Estimate of the variability of the lysine requirement of growing pigs using the indicator amino acid oxidation technique1

Bertolo, Robert F.; Moehn, Soenke; Pencharz, Paul B.; Ball, Ronald O.

doi:10.2527/2005.83112535x

Cited by 30 publications

(38 citation statements)

References 18 publications

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“…Additionally, the range of Lys : NE requirements of young pigs are much higher than the ranges obtained with older pigs. Bertolo et al (2005) estimated individual Lys requirements using the amino acid oxidation indicator technique in nine pigs having a weight range similar to that in this study's first phase and obtained a CV of 9.8%, which is slightly lower that the value obtained in this study. With this method, in which only 2 days of adaptation to each level of Lys are required, sufficient data can be obtained from each pig in a short period of time to estimate individual requirements.…”

Section: Resultscontrasting

confidence: 45%

Systematic comparison of the empirical and factorial methods used to estimate the nutrient requirements of growing pigs

Hauschild

Pomar

Lovatto

2010

Animal

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Empirical and factorial methods are currently used to estimate nutrient requirements for domestic animals. The purpose of this study was to estimate the nutrient requirements of a given pig population using the empirical and factorial methods; to establish the relationship between the requirements estimated with these two methods; and to study the limitations of the methods when used to determine the level of a nutrient needed to optimize individual and population responses of growing pigs. A systematic analysis was carried out on optimal lysine-to-net-energy (Lys : NE) ratios estimated by the empirical and factorial methods using a modified InraPorc R growth model. Sixty-eight pigs were individually simulated based on detailed experimental data. In the empirical method, population responses were estimated by feeding pigs with 11 diets of different Lys : NE ratios. Average daily gain and feed conversion ratio were the chosen performance criteria. These variables were combined with economic information to estimate the economic responses. In the factorial method, the Lys : NE ratio for each animal was estimated by model inversion. Optimal Lys : NE ratios estimated for growing pigs (25 to 105 kg) differed between the empirical and the factorial method. When the average pig is taken to represent a population, the factorial method does not permit estimation of the Lys : NE ratio that maximizes the response of heterogeneous populations in a given time or weight interval. Although optimal population responses are obtained by the empirical method, the estimated requirements are fixed and cannot be used for other growth periods or populations. This study demonstrates that the two methods commonly used to estimate nutrient requirements provide different nutrient recommendations and have important limitations that should be considered when the goal is to optimize the response of individuals or pig populations.

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Section: Resultscontrasting

confidence: 45%

Systematic comparison of the empirical and factorial methods used to estimate the nutrient requirements of growing pigs

Hauschild

Pomar

Lovatto

2010

Animal

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“…Our reported lysine requirement data for piglets are also in line with several other studies (Gatel et al, 1992;Whittemore et al, 2003;Wecke and Liebert, 2009). For feed formulation, Bertolo et al (2005) recommended 0.91% ileal digestible lysine (24.1 kg BW; 982 g daily feed intake), which are in line with our data (85% predicted ileal lysine digestibility) and several other studies (Martinez and Knabe, 1990;Coma et al, 1995). In contrast, Fu et al (2004) recommended 1.32% true digestible lysine for late nursery pig diets (29 kg BW).…”

Section: Discussionsupporting

confidence: 88%

Lysine efficiency in piglet fed diets with a phytogenic feed additive and conclusion of lysine requirement data

Muhl¹,

Liebert²

2010

J. Anim. Feed Sci.

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Two experiments were conducted to examine effects of a commercial phytogenic feed additive (PFA), containing inulin, an essential oil mix (carvacrol, thymol), and chest nut meal (polyphenols) on nutrient digestibility, protein utilization, and lysine efficiency in piglets. Each experiment utilized sixteen piglets (male castrated, 8 wk) and four experimental groups. Experiment 1 studied graded levels of the PFA (0, 0.05, 0.1, 0.15%) in lysine limited diets (wheat, barley, soyabean meal, fish meal). Experiment 2 examined 0.1% of the PFA and two dietary levels of lysine. The results indicated that apparent nutrient digestibility, protein utilization, and lysine efficiency were not significantly affected by the PFA (P>0.05). Observed daily lysine requirements (7.3, 9.9 and 13.1 g for 76, 100, 124 g daily protein deposition) in growing barrows (20-30 kg body weight) were in line with recommendations and contribute to the limited database for modelling of lysine requirements in piglets.

