The effect of tissue mobilization and stage of lactation on energy partitioning in lactating sows: an analysis of commercial data

Abstract

The objective of this paper was to investigate how the predicted level of body energy mobilized and the stage of lactation affects performance and energy partitioning in lactating sows kept under commercial conditions. Seventy-seven lactating sows from three consecutive batches were weaned at 28 d and all measures were taken over the first 20 d. Total feed consumption was measured and sows’ live weight was registered when entering the lactation facilities and at 21 d of lactation. Blood samples were collected at farrowing and once a week thereafter. Net energy (NE) mobilization or loss was calculated by difference using the general NRC equation for ME partitioning. Compared to low mobilizers (low NE loss values), high mobilizing sows had lower feed intake and higher loss of live weight, body fat and body protein. High mobilizers also weaned more piglets and had heavier litters than low mobilizers. Energy mobilization (NE loss) was higher from day 1 to 10 of lactation compared to day 11 to 20, and the difference in mobilized energy between high and low mobilizing sows was also higher in the first than in the second half of lactation. Body weight and back fat thickness losses were significantly correlated with NE loss. A more accurate prediction of the changes in live weight or back fat thickness over lactation should help better predict total amount of energy mobilized, and more research is needed to assess the relative contribution of lean and fat to mobilized tissue.

Introduction

Lactation is the most demanding period of a sow's reproductive cycle and optimizing nutrition appears an excellent tool to ensure health, wellbeing and long-term productivity (Trottier et al., 2015; Tokach et al., 2019). Milk production depends on the sow's genetic potential and feed intake, but it is strongly related to litter size and piglet suckling capacity (Hartmann et al., 1997; Eissen et al., 2000; King, 2000). During lactation (≥3 wk), many sows undergo negative net energy balance (losing up to 40 kg of body weight (BW) and 5–10 mm of back fat thickness (BT)) to produce milk (Rojkittikhun et al., 1993; Dourmad et al., 1996; Thaker and Bilkei, 2005; Cerisuelo et al., 2008; Gourley et al., 2020) affecting subsequent reproductive performance (Johnston et al., 1989; Zak et al., 1997; Yoder et al., 2013). However, other authors (Willis et al., 2003) have also pointed out that those lactation effects on reproductive performance are marginal. Studies on sows show contradicting results regarding the link between body mobilization and milk production, and whether high feed intake (5.0 to 7.6 kg/day) can prevent excessive BW loss (Eissen et al., 2003; Mosnier et al., 2010; Strathe et al., 2017).

More than thirty years ago, Noblet and coworkers did foundational work studying energy and protein metabolism of lactating sows (Noblet and Etienne, 1987; Noblet et al., 1990; Quiniou and Noblet, 1999) and established the principles of sow's energy and tissue mobilization. However, direct measurement of energy and tissue mobilized in lactating sows is difficult and expensive (Everts and Dekker, 1994b; Dourmad et al., 1997) and they are often predicted using the variation of maternal body fat and protein pools, calculated from changes in maternal empty body weight and in P2 back fat thickness (Dourmad et al., 2008; NRC, 2012). The first equations were mainly obtained from original slaughtering data published by Dourmad et al. (1997). In any case, quantifying the variability in composition of BW loss during lactation has received limited attention and NRC (2012) assumed it constant. However, the rate and composition of tissue mobilized may change substantially with genetic line, age and stage of lactation, body composition at farrowing and even individually between sows (Mullan et al., 1989; Noblet et al., 1990; Sauber et al., 1998; Kim and Easter, 2001; Gauthier et al., 2019; Pedersen et al., 2019). Furthermore, other factors, such as litter size and vigorousness of the suckling piglets, pattern and management of feed intake, environmental conditions and sow genetic potential (Eissen et al., 2000; Kim and Easter, 2001) may also have an effect.

The aim of the present study was to investigate how the predicted level of body energy mobilized and the stage of lactation (first and second half) affects performance and energy partitioning of lactating sows kept under commercial conditions.

Material and methods

Animals, management, experimental design and measurements

The data were collected from a commercial farm located in Osona (Barcelona, Spain) in 2014, with a breeding stock of 350 Landrace × Large White (LD × LW) sows. The general management of the farm was a three week batch system line.

