Sow behavior on the day of farrowing: The main determinant of early piglet growth among maternal ability traits

Sow behavior on the day of farrowing: The main determinant of early piglet growth among maternal ability traits | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Sow behavior on the day of farrowing: The main determinant of early piglet growth among maternal ability traits Océane Girardie, Denis Laloë, Mathieu Bonneau, Yvon Billon, Jean Bailly, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3836704/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Large White and Meishan sows differ in maternal ability and early piglet growth. We investigated the relationships between piglet growth over three periods after birth (D0-D1, D1-D3 and D3-D7; D0 starting at the onset of farrowing) and 101 maternal traits, grouped into 11 blocks according to the biological function they describe. Within and between breed variation was exploited to account for a maximum of variability. The objective was to quantify the contribution of maternal traits to early piglet growth. The relationships were analyzed with multiblock and triadic partial analyses. Several behavioral traits (standing activity, reactivity, postural) and functional traits (body reserves, teat quality) at farrowing had substantial contributions to piglet growth from D0 to D7. Sow aggressiveness towards piglets and time spent standing at D0 were unfavorably correlated to D1-D3 growth. Time spent lying with udder exposed at D0 was favorably correlated to D1-D3 growth. The farrowing duration was negatively correlated to growth from D0 to D3. Furthermore, D3-D7 growth was positively correlated to feed intake in the same period. Several behavior traits and some functional traits play part in early piglet growth, with a greater contribution of sow behavior in the critical period around farrowing than in later days. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction The early growth of the newborn piglet may have an effect on its survival until weaning. This performance depends on interactions with littermates and the dam. Compared to its littermates, a piglet that is heavier at birth grows faster on average 1 (a 22% difference in average daily gain the first week of lactation) 2 , 3 and is heavier at weaning 3 – 7 , in relation to a more efficient suckling activity 8 . However, this general trend is not confirmed for all piglets. In Huting et al. 9 , 51.9% of piglets born heavy fell into the lower weaning weight category. Although growth in the first week after birth can predict growth up until weaning, very few studies have addressed this association 10 . The risk of delayed growth in early lactation for weaning performance remained a secondary issue to the overriding problem of piglet mortality. The measurement of early growth and use for selective breeding could be a mean to indirectly improve piglet survival in pig maternal lines. Early growth is partly determined by the piglet itself through intrinsic factors including physiology (body weight), behavior and genotype 11 , 12 . But it is the sow, who, through its maternal ability, has the most decisive role on early piglet performance. As a result, most studies on piglet growth are devoted exclusively to maternal factors. Maternal abilities encompass a large set of sow physiological and behavioral traits. Some genetic studies show that maternal effects on piglet performance are large. Maternal effects explain more piglet weight at birth compared to direct effects of the piglet 13 , 14 . The main sow maternal effects are reflected in milk production (ranging from 7 to 10 kg/d) 1,12,15 , which results from feed intake 16 and the use of body reserves 17 . The functionality of teats and their physical characteristics may also influence early growth. They influence milk intake along the udder 18 – 20 . Sow behavior in the period around farrowing (D-3 to D7) also influences early piglet growth. In a study focused on the 24 hours around farrowing, Illmann et al. 21 showed that the number of postural changes at farrowing was positively correlated with piglet growth on the first day after birth. In the same population as in the current study, we showed that early growth (to D7) of piglets from sows that change postural more often to hide the udder on the day of farrowing is lower than that of sows that do not hide the udder 22 . While their growth is on average 250 g/d over lactation, the average weight gain of pure Meishan piglets during the first week after birth was 110 g/d, and that of pure Large White piglets was 160 g/d. Although some previous studies focused on the relationship of certain aspects of maternal behavior and piglet performance, none have accounted for sow functional traits simultaneously. The objective of the current study was to explore the variability in associations between sow maternal ability traits and early piglet growth. We used genetically heterogeneous population consisting of a total of 21 Large-White (LW) sows and 22 Meishan (MS) sows, housed in individual farrowing pens. They produced both purebred and crossbred piglets in their litter since they had been inseminated with mixed semen from the two breeds. We analyzed the relationships between 101 maternal traits measured from entrance into the farrowing unit to 7 days after farrowing, and three piglet growth traits obtained from weighing at several occasions in the 7 days after birth (D0-D1, D1-D3 and D3-D7). Multivariate methods enabled to analyze the variations underlying each trait and the correlations among traits. First, a factor analysis of mixed data (FAMD) was used to describe the structure of the database. Then, a partial least square (PLS) multiblock analysis was run to quantify the effect of each maternal variable on early piglet growth. Finally, partial triadic analyses were used to analyze the evolution of sow behavior traits with time and determine the period(s) in which they have the greatest influence on early piglet growth. Results Description of the data base The breed differences in maternal ability traits are reported in Additional File 1. At farrowing, LW sows were significantly older (433 days vs. 391 days), heavier (240 kg vs. 167 kg) and had a larger amount of protein reserves than MS sows. They gave birth to larger litters (15.1 vs. 12.5) and piglets that grew up faster after D1 than those born from MS sows (ADG of 160 g vs. 95 g from D1 to D3, and 224 g vs. 143 g from D3 to D7). On the other hand, MS sows were characterized by a larger amount of fat reserves (backfat depth: 49 mm vs. 25 mm; fat content: 101 vs. 85 kg). They had a higher number of teats (total and functional) than LW sows. The two breeds also differed in behavior. The LW sows vocalized more than MS sows in all situations, were more aggressive towards humans and piglets, and rested less during farrowing (131 vs. 287 postural changes). The results of the FAMD applied to the 101 variables are presented in Fig. 1 . The FAMD exhibits a clear separation between the two breeds on the first axis (21.5% of data variation explained (inertia), while the second axis explains only 7.0% of data variation). For an overview of the range of associations between variables and early piglet growth that could be detected in a commercial population, we considered that it was a priority to analyze the associations between the multitude of variables that describe maternal ability and piglet growth, independent of the sow breed factor. The correction for breed effect was separately applied to each of the 101 variables using linear models. Residuals were used as variables of interest in the following analyses. Relative influence of the blocks of maternal ability traits in the prediction of early piglet growth according to the MBPLS analysis The relationship between the 101 maternal traits (explanatory variables X ) and the three average daily piglet weight gains (variable to be explained Y ) were evaluated on the basis of the multiblock analysis. The first three dimensions of the multiblock analysis accounted for 68.2% of the total inertia in data structure (42.9%, 13.2% and 12.1%, respectively). The three ADG were lowly correlated with each other (0.11 to 0.23). The Block Importance (BlockImp) that makes it possible to observe the importance of each of the 11 blocks ( X ) to explain the three ADG ( Y ) is presented in Fig. 2 . Given this statistic, only the block considering sow activity while standing on D0 was significantly correlated with the global ADG (BlockImp X7 = 14.36% [10.43; 24.94] 95% ). Even if their CI included the threshold value of 1/11, four other blocks showed an average BlockImp index value greater than 1/11, which underlies a substantial contribution to early piglet growth. Those were blocks describing farrowing reactivity (BlockImp X5 = 12.08% [3.31; 19.34] 95% ), body reserves (BlockImp X2 = 10.34% [4.20; 17.88] 95% ), postural activity on D0 (BlockImp X10 = 9.87% [2.45; 15.43] 95% ), and teat quality (BlockImp X3 = 9.46% [4.57; 12.76] 95% ). The importance index (VarImp) makes it possible to evaluate the importance of each of the 101 variables within the blocks on ADG for the three periods studied together. The VarImp index of the 33 maternal traits with the most significant importance over the three ADG periods (VarImp > 1/101%) are presented in Fig. 3 . These 33 maternal traits explain 85% of the variation in ADG in the three periods (D0-D1, D1-D3 and D3-D7). Of these 33 variables, three variables in blocks X 7 and X 1 had a significant effect on ADG in early lactation (D0 to D7): time spent doing something other than eating and drinking when the sow is standing on D0 (VarImp otherD0 = 6.76% [1.58; 13.4] 95% , X 7 ); time spent eating on D0 (VarImp eatD0 = 7.50% [1.87; 14.8] 95% , X 7 ); and farrowing duration (VarImp FarrowingDuration = 3.77 [1.88; 7.40] 95% , X 1 ). These three maternal traits explain 18.03% of ADG in the three periods. Additional maternal traits in blocks X 5 , X 2 and X 10 , showed an important influence on ADG in the three periods but were associated with wide confidence intervals: aggressiveness towards piglets (VarImp AggressivePiglets = 10.13 [-0.45; 19.94] 95% , X 5 ) and aggressiveness towards humans (VarImp AggressiveHuman = 4.23 [-12.35; 8.26] 95% , X 5 ), the amount of body protein (VarImp Proteins = 5.04 [-0.03; 9.94] 95% , X 2 ), sow body weight (VarImp SowWeight = 3.93 [0.54; 7.73] 95% , X 2 ), and the time spent standing on D0 (VarImp STD0 = 3.92 [0.55, 7.63] 95% , X 10 ). These five maternal traits explained 27.25% of ADG in the three periods. The graphical representation of the relationship between sow traits and ADG considering the first three axes of the PLS multiblock analysis is given in Fig. 4 . This figure shows which variables are associated with ADG 0 − 1 , ADG 1 − 3 and ADG 3 − 7 . ADG 0 − 1 and ADG 1 − 3 were in the opposite direction of ADG 3 − 7 on axis 2, and ADG 0 − 1 and ADG 1 − 3 were in the opposite direction to each other on axis 3. Axes 2 and 3 explained 24% of the variance in the Y blocks and 13.3% of the variance in the X blocks. The number of functional teats at D7 ( X 3 ), time spent sitting in the days after farrowing ( X 11 ), as well as the total number of postural changes before farrowing ( X 9 ), were positively correlated with ADG 0 − 1 . Conversely, the time spent doing something other than drinking and eating while standing at D0 ( X 7 ), farrowing duration ( X 1 ) and aggressiveness towards piglets at D0 ( X 5 ) were negatively correlated with ADG 0 − 1 . ADG 1 − 3 was positively correlated with the time spent lying with udder exposed at D0 ( X 10 ), with aggressiveness towards humans on D0 ( X 5 ) and with protein reserves ( X 2 ). However, it was negatively correlated with the time spent standing before farrowing ( X 9 ), farrowing duration ( X 1 ) and aggressiveness towards piglets on D0 ( X 5 ). A positive association was revealed between ADG 3 − 7 and farrowing duration ( X 1 ) and the time spent eating at D0 ( X 7 ). A negative association was found between ADG 3 − 7 and the total number of postural changes before parturition ( X 9 ). These results were confirmed by the multiblock PLS regression coefficients obtained after bootstrapping, with the exception of ADG 3 − 7 , which showed a positive correlation with farrowing duration (X1) and the intercept of the ingestion curve after farrowing (X8), and a negative correlation with aggressiveness towards human at D0 (X5) and time spent drinking at D0 (X7). Temporal variation in the relationships between sow behavior and litter growth: PTA analysis In summary, on the basis of the multiblock analysis, sow behaviors on the day of farrowing and during the first day of lactation appeared to be more highly correlated with ADG on the three periods than other maternal traits. The blocks “standing activity” and “postural activity” were built from the longitudinal analysis of video images enabled from the use of convolutional neural networks (CNN). A Partial Triadic Analysis (PTA) was carried out to consider the temporal effect of these two blocks on ADG values. Thus, it was possible to estimate the correlations of postural activity traits and standing activity traits with ADG for the three periods D0-D1, D1-D3 and D3-D7. Referring to the vector correlation matrix, the structures of the three period tables according to postural activity changed with time. The correlations of the D0-D1 table were 0.59 with the D1-D3 table and 0.51 with the D3-D7 table. The three tables contributed to the definition of the compromise, with a participation between 0.54 to 0.61 αk. The D0-D1 table contributed less to the construction of the compromise table (αk: 0.54 and Cos²: 0.83) than the two other tables. The D1-D3 table contributed more than the others (αk: 0.61 and Cos²: 0.92). In the compromise table, the first axis explained 48% of the variation and the second axis 28% (Fig. 5 A). On the factorial map of projection according to axes 1–2, axis 1 was highly defined by time spent lying laterally with udder exposed (LLU) and axis 2 by time spent sitting (SI) and time spent sternal lying (SL) in the opposite direction. Referring to the compromise table, ADG 0 − 1 was mainly correlated with the number of postural changes (PCAll and PCStopNurse, Fig. 5 A). ADG 1 − 3 and ADG 3 − 7 were weakly explained by postural activity. None of the data structure developed per period (nb. of postural changes and postural activity from one of the three periods analyzed jointly) deviated from the compromise (Fig. 5 B, D and F). The association between ADG and sow restlessness was low but more pronounced in the period D0-D1 than in the following periods. The ADG was lowly correlated with sow activity in the D1-D3 period. A low but substantial association between ADG and time spent lying laterally (LL) was observed on the D3-D7 period and not in the two previous periods (Fig. 5 C, E and G). Referring to the vector correlation matrix, the structures of the three periodic tables changed over time as a function of standing activity. The correlations with the D0-D1 table decreased from 0.50 (D1-D3) to 0.25 (D3-D7). The compromise was defined with a weighted average of the three tables. The participation of each table in the calculation of the compromise ranged from 0.51 to 0.65 αk. Table D1-D3 had a higher contribution (αk: 0.65 and Cos²: 0.90) to the calculation of the compromise than the other two tables (αk: 0.51 and 0.57; Cos²: 0.74). In the compromise table, the first two axes explained 86% of the variation (axis 1: 55%; axis 2: 31%, Fig. 6 A). On the factorial map of the projection along axes 1–2, axis 1 was defined by feed intake and time spent drinking while standing in opposite directions, and axis 2 was defined by time spent doing something else while standing. On the compromise, ADG 0-1 was mainly correlated with time spent eating (Fig. 6 A). ADG 1-3 and ADG 3-7 were weakly explained by the standing activity. Food intake and standing activity (analyzed jointly in one period) did not significantly deviate from the compromise (Fig. 6 B, D, and F). The association between ADG and time spent eating (and feed intake as well) was low but more pronounced in the period D0-D1 than in the following periods. ADG 3-7 was negatively correlated with the time spent doing something other than eating or drinking while standing in the period D3-D7 (Fig. 6 C, E and G). The partial triadic analysis and the multiblock analysis indicated a stronger relationship of growth from D0 to D1 with sow behavior on farrowing than on other maternal traits. Discussion The use of breeds contrasting in maternal ability allows to access a large variation in maternal traits and in their relationships with piglet growth 23 , 24 . The design makes it possible to discover the maximum range of variation observable in any pig population, on these traits. The detection of maternal effects was maximized by construction, with an experimental design with both purebred and crossbred piglets in the litters. The two breeds drastically differ in metabolism and in the ability to invest in piglet production as well 25 . The LW sows have a greater number of functional teats 1 and a greater capacity to use fat reserves in early lactation 25 . The LW sows outperform MS sows in investment capacity due to greater body size and feed intake capacity. Selective breeding has also led LW sows to outperform MS sows in litter size 27 . Piglets from LW sows are also heavier than piglets from MS