Improving a nonlinear Gompertz growth model using bird-specific random coefficients in two heritage chicken lines

Growth models describe body weight (BW) changes over time, allowing information from longitudinal measurements to be combined into a few parameters with biological interpretation. Nonlinear mixed models (NLMM) allow for the inclusion of random factors. Random factors can account for a relatively large subset of the total variance explained by bird-specific measurement correlation. The aim of this study was to evaluate different NLMM using birds from 2 heritage chicken lines; New Hampshire (NH) and Brown Leghorn (BL). A total of 32 birds (16 mixed sex birds from each strain) were raised to 17 wk of age. After 12 wk, half were continued on ad libitum (AL) feed intake, and half were pair-fed, using a precision feeding system; they were given 95% of the AL intake of a paired bird closest in BW. Residual feed intake (RFI) of birds, as an indicator of production efficiency, was increased in pair-fed BL birds as a result of minor feed restriction. Growth data of the birds were fit to a mixed Gompertz model with a variety of different bird-specific random coefficients. The model had the form: BW=Wm×exp−exp−b(t−tinf); where Wm was the mature BW, b was the rate of maturing, t was age (d), tinf was the inflection point (d). This fixed-effects model was compared with NLMM using model evaluation criteria to evaluate relative model suitability. Random coefficients, Wmu ∼ N(0,VWm) and bu ∼ N(0,Vb), were tested separately and together and their differences, for strains, sex, and feeding treatments, were reported as different where P ≤ 0.05. The model with both random coefficients was determined to be the most parsimonious model, based on an assessment of serial correlation of the residuals. NLMM coefficients allow stochastic prediction of the mean age and its variation that birds need to achieve a certain BW, allowing for unique new decision support modeling applications; these could be used in stochastic modeling to evaluate the economic impact of management decisions.</p

Architecture of broiler breeder energy partitioning models

A robust model that estimates the ME intake over broiler breeder lifetime is essential for formulating diets with optimum nutrient levels. The experiment was conducted as a randomized controlled trial with 40 Ross 708 broiler breeder pullets reared on 1 of 10 target growth trajectories, which were designed with 2 levels of cumulative BW gain in prepubertal growth phase and 5 levels of timing of growth around puberty. This study investigated the effect of growth pattern on energy efficiency of birds and tested the effects of dividing data into daily, 4-d, weekly, 2-wk, and 3-wk periods and the inclusion of random terms associated with individual maintenance ME and ADG requirements, and age on ME partitioning model fit and predictive performance. Model [I] was: MEId = a × BWb + c × ADGp + d × ADGn + e × EM + ε, where MEId was daily ME intake (kcal/d); BW in kg; ADGp was positive ADG; ADGn was negative ADG (g/d); EM was egg mass (g/d); ε was the model residual. Models [II to IV] were nonlinear mixed models based on the model [I] with inclusion of a random term for individual maintenance requirement, age, and ADG, respectively. Model [II] – 3 wk was chosen as the most parsimonious based on lower autocorrelation bias, closer fit of the estimates to the actual data (lower model MSE and closer R2 to 1), and greater predictive performance among the models. Estimated ME partitioned to maintenance in model [II] – 3 wk was 100.47 ± 7.43 kcal/kg0.56, and the ME requirement for ADGp, ADGn, and EM were 3.49 ± 0.37; 3.16 ± 3.91; and 2.96 ± 0.13 kcal/g, respectively. Standard treatment had lower residual heat production (RHP; -0.68 kcal/kg BW0.56) than high early growth treatment (0.79 kcal/kg BW0.56), indicating greater efficiency in utilizing the ME consumed. Including random term associated with individual maintenance ME in a 3-wk chunk size provided a robust, biologically sound life-time energy partitioning model for breeders

Arsenic Metabolites, Including <i>N</i>‑Acetyl-4-hydroxy-m-arsanilic Acid, in Chicken Litter from a Roxarsone-Feeding Study Involving 1600 Chickens

