Add Journal to My Library
Poultry Science
, Volume 97 (3) – Mar 1, 2018

9 pages

/lp/ou_press/estimation-of-broiler-responses-to-increased-dietary-methionine-e50Rbe00T3

- Publisher
- Oxford University Press
- Copyright
- © 2018 Poultry Science Association Inc.
- ISSN
- 0032-5791
- eISSN
- 1525-3171
- D.O.I.
- 10.3382/ps/pex330
- Publisher site
- See Article on Publisher Site

Abstract As the first limiting amino acid in corn-soy broiler diets, methionine (Met) is supplemented using commercial synthetic sources as demanded to obtain economic feed formulations. The Met analogue DL-2-hydroxy-4-(methylthio)-butanoic acid (HMTBA) is largely utilized with that objective. This study intended to obtain responses of broilers fed with increasing levels of HMTBA, from 28 to 42 d, such that economic returns can be calculated. A total of 2,106 Cobb × Cobb 500 one-day-old male broilers was randomly placed in 81 floor pens (2.7 m2 each). Birds were fed conventional starter (zero to 14 d) and grower (14 to 28 d) diets. Starting at 28 d of age, pens of 26 birds were randomly allocated into 9 feed treatments with 9 replications having increasing supplementations with HMTBA (0.00, 0.07, 0.14, 0.21, 0.28, 0.35, 0.42, 0.49 and 0.56%). These were prepared by mixing different proportions of corn-soy dilution and summit diets, which had the same formulated concentration of nutrients and energy [19.7% CP, 0.90% Ca, 0.45% Av. P, 0.95% digestible Lys, and 3,150 kcal/kg AMEn], with the exception of HMTBA [0.56% in the summit but not supplemented in the corn-soy dilution diet (0.52% digestible TSAA)]]. Growth performance was evaluated until 42 d when carcass yield and commercial cuts were evaluated using 6 birds randomly taken from each pen. Body weight gain (BWG), feed conversion ratio (FCR), proportion of breast fillets, and abdominal fat were adjusted using linear broken-line, exponential asymptotic and quadratic polynomial regression models (P < 0.05). Estimations of maximum responses for supplemented HMTBA by the linear broken-line model were 0.17% for BWG, 0.14% for FCR, and 0.29% for breast fillets. Using exponential and quadratic regressions, optimized HMTBA supplementations were obtained at 0.34 and 0.35% for BWG, 0.20 and 0.33% for FCR, and 0.31 and 0.36% for breast fillets, respectively. Supplemental levels of HMTBA that optimize growth performance and breast meat in male broilers from 28 to 42 d, using different regression models, varied from 0.14 to 0.36%. INTRODUCTION Adding synthetic and crystalline forms of amino acids (AA) in broiler diets has allowed extensive requirement investigations for broilers in the last decades. In parallel, broiler responses to variations in dietary AA remain important subjects for investigation, because improvements in live performance and carcass yield are constantly delivered by genetic selection. Nutrient recommendations for broilers intend to optimize growth performance as well as the proportions of individual carcass components, especially breast meat, such that optimum economic returns are obtained. The dietary concentration of AA that maximizes body weight gain (BWG), feed conversion ratio (FCR), and breast meat yields can be different for each one of these parameters. For instance, optimum total sulfur amino acids (TSAA) levels for breast meat yield have been shown to be higher when compared with those for whole carcass yield, FCR, or BWG and are dependent of broiler genetics (Vieira et al., 2004). It is widely known that methionine (Met) is the first limiting AA for broilers fed corn-soy diets. This AA plays important roles for growing broilers because its limited concentration in feeds affects muscle accretion and feather synthesis, as well as the biochemical processes dependent of the presence of methyl groups donated by Met (NRC, 1994). Met is the initiating AA in the synthesis of virtually all eukaryotic proteins (Lucas-Lenard and Lipmann, 1971), and its metabolism begins with its activation to S-adenosylmethionine, which is used in methylation reactions and is also converted to cysteine (Cys) by the transsulfuration pathway (Brosnan and Brosnan, 2006). The synthetic products mainly used as sources of Met that are routinely supplemented in broiler feeds are DL-methionine (DL-Met) and DL-2-hydroxy-4-(methylthio)-butanoic acid (HMTBA). Both have been utilized for many years allowing the reduction in the dietary inclusion of protein feedstuffs without affecting bird performance (Warnick and Anderson, 1968; Wallis, 1999). It has been demonstrated that DL-Met and HMTBA are readily converted into L-methionine (L-Met), whereas both D and L isomers of HMTBA have to be converted into L-Met (Dibner and Knight, 1984; Martín-Venegas et al., 2006), which is the final form of Met used in the animal metabolism. However, these molecules follow unique processes from absorption to final transformation into L-Met. For instance, the absorption of DL-Met is an active process that is sodium dependent prior to its final use as L-Met before undergoing the process of oxidative deamination and transamination of its keto acid (Gilbert et al., 2008). On the other hand, HMTBA has a hydroxyl group on the alpha carbon rather than the amino group present in DL-Met (Dibner and Knight, 1984). Therefore, as an organic acid, HMTBA is passively absorbed and later converted into L-Met (Dibner and Knight, 1984; Martín-Venegas et al., 2011). Many experiments comparing DL-Met and HMTBA are available in the literature (van Weerden and Schutte, 1984; Lemme et al., 2002; Opapeju et al., 2012), as well as meta-analyses (Kratzer and Littell, 2006; Vázquez-Añón et al., 2006; Sauer et al., 2008). Bioequivalence of these two Met sources, however, remains a controversial issue, probably because of the diversity of the statistical models and/or to the selection criteria of the publications used (Agostini et al., 2015). Since both Met sources have similar market share worldwide, estimation of broiler responses to HMTBA supplemented into practical diets may provide significant information for those that use this source as the only Met supplement, such that users can estimate biological as well as economic performances while choosing its dietary inclusion. The objective of this study was to evaluate growth performance, carcass, and yield of commercial cuts of male broilers fed graded levels of HMTBA from 28 to 42 d as the sole TSAA supplement in corn-soy diets. Estimations of maximum responses are provided for each of these responses. MATERIAL AND METHODS All procedures adopted in the present study avoided unnecessary animal discomfort and were approved by the directives of Ethics and Research Committee of the Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil. General Bird Husbandry A total of 2,106 male Cobb × Cobb 500 slow feathering broiler chickens was randomly placed into 81 floor pens (1.65 × 1.65 m), 26 birds in each, having rice hulls