Sows from three consecutive batches were used. After weaning, sows were monitored daily for signs of oestrus. At oestrus, each sow was subjected to insemination with refrigerated semen following the detection of heat by a teaser boar. The sows remained in individual stalls for approximately 30 d until pregnancy testing, after which pregnant sows were group housed in gestation pens holding 8–10 sows each. Approximately 3–4 d before farrowing, all sows in the gestation pens were moved to the farrowing building and were allocated to individual farrowing crates. Each farrowing crate was previously thoroughly washed and disinfected. The introduction of late gestation sows to the rooms was never earlier than 1–2 d after disinfection. All farrowing rooms were naturally ventilated and were equipped with commercial crates for each sow including a creep area for her piglets. The sow area had a metal slatted floor whilst that of the creep area was partially slatted and concrete. All farrowing crates were equipped with two nipple drinkers for sow and piglets, and a feeder for sows. Twice a day extra water was dispensed via the feeder to all sows. Every three weeks a new batch of pre-partum sows filled the crates and remained there until the weaning of their litters approximately 28 d post farrowing. All batch piglets were then moved to the nursery building, whereas their dams were moved to the breeding–gestation building and placed separately in individual stalls, each with an automatic feed dispenser and water permanently available.

The experiment included 77 sows (28, 20 and 29 sows from each batch) distributed by parity from gilts up to seventh parity sows (22 gilts; 35 from 2rd to 4th parity, and 20 >4th parity). Farrowing was performed with minimal use of pharmacological products and low human intervention. Cross-fostering was permitted only within 24 h post farrowing and was carried out following the protocol of the commercial farm. Litters of between 9 and 14 piglets born alive were started, the litters were equalized to 12, trying to leave most piglets with their mothers and make as few changes as possible. Some gilts were allocated 13 piglets. Piglets were treated using routine management practices (ear notching, iron injection and deworming) in the first 48 h post farrowing. Extra heat was provided for piglets from a proper heated area plus using infrared electric lamps placed in the creep area for the first 2 d of life. Each farrowing crate was cleaned daily. No creep feed was provided before day 20 of lactation.

As farrowing in each batch spread from Tuesday to Saturday, sows were offered a predetermined amount of gestation feed [12.43 MJ metabolizable energy (ME)/kg, 13.5% crude protein (CP) and 0.64% total lysine] until the following Monday, at a rate of 1.5, 3.0; 4.0; 4.5 and 5.0 kg/sow, starting the day after farrowing. On Monday, lactation feed was offered twice a day by hand, to reach maximum daily intake as soon as possible whilst trying to avoid refusals. Table 1 shows the composition of the lactation feed.

Table 1. Ingredients and nutrient composition of lactation diet

Vitamin and mineral complex provided the following per kg of feed: 12 500 IU of vitamin A, 2000 IU of vitamin D3, 20 mg of vitamin E, 2 mg of vitamin K3, 4 mg of vitamin B1, 5 mg of vitamin B2, 25 mg of vitamin B3, 2.6 mg of vitamin B6, 0.02 mg of vitamin B12, 12 mg of calcium pantothenate, 25 mg of nicotinic acid, 0.100 mg of biotin, 300 mg of choline-Cl, 100 mg of Fe, 10 mg of Cu, 0.5 mg of Co, 100 mg of Zn, 80 mg of Mn, 0.5 mg of I and 0.22 mg of Se.

Total cumulative feed intake at day 20 of lactation, gestation plus lactation feed, was measured individually. Furthermore, feed consumption was registered by weighing the feed on offer and the refusals every Monday, Wednesday and Friday of the lactation weeks starting the first Monday post farrowing. By the end of the 20 d lactation period, a total of 9–10 cumulative feed intake observations had been made for each sow. All piglets were individually weighed on day 20 post farrowing and litter weight was measured four or five times, i.e. during the 24 h after farrowing and every Wednesday throughout lactation. Mean, maximum and minimum ambient temperatures were also monitored (HOBO UX100-003 Temperature/Relative Humidity data logger; Onset Computer Corporation, Bourne, MA) daily in each farrowing room.

All sows were weighed when entering the farrowing room and again on day 21 of lactation. Back fat thickness was measured by ultrasound at the P2 position (65 mm from the midline over the last rib) when sows entered the farrowing room and on each Monday throughout lactation (five recordings for each sow). Sow BW at farrowing was estimated using the equation published by Mallmann et al. (2018); post-farrowing sow body weight (kg) = 13.03 + (0.93 × pre-farrowing body weight, kg) + (–1.23 × total piglets born). The individual sow's lipid and protein body mass were estimated using sow BW and BT and following Dourmad et al. (2008). Thereafter, total loss of lipid and protein through 20 d of lactation (kg) were also calculated individually, subtracting the total predicted protein and lipid amount obtained at weaning from that obtained at farrowing.

