Calculating economic values for turkeys using a deterministic production model

2009 ◽  
Vol 89 (2) ◽  
pp. 201-213 ◽  
Author(s):  
B J Wood
Keyword(s):  
Economic Model ◽  
Economic Value ◽  
Production Model ◽  
Feed Consumption ◽  
Production Traits ◽  
Breast Meat ◽  
Economic Values ◽  
High Fecundity ◽  
Production Chain ◽  
Breeding Objectives

Modern poultry breeding has been successful in achieving significant gains in production due to high fecundity, relatively short generation interval (in comparison with other species) and, last, the application of scientific processes in genetic evaluation. The objective of this paper was to document the development of an economic model relevant to the integrated turkey industry and to use the model to describe appropriate breeding objectives by calculating economic values for important production traits. The industry was modelled from the multiplier breeder down through to the processor. Each level in the production chain used a unit of production such as a live poult produced, a carcass delivered at the processing plant or a processed unit of meat to scale between different production divisions. Growth rate, feed consumption and breast meat yield all had similar relative economic value, while the reproductive traits (egg production, fertility and hatchability) had similar economic values to each other, but were smaller in comparison with the commercial production traits. The model was sensitive to assumed costs, such as feed price and, also for assumed returns in the form of breast meat value, and, as a consequence, care must be taken in the assumed pricing structure when calculating economic values for turkey breeding.Key words: Economic model, economic value, turkeys, breeding objectives

scholarly journals Deriving economic values for national sheep breeding objectives using a bio-economic model

2019 ◽  
Vol 227 ◽  
pp. 44-54 ◽  
Author(s):  
A. Bohan ◽  
L. Shalloo ◽  
P. Creighton ◽  
D.P. Berry ◽  
T.M. Boland ◽  
...  
Keyword(s):  
Economic Model ◽  
Economic Values ◽  
Sheep Breeding ◽  
Breeding Objectives

Effects of production and marketing circumstances on economic values for beef production traits

1998 ◽  
Vol 78 (1) ◽  
pp. 47-55 ◽  
Author(s):  
K. R. Koots ◽  
J. P. Gibson
Keyword(s):  
Beef Cattle ◽  
Key Words ◽  
Production System ◽  
Economic Value ◽  
Fixed Costs ◽  
Production Traits ◽  
Beef Production ◽  
Fixed Amount ◽  
Economic Values ◽  
Mature Size

The effect of altering production and marketing circumstances on economic values is quantified for a complete beef production system. Absolute and relative economic values were found to vary substantially with large, but realistic fluctuations in prices and costs. In addition, several examples of different management and different genotypes gave markedly different economic values than in the base situation. Also investigated were the effects of rescaling the enterprise to accommodate three alternative limitations; fixed feed available from pasture, fixed dollars available for feed or fixed amount of beef produced. The effects of rescaling were highly dependent on whether or not fixed costs were accounted for. When fixed costs were ignored (corresponding to a small positive profit) the economic value for mature size decreased while that for fertility increased, but other traits were largely unaffected by rescaling. Overall, production circumstances that reduced survival and fertility yielded the largest changes to economic values. Key words: Economic values, beef cattle, rescaling

Biomarkers as management tools for industries in the pork production chain

2011 ◽  
Vol 11 (2) ◽  
pp. 155-166 ◽  
Author(s):  
Marinus Te Pas ◽  
Arend Hoekman ◽  
Mari Smits
Keyword(s):  
Economic Value ◽  
Biological Processes ◽  
Production Traits ◽  
Management Tools ◽  
Production Chain ◽  
Pork Production ◽  
The Status ◽  
A Chain ◽  
Detection Of Biomarkers ◽  
Pooled Samples

In livestock production, traits such as meat quantity and quality are mainly determined by biological processes. Knowing the biological background of traits makes it possible to identify relevant processes, genes or molecules that may be used as indicators to rapidly and easily detect the status and phase of biological processes. Such indicators are called biomarkers. Thus biomarkers provide information about the status and phase of biological processes underlying particular traits. This information can be used to modulate these processes and thereby optimize the economic value of these traits. To produce products from livestock, pork industries are organized in a production chain – from the breeding industry to the retail industry. Industries in a chain interact with each other to optimize economic value. (Automated) detection of biomarkers could activate processes throughout the chain that can be robotized and computerized, thereby creating economic benefit for all participants in the chain. Biomarkers may be used on individual animals and on pooled samples representing a whole herd for herd management. Here we describe how biomarkers can be developed and how they may be used to enhance value for the pork production chain industries.

scholarly journals  Impact of economic parameters on economic values in dairy sheep

