Analyzing the influence of external shocks on the pricing dynamics of the live pig industry chain is essential for effective macroeconomic control. Utilizing monthly data spanning from January 2010 to August 2023, this study employs the TVP-SV-VAR (Time-Varying Parameter—Stochastic Volatility—Vector Autoregression) model to analyze the effects of EPU (Economic Policy Uncertainty) and INU (Live Pig Industry News Uncertainty) on industry pricing. The findings are as follows: Firstly, the impacts of EPU and INU on industry prices exhibit time variability and distinct characteristics. Specifically, the impact magnitude of EPU ranges between [−0.025, 0.025], and that of INU between [−0.01, 0.01]. These differences in impact magnitude elicit varied responses from manufacturers and consumers to the indices. Secondly, uncertainty shocks at particular time points show high consistency, suggesting a patterned influence of external shocks on industry pricing that aligns with historical trends. Thirdly, robustness tests with alternative explanatory variables confirm the reliability of the findings. An uncertainty index, crafted from more comprehensive information sources, more accurately captures the effects of external shocks on industry pricing. Additionally, the volume of live pig slaughters illustrates the potential interaction between external shocks and pricing dynamics. In an era marked by increasingly frequent external shocks, this research offers valuable insights for policymakers to implement macro-control and foster high-quality industrial development.

Backgrounds: Objective of this study is to conduct a genome-wide association study (GWAS) of first-parity reproductive traits in Suzi pigs to identify significant single-nucleotide polymorphisms (SNPs) or candidate genes influencing these traits. Methods: This research employed technologies including the Zhongxin 50K SNP chip, simplified genome sequencing, resequencing, and the 100K SNP liquid chip to perform genome-wide SNP detection on 898 Suzi sows. Genotype data and phenotypic data were combined to do GWAS, gene annotation, and enrichment analysis. Results: Results showed that this study obtained phenotypes of 33 first-parity reproductive traits from 574 sows. GWAS results indicated there were 10 first-parity reproductive traits significantly associated with SNPs, and these traits were AFS, AFF, NNB, NH, NW, NS, NM, ND, PB, and CCN. These 10 traits were significantly associated with 60 SNPs, with 15 (25%) located on chromosome 2-the highest proportion. The SNPs significantly associated with AFS and AFF were largely identical. Genome-wide variance component analysis revealed that among the 10 traits with significantly associated SNPs in GWAS, there were 5 traits that exhibited genome-wide heritability ≥ 0.01. Trait of NM showed the highest heritability (0.65–0.7). These significantly associated SNPs annotated 20 candidate genes, including ADAMTS19, PROP1, ZNF354B, PCARE, LUZP2, VIRMA, EPHA5, AAAS, SLCO3A1-SV2B, KIF18A-BDNF, SERGEF, DYNLRB2, HNF4G, CATSPERD, HSD11B1L, DICER1, RARG, PCDHAC2, KRT79, and HSD17B2. GO analysis of candidate genes revealed that the top three biological processes were cell adhesion, positive regulation of cell projection organization, and positive regulation of neuron projection development. KEGG results showed the top three pathways were inositol phosphate metabolism, glutamatergic synapse, and phosphatidylinositol signaling system. Conclusions: These findings provide a foundation for the reproductive breeding of Suzi pigs and offer new insights into biological breeding in pigs.

Exploring the influence of external shocks on the pricing dynamics of the live pig industry chain is essential for effective macroeconomic control. Utilizing monthly data spanning from January 2010 to August 2023, this study employs a Time-Varying Parameter - Stochastic Volatility - Vector Autoregression (TVP-SV-VAR) model to analyze the effects of Economic Policy Uncertainty (EPU) and Live Pig Industry News Uncertainty (INU) on industry pricing. The findings are as follows: Firstly, the impacts of EPU and INU on industry prices exhibit time variability and distinct characteristics. Specifically, the impact strength of EPU ranges between [-0.025, 0.025], and that of INU between [-0.01, 0.01]. These differences in impact strength elicit varied responses from manufacturers and consumers to the indices. Secondly, uncertainty shocks at particular time points show high consistency, suggesting a patterned influence of external shocks on industry pricing that aligns with historical trends. Thirdly, robustness tests with alternative explanat ory variables confirm the reliability of the findings. An uncertainty index, crafted from more comprehensive information sources, more accurately captures the effects of external shocks on industry pricing. Additionally, the volume of live pig slaughters illustrates the potential interaction between external shocks and pricing dynamics. In an era marked by increasingly frequent external shocks, this research offers valuable insights for policymakers to implement macro-control and foster high-quality industrial development.