as bedding. Each pen was equipped with one tube feeder and one bell drinker. Environmental temperature was controlled to maintain bird comfort throughout the study (Cobb-Vantress, 2013), which was reduced by 1°C every 2 d through the use of thermostatically controlled heaters, fans, and foggers. Lighting was continuous until 7 d of age, with a 14L:10D cycle afterwards. Birds had ad libitum access to water and mash feed. Dietary Treatments Birds were fed common corn-soy starter (zero to 14 d, 23.0% CP, 0.97% dig. TSAA, and 3,095 kcal/kg AMEn) and grower diets (14 to 28 d, 22.0% CP, 0.84% dig. TSAA, and 3,115 kcal/kg AMEn) following Brazilian industry standards (Rostagno et al., 2011), as shown in Table 1. Treatments had variable dig. TSAA to comply with the increased projected levels. Two-thousand-one hundred-and-six 28-day-old chicks were weighed individually, sorted by individual BW (1,469 ± 53.0 g), and assigned to 9 replicate pens per treatment diet with 26 birds per pen. Birds were allocated in a completely randomized design. Treatments were produced by mixing a non-supplemented HMTBA diet (dilution) with a summit diet having 0.56% supplemented HMTBA. The experimental diets had 9 levels of supplemented HMTBA (0, 0.07, 0.14, 0.21, 0.28, 0.35, 0.42, 0.49 or 0.56%). The TSAA level was considered for each treatment, since the regression models are rather based on the TSAA inclusion (X axis) than on HMTBA inclusion. The manufacturer recommendation of 88% equivalence of HMTBA to TSAA was used to formulate experimental diets (Alimet, Novus International, Indaiatuba, SP, Brazil). Table 1. Composition of the experimental diets for broiler chickens from 28 to 42 d. Item HMTBA supplementation, % 0.00 0.07 0.14 0.21 0.28 0.35 0.42 0.49 0.56 Ingredients, % Corn, 7.8% 64.8 64.7 64.5 64.4 64.2 64.1 64.0 63.8 63.7 Soybean meal, 45% 26.3 26.3 26.4 26.4 26.4 26.5 26.5 26.5 26.5 Soybean oil 2.6 2.7 2.7 2.8 2.8 2.9 2.9 3.0 3.0 Meat and bone meal, 48% 5.0 Calcium carbonate 0.38 Dicalcium phosphate 0.63 Sodium bicarbonate 0.23 Salt 0.23 HMTBA1, 88% - 0.07 0.14 0.21 0.28 0.35 0.42 0.49 0.56 L-Lysine HCl, 78% 0.08 0.08 0.08 0.08 0.07 0.07 0.07 0.07 0.07 L-Threonine, 98.5% 0.02 Choline chloride 0.09 Vitamin and mineral mix2 0.15 Nutrient composition, % or as shown3 AMEn4, kcal/kg 3,200 Crude protein 19.7 Calcium 0.90 Available phosphorus 0.45 Sodium 0.20 Digestible Lys 0.95 Digestible Met 0.27 0.33 0.39 0.45 0.51 0.57 0.63 0.69 0.75 Digestible TSAA 0.52 0.58 0.64 0.71 0.77 0.83 0.89 0.95 1.01 Digestible Thr 0.64 Digestible Val 0.78 Digestible Ile 0.69 Total His 0.49 Total Lys 1.05 (1.06) 1.05 (1.06) 1.05 (1.08) 1.05 (1.07) 1.05 (1.04) 1.05 (1.05) 1.05 (1.07) 1.05 (1.04) 1.05 (1.07) Total TSAA 0.61 (0.60) 0.66 (0.63) 0.71 (0.74) 0.76 (0.75) 0.81 (0.80) 0.86 (0.88) 0.91 (0.92) 0.96 (0.96) 1.01 (1.05) Total Thr 0.74 (0.75) 0.74 (0.76) 0.74 (0.77) 0.74 (0.78) 0.74 (0.73) 0.74 (0.73) 0.74 (0.78) 0.74 (0.73) 0.74 (0.78) Total Val 0.91 (0.93) 0.91 (0.90) 0.91 (0.95) 0.91 (0.89) 0.91 (0.95) 0.91 (0.95) 0.91 (0.95) 0.91 (0.94) 0.91 (0.95) Total Ile 0.79 (0.81) 0.79 (0.83) 0.79 (0.82) 0.79 (0.83) 0.79 (0.80) 0.79 (0.79) 0.79 (0.82) 0.79 (0.78) 0.79 (0.77) Total His 0.52 (0.49) 0.52 (0.47) 0.52 (0.52) 0.52 (0.47) 0.52 (0.51) 0.52 (0.51) 0.52 (0.51) 0.52 (0.54) 0.52 (0.54) Item HMTBA supplementation, % 0.00 0.07 0.14 0.21 0.28 0.35 0.42 0.49 0.56 Ingredients, % Corn, 7.8% 64.8 64.7 64.5 64.4 64.2 64.1 64.0 63.8 63.7 Soybean meal, 45% 26.3 26.3 26.4 26.4 26.4 26.5 26.5 26.5 26.5 Soybean oil 2.6 2.7 2.7 2.8 2.8 2.9 2.9 3.0 3.0 Meat and bone meal, 48% 5.0 Calcium carbonate 0.38 Dicalcium phosphate 0.63 Sodium bicarbonate 0.23 Salt 0.23 HMTBA1, 88% - 0.07 0.14 0.21 0.28 0.35 0.42 0.49 0.56 L-Lysine HCl, 78% 0.08 0.08 0.08 0.08 0.07 0.07 0.07 0.07 0.07 L-Threonine, 98.5% 0.02 Choline chloride 0.09 Vitamin and mineral mix2 0.15 Nutrient composition, % or as shown3 AMEn4, kcal/kg 3,200 Crude protein 19.7 Calcium 0.90 Available phosphorus 0.45 Sodium 0.20 Digestible Lys 0.95 Digestible Met 0.27 0.33 0.39 0.45 0.51 0.57 0.63 0.69 0.75 Digestible TSAA 0.52 0.58 0.64 0.71 0.77 0.83 0.89 0.95 1.01 Digestible Thr 0.64 Digestible Val 0.78 Digestible Ile 0.69 Total His 0.49 Total Lys 1.05 (1.06) 1.05 (1.06) 1.05 (1.08) 1.05 (1.07) 1.05 (1.04) 1.05 (1.05) 1.05 (1.07) 1.05 (1.04) 1.05 (1.07) Total TSAA 0.61 (0.60) 0.66 (0.63) 0.71 (0.74) 0.76 (0.75) 0.81 (0.80) 0.86 (0.88) 0.91 (0.92) 0.96 (0.96) 1.01 (1.05) Total Thr 0.74 (0.75) 0.74 (0.76) 0.74 (0.77) 0.74 (0.78) 0.74 (0.73) 0.74 (0.73) 0.74 (0.78) 0.74 (0.73) 0.74 (0.78) Total Val 0.91 (0.93) 0.91 (0.90) 0.91 (0.95) 0.91 (0.89) 0.91 (0.95) 0.91 (0.95) 0.91 (0.95) 0.91 (0.94) 0.91 (0.95) Total Ile 0.79 (0.81) 0.79 (0.83) 0.79 (0.82) 0.79 (0.83) 0.79 (0.80) 0.79 (0.79) 0.79 (0.82) 0.79 (0.78) 0.79 (0.77) Total His 0.52 (0.49) 0.52 (0.47) 0.52 (0.52) 0.52 (0.47) 0.52 (0.51) 0.52 (0.51) 0.52 (0.51) 0.52 (0.54) 0.52 (0.54) 1HMTBA, DL-2-hydroxy-4-(methylthio)-butanoic acid formulated at 88% methionine equivalency. 2Supplied the following per kilogram of diet: vitamin A, 8.000 UI; vitamin D3, 2.000 UI; vitamin E, 30 UI; vitamin K3, 2 mg; thiamine, 2 mg; riboflavin, 6 mg; pyridoxine, 2.5 mg; cyanocobalamin, 0.012 mg. pantothenic acid, 15 mg; niacin, 35 mg; folic acid, 1 mg; biotin, 0.08 mg; iron, 40 mg; zinc, 80 mg; manganese, 80 mg; copper, 10 mg; iodine, 0.7 mg; selenium, 0.3 mg. 3Values between parentheses are analyzed. 4Apparent metabolizable energy corrected for nitrogen retention. View Large Analyses of AA in ingredients and diets were conducted according to the method 914.12 using a high performance liquid chromatography (HPLC) auto analyzer and employed performic acid oxidation of the feed sample prior to acid hydrolysis (AOAC International, 1998). Analysis of HMTBA in the supplemental diets also was done using HPLC (Ontiveros et al., 1987). Measurements Growth performance was evaluated from 28 to 42 d when feed intake (FI), BWG, and FCR corrected for mortality were calculated. Mortality was recorded daily. At 42 d, 6 birds were randomly selected from each pen (n = 486) and processed for carcass and commercial cuts evaluation at the poultry slaughterhouse of the Federal University of Rio Grande do Sul. Prior to processing, broilers were fasted for 8 h and individually weighed. Birds were humanely rendered insensible using electrical stunning (45 V for 3 s), then bled through a jugular vein cut for 3 min, scalded at 60°C for 45 s, and, lastly, defeathered. Evisceration was manually performed and carcasses were statically chilled in ice for approximately 3 hours. Eviscerated carcasses (without feet or neck) were hung for 3 min to remove excess water prior to weighing. Commercial cuts were performed by a crew of industry-trained personnel into bone-in drumsticks, thighs, and wings, as well as deboned breast fillets and tenders. Abdominal fat was weighed separately. Carcass yield was expressed relative to live weight, while