2013 ◽  
Vol 58 (No. 1) ◽  
pp. 21-30 ◽  
Author(s):  
Z. Krupová ◽  
E. Krupa ◽  
M. Wolfová
Keyword(s):  
Milk Production ◽  
Litter Size ◽  
Functional Traits ◽  
Milk Yield ◽  
Growth Traits ◽  
Economic Value ◽  
Production Traits ◽  
Economic Values ◽  
Economic Parameters ◽  
The Impact

The impact of variation in economic conditions on the economic values of fourteen production and functional traits was examined for the Improved Valachian breed using a bio-economic model implemented in the ECOWEIGHT software. The following economic parameters were investigated: market prices of lambs, milk, and cheese (variation ± 40%), costs for roughage, concentrates, and total feeding rations , costs for labour and veterinary care, fixed costs (variation ± 20% for all costs), and discount rate of revenues and costs (0 and 3%). Results of the analyses were presented in detail for the marginal and relative economic values of the four most important traits: milk yield in the 150-day milking period, conception rate of ewes, litter size per lambed ewe, and productive lifetime of ewes. Furthermore, cumulative relative economic values of the four trait complexes – milk production, growth, functional, and wool traits – were presented. Prices for sheep products were found to be the most important factor for both the marginal and the relative economic values of the evaluated traits. The four traits with the highest relative economic values in the base calculation stayed the most important for all investigated economic parameters ranges. The relative economic values of the remaining 10 traits did not exceed 6.1%. The relative economic values of milk yield and litter size were the most sensitive to the variation in economic circumstances. For the investigated range of economic parameters, the relative economic value for the complex of milk production traits ranged 30.6–48.1%, for growth traits 6.3–9.4%, and that for functional traits 45.4–59.7%. The relative economic value for the wool trait did not exceed 0.3%.

scholarly journals Breeding objectives for a Nellore cattle rearing system

2015 ◽  
Vol 50 (9) ◽  
pp. 814-820 ◽  
Author(s):  
Caio Victor Damasceno Carvalho ◽  
Thereza Cristina Calmon de Bittencourt
Keyword(s):  
Economic Model ◽  
Selection Criteria ◽  
The Other ◽  
Economic Values ◽  
Weaning Weight ◽  
Breeding Objectives ◽  
Nellore Cattle ◽  
Indirect Evaluation ◽  
Cattle Rearing ◽  
The Impact

Abstract:The objective of this work was to define the traits that should be included as breeding objectives for Nellore cattle, according to simulations with a bio-economic model for rearing systems. The economic values (EVs) of the traits were calculated as the differences between the profits due to an increased performance of 1% in each trait, with the others traits remaining constant. To determine the impact of each selection on the revenue system, two scenarios were simulated based on the traits being selected. In the first scenario, the adopted selection criteria were: weaning weight (WW), weaning rate (WR), yearling weight (YW), and mature cow weight (MCW). In the second scenario, the cumulative productivity (CP) of dams was used as an indirect evaluation of the performance of calves, with all the other traits included, except WW. In the first scenario, an EV of R$ 1.44 kg-1 was obtained for WW. In the second scenario, an EV of R$ 2.91 kg-1 was obtained for CP. The trait with the highest EV in both scenarios was WR, which enhanced the profits by R$ 3.21 for each 1% increased performance. The meat price paid to the producer is the factor with the greatest impact on the EVs of all examined traits.

scholarly journals Economic values of pork production related traits in Finland

2008 ◽  
Vol 16 (2) ◽  
pp. 79 ◽  
Author(s):  
T. SERENIUS ◽  
P. MUHONEN ◽  
K. STALDER
Keyword(s):  
Meat Quality ◽  
Genetic Gain ◽  
Economic Model ◽  
Production System ◽  
Meat Production ◽  
Production Traits ◽  
Feed Conversion ◽  
Economic Values ◽  
Pork Production ◽  
Lean Meat

The objective of the present study was to estimate economic values for sow efficiency and meat production traits in the Finnish pork production system including the consideration for subsidies. Economic values were estimated by developing a bio-economic model that describes the Finnish production system. Genetic improvement estimates for meat production traits were also developed in order to evaluate how much genetic gain is reduced due to selection for meat quality. Results showed that the highest economic values, when expressed in genetic standard deviations, were obtained for total number of piglets born (€2.07 per piglet), feed conversion ratio (€2.07 per feed unit per kg), and lean meat percentage (€1.69 per %). Economic values for litter size, piglet mortality, sows length of productive life, and lean meat percentage increased when subsidies were not accounted for in the bio-economic model. Results show further that meat quality should have 15–20 percent weight in the Finnish production trait index in order to prevent its deterioration. When the selection weights are 15–20% for meat quality, the expected loss in genetic gain is approximately 3 percent for other production traits when compared to selection indices where meat quality traits are not included.;