Blood samples (of approximately 10 ml) were collected from the external jugular vein at farrowing and each Wednesday until day 20 of lactation (four samples for each sow). Blood collections were done, on average, between 3 and 4 h after the morning meal. All blood samples were centrifuged at 800 g for 10 min for serum recovery, which was frozen and stored at −80°C for further analyses. Serum samples were analysed for NEFA, glycerol, urea and creatinine. Briefly, the following methods were used for metabolite determination: reagent NEFA C (Wako Chemicals GmbH, Germany) for non-esterified fatty acid (NEFA); glycerol phosphate oxidase enzymatic method (Beckman Coulter Reagent) for triglycerides; glucose-dehydrogenase (GLDH) for urea; and colorimetric Jaffé method reaction for creatinine. All the assays were performed with an Olympus AU400 analyser following the manufacturer's recommendations for the different metabolites.

Energy partitioning: assessing stage of lactation and individual energy balance

Under commercial conditions a well-managed and not pharmacologically induced farrowing batch lasts several days (3 d minimum) and, as weaning is completed at a fixed day, lactation length differs between litters. In such circumstances, to follow individual sows day by day from farrowing to weaning slows down regular management at the farrowing house, and collecting feed intake and litter growth data on fixed days and adjusting the individual curves later provides an alternative approach to measuring energy balance.

The individual feed intake data collected from farrowing to weaning (kg fresh feed/sow and day) were fitted using a rectangular hyperbola, a simplification of the modified generalized Michaelis-Menten proposed by Schinckel et al. (2010) and adopted by the NRC (2012):

(1)$${\rm DMI\ }( {{\rm kg/d}} ) = a/ ( {1 + ( {b/t} ) } ) $$

where DMI is dry matter intake, t is day of lactation, a is the asymptote of the curve, and b is a parameter representing t at the half-maximal value of a.

Likewise, the litter weight (LW, kg) recorded over lactation was fitted using a simple polynomial, i.e. the quadratic equation:

(2)$${\rm LW\ }( {{\rm kg}} ) = a + bt - ct^2$$

where t is day of lactation and a, b and c are equation parameters. For about 12% of litters, the weight at cross fostering was not available when fitting the curve.

Provided with Equations (1) and (2), total, partial and daily ME partitioning in the body of the sow (Mcal/sow/d) was expressed as:

(3)$${\rm M}{\rm E}_{{\rm intake}}{\rm} = {\rm M}{\rm E}_{{\rm maintenance}}{\rm} + {\rm M}{\rm E}_{{\rm for\ milk}}{\rm \pm M}{\rm E}_{{\rm from\ body\ tissues}}$$

and consequently, the contribution of tissue mobilization to the overall ME pool (ME equivalent from tissues; Mcal) was calculated by difference, using the equation:

(4)$$\hskip-9pt\eqalign{& {\rm ME\ from\ body\ tissues} = \cr& \qquad{\rm ME\ intake -}( {{\rm ME\ maintenance} + {\rm ME\ excreted\ in\ milk}} )} $$

where ME intake was determined by multiplying total feed intake (kg DM) by ME concentration of the feed (MJ/kg DM), ME maintenance was calculated assuming 460 kJ ME/kg of the mean metabolic body weight (Dourmad et al., 2008), and ME for milk (ME dedicated to milk production) was determined using the NRC (2012) equation to estimate mean milk energy output, knowing mean litter growth (g/d), and assuming an efficiency of utilization of ME for milk production (K_m) of 0.72 (Dourmad et al., 2008). Calculations for the 20 d lactation were carried out using individual measured feed intake and litter growth, with calculations for the remaining days (of the 4-week period) based on the fitted curves.

Knowing the ME contribution from tissues, total NE loss or mobilized (MJ/d) was calculated. Values of 0.72 for K_m, 0.87 for the efficiency of energy utilization from body reserves for milk production and 0.75 for the efficiency of energy utilization for the sow growth during lactation were assumed (Dourmad et al., 2008).