sows. Conversely, the two breeds do not differ in their general behavior in the days after farrowing, as described in Girardie et al. 22 . The same range of variation was observed for postural and standing activity. Consequently, the adjustment of data for sow breed did not restrict the range of behavioral variation we were able to exploit. We found breed differences in behavioral reactivity that are in line with Farmer and Robert 28 who showed that MS sows are less response to piglets than LW sows in most situations. Sow breed explained a significant part of the data variability (21.5%). We explored the range of possible associations between maternal ability traits and mean piglet growth. Adjusting data for this breed effect allowed us to highlight generic associations that should be detectable in many pig maternal populations. For this aim, we used multifactorial analyses, notably the Multiblock Partial Least Square analysis that is robust when considering many traits recorded on a limited number of individuals. Growth during the first days after birth can determine subsequent piglet survival and growth. Indeed, survival of piglets during lactation is correlated with piglet weight gain in the first 48 hours after birth 29 . In addition, piglet survival is lower when colostrum intake is not sufficient 30 . In the current study, weak correlations of 0.11 to 0.23 between average daily weight gains estimated at the three periods (D0-D1, D1-D3, and D3-D7) were found, thus constituting lowly dependent variables with possibly different determinism. The regression coefficients obtained with the multiblock analysis showed that each mean daily weight gain was strongly correlated with a different set of maternal traits. Sow restlessness before farrowing influence piglet growth after birth, differently at two growth periods. ADG 0 − 1 was favorably correlated to pre-farrowing sow restlessness and ADG 3 − 7 was unfavorably correlated to this behavior. These associations between traits measured at different times are due to indirect effects. In particular, higher pre-farrowing restlessness can relate to the nest building activity 31 , a behavior that is favorable to newborn piglets’ growth 32 as it induces the release of oxytocin, the hormone of lactation. Early piglet growth is influenced by diverse maternal factors. The study encompassed 3 blocks of physiological data and 8 blocks of behavioral data. Five blocks of maternal traits ranging from sow behavior to body composition at farrowing influenced early piglet growth: standing activity at D0 (14.4% of the three mean average daily weight gain explained), responsiveness to piglets and humans at farrowing (12.1%), body reserves at maternity entrance (10.3%), postural at D0 (9.9%), and teat quality (9.5%). Following are some elements of discussion on the main results highlighted by these multifactorial analyses. As is well known, piglet growth relies on sow milk production, which variation is generally dependent on differences in body protein use and feed intake among sows 33 . In the present study, sows with higher body weight at farrowing entry and, concordantly, more protein reserves had lower piglet growth on the first day after birth than other sows. Consistently, Cools et al. 34 showed that piglet weight gain from D0 to D1 is lower if the sow is heavier at farrowing entrance. Then, sows that spend more time eating on D0 have a higher weight gain of their piglets in the following days. Protein intake from the sow's diet is rapidly used for milk production. 16 Sows that ingest more proteins gain up to 52 g/d more in piglet growth than the other sows 35 . Often, on the day of farrowing, the sow ingests only a very small amount of feed 36 , 37 , so it is important that she quickly resumes feeding activity to stimulate lactation 38 . This is particularly the case for gilts that have not finished growing and that jointly use more energy for their own growth and milk production 39 . Feeding and also watering condition milk production 40 , 41 . A sow that is more passive in the first days after farrowing and does not take in an adequate amount of water produces less milk than other sows. Indeed, water consumption varies between 6 and 14 L/d around farrowing 42 . Teat quality is also a key factor for piglet growth. In our study, piglet weight gain on D1 was favorably correlated to the number of teats still functional at D7. The efficient suckling activity of the piglets promotes the maintenance of teat functioning during lactation. In addition, the use of several teats per piglet boosts milk production 19 , 43 . Our study showed a correlation of 0.55 between the number of functional teats 24 h after the onset of farrowing and at D7. In addition to the main blocks identified, it is worth noting the marked influence of a single variable in the "farrowing performance" block on piglet growth at each of the three periods: the duration of farrowing. The longer the farrowing period is, the lower the average weight gain of piglets from D0 to D3, and the higher the weight gain from D3 to D7 will be. A long farrowing can be synonymous with health problems for the sow, which have eventually more difficulty starting lactation. In addition to litter size being the main determinant of farrowing duration, 44 stress can lead to a longer farrowing and decreased colostrum production 45 . A long farrowing period results in more stillbirths 44 which decreases subsequent competition at the udder. Finally, a long farrowing favors hypoxia, which reduces viability in some piglets 46 , 47 so they take longer to access the udder and ingest less colostrum than their littermates 48 . However in that situation of more critical farrowing, piglets that survive the first days after birth are likely to be more vigorous than those born in other litters 44 . As a consequence, and especially if they are heavier, they can consume more milk and grow faster than those born from sows with easier farrowing 8 . In a more pronounced way than sow physiology, we showed that the behavior of the sow on the day of farrowing played part in early piglet growth. The weight gain of piglets in the first days after birth was lower in sows aggressive towards them (12% of sows in the current study). Primiparous sows, as seen in our study, are usually more aggressive towards their piglets than older sows 49 – 52 . One hypothesis is that piglets raised by an aggressive sow develop a distrustful behavior towards the sow and would be less likely to approach her to suckle and it may affect milk production 19 . As regards to general activity, sows that spend more time standing at D0 have piglets that grow slower than others sows, due to a more limited access to the udder. Piglets that consume less colostrum have lower growth during lactation 53 – 55 . Sows that spend more time standing doing something other than eating and drinking have lower litter growth than other sows. Standing sows use more energy than other posturals, which may have consequences on milk production and subsequently, piglet growth 56 . Standing activity on the day of farrowing may be related to exploration of the environment and newborn piglets 57 . The arrangement of the nest, may have a positive effect on piglet growth as nest-building favors the release of oxytocin 58 . A correlation of 0.30 between nest-building behavior and piglet growth from D0 to D7 was reported in the literature 58 . We showed that sow behavior on the day of farrowing significantly explains piglet growth on the following days. In that case, sow aggressiveness towards piglets and humans and standing activity have a significant influence on piglet average daily gain between D0 and D7. This association is negative with aggressiveness toward piglets. Our study showed that aggressiveness towards piglets affects the growth of piglets that survive to D3. It can be assumed that the bond between the aggressive sow and its piglets is weaker than in a non-aggressive sow, resulting in less efficient nursing activity, and with possible implications for piglet growth. In contrast, sows that are aggressive towards human have piglets that grow faster from D1 to D3. A similar result was established by Marchant Forde 59 from D0 to D7, with a difference of 25 g/day in favor of aggressive sows toward human as compared to non-aggressive sows. To better understand the contribution of sow behavior in the determinism of early piglet growth, partial triadic analysis allows us to assess the importance of associations between the three time periods by comparing projections of the data over a compromise structure of correlations. Although little of the variation in growth was explained by the behavior maternal traits in each time period, this approach confirmed the more pronounced association of sow activity with piglet growth on the first day after birth. This association was more pronounced with the frequency of postural changes. Although the pattern of correlations among behavioral variables remained the same over time, it was less and less correlated to piglet growth. Accordingly, Valros et al. 60 found no association of sow restlessness after D3 with piglet growth in lactation. Conclusion This study depicted the relationships between a large number of maternal traits, and early piglet growth. Piglet growth was related to several maternal traits in three distinct periods in early lactation. Sows more aggressive to piglets or that spent more time standing at D0 had lower piglet mean weight gain than other sows. Conversely, sows that spent more time with udder exposed at D0 had higher weight gain. From D3 to D7, piglet growth was lower in sows that had spent less time drinking and eating at D0 and that were aggressive toward human than in other sows. At D0, certain behavioral features had a higher influence on early piglet growth than other maternal ability traits. Sow behavior can be used to detect litters at risk of delayed growth in early lactation. Material and Method Ethical statement The experimental protocol was designed in compliance with the legislations of the European Union (Directive 86/609/EEC) and France (Decree 2001–464 29/05/01) for the care and use of animals (Agreement For Animal Housing Number C-35-275-32). All experiments were performed in accordance with relevant guidelines and regulations and were approved by the ethical committee of the Midi-Pyrénées Regional Council (authorization MP/01/01/01/11). Reporting in the manuscript follows the ARRIVE guidelines recommendations. Animals and Housing This study is based on a crossbreeding scheme, set up to quantify direct and maternal effects on piglet development during the suckling phase (the present study was carried out on sows in first parity) and before, during the intrauterine phase (e.g., study 61 on the same sows in second parity). The experimental design is described in detail in Girardie et al. 22 . This design included 21 primiparous LW and 22 primiparous MS sows kept in individual farrowing pens at the Le Magneraud INRAE GenESI experimental farm (doi: 10.15454/1.5572415481185847E12). Sows were inseminated with a mix of semen of MS and LW boars, so that each sow produced both purebred and crossbred piglets. As a consequence, four piglet genetic types were produced (dam/sire): LW purebred (LW/LW), LW crossbred (LW/MS), MS purebred (MS/MS) and MS crossbred (MS/LW). Farrowing was not induced. To assess the sow’s ability to raise her progeny, crossfostering was not allowed. Intervention from the caretakers hired by the experimental unit was limited to unblocking piglets from foetal membranes at birth and saving piglets trapped under the sow. Piglet measurements Each piglet was weighed immediately after birth (D0), 24 h after birth (D1), and at 3 days (D3) and 7 days (D7) after birth. Weighing was carried out in the central corridor of the farrowing unit. The average daily gain (ADG) on D0 to D1, D1 to D3 and D3 to D7 were calculated for each piglet and averaged per sow to obtain a piglet mean average daily gain for each litter on D0-D1 (ADG 0-1 ), D1-D3 (ADG 1-3 ) and D3-D7 (ADG 3-7 ). Sow measurements The behavioral and physiological characteristics of each sow were established on the basis of 101 variables recorded or calculated on each sow. Farrowing performance and environment The litter size, the number of piglets born alive, the age of the sow at farrowing (in days), the % of MS piglets in the litter ((number of MS piglets/litter size) * 100) and the farrowing duration (in minutes) were recorded for each sow. Farrowing duration was defined as the interval between birth of the first piglet and the last piglet in the litter (min = 30 min and max = 390). An environmental variable, the pen, was recorded:, this variable is divided into four categorical variables (A, B, C and D) 22 according to its position in the maternity room. We designated pen A as the pen that was the nearest to the weighing area in the central corridor and D as the pen that was the furthest from the weighing area. Body reserves When entering the maternity unit, the sow was weighed (weight in kg) and its back fat was measured by ultrasound on six points on the back: left and right kidney, back and shoulder. The back fat depth was then obtained as the average of the six measurements. The composition of sows in terms of lipids, proteins and energy was calculated using the equation proposed by Dourmad et al. 62 . Feed intake Sows were fed twice daily, at 8 a.m. and 4 p.m. with a feed of 0.7 kg/L density. The volume (V) of feed intake was measured by subtracting the volume of refusals from the given amount. The daily feed intake in kg was calculated as V*0.7. A random regression was then applied to these longitudinal data per period, smoothed using the Nadaraya-Watson estimator in order to summarize the dynamic of the feed intake for each individual into two variables per period (the intercept and the slope). Teat quality Teat qualification (length) was noted as little, medium, large or irregular. The number of teats and their functionality were recorded at 24 h and 7 days after farrowing. The average interval between teats was measured (cm) and information on the regularity of this interval was noted (regular, irregular). A qualification of average teat diameter was also reported (0.5 to 1 cm, 1 to 1.5 cm or 1.5 to 2 cm). Behavior A 2D camera was fixed above each pen to film the sow 24 h a day. The video recording started 3 days before farrowing (D-3) and stopped 7 days after farrowing (at D7 of lactation) for all sows. Sow behavior was extracted from the video recording using convolution neural networks 22 . The automatically registered behaviors were (i) postural: standing (ST), sitting (SI), sternal lying (SL), lateral lying (LL) and lateral lying with udder exposed (LLU); (ii) standing activity: eating, drinking and doing something else (exploring or rooting). Other variables describing sow behavior were obtained from notations on the farm. Behavior at farrowing entrance The difficulty to get out of the trailer indicated the ease at handling and was noted on a scale from -1 to +1 (-1 = difficulty to get out, 0 = easy, and +1 = very easy to get out). The adaption to the farrowing pen was noted by observing the ease to enter the farrowing pen on a scale from -1 to +1 (1: enter rapidly; 0 and -1: force to enter), and sow vocalizations (0 = no vocalization and 1 = > =1 vocalizations) and sow postural (lateral lying, sitting or standing) 30 min and 1 h after entrance in the farrowing unit. Habituation to humans was also observed with a test inspired by Grandisson et al. 63 This test consists of observing the reaction of the sow when a human is at a distance, outside the pen and in contact with the hand. Different information was recorded: behavior of the sow (positive, negative or in continuity with behavior before the test starts), vocalization (0 = no vocalization; 1 = > =1 vocalization), initial postural when the test starts (sitting, lateral lying, sternal lying and standing), and the index of postural change described in Grandisson et al. 63 . Reactivity at farrowing During the farrowing process, caretakers regularly visited each sow to collect newborn piglets, dry them and weigh them. Restlessness (0/1) and aggression towards piglets (0/1) and humans (0/1) were noted. Postural activity and standing activity The time spent in each postural and in each activity while standing was calculated for three periods: before farrowing, on the day of farrowing and after farrowing. This compositional data was transformed with Centered Log Ratio (CLR) 64 before analysis. Two specific amounts of postural changes were also calculated from the behavior prediction database: an average daily number of postural changes per period was calculated as the total number of postural changes divided by the number of days in the period (PCAll). The same calculation was applied for the number of postural changes hiding the udder (PCStopNurse) 22 . Statistics Data exploration Means or proportions per breed were calculated for each variable studied. To evaluate if there was a significant difference between breed, Student's t tests were performed on quantitative variables and chi-square tests on qualitative variables. In order to describe the overall structuration of the data, we used a Factorial Analysis of Mixed Data (FAMD). FAMD is a factorial analysis that can handle a mix of continuous and categorical variables 65 . Categorical variables are transformed into 0/1 variables. Note