commercial cuts and abdominal fat were expressed as percentage of the eviscerated carcass. Statistical Analysis Data were analyzed using the GLM procedure of SAS Institute (SAS, 2009), and significance was accepted at P < 0.05. BWG, FCR, and carcass traits (carcass, abdominal fat, breast meat, thighs, drumsticks, and wings yield) were used as analyzed broiler responses. Pens were considered as experimental units for the evaluation of live performance and the average of 6 processed birds per pen for carcass traits. Means were compared by the Tukey test when effects of dietary treatments were significant at 5% (Tukey, 1991). In order to estimate the different optimized responses, 3 statistical models were used: linear broken-line (LBL), exponential asymptotic (EA), and quadratic polynomial (QP) (Robbins et al., 1979; Pesti et al., 2009). The models had structures as follow: LBL, Y = β0 + β1 × (β2 – X), where (β2 – X) = 0 for X > β2, Y is the response variable, X is the dietary HMTBA, β0 is the value at the plateau, β1 is the slope, and β2 is the HMTBA supplementation at the break point (maximum response); EA, Y = β0 + β1 × (1 – EXP(–β2 × X)), where Y is the response variable, X is the dietary HMTBA, β0 is the response variable estimated for the lowest HMTBA level, β1 is the difference between the maximum and minimum response obtained by the increasing HMTBA levels, and β2 is the slope of the exponential curve (maximum response at 95% of the plateau was obtained by ln(0.05) ÷—β2); QP, Y = β0 + β1 × X + β2 × X2, where Y is the response variable, X is the dietary HMTBA, β0 is the intercept, and β1 and β2 are the linear and quadratic coefficients, respectively; maximum responses were obtained by– β1 ÷ (2 × β2). RESULTS Formulated diets with increasing levels of HMTBA are presented in Table 1. Slight deviations between analyzed and formulated crude protein, AA, and HMTBA existed. These were considered acceptable for the interpretation from the originally intended study structure, since analyzed values demonstrated trends as expected in the formulated diets and, therefore, were assumed to be adequate for the interpretation of results. Growth performance of broilers fed diets supplemented with HMTBA is presented in Table 2. Broilers fed corn-soy diets supplemented with graded increases of HMTBA showed gradual improvements in BWG and FCR allowing LBL, EA, and QP adjustments (P < 0.001), as shown in Table 3 and Figures 1 and 2. The obtained regressions for BWG and FCR of broilers from 28 to 42 d estimated the supplemental HMTBA levels of 0.165% (R2 = 0.25), 0.342% (R2 = 0.25), and 0.354% (R2 = 0.29) for BWG and 0.135% (R2 = 0.25), 0.204% (R2 = 0.23), and 0.330% (R2 = 0.26) for FCR, respectively, using LBL, EA, and QP models. Data obtained from 28 to 35 and 35 to 42 d are also presented in Tables 2 and 3. The obtained regressions for BWG and FCR of broilers from 28 to 35 d estimated the supplemental HMTBA levels of 0.103, 0.211, and 0.358% for BWG and 0.097, 0.160, and 0.357% for FCR, respectively, using LBL, EA, and QP models. Additionally, regressions for BWG and FCR of broilers from 35 to 42 d estimated the supplemental HMTBA levels of 0.260, 0.412, and 0.348% for BWG and 0.112, 0.185, and 0.326% for FCR, respectively, using LBL, EA, and QP models. Figure 1. View largeDownload slide Body weight gain (Y, in g) vs. HMTBA supplementation (X, in %) fed from 28 to 42 d of age. Linear broken-line, Y = 1519–948 × (0.165 – X), r2 = 0.2517; exponential asymptotic, Y = 1362 + 168.7 × (1 – EXP(– 8.757X)), r2 = 0.2538; quadratic polynomial, Y = + 1362 + 1023X – 1444X2, r2 = 0.2933. Figure 1. View largeDownload slide Body weight gain (Y, in g) vs. HMTBA supplementation (X, in %) fed from 28 to 42 d of age. Linear broken-line, Y = 1519–948 × (0.165 – X), r2 = 0.2517; exponential asymptotic, Y = 1362 + 168.7 × (1 – EXP(– 8.757X)), r2 = 0.2538; quadratic polynomial, Y = + 1362 + 1023X – 1444X2, r2 = 0.2933. Figure 2. View largeDownload slide Feed conversion ratio (Y, in g: g) vs. HMTBA supplementation (X, in %) fed from 28 to 42 d of age. Linear broken-line, Y = 1.880 + 1.265 × (0.135 – X), r2 = 0.2452; exponential asymptotic, Y = 2.055–0.178 × (1 – EXP(–14.721X)), r2 = 0.2334; quadratic polynomial, Y = 2.038–1.140X + 1.725X2, r2 = 0.2595. Figure 2. View largeDownload slide Feed conversion ratio (Y, in g: g) vs. HMTBA supplementation (X, in %) fed from 28 to 42 d of age. Linear broken-line, Y = 1.880 + 1.265 × (0.135 – X), r2 = 0.2452; exponential asymptotic, Y = 2.055–0.178 × (1 – EXP(–14.721X)), r2 = 0.2334; quadratic polynomial, Y = 2.038–1.140X + 1.725X2, r2 = 0.2595. Table 2. Growth performance of male broiler chickens fed diets supplemented with a methionine analogue (HMTBA) to provide increasing levels of its inclusion. BWG2, g FCR3 HMTBA1 supplementation, % Digestible TSAA, % 28 to 35 d 35 to 42 d 28 to 42 d 28 to 35 d 35 to 42 d 28 to 42 d 0.00 0.52 630b 712 1,369c 1.916a 2.264a 2.051a 0.07 0.58 703a,b 718 1,415b,c 1.783a,b 2.142a,b 1.965a,b 0.14 0.64 731a 754 1,499a,b,c 1.729b 2.022b 1.862b 0.21 0.71 730a 763 1,474a,b,c 1.727b 2.063a,b 1.922a,b 0.28 0.77 730a 788 1,531a,b 1.730b 1.986b 1.847b 0.35 0.83 759a 785 1,542a,b 1.709b 2.066a,b 1.872b 0.42 0.89 768a 780 1,566a 1.720b 2.018b 1.852b 0.49 0.95 738a 790 1,528a,b 1.742b 1.988b 1.867b 0.56 1.01 729a 744 1,473a,b,c 1.720b 2.025b 1.893b SEM 7.8 7.1 1.2 0.014 0.018 0.013 P-value 0.001 0.161 0.001 0.008 0.001 0.001 BWG2, g FCR3 HMTBA1 supplementation, % Digestible TSAA, % 28 to 35 d 35 to 42 d 28 to 42 d 28 to 35 d 35 to 42 d 28 to 42 d 0.00 0.52 630b 712 1,369c 1.916a 2.264a 2.051a 0.07 0.58 703a,b 718 1,415b,c 1.783a,b 2.142a,b 1.965a,b 0.14 0.64 731a 754 1,499a,b,c 1.729b 2.022b 1.862b 0.21 0.71 730a 763 1,474a,b,c 1.727b 2.063a,b 1.922a,b 0.28 0.77 730a 788 1,531a,b 1.730b 1.986b 1.847b 0.35 0.83 759a 785 1,542a,b 1.709b 2.066a,b 1.872b 0.42 0.89 768a 780 1,566a 1.720b 2.018b 1.852b 0.49 0.95 738a 790 1,528a,b 1.742b 1.988b 1.867b 0.56 1.01 729a 744 1,473a,b,c 1.720b 2.025b 1.893b SEM 7.8 7.1 1.2 0.014 0.018 0.013 P-value 0.001 0.161 0.001 0.008 0.001 0.001 a–cValues within a column not sharing a common superscript differ (P < 0.05) by the Tukey test. 1HMTBA, DL-2-hydroxy-4-(methylthio)-butanoic acid. 2BWG, body weight gain. 3FCR, feed conversion ratio corrected for dead birds. View Large Table 3. Dose response regressions for growth performance of broilers fed diets supplemented with a methionine analogue from 28 to 42 d. Model Parameters Regression equation Maximum response, % P-value R2 28 to 35 d Linear broken-line1 BWG2 Y = +741–1084 × (0.103 – X) 0.103 0.001 0.2597 FCR3 Y = +1.725 + 1.966 × (0.097 – X) 0.097 0.001 0.2363 Exponential asymptotic4 BWG Y = +630 + 114.6 × (1 – EXP(–14.205X)) 0.211 0.001 0.2652 FCR Y = +1.917–0.194 × (1 – EXP(–18.689X)) 0.160 0.001 0.2351 Quadratic polynomial5 BWG Y = +646 + 626X – 875X2 0.358 0.001 0.2586 FCR Y = +1.875–0.979X + 1.372X2 0.357 0.001 