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“…Another interest of modelling studies is to extrapolate results from metabolism studies to other different situations (BW, age) or larger populations. For instance, Bertolo et al (2005), using the indicator amino acid oxidation technique, estimated the mean and variability of the true ileal digestible Lys requirement of growing pigs, but using only nine animals.…”

Section: Discussionmentioning

confidence: 99%

“…genetic, sex, weight, composition of the growth at a given BW), environmental conditions and feeding factors (Noblet and Quiniou, 1999). Even though some of these factors may be controlled, the Lys requirement varies between individual pigs (Bertolo et al, 2005). Formulating diets for the mean requirement of a population implies that the requirements of some animals will not be met and that their potential performance will not be realised.…”

Section: Introductionmentioning

confidence: 99%

Modelling the variation in performance of a population of growing pig as affected by lysine supply and feeding strategy

Brossard

Dourmad

Rivest

et al. 2009

Animal

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Considerable progress has been made in the nutritional modelling of growth. Most models typically predict (or analyse) the response of a single animal. However, the response to nutrients of a single, representative animal is likely to be different from the response of the herd. To address the variation in response between animals, a stochastic approach towards nutritional modelling is required. In the present study, an analysis method is presented to describe growth and feed intake curves of individual pigs within a population of 192 pigs. This method was developed to allow end-users of InraPorc (a nutritional model predicting and analysing growth in pigs) to easily characterise their animals based on observed data and then use the model to test different scenarios. First, growth and intake data were curve-fitted to characterise individual pigs in terms of BW (Gompertz function of age) and feed intake (power function of BW) by a set of five parameters, having a biological or technico-economical meaning. This information was then used to create a population of virtual pigs in InraPorc, having the same feed intake and growth characteristics as those observed in the population. After determination of the mean lysine (Lys) requirement curve of the population, simulations were carried out for each virtual pig using different feeding strategies (i.e. 1, 2, 3 or 10 diets) and Lys supply (ranging from 70% to 130% of the mean requirement of the population). Because of the phenotypic variation between pigs and the common feeding strategies that were applied to the population, the Lys requirement of each individual pig was not always met. The percentage of pigs for which the Lys requirement was met increased concomitantly with increasing Lys supply, but decreased with increasing number of diets used. Simulated daily gain increased and feed conversion ratio decreased with increasing Lys supply ( P , 0.001) according to a curvilinear-plateau relationship. Simulated performance was close to maximum when the Lys supply was 110% of the mean population requirement and did not depend on the number of diets used. At this level of Lys supply, the coefficient of variation of simulated daily gain was minimal and close to 10%, which appears to be a phenotypic characteristic of this population. At lower Lys supplies, simulated performance decreased and variability of daily gain increased with an increasing number of diets ( P , 0.001). Knowledge of nutrient requirements becomes more critical when a greater number of diets are used. This study shows the limitations of using a deterministic model to estimate the nutrient requirements of a population of pigs. A stochastic approach can be used provided that relationships between the most relevant model parameters are known.

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Estimate of the variability of the lysine requirement of growing pigs using the indicator amino acid oxidation technique1

Cited by 30 publications

References 18 publications

Systematic comparison of the empirical and factorial methods used to estimate the nutrient requirements of growing pigs

Systematic comparison of the empirical and factorial methods used to estimate the nutrient requirements of growing pigs

Lysine efficiency in piglet fed diets with a phytogenic feed additive and conclusion of lysine requirement data

Modelling the variation in performance of a population of growing pig as affected by lysine supply and feeding strategy

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