<p/>In pig breeding it is quite common to select for bodyweight gain, feed conversion and slaughter quality. Various values have been found by different research- workers for the relationships between these traits. These differences in values have mainly been caused by differences between feeding levels and by those between chemical composition of carcases. Protein and fat deposition can be calculated from bodyweight gain and feed intake; these traits would take into account differences in feeding level and. chemical composition of carcases better than bodyweight gain and feed conversion do.<p/>Therefore an investigation was done<br/>- to find out how precisely protein and fat deposition could be predicted from bodyweight gain, bodyweight and feed intake, and<br/>- to study the variation in protein and fat deposition at restricted and ad libitum feeding and the relation between these factors, growth and carcase traits.<p/>For the calculation of protein and fat deposition three models were obtained from data in the literature (EBC, EBK and MEK models - Section 2.3). These models were based on physiological data connected with bodyweight and feed utilization (maintenance, protein and fat deposition).<p/>In the MEK model it was assumed that all ME was used for maintenance, protein and fat deposition according to the following equation:<br/><em>ME = ME <sub><font size="-1">M</font></sub> + c ΔP + d ΔF.</em><p/>The EBC and EBK models started from the energy balance:<br/><em>EB = 5.7 ΔP + 9.46 ΔF.</em><p/>In order to estimate the amount of <em>ME <sub><font size="-1">P</font></sub></em> or <em>EB</em> that was used for protein and fat deposition, respectively, the research-workers calculated from literature or their own data the relationships between the components of growth. <em>EB</em> was calculated from <em>ME</em> using the equation<br/><em>EB = (ME - ME <sub><font size="-1">M</font></sub> )</em> x efficiency.<p/>The equations that were used to calculate protein <em>(ΔP)</em> and fat <em>(ΔF)</em> deposition in the EBC, EM and MEK models, were:<br/><img src="/wda/abstracts/i605_1.gif" height="163" width="600"/><p/>In these models 4 factors were varied:<br/>- maintenance requirement: 80, 100 or 120 kcal <em>ME/kg</em><sup><font size="-1">3/4</font></SUP>;<br/>- efficiency for synthesizing protein and fat from <em>ME <sub><font size="-1">P</font></sub> .</em> For the EBC and EBK models the same figure was assumed for protein as for fat: 0. 55, 0.65 or 0. 75. In the MEK model the <em>ME</em> costs (kcal/g) for synthesizing protein and fat were assumed to be: 16 and 13, 13 and 13, or 11.4 and 12.6;<br/>- the ratio protein to protein + water in the EBC model: a constant value was assumed or a value was calculated from the amount of protein and water at each bodyweight. These amounts have been estimated using allometric equations;<br/>- the amounts of protein, water and fat gain (in the EBC model) or the amount of bodyweight gain minus gut fill (in the EBK and MEK models). The alternative values of this factor have been obtained using linear or allometric equations between bodyweight and the amounts of ash and gut fill or gut fill.<p/>The equations or values used for calculating the values of the 4 factors are shown in Table 3.4.<p/>To judge the precision of the prediction of protein and fat deposition the following 4 traits were calculated:<br/>- the level of protein and fat deposition;<br/>- the values of correlation coefficients between calculated and found protein and fat deposition.<p/>The data used consisted of energy and N balances from 6 different investigations, and results of chemical analysis of the empty body of pigs. In addition, bodyweight gain was estimated using a cubic curve in 3 sets of data mentioned above. Thus, totally 10 sets of data were available for the computations. For the computations the values of correlation coefficients between calculated and found protein and fat deposition were transformed by the Z transformation of FISHER.<p/>With the statistical Model 3.1, the following effects were tested for each trait and each model:<br/>- differences between sets of data,<br/>- differences between factors, and<br/>- differences between models.<p/>The level of the four traits differed considerably between the various sets of data (Tables 3.5 and 3.7). In addition the interaction between data and factors was always significant. These interactions are also shown in Table 3.6 by the great differences between sets of data for the values of regression coefficients of the traits on the factors. The differences between sets of data might be caused by:<br/>- differences between feeding level, feed composition, sex or breed;<br/>- systematic differences between experimental procedures used by the research workers for energy and N balances, weighings etc.