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Poult Sci ; 100(9): 101375, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34358953


The amount and timing of growth are important factors that affect age at first egg, body conformation, reproductive performance, and hunger in broiler breeders. To investigate the effect of growth pattern on feeding motivation and reproductive performance, 10 unique growth trajectories were designed with 2 levels of the amount of early growth and 5 levels of timing of growth around puberty. A 3-phase Gompertz model that described growth in phase 1 (prepubertal), phase 2 (pubertal), and phase 3 (postpubertal) was used to design the growth trajectories. Second growth phase inflection point (I2) was advanced by 0, 5, 10, 15, or 20% of the coefficient estimated from the breeder-recommended target BW. The growth trajectories were designed with 2 discrete levels of total gain in the prepubertal phase (g1); g1 was either the prepubertal phase gain coefficient, estimated from the breeder-recommended BW (Standard g1) target, or 10% higher (High g1). Forty females were randomly assigned to the growth trajectories using a precision feeding (PF) system. Analysis of covariance was conducted on dependent variables in ten 4-wk periods with g1 and periods as discrete fixed effects, I2 as a continuous fixed effect, and age as a random effect. Differences were reported at P ≤ 0.05. For every week of earlier I2, body weight at photostimulation (BWPS) increased by 126 g; BW at first egg (BWFE) increased by 94 g; 24 wk shank length increased by 0.038 and 1.495 mm in the Standard g1 and High g1 treatments; 24 wk body fat increased by 0.38%; pullets came to lay earlier by 0.49 d; egg weight (EW) increased by 0.27 g; egg production and egg mass (EM) increased by 0.33 egg/hen/d and 0.916 g/d in the High g1 treatment but decreased by 0.27 egg/hen/d and 0.29 g/d in the Standard g1 treatment, respectively. Increasing g1 reduced feeding motivation index by 1.6 and 0.8 visits/meal during rearing and laying phase, respectively. Earlier pubertal growth showed prominent effects on the reproductive performance.

Galinhas , Motivação , Ração Animal/análise , Animais , Peso Corporal , Dieta , Feminino , Fenótipo , Reprodução , Maturidade Sexual
Poult Sci ; 100(8): 101187, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34198100


Identifying daily oviposition events for individual broiler breeders is important for bird management. Identifying non-laying birds in a flock that might be caused by improper nutrition or diseases can guide diet changes or disease treatments for these individuals. Oviposition depends on follicle maturation and egg formation, and follicle maturation can be variable. As such, the day and time of oviposition events of individual birds in a free-run flock can be hard to predict. Based on a precision feeding (PF) system that can record the feeding activity of individual birds, a recent study reported a machine learning model to predict daily egg-laying events of broiler breeders. However, there were 2 limitations in that study: 1) It could only be used to identify daily egg-laying events on a subsequent day; 2) The prediction outputs that were binary labels were unable to indicate more details among the outputs with the same label. To improve the previous approach, the current study aimed to predict and output the probability of daily oviposition events occurring using a specific time point in 1 day. In the current study, 706 egg-laying events recorded by nest boxes with radio frequency identification of hens and 706 randomly selected no-egg-laying events were used. The anchor point was newly defined in the current study as a specific time point in 1 day, and 26 features around the anchor point were created for all events (706 egg-laying events and 706 no-egg-laying events). A feed-forward artificial neural network (ANN) model was built for prediction. The area under the receiver operating characteristic (ROC) curve was 0.9409, indicating that the model had an outstanding classification performance. The ANN model could predict oviposition events on the current day, and the output was a probability that could be informative to indicate the likelihood of an oviposition event for an individual breeder. In situations where total egg production was known for a group, the ANN model could predict the probability of daily oviposition events occurring of all individual birds and then rank them to choose those most likely to have laid an egg.

Galinhas , Oviposição , Ração Animal , Animais , Feminino , Redes Neurais de Computação , Probabilidade
Poult Sci ; 100(6): 101090, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-33975037


Maternal growth patterns affect broiler growth performance. The current study investigated the impact of lesser growth restriction, compared to the breeder-recommended target growth, during the prepubertal growth phase and earlier pubertal growth in breeders on their offspring growth and carcass traits. In a randomized controlled trial, a total of 40 female broiler breeders were randomly assigned to 10 unique growth trajectories with 2 levels of maternal BW gain (MW) in prepubertal phase and 5 levels of maternal pubertal growth inflection (MI) for each level of the MW. Growth parameters (MW and MI) were estimated by fitting a 3-phase Gompertz model to the breeder-recommended BW target (Standard MW; SMW), or 10% higher (HMW). Maternal pubertal inflection was advanced by 0, 5, 10, 15, or 20% in both SMW and HMW groups. Maternal growth trajectories were implemented from 0 to 42 wk of age using a precision feeding (PF) system. The current study consisted of two cohorts that varied in maternal age (MA) of 35 and 42 wk. The broiler chicks were fed to 35 d of age, also with the PF system. Analysis of covariance was conducted on all dependent variables (BW, FCR, carcass traits) with MA, MW, and offspring sex as categorical variables and MI as a continuous predictor variable. Chicks from 42 wk old hens had higher 0 (hatch), 14, 21, and 28 d BW, liver, and heart weight, and lower FCR from 7 to 35 d of age than those from the 35 wk old hens. Compared to SMW hens, HMW hens produced female offspring with lower FCR, and male offspring with heavier gut weight. Advancing MI increased hatch BW in both sexes and 35 d BW in male broilers. For every week that the MI was advanced, hatch BW increased by 0.26 g in females and 0.39 g in males; however, 21 and 35 d BW decreased by 6.85 and 17.29 g/wk in females and increased by 10.53 and 25.94 g/wk in males, respectively. Overall, a lesser degree of growth restriction during prepubertal and earlier pubertal growth increased male offspring growth.

Galinhas , Fígado , Ração Animal/análise , Animais , Peso Corporal , Dieta , Feminino , Masculino
Poult Sci ; 100(5): 101059, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-33756248


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: [Formula: see text] ; 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 âˆ¼ N(0,VWm) and bu âˆ¼ 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.

Galinhas , Ingestão de Alimentos , Ração Animal/análise , Animais , Peso Corporal , Galinhas/genética , Dinâmica não Linear