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Letting Data Speak: New Era in Sow Health and Reproductive Performance

5 minute read

For decades, claw health in sows has been viewed primarily as a welfare issue related to lameness in pigs. Important, yes, but often siloed from broader productivity metrics. Despite its clear link to sow lameness and early culling, claw health was rarely measured, tracked or quantified in a way that could inform herd-level decisions. Today, that narrative is changing. Thanks to advanced data analysis techniques and a commitment to letting the data tell the story, Zinpro now has undeniable proof that claw lesions are directly correlated with reproductive performance. 

This isn’t just a hypothesis, it’s a conclusion drawn from rigorous multivariate analysis, clustering algorithms and predictive modeling. And it’s reshaping how we think about sow productivity, profitability and longevity

From Observation to Insight: The Power of Data Analysis

In the past, claw lesion scoring was a manual, observational process – valuable but limited in scale and consistency. Today, Zinpro is leveraging advanced statistical tools to analyze large datasets from over 6,000 sows (a subset of over 30,000 sow database) across hundreds of commercial herds. These methods allow us to group pigs by claw health status, predict reproductive outcomes and identify which lesions most significantly impact overall claw quality that could lead to sow lameness. By reducing data complexity and solving classification challenges, we’ve transformed claw health from a subjective observation into a measurable, actionable benchmark.1 

Take the Zinpro® Lesion Index (L-index), for example. It is a composite score that quantifies claw lesion severity across multiple types of lesions. By analyzing L-index scores alongside reproductive key performance indicators (KPIs), we’ve uncovered patterns that were previously invisible. Sows with higher L-index scores consistently show poorer farrowing performance, including fewer liveborn piglets and higher stillbirth rates. 

Clustering Reveals the Hidden Story

Using K-means clustering, sows were divided into two distinct groups based on claw health: 

  • Cluster 1 (C1): Sows with poor claw quality and lower reproductive performance 
  • Cluster 2 (C2): Sows with better claw health and stronger reproductive outcomes 

Sows from C1 had greater L-index compared to C2 sows (P < 0.05). 

This segmentation allowed Zinpro to tailor interventions and understand how claw health impacts productivity over time. Notably, sows in C1 reached their reproductive potential earlier but declined faster, while C2 sows maintained performance longer.1 

Parity Matters, But So Does Timing

Zinpro data analysis also showed that parity order plays a critical role. Older sows tend to have worse claw health, especially in heel overgrowth and erosion (HOE1 These lesions, in turn, are linked to inflammation, pain and reproductive inefficiency. 

  • Sows from parity order (PO) 4, 5 and 6 had greater L-Index compared to sows from PO1 and PO2, with PO3 being intermediate (P < 0.05) 
  • Sows from PO1-C1, PO1-C2, PO2-C1 and PO2-C2 had breakpoints (duration of ZINPRO® Performance Mineral supplementation for minimal L-Index) of 10.36, 12.41, 14.85 and 16.02 months, respectively (P < 0.05) 
  • The breakpoints for PO3, 4, 5 and 6 from C2 were 15.02, 14.08, 14.28 and 10.50, respectively (P < 0.05 Ö). There was no breakpoint achieved for PO3, 4, 5 and 6 from C1 (P > 0.05) 

Why This Matters

This isn’t just about data, it’s about what the data enables. By embracing a multivariate approach, Zinpro is helping pork producers move from reactive treatment to proactive management. We’re identifying at-risk animals earlier, tailoring interventions by cluster and improving outcomes across the herd. 

For pork producers, herd managers, veterinarians and nutritionists, this means better decision-making, improved sow longevity and stronger return on investment (ROI). For the pork industry, it means a new benchmark for excellence. 

Find out more by downloading the Zinpro® Sow Excellence Index.