated probability levels were 0.311 during training and 0.303 during testing, indicating an accurate probability estimation. When categorizing using the optimal cutoff point of 0.395, the predictive efficiency as measured by the area under the Receiver Operating Characteristic (ROC) curve was 0.846 for training and 0.813 for testing. <strong>Implications:</strong> Implementing this model of information-management software could make it possible to provide swift, efficient technical assistance to sows in need, with a high level of predictive efficiency. <strong>Conclusions:</strong> The probabilistic model described here based on a Bayesian approach and adjusted based on a categorization criterion showed effective predictive efficiency in the prediction of stillborn piglets. </p>

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Journal
Tropical and Subtropical Agroecosystems
Published
2025-03-24
DOI
https://doi.org/10.56369/tsaes.5658
Primary Topic
Animal Behavior and Welfare Studies
Type
article
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article

PREDICTION OF STILLBORN PIGLETS FROM MULTIPAROUS SOWS

José R. Bárcena-Gama, Antonio José Rouco-Yáñez, Francisco Ernesto Martínez-Castañeda, Nathaniel A. Rogers-Montoya et al.
Tropical and Subtropical Agroecosystems
Animal Behavior and Welfare Studies
article

PREDICTION OF STILLBORN PIGLETS FROM MULTIPAROUS SOWS

José R. Bárcena-Gama, Antonio José Rouco-Yáñez, Francisco Ernesto Martínez-Castañeda, Nathaniel A. Rogers-Montoya, María Esther Ortega-Cerrilla, José G. Herrera‐Haro, María Angélica Ortiz-Heredia, Daniel Alonso Domínguez-Olvera
article en

Abstract

<p><strong>Background:</strong> Assisting sows during parturition reduces the number of stillborn piglets caused by anoxia. However, in industrial settings with a large number of animals, the capacity for assistance is limited. The development of predictive models based on existing data can enable farms to anticipate stillbirths in sows. <strong>Objective: </strong>To develop a predictive model to identify factors affecting the presence of stillborn piglets (PSbP), estimate the probability of their occurrence, and establish a classification criterion accordingly. <strong>Methodology:</strong> Data from 2 415 farrowings in 822 sows (Landrace, Yorkshire, and their crossbreeds) were analyzed. Five variables relating to the current farrowing and five variables related to the preceding one were examined. Our study used cross-validation (groups = 5), modeling the response variable (PSbP, 1: presence, 0: absence). <strong>Results:</strong> The only factor shown to have a negative effect (p<0.01) on PSbP was litter weight at birth, while litter size at birth and parity (number of farrowings) were seen to have a positive effect (p<0.01). PSbP prevalence during training and testing were 0.297 and 0.296 respectively. The model's estimated probability levels were 0.311 during training and 0.303 during testing, indicating an accurate probability estimation. When categorizing using the optimal cutoff point of 0.395, the predictive efficiency as measured by the area under the Receiver Operating Characteristic (ROC) curve was 0.846 for training and 0.813 for testing. <strong>Implications:</strong> Implementing this model of information-management software could make it possible to provide swift, efficient technical assistance to sows in need, with a high level of predictive efficiency. <strong>Conclusions:</strong> The probabilistic model described here based on a Bayesian approach and adjusted based on a categorization criterion showed effective predictive efficiency in the prediction of stillborn piglets. </p>

Tropical and Subtropical AgroecosystemsVol. 28(1)
Universidad Autónoma del Estado de México (MX), Colegio de Postgraduados (MX), Universidad de Murcia (ES), Universidad Nacional Autónoma de México (MX)
Openalex Percentile: Top 93%
Animal Behavior and Welfare Studies
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