Although calculation of NE loss is obtained by difference and is affected by errors in quantifying the other components of Equation (4), we propose a simple factorial approach to categorize sows according to their NE mobilization. Table 2 classifies the sows as High, Medium or Low mobilizers (including sows in positive energy balance), the theoretical amount of BW lost (kg/d), and theoretical composition of the tissue mobilized. The latter is considered in two extreme scenarios (850 g/kg fat and 150 g/kg lean or 550 g/kg fat and 450 g/kg lean), following the results of Kim and Easter (2001). It is assumed that body fat and protein contain 39.3 and 23.4 kJ/g, respectively (Whittemore et al., 2003), and that fat tissue is 970 g/kg lipids and lean tissue is 230 g/kg protein (NRC, 1998).

Table 2. Proposed range of energy mobilization (MJ NE/d) of lactating sows depending on theoretical total body weight (BW) loss and composition of that loss (fat or lean tissue)

NE loss was calculated assuming that each kg of BW loss contained either 850 or 550 g/kg of fat tissue (97% lipid and 38.1 kJ/g) and either 150 or 450 g/kg of lean tissue (23% of protein and 5.4 kJ/g), following Kim and Easter (2001), Whittemore et al. (2003) and NRC (1998). Both scenarios represent two extreme options, high fat sows or high lean sows.

Statistical analysis

All statistical procedures employed were part of the SAS V.9.3 statistical package (SAS Inst. Inc., Cary, NC) and R. The data were analysed for normality and homoscedasticity using the Shapiro-Wilk test of the Univariate procedure and the GLM procedure, respectively. Energy partitioning and performance were analysed as a 2 × 3 factorial arrangement of treatments for main effects of parity (primiparous or multiparous) and degree of mobilization (high (H); medium (M) or low (L), as categorized earlier) and degree of interaction of parity × mobilization, using the maximum likelihood method and considering the individual sow as a random effect. No effect of batch was observed and therefore it was not considered for further analysis. Serum metabolite concentrations were analysed using first and second order polynomial models, adjusted by means of the gls:nmle function in R (Pinheiro and Bates, 2023), in order to perform a repeated measures analysis with an unstructured covariance matrix (Pinheiro and Bates, 2000; Piepho and Edmondson, 2018). In the second order models, orthogonal polynomials were selected due to their computational benefits and the stability of the estimates. Indeed, removing higher order terms did not affect estimates of the coefficients of the lower order terms when orthogonal polynomials were used. Furthermore, piglet number at cross-fostering and at weaning as count variables did not satisfy normality and homoscedasticity of the variances. Therefore, they were analysed by logistic regression with generalized linear models following the same factorial arrangement previously described, with the GENMOD procedure fitting a Poisson distribution. The individual sow or litter was the experimental unit for all parameters. When significant P values (P < 0.05) were observed, least square-mean (LS-mean) comparisons were performed with a Tukey adjustment test for the ANOVA and 0.95 confidence limits for each of the LS-means for the non-normal data. Means were considered significantly different when P < 0.05 in both cases.

Results

Mean daily temperature in the farrowing barn was always below 24.5°C, with maximum daily variations between 3 and 6°C; humidity was permanently registered below 70%.

Table 3 shows the mean, standard deviation, and minimum and maximum values of the main recorded or calculated performance parameters. Mean daily feed intake was 5.03 kg/d, total average litter gain 46.6 kg and sows lost an average of 21.1 kg BW and 2.68 mm of BT. Weaning to oestrus interval averaged 5.5 d though in some sows it extended up to 15 d. As far as some calculated parameters were concerned, total lipid and protein predicted losses accounted for 6.9 and 2.7 kg/sow, respectively, and the mean calculated NE loss was 601.7 MJ in 20 d.

Table 3. Sow performance parameters for the lactating period (20 d)

ADFI, average daily feed intake; CF, cross fostering; BW, body weight; BT, back fat thickness. BW at farrowing corrected according to NRC (2012). Lipid and protein losses calculated according to the equations given by Dourmad et al. (2008). NE loss obtained by difference and assuming a constant value of 0.72 (K_m) and 0.87 (K_bm, efficiency of utilization of body reserves for milk production; Dourmad et al., 2008). The efficiency of utilization for growth during lactation (K_mb) was assumed to be 0.75.

