A cross-specific multiplicative binomial recursive model for the analysis of perinatal mortality in a diallel cross among three varieties of Iberian 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.

Determinants of Sick and Dead Pig Waste Recycling—A Case Study of Hebei, Shandong, and Henan Provinces in China

Simple Summary

Proper handling of dead and sick pig carcasses is a significant concern for farmers, the general public, academia, and government. By drawing on the existing literature, the study selects various determinants of sick and dead pig recycling and evaluates the impacts of rewards and punishment mechanisms on farmers’ commitment to proper handling of dead and sick pigs. We utilized face-to-face discussion accompanied by a structured questionnaire to grasp the opinion of the Chinese pig farmers. The article elucidates the moderating effects of reward and punishment mechanisms, which will be crucial for understanding the on-hand experience of the farmers towards dead and sick pig recycling.

Abstract

Improper handling of sick and dead pigs may seriously affect public health, socio-economic conditions, and eventually cause environmental pollution. However, effective promotion of sick and dead pig (SDP) waste recycling has become the prime focus of current rural governance. Therefore, the study explores the impact of commitment, rewards, and punishments to capture the recycling behavior of farmers’ sick and dead pig waste management. The study employs factor analysis, the probit model, and the moderating effect model to craft the findings. The study’s empirical setup comprises the survey data collected from the Hebei, Shandong, and Henan provinces, representing the major pig-producing provinces in China. The study found that the commitment, reward, and punishment mechanisms are essential factors affecting the farmers’ decision-making on recycling sick and dead pig waste. The marginal effect analysis found that the reward and punishment mechanism is more effective than the farmers’ commitment. The study confirmed that in the recycling treatment of sick and dead pig waste, the farmers’ commitment and the government’s reward and punishment policy are the main factors that influence farmers to manage sick and dead pig waste properly. Therefore, the government should highlight the importance of effective waste management, and training facilities should also be extended firmly. The government should impose strict rules and regulations to restrict the irresponsible dumping of farm waste. Monitoring mechanisms should be put in place promptly.