Management Influences on Birth Weight, Phase 2

by 5m Editor
25 January 2011, at 12:00am

This is a report based on the field survey which has been performed on farms. This is not a scientific report in the sense that all kinds of literature has been included and so conclusions should be drawn with care, write Chris T. Opschoor, Saskia Bloemhof, Mark Knauer and Egbert F. Knol.


Selection for increased litter size has a correlated response of lighter individual piglet birth weights (Roehe, 1999). In the TOPIGS breeding database, an increase of one piglet per litter is associated with a 30- to 50-g reduction in average piglet birth weight. Low birth weight piglets are associated, by farmers, with increased mortality, reduced weaned pig quality and slower growth rates, thus compromising kilograms marketed.

Individual piglet birth weight has a low heritability (as a litter trait, it is 0.30 or so; properly modelled it has additive component of 0.06 and maternal one of 0.18); still, much of the variation is explained by environmental causes. Therefore, identification of managerial factors that influence birth weight may be useful in improving the trait. TOPIGS nucleus farms have been recording the birth weight of individual piglets for several years. A preliminary analysis was made from eight farms, four each with high and low birth weights (Opschoor et al., 2009). Farms differed for average birth weight by more than 200g with similar genetics and litter size. To investigate further the differences in average piglet birth weight between farms a survey was distributed to study management differences.

The objective of the current study was to investigate environmental factors influencing average piglet birth weight and define methods to improve birth weight through management.

Material and Methods

Farm selection

Data consisted of 41,130 TOPIGS sows from 59 Dutch farms. Each sow entry included parity, litter size, litter weight and average birth weight per piglet recorded between 2 January 2008 and 30 January 2009.

Each farm housed one pure-line (B-line, F-line, N-line, T-line, Z-line) which was then mated to produce TOPIGS F1 gilts. The five pure-lines were combined to form 17 different F1 lines. Farms were selected if they recorded birth weights on a minimum of 300 litters during the specified time period. Of the 28 farms meeting these criteria, 19 were visited and chosen for analysis. The resulting farms contained four pure-lines (F-line, N-line, T-line, Z-line) and eight F1 combinations (BBFF, BBZZ, FFTT, FFZZ, ZZFF, NNBB, NNZZ, ZZNN). Gestation housing included both boxes and group pens. Gestation feeding was separated into three phases (phase 1, weeks 1 to 6; phase 2, weeks 7 to 10; and phase 3, weeks 11 to 16).


A questionnaire was formulated with 80 questions that could be related to birth weight. The questionnaire started with general questions such as farm size and farm staff. Subsequently, farmers were asked to give their opinion and impression of the birth weight measured on their farm.

To verify if the piglet weighing protocol was performed correctly by the farmers, several checks were performed. Scales were validated and time of weighing after birth and individual piglet weighing was checked.

The questionnaire also included subjects as: housing, feeding and health status of farms. The questions consisted of open and closed questions.

Statistical analysis

Analysis was conducted using SAS 9.2. Birth weight was pre-adjusted across farms using the following equation:

birth weightijklm =μ+bl *tnbi + parityj + yearseason(farm)k + farm*line litteri + eijklm

This equation indicates birth weight was adjusted to a common litter size, parity, year × season interaction, and farm × F1 line interaction. Birth weight was adjusted to 14 piglets per litter, the database average.

Regression analysis from PROC GLM was used to relate the independent variable birth weight (y) to the multiple dependent variables (x) resulting from the survey. The regression coefficients can be interpreted as for every increase in one unit of x there is an associated change in birth weight (y). For categorical variables, LS MEANS from PROC GLM was used to make comparisons.

Results and Discussion

Results are shown when they were found to be interesting. No effect was found on farm health status.

General farm effects

General farm descriptive statistics and regression coefficients are presented in Table 1. Average piglet birth weight was 1.36kg, which is within the range of reported literature values (Knol et al., 2002). The regression coefficient for litters per sow per year was -560. This number can be interpreted that for every extra litter (over the average of 2.4) a sow farrows per year average piglet birth weight decreases by 560g, or for every extra 0.1 of a litter a sow farrows, average piglet birth weight decreases by 56g. Although not statistically significant (P=0.13), perhaps a reduction in average piglet birth weight can be expected as litters per sow per year increases under current environmental conditions.


Lactation descriptive statistics and regression coefficients are shown in Table 2. Total lactation feed intake between farms was not associated (P=0.55) with average piglet birth weight. An insufficient level of total lactation feed intake is commonly associated with a prolonged wean-to-service intervals and reduced subsequent litter size. However, these Dutch farms have relatively long lactation lengths (25 days) in comparison to the United States (19.5 days, PigCHAMP 2008) and good lactation feed intakes, a combination that allows a sow’s uterus time to repair itself for subsequent reproduction.