that FAMD is similar to PCA when there are only continuous variables and to MCA when there are only categorical variables. For more detail, see Husson et al. 66 . All the variables were corrected for breed effect with a linear model. The residuals of this model were used in the following two analyses. They were not expressed in the same unit of measurement; they were column centered and scaled to unit variance beforehand. Multiblock analysis The multiblock Partial Least Squares (mbPLS) 67 was used to explore the potential drivers that could influence/explain early piglet growth. It is an extension of the PLS method to the multiblock case, i.e., where a dataset Y is to be explained or predicted by a dataset X that is organized into K blocks: X=(X1,…,Xk). In this study, we studied the link between ADG of three different periods ( Y , matrix , where is the number of sows) and 101 maternal components. The latter were grouped into 11 blocks that included farrowing performance and environment ( X 1 , eight variables), body reserves ( X 2 , five variables), teat quality ( X 3 , 15 variables), sow behavior at entrance in maternity room ( X 4 , 36 variables), farrowing reactivity ( X 5 , three variables), postural activity before farrowing ( X 6 , six variables), postural activity at farrowing ( X 7 , six variables), postural activity after farrowing ( X 8 , six variables), standing activity before farrowing ( X 9 , four variables), standing activity at farrowing ( X 10 , four variables) and standing activity after farrowing ( X 11 , four variables). The variables included in each block were those presented in the Measurement section. The multiblock analysis is a latent variable technique. The whole procedure is detailed in Bougeard et al. 67 . Briefly, it consists of three steps (Figure 7). First, each of the (K+1) datasets, i.e., Y and (X1,…Xk), are summarized by the latent variables u and (t1,…tk), respectively. In a second step, a global latent variable t is derived as a weighted sum of the tk, so that the squared covariance of t and u is maximized. Finally, the method provides interpretation tools such as the Block Importance that is equal to a2k, and the Variable Importance, equal to the product of the Block Importance and the weight of the variable in the latent variable. Since both Block Importance and Variable Importance sum to 1, these values can be interpreted as percentages. Ultimately, the significance of Block Importance and Variable Importance can be appreciated via a bootstrap procedure (999 samples). An explicative block was significantly important for ADG if its 95% confidence interval did not include the threshold value 1/11. In addition, an explicative variable was significantly important for ADG if its 95% confidence interval did not include the threshold value 1/101. Partial Triadic Analysis To better comprehend the evolution of the relationships between variables over time, we carried out a Partial Triadic Analysis (PTA) 69,70 . PTA is the analysis of a three-dimensional matrix (sows × variables × periods, Figure 8). In this study, three periods of time (= three tables) were considered on the same animals and variables. PTA consists of three steps; 69,70 The interstructure (relationships among tables), with the so-called RV coefficient, which measures the similarity among tables. The RV coefficient is an extension of the correlation coefficient. The RV coefficient, located between -1 and 1, has the same interpretation as a correlation coefficient. The compromise, or consensus table, that is a weighted average of the tables. This table made it possible to observe the average relationships between variables. The intrastructure, which consists in studying the specificity of each table compared to the compromise table. It is obtained by the projection of each individual table (rows and columns) onto the compromise. PTA was run separately for standing activity and for postural activity between D0 and D7. For each PTA, ADG 0-1 , ADG 1-3 and ADG 3-7 were added as supplementary variables to evaluate the link between standing and postural activity and piglet average daily gain. Multivariate and statistical analyses were performed using the ade4 package 71 from R 72 . Declarations Additional Information The author(s) declare no competing interests. Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request. The system used during the current study are available from the corresponding author upon reasonable request. Author contributions LC conceived the project. LC, YB, and JB carried out the experiment. MB supervised the automated video analysis of sow behavior. OG, LC, ID, and DL participated in the data analysis. OG, LC, ID, DL contributed to writing the manuscript. All authors contributed to the article and approved the submitted version. References Skok, J., Brus, M. & Škorjanc, D. Growth of piglets in relation to milk intake and anatomical location of mammary glands. Acta Agriculturae Scandinavica, Section A — Animal Science 57 , 129–135 (2007). Ferrari, C. V. et al. Effect of birth weight and colostrum intake on mortality and performance of piglets after cross-fostering in sows of different parities. Preventive Veterinary Medicine 114 , 259–266 (2014). Romero, M. et al. Short- and Long-Term Effects of Birth Weight and Neonatal Care in Pigs. Animals (Basel) 12 , 2936 (2022). Devillers, N., Farmer, C., Dividich, J. L. & Prunier, A. Variability of colostrum yield and colostrum intake in pigs. animal 1 , 1033–1041 (2007). Devillers, N., Dividich, J. L. & Prunier, A. Influence of colostrum intake on piglet survival and immunity. animal 5 , 1605–1612 (2011). Quiniou, N., Dagorn, J. & Gaudré, D. Variation of piglets’ birth weight and consequences on subsequent performance. Livestock Production Science 78 , 63–70 (2002). Högberg, A. & Rydhmer, L. A Genetic Study of Piglet Growth and Survival. Acta Agriculturae Scandinavica, Section A — Animal Science 50 , 300–303 (2000). Hemsworth, P. H., Winfield, C. G. & Mullaney, P. D. Within-litter variation in the performance of piglets to three weeks of age. Animal Science 22 , 351–357 (1976). Huting, A. M. S., Sakkas, P., Wellock, I., Almond, K. & Kyriazakis, I. Once small always small? To what extent morphometric characteristics and post-weaning starter regime affect pig lifetime growth performance. Porcine Health Management 4 , 21 (2018). Fraser, D. & Thompson, B. K. Variation in piglet weights: relationship to suckling behavior, parity number and farrowing crate design. Can. J. Anim. Sci. 66 , 31–46 (1986). Rydhmer, L. Genetics of sow reproduction, including puberty, oestrus, pregnancy, farrowing and lactation. Livestock Production Science 66 , 1–12 (2000). King, R. H., Mullan, B. P., Dunshea, F. R. & Dove, H. The influence of piglet body weight on milk production of sows. Livestock Production Science 47 , 169–174 (1997). Banville, M., Riquet, J., Bahon, D., Sourdioux, M. & Canario, L. Genetic parameters for litter size, piglet growth and sow’s early growth and body composition in the Chinese-European line Tai Zumu. Journal of Animal Breeding and Genetics 132 , (2014). Solanes, F. X. et al. Direct and maternal influences on the early growth, fattening performance, and carcass traits of pigs. Livestock Production Science 88 , 199–212 (2004). Hojgaard, C. K., Bruun, T. S. & Theil, P. K. Impact of milk and nutrient intake of piglets and sow milk composition on piglet growth and body composition at weaning. J Anim Sci 98 , 1–12 (2020). Hurley, W. L. Mammary gland growth in the lactating sow. Livestock Production Science 70 , 149–157 (2001). Lundgren, H. et al. Genetic parameters for feed intake, litter weight, body condition and rebreeding success in primiparous Norwegian Landrace Sows. Animal : an international journal of animal bioscience 8 , 1–10 (2013). Balzani, A., Cordell, H. J. & Edwards, S. A. Relationship of sow udder morphology with piglet suckling behavior and teat access. Theriogenology 86 , 1913–1920 (2016). Devillers, N., Giraud, D. & Farmer, C. Neonatal piglets are able to differentiate more productive from less productive teats. Applied Animal Behaviour Science 174 , 24–31 (2016). Vasdal, G. & Andersen, I. L. A note on teat accessibility and sow parity — consequences for newborn piglets. Livestock Science 146 , 91–94 (2012). Illmann, G., Chaloupková, H. & Neuhauserová, K. Effect of pre- and post-partum sow activity on maternal behaviour and piglet weight gain 24h after birth. Appli Anim Behav Sci 163 , 80–88 (2015). Girardie, O. et al. Analysis of image-based sow activity patterns reveals several associations with piglet survival and early growth. Front. Vet. Sci. 9 , (2023). Miles, J. R. et al. Contributions of the maternal uterine environment and piglet genotype on weaning survivability potential: II. Piglet growth, lactation performance, milk composition, and piglet blood profiles during lactation following reciprocal embryo transfers between Meishan and White crossbred gilts. J Anim Sci 93 , 1555–1564 (2015). Canario, L., Billon, Y. Y., Mormède, P., Poirel, D. & Moigneau, C. Temperament, adaptation and maternal abilities of Meishan and Large White sows kept in a loosehousing system during lactation. in (2009). Farmer, C., Palin, M.-F., Sorensen, M. & Robert, S. Lactational performance, nursing and maternal behavior of Upton-Meishan and Large White sows. Canadian Journal of Animal Science 81 , 487–493 (2001). Sinclair, A. G., Edwards, S. A., Hoste, S. & McCartney, A. Evaluation of the influence of maternal and piglet breed differences on behaviour and production of Meishan synthetic and European White breeds during lactation. Anim. Sci. 66 , 423–430 (1998). Canario, L., Moigneau, C., Lagant, H., Billon, Y. & Bidanel, J. P. Comparaison des performances de reproduction et des aptitudes maternelles de truies Meishan et Large White élevées en enclos individuels de la mise bas au sevrage. in vol. 40 137–140 (2008). Farmer and S. Robert, C. Hormonal, behavioural and performance characteristics of Meishan sows during pregnancy and lactation. Can. J. Anim. Sci. 83 , 1–12 (2003). Craig, A., Gordon, A. & Magowan, E. Understanding the drivers of improved pig weaning weight by investigation of colostrum intake, sow lactation feed intake, or lactation diet specification1. Journal of Animal Science 95 , 4499–4509 (2017). Dividich, J. L., Charneca, R. & Thomas, F. Relationship between birth order, birth weight, colostrum intake, acquisition of passive immunity and pre-weaning mortality of piglets. Spanish Journal of Agricultural Research 15 , e0603–e0603 (2017). Ocepek, M., Newberry, R. C. & Andersen, I. L. Trade-offs between litter size and offspring fitness in domestic pigs subjected to different genetic selection pressures. Appli Anim Behav Sci 193 , 7–14 (2017). Cronin, G. M. & Smith, J. A. Effects of accommodation type and straw bedding around parturition and during lactation on the behaviour of primiparous sows and survival and growth of piglets to weaning. Applied Animal Behaviour Science 33 , 191–208 (1992). Kim, J. S., Yang, X., Pangeni, D. & Baidoo, S. K. Relationship between backfat thickness of sows during late gestation and reproductive efficiency at different parities. Acta Agriculturae Scandinavica, Section A — Animal Science 65 , 1–8 (2015). Cools, A. et al. Ad libitum feeding during the peripartal period affects body condition, reproduction results and metabolism of sows. Animal Reproduction Science 145 , 130–140 (2014). Tummaruk, P., Sumransap, P. & Jiebna, N. Fat and whey supplementation influence milk composition, backfat loss, and reproductive performance in lactating sows. Trop Anim Health Prod 46 , 753–758 (2014). Genest, M. & D’Allaire, S. Feeding strategies during the lactation period for first-parity sows. Can. J. Anim. Sci. 75 , 461–467 (1995). Martí, L., Latorre, M. Á. & Álvarez-Rodríguez, J. Does Ad Libitum Feeding during the Peri-Partum Improve the Sow Feed Intake and Performances? Animals 9 , 1078 (2019). Farmer, C. & Edwards, S. A. Review: Improving the performance of neonatal piglets. animal 16 , 100350 (2022). Rauw, W. M. et al. Behavioural differences in non-reproductive adult females in a long-term selection experiment for litter size in mice. Applied Animal Behaviour Science 66 , 249–262 (2000). Strathe, A. V., Bruun, T. S. & Hansen, C. F. Sows with high milk production had both a high feed intake and high body mobilization. animal 11 , 1913–1921 (2017). Peng, J. J., Somes, S. A. & Rozeboom, D. W. Effect of system of feeding and watering on performance of lactating sows1. Journal of Animal Science 85 , 853–860 (2007). Fraser, D. & Phillips, P. A. Lethargy and low water intake by sows during early lactation: A cause of low piglet weight gains and survival? Appli Anim Behav Sci 24 , 13–22 (1989). Jensen, P., Stangel, G. & Algers, B. Nursing and suckling behaviour of semi-naturally kept pigs during the first 10 days postpartum. Applied Animal Behaviour Science 31 , 195–209 (1991). Canario, L. et al. Between-breed variability of stillbirth and its relationship with sow and piglet characteristics. Journal of Animal Science 84 , 3185–3196 (2006). Oliviero, C., Heinonen, M., Valros, A., Hälli, O. & Peltoniemi, O. A. T. Effect of the environment on the physiology of the sow during late pregnancy, farrowing and early lactation. Animal Reproduction Science 105 , 365–377 (2008). Islas-Fabila, P. et al. Effect of thiamine pyrophosphate on the characteristics of farrowing and piglet vitality. Theriogenology 200 , 49–59 (2023). Zaleski, H. M. & Hacker, R. R. Variables related to the progress of parturition and probability of stillbirth in swine. Can Vet J 34 , 109–113 (1993). Canario, L., Bidanel, J.-P. & Rydhmer, L. Genetic trends in maternal and neonatal behaviors and their association with perinatal survival in French Large White swine. Front. Genet. 5 , (2014). Chen, C. et al. Maternal infanticide in sows: Incidence and behavioural comparisons between savaging and non-savaging sows at parturition. Applied Animal Behaviour Science 109 , 238–248 (2008). Knap, P. W. & Merks, J. W. M. A note on the genetics of aggressiveness of primiparous sows towards their piglets. Livestock Production Science 17 , 161–167 (1987). Quilter, C. R. et al. Porcine maternal infanticide as a model for puerperal psychosis. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 144B , 862–868 (2007). van der Steen, H. A. M., Schaeffer, L. R., de Jong, H. & de Groot, P. N. Aggressive Behavior of Sows at Parturition. Journal of Animal Science 66 , 271–279 (1988). Cabrera, R. A., Lin, X., Campbell, J. M., Moeser, A. J. & Odle, J. Influence of birth order, birth weight, colostrum and serum immunoglobulin G on neonatal piglet survival. Journal of Animal Science and Biotechnology 3 , 42 (2012). Decaluwé, R. et al. Piglets׳ colostrum intake associates with daily weight gain and survival until weaning. Livest Sci 162 , 185–192 (2014). Dividich, J. L., Rooke, J. A. & Herpin, P. Nutritional and immunological importance of colostrum for the new-born pig. The Journal of Agricultural Science 143 , 469–485 (2005). Valros, A. et al. Metabolic state of the sow, nursing behaviour and milk production. Livestock Production Science 79 , 155–167 (2003). Valros, A. E. et al. Nursing behaviour of sows during 5 weeks lactation and effects on piglet growth. Applied Animal Behaviour Science 76 , 93–104 (2002). Yun, J. et al. Prepartum nest-building has an impact on postpartum nursing performance and maternal behaviour in early lactating sows. Appli Anim Behav Sci 160 , 31–37 (2014). Marchant Forde, J. N. Piglet- and stockperson-directed sow aggression after farrowing and the relationship with a pre-farrowing, human approach test. Applied Animal Behaviour Science 75 , 115–132 (2002). Valros, A., Rundgren, M., Špinka, M., Saloniemi, H. & Algers, B. Sow activity level, frequency of standing-to-lying postural changes and anti-crushing behaviour—within sow-repeatability and interactions with nursing behaviour and piglet performance. Appli Anim Behav Sci 83 , 29–40 (2003). Lefort, G. et al. The maturity in fetal pigs using a multi-fluid metabolomic approach. Sci Rep 10 , 19912 (2020). Dourmad, J.-Y. et al. InraPorc : un outil d’aide à la décision pour l’alimentation des truies reproductrices. (2022). Grandinson, K., Rydhmer, L., Strandberg, E. & Thodberg, K. Genetic analysis of on-farm tests of maternal behaviour in sows. Livest Prod Sci 83 , 141–151 (2003). Egozcue, J. J., Pawlowsky-Glahn, V., Mateu-Figueras, G. & Barceló-Vidal, C. Isometric Logratio Transformations for Compositional Data Analysis. Mathematical Geology 35 , 279–300 (2003). Pagès, J. Multiple Factor Analysis by Example Using R . (Chapman and Hall/CRC, 2014). doi:10.1201/b17700. Husson, F., Josse, J., Narasimhan, B. & Robin, G. Imputation of mixed data with multilevel singular value decomposition. Journal of Computational and Graphical Statistics 28 , 552 (2019). Bougeard, S., Qannari, E. M., Lupo, C. & Hanafi, M. From multiblock partial least squares to multiblock redundancy analysis. A continuum approach. Informatica 22 , 11–26 (2011). Bougeard, S. & Cardinal, M. Multiblock modeling for complex preference study. Application to European preferences for smoked salmon. Food Quality and Preference 32 , 56–64 (2014). Abdi, H., Williams, L. J., Valentin, D. & Bennani-Dosse, M. STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling. WIREs Comp Stat 4 , 124–167 (2012). Thioulouse, J. Simultaneous Analysis of a Sequence of Paired Ecological Tables: A Comparison of Several Methods. Annals of Applied Statistics 5 , 2300–2325 (2011). Dray, S. & Dufour, A.