Sow precision feeding cuts costs, lowers environmental impact

Using a database of 3098 gestations from 1121 sows containing sows’ parity, BW, BT, feed intake, and litter performances, the study team calibrated predictive equations of the sows’ body chemical composition in a nutritional model.

Comparing feeding strategies

During gestation, four feeding strategies were compared. The conventional strategy (CF) gave all sows the same feed amount. The standard strategy (SF) adjusted feed to each sow’s energy needs.

Two precision feeding strategies (PF_AA and PF_AA‑P) went further. PF_AA adjusted feed amounts and lysine content by sow and day. PF_AA‑P added phosphorus adjustments, tailoring both lysine and phosphorus levels across sows and days.

The database was divided into two parts: a training set and a testing set. The training set fit body composition equations, while the testing set evaluated differences between observed and predicted BW and BT at farrowing.

What the data revealed

• 🐷 For the calibrated equations, the root mean squared error (RMSE) of sows’ BW and BT at farrowing were 10 kg and 1.7 mm, respectively.
• 🐷 Compared to the parameters before calibration, RMSE of sows’ BW increased by 3 kg and RMSE of sows’ BT decreased by −5.2 mm.
• 🐷 At the sixth farrowing, BT was 2 mm lower for CF compared to BT target and BT of other feeding strategies (P < 0.001).
• 🐷 The BT variability in the herd was also 19% greater for CF than SF, PF_AA, and PF_AA-P (P < 0.001).
• 🐷 Over six successive gestations, feed costs were reduced by EUR 17 and EUR 26, while nitrogen efficiency and P efficiency increased by 30 and 5% and by 15 and 30%, respectively for PF_AA and PF_AA-P strategies compared to CF (P < 0.001).

Based on in silico results, feeding the gestating sows individually according to their energy requirements improves the ability to reach the target BT at farrowing across cycles.

Adjusting nutrients to individual sow requirements, whether AA alone or combined with P, reduces feed costs and enhances nutrient efficiency over the long term.