Total lactation crude fat was positively associated (P=0.05) with average piglet birth weight. These results concur with our preliminary findings from eight other farms (Opschoor et al., 2009). However, per cent crude fat is confounded with total lactation feed intake. This means we do not know whether increasing per cent crude fat or total lactation feed intake may increase average piglet birth weight. Lactation feed descriptive statistics and regression coefficients by week were not significant (P>0.05).


Insemination descriptive statistics and regression coefficients are shown in Table 3. Total insemination feed intake per day was significantly (P=0.02) associated with average piglet birth weight. These results are supported by our preliminary findings and King and Williams (1984).

Collectively, these results uphold the long-held belief that sows should be flushed from weaning to insemination (Whittemore, 1996). In the present study, the regression coefficient for total insemination feed intake per day indicates a one-kilo increase in daily feed intake would increase average piglet birth weight by 45g. Therefore, increasing feed intake during the insemination period may be profitable.

Nevertheless, it may be more economical to change diet composition. Regression coefficients for both digestible lysine and threonine were significant (P=0.02) and positive. However, percentage of lysine and threonine are confounded with total insemination feed intake. This means we do not know whether increasing the percentage of lysine and threonine or level, due to increased insemination feed intake, may increase average piglet birth weight. Sows fed lactation diets had numerically higher (P=0.44) average piglet birth weights than those fed insemination (55g) or gestation diets (51g). Perhaps the difference is due to the higher lysine, threonine or energy density that would commonly be found in lactation feed in comparison to insemination or gestation diets.


Gestation descriptive statistics and regression coefficients are shown in Table 4. Total gestation feed intake was significantly (P=0.04) associated with average piglet birth weight. These results are not supported by Mahan (1998) and Heyer et al. (2004) who reported gestation feed intake had no effect on average piglet birth weight. However, today’s sow is more prolific than those from previous studies. Whittemore (1996) suggests a higher feeding level when birth weights are lower than 1kg. There is likely an intermediate optimum gestation feeding level in relation to average piglet birth weight.

Underfeeding in gestation can lower litter weights and result in poor body condition while overfeeding gestating sows can cause excessive weight gains leading to farrowing problems (Rozeboom et al., 1996) and reduced lactation feed intake (Whittemore, 1996).

In the current study, the positive regression coefficient indicates as total gestation feed intake increased 1kg average piglet birth weight increased 1.2g. By feed intake phase, regression coefficients for phase’s 1, 2, and 3 were 1.47 (P=0.20), 3.13 (P=0.13), and 1.48 (P= 0.20), respectively. Higher total gestation digestible lysine tended (P=0.09) to be associated with increased average piglet birth weight. Regression coefficients for total gestation digestible lysine for phase 1, 2, and 3 were 0.22 (P=0.07), 0.32 (P=0.07) and 0.12 (P=0.15), respectively.

In contrast, past studies indicate lysine or crude protein levels have little influence on piglet birth weights (Mahan, 1998; Clowes et al., 2003) unless they are very low (Shields et al., 1985). In the present study, the highest regression coefficients for total feed intake and total digestible lysine from the three gestation phases were in phase 2 (3.13 and 0.32, respectively). However, total gestation feed intake and total gestation digestible lysine are confounded. This means we do not know whether increasing the total gestation feed intake or the percentage of lysine may increase average piglet birth weight.

Categorical survey questions

Farmers were asked a multitude of questions relating to their farm. The following given answers are not significantly different (P>0.05) but numerically meaningful.

Although not significant (P=0.30), gilts quarantined before herd entry had a 39g higher average piglet birth weight than gilts directly introduced.

Sows group housed had a 61-g higher (P=0.34) average piglet birth weights in comparison to sows housed in boxes. These results are supported by Bates et al. (2003) who reported sows from a group housing system had higher litter birth weight than sows from individual stall gestation.

The reason sows from group gestation systems tend to have higher piglet birth weights relative to stalls is unclear. Perhaps increased exercise in group gestation relative to sows in stalls increases average piglet birth weight. This is supported by Hale et al. (1981) who reported sows that were exercised on a treadmill for 15 minutes a day had numerically higher average piglet birth weights (~70g) than those that were not.

In the current study, the use of prostaglandins in comparison to natural farrowing resulted in a 43g lower (P=0.32) average piglet birth weight. In agreement, Welp and Holtz (1985) reported birth weight was slightly lower in sows given prostaglandins under field conditions. Since rapid piglet growth occurs during the latter part of gestation, it would be expected that artificially shortening gestation length through prostaglandin use would reduce average piglet birth weight.