0.1960 35 to 42 d Linear broken-line BWG Y = +778–260 × (0.260 – X) 0.260 0.002 0.1444 FCR Y = +2.040 + 1.786 × (0.126 – X) 0.126 0.001 0.2208 Exponential asymptotic BWG Y = +707 + 72.8 × (1 – EXP(–7.266X)) 0.412 0.005 0.1267 FCR Y = +2.269–0.232 × (1 – EXP(–16.187X)) 0.185 0.001 0.2111 Quadratic polynomial BWG Y = +702 + 471X – 678X2 0.348 0.001 0.1617 FCR Y = +2.241–1.488X + 2.282X2 0.326 0.001 0.2300 28 to 42 d Linear broken-line BWG Y = +1519–948 × (0.165 – X) 0.165 0.001 0.2517 FCR Y = +1.880 + 1.265 × (0.135 – X) 0.135 0.001 0.2452 Exponential asymptotic BWG Y = +1362 + 168.7 × (1 – EXP(–8.757X)) 0.342 0.001 0.2538 FCR Y = +2.055–0.178 × (1 – EXP(–14.721X)) 0.204 0.001 0.2334 Quadratic polynomial BWG Y = +1362 + 1023X – 1444X2 0.354 0.001 0.2933 FCR Y = +2.038–1.140X + 1.725X2 0.330 0.001 0.2595 Model Parameters Regression equation Maximum response, % P-value R2 28 to 35 d Linear broken-line1 BWG2 Y = +741–1084 × (0.103 – X) 0.103 0.001 0.2597 FCR3 Y = +1.725 + 1.966 × (0.097 – X) 0.097 0.001 0.2363 Exponential asymptotic4 BWG Y = +630 + 114.6 × (1 – EXP(–14.205X)) 0.211 0.001 0.2652 FCR Y = +1.917–0.194 × (1 – EXP(–18.689X)) 0.160 0.001 0.2351 Quadratic polynomial5 BWG Y = +646 + 626X – 875X2 0.358 0.001 0.2586 FCR Y = +1.875–0.979X + 1.372X2 0.357 0.001 0.1960 35 to 42 d Linear broken-line BWG Y = +778–260 × (0.260 – X) 0.260 0.002 0.1444 FCR Y = +2.040 + 1.786 × (0.126 – X) 0.126 0.001 0.2208 Exponential asymptotic BWG Y = +707 + 72.8 × (1 – EXP(–7.266X)) 0.412 0.005 0.1267 FCR Y = +2.269–0.232 × (1 – EXP(–16.187X)) 0.185 0.001 0.2111 Quadratic polynomial BWG Y = +702 + 471X – 678X2 0.348 0.001 0.1617 FCR Y = +2.241–1.488X + 2.282X2 0.326 0.001 0.2300 28 to 42 d Linear broken-line BWG Y = +1519–948 × (0.165 – X) 0.165 0.001 0.2517 FCR Y = +1.880 + 1.265 × (0.135 – X) 0.135 0.001 0.2452 Exponential asymptotic BWG Y = +1362 + 168.7 × (1 – EXP(–8.757X)) 0.342 0.001 0.2538 FCR Y = +2.055–0.178 × (1 – EXP(–14.721X)) 0.204 0.001 0.2334 Quadratic polynomial BWG Y = +1362 + 1023X – 1444X2 0.354 0.001 0.2933 FCR Y = +2.038–1.140X + 1.725X2 0.330 0.001 0.2595 1Linear broken-line: Y = β0 + β1 × (β2 - X), where (β2 - X) = 0 for X > β2, Y is the response variable, X is the dietary HMTBA, β0 is the value at the plateau, and β1 is the slope and β2 is the HMTBA at maximum response. 2BWG, body weight gain. 3FCR, feed conversion ratio corrected for dead birds. 4Exponential asymptotic: Y = β0 + β1 × (1 – EXP(– β2 × X)), where Y is the response variable, X is the dietary HMTBA, β0 is the response variable at the lowest HMTBA, β1 is the difference between maximum and minimum responses obtained by the increasing HMTBA, and β2 is the slope of the exponential curve. Inclusion estimated for the maximum response (95% of the plateau) was obtained by ln(0.05) ÷—β2. 5Quadratic polynomial: Y = β0 + β1 × X + β2 × X2, where Y is the response variable, X is the dietary HMTBA, β0 is the intercept, and β1 and β2 are the linear and quadratic coefficients, respectively; maximum response was obtained by—β1 ÷ (2 × β2). View Large Carcass and yields of commercial cuts obtained in the present study are shown in Table 4 and in Figure 3. No statistical significance was found for carcass yield. An increased proportion of breast fillets with a concurrent decrease in the proportion of abdominal fat (P < 0.004), thighs, and drumsticks (P < 0.001) occurred. Dose response regressions for carcass traits of broilers are presented in Table 5. Maximum responses were obtained for proportions of carcass (P < 0.006, R2 = 0.12, 0.410% HMTBA) and breast fillets (P < 0.001, R2 = 0.43, 0.205% HMTBA), as well as the lowest abdominal fat (P < 0.001, R2 = 0.23, 0.160% HMTBA) with the LBL adjustment. Corresponding values using the EA and the QP were 0.307 (R2 = 0.21) and 0.361% (R2 = 0.25) for breast fillets and 0.262% (R2 = 0.39) and 0.334% (R2 = 0.41) for abdominal fat. Figure 3. View largeDownload slide Breast fillets (Y, in %) vs. HMTBA supplementation (X, in %) fed from 28 to 42 d of age. Linear broken-line, Y = 34.98–10.256 × (0.205 – X), r2 = 0.4253; exponential asymptotic, Y = 32.70 + 2.336 × (1 – EXP(–9.759X)), r2 = 0.3937; Y = 32.84 + 13.146X – 18.202X2, r2 = 0.4119. Figure 3. View largeDownload slide Breast fillets (Y, in %) vs. HMTBA supplementation (X, in %) fed from 28 to 42 d of age. Linear broken-line, Y = 34.98–10.256 × (0.205 – X), r2 = 0.4253; exponential asymptotic, Y = 32.70 + 2.336 × (1 – EXP(–9.759X)), r2 = 0.3937; Y = 32.84 + 13.146X – 18.202X2, r2 = 0.4119. Table 4. Carcass and commercial cut yields from male broiler chickens fed diets supplemented with a methionine analogue (HMTBA), %. HMTBA1 supplementation, % Digestible TSAA, % Carcass Abdominal fat Breast fillets Breast tenders Drumsticks Thighs Wings 0.00 0.52 77.3 2.1a 32.8c 5.4 13.3a 19.0a 9.8 0.07 0.58 77.6 1.9a,b 33.8b,c 5.6 13.1a 18.8a,b 9.8 0.14 0.64 77.4 1.7a,b 33.9b,c 5.6 13.0a 18.7a,b 9.8 0.21 0.71 77.6 1.6b 35.3a 5.7 12.1b 18.5a,b 9.5 0.28 0.77 78.4 1.6b 35.1a,b 5.6 12.7a,b 18.8a,b 9.6 0.35 0.83 79.0 1.6b 35.1a,b 5.6 12.8a,b 18.6a,b 9.7 0.42 0.89 79.1 1.7a,b 34.9a,b 5.5 12.6a,b 18.3a,b 9.6 0.49 0.95 79.4 1.6b 34.9a,b 5.5 12.6a,b 18.3b 9.7 0.56 1.01 79.2 1.7a,b 34.8a,b 5.5 12.6a,b 18.3b 9.7 SEM 0.18 0.04 0.13 0.03 0.07 0.06 0.03 P-value 0.064 0.004 0.001 0.104 0.001 0.001 0.195 HMTBA1 supplementation, % Digestible TSAA, % Carcass Abdominal fat Breast fillets Breast tenders Drumsticks Thighs Wings 0.00 0.52 77.3 2.1a 32.8c 5.4 13.3a 19.0a 9.8 0.07 0.58 77.6 1.9a,b 33.8b,c 5.6 13.1a 18.8a,b 9.8 0.14 0.64 77.4 1.7a,b 33.9b,c 5.6 13.0a 18.7a,b 9.8 0.21 0.71 77.6 1.6b 35.3a 5.7 12.1b 18.5a,b 9.5 0.28 0.77 78.4 1.6b 35.1a,b 5.6 12.7a,b 18.8a,b 9.6 0.35 0.83 79.0 1.6b 35.1a,b 5.6 12.8a,b 18.6a,b 9.7 0.42 0.89 79.1 1.7a,b 34.9a,b 5.5 12.6a,b 18.3a,b 9.6 0.49 0.95 79.4 1.6b 34.9a,b 5.5 12.6a,b 18.3b 9.7 0.56 1.01 79.2 1.7a,b 34.8a,b 5.5 12.6a,b 18.3b 9.7 SEM 0.18 0.04 0.13 0.03 0.07 0.06 0.03 P-value 0.064 0.004 0.001 0.104 0.001 0.001 0.195 a–cValues within a column not sharing a common superscript differ (P < 0.05) by the Tukey test. 1HMTBA, DL-2-hydroxy-4-(methylthio)-butanoic acid. View Large Table 5. Dose response regressions for carcass traits of broiler chickens fed diets supplemented with a methionine analogue at 42 d. Model Parameter1 Regression equation Maximum response, %2 P-value R2 Linear broken-line3 Carcass yield Y = +78.90–4.103 × (0.410 – X) 0.410 0.006 0.1231 Abdominal fat yield Y = +1.64 + 2.810 × (0.160 – X) 0.160 0.001 0.2264 Breast fillets yield Y = +34.98–10.256 × (0.205 – X) 0.205 0.001 0.4253 Exponential asymptotic4 Abdominal fat yield Y = +2.09–0.464 × (1 – EXP(–11.441X)) 0.262 0.001 0.2094 Breast fillets yield Y = +32.70 + 2.336 × (1 – EXP(–9.759X)) 0.307 0.001 0.3937 Quadratic polynomial5 Abdominal fat yield Y = +2.07–3.035X + 4.547X2 0.334 0.001 0.2450 Breast fillets yield Y = +32.84 + 13.146X – 18.202X2 0.361 0.001 0.4119 Model Parameter1 Regression equation Maximum response, %2 P-value R2 Linear broken-line3 Carcass yield Y = +78.90–4.103 × (0.410 – X) 0.410 0.006 0.1231 Abdominal fat yield Y = +1.64 + 2.810 × (0.160 – X) 0.160 0.001 0.2264 Breast fillets yield Y = +34.98–10.256 × (0.205 – X) 0.205 0.001 0.4253 Exponential asymptotic4 Abdominal fat yield Y = +2.09–0.464 × (1 – EXP(–11.441X)) 0.262 0.001 0.2094 Breast fillets yield Y = +32.70 + 2.336 × (1 – EXP(–9.759X)) 0.307 0.001 0.3937 Quadratic polynomial5 Abdominal fat yield Y = +2.07–3.035X + 4.547X2 0.334 0.001 0.2450 Breast fillets yield Y = +32.84 + 13.146X – 18.202X2 0.361 0.001 0.4119 1Means from 9 replicates of 6 birds each; carcass as a percentage of live weight but cuts and abdominal fat as percentage of eviscerated carcass. 