scholarly journals Nigerian Fulani ecotype chickens - II – Estimation of growth curve parameters

2019 ◽  
Vol 46 (3) ◽  
pp. 10-22
Author(s):  
A. R. Sanusi ◽  
S. O. Oseni
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Goodness Of Fit ◽  
Management Practices ◽  
Linear Growth ◽  
Production Systems ◽  
Poultry Production ◽  
Growth Functions ◽  
Non Linear ◽  
Best Fit

In the study, growth curves of Nigerian Fulani ecotype chickens (NFEC) were modelled  under two production systems with four non-linear growth functions with a view to  establishing growth descriptors for NFEC. Two hundred, day-old chicks of NFEC were  obtained from an established population of NFEC. The chickens were separated randomly to  intensive and pastured poultry production systems at 12 weeks of age. Data on body weight  were taken weekly over a period of 20 weeks. Four non-linear growth functions including  Gompertz, Logistic, Bertalanffy and Richard's models were fitted using the NLIN procedure  of SAS while the best fit model was selected using the goodness-of-fit tests. For all the models, parameter (A), the asymptotic weight, ranged between 1800g and 2417g for male  and 1208g and 1550g for female chickens respectively. Parameter (B), the scaling parameter  ranged from 0.77 and 19.79. Parameter K, which is the maturity index, ranged between 0.16 and 3.97 for both sexes. The R values ranged between 0.9689 and 0.9987 for all the models  fitted. Gompertz and Bertalanffy models emerged as the best fit functions. Age and body  weight at inflection of NFEC were also predicted by the study. Growth curve parameters of  NFEC in the pastured poultry system were not significantly different from those in the  intensive system. The growth curve parameters estimated indicates that NFEC growth  performance can be improved through effective breeding strategies and improved  management practices.

scholarly journals Application of Non-linear Growth Curve Models to Body Weight in Egg-type Chicken.

1995 ◽  
Vol 32 (6) ◽  
pp. 394-401 ◽  
Author(s):  
Shunzo MIYOSHI ◽  
Mitsuyoshi SUZUKI ◽  
Takatsugu MITSUMOTO
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Linear Growth ◽  
Growth Curve Models ◽  
Non Linear ◽  
Linear Growth Curve

scholarly journals The Effects of Heat Stress on Production, Reproduction, Health in Chicken and Its Dietary Amelioration

2021 ◽  
Author(s):  
Mathew Gitau Gicheha
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Management Practices ◽  
Production Systems ◽  
Thermal Environment ◽  
Climatic Variability ◽  
Poultry Production ◽  
Subsequent Increase ◽  
Thermal Environments ◽  
Genetic Potential

Farm profitability is the key driver of most livestock enterprises. The productivity and profitability are driven by genetic potential of the animals and the ability to express the superiority in the production environment. In an ideal situation, an animal should produce maximally as dictated by the genetic potential. It is noteworthy that the environment in which an animal lives in impacts on its ability to expose its genetic potential. Studies have shown that it is rarely feasible to provide animals with ideal conditions to express their full genetic potential. The environment in which animals are reared is characterised by many factors that interact in ways that result in different performance even in animals of similar genetic makeup. For instance, thermal environment is critical in poultry production as it affects both the production and reproduction in different ways. The thermal environment affects chicken differently depending on the stage of growth or production phase. This environment has been impacted by the climate change and subsequent increase in climatic variability resulting in thermal challenges in naturally produced chicken thus altering production and reproduction. This implies that there is need to consider thermal resource in the routine poultry management practices. This would result to design of poultry production systems responsive to the thermal environments more so in the light of climate change and the subsequent increase in climatic variability. This chapter explores the impact of heat stress on chicken production, reproduction, health and its dietary amelioration.

scholarly journals Modeling the Growth of Four Commercial Broiler Genotypes Reared in the Tropics

2021 ◽  
Author(s):  
Bernard Ato Hagan ◽  
Christian Asumah ◽  
Ernest Darkwah Yeboah ◽  
Vida Korkor Lamptey
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Polynomial Growth ◽  
Gompertz Function ◽  
Final Body Weight ◽  
Growth Functions ◽  
Broiler Production ◽  
Commercial Broiler ◽  
The Tropics ◽  
Late Growth

Abstract Genetic improvement in commercial broilers worldwide is heavily focused on selection for higher final body weight at a given age. Although commercial broilers are mostly sold by their final body weight, it is important to pay attention to how this weight is attained and at what cost. The cost of feeding broilers, which constitutes about 70% of the total cost of broiler production, varies considerably at different stages of the bird. It is, therefore, important to pay attention to the growth curve of broilers and the parameters of the growth curve to maximise profitability of commercial broiler production. The objective of this study was to model the variations of the growth curves of 4 commercial broiler genotypes reared in Ghana using the Gompertz and polynomial growth functions. Data on body weights at 1, 7, 14, 21, 28, 35 and 42 days for 4 unsexed commercial broiler genotypes were used to model both the Gompertz and polynomial growth functions. The 4 genotypes ranked differently for Gompertz predicted early (1 - 28 days), late growth (28 – 42 days) and body weight at 42 days. Gompertz function predicted growth better for broiler chicken than the polynomial as the parameters of the Gompertz function are biologically meaningful and heritable. Selection of broiler genotypes for production based on their growth curve (slower early growth and faster late growth) could minimize cost of production and thereby increase the profitability of commercial broiler production in the tropics.

