Modelling approaches have been developed since the 1970s to predict the response of growing pigs to nutrient supply and to simulate their performance (growth, feed intake, lipid and protein deposition, etc.) [1
]. The models have been largely applied to conventional breeds. Indeed, performance data and information on diets are often necessary to parameterize the models or compare simulation results to observed performance. Additionally, to obtain reference parameters for a genotype, the modelling approach requires data obtained in conditions that allow full expression of animal potential for feed intake and growth. For conventional breeds, such data, for different stages or for the entire growth period, are numerous and easy to obtain from field trials or previously published studies. Experimental results on nutrient requirements are also abundant for modern pig genotypes. Some models have been used as decision tools to synthetize data on requirements, determine nutrient requirements, and identify adapted feeding strategies depending on the genotype (i.e., InraPorc) [3
Current knowledge on the growth and performance of local pig breeds is very limited. There have been few studies showing the specific metabolic characteristics of local breeds [5
] and their lower rates of growth and lean-tissue deposition [6
] compared to conventional, genetically improved pig breeds. This particular metabolic profile implies that they also have specific nutritional requirements. For autochthonous or local pig breeds, the data on their growth, feed ingestion capacity, and nutrient requirements are very scarce and of limited adequacy for modelling, except for more developed breeds, such as Iberian pigs. Although optimum dietary protein/energy ratios for growing and fattening Iberian pigs have been studied [7
], additional studies on different productive phases and on other local pig breeds are needed in order to acquire knowledge of their nutritional requirements prior to optimizing growth and performance of autochthonous pig breeds. Furthermore, to our knowledge, modelling approaches have not been applied yet to pigs from local breeds and/or reared in non-conventional systems. Indeed, studies on local breeds are often made in very diverse conditions of feeding and management, many of them reflecting the practical use. Only a small number of the studies performed on these breeds offer adequate data that allow for the evaluation of each breed’s potential for growth.
The present study aimed to apply a modelling approach with InraPorc model to determine the nutrient requirements of growing pigs from local breeds in the H2020 European Union project TREASURE.
3. Results and Discussion
InraPorc parameters and simulation results between 40 and 100 kg BW for the 16 profiles are presented in Table 2
Ages at 40 kg and 100 kg BW ranged between 110 and 206 days, and between 195 and 323 days, respectively. This difference between studied breeds is also revealed by profile parameters and may stem from genetic differences or in feeding management (or both) among breeds before the monitored growth period. It should be noted that in the InraPorc model, potential PD is driven by state (i.e., current protein content in body) and not by age [3
]. This means that in cases where two animals had the same BW at the start, even if they have very different ages, the same PD can be observed if the current protein content in body is close. As such, the period before the monitored growth period can influence the modelling results, for instance, by impacting the protein content in body at the start and thus potential PD in following period.
For the interval 40–100 kg BW, the PDm ranged between 41 and 105 g/d. This can be considered rather low when compared to values reported for conventional, genetically improved breeds. Applying the same procedure as in the present study, Vautier et al. [8
] obtained profiles from pigs of nine commercial pure or synthetic lines. In their results, the PDm for a 30–110 kg BW interval, quite comparable to the 40–100 kg BW interval in the present study, ranged between 130 and 166 g/day. Differences observed in PDm among the studied local breeds could reflect genetic differences. Alentejana, Cinta Senese, Mangalitsa, and Moravka presented PDm lower than 55 g/d, whereas others breeds had PDm higher than 65 g/d. Data on protein deposition are scarce for local breeds, although in Iberian pigs, studies to determine protein deposition in different growing phases have been reported. Nieto et al. [16
] reported a PD of 74 g/day and Barea et al. [6
] reported a PD of 71 g/day for Iberian pigs followed, respectively, from 15 to 50 kg BW and from 50 to 100 kg BW and fed adequate protein diets to each phase at a feed intake level close to ad libitum
. These values are close to those obtained in this simulation study.
The average daily gain (ADG) ranged between 389 to 854 g/d. Even if the relation between PDm and ADG is not strictly linear, breeds with higher PDm presented higher ADG, and conversely, breeds with lower PDm presented lower ADG (Figure 1
). Local breeds are known to have lower growth potential, and thus lower protein deposition rates, than conventional breeds that can reach ADG values higher than 1000 g/d in optimal conditions under intensive rearing systems. Candek-Potokar et al. [17
] have reviewed the performance characteristics of local pig breeds, including those of the present study, for different growth periods. For the period 30–100 kg BW, quite comparable to the BW range chosen in our study, the pooled average ADG found for the breeds selected was 477 g/d vs. 590 g/d obtained in the present study. Some profiles fitted well with data from Candek-Potokar et al. [17
]. For instance, those authors reported an ADG of 483 g/d for the Alentejana breed, 508 g/d for the Moravka breed, and 412 g/d for the Cinta Senese breed vs. 459 g/d, 550 g/d, and 389 g/d, respectively, in the present study. Conversely, larger differences were observed for the Krškopolje pig (580 g/d vs. 854 g/d in the present study) or the Apulo Calabrese breed (418 vs. 760 g/d in the present study), for instance. This can be partly explained by the type of data used for calibration and by ad libitum
simulation compared to field practices.
In the studied local breeds, BGompertz
ranged between 0.0024 and 0.0183/d. As for growth potential, local breeds presented lower values than conventional breeds. Vautier et al. [8
] reported BGompertz
ranging between 0.0129 and 0.0256/day for conventional breeds. This indicates that local breeds have generally less intensive but more persistent growth than conventional breeds. However, the range of BGompertz
values also reflects a large difference between the studied local breeds.