Net energy loss was negatively and positively related to ME intake and ME for milk, respectively. The r value was higher for ME for milk (0.790; P < 0.001) than for ME intake (0.541; P < 0.001) and this relationship was higher for the first than for the second part of lactation (r values of 0.809 and 0.720 and of 0.566 and 0.484 for ME for milk and ME intake, respectively). Net energy loss only had a moderate relationship with sow body weight loss (r = 0.517; P < 0.001), BT total loss (r = 0.464; P < 0.001) and BT loss as a percentage of BT at farrowing (r = 0.474; P < 0.001).

Effect of stage of lactation

Figure 1 shows daily means (MJ/sow) and standard error of ME intake, ME used for maintenance and milk production, and NE mobilized. As expected, at the beginning of lactation ME used increased faster than ME intake, although the average sow continued mobilizing throughout the 20 d of lactation. The standard errors were high at the beginning of lactation and reduced thereafter. Overall, NE losses had the highest standard error, followed by ME used for maintenance and milk production, and ME intake. Differences among the latter two were mainly found during the first days of lactation.

Figure 1. Daily ME intake (MJ/sow/d, circle), ME needed for maintenance and milk production (square) and NE loss (MJ/sow/d; diamond). Mean values (symbols) and standard error of the mean (error bars) are illustrated.

Effect of week of lactation and age on blood parameters comparing gilts and multiparous sows is shown in Fig. 2 and Table 4 and include the statistical analysis. A quadratic model was preferred for all the metabolites studied (Table 4). The models, significantly differ from the constant model (see the P-value (Trend) column; Table 4). All values increased throughout lactation and were significantly higher than on the day of farrowing (Fig. 2). NEFA, glycerol and urea levels increased faster for multiparous sows than for gilts, even though gilts reached higher serum concentrations in week three (Fig. 2). Also in Fig. 2, gilts show lower creatinine concentration and a higher urea:creatinine ratio than multiparous sows over the whole lactation; the differences in urea:creatinine ratio increased through lactation.

Figure 2. Adjusted first (linear) and second (quadratic) order polynomials for the serum metabolite concentrations (NEFA, mmol/L, glycerol, μmol/L, urea, mg/dL, creatinine, mg/dL and urea:creatinine ratio) over the lactation period according to the age of the sow (gilts, G vs multiparous, M).

Table 4. Akaike information criterion (AIC) for the linear and quadratic tendency and the effect of the age of the sow (gilts vs multiparous), the tendency and their interaction on serum concentration of non-esterified fatty acids (NEFA), glycerol, urea and creatinine plus the urea:creatinine ratio

U:C: urea:creatinine ratio, RSE: residual standard error. ANOVA comparing quadratic (Q) against linear model.

Effect of sow's age and level of energy mobilization

Results presented in Tables 5 and 6 refer to 20 d of lactation and presupposes an average constant composition of mobilized tissue of 720 g/kg fat and 280 g/kg protein, coincident with the mean individual values of total predicted lipid and protein losses (see Table 3). Table 5 shows the effects of level of energy mobilization and age for gilts v. multiparous sows on the main performance parameters, and Table 6 on energy partitioning in the body of the sow and losses of body weight, BT, lipid and protein.

Table 5. Effect of level of NE mobilized (high, medium, low) and age of the sow (gilts, G vs. multiparous, M) on litter and piglet performance and the sow's weaning to oestrus interval (WEI)

SD: standard deviation, CF: cross-fostering. Eight sows included as low mobilizers, two gilts plus six multiparous, showed positive NE balance over the entire lactation.

Table 6. Effect of level of NE mobilized (high, medium, low) and age of the sow (gilts, G vs. multiparous, M) on metabolizable energy partitioning, body weight (BW) and back fat thickness (BT) measured pre-farrow and BW estimated just post-farrow and BT, BW and body lipid and protein (kg) losses, and the NE balance over the 20 d lactation period

SD: standard deviation. Eight sows included as low mobilizers, two gilts plus six multiparous, showed positive NE balance over the entire lactation. ME in milk calculated using a constant value of 0.72 for K_m (efficiency of utilization of ME for milk synthesis) according to Dourmad et al. (2008). Lipid and protein losses were estimated using the NRC (2012) equations. NE loss obtained by difference assuming constant values of 0.72 (K_m) and 0.87 (K_bm, efficiency of utilization of body reserves for milk production; Dourmad et al., 2008). The efficiency of utilization for growth during lactation (K_mb) was assumed to be 0.75.