2Not estimated when not significant fit (P > 0.05). 3Linear broken-line: Y = β0 + β1 × (β2 - X), where (β2 - X) = 0 for X > β2, Y is the response variable, X is the HMTBA, β0 is value at the plateau, β1 is the slope, and β2 is the HMTBA inclusion at maximum response. 4Exponential asymptotic: Y = β0 + β1 × (1 – EXP(–β2 × X)), Y is the response variable, X is HMTBA, β0 is the response variable estimated at lowest HMTBA inclusion, β1 is the difference between maximum and minimum response with increased HMTBA, and β2 is the slope of the exponential curve. Maximum response (95% of the plateau) was obtained by ln(0.05) ÷—β2. 5Quadratic polynomial: Y = β0 + β1 × X + β2 × X2, Y is the response variable, X is the dietary HMTBA inclusion, β0 is the intercept, and β1 and β2 are the linear and quadratic coefficients, respectively; maximum response wasobtained by—β1 ÷ (2 × β2). View Large DISCUSSION Routine evaluations of nutrient requirements of broiler chickens are needed, as consistent changes in the proportions of body components, especially increases in breast meat yields, are delivered from genetic selection. Impressive improvements in the yields of breast meat have been occurring with existing estimations of 80% increases between 1940 and 2009 (Schmidt et al., 2009). In order to support the fulfillment of the genetic potential of the modern broiler, such that breast muscle growth is maximized, increases in dietary concentrations of AA are needed (Garcia and Batal, 2005; Corzo et al., 2006; 2007; Lumpkins et al., 2007; Dozier et al., 2008a; Dozier et al., 2008b). Since continuous increases in breast muscle growth are expected in the next yr, a scenario with further increases in the demands in the dietary concentrations of AA in broiler feeds is projected. A chronological observation of the published requirements for broiler chickens shows a continuous increase in dig. TSAA requirements. For instance, the NRC (1994) suggested 0.72% TSAA for 3- to 6-week-old broilers, which was parallel with most data reported in the yr that immediately preceded that date (Holsheimer, 1981; Wheeler and Latshaw, 1981; Mitchell and Robbins, 1983; Baker et al., 1996). Later on, Kalinowski et al. (2003) reported TSAA requirements for slow- and fast-feathering broilers from 21 to 42 d as 0.83 and 0.88%, which already presented significant increments from the NRC (1994). Rostagno et al. (2005) suggested TSAA requirements for 22 to 35 d broilers as 0.79% and for 34- to 42-day-old broilers as 0.76%, but, more recently, their reviewed table suggested 0.91% and 0.85 for that same age interval (Rostagno et al., 2011). Suggestions of TSAA from the breeder companies also have increased when compared to the NRC (1994); for instance, recommendation values for Ross 308 broilers were of 0.83% from 25 to 42 d (Aviagen, 2009) and for Cobb 500 males were of 0.82%, from 23 to 42 d (Cobb-Vantress, 2015). Studies on Met or TSAA requirements of broiler chickens have usually been conducted with the supplementation with DL-Met. The present study did not intend to compare HMTBA with DL-Met, but to provide values using HMTBA. The bioequivalence subject remains controversial, with reports indicating similar efficacies at equimolar level (Bishop and Halloran, 1977; Liu et al., 2006; Yodseranee and Bunchasak, 2012), as well as improved growth performance with DL-Met when compared to HMTBA (Van Weerden et al., 1983; Lemme et al., 2002; Sangali et al., 2014). Agostini et al. (2015), however, have shown that comparisons between the 2 sources depend on the TSAA consumed by the bird and that the DL-Met and HMTBA had similar performances when diet TSAA were around requirement level. They also have shown that, when TSAA was above requirement level, HMTBA had higher Met efficacy than DL-Met. Authors observed that the opposite was observed in females below TSAA requirement levels. Nutrient requirement values usually presented in the literature derive from regression equations that intend to model growth, such that their estimations can adequately predict bird responses. Different models have been used with that intention, which, however, produce estimations of requirements that can be highly variable due to differences in their shape as well as in their point of maxima. The most commonly utilized models to estimate AA requirements for broilers, which also have been utilized in the present study, are QP, EA, and LBL. Vedenov and Pesti (2008) tested several nonlinear models using different data sets and observed that no particular model was best for all nutritional responses. Therefore, it was suggested that the objective of this type of experiments should indicate in advance the model of choice. Others have specifically evaluated the impact of different statistical models on TSAA requirements (Esteve-Garcia and Llauradó, 1997; Lemme et al., 2002; Dibner et al., 2004; Gonzáles-Esquerra et al., 2007; Vedenov and Pesti, 2010). The QP, EA, and LBL models have been thoroughly reviewed by Pesti et al. (2009). Studies using graded increases in HMTBA as the sole source of supplemental Met presented in the literature are not many. Comparisons between the findings from these studies also are confusing because of the statistics used to estimate the supplementation levels that optimize the evaluated responses. Esteve-Garcia and Llauradó (1997) found maximum BWG and breast meat yields using 0.15% HMTBA, estimated by exponential models in male broilers from 7 to 41 days. Lemme et al. (2002) observed an increase in BWG after supplementing corn-soy diets with HMTBA at 0.24% in 42-day-old male broilers when estimated by the EA model. Dibner et al. (2004) also demonstrated significant increases in BW when supplementing 35-day-old male broilers with 0.2% HMTBA and using QP regressions. Gonzáles-Esquerra et al. (2007) reported that 0.32% HMTBA supplementation provided best BWG and FCR in 21-day-old turkeys when estimated by linear, quadratic, and exponential combined models. Vedenov and Pesti (2010) demonstrated that 0.32% HMTBA supplementation provided higher BWG in 28-day-old broilers using EA models. From the data obtained in the present study, higher HMTBA levels (0.36%) were required to