-B. The ade4 Package: Implementing the Duality Diagram for Ecologists. Journal of Statistical Software 22 , 1–20 (2007). R Core Team. R: A language and environment for statistical computing (Version 4.0. 5)[Computer software]. R Foundation for Statistical Computing (2021). Additional Declarations No competing interests reported. Supplementary Files AdditionalFile1.docx Cite Share Download PDF Status: Published Journal Publication published 08 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 09 Apr, 2024 Reviews received at journal 03 Apr, 2024 Reviewers agreed at journal 21 Mar, 2024 Reviewers agreed at journal 19 Mar, 2024 Reviews received at journal 14 Mar, 2024 Reviewers agreed at journal 14 Mar, 2024 Reviewers invited by journal 06 Mar, 2024 Editor assigned by journal 22 Feb, 2024 Editor invited by journal 25 Jan, 2024 Submission checks completed at journal 25 Jan, 2024 First submitted to journal 05 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3836704","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":269686645,"identity":"3313a134-1e38-44a7-bf60-811b8574bc71","order_by":0,"name":"Océane Girardie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYDADNhDBY8AgxwbhyxGvxRiqxZhIq3gYGBIbCGnhZz988HNBBYNdn/ThZx/eFNik90n3PvzwgcEgH5cWyZ60ZOkZZxiS2/jSjGfOMUjLbZM5biw5g8HAsgGHFoMbPAbSvG0MyWw8DMbMPAaHc9sk0hikeRj+GOCyxeAG/+ffvP9AWtg/A7X8T2eTSGP+/YfBAI8WHjZp3gYGOzYeHpAtBxKAWtikGfBoAfrFzJrnmEQCUEsx4xyDZEOgw9gsewxwawGG2OPbPDU29vI97JsZ3vyxk5efkcZ840cFbi1QIAGLDriDCWgAAnvCSkbBKBgFo2DEAgBVUEJq8b4PPAAAAABJRU5ErkJggg==","orcid":"","institution":"UMR1388 GenPhySE, INRAE, Université de Toulouse, INPT","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Océane","middleName":"","lastName":"Girardie","suffix":""},{"id":269686646,"identity":"f6d0d082-16e5-47f6-90b3-80ddca9b8597","order_by":1,"name":"Denis Laloë","email":"","orcid":"","institution":"UMR1313 GABI, INRAE, Université Paris-Saclay","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Denis","middleName":"","lastName":"Laloë","suffix":""},{"id":269686647,"identity":"9d7ea780-a9df-43ac-8529-53ef583d9bf1","order_by":2,"name":"Mathieu Bonneau","email":"","orcid":"","institution":"UR0143 ASSET, INRAE","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mathieu","middleName":"","lastName":"Bonneau","suffix":""},{"id":269686648,"identity":"fb8f8490-6a81-4e00-b07e-687244bf275c","order_by":3,"name":"Yvon Billon","email":"","orcid":"","institution":"UE GenESI, INRAE","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yvon","middleName":"","lastName":"Billon","suffix":""},{"id":269686649,"identity":"7b92bda0-3013-40f2-9f5c-09505170e6e0","order_by":4,"name":"Jean Bailly","email":"","orcid":"","institution":"UE GenESI, INRAE","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jean","middleName":"","lastName":"Bailly","suffix":""},{"id":269686650,"identity":"c597a8d4-1816-424e-b983-d3bac05d6fa8","order_by":5,"name":"Ingrid David","email":"","orcid":"","institution":"UMR1388 GenPhySE, INRAE, Université de Toulouse, INPT","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ingrid","middleName":"","lastName":"David","suffix":""},{"id":269686651,"identity":"1842782b-bdc0-42d1-be0d-d1273c8ce409","order_by":6,"name":"Laurianne Canario","email":"","orcid":"","institution":"UMR1388 GenPhySE, INRAE, Université de Toulouse, INPT","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Laurianne","middleName":"","lastName":"Canario","suffix":""}],"badges":[],"createdAt":"2024-01-05 08:29:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3836704/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3836704/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-69358-8","type":"published","date":"2024-08-08T15:57:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":50292639,"identity":"3a6731af-56b2-40bc-af2f-fa38f26fa2c0","added_by":"auto","created_at":"2024-01-29 09:01:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":88524,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentation of the distribution of individuals established according to the factor analysis of mixed data (FAMD) on the first two dimensions (Dim1 and Dim2) defined by the analysis.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/82b82c0c85f3f4a961dcbd92.png"},{"id":50292644,"identity":"971d0d83-f7c8-4197-87dc-bae19adbd49f","added_by":"auto","created_at":"2024-01-29 09:01:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":196025,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentation of the block importance index on early piglet growth for the 11 explanatory blocks. Multiblock partial least-squares (mbPLS) regression of early piglet growth explained by farrowing performance and environment (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sub\u003e), body reserves (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e), teat quality (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e), sow behavior at maternity entrance (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/sub\u003e), farrowing reactivity (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/sub\u003e), standing activity before farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/sub\u003e), standing activity at farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/sub\u003e), standing activity after farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/sub\u003e), postural activity before farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/sub\u003e), postural activity at farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/sub\u003e) and postural activity after farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/sub\u003e).\u0026nbsp; BlockImp index represents the relative contribution of each explanatory block to early piglet growth and satisfies the condition ∑kBlockImpk\u0026nbsp;=\u0026nbsp;100% for\u0026nbsp;K\u0026nbsp;=\u0026nbsp;1 to 11. Bars represent the 95% confidence interval around the BlockImp index estimate.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/a20c801137d87849db79eba4.png"},{"id":50292640,"identity":"c5450b7d-6612-4750-8e7e-dfb592c2a89b","added_by":"auto","created_at":"2024-01-29 09:01:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":201873,"visible":true,"origin":"","legend":"\u003cp\u003eGraph showing the VarImp Index of the 33 most important maternal traits (VarImp \u0026gt; 0.89%) with a 95% confidence interval. The threshold value is shown with the vertical red line at 1/101% = 0.99%. Multiblock analysis of the three average daily gains (\u003cstrong\u003eY\u003c/strong\u003e) explained by farrowing performance and environment (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sub\u003e), body reserves (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e), teat quality (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e), sow behavior at maternity entrance (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/sub\u003e), farrowing reactivity (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/sub\u003e), standing activity before farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/sub\u003e), standing activity at farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/sub\u003e), standing activity after farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/sub\u003e), postural activity before farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/sub\u003e), postural activity at farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/sub\u003e) and postural activity after farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/sub\u003e).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/b3fbe70df7c0d321064f763d.png"},{"id":50292641,"identity":"66343b57-3bba-49d5-bf01-9957b322cce3","added_by":"auto","created_at":"2024-01-29 09:01:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":169378,"visible":true,"origin":"","legend":"\u003cp\u003ePlots of variables the most commonly represented on the three first dimensions (\u0026gt; |0.3|) of the multiblock analysis for the three average daily gains (\u003cstrong\u003eY\u003c/strong\u003e) explained by the 101 maternal variables grouped into 11 blocks: farrowing performance and environment (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sub\u003e), body reserves (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e), teat quality (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/sub\u003e), sow behavior at entrance in maternity room (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/sub\u003e), farrowing reactivity (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/sub\u003e), standing activity before farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/sub\u003e), standing activity at farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/sub\u003e), standing activity after farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/sub\u003e), postural activity before farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/sub\u003e), postural activity at farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/sub\u003e) and postural activity after farrowing (\u003cstrong\u003eX\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/sub\u003e).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/906f216aab1dc86c203cd496.png"},{"id":50292646,"identity":"9ec1988b-12c3-43df-b527-1f2140f52d66","added_by":"auto","created_at":"2024-01-29 09:01:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":229685,"visible":true,"origin":"","legend":"\u003cp\u003ePartial triadic analysis of postural activity and early piglet weight gain. (A) Variable representation in dimensions 1-2 of the compromise. (B,D,F) Deviations from the compromise: (B) on D0-D1; (D) on D1-D3; (F) on D3-D7. Arrows 1 to 4 were the principal axes of a given table projected on the compromise of the first two axes; the distance between arrows and axes shows the deviation between a table and the compromise. (C,E,G) Loadings of variables on Tables D0-D1, D1-D3 and D3-D7.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/bec21bb88538b9009e023766.png"},{"id":50293085,"identity":"dfcbb633-a952-4b92-8c49-a9172ecc41ff","added_by":"auto","created_at":"2024-01-29 09:09:04","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":214265,"visible":true,"origin":"","legend":"\u003cp\u003ePartial triadic analysis of standing activity and early piglet weight gain. (A) Variable representation in dimensions 1-2 of the compromise. (B,D,F) Deviations from the compromise: (B) on D0-D1; (D) on D1-D3; (F) on D3-D7. Arrows 1 to 4 were the principal axes of a given table projected on the compromise of the first two axes; the distance between arrows and axes shows the deviation between a table and the compromise. (C,E,G) Loadings of variables on Tables D0-D1, D1-D3 and D3-D7.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/5539f619dbf390221c24f5fa.png"},{"id":50293087,"identity":"bc3d7e02-2981-423c-9d72-0ebff248a273","added_by":"auto","created_at":"2024-01-29 09:09:07","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":275629,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/a8b9718305ece7f9aead636f.png"},{"id":50293083,"identity":"90f0fcbc-d30c-4f79-a017-6e8e74927211","added_by":"auto","created_at":"2024-01-29 09:09:03","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":63445,"visible":true,"origin":"","legend":"\u003cp\u003eMatrix used in Partial Triadic Analysis inspired by Thioulouse\u003csup\u003e70\u003c/sup\u003e\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/f54489027645f99925697a73.png"},{"id":62298288,"identity":"7f57146d-8c59-4c53-99ac-806d0d6dba8e","added_by":"auto","created_at":"2024-08-12 16:11:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2211800,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/1aadb9c4-0d39-4492-9cd0-6f02107f7470.pdf"},{"id":50293084,"identity":"8e2721d8-94e7-49b3-9a8e-89184ef023e8","added_by":"auto","created_at":"2024-01-29 09:09:04","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27695,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3836704/v1/37310e337af055309636d793.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sow behavior on the day of farrowing: The main determinant of early piglet growth among maternal ability traits","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe early growth of the newborn piglet may have an effect on its survival until weaning. This performance depends on interactions with littermates and the dam. Compared to its littermates, a piglet that is heavier at birth grows faster on average\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e (a 22% difference in average daily gain the first week of lactation)\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e and is heavier at weaning\u003csup\u003e\u003cspan additionalcitationids=\"CR4 CR5 CR6\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, in relation to a more efficient suckling activity\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. However, this general trend is not confirmed for all piglets. In Huting et al.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, 51.9% of piglets born heavy fell into the lower weaning weight category. Although growth in the first week after birth can predict growth up until weaning, very few studies have addressed this association\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The risk of delayed growth in early lactation for weaning performance remained a secondary issue to the overriding problem of piglet mortality. The measurement of early growth and use for selective breeding could be a mean to indirectly improve piglet survival in pig maternal lines.\u003c/p\u003e \u003cp\u003eEarly growth is partly determined by the piglet itself through intrinsic factors including physiology (body weight), behavior and genotype\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. But it is the sow, who, through its maternal ability, has the most decisive role on early piglet performance. As a result, most studies on piglet growth are devoted exclusively to maternal factors. Maternal abilities encompass a large set of sow physiological and behavioral traits. Some genetic studies show that maternal effects on piglet performance are large. Maternal effects explain more piglet weight at birth compared to direct effects of the piglet \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The main sow maternal effects are reflected in milk production (ranging from 7 to 10 kg/d)\u003csup\u003e1,12,15\u003c/sup\u003e, which results from feed intake\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and the use of body reserves\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The functionality of teats and their physical characteristics may also influence early growth. They influence milk intake along the udder\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Sow behavior in the period around farrowing (D-3 to D7) also influences early piglet growth. In a study focused on the 24 hours around farrowing, Illmann et al.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e showed that the number of postural changes at farrowing was positively correlated with piglet growth on the first day after birth. In the same population as in the current study, we showed that early growth (to D7) of piglets from sows that change postural more often to hide the udder on the day of farrowing is lower than that of sows that do not hide the udder\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. While their growth is on average 250 g/d over lactation, the average weight gain of pure Meishan piglets during the first week after birth was 110 g/d, and that of pure Large White piglets was 160 g/d. Although some previous studies focused on the relationship of certain aspects of maternal behavior and piglet performance, none have accounted for sow functional traits simultaneously.\u003c/p\u003e \u003cp\u003eThe objective of the current study was to explore the variability in associations between sow maternal ability traits and early piglet growth. We used genetically heterogeneous population consisting of a total of 21 Large-White (LW) sows and 22 Meishan (MS) sows, housed in individual farrowing pens. They produced both purebred and crossbred piglets in their litter since they had been inseminated with mixed semen from the two breeds. We analyzed the relationships between 101 maternal traits measured from entrance into the farrowing unit to 7 days after farrowing, and three piglet growth traits obtained from weighing at several occasions in the 7 days after birth (D0-D1, D1-D3 and D3-D7).\u003c/p\u003e \u003cp\u003eMultivariate methods enabled to analyze the variations underlying each trait and the correlations among traits. First, a factor analysis of mixed data (FAMD) was used to describe the structure of the database. Then, a partial least square (PLS) multiblock analysis was run to quantify the effect of each maternal variable on early piglet growth. Finally, partial triadic analyses were used to analyze the evolution of sow behavior traits with time and determine the period(s) in which they have the greatest influence on early piglet growth.