Gilts weaned more piglets (P < 0.006) and had a lower piglet mortality (P = 0.004) compared to multiparous sows, but multiparous sows produced higher piglet gain (P < 0.001). As a result, litter gain (kg) in the 20 d period did not differ between gilts and multiparous sows (45.1 vs. 46.7, P = 0.344, respectively). Accordingly, gilts used a similar amount of ME for milk production (P = 0.416) but had a lower ME intake (P = 0.015), a higher body weight loss (P = 0.004) and a higher body lipids loss (P = 0.020). Gilts also apparently (P > 0.05) lost more BT and body protein than multiparous sows, although NE losses do not reflect body composition changes. Gilts had a higher weaning to oestrus interval (P = 0.006). The interaction found with BT loss (P = 0.030) indicates that BT loss increases with energy mobilization only with multiparous sows while medium mobilizing gilts registered the highest BT loss.

As expected (Tables 5 and 6), high mobilizing sows had lower ME intakes than low mobilizers (P = 0.006) and, consequently, they lost more body weight (P = 0.003), body lipids (P = 0.002) and body protein (P < 0.001). High mobilizing sows used more ME to produce milk (P < 0.001), and compared to low mobilizers, promoted higher litter gains (P < 0.001) as they weaned more piglets (P = 0.010), with those piglets being heavier (P < 0.001) and having lower lactation mortality (P = 0.013). Medium mobilizers were found as well as high and low mobilizing sows for all parameters studied (Tables 5 and 6).

Table 7 shows the effect of the sow's level of mobilization and stage of lactation (day 0 to 10 vs. day 11 to 20) on ME intake, ME for milk and NE balance (MJ/sow/d). As expected, ME intake and ME for milk was higher in the second half of lactation than in the first (P < 0.001), while NE balance (NE loss) trended in the opposite direction (P < 0.001).

Table 7. Effect of amount of energy mobilized (High, Medium, Low) and stage of lactation (SL: first vs. second half) on metabolizable energy intake, metabolizable energy for milk and net energy loss (MJ/sow/d)

SD: standard deviation. ME in milk calculated using a constant value of 0.72 for K_m (efficiency of utilization of ME for milk synthesis) according to Dourmad et al. (2008). NE loss obtained by difference assuming constant values of 0.72 (K_m) and 0.87 (K_bm efficiency of utilization of body reserves for milk production; Dourmad et al., 2008). The efficiency of utilization for growth during lactation (K_mb) was assumed to be 0.75.

The interactions found between level of mobilization and stage of lactation for ME for milk (P < 0.022) and NE losses (P < 0.010) show that the difference in ME for milk among high and low mobilizing sows (MJ/d) was greater in the first (68.2 vs. 41.8) than in the second half of lactation (76.0 vs. 59.4), in accordance with a higher NE loss difference (59.1 vs. 39.7 MJ/d, respectively).

Discussion

Prediction of lactation energy balance

Sow and litter performance are in line with those reported in recent publications with similar lactation length (Stewart et al., 2021, Williams et al., 2021; Ye et al., 2022). Milk production has the highest priority for the sow during lactation, which means that energy and most dietary nutrients are directed toward the mammary glands (Strathe et al., 2017). In fact, almost 100% of maternal dietary energy intake (or even more) may be required for milk synthesis (Pluske et al., 1995; Pedersen et al., 2019; also Table 3) and among sows within farms, milk production costs explain 95% of variability in the daily ME requirement (Gauthier et al., 2019). The fact that in this study ME intake and ME used for milk production were poorly correlated suggests that, probably, daily feed intake did not reach full ad libitum and illustrates the importance of energy mobilization. Adiposities reduce in size and lipoprotein lipase activity in fat tissue decreases considerably during lactation (Steingrimsdottir et al., 1980), and a considerable amount of protein can be depleted from lean tissue stores (Kim and Easter, 2001). In fact, the sow compensates for inadequate feed intake to maintain a high milk production, even though it is expensive as the body reserves lost must be reconstituted during the following gestation, resulting in an increased feed cost (Strathe et al., 2017).

Energy mobilization (NE loss) is mainly a consequence of a limitation on feed intake (Eissen et al., 2000; Gauthier et al., 2019). However, a better relationship with ME for milk (r = 0.790) than with ME intake (r = 0.541) was found, suggesting litter size and vitality of the piglets, which are the main determinants of milk production (Hartmann et al., 1997), are also responsible.