Two growth models to estimate economic values for food intake capacity in pigs

1999 ◽  
Vol 69 (1) ◽  
pp. 49-57 ◽  
Author(s):  
P. von Rohr ◽  
A. Hofer ◽  
N. Künzi
Keyword(s):  
Food Intake ◽  
Growth Models ◽  
Average Daily Gain ◽  
Economic Value ◽  
Production Costs ◽  
Production Model ◽  
Economic Values ◽  
Protein Deposition ◽  
Selection Responses ◽  
Economic Production

AbstractEconomic values for average ad libitum food intake capacity (FIC) were estimated with two different linear-plateau models. One model based on a constant minimum fat to protein deposition ratio (Rmin). The other model relied on a constant minimum marginal ratio between fat and protein deposition (MR). Economic values were used to define aggregate genotypes where the driving variables of the growth models were considered as traits. The consequences of a possible implementation of such aggregate genotypes were evaluated with a comparison of the expected selection responses for the different traits.Economic values for the traits under the two models indicated the same direction of selection and differed only slightly in their magnitude. For a FIC below its optimum, FIC had a positive and Rmin or MR a negative, economic value. In this situation the maximum protein deposition rate Pdmax had no influence on the production costs and therefore an economic value of zero. Selection emphasis is then mainly put on FIC which leads to an increase in average daily gain (ADG). If FIC is above its optimum, economic values for FIC were negative, positive for Pdmax and equal to zero for Rmin or MR. Practically no differences between the selection responses under the two growth models were observed.The use of growth models to estimate economic values for FIC allowed to attribute a positive economic value to this trait if it is below its optimum. This is not possible when economic values are estimated with an economic production model.

Co-producing Sea-Ice Predictions with Stakeholders Using Simulation

2021 ◽  
Keyword(s):  
Sea Ice ◽  
Local Community ◽  
Economic Value ◽  
Arctic Region ◽  
Production Model ◽  
The Arctic ◽  
Simulation Game ◽  
Climate Services ◽  
Diverse Range ◽  
Uncertainty Information

Abstract Forecasts of sea-ice evolution in the Arctic region for several months ahead can be of considerable socio-economic value for a diverse range of marine sectors and for local community supply logistics. However, subseasonal-to-seasonal (S2S) forecasts represent a significant technical challenge, while translating user needs into scientifically manageable procedures and robust user confidence requires collaboration among a range of stakeholders. We developed and tested a novel, transdisciplinary co-production approach that combined socio-economic scenarios and participatory, research-driven simulation-gaming to test a new S2S sea-ice forecast system with experienced mariners in the cruise tourism sector. Our custom-developed computerized simulation-game ICEWISE integrated sea-ice parameters, forecast technology and human factors, as a participatory environment for stakeholder engagement. We explored the value of applications-relevant S2S sea-ice prediction and linked uncertainty information. Results suggest that the usefulness of S2S services is currently most evident in schedule-dependent sectors but expected to increase due to anticipated changes in the physical environment and continued growth in Arctic operations. Reliable communication of uncertainty information in sea-ice forecasts must be demonstrated and trialed before users gain confidence in emerging services and technologies. Mariners’ own intuition, experience, and familiarity with forecast service provider reputation impact the extent to which sea-ice information may reduce uncertainties and risks for Arctic mariners. Our insights into the performance of the combined foresight/simulation co-production model in brokering knowledge across a range of domains demonstrates promise. We conclude with an overview of the potential contributions from S2S sea-ice predictions and from experiential co-production models to the development of decision-driven and science-informed climate services.

Genetic variation in net feed efficiency in Hereford cattle and its association with other production traits

1999 ◽  
Vol 1999 ◽  
pp. 47-47
Author(s):  
R.M. Herd ◽  
S.C. Bishop
Keyword(s):  
Growth Rate ◽  
Genetic Variation ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Genetic Correlations ◽  
Feed Consumption ◽  
Production Traits ◽  
Performance Measurements ◽  
Hereford Cattle ◽  
Rate Selection

Net feed efficiency refers to variation in feed consumption between animals net of requirements for maintenance and production, and may be measured as residual feed intake (RFI). Because RFI is independent of liveweight (LW) and growth rate, selection for improved net feed efficiency is likely to reduce feed intake with little change in growth. The purpose of this study was to establish whether there exists genetic variation in RFI in young British Hereford bulls, and to determine the phenotypic and genetic correlations of RFI with key production traits.The data consisted of performance measurements on 540 bull progeny of 154 British Hereford sires, collected over ten 200-day postweaning performance tests conducted between 1979 and 1988. The traits analysed were food intake (FI), 200 to 400-day daily gain (ADG), 400-day weight (W400), predicted carcass lean content (LEAN), lean growth rate (LGR), food conversion ratio (FI/ADG) and lean FCR (LFCR; FI/(ADG x LEAN), described by Bishop (1992).

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