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDescription of the data base\u003c/h2\u003e \u003cp\u003eThe breed differences in maternal ability traits are reported in Additional File 1. At farrowing, LW sows were significantly older (433 days vs. 391 days), heavier (240 kg vs. 167 kg) and had a larger amount of protein reserves than MS sows. They gave birth to larger litters (15.1 vs. 12.5) and piglets that grew up faster after D1 than those born from MS sows (ADG of 160 g vs. 95 g from D1 to D3, and 224 g vs. 143 g from D3 to D7). On the other hand, MS sows were characterized by a larger amount of fat reserves (backfat depth: 49 mm vs. 25 mm; fat content: 101 vs. 85 kg). They had a higher number of teats (total and functional) than LW sows. The two breeds also differed in behavior. The LW sows vocalized more than MS sows in all situations, were more aggressive towards humans and piglets, and rested less during farrowing (131 vs. 287 postural changes).\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe results of the FAMD applied to the 101 variables are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The FAMD exhibits a clear separation between the two breeds on the first axis (21.5% of data variation explained (inertia), while the second axis explains only 7.0% of data variation). For an overview of the range of associations between variables and early piglet growth that could be detected in a commercial population, we considered that it was a priority to analyze the associations between the multitude of variables that describe maternal ability and piglet growth, independent of the sow breed factor. The correction for breed effect was separately applied to each of the 101 variables using linear models. Residuals were used as variables of interest in the following analyses.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eRelative influence of the blocks of maternal ability traits in the prediction of early piglet growth according to the MBPLS analysis\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe relationship between the 101 maternal traits (explanatory variables \u003cb\u003eX\u003c/b\u003e) and the three average daily piglet weight gains (variable to be explained \u003cb\u003eY\u003c/b\u003e) were evaluated on the basis of the multiblock analysis. The first three dimensions of the multiblock analysis accounted for 68.2% of the total inertia in data structure (42.9%, 13.2% and 12.1%, respectively). The three ADG were lowly correlated with each other (0.11 to 0.23).\u003c/p\u003e \u003cp\u003eThe Block Importance (BlockImp) that makes it possible to observe the importance of each of the 11 blocks (\u003cb\u003eX\u003c/b\u003e) to explain the three ADG (\u003cb\u003eY\u003c/b\u003e) is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Given this statistic, only the block considering sow activity while standing on D0 was significantly correlated with the global ADG (BlockImp\u003csub\u003eX7\u003c/sub\u003e = 14.36% [10.43; 24.94]\u003csub\u003e95%\u003c/sub\u003e). Even if their CI included the threshold value of 1/11, four other blocks showed an average BlockImp index value greater than 1/11, which underlies a substantial contribution to early piglet growth. Those were blocks describing farrowing reactivity (BlockImp\u003csub\u003eX5\u003c/sub\u003e = 12.08% [3.31; 19.34]\u003csub\u003e95%\u003c/sub\u003e), body reserves (BlockImp\u003csub\u003eX2\u003c/sub\u003e = 10.34% [4.20; 17.88]\u003csub\u003e95%\u003c/sub\u003e), postural activity on D0 (BlockImp\u003csub\u003eX10\u003c/sub\u003e = 9.87% [2.45; 15.43]\u003csub\u003e95%\u003c/sub\u003e), and teat quality (BlockImp\u003csub\u003eX3\u003c/sub\u003e = 9.46% [4.57; 12.76]\u003csub\u003e95%\u003c/sub\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe importance index (VarImp) makes it possible to evaluate the importance of each of the 101 variables within the blocks on ADG for the three periods studied together. The VarImp index of the 33 maternal traits with the most significant importance over the three ADG periods (VarImp\u0026thinsp;\u0026gt;\u0026thinsp;1/101%) are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e. These 33 maternal traits explain 85% of the variation in ADG in the three periods (D0-D1, D1-D3 and D3-D7). Of these 33 variables, three variables in blocks \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e7\u003c/b\u003e\u003c/sub\u003e and \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sub\u003e had a significant effect on ADG in early lactation (D0 to D7): time spent doing something other than eating and drinking when the sow is standing on D0 (VarImp\u003csub\u003eotherD0\u003c/sub\u003e = 6.76% [1.58; 13.4]\u003csub\u003e95%\u003c/sub\u003e, \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e7\u003c/b\u003e\u003c/sub\u003e); time spent eating on D0 (VarImp\u003csub\u003eeatD0\u003c/sub\u003e = 7.50% [1.87; 14.8]\u003csub\u003e95%\u003c/sub\u003e, \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e7\u003c/b\u003e\u003c/sub\u003e); and farrowing duration (VarImp\u003csub\u003eFarrowingDuration\u003c/sub\u003e = 3.77 [1.88; 7.40]\u003csub\u003e95%\u003c/sub\u003e, \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sub\u003e). These three maternal traits explain 18.03% of ADG in the three periods. Additional maternal traits in blocks \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e5\u003c/b\u003e\u003c/sub\u003e, \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e and \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e10\u003c/b\u003e\u003c/sub\u003e, showed an important influence on ADG in the three periods but were associated with wide confidence intervals: aggressiveness towards piglets (VarImp\u003csub\u003eAggressivePiglets\u003c/sub\u003e = 10.13 [-0.45; 19.94]\u003csub\u003e95%\u003c/sub\u003e, \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e5\u003c/b\u003e\u003c/sub\u003e) and aggressiveness towards humans (VarImp\u003csub\u003eAggressiveHuman\u003c/sub\u003e = 4.23 [-12.35; 8.26]\u003csub\u003e95%\u003c/sub\u003e, \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e5\u003c/b\u003e\u003c/sub\u003e), the amount of body protein (VarImp\u003csub\u003eProteins\u003c/sub\u003e = 5.04 [-0.03; 9.94]\u003csub\u003e95%\u003c/sub\u003e, \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e), sow body weight (VarImp\u003csub\u003eSowWeight\u003c/sub\u003e = 3.93 [0.54; 7.73]\u003csub\u003e95%\u003c/sub\u003e, \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e), and the time spent standing on D0 (VarImp\u003csub\u003eSTD0\u003c/sub\u003e = 3.92 [0.55, 7.63]\u003csub\u003e95%\u003c/sub\u003e, \u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e10\u003c/b\u003e\u003c/sub\u003e). These five maternal traits explained 27.25% of ADG in the three periods.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe graphical representation of the relationship between sow traits and ADG considering the first three axes of the PLS multiblock analysis is given in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e. This figure shows which variables are associated with ADG\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/sub\u003e, ADG\u003csub\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/sub\u003e and ADG\u003csub\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;7\u003c/sub\u003e. ADG\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/sub\u003e and ADG\u003csub\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/sub\u003e were in the opposite direction of ADG\u003csub\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;7\u003c/sub\u003e on axis 2, and ADG\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/sub\u003e and ADG\u003csub\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/sub\u003e were in the opposite direction to each other on axis 3. Axes 2 and 3 explained 24% of the variance in the \u003cb\u003eY\u003c/b\u003e blocks and 13.3% of the variance in the \u003cb\u003eX\u003c/b\u003e blocks. The number of functional teats at D7 (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e), time spent sitting in the days after farrowing (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e11\u003c/b\u003e\u003c/sub\u003e), as well as the total number of postural changes before farrowing (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e9\u003c/b\u003e\u003c/sub\u003e), were positively correlated with ADG\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/sub\u003e. Conversely, the time spent doing something other than drinking and eating while standing at D0 (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e7\u003c/b\u003e\u003c/sub\u003e), farrowing duration (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sub\u003e) and aggressiveness towards piglets at D0 (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e5\u003c/b\u003e\u003c/sub\u003e) were negatively correlated with ADG\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/sub\u003e. ADG\u003csub\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/sub\u003e was positively correlated with the time spent lying with udder exposed at D0 (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e10\u003c/b\u003e\u003c/sub\u003e), with aggressiveness towards humans on D0 (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e5\u003c/b\u003e\u003c/sub\u003e) and with protein reserves (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e). However, it was negatively correlated with the time spent standing before farrowing (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e9\u003c/b\u003e\u003c/sub\u003e), farrowing duration (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sub\u003e) and aggressiveness towards piglets on D0 (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e5\u003c/b\u003e\u003c/sub\u003e). A positive association was revealed between ADG\u003csub\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;7\u003c/sub\u003e and farrowing duration (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sub\u003e) and the time spent eating at D0 (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e7\u003c/b\u003e\u003c/sub\u003e). A negative association was found between ADG\u003csub\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;7\u003c/sub\u003e and the total number of postural changes before parturition (\u003cb\u003eX\u003c/b\u003e\u003csub\u003e\u003cb\u003e9\u003c/b\u003e\u003c/sub\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese results were confirmed by the multiblock PLS regression coefficients obtained after bootstrapping, with the exception of ADG\u003csub\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;7\u003c/sub\u003e, which showed a positive correlation with farrowing duration (X1) and the intercept of the ingestion curve after farrowing (X8), and a negative correlation with aggressiveness towards human at D0 (X5) and time spent drinking at D0 (X7).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTemporal variation in the relationships between sow behavior and litter growth: PTA analysis\u003c/h2\u003e \u003cp\u003eIn summary, on the basis of the multiblock analysis, sow behaviors on the day of farrowing and during the first day of lactation appeared to be more highly correlated with ADG on the three periods than other maternal traits. The blocks \u0026ldquo;standing activity\u0026rdquo; and \u0026ldquo;postural activity\u0026rdquo; were built from the longitudinal analysis of video images enabled from the use of convolutional neural networks (CNN). A Partial Triadic Analysis (PTA) was carried out to consider the temporal effect of these two blocks on ADG values. Thus, it was possible to estimate the correlations of postural activity traits and standing activity traits with ADG for the three periods D0-D1, D1-D3 and D3-D7. Referring to the vector correlation matrix, the structures of the three period tables according to postural activity changed with time. The correlations of the D0-D1 table were 0.59 with the D1-D3 table and 0.51 with the D3-D7 table.\u003c/p\u003e \u003cp\u003eThe three tables contributed to the definition of the compromise, with a participation between 0.54 to 0.61 αk. The D0-D1 table contributed less to the construction of the compromise table (αk: 0.54 and Cos\u0026sup2;: 0.83) than the two other tables. The D1-D3 table contributed more than the others (αk: 0.61 and Cos\u0026sup2;: 0.92).\u003c/p\u003e \u003cp\u003eIn the compromise table, the first axis explained 48% of the variation and the second axis 28% (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). On the factorial map of projection according to axes 1\u0026ndash;2, axis 1 was highly defined by time spent lying laterally with udder exposed (LLU) and axis 2 by time spent sitting (SI) and time spent sternal lying (SL) in the opposite direction. Referring to the compromise table, ADG\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/sub\u003e was mainly correlated with the number of postural changes (PCAll and PCStopNurse, Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). ADG\u003csub\u003e1\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/sub\u003e and ADG\u003csub\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;7\u003c/sub\u003e were weakly explained by postural activity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNone of the data structure developed per period (nb. of postural changes and postural activity from one of the three periods analyzed jointly) deviated from the compromise (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, D and F). The association between ADG and sow restlessness was low but more pronounced in the period D0-D1 than in the following periods. The ADG was lowly correlated with sow activity in the D1-D3 period. A low but substantial association between ADG and time spent lying laterally (LL) was observed on the D3-D7 period and not in the two previous periods (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, E and G).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eReferring to the vector correlation matrix, the structures of the three periodic tables changed over time as a function of standing activity. The correlations with the D0-D1 table decreased from 0.50 (D1-D3) to 0.25 (D3-D7). The compromise was defined with a weighted average of the three tables. The participation of each table in the calculation of the compromise ranged from 0.51 to 0.65 αk. Table D1-D3 had a higher contribution (αk: 0.65 and Cos\u0026sup2;: 0.90) to the calculation of the compromise than the other two tables (αk: 0.51 and 0.57; Cos\u0026sup2;: 0.74).\u003c/p\u003e \u003cp\u003eIn the compromise table, the first two axes explained 86% of the variation (axis 1: 55%; axis 2: 31%, Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). On the factorial map of the projection along axes 1\u0026ndash;2, axis 1 was defined by feed intake and time spent drinking while standing in opposite directions, and axis 2 was defined by time spent doing something else while standing. On the compromise, ADG\u003csub\u003e0-1\u003c/sub\u003e was mainly correlated with time spent eating (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). ADG\u003csub\u003e1-3\u003c/sub\u003e and ADG\u003csub\u003e3-7\u003c/sub\u003e were weakly explained by the standing activity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFood intake and standing activity (analyzed jointly in one period) did not significantly deviate from the compromise (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eB, D, and F). The association between ADG and time spent eating (and feed intake as well) was low but more pronounced in the period D0-D1 than in the following periods. ADG\u003csub\u003e3-7\u003c/sub\u003e was negatively correlated with the time spent doing something other than eating or drinking while standing in the period D3-D7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eC, E and G).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe partial triadic analysis and the multiblock analysis indicated a stronger relationship of growth from D0 to D1 with sow behavior on farrowing than on other maternal traits.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe use of breeds contrasting in maternal ability allows to access a large variation in maternal traits and in their relationships with piglet growth\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The design makes it possible to discover the maximum range of variation observable in any pig population, on these traits. The detection of maternal effects was maximized by construction, with an experimental design with both purebred and crossbred piglets in the litters. The two breeds drastically differ in metabolism and in the ability to invest in piglet production as well\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The LW sows have a greater number of functional teats\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e and a greater capacity to use fat reserves in early lactation\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The LW sows outperform MS sows in investment capacity due to greater body size and feed intake capacity. Selective breeding has also led LW sows to outperform MS sows in litter size\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Piglets from LW sows are also heavier than piglets from MS sows.\u003c/p\u003e \u003cp\u003eConversely, the two breeds do not differ in their general behavior in the days after farrowing, as described in Girardie et al.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The same range of variation was observed for postural and standing activity. Consequently, the adjustment of data for sow breed did not restrict the range of behavioral variation we were able to exploit. We found breed differences in behavioral reactivity that are in line with Farmer and Robert\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e who showed that MS sows are less response to piglets than LW sows in most situations.