<p/>Computation of bodyweight gain from a cubic curve doubled the value of the correlation coefficient between calculated and found protein deposition in JUST NIELSEN's data, compared with those, found by using the weight gain obtained from linear interpolation between 2 weighings. Using a cubic curve, in LUDVIGSEN and THORBEK's data the same value of correlation coefficient was found, and in BREIREM's data a lower value, compared with those obtained by calculating bodyweight gain from linear interpolation. The value of the correlation coefficient between calculated and found fat deposition in JUST NIELSEN's data was 0.970, using data from energy balances, compared with 0.257 using chemical analysis of the empty body. With reference to JUST NIELSEN (1970), it has been stated that more data are necessary to be sure about the value and precision of results from energy and N balances or from comparative slaughter techniques.<p/>It has been indicated that the interactions between factors and sets of data have been partly caused by systematic differences in the various sets of data between bodyweights of the pigs (Table 3.14).<p/>The relative contribution of the variance in calculated protein and fat deposition to differences between sets of data was 60 to 70 % in the three models; the relative contribution to this effect by the variance in the value of correlation coefficients between calculated and found protein and fat deposition was 95 to 99 % (Table 3.8). The relative contribution of the variance in protein and fat deposition to the factors, maintenance and efficiency was - excluding protein deposition in the MEK Model - considerably higher than their contribution to the other two factors.<p/>If a higher maintenance requirement, a lower efficiency or a greater amount of water in the bodyweight gain were considered, the protein deposition and the value of the correlation coefficient between calculated and found protein deposition increased; however, then the fat deposition and the value of correlation coefficient between calculated and found fat deposition decreased (Tables 3.6 and 3.15). These changes in protein and fat deposition follow from the equations in Section 2.3, but they can also be explained by the difference between energy content of protein and fat. The changes in the values of correlation coefficients between calculated and found protein and fat deposition has been explained by a non-linear relationship between calculated and found protein and fat deposition.<p/>It is doubtful, whether the highest values of the correlation coefficients between calculated and found protein deposition also gave the best prediction of these traits.<p/>There were only small differences between the 3 models (Table 3.10). The value of 4.6838 for <em>LBM</em> /protein in the EBK and MEK models was lower than it should be, if based on the average bodyweight of the pigs in the various sets of data. Therefore with this value, protein deposition was overestimated and fat deposition was underestimated. The values of correlation coefficients between calculated and found protein deposition were significantly lower in the MEK model than in the EBC and EBK models.<p/>The equations used for the calculation of protein and fat deposition in Chapter 4 were based on the EBK model. To make a choice between the different combinations of the 4 factors it was assumed that:<br/>- maintenance requirement is 100 kcal <em>ME/kg</em><sup><font size="-1">3/4</font></SUP>, <em></em><br/>- protein deposition using <em>N</em> balances was overestimated by 15.5 %, and<br/>- 'real' <em>EB</em> was: 9.46 Δ <em>F</em> (found) + 5.7 (1-0.845) Δ <em>P</em> (found).<p/>If this 'real' <em>EB</em> was taken into account, a value of 0.62 for the factor efficiency was obtained. For the factor <em>LBM</em> /protein the value was used, that was obtained at each bodyweight from the bodyweight and the amount of fat, gut fill and protein, using allometric equations (Table 3.3). Δ <em>L <sub><font size="-1">E</font></sub></em> was calculated from the bodyweight and amount of gut fill changing linearly in relation to weight.