The poultry industry has used organoarsenicals, such as 3-nitro-4-hydroxyphenylarsonic acid (Roxarsone, ROX), to prevent disease and to promote growth. Although previous studies have analyzed arsenic species in chicken litter after composting or after application to agricultural lands, it is not clear what arsenic species were excreted by chickens before biotransformation of arsenic species during composting. We describe here the identification and quantitation of arsenic species in chicken litter repeatedly collected on days 14, 24, 28, 30, and 35 of a Roxarsone-feeding study involving 1600 chickens of two strains. High performance liquid chromatography separation with simultaneous detection by both inductively coupled plasma mass spectrometry and electrospray ionization tandem mass spectrometry provided complementary information necessary for the identification and quantitation of arsenic species. A new metabolite, <i>N</i>-acetyl-4-hydroxy-m-arsanilic acid (N-AHAA), was identified, and it accounted for 3–12% of total arsenic. Speciation analyses of litter samples collected from ROX-fed chickens on days 14, 24, 28, 30, and 35 showed the presence of N-AHAA, 3-amino-4-hydroxyphenylarsonic acid (3-AHPAA), inorganic arsenite (As^III), arsenate (As^V), monomethylarsonic acid (MMA^V), dimethylarsinic acid (DMA^V), and ROX. 3-AHPAA accounted for 3–19% of the total arsenic. Inorganic arsenicals (the sum of As^III and As^V) comprised 2–6% (mean 3.5%) of total arsenic. Our results on the detection of inorganic arsenicals, methylarsenicals, 3-AHPAA, and <i>N</i>-AHAA in the chicken litter support recent findings that ROX is actually metabolized by the chicken or its gut microbiome. The presence of the toxic metabolites in chicken litter is environmentally relevant as chicken litter is commonly used as fertilizer

Involvement of tachykinin NK1 receptor in the development of allergen-induced airway hyperreactivity and airway inflammation in conscious, unrestrained guinea pigs

It has been suggested that tachykinin NK1 receptor-mediated neurogenic inflammation, characterized by microvascular leakage, mucus secretion, and infiltration and activation of inflammatory cells in the airways, may be involved in allergic asthma. Therefore, in a guinea pig model of allergic asthma, we investigated the involvement of the NK1 receptor in allergen-induced early (EAR) and late (LAR) asthmatic reactions, airway hyperreactivity (AHR) after these reactions and airway inflammation, using the selective nonpeptide NK1 receptor antagonist SR140333. On two different occasions, separated by 1 wk interval, OA-sensitized guinea pigs inhaled either saline (3 min) or SR140333 (100 nM, 3 min) at 30 min before as well as at 5.5 h after OA provocation (between the EAR and LAR) in a random crossover design. A control group, receiving saline inhalations before and at 5.5 h after the two OA provocations, was included as well. SR140333 had no significant effect on either the EAR or the LAR compared with saline control inhalations. However, the NK1 receptor antagonist significantly reduced the OA-induced AHR to histamine, both after the EAR at 5 h after OA challenge (1.77+/- 0.13-fold increase in histamine reactivity versus 2.50 +/- 0.25-fold increase in the control animals, p <0.01) and after the LAR at 23 h after OA challenge (1.15 +/- 0.12-fold increase versus 1.98 +/- 0.34-fold increase, respectively, p <0.05). Moreover, bronchoalveolar ravage studies performed at 25 h after the second OA provocation indicated that SR140333 significantly inhibited the allergen-induced infiltration of eosinophils, neutrophils, and lymphocytes in the airways (p <0.05 for all observations), whereas a tendency to reduced accumulation of ciliated epithelial cells in the airway lumen was observed (p = 0.10). These results indicate that the NK1 receptor is involved in the development of allergen-induced AHR to histamine, and that NK1 receptor-mediated infiltration of inflammatory cells in the airways may contribute to this AHR