The ADFI, NE50
, and NE100
values ranged between 18.5 and 27.2 MJ NE/d, 15.7 and 24 MJ NE/d, and 19.3 and 35.2 MJ NE/d, respectively. The breeds with higher ADGs presented generally higher ADFI even if the relationship was not strict (Figure 2
). For conventional breeds, Vautier et al. [8
] reported NE50
values ranging between 18.6 and 24.0 MJ NE/d and for NE100 ranging between 23.7 and 31.2 MJ NE/d. The difference between conventional and local breeds is not so clear here. In the present study, we collected data in feeding conditions that were supposed to be ad libitum
. Assuming a ratio NE/metabolizable energy (ME) of 0.74 and the NRC (National Research Council) value for ME for maintenance (448 kJ ME per kg BW0.75; [4
]), and using feed allowance indicated in Table 1
, it can be estimated then that feed allowance ranged in our data from 2.23 (Iberian study 1) to 3.32 (Mangalitsa and Moravka) times ME for maintenance. In reference to the assumption that voluntary DFI equals approximately 3 to 4 times the ME requirements for maintenance, some breeds could have been somewhat below ad libitum
The average SID lysine requirement between 40 and 100 kg BW ranged between 5.2 to 12.8 g/d. In the present study, the SID lysine requirements accounted for between 25% and 75% of dietary supplies, indicating that the studied breeds were not limited in lysine supply in this simulation. There is a clear and logical relationship between lysine requirement and PDm or ADG, with the breeds with higher PDm or ADG presenting higher requirements. Indeed, the SID lysine requirement is mainly due to protein deposition. In addition to average values, the InraPorc model allows the kinetics of evolution to be described for different criteria. The evolution of SID lysine requirements for the obtained profiles depending on BW is presented in Figure 3
. A diversity of kinetics is observed beyond the range of mean values, also linked to BGompertz
values, which are indicators of the shape of growth rate and PD curves, as explained above. For instance, the simulations for the two profiles of the Alentejana breed resulted in similar SID lysine requirements but different kinetics. For the Alentejana_1 profile, the kinetic indicates a decrease of requirements in the 40–100 kg BW range, whereas the kinetic for the Alentejana_2 profile is flatter. This can be linked to the higher BGompertz
value for the Alentejana_1 profile compared to the Alentejana_2 profile. More generally, in the present study, the profiles with higher BGompertz
values presented more pronounced curves for SID lysine requirement kinetics.
The energy retained in protein and lipid ranged between 0.97 and 2.77 MJ/d and 7.28 and 14.95 MJ/d, respectively (Figure 4
). The total energy retention ranged between 9.22 and 16.88 MJ/d. In all breeds and profiles, a low proportion (8% to 21%) of total energy retention was directed towards protein, with the remaining proportion being dedicated to lipid deposition. In InraPorc, ingested energy is modeled as being used first for maintenance functions (including physical activity), with the remaining energy being used for protein deposition and then for lipid deposition. As such, lipid deposition is considered as an energy sink, as often the case for modelling approaches on pig growth [12
]. Energy deposition in the studied breeds, presenting low PD, is then oriented mainly to lipid deposition, which is taken into account in the model. This reflects also the observations that pigs from local breeds are considered to be fatty pigs, or at least fatter than conventional breeds [18
]. As indicated in the review of Candek-Potokar et al. [18
], the average lean meat percentage for the local breeds included in the present study was situated between 32.9% and 48.4%, and the average loin eye area was between 18.1 to 36.3 cm2
, which demonstrates low muscular development. With lower PDm than conventional breeds but comparable NE50
, a larger part of ingested and retained energy is dedicated to lipid deposition, explaining the higher fat composition of the carcasses of these breeds [18
The InraPorc profiles obtained in the present study reflect the genetic differences among the breeds concerning NE intake, growth capacity, and precocity of growth. For breeds where several profiles have been calibrated, profiles of the same breeds are more or less comparable. For instance, both of the Alentejana profiles have quite comparable parameters, except for BGompertz
. The differences among Iberian profiles are more pronounced on some parameters, such as BGompertz
between data source, or even for the same source, depending on the diet composition parameters (e.g., ADG). Calibration of profiles in InraPorc depends on the availability of data fitting with calibration process. InraPorc parameters in a profile representing a specific type of pigs reveal genetic differences but also reflect rearing conditions in which the data used for profile calibration were obtained [3
]. Indeed, even if pigs are fed ad libitum
, rearing conditions such as ambient temperature, diet composition, space allowance, or health status can influence the expression of growth potential through the effect on feed intake level or nutrient use. For instance, energy requirements for maintenance or activity can increase depending on space allowance or temperature. This can imply lower availability for protein deposition. Moreover, this can affect the level of observed performances without deviating growth and feed intake kinetics from a normal shape. Thus, it is important to emphasize that an animal profile in InraPorc reflects a phenotype (i.e., the potential of a genotype reared in a specific environment and submitted to management practices). For breeds with several profiles, we could observe that the conditions of data collection clearly influenced the calibration results. Some approximations were needed for calibration in the present study (e.g., feed allowance was supposed to be ad libitum
following information given in some studies or recalculated nutrient composition of some diets when there was an uncertainty on real composition). These different elements can partly explain differences in profile parameters for the same breed.