Assessment of nitrogen and phosphorus loads present in environments impacted by alternative poultry processing operations utilized in pasture-raised poultry production

2015 ◽  
Vol 32 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Corliss A. O'Bryan ◽  
Philip Crandall ◽  
Divya Jaroni ◽  
Steven C. Ricke ◽  
Kristen E. Gibson
Keyword(s):  
Moisture Content ◽  
Best Management Practices ◽  
Pilot Plant ◽  
Management Practices ◽  
Production Systems ◽  
Land Application ◽  
Published Data ◽  
Poultry Production ◽  
Poultry Processing ◽  
On Farm

AbstractPasture-raised poultry (PP) production systems allow chickens, turkeys or other poultry types to be raised entirely on pasture or in small, open-air moveable pens with access to fresh pasture daily. With an increase in consumer demand for poultry products produced using more humane and potentially environmentally sustainable practices, PP production systems are regaining popularity among farmers across the USA. The majority of research on PP is related to meat quality and forage conditions while the environmental effects have remained largely unstudied. The rotation of poultry on pasture is one of the primary best management practices (BMP) used to avoid over grazing and buildup of excess nutrients and pathogens; however, BMPs for handling and processing of the associated wastes (i.e., wastewater, feathers, offal) related to on-farm processing and mobile poultry processing units (MPPU) are not as well established. Therefore, a study with PP growers in the southern USA was initiated to provide important baseline information on the potential environmental impacts of processing methods used by PP production systems. Here, three farms utilizing on-farm processing were sampled over a 9-month period and two farms utilizing a MPPU pilot plant were sampled over a 3-month period. Soil, compost and wastewater samples were collected during each sampling date for on-farm processing while only wastewater was collected at the MPPU pilot plant. Soil samples (24-cm cores) were analyzed for total nitrogen (TN), Mehlich-3 extractable phosphorus (M3-P) and moisture content. Compost derived from processing wastes was analyzed for TN, total phosphorus (TP), water extractable P and moisture content. Wastewaters were analyzed for total Kjeldahl nitrogen (TKN) and TP. Soil TN levels (0.075–0.30%) reported here are comparable with TN levels reported for various soils in the Southeastern USA while M3-P was generally below levels found in agricultural soils subject to conventional poultry litter application based on previously published data. Conversely, TN and TP levels—0.3 to 1.3 and <0.4%, respectively—in compost were well below recommended values (i.e., approximately 2% each of N and P) for compost highlighting an opportunity for PP growers to create a more useful compost for land application. Last, wastewater collected from both, on-farm processing and the MPPU measure TKN and TP levels were much less than conventional processing. Overall, the present study provided baseline data on soil and compost nutrients related to on-farm poultry processing as well as wastewater composition for on-farm processing and MPPUs.

Two Aspects of the Simplex Model: Goodness of Fit to Linear Growth Curve Structures and the Analysis of Mean Trends

1994 ◽  
Vol 19 (3) ◽  
pp. 201-215 ◽  
Author(s):  
Frantisek Mandys ◽  
Conor V. Dolan ◽  
Peter C. M. Molenaar
Keyword(s):  
Individual Differences ◽  
Growth Curve ◽  
Goodness Of Fit ◽  
Linear Growth ◽  
Covariance Structure ◽  
Growth Curve Model ◽  
Simplex Model ◽  
Curve Model ◽  
Structured Means ◽  
Linear Growth Curve

This article has two objectives. The first is to investigate in greater detail the finding of Rogosa and Willett that the quasi-Markov simplex model fits a linear growth curve covariance structure. It is found that under various circumstances the quasi-Markov simplex model is rejected. Furthermore, the procedure is reversed by fitting the linear growth curve to quasi-Markov simplex covariance structure. It is found that the linear growth curve, like the quasi-Markov simplex, is not always rejected even though the model is formally incorrect. The second objective of this article is to present a quasi-Markov simplex model with structured means. This model, like the linear growth curve model with structured means, is based on the assumption that the variation in means and individual differences are attributable to the same causal agents. We argue that this assumption should be tested explicitly. An example is given.

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