<p/>The variation in protein and fat deposition and the relation between these traits, growth and carcase traits were investigated in pigs fed restrictedly and ad libitum. The data of the restrictedly fed pigs were obtained from 356 males, 540 castrated males and 770 females of the DL and DY breeds (Table 4.2). The data of the ad libitum fed pigs were obtained from 29 progeny groups (4 to 9 DL females per group) of sires (Table 4.4). The restrictedly fed pigs were tested from 25 to 100 kg bodyweight, and the feed was adjusted according to liveweight (Table 4.1). The ad libitum fed pigs got the same ration. They were fattened - starting at an age of about 9 weeks - for 4 or 6 months. The pigs were divided at random between treatments within litters and within pens. The bodyweight at each day was computed using a cubic curve. For the restrictedly fed pigs it was assumed that the feeding level was proportional to the feeding schedule advised (Table 4.1). For the ad libitum fed pigs the daily feed intake was computed from the weekly intakes by the method of 'parabolic splines'.<p/>The course of protein and fat deposition of restrictedly fed males, females and castrated males in relation to bodyweight was in rather good agreement with the data in literature (Figure 4. 1). The protein deposition in castrated males and females of the DL breed was significantly lower than those in the DY breed from about 45 kg onwards; in males of DL breed the protein deposition was lower during the whole testing period. At the end of the testing period the difference between males and females was about +40 g protein per day. At that moment the difference between females and castrated males was +7 g protein in the DL breed and + 16 g in the DY breed. The average difference between breeds and between sexes for the whole testing period are given in Table 4.9. The average daily protein deposition was 7.53 g higher in the DY breed than it was in the DL breed, and the fat deposition was 4.90 g lower in the DY breed. The differences between sexes were smaller than those mentioned in the literature. Probably, these smaller differences were partly caused by an underestimation of maintenance in pigs with a higher protein deposition. In ad libitum fed pigs the average daily protein deposition was about 25 % lower than in restrictedly fed pigs, and the daily fat deposition was about 25 % higher (Tables 4.8 and 4.11). These differences could be partly attributed to wastage of feed with self-feeders, by differences in activity between restrictedly fed pigs (housed individually) and the ad libitum fed pigs (housed in groups) and the possible influence of the feeding level on the ratio <em>LBM</em> to protein.<p/>The coefficients of variation of daily protein deposition was 1.6 times higher than those of bodyweight gain and feeding level; the coefficients of variation of daily fat deposition were 30% lower. The values of the heritabilities of protein and fat deposition were 0.176 and 0.080. These values computed for the traits bodyweight gain, feed conversion and backfat thickness were 0.249, 0.231 and 0.545, respectively.<p/>The values of correlation coefficients between protein deposition and bodyweight gain in restrictedly fed pigs were nearly +1. It was argued that these values were to be expected when the feeding schedule was according to bodyweight. The values of correlation coefficients between bodyweight gain and feed conversion, and carcase traits were nearly the same compared with those between protein and fat deposition, and carcase traits (Tables 4.12 and 4.13). The values of correlation coefficients between protein deposition, fat deposition, bodyweight gain and feed conversion in ad libitum fed pigs were significantly lower than those in restrictedly fed pigs (Table 4.15). The value of the correlation coefficient between bodyweight gain and protein deposition in ad libitum fed pigs was in rather good agreement with the value found in literature (Table 4.17). The value of correlation coefficient between protein deposition and lean cuts (0.743) and this between fat deposition and backfat thickness (0.796) in ad libitum fed pigs were significantly higher than those in restrictedly fed pigs. However one should keep in mind that only 29 groups of pigs were fattened ad libitum. To make clear the variation in protein and fat deposition and the relationships between these traits and bodyweight gain, feed conversion and carcase traits, it is necessary to collect more energy and <em>N</em> balances of pigs fed individually and at various feeding levels.
|Qualification||Doctor of Philosophy|
|Award date||11 Dec 1974|
|Place of Publication||Wageningen|
|Publication status||Published - 1974|