| Literature DB >> 29376058 |
Karin Alvåsen1, Helena Hansson2, Ulf Emanuelson1, Rebecka Westin3.
Abstract
The number of born piglets per litter has increased in Swedish pig industry, and farmers are struggling to improve piglet survival. A common practice is to make litters more equally sized by moving piglets from large litters to smaller to make sure that all piglets get an own teat to suckle. Litter equalization is not always enough, as many sows have large litters and/or damaged teats, which results in an insufficient number of available teats. One way to solve this problem is to use nurse sows. A nurse sow raises, and weans, her own piglets before receiving a foster litter. The objectives of this study were to address how the use of nurse sows affects the welfare of sows and piglets and to explore how it impacts the contribution margin of pig production in Sweden. A literature search was made to investigate welfare aspects on sows and piglets. As there were few published studies on nurse sows, an expert group meeting was organized. In order to explore the impact on the contribution margin of pig production, a partial budgeting approach with stochastic elements was used for a fictive pig farm. Standard templates for calculating costs and benefits were supplemented with figures from existing literature and the gathered expert opinions. In Sweden, the minimum suckling period is 28 days while published studies involving nurse sows, all from outside of Sweden, weaned the piglets at 21 days. A Swedish nurse sow will thus get longer lactation period which might increase the risk of poor body condition, damaged teats, and shoulder ulcers. This indicates a reduced welfare of the sow and may lead to impaired fertility and increased culling risk. On the other hand, the piglet mortality could be reduced with the use of nurse sows, but the separation and mixing of piglets could be stressful. The partial budgeting suggested that the nurse sow system is slightly more profitable (+6,838 Swedish krona) per farrowing group during one dry and one lactation period compared to the conventional system. The result is, however, highly dependent on the input values, and welfare aspects were not considered in the calculations.Entities:
Keywords: contribution margin; modeling; pig industry; piglet; stochastic simulation
Year: 2017 PMID: 29376058 PMCID: PMC5770636 DOI: 10.3389/fvets.2017.00204
Source DB: PubMed Journal: Front Vet Sci ISSN: 2297-1769
Overview of stochastic input variables used in the partial budgeting model.
| Input variable | System | Mean (SD) | Mode; min; max | Distribution | Reference |
|---|---|---|---|---|---|
| Number of live-born piglets per litter | Both | 13.7 (0.8) | Normal | ( | |
| Piglet mortality rate (deaths/100 piglet-years) | Conventional | 0.18; 0.08; 0.33 | Triangular | WinPig and expert opinion | |
| Nurse sow | 0.14; 0.07; 0.25 | Triangular | Expert opinion | ||
| Weight at sale (79 days) | Conventional | 31 (3) | Normal | ( | |
| Nurse sow | 31 (2) | Normal | Expert opinion | ||
| Feed consumption during lactation (MJ per week) | Both | 510; 490; 530 | Triangular | TN-70 feed recommendation, 2016 | |
| Feed consumption during dry period (MJ per week) | Both | 220.5; 245; 269.5 | Triangular | TN-70 feed recommendation, 2016 | |
Overview of deterministic input variables used in the partial budget model of economic consequences of using nurse sows.
| Input variable | Fixed | Reference |
|---|---|---|
| Price at sale [Swedish krona (SEK)/79 days old piglet] | 580 | HK Scan, 2016 |
| Additional bonus at sale if piglet batch weight > 30 kg (SEK/extra kg) | 6 | HK Scan, 2016 |
| Feed consumption piglet (kg/week) | 1 | Expert opinion |
| Price of feed during lactation (SEK/MJ) | 0.22 | ( |
| Price of feed during dry period (SEK/MJ) | 0.20 | ( |
| Price of piglet feed (SEK/kg) | 6 | |
| Semen costs (SEK/unit) | 40 | ( |
Figure 1The input variables with greatest impact on the partial budget analysis comparing contribution margin of a nurse sow system with a conventional system. Values on either side of the bar represent the mean of the 10% lowest and 10% highest simulated values in Swedish krona for each variable.
Figure 2A tornado graph (with regressed mapped values) demonstrating the change in contribution margin (Swedish krona) if the input variables are increased by 1 SD and the other variables are held constant.