maximize broiler performance with 42-day-old male broilers when compared to research previously reported. In the present study, the obtained regressions for BWG and FCR of broilers from 28 to 35 d estimated the supplemental HMTBA levels of 0.13, 0.21, and 0.36% for BWG and 0.10, 0.16, and 0.36% for FCR, respectively, using LBL, EA, and QP models. From 28 to 42 d, the obtained regressions for BWG and FCR estimated the supplemental HMTBA levels of 0.17, 0.34, and 0.35% for BWG and 0.14, 0.20, and 0.330% for FCR, respectively, using LBL, EA, and QP models. Additionally, based on this comparison, 2 factors may be playing a role in the outcomes: the regression model considered and the Met requirement in the finisher period, which was expected to be age dependent. The present study was conducted with Cobb 500 slow-feathering males, which are early maturing birds. This may have impacted the requirement values as they compare to other data earlier presented. It is well known that mathematical significance does not mean biological significance and, therefore, the model of choice utilized to provide requirement estimations should meet both aspects (Rodehutscord and Pack, 1999). Comparing models through their R2 as well as their sum of residual squares is also important to determine nutrient requirements for broilers based on performance and carcass responses, since they provide the fits that best match the response of birds within the supplementation interval utilized. In the present study, all models tested were statistically significant (P < 0.001), with the exception of carcass yield, and the R2 of LBL, EA, and QP regressions were quite similar. Optimized responses were obtained with HMTBA supplementation levels that were higher for BWG when compared with those for FCR. Also, optimized live performance and carcass responses had the QP model estimating higher values of HMTBA supplementation when compared to LBL an EA models. The QP regression also was able to estimate that the highest HMTBA level provides a very high dig. TSAA level (dig. TSAA/dig. Lys = 1.06), which indicates that the excess of Met starts becoming toxic for the birds. To the authors’ knowledge, estimations of TSAA requirements with LBL, EA, and QP statistical models using the same data set and when broilers were supplemented with HMTBA as the sole Met source have not been done. Obviously, comparisons among the present study with previous research have to take into consideration the differences in studied variables such as strain, sex, age, type of diet, statistical model, and method (factorial vs. empirical). In conclusion, male broilers from 28 to 42 d fed a basal diet with 0.52% digestible TSAA and supplemented with HMTBA levels had optimized BWG, FCR, and breast meat yield estimated as: 0.17, 0.34, and 0.35%; 0.14, 0.21, and 0.33%; and 0.21, 0.31, and 0.36%, using LBL, EA, and QP regressions, respectively. ACKNOWLEDGEMENTS The authors wish to thank Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Novus International for their support. REFERENCES Agostini P. S., Dalibard P., Mercier Y., Van der Aar P., Van der Klis J. D.. 2015. Comparison of methionine sources around requirement levels using a methionine efficacy method in 0 to 28 day old broilers. Poult. Sci. 95: 560– 569. Google Scholar CrossRef Search ADS PubMed AOAC International. 1998. Official Methods of Analysis of AOAC International . AOAC Int., Arlington, VA. Aviagen. 2009. Ross Nutrient Supplement . Aviagen, Scotland, UK. http://www.aviagen.com. Baker D. H., Fernandez S. R., Webel D. M., Parsons C. M.. 1996. Sulfur amino acid requirement and cystine replacement value of broiler chicks during the period three to six weeks post-hatching. Poult. Sci. 75: 737– 742. Google Scholar CrossRef Search ADS PubMed Bishop R. B., Halloran H. R.. 1977. The effect of methionine or methionine hydroxy analogue supplementation on chick response to total sulfur amino acid intake. Poult. Sci. 56: 383– 385. Google Scholar CrossRef Search ADS PubMed Brosnan J. T., Brosnan M. E.. 2006. The sulfur-containing amino acids: An overview. J. Nutr. 136: 1636– 1640. Google Scholar CrossRef Search ADS Cobb-Vantress. 2013. Breeder management guide Cobb 500 . Cobb Vantress Inc., Siloam Springs, AR. Cobb-Vantress. 2015. Breeder management guide Cobb 500 . Cobb Vantress Inc., Siloam Springs, AR. Corzo A., Dozier W. A., Kidd M. T.. 2006. Dietary lysine needs of late-developing heavy broilers. Poult. Sci. 85: 457– 461. Google Scholar CrossRef Search ADS PubMed Corzo A., Kidd M. T., Dozier W. A., Pharr G. T., Koutsos E. A.. 2007. Dietary threonine needs for growth and immunity of broilers raised under different litter conditions. J. Appl. Poult. Res. 16: 574– 582. Google Scholar CrossRef Search ADS Dibner J. J., Knight C. D.. 1984. Conversion of 2-hydroxy-4-(methylthio) butanoic acid to L-methionine in the chick: A stereospecific pathway. J. Nutr. 114: 1716– 1723. Google Scholar CrossRef Search ADS PubMed Dibner J. J., Vázquez-Añón M., Parker D.. 2004. Use of Alimet feed supplements [2-hydroxy-4-(methylthio) butanoic acid, HMTBA] for broiler production. Japan. Poult. Sci. 4: 213– 222. Google Scholar CrossRef Search ADS Dozier W. A., Corzo A., Kidd M. T., Schilling M. W.. 2008a. Dietary digestible lysine requirements of male and female broilers from forty-nine to sixty-three days of age. Poult. Sci. 87: 1385– 1391. Google Scholar CrossRef Search ADS Dozier W. A., Kidd M. T., Corzo A.. 2008b. Dietary amino acid responses of broiler chickens. J. Appl. Poult. Res. 17: 157– 167. Google Scholar CrossRef Search ADS Esteve-Garcia E., Llaurado L.. 1997. Performance, breast meat yield and abdominal fat deposition of male broiler chickens fed diets supplemented with DL-methionine or DL-methionine hydroxy analog free acid. Br. Poult. Sci. 38: 397– 404. Google Scholar CrossRef Search ADS PubMed Garcia A., Batal A. B.. 2005. Changes in the digestible lysine and sulfur amino acid needs of broiler chicks during the first three weeks posthatching. Poult. Sci. 84: 1350– 1355. Google Scholar CrossRef Search ADS PubMed Gilbert E. R., Wong E. A., Webb K. E.. 2008. Board-invited review: Peptide absorption and utilization: Implications for animal nutrition and health. J. Anim. Sci. 86: 2135– 2155. Google Scholar CrossRef Search ADS PubMed Gonzales-Esquerra R., Vásquez-Añón M., Hampton T., York T., Feine S., Wuelling C., Knight C.. 2007. Evidence of a different dose response in turkeys when fed 2-hydroxy-4(methylthio) butanoic acid versus DL-Methionine. Poult. Sci. 86: 517– 524. Google Scholar PubMed Holsheimer J. P. 1981. The protein and amino-acid requirements of broilers between 5 and 6 weeks. 2. Feeding diets supplemented with essential and nonessential amino acids. Arch. Gefluegelkd. 