schauer birgit (12 résultats)

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Taschenbuch. Etat : Neu. Factors associated with market weight on three New Zealand pig farms | An observational study to identify performance parameters that allow predicting market weight on commercial pig farms | Birgit Schauer (u. a.) | Taschenbuch | 168 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844382259 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents research on sources of errors in pig weight measurements. Three studies were conducted on a New Zealand pig farm. First, finisher pigs fed ad libitum or via a liquid feeding system were weighed four times a day over a four-day period. Results showed that standardizing weighing time reduced fluctuations in pig weights. Next, the effect of overnight feed withdrawal on reducing variation in pig weigths and growth rate was investigated. Feed withdrawal reduced variability by up to 11.5% in grower and finisher pigs, whilst the effect was inconsistent in weaner pigs. Lastly, sampling error was compared when sampling pens from batches of pigs using different sample sizes and sampling methods. Increasing the portion of randomly selected pens reduced sampling error, but in a diminishing manner. Purposive selection of two pens reduced sampling error by 64% compared with random sampling, but it introduces the risk of bias. Thus, pens should be selected at random. Results may serve as an educational tool on how to reduce errors in pig weights. More accurate data will lead to improved interpretability of growth records. 152 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The aim of this observational study was to identify performance parameters, which can be used to predict market weight of a batch of pigs on commercial farms. Weekly retro- and prospective production records were obtained from three New Zealand pig farms. Observation periods on farms A, B, and C were 140, 127 and 90 weeks. Two modelling approaches were used for multivariable analysis to account for autocorrelation: An autoregressive (AR) and an ordinary least squares (OLS) regression model ( naive approach ). Each farm was analysed separately. Using an AR-model, four production parameters (weaning age, two sample weights and days to market) were identified across all farms that were effective in predicting market weight with accuracies greater than 70%. All AR-models yielded stationary and normally distributed residuals. In contrast, residuals of the OLS-models showed remaining autocorrelation on two farms indicating biased model estimates. Using an AR-model also has the advantage that immediate future observations can be forecasted. This is particularly useful as predictor variables (apart from 'Days to market') could be obtained a month prior to marketing. 168 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents research on sources of errors in pig weight measurements. Three studies were conducted on a New Zealand pig farm. First, finisher pigs fed ad libitum or via a liquid feeding system were weighed four times a day over a four-day period. Res.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Schauer BirgitDr Birgit Schauer, studied veterinary medicine at Ludwig-Maximilian-Univ (LMU). Specialized in epidemiology. German doctorate (joint project betw. LMU and EpiCentre, Massey, NZ). MVSt at the EpiCentre. Since 2008, techn.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents research on sources of errors in pig weight measurements. Three studies were conducted on a New Zealand pig farm. First, finisher pigs fed ad libitum or via a liquid feeding system were weighed four times a day over a four-day period. Results showed that standardizing weighing time reduced fluctuations in pig weights. Next, the effect of overnight feed withdrawal on reducing variation in pig weigths and growth rate was investigated. Feed withdrawal reduced variability by up to 11.5% in grower and finisher pigs, whilst the effect was inconsistent in weaner pigs. Lastly, sampling error was compared when sampling pens from batches of pigs using different sample sizes and sampling methods. Increasing the portion of randomly selected pens reduced sampling error, but in a diminishing manner. Purposive selection of two pens reduced sampling error by 64% compared with random sampling, but it introduces the risk of bias. Thus, pens should be selected at random. Results may serve as an educational tool on how to reduce errors in pig weights. More accurate data will lead to improved interpretability of growth records.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 152 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents research on sources of errors in pig weight measurements. Three studies were conducted on a New Zealand pig farm. First, finisher pigs fed ad libitum or via a liquid feeding system were weighed four times a day over a four-day period. Results showed that standardizing weighing time reduced fluctuations in pig weights. Next, the effect of overnight feed withdrawal on reducing variation in pig weigths and growth rate was investigated. Feed withdrawal reduced variability by up to 11.5% in grower and finisher pigs, whilst the effect was inconsistent in weaner pigs. Lastly, sampling error was compared when sampling pens from batches of pigs using different sample sizes and sampling methods. Increasing the portion of randomly selected pens reduced sampling error, but in a diminishing manner. Purposive selection of two pens reduced sampling error by 64% compared with random sampling, but it introduces the risