Using Models to Enhance Sow Productivity

Monday, March 24, 2025

Meeting the Genetic Potential of Animals While Maintaining Sustainable & Cost-Effective Practices

By Mohsen Abedin, Ph.D.

Modern swine production demands precision in feeding high-prolific sows to ensure both longevity and optimal performance. Over the past decade, advances in sow genetics and feeding systems have reinforced the need for accurate nutritional programs that prevent overfeeding or underfeeding individual sows. Advanced sow nutritional and management models offer swine nutritionists reliable, data-driven insights to support long-term productivity. When provided with accurate information on sow genotype, productivity, feed programs, and barn environmental data, these models have proven effective in helping producers refine feeding strategies, optimize production, and reduce feed costs. Even minor improvements in feeding precision can result in substantial economic benefits.

The role of models in sow nutrition

Advanced analysis and predictive modelling capabilities can assist swine nutritionists in designing sow feeding programs by integrating complex data on genetics, production history, and environmental conditions. Overfeeding or underfeeding sows can negatively affect their body condition and reproductive performance, ultimately shortening their productive lifespan. Nutritional models, such as the advanced NutriOpt Sow Model, help farmers fine-tune feeding strategies, ensuring that each sow receives the right nutrients at the right time, avoiding these challenges.

Models can create a ‘digital twin’ of the farm, consider the physiological requirement of a specifically-defined sow, and recommend a feed curve for sows in different body conditions (normal, lean, or fat). Key variables such as parity, litter size, housing, weaning weight, and feeding management are used to predict how diet and daily feed intake will affect body weight and back fat. This data-driven approach helps farmers optimize feed programs for individual sows, reducing the risks associated with generic feeding plans.

By simulating various scenarios, modelling allows farmers to avoid overfeeding, which can lead to fat accumulation and poor reproductive performance, or underfeeding, which can impact milk production and reproductive health. This precision improves sow longevity and reproductive performance, ensuring each animal reaches its full genetic potential while maintaining optimal body condition.

Achieving longevity and optimal performance

High-prolific sows, bred for larger litters and greater milk production, require precise nutrition to support their high output during gestation and lactation. Models like the NutriOpt Sow model ensure that each sow’s nutritional needs are met while minimizing stress, ultimately leading to longer productive lives and more efficient herd management. Models and electric feeding systems enable individualized feeding programs, recognizing that no two sows are alike.

Each sow’s body condition, litter size, and reproductive history are considered, making one-size-fits-all feeding approaches obsolete. When paired with electronic feeders, the model allows for blend feeding, ensuring precise nutrition and reducing waste.

Conclusion

Mechanistic models such as the NutriOpt Sow model, which uses a factorial approach to determine requirements based on parity, body weight, and backfat, are very helpful for optimizing feed programs in modern sow management. By integrating genetic and production data, these models enable precise, individualized feeding strategies that support the longevity and productivity of high-prolific sows. As the industry continues to evolve, such models will play an increasingly important role in helping producers meet the genetic potential of their animals while maintaining sustainable and cost-effective practices. BP