\u003c/p\u003e \u003cp\u003eSow breed explained a significant part of the data variability (21.5%). We explored the range of possible associations between maternal ability traits and mean piglet growth. Adjusting data for this breed effect allowed us to highlight generic associations that should be detectable in many pig maternal populations. For this aim, we used multifactorial analyses, notably the Multiblock Partial Least Square analysis that is robust when considering many traits recorded on a limited number of individuals.\u003c/p\u003e \u003cp\u003eGrowth during the first days after birth can determine subsequent piglet survival and growth. Indeed, survival of piglets during lactation is correlated with piglet weight gain in the first 48 hours after birth\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. In addition, piglet survival is lower when colostrum intake is not sufficient\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. In the current study, weak correlations of 0.11 to 0.23 between average daily weight gains estimated at the three periods (D0-D1, D1-D3, and D3-D7) were found, thus constituting lowly dependent variables with possibly different determinism. The regression coefficients obtained with the multiblock analysis showed that each mean daily weight gain was strongly correlated with a different set of maternal traits. Sow restlessness before farrowing influence piglet growth after birth, differently at two growth periods. ADG\u003csub\u003e0\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/sub\u003e was favorably correlated to pre-farrowing sow restlessness and ADG\u003csub\u003e3\u0026thinsp;\u0026minus;\u0026thinsp;7\u003c/sub\u003e was unfavorably correlated to this behavior. These associations between traits measured at different times are due to indirect effects. In particular, higher pre-farrowing restlessness can relate to the nest building activity\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, a behavior that is favorable to newborn piglets\u0026rsquo; growth\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e as it induces the release of oxytocin, the hormone of lactation.\u003c/p\u003e \u003cp\u003eEarly piglet growth is influenced by diverse maternal factors. The study encompassed 3 blocks of physiological data and 8 blocks of behavioral data. Five blocks of maternal traits ranging from sow behavior to body composition at farrowing influenced early piglet growth: standing activity at D0 (14.4% of the three mean average daily weight gain explained), responsiveness to piglets and humans at farrowing (12.1%), body reserves at maternity entrance (10.3%), postural at D0 (9.9%), and teat quality (9.5%). Following are some elements of discussion on the main results highlighted by these multifactorial analyses.\u003c/p\u003e \u003cp\u003eAs is well known, piglet growth relies on sow milk production, which variation is generally dependent on differences in body protein use and feed intake among sows\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. In the present study, sows with higher body weight at farrowing entry and, concordantly, more protein reserves had lower piglet growth on the first day after birth than other sows. Consistently, Cools et al.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e showed that piglet weight gain from D0 to D1 is lower if the sow is heavier at farrowing entrance. Then, sows that spend more time eating on D0 have a higher weight gain of their piglets in the following days. Protein intake from the sow's diet is rapidly used for milk production.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Sows that ingest more proteins gain up to 52 g/d more in piglet growth than the other sows\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Often, on the day of farrowing, the sow ingests only a very small amount of feed\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, so it is important that she quickly resumes feeding activity to stimulate lactation\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. This is particularly the case for gilts that have not finished growing and that jointly use more energy for their own growth and milk production\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Feeding and also watering condition milk production\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. A sow that is more passive in the first days after farrowing and does not take in an adequate amount of water produces less milk than other sows. Indeed, water consumption varies between 6 and 14 L/d around farrowing\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Teat quality is also a key factor for piglet growth. In our study, piglet weight gain on D1 was favorably correlated to the number of teats still functional at D7. The efficient suckling activity of the piglets promotes the maintenance of teat functioning during lactation. In addition, the use of several teats per piglet boosts milk production\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Our study showed a correlation of 0.55 between the number of functional teats 24 h after the onset of farrowing and at D7.\u003c/p\u003e \u003cp\u003eIn addition to the main blocks identified, it is worth noting the marked influence of a single variable in the \"farrowing performance\" block on piglet growth at each of the three periods: the duration of farrowing. The longer the farrowing period is, the lower the average weight gain of piglets from D0 to D3, and the higher the weight gain from D3 to D7 will be. A long farrowing can be synonymous with health problems for the sow, which have eventually more difficulty starting lactation. In addition to litter size being the main determinant of farrowing duration,\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e stress can lead to a longer farrowing and decreased colostrum production\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. A long farrowing period results in more stillbirths\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e which decreases subsequent competition at the udder. Finally, a long farrowing favors hypoxia, which reduces viability in some piglets\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e so they take longer to access the udder and ingest less colostrum than their littermates\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. However in that situation of more critical farrowing, piglets that survive the first days after birth are likely to be more vigorous than those born in other litters\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. As a consequence, and especially if they are heavier, they can consume more milk and grow faster than those born from sows with easier farrowing\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn a more pronounced way than sow physiology, we showed that the behavior of the sow on the day of farrowing played part in early piglet growth. The weight gain of piglets in the first days after birth was lower in sows aggressive towards them (12% of sows in the current study). Primiparous sows, as seen in our study, are usually more aggressive towards their piglets than older sows\u003csup\u003e\u003cspan additionalcitationids=\"CR50 CR51\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. One hypothesis is that piglets raised by an aggressive sow develop a distrustful behavior towards the sow and would be less likely to approach her to suckle and it may affect milk production\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. As regards to general activity, sows that spend more time standing at D0 have piglets that grow slower than others sows, due to a more limited access to the udder. Piglets that consume less colostrum have lower growth during lactation\u003csup\u003e\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Sows that spend more time standing doing something other than eating and drinking have lower litter growth than other sows. Standing sows use more energy than other posturals, which may have consequences on milk production and subsequently, piglet growth\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Standing activity on the day of farrowing may be related to exploration of the environment and newborn piglets\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. The arrangement of the nest, may have a positive effect on piglet growth as nest-building favors the release of oxytocin\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. A correlation of 0.30 between nest-building behavior and piglet growth from D0 to D7 was reported in the literature\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe showed that sow behavior on the day of farrowing significantly explains piglet growth on the following days. In that case, sow aggressiveness towards piglets and humans and standing activity have a significant influence on piglet average daily gain between D0 and D7. This association is negative with aggressiveness toward piglets. Our study showed that aggressiveness towards piglets affects the growth of piglets that survive to D3. It can be assumed that the bond between the aggressive sow and its piglets is weaker than in a non-aggressive sow, resulting in less efficient nursing activity, and with possible implications for piglet growth. In contrast, sows that are aggressive towards human have piglets that grow faster from D1 to D3. A similar result was established by Marchant Forde\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e from D0 to D7, with a difference of 25 g/day in favor of aggressive sows toward human as compared to non-aggressive sows.\u003c/p\u003e \u003cp\u003eTo better understand the contribution of sow behavior in the determinism of early piglet growth, partial triadic analysis allows us to assess the importance of associations between the three time periods by comparing projections of the data over a compromise structure of correlations. Although little of the variation in growth was explained by the behavior maternal traits in each time period, this approach confirmed the more pronounced association of sow activity with piglet growth on the first day after birth. This association was more pronounced with the frequency of postural changes. Although the pattern of correlations among behavioral variables remained the same over time, it was less and less correlated to piglet growth. Accordingly, Valros et al.\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e found no association of sow restlessness after D3 with piglet growth in lactation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study depicted the relationships between a large number of maternal traits, and early piglet growth. Piglet growth was related to several maternal traits in three distinct periods in early lactation. Sows more aggressive to piglets or that spent more time standing at D0 had lower piglet mean weight gain than other sows. Conversely, sows that spent more time with udder exposed at D0 had higher weight gain. From D3 to D7, piglet growth was lower in sows that had spent less time drinking and eating at D0 and that were aggressive toward human than in other sows. At D0, certain behavioral features had a higher influence on early piglet growth than other maternal ability traits. Sow behavior can be used to detect litters at risk of delayed growth in early lactation.\u003c/p\u003e"},{"header":"Material and Method","content":"\u003ch2\u003e\u003cstrong\u003e\u003cu\u003eEthical statement\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe experimental protocol was designed in compliance with the legislations of the European Union (Directive 86/609/EEC) and France (Decree 2001\u0026ndash;464 29/05/01) for the care and use of animals (Agreement For Animal Housing Number C-35-275-32). All experiments were\u003c/p\u003e\n\u003cp\u003eperformed in accordance with relevant guidelines and regulations and were approved by the ethical committee of the Midi-Pyr\u0026eacute;n\u0026eacute;es Regional Council (authorization MP/01/01/01/11). Reporting in the manuscript follows the ARRIVE guidelines recommendations.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAnimals and Housing\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is based on a crossbreeding scheme, set up to quantify direct and maternal effects on piglet development during the suckling phase (the present study was carried out on sows in first parity) and before, during the intrauterine phase (e.g., study\u003csup\u003e61\u003c/sup\u003e on the same sows in second parity). The experimental design is described in detail in Girardie et al.\u003csup\u003e22\u003c/sup\u003e. This design included 21 primiparous LW and 22 primiparous MS sows kept in individual farrowing pens at the Le Magneraud INRAE GenESI experimental farm (doi: 10.15454/1.5572415481185847E12). Sows were inseminated with a mix of semen of MS and LW boars, so that each sow produced both purebred and crossbred piglets. As a consequence, four piglet genetic types were produced (dam/sire): LW purebred (LW/LW), LW crossbred (LW/MS), MS purebred (MS/MS) and MS crossbred (MS/LW). Farrowing was not induced. To assess the sow\u0026rsquo;s ability to raise her progeny, crossfostering was not allowed.\u0026nbsp;Intervention from the caretakers hired by the experimental unit was limited to unblocking piglets from foetal membranes at birth and saving piglets trapped under the sow.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003ePiglet measurements\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach piglet was weighed immediately after birth (D0), 24 h after birth (D1), and at 3 days (D3) and 7 days (D7) after birth. Weighing was carried out in the central corridor of the farrowing unit.\u0026nbsp;The average daily gain (ADG) on D0 to D1, D1 to D3 and D3 to D7 were calculated for each piglet and averaged per sow to obtain a piglet mean average daily gain for each litter on D0-D1 (ADG\u003csub\u003e0-1\u003c/sub\u003e), D1-D3 (ADG\u003csub\u003e1-3\u003c/sub\u003e) and D3-D7 (ADG\u003csub\u003e3-7\u003c/sub\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cstrong\u003e\u003cu\u003eSow measurements\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe behavioral and physiological characteristics of each sow were established on the basis of 101 variables recorded or calculated on each sow.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFarrowing performance and environment\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe litter size, the number of piglets born alive, the age of the sow at farrowing (in days), the % of MS piglets in the litter ((number of MS piglets/litter size) * 100) and the farrowing duration (in minutes) were recorded for each sow. Farrowing duration was defined as the interval between birth of the first piglet and the last piglet in the litter (min = 30 min and max = 390). An environmental variable, the pen, was recorded:, this variable is divided into four categorical variables (A, B, C and D)\u003csup\u003e22\u003c/sup\u003e according to its position in the maternity room. We designated pen A as the pen that was the nearest to the weighing area in the central corridor and D as the pen that was the furthest from the weighing area. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBody reserves\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhen entering the maternity unit, the sow was weighed (weight in kg) and its back fat was measured by ultrasound on six points on the back: left and right kidney, back and shoulder. The back fat depth was then obtained as the average of the six measurements. The composition of sows in terms of lipids, proteins and energy was calculated using the equation proposed by Dourmad et al.\u003csup\u003e62\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFeed intake\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSows were fed twice daily, at 8 a.m. and 4 p.m. with a feed of 0.7 kg/L density. The volume (V) of feed intake was measured by subtracting the volume of refusals from the given amount. The daily feed intake in kg was calculated as V*0.7. A random regression was then applied to these longitudinal data per period, smoothed using the Nadaraya-Watson estimator in order to summarize the dynamic of the feed intake for each individual into two variables per period (the intercept and the slope).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTeat quality\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTeat qualification (length) was noted as little, medium, large or irregular. The number of teats and their functionality were recorded at 24 h and 7 days after farrowing. The average interval between teats was measured (cm) and information on the regularity of this interval was noted (regular, irregular). A qualification of average teat diameter was also reported (0.5 to 1 cm, 1 to 1.5 cm or 1.5 to 2 cm).