In any case, the mean value for lactation efficiency, defined by Bergsma et al. (2009) as ME for milk divided by the sum of ME intake and ME equivalent from body reserves, was 0.678 (SD = 0.055). This mean value is similar to the found by Everts and Dekker (1994a) using respiratory chambers, but lower than that found by Pedersen et al. (2019) using D₂O space to assess energy mobilization (0.87). Cabezón et al. (2017) also found substantial variation in daily heat production between sows within the same parity. In any case, the correlations observed between changes in BT or BW and NE loss (r ≤ 0.55) may suggest that both changes in BT and BW are useful predictors of energy mobilization but the way to utilize them may need to be re-evaluated.

Higher body NE loss was found during the first half of lactation compared to the second half. This is because of the higher difference between ME intake and ME used for maintenance and milk production (Fig. 1, Table 7), and is in agreement with other published results (Rojkittikhun et al., 1993; Gauthier et al., 2019; Tokach et al., 2019). The origin of the tissue mobilized is also different. First, protein accumulated during gestation in the reproductive tract and other internal viscera is quickly mobilized at the beginning of lactation (Kim and Easter, 2001; Theil, 2015; Gauthier et al., 2019). It has been estimated that the regressing uterus released about 14 MJ ME into the endogenous plasma pool during lactation (Feyera and Theil, 2017), contributing to total energy supply with the same efficiency as that from body reserves; the half-life of post-partum uterine involution is 6.2 d (Gauthier et al., 2019). Second, since deposition of adipose tissue in mammals occurs in at least two different anatomic depots, namely around abdominal viscera in the mesentery and omentum, and in a subcutaneous location (Pond, 1992), the way fat is mobilized may be different. Straughen et al. (2013) indicated that both fat depots in humans differ in endocrine function and lipolytic activity. Furthermore, Frayn et al. (2003) indicated, also in humans, that visceral fat, mainly accumulated during gestation, is mobilized faster than subcutaneous fat because intra-abdominal adipocytes have a higher rate of lipolysis when stimulated with a beta-adrenoreceptor agonist. However, Pond (1992) pointed out that the distribution of adipose tissue differs greatly between species and is physiologically adaptive. This author indicated that the relative volume of adiposities in different depots is constant but the relative numbers of such adiposities, and hence the relative mass of the depots, varies greatly between species, and to a lesser extent between individuals of the same species. Compared to humans, pigs probably have proportionately less intra-abdominal adipose tissue, and more subcutaneous depots, but since the larger depots are less metabolically active and less responsive than the smaller ones (Pond, 1992), intra-abdominal fat still may make a key contribution to energy balance in early lactation.

As lactation progresses, serum NEFA and glycerol concentrations increase (Fig. 2) while energy mobilization decreases (Fig. 1) and, although blood levels of glycerol and NEFA are respective indicators of body fatness and fat metabolization (Revell et al., 1998), they were not correlated (r < 0.17) with either calculated body energy or lipid loss during lactation. Frayn et al. (2003) indicate than visceral adipose tissue provides little NEFA and no glycerol to the systemic circulation and that the specific contribution to NEFA delivery to the liver from visceral depots is small relative to the contribution of subcutaneous fat. In fact, Despres and Lemieux (2006) indicate that, in humans, visceral fat goes directly to the liver via the portal vein and, consequently, does not necessarily contribute to increase plasma NEFA concentration. As those visceral fat depots are mobilized quickly, this would justify part of the discrepancy found between NEFA and glycerol serum concentrations and energy mobilization at early lactation. The increase in urea serum concentration and in the ratio urea:creatinine (Fig. 2) would be a direct consequence of the increase of feed intake through lactation.

Effect of level of energy mobilization

The range of NE loss is broad and has a high standard deviation (Table 3). This large variability may be partially attributed to calculation errors but must be mainly due to other factors related to the sow or the environmental conditions. Grandinson et al. (2005) reported heritability coefficients (h ²) for body weight loss and back fat loss in lactating cows of 0.20 and 0.10, respectively. Dairy cows with high genetic merit for milk production mobilize more body reserves than cows of low genetic merit (Pryce et al., 2001) and there appears considerable variation between selected dairy cows for releasing energy fuels from adipose tissue stores (Hammon et al., 2009). These results for cows suggest some genetic capacity or animal predisposition for tissue and energy mobilization in lactation, and perhaps this could be extended to sows. Bergsma et al. (2008) found a high h ² in sows for body weight and body composition at the beginning of lactation (0.4 to 0.5), but mobilization of body tissue during lactation was less heritable (<0.1).