The individual collecting the data gave an overall farm hygiene score (very good, good, or average) when visiting each farm. This subjective score was based on availability of protocols and overall impression on hygiene. Average piglet birth weight tended (P=0.10) to be different between farms for hygiene. Piglets from farms with very good hygiene weighed 104g more than good farms and 224g more than average farms. These results support the idea that excellent management will be reflected in the farms reproduction results.

What can we gain from the above categorical survey questions? To draw statistical conclusions, we would need more farms to increase our statistical power. However, assuming the above results were significant and no interactions between variables, gilts quarantined, housed in groups, no prostaglandins at farrowing, fed lactation diets from weaning to insemination, and from very good hygiene farms would have a 422g larger average piglet birth weight than those gilts not quarantined, housed in boxes, given prostaglandins at farrowing, fed the insemination diet, and had average farm hygiene. From this unique data set one can see the potential for increasing average piglet birth weight through management.

Conclusions and Recommendations

Results supported the findings of the preliminary study. Farm insemination, gestation, and lactation feeding were all found to be associated with average piglet birth weight. During lactation and from weaning to insemination sow feed intake should be ad libitum or at a high level. During gestation, sows should be fed according to body condition. Feeding topics that warrant further research include separating the effects on average piglet birth weight of:

  • total lactation feed intake and crude fat content
  • total insemination feed intake with lysine and threonine
  • total gestation feed intake and lysine

Before diet or feeding level adjustments are implemented an analysis should be conducted to investigate whether the changes are economically beneficial.

Several management factors including gilt pool management, type of gestation housing, prostaglandin use at farrowing, type of insemination feed, and overall farm hygiene may be related to average piglet birth weight. Overall farm hygiene had the largest effect of the categorical survey questions and may be the easiest to change.


Aron van Balkom is greatly acknowledged for taking the surveys. Farmers participating in this study are greatly acknowledged.


Bates, R.O., D.B. Edwards and R.L. Korthals. 2003. Sow performance when housed either in groups with electronic sow feeders or stalls. Livest. Prod. Sci. 79:29-35.

Clowes, E.J., R. Kirkwood, A. Cegielski and F.X. Aherne. 2003. Phase-feeding protein over three parities reduced nitrogen excretion without affecting sow performance. Livest. Prod. Sci. 81:235-246.

Hale, O.M., C.V. Booram and W.C. McCormick. 1981. Effects of forced exercise during gestation on farrowing and weaning performance in swine. J. Anim. Sci. 52:1240-1243.

Heyer, A., H.K. Andersson, J.E. Lindberg and K. Lundstrom. 2004. Effect of extra maternal feed supply in early gestation on sow and piglet performance and production and meat quality of growing/finishing pigs. Acta Agric. Scand. 54:44-55.

King, R.H. and L.H. Williams. 1984. The effect of nutrition on the reproductive performance of first litter sows. 1. Feeding level during lactation and between weaning and mating. Anim. Prod. 38:241-247.

Knol, E.F., B.J. Ducro, J.A.M. van Arendonk and T. van der Lende. 2002. Direct, maternal and nurse sow genetic effects on farrowing, pre-weaning, and total piglet survival. Livest. Prod. Sci. 73:153-164.

Mahan, D.C., 1998. Relationship of gestation protein and feed intake level over a five-parity period using a high-producing sow genotype. J. Anim. Sci. 76:533-541.

Opschoor, C.T., S. Bloemhof and E.F. Knol. 2009. Management influences on birth weight: High Low study. TOPIGS 2009.

PigCHAMP. 2008. Accessed 27 January 2010.

Roehe, R. 1999. Genetic determination of individual birth weight and its association with sow productivity traits using Bayesian analyses. J. Anim. Sci. 77:330-343.

Rozeboom, D.W., J.E. Pettigrew, R.L. Moser, S.G. Cornelius and S.M. el Kandelgy. 1996. Influence of gilt age and body composition at first breeding on sow reproductive performance and longevity. J. Anim. Sci. 74:138-150.

Shields, R.G. Jr., D.C. Mahan and M.F. Maxson. 1985. Effect of dietary gestation and lactation protein levels on reproductive performance and body composition of first-litter female swine. J. Anim. Sci. 60:179-189.

Welp, C and W. Holtz. 1985. Induction of parturition with prostaglandin analogs under field conditions. Anim. Reprod. Sci. 8:171-179.

Whittemore, C.T. 1996. Review: Nutrition reproduction interactions in primiparous sows. Livest. Prod. Sci. 46:65-83.

Further Reading

- You can view the full report by clicking here.

January 2011