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBehavior\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA 2D camera was fixed above each pen to film the sow 24 h a day. The video recording started 3 days before farrowing (D-3) and stopped 7 days after farrowing (at D7 of lactation) for all sows. Sow behavior was extracted from the video recording using convolution neural networks\u003csup\u003e22\u003c/sup\u003e. The automatically registered behaviors were (i) postural: standing (ST), sitting (SI), sternal lying (SL), lateral lying (LL) and lateral lying with udder exposed (LLU); (ii) standing activity: eating, drinking and doing something else (exploring or rooting). Other variables describing sow behavior were obtained from notations on the farm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBehavior at farrowing entrance\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe difficulty to get out of the trailer indicated the ease at handling and was noted on a scale from -1 to +1 (-1 = difficulty to get out, 0 = easy, and +1 = very easy to get out). The adaption to the farrowing pen was noted by observing the ease to enter the farrowing pen on a scale from -1 to +1 (1: enter rapidly; 0 and -1: force to enter), and sow vocalizations (0 = no vocalization and 1 = \u0026gt; =1 vocalizations) and sow postural (lateral lying, sitting or standing) 30 min and 1 h after entrance in the farrowing unit. Habituation to humans was also observed with a test inspired by Grandisson et al.\u0026nbsp;\u003csup\u003e63\u003c/sup\u003e This test consists of observing the reaction of the sow when a human is at a distance, outside the pen and in contact with the hand. Different information was recorded: behavior of the sow (positive, negative or in continuity with behavior before the test starts), vocalization (0 = no vocalization; 1 = \u0026gt; =1 vocalization), initial postural when the test starts (sitting, lateral lying, sternal lying and standing), and the index of postural change described in Grandisson et al.\u003csup\u003e63\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eReactivity at farrowing\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the farrowing process, caretakers regularly visited each sow to collect newborn piglets, dry them and weigh them. Restlessness (0/1) and aggression towards piglets (0/1) and humans (0/1) were noted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePostural activity and standing activity\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe time spent in each postural and in each activity while standing was calculated for three periods: before farrowing, on the day of farrowing and after farrowing. This compositional data was transformed with Centered Log Ratio (CLR)\u003csup\u003e64\u003c/sup\u003e before analysis. Two specific amounts of postural changes were also calculated from the behavior prediction database: an average daily number of postural changes per period was calculated as the total number of postural changes divided by the number of days in the period (PCAll). The same calculation was applied for the number of postural changes hiding the udder (PCStopNurse)\u003csup\u003e22\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eStatistics\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003eData exploration\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeans or proportions per breed were calculated for each variable studied. To evaluate if there was a significant difference between breed, Student\u0026apos;s t tests were performed on quantitative variables and chi-square tests on qualitative variables.\u0026nbsp;In order to describe the overall structuration of the data, we used a Factorial Analysis of Mixed Data (FAMD). FAMD is a factorial analysis that can handle a mix of continuous and categorical variables\u003csup\u003e65\u003c/sup\u003e. Categorical variables are transformed into 0/1 variables. Note that FAMD is similar to PCA when there are only continuous variables and to MCA when there are only categorical variables. For more detail, see Husson et al.\u003csup\u003e66\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll\u0026nbsp;the variables were corrected for breed effect with a linear model. The residuals of this model were used in the following two analyses. They were not expressed in the same unit of measurement; they were column centered and scaled to unit variance beforehand.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMultiblock analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe multiblock Partial Least Squares (mbPLS)\u003csup\u003e67\u003c/sup\u003e was used to explore the potential drivers that could influence/explain early piglet growth.\u0026nbsp;It is an extension of the PLS method to the multiblock case, i.e., where a dataset \u003cstrong\u003eY\u003c/strong\u003e is to be explained or predicted by a dataset \u003cstrong\u003eX\u003c/strong\u003e that is organized into K blocks: X=(X1,\u0026hellip;,Xk).\u0026nbsp;\u0026nbsp;In this study, we studied the link between ADG of three different periods (\u003cstrong\u003eY\u003c/strong\u003e, matrix\u0026nbsp;\u0026nbsp;, where\u0026nbsp;\u0026nbsp;\u0026nbsp;is the number of sows) and 101 maternal components. The latter were grouped into 11 blocks that included farrowing performance and environment (\u003cstrong\u003eX\u003csub\u003e1\u003c/sub\u003e\u003c/strong\u003e, eight variables), body reserves (\u003cstrong\u003eX\u003csub\u003e2\u003c/sub\u003e\u003c/strong\u003e, five variables), teat quality (\u003cstrong\u003eX\u003csub\u003e3\u003c/sub\u003e\u003c/strong\u003e, 15 variables), sow behavior at entrance in maternity room (\u003cstrong\u003eX\u003csub\u003e4\u003c/sub\u003e\u003c/strong\u003e, 36 variables), farrowing reactivity (\u003cstrong\u003eX\u003csub\u003e5\u003c/sub\u003e\u003c/strong\u003e, three variables), postural activity before farrowing (\u003cstrong\u003eX\u003csub\u003e6\u003c/sub\u003e\u003c/strong\u003e, six variables), postural activity at farrowing (\u003cstrong\u003eX\u003csub\u003e7\u003c/sub\u003e\u003c/strong\u003e, six variables), postural activity after farrowing (\u003cstrong\u003eX\u003csub\u003e8\u003c/sub\u003e\u003c/strong\u003e, six variables), standing activity before farrowing (\u003cstrong\u003eX\u003csub\u003e9\u003c/sub\u003e\u003c/strong\u003e, four variables), standing activity at farrowing (\u003cstrong\u003eX\u003csub\u003e10\u003c/sub\u003e\u003c/strong\u003e, four variables) and standing activity after farrowing (\u003cstrong\u003eX\u003csub\u003e11\u003c/sub\u003e\u003c/strong\u003e, four variables). The variables included in each block were those presented in the Measurement section.\u003c/p\u003e\n\u003cp\u003eThe multiblock analysis is a latent variable technique. The whole procedure is detailed in Bougeard et al.\u003csup\u003e67\u003c/sup\u003e. Briefly, it consists of three steps (Figure 7).\u003c/p\u003e\n\u003cp\u003eFirst, each of the (K+1) datasets, i.e., Y and (X1,\u0026hellip;Xk), are summarized by the latent variables u and (t1,\u0026hellip;tk), respectively. In a second step, a global latent variable t is derived as a weighted sum of the tk, so that the squared covariance of t and u is maximized.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1706518236.png\"\u003e\u003c/p\u003e\n\u003cp\u003eFinally, the method provides interpretation tools such as the Block Importance that is equal to a2k, and the Variable Importance, equal to the product of the Block Importance and the weight of the variable in the latent variable. \u0026nbsp;Since both Block Importance and Variable Importance sum to 1, these values can be interpreted as percentages. Ultimately, the significance of Block Importance and Variable Importance can be appreciated via a bootstrap procedure (999 samples). An explicative block was significantly important for ADG if its 95% confidence interval did not include the threshold value 1/11. In addition, an explicative variable was significantly important for ADG if its 95% confidence interval did not include the threshold value 1/101.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePartial Triadic Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo better comprehend the evolution of the relationships between variables over time, we carried out a Partial Triadic Analysis (PTA)\u003csup\u003e69,70\u003c/sup\u003e. PTA is the analysis of a three-dimensional matrix (sows\u0026thinsp;\u0026times;\u0026thinsp;variables\u0026thinsp;\u0026times;\u0026thinsp;periods, Figure 8). In this study, three periods of time (= three tables) were considered on the same animals and variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePTA consists of three steps;\u0026nbsp;\u003csup\u003e69,70\u003c/sup\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eThe interstructure (relationships among tables), with the so-called RV coefficient, which measures the similarity among tables. The RV coefficient is an extension of the correlation coefficient. The RV coefficient, located between -1 and 1, has the same interpretation as a correlation coefficient.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe compromise, or consensus table, that is a weighted average of the tables. This table made it possible to observe the average relationships between variables. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe intrastructure, which consists in studying the specificity of each table compared to the compromise table. It is obtained by the projection of each individual table (rows and columns) onto the compromise.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003ePTA was run separately for standing activity and for postural activity between D0 and D7. For each PTA, ADG\u003csub\u003e0-1\u003c/sub\u003e, ADG\u003csub\u003e1-3\u003c/sub\u003e and ADG\u003csub\u003e3-7\u0026nbsp;\u003c/sub\u003ewere added as supplementary variables to evaluate the link between standing and postural activity and piglet average daily gain.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMultivariate and statistical analyses were performed using the ade4 package\u0026nbsp;\u003csup\u003e71\u003c/sup\u003e from R\u003csup\u003e72\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAdditional Information\u003c/strong\u003e\u003cbr\u003e The author(s) declare no competing interests.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request. The system used during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eLC conceived the project. LC, YB, and JB carried out the experiment. MB supervised the automated video analysis of sow behavior. OG, LC, ID, and DL participated in the data analysis. OG, LC, ID, DL contributed to writing the manuscript. All authors contributed to the article and approved the submitted version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSkok, J., Brus, M. \u0026amp; \u0026Scaron;korjanc, D. Growth of piglets in relation to milk intake and anatomical location of mammary glands. \u003cem\u003eActa Agriculturae Scandinavica, Section A \u0026mdash; Animal Science\u003c/em\u003e \u003cstrong\u003e57\u003c/strong\u003e, 129\u0026ndash;135 (2007).\u003c/li\u003e\n\u003cli\u003eFerrari, C. V. \u003cem\u003eet al.\u003c/em\u003e Effect of birth weight and colostrum intake on mortality and performance of piglets after cross-fostering in sows of different parities. \u003cem\u003ePreventive Veterinary Medicine\u003c/em\u003e \u003cstrong\u003e114\u003c/strong\u003e, 259\u0026ndash;266 (2014).\u003c/li\u003e\n\u003cli\u003eRomero, M. \u003cem\u003eet al.\u003c/em\u003e Short- and Long-Term Effects of Birth Weight and Neonatal Care in Pigs. \u003cem\u003eAnimals (Basel)\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 2936 (2022).\u003c/li\u003e\n\u003cli\u003eDevillers, N., Farmer, C., Dividich, J. L. \u0026amp; Prunier, A. Variability of colostrum yield and colostrum intake in pigs. \u003cem\u003eanimal\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, 1033\u0026ndash;1041 (2007).\u003c/li\u003e\n\u003cli\u003eDevillers, N., Dividich, J. L. \u0026amp; Prunier, A. Influence of colostrum intake on piglet survival and immunity. \u003cem\u003eanimal\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 1605\u0026ndash;1612 (2011).\u003c/li\u003e\n\u003cli\u003eQuiniou, N., Dagorn, J. \u0026amp; Gaudr\u0026eacute;, D. Variation of piglets\u0026rsquo; birth weight and consequences on subsequent performance. \u003cem\u003eLivestock Production Science\u003c/em\u003e \u003cstrong\u003e78\u003c/strong\u003e, 63\u0026ndash;70 (2002).\u003c/li\u003e\n\u003cli\u003eH\u0026ouml;gberg, A. \u0026amp; Rydhmer, L. A Genetic Study of Piglet Growth and Survival. \u003cem\u003eActa Agriculturae Scandinavica, Section A \u0026mdash; Animal Science\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, 300\u0026ndash;303 (2000).\u003c/li\u003e\n\u003cli\u003eHemsworth, P. H., Winfield, C. G. \u0026amp; Mullaney, P. D. Within-litter variation in the performance of piglets to three weeks of age. \u003cem\u003eAnimal Science\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 351\u0026ndash;357 (1976).\u003c/li\u003e\n\u003cli\u003eHuting, A. M. S., Sakkas, P., Wellock, I., Almond, K. \u0026amp; Kyriazakis, I. Once small always small? To what extent morphometric characteristics and post-weaning starter regime affect pig lifetime growth performance. \u003cem\u003ePorcine Health Management\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 21 (2018).\u003c/li\u003e\n\u003cli\u003eFraser, D. \u0026amp; Thompson, B. K. Variation in piglet weights: relationship to suckling behavior, parity number and farrowing crate design. \u003cem\u003eCan. J. Anim. Sci.\u003c/em\u003e \u003cstrong\u003e66\u003c/strong\u003e, 31\u0026ndash;46 (1986).\u003c/li\u003e\n\u003cli\u003eRydhmer, L. Genetics of sow reproduction, including puberty, oestrus, pregnancy, farrowing and lactation. \u003cem\u003eLivestock Production Science\u003c/em\u003e \u003cstrong\u003e66\u003c/strong\u003e, 1\u0026ndash;12 (2000).\u003c/li\u003e\n\u003cli\u003eKing, R. H., Mullan, B. P., Dunshea, F. R. \u0026amp; Dove, H. The influence of piglet body weight on milk production of sows. \u003cem\u003eLivestock Production Science\u003c/em\u003e \u003cstrong\u003e47\u003c/strong\u003e, 169\u0026ndash;174 (1997).\u003c/li\u003e\n\u003cli\u003eBanville, M., Riquet, J., Bahon, D., Sourdioux, M. \u0026amp; Canario, L. Genetic parameters for litter size, piglet growth and sow\u0026rsquo;s early growth and body composition in the Chinese-European line Tai Zumu. \u003cem\u003eJournal of Animal Breeding and Genetics\u003c/em\u003e \u003cstrong\u003e132\u003c/strong\u003e, (2014).\u003c/li\u003e\n\u003cli\u003eSolanes, F. X. \u003cem\u003eet al.\u003c/em\u003e Direct and maternal influences on the early growth, fattening performance, and carcass traits of pigs. \u003cem\u003eLivestock Production Science\u003c/em\u003e \u003cstrong\u003e88\u003c/strong\u003e, 199\u0026ndash;212 (2004).\u003c/li\u003e\n\u003cli\u003eHojgaard, C. K., Bruun, T. S. \u0026amp; Theil, P. K. Impact of milk and nutrient intake of piglets and sow milk composition on piglet growth and body composition at weaning. \u003cem\u003eJ Anim Sci\u003c/em\u003e \u003cstrong\u003e98\u003c/strong\u003e, 1\u0026ndash;12 (2020).\u003c/li\u003e\n\u003cli\u003eHurley, W. L. Mammary gland growth in the lactating sow. \u003cem\u003eLivestock Production Science\u003c/em\u003e \u003cstrong\u003e70\u003c/strong\u003e, 149\u0026ndash;157 (2001).\u003c/li\u003e\n\u003cli\u003eLundgren, H. \u003cem\u003eet al.\u003c/em\u003e Genetic parameters for feed intake, litter weight, body condition and rebreeding success in primiparous Norwegian Landrace Sows. \u003cem\u003eAnimal : an international journal of animal bioscience\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 1\u0026ndash;10 (2013).\u003c/li\u003e\n\u003cli\u003eBalzani, A., Cordell, H. J. \u0026amp; Edwards, S. A. Relationship of sow udder morphology with piglet suckling behavior and teat access. \u003cem\u003eTheriogenology\u003c/em\u003e \u003cstrong\u003e86\u003c/strong\u003e, 1913\u0026ndash;1920 (2016).\u003c/li\u003e\n\u003cli\u003eDevillers, N., Giraud, D. \u0026amp; Farmer, C. Neonatal piglets are able to differentiate more productive from less productive teats. \u003cem\u003eApplied Animal Behaviour Science\u003c/em\u003e \u003cstrong\u003e174\u003c/strong\u003e, 24\u0026ndash;31 (2016).\u003c/li\u003e\n\u003cli\u003eVasdal, G. \u0026amp; Andersen, I. L. A note on teat accessibility and sow parity \u0026mdash; consequences for newborn piglets. \u003cem\u003eLivestock Science\u003c/em\u003e \u003cstrong\u003e146\u003c/strong\u003e, 91\u0026ndash;94 (2012).\u003c/li\u003e\n\u003cli\u003eIllmann, G., Chaloupkov\u0026aacute;, H. \u0026amp; Neuhauserov\u0026aacute;, K. Effect of pre- and post-partum sow activity on maternal behaviour and piglet weight gain 24h after birth. \u003cem\u003eAppli Anim Behav Sci\u003c/em\u003e \u003cstrong\u003e163\u003c/strong\u003e, 80\u0026ndash;88 (2015).\u003c/li\u003e\n\u003cli\u003eGirardie, O. \u003cem\u003eet al.\u003c/em\u003e Analysis of image-based sow activity patterns reveals several associations with piglet survival and early growth. \u003cem\u003eFront. Vet. Sci.\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eMiles, J. R. \u003cem\u003eet al.\u003c/em\u003e Contributions of the maternal uterine environment and piglet genotype on weaning survivability potential: II. Piglet growth, lactation performance, milk composition, and piglet blood profiles during lactation following reciprocal embryo transfers between Meishan and White crossbred gilts. \u003cem\u003eJ Anim Sci\u003c/em\u003e \u003cstrong\u003e93\u003c/strong\u003e, 1555\u0026ndash;1564 (2015).\u003c/li\u003e\n\u003cli\u003eCanario, L., Billon, Y. Y., Morm\u0026egrave;de, P., Poirel, D. \u0026amp; Moigneau, C. Temperament, adaptation and maternal abilities of Meishan and Large White sows kept in a loosehousing system during lactation. in (2009).\u003c/li\u003e\n\u003cli\u003eFarmer, C., Palin, M.