The way of distributing sows between their levels of energy mobilization (Table 2) may be criticized. The method employed is empirical and factorial. The main concerns are the assumption of constant values and the means of deciding the composition of mobilized tissue and consequently the origin of body energy losses. Whilst acknowledging that the composition of mobilized tissues varies with several factors during the sow's lactation, NRC (2012) assume constant values and even more recent models fail to take this into account (Gauthier et al., 2019). The proportions of fat and protein chosen (720 and 280 g/kg, respectively) are the mean of results presented here (Table 3) and agree well with data reported in several studies (e.g. Everts and Dekker, 1994b; Revell et al., 1998; Sauber et al., 1998; Kim and Easter, 2001; Bergsma et al., 2009; Strathe et al., 2017). However, there are other approaches to distributing sows according to their energy or tissue mobilization. Weber et al. (2013), studying fat mobilization in cows around calving, distributed the animals between high and low mobilizers depending on their liver fat concentrations post-partum measured by liver biopsy. Mitchell et al. (2001) used magnetic resonance imaging and Arthur et al. (2011) X-ray-computer tomography to estimate the body composition of growing pigs. Recently, Pedersen et al. (2019 and 2020) used deuterated water (D₂O) to estimate sow's body composition around farrowing and Johnson et al. (2022) used indirect calorimetry to determine total metabolic heat production in lactating sows. A sequential slaughtering experiment would also give an accurate picture (Everts and Dekker, 1994a). However, these methodologies are expensive, all have their own limitations, and most of them would be difficult to perform under commercial conditions.

The results appear generally sound and in agreement with Strathe et al., (2017) when comparing gilts and multiparous sows (Tables 5 and 6), and as gilts consume less ME than multiparous sows, they made greater metabolic effort to achieve similar total litter gains. Consequently gilts lost more body weight during lactation, i.e. more lipid and protein. However, mean NE loss for the gilts did not differ from that for multiparous sows. The composition of the tissue loss may be different. Mullan et al. (1989) suggest that the composition of mobilized tissue during lactation changes with age of the sow, and it appears that the composition of tissue losses may play a central role. The different evolution of the serum NEFA and glycerol concentrations through lactation between gilts and multiparous sows (Fig. 2) may support this idea. Furthermore, Pluske et al. (1995) demonstrate that increasing the energy intake of gilts above ad libitum feeding via a gastric cannula did not stimulate milk production and suggest that, unlike the sows, gilts are likely to partition extra energy into body growth rather than milk production. The lower creatinine level and the higher urea:creatinine ratio found in the serum of gilts compared to multiparous sows (Fig. 2) may indicate a lower rate of protein and lean tissue mobilization.

In agreement with some authors (e.g. Rojkittikhun et al., 1993; Everts and Dekker, 1994b; Revell et al., 1998; Kim and Easter, 2001; Bergsma et al., 2009), high mobilizing sows had a lower ME intake (Table 6) than low mobilizers. As a consequence, the high mobilizers lost more body weight, BT, lipid and protein. In cows, Weber et al. (2013) also found that the decrease in body weight post-partum was greatest in high fat-mobilizers, but the decrease in back fat thickness was greatest in medium fat-mobilizers.

Finally, since high mobilizing sows, compared to low mobilizers, used a greater amount of ME for milk production (Table 6), which is in agreement with a higher litter gain (Table 5), the results suggest that mobilizing up to a certain amount of body energy improves litter gain without seriously damaging the mother. Besides, it may also be of interest to identify the sows with positive energy balance, which might result from low milk production or a large appetite (Gauthier et al., 2019). However, such results may be different depending on litter size and body composition of the sow.

Conclusion

Reliable values of NE loss during lactation may be obtained by difference after curvilinear fitting daily feed intake and litter growth data. The results showed that in controlled commercial conditions, sows that mobilize more tissue and energy up to a certain level have a lower feed intake, but weaned more piglets and heavier litters than the other sows. Net energy loss was higher over the first half of lactation than thereafter. More research is required to assess the total amount and a safe threshold of energy mobilized by the lactating sow and the relative contribution of lean and fat tissue mobilized. A better understanding of the changes in live weight or back fat thickness would be helpful.