45: 151. Kalinowski A., Moran E. T. Jr., Wyatt C.. 2003. Methionine and cystine requirements of slow- and fast-feathering male broilers from three to six weeks of age. Poult. Sci. 82: 1428– 1437. Google Scholar CrossRef Search ADS PubMed Kratzer D. D., Littell R. C.. 2006. Appropriate statistical methods to compare dose responses of methionine sources. Poult. Sci. 85: 947– 954. Google Scholar CrossRef Search ADS PubMed Lemme A., Hoehler D., Brennan J. J., Mannion P. F. 2002. Relative effectiveness of methionine hydroxy analog compared to DL-methionine in broiler chickens. Poult. Sci. 81: 838– 845. Google Scholar CrossRef Search ADS PubMed Liu Y. L., Song G. L., Yi G. F., Hou Y. Q., Huang J. W., Vázquez-Añón M., Knight C. D.. 2006. Effect of supplementing 2-hydroxy-4-(methylthio) butanoic acid and DL-methionine in corn-soybean-cottonseed meal diets on growth performance and carcass quality of broilers. Asian Australas. J. Anim. Sci. 19: 1197– 1205. Google Scholar CrossRef Search ADS Lucas-Lenard J., Lipmann F.. 1971. Protein biosynthesis. Annu. Rev. Biochem. 40: 409– 448. Google Scholar CrossRef Search ADS PubMed Lumpkins B. S., Batal A. B., Baker D. H.. 2007. Variations in the digestible sulfur amino acid requirement of broiler chickens due to sex, growth criteria, rearing environment, and processing yield characteristics. Poult. Sci. 86: 325– 330. Google Scholar CrossRef Search ADS PubMed Martín-Venegas R., Geraert P. A., Ferrer R.. 2006. Conversion of the methionine hydroxy analogue DL-2-hydroxy-(4-methylthio) butanoic acid to sulfur-containing amino acids in the chicken small intestine. Poult. Sci. 85: 1932– 1938. Google Scholar CrossRef Search ADS PubMed Martín-Venegas R., Teresa Brufau M., Mercier Y., Geraert P. A., Ferrer R.. 2011. Intestinal cell conversion of DL-2-hydroxy-(4-methylthio) butanoic acid in vitro: dietary up-regulation by this methionine precursor. Brit. J. Nutr. 106: 350– 356. Google Scholar CrossRef Search ADS Mitchell N. S., Robbins K. R.. 1983. Effect of dietary energy level on the total sulfur amino acid requirement of growing broilers. Tenn. Farm Home Sci. 125: 6. National Research Council. 1994. Nutrient Requirements of Poultry . 9th rev. ed. Natl. Acad. Press, Washington, DC. Ontiveros R. R., Shermer W. D., Berner R. A.. 1987. An HPLC method for the determination of 2-hydroxy-4-(methylthio)-butanoic acid (HMB) in supplemented animal feeds. J. Agr. Food. Chem. 35: 692– 694. Google Scholar CrossRef Search ADS Opapeju F. O., Htoo J. K., Dapoza C., Nyachoti C. M.. 2012. Bioavailability of methionine hydroxy analog-calcium salt relative to DL-methionine to support nitrogen retention and growth in starter pigs. Anim . 6: 1750– 1756. Google Scholar CrossRef Search ADS Pesti G. M., Vedenov D., Cason J. A., Billard L.. 2009. A comparison of methods to estimate nutritional requirements from experimental data. Brit. Poult. Sci. 50: 16– 32. Google Scholar CrossRef Search ADS Robbins K. R., Norton H. W., Baker D. H.. 1979. Estimation of nutrient requirements from growth data. J. Nutr. 109: 1710– 1714. Google Scholar CrossRef Search ADS PubMed Rodehutscord M., Pack M.. 1999. Estimates of essential amino acid requirements from dose-response studies with rainbow trout and broiler chicken: Effect of mathematical model. Arch. Anim. Nutr. 52: 223– 244. Rostagno H. S., Albino L. F. T., Donzele J. L., Gomes P. C., Oliveira R. F., Lopes D. C., Ferreira A. S., Barreto S. L. T.. 2005. Tabelas brasileiras para aves e suínos: Composição de alimentos e exigências nutricionais . 2nd ed. UFV, Viçosa, MG, Brazil. Rostagno H. S., Albino L. F. T., Donzele J. L., Gomes P. C., Oliveira R. F., Lopes D. C., Ferreira A. S., Barreto S. L. T., Euclides P. F.. 2011. Tabelas brasileiras para aves e suínos. Composição de alimentos e exigências nutricionais . 3rd ed. UFV, Viçosa, MG, Brazil. Sangali C. P., Bruno L. D. G., Nunes R. V., Neto A. R. O., Pozza P. C., Oliveira T. M. M., Frank R., Schöne R. A.. 2014. Bioavailability of different methionine sources for growing broilers. R. Bras. Zootec. , 43: 140– 145. Google Scholar CrossRef Search ADS Sauer N., Emrich K., Piepho H. P., Lemme A., Redshaw M. S., Mosenthin R.. 2008. Meta-analysis of the relative efficiency of methionine-hydroxy-analogue-free-acid compared with dl-methionine in broilers using nonlinear mixed models. Poult. Sci. 87: 2023– 2031. Google Scholar PubMed SAS User's Guide. 2009. Version 9.2 ed. SAS Inst. Inc., Cary, NC. Schmidt C. J., Persia M. E., Feierstein E., Kingham B., Saylor W. W.. 2009. Comparison of a modern broiler line and a heritage line unselected since the 1950 s. Poult. Sci. 88: 2610– 2619. Google Scholar CrossRef Search ADS PubMed Tukey J. 1991. The philosophy of multiple comparisons. Stat. Sci. 6: 100– 116. Google Scholar CrossRef Search ADS Van Weerden E. J., Schutte J. B., Bertram H. L.. 1983. DL-Methionine and DL-Methionine hydroxy free acid in broiler diets. Poult. Sci. 62: 1269– 1274. Google Scholar CrossRef Search ADS Van Weerden E. J., Schutte J. B.. 1984. Comparison of DL-Methionine, DL-Methionine-Na, DL-Methionine hydroxyanalogue-Ca, and DL-Methionine hydroxy-analogue free acid with layers. Poult. Sci. 63: 1793– 1799. Google Scholar CrossRef Search ADS Vázquez-Añón M., Kratzer D., González-Esquerra R., Yi I. G., Knight C. D.. 2006. A multiple regression model approach to contrast the performance of 2-hydroxy-4-methylthio butanoic acid and DL-methionine supplementation tested in broiler trials that are reported in the literature. Poult. Sci. 85: 693– 705. Google Scholar CrossRef Search ADS PubMed Vedenov D., Pesti G. M.. 2008. A comparison of methods of fitting several models to nutritional response data. J. Anim. Sci. 86: 500– 507. Google Scholar CrossRef Search ADS PubMed Vedenov D., Pesti G. M.. 2010. An economic analysis of a methionine source comparison response model. Poult. Sci. 89: 2514– 2520. Google Scholar CrossRef Search ADS PubMed Vieira S. L., Lemme A., Goldenberg D. B., Brugalli I.. 2004. Responses of growing broilers to diets with increased sulfur amino acids to lysine ratios at two dietary protein levels. Poult. Sci. 83: 1307– 1313. Google Scholar CrossRef Search ADS PubMed Wallis I. R. 1999. Dietary supplements of methionine increase breast meat yield and decrease abdominal fat in growing broiler chickens. Aust. J. Exp. Agr. 39: 131– 141. Google Scholar CrossRef Search ADS Warnick R. E., Anderson J. O.. 1968. Limiting essential amino acids in soybean meal for growing chickens and the effects of heat upon availability of the essential amino acids. Poult. Sci. 47: 281– 287. Google Scholar CrossRef Search ADS PubMed Wheeler K. B., Latshaw J. D.. 1981. Sulfur amino acid requirements and interactions in broilers during two growth periods. Poult. Sci. 60: 228. Google Scholar CrossRef Search ADS PubMed Yodseranee R., Bunchasak C.. 2012. Effects of dietary methionine source on productive performance, blood chemical, and hematological profiles in broiler chickens under tropical conditions. Trop. Anim. Health Prod. 44: 1957– 1963. Google Scholar CrossRef Search ADS PubMed © 2018 Poultry Science Association Inc.