-F., Sorensen, M. \u0026amp; Robert, S. Lactational performance, nursing and maternal behavior of Upton-Meishan and Large White sows. \u003cem\u003eCanadian Journal of Animal Science\u003c/em\u003e \u003cstrong\u003e81\u003c/strong\u003e, 487\u0026ndash;493 (2001).\u003c/li\u003e\n\u003cli\u003eSinclair, A. G., Edwards, S. A., Hoste, S. \u0026amp; McCartney, A. Evaluation of the influence of maternal and piglet breed differences on behaviour and production of Meishan synthetic and European White breeds during lactation. \u003cem\u003eAnim. Sci.\u003c/em\u003e \u003cstrong\u003e66\u003c/strong\u003e, 423\u0026ndash;430 (1998).\u003c/li\u003e\n\u003cli\u003eCanario, L., Moigneau, C., Lagant, H., Billon, Y. \u0026amp; Bidanel, J. P. Comparaison des performances de reproduction et des aptitudes maternelles de truies Meishan et Large White \u0026eacute;lev\u0026eacute;es en enclos individuels de la mise bas au sevrage. in vol. 40 137\u0026ndash;140 (2008).\u003c/li\u003e\n\u003cli\u003eFarmer and S. Robert, C. Hormonal, behavioural and performance characteristics of Meishan sows during pregnancy and lactation. \u003cem\u003eCan. J. Anim. Sci.\u003c/em\u003e \u003cstrong\u003e83\u003c/strong\u003e, 1\u0026ndash;12 (2003).\u003c/li\u003e\n\u003cli\u003eCraig, A., Gordon, A. \u0026amp; Magowan, E. Understanding the drivers of improved pig weaning weight by investigation of colostrum intake, sow lactation feed intake, or lactation diet specification1. \u003cem\u003eJournal of Animal Science\u003c/em\u003e \u003cstrong\u003e95\u003c/strong\u003e, 4499\u0026ndash;4509 (2017).\u003c/li\u003e\n\u003cli\u003eDividich, J. L., Charneca, R. \u0026amp; Thomas, F. Relationship between birth order, birth weight, colostrum intake, acquisition of passive immunity and pre-weaning mortality of piglets. \u003cem\u003eSpanish Journal of Agricultural Research\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, e0603\u0026ndash;e0603 (2017).\u003c/li\u003e\n\u003cli\u003eOcepek, M., Newberry, R. C. \u0026amp; Andersen, I. L. Trade-offs between litter size and offspring fitness in domestic pigs subjected to different genetic selection pressures. \u003cem\u003eAppli Anim Behav Sci\u003c/em\u003e \u003cstrong\u003e193\u003c/strong\u003e, 7\u0026ndash;14 (2017).\u003c/li\u003e\n\u003cli\u003eCronin, G. M. \u0026amp; Smith, J. A. Effects of accommodation type and straw bedding around parturition and during lactation on the behaviour of primiparous sows and survival and growth of piglets to weaning. \u003cem\u003eApplied Animal Behaviour Science\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e, 191\u0026ndash;208 (1992).\u003c/li\u003e\n\u003cli\u003eKim, J. S., Yang, X., Pangeni, D. \u0026amp; Baidoo, S. K. Relationship between backfat thickness of sows during late gestation and reproductive efficiency at different parities. \u003cem\u003eActa Agriculturae Scandinavica, Section A \u0026mdash; Animal Science\u003c/em\u003e \u003cstrong\u003e65\u003c/strong\u003e, 1\u0026ndash;8 (2015).\u003c/li\u003e\n\u003cli\u003eCools, A. \u003cem\u003eet al.\u003c/em\u003e Ad libitum feeding during the peripartal period affects body condition, reproduction results and metabolism of sows. \u003cem\u003eAnimal Reproduction Science\u003c/em\u003e \u003cstrong\u003e145\u003c/strong\u003e, 130\u0026ndash;140 (2014).\u003c/li\u003e\n\u003cli\u003eTummaruk, P., Sumransap, P. \u0026amp; Jiebna, N. Fat and whey supplementation influence milk composition, backfat loss, and reproductive performance in lactating sows. \u003cem\u003eTrop Anim Health Prod\u003c/em\u003e \u003cstrong\u003e46\u003c/strong\u003e, 753\u0026ndash;758 (2014).\u003c/li\u003e\n\u003cli\u003eGenest, M. \u0026amp; D\u0026rsquo;Allaire, S. Feeding strategies during the lactation period for first-parity sows. \u003cem\u003eCan. J. Anim. Sci.\u003c/em\u003e \u003cstrong\u003e75\u003c/strong\u003e, 461\u0026ndash;467 (1995).\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;, L., Latorre, M. \u0026Aacute;. \u0026amp; \u0026Aacute;lvarez-Rodr\u0026iacute;guez, J. Does Ad Libitum Feeding during the Peri-Partum Improve the Sow Feed Intake and Performances? \u003cem\u003eAnimals\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 1078 (2019).\u003c/li\u003e\n\u003cli\u003eFarmer, C. \u0026amp; Edwards, S. A. Review: Improving the performance of neonatal piglets. \u003cem\u003eanimal\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 100350 (2022).\u003c/li\u003e\n\u003cli\u003eRauw, W. M. \u003cem\u003eet al.\u003c/em\u003e Behavioural differences in non-reproductive adult females in a long-term selection experiment for litter size in mice. \u003cem\u003eApplied Animal Behaviour Science\u003c/em\u003e \u003cstrong\u003e66\u003c/strong\u003e, 249\u0026ndash;262 (2000).\u003c/li\u003e\n\u003cli\u003eStrathe, A. V., Bruun, T. S. \u0026amp; Hansen, C. F. Sows with high milk production had both a high feed intake and high body mobilization. \u003cem\u003eanimal\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 1913\u0026ndash;1921 (2017).\u003c/li\u003e\n\u003cli\u003ePeng, J. J., Somes, S. A. \u0026amp; Rozeboom, D. W. Effect of system of feeding and watering on performance of lactating sows1. \u003cem\u003eJournal of Animal Science\u003c/em\u003e \u003cstrong\u003e85\u003c/strong\u003e, 853\u0026ndash;860 (2007).\u003c/li\u003e\n\u003cli\u003eFraser, D. \u0026amp; Phillips, P. A. Lethargy and low water intake by sows during early lactation: A cause of low piglet weight gains and survival? \u003cem\u003eAppli Anim Behav Sci\u003c/em\u003e \u003cstrong\u003e24\u003c/strong\u003e, 13\u0026ndash;22 (1989).\u003c/li\u003e\n\u003cli\u003eJensen, P., Stangel, G. \u0026amp; Algers, B. Nursing and suckling behaviour of semi-naturally kept pigs during the first 10 days postpartum. \u003cem\u003eApplied Animal Behaviour Science\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 195\u0026ndash;209 (1991).\u003c/li\u003e\n\u003cli\u003eCanario, L. \u003cem\u003eet al.\u003c/em\u003e Between-breed variability of stillbirth and its relationship with sow and piglet characteristics. \u003cem\u003eJournal of Animal Science\u003c/em\u003e \u003cstrong\u003e84\u003c/strong\u003e, 3185\u0026ndash;3196 (2006).\u003c/li\u003e\n\u003cli\u003eOliviero, C., Heinonen, M., Valros, A., H\u0026auml;lli, O. \u0026amp; Peltoniemi, O. A. T. Effect of the environment on the physiology of the sow during late pregnancy, farrowing and early lactation. \u003cem\u003eAnimal Reproduction Science\u003c/em\u003e \u003cstrong\u003e105\u003c/strong\u003e, 365\u0026ndash;377 (2008).\u003c/li\u003e\n\u003cli\u003eIslas-Fabila, P. \u003cem\u003eet al.\u003c/em\u003e Effect of thiamine pyrophosphate on the characteristics of farrowing and piglet vitality. \u003cem\u003eTheriogenology\u003c/em\u003e \u003cstrong\u003e200\u003c/strong\u003e, 49\u0026ndash;59 (2023).\u003c/li\u003e\n\u003cli\u003eZaleski, H. M. \u0026amp; Hacker, R. R. Variables related to the progress of parturition and probability of stillbirth in swine. \u003cem\u003eCan Vet J\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e, 109\u0026ndash;113 (1993).\u003c/li\u003e\n\u003cli\u003eCanario, L., Bidanel, J.-P. \u0026amp; Rydhmer, L. Genetic trends in maternal and neonatal behaviors and their association with perinatal survival in French Large White swine. \u003cem\u003eFront. Genet.\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, (2014).\u003c/li\u003e\n\u003cli\u003eChen, C. \u003cem\u003eet al.\u003c/em\u003e Maternal infanticide in sows: Incidence and behavioural comparisons between savaging and non-savaging sows at parturition. \u003cem\u003eApplied Animal Behaviour Science\u003c/em\u003e \u003cstrong\u003e109\u003c/strong\u003e, 238\u0026ndash;248 (2008).\u003c/li\u003e\n\u003cli\u003eKnap, P. W. \u0026amp; Merks, J. W. M. A note on the genetics of aggressiveness of primiparous sows towards their piglets. \u003cem\u003eLivestock Production Science\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 161\u0026ndash;167 (1987).\u003c/li\u003e\n\u003cli\u003eQuilter, C. R. \u003cem\u003eet al.\u003c/em\u003e Porcine maternal infanticide as a model for puerperal psychosis. \u003cem\u003eAmerican Journal of Medical Genetics Part B: Neuropsychiatric Genetics\u003c/em\u003e \u003cstrong\u003e144B\u003c/strong\u003e, 862\u0026ndash;868 (2007).\u003c/li\u003e\n\u003cli\u003evan der Steen, H. A. M., Schaeffer, L. R., de Jong, H. \u0026amp; de Groot, P. N. Aggressive Behavior of Sows at Parturition. \u003cem\u003eJournal of Animal Science\u003c/em\u003e \u003cstrong\u003e66\u003c/strong\u003e, 271\u0026ndash;279 (1988).\u003c/li\u003e\n\u003cli\u003eCabrera, R. A., Lin, X., Campbell, J. M., Moeser, A. J. \u0026amp; Odle, J. Influence of birth order, birth weight, colostrum and serum immunoglobulin G on neonatal piglet survival. \u003cem\u003eJournal of Animal Science and Biotechnology\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 42 (2012).\u003c/li\u003e\n\u003cli\u003eDecaluw\u0026eacute;, R. \u003cem\u003eet al.\u003c/em\u003e Piglets׳ colostrum intake associates with daily weight gain and survival until weaning. \u003cem\u003eLivest Sci\u003c/em\u003e \u003cstrong\u003e162\u003c/strong\u003e, 185\u0026ndash;192 (2014).\u003c/li\u003e\n\u003cli\u003eDividich, J. L., Rooke, J. A. \u0026amp; Herpin, P. Nutritional and immunological importance of colostrum for the new-born pig. \u003cem\u003eThe Journal of Agricultural Science\u003c/em\u003e \u003cstrong\u003e143\u003c/strong\u003e, 469\u0026ndash;485 (2005).\u003c/li\u003e\n\u003cli\u003eValros, A. \u003cem\u003eet al.\u003c/em\u003e Metabolic state of the sow, nursing behaviour and milk production. \u003cem\u003eLivestock Production Science\u003c/em\u003e \u003cstrong\u003e79\u003c/strong\u003e, 155\u0026ndash;167 (2003).\u003c/li\u003e\n\u003cli\u003eValros, A. E. \u003cem\u003eet al.\u003c/em\u003e Nursing behaviour of sows during 5 weeks lactation and effects on piglet growth. \u003cem\u003eApplied Animal Behaviour Science\u003c/em\u003e \u003cstrong\u003e76\u003c/strong\u003e, 93\u0026ndash;104 (2002).\u003c/li\u003e\n\u003cli\u003eYun, J. \u003cem\u003eet al.\u003c/em\u003e Prepartum nest-building has an impact on postpartum nursing performance and maternal behaviour in early lactating sows. \u003cem\u003eAppli Anim Behav Sci\u003c/em\u003e \u003cstrong\u003e160\u003c/strong\u003e, 31\u0026ndash;37 (2014).\u003c/li\u003e\n\u003cli\u003eMarchant Forde, J. N. Piglet- and stockperson-directed sow aggression after farrowing and the relationship with a pre-farrowing, human approach test. \u003cem\u003eApplied Animal Behaviour Science\u003c/em\u003e \u003cstrong\u003e75\u003c/strong\u003e, 115\u0026ndash;132 (2002).\u003c/li\u003e\n\u003cli\u003eValros, A., Rundgren, M., \u0026Scaron;pinka, M., Saloniemi, H. \u0026amp; Algers, B. Sow activity level, frequency of standing-to-lying postural changes and anti-crushing behaviour\u0026mdash;within sow-repeatability and interactions with nursing behaviour and piglet performance. \u003cem\u003eAppli Anim Behav Sci\u003c/em\u003e \u003cstrong\u003e83\u003c/strong\u003e, 29\u0026ndash;40 (2003).\u003c/li\u003e\n\u003cli\u003eLefort, G. \u003cem\u003eet al.\u003c/em\u003e The maturity in fetal pigs using a multi-fluid metabolomic approach. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 19912 (2020).\u003c/li\u003e\n\u003cli\u003eDourmad, J.-Y. \u003cem\u003eet al.\u003c/em\u003e InraPorc : un outil d\u0026rsquo;aide \u0026agrave; la d\u0026eacute;cision pour l\u0026rsquo;alimentation des truies reproductrices. (2022).\u003c/li\u003e\n\u003cli\u003eGrandinson, K., Rydhmer, L., Strandberg, E. \u0026amp; Thodberg, K. Genetic analysis of on-farm tests of maternal behaviour in sows. \u003cem\u003eLivest Prod Sci\u003c/em\u003e \u003cstrong\u003e83\u003c/strong\u003e, 141\u0026ndash;151 (2003).\u003c/li\u003e\n\u003cli\u003eEgozcue, J. J., Pawlowsky-Glahn, V., Mateu-Figueras, G. \u0026amp; Barcel\u0026oacute;-Vidal, C. Isometric Logratio Transformations for Compositional Data Analysis. \u003cem\u003eMathematical Geology\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 279\u0026ndash;300 (2003).\u003c/li\u003e\n\u003cli\u003ePag\u0026egrave;s, J. \u003cem\u003eMultiple Factor Analysis by Example Using R\u003c/em\u003e. (Chapman and Hall/CRC, 2014). doi:10.1201/b17700.\u003c/li\u003e\n\u003cli\u003eHusson, F., Josse, J., Narasimhan, B. \u0026amp; Robin, G. Imputation of mixed data with multilevel singular value decomposition. \u003cem\u003eJournal of Computational and Graphical Statistics\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 552 (2019).\u003c/li\u003e\n\u003cli\u003eBougeard, S., Qannari, E. M., Lupo, C. \u0026amp; Hanafi, M. From multiblock partial least squares to multiblock redundancy analysis. A continuum approach. \u003cem\u003eInformatica\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 11\u0026ndash;26 (2011).\u003c/li\u003e\n\u003cli\u003eBougeard, S. \u0026amp; Cardinal, M. Multiblock modeling for complex preference study. Application to European preferences for smoked salmon. \u003cem\u003eFood Quality and Preference\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 56\u0026ndash;64 (2014).\u003c/li\u003e\n\u003cli\u003eAbdi, H., Williams, L. J., Valentin, D. \u0026amp; Bennani-Dosse, M. STATIS and DISTATIS: optimum multitable principal component analysis and three way metric multidimensional scaling. \u003cem\u003eWIREs Comp Stat\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 124\u0026ndash;167 (2012).\u003c/li\u003e\n\u003cli\u003eThioulouse, J. Simultaneous Analysis of a Sequence of Paired Ecological Tables: A Comparison of Several Methods. \u003cem\u003eAnnals of Applied Statistics\u003c/em\u003e \u003cstrong\u003e5\u003c/strong\u003e, 2300\u0026ndash;2325 (2011).\u003c/li\u003e\n\u003cli\u003eDray, S. \u0026amp; Dufour, A.-B. The ade4 Package: Implementing the Duality Diagram for Ecologists. \u003cem\u003eJournal of Statistical Software\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 1\u0026ndash;20 (2007).\u003c/li\u003e\n\u003cli\u003eR Core Team. R: A language and environment for statistical computing (Version 4.0. 5)[Computer software]. \u003cem\u003eR Foundation for Statistical Computing\u003c/em\u003e (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3836704/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3836704/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLarge White and Meishan sows differ in maternal ability and early piglet growth. We investigated the relationships between piglet growth over three periods after birth (D0-D1, D1-D3 and D3-D7; D0 starting at the onset of farrowing) and 101 maternal traits, grouped into 11 blocks according to the biological function they describe. Within and between breed variation was exploited to account for a maximum of variability. The objective was to quantify the contribution of maternal traits to early piglet growth. The relationships were analyzed with multiblock and triadic partial analyses. Several behavioral traits (standing activity, reactivity, postural) and functional traits (body reserves, teat quality) at farrowing had substantial contributions to piglet growth from D0 to D7. Sow aggressiveness towards piglets and time spent standing at D0 were unfavorably correlated to D1-D3 growth. Time spent lying with udder exposed at D0 was favorably correlated to D1-D3 growth. The farrowing duration was negatively correlated to growth from D0 to D3. Furthermore, D3-D7 growth was positively correlated to feed intake in the same period. Several behavior traits and some functional traits play part in early piglet growth, with a greater contribution of sow behavior in the critical period around farrowing than in later days.\u003c/p\u003e","manuscriptTitle":"Sow behavior on the day of farrowing: The main determinant of early piglet growth among maternal ability traits","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-29 09:00:58","doi":"10.21203/rs.3.rs-3836704/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-09T11:09:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-03T09:36:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c041403b-fd26-4419-be40-30f6e869c46b_SNPRID","date":"2024-03-21T08:04:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0a1a8b6c-c077-42fe-bbb4-7e3bb9fb0194","date":"2024-03-19T12:40:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-14T16:02:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8c816892-25b2-4834-8996-bd8af664702e","date":"2024-03-14T11:42:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-06T11:16:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-02-22T11:44:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-01-25T09:02:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-25T08:58:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-01-05T08:18:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8fccb9c2-cb14-4b47-b502-e00cdef14c4c","owner":[],"postedDate":"January 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-12T16:01:10+00:00","versionOfRecord":{"articleIdentity":"rs-3836704","link":"https://doi.org/10.1038/s41598-024-69358-8","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-08-08 15:57:17","publishedOnDateReadable":"August 8th, 2024"},"versionCreatedAt":"2024-01-29 09:00:58","video":"","vorDoi":"10.1038/s41598-024-69358-8","vorDoiUrl":"https://doi.org/10.1038/s41598-024-69358-8","workflowStages":[]},"version":"v1","identity":"rs-3836704","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3836704","identity":"rs-3836704","version":["v1"]},"buildId":"ApUGefWb6u5IBVtyqm6d5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}