Poultry Science – Oxford University Press

**Published: ** Mar 1, 2018

Loading...

personal research library

It’s your single place to instantly

**discover** and **read** the research

that matters to you.

Enjoy **affordable access** to

over 12 million articles from more than

**10,000 peer-reviewed journals**.

All for just $49/month

Read as many articles as you need. **Full articles** with original layout, charts and figures. Read **online**, from anywhere.

Keep up with your field with **Personalized Recommendations** and **Follow Journals** to get automatic updates.

It’s easy to organize your research with our built-in **tools**.

Read from thousands of the leading scholarly journals from *SpringerNature*, *Elsevier*, *Wiley-Blackwell*, *Oxford University Press* and more.

All the latest content is available, no embargo periods.

## “Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”

Daniel C.

## “Whoa! It’s like Spotify but for academic articles.”

@Phil_Robichaud

## “I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”

@deepthiw

## “My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”

@JoseServera

## DeepDyve Freelancer | ## DeepDyve Pro | |

Price | FREE | $49/month $360/year |

Save searches from Google Scholar, PubMed | ||

Create lists to organize your research | ||

Export lists, citations | ||

Access to DeepDyve database | Abstract access only | Unlimited access to over 18 million full-text articles |

Print | 20 pages/month | |

PDF Discount | 20% off | |

Read and print from thousands of top scholarly journals.

System error. Please try again!

or

By signing up, you agree to DeepDyve’s Terms of Service and Privacy Policy.

Already have an account? Log in

Bookmark this article. You can see your Bookmarks on your DeepDyve Library.

To save an article, **log in** first, or **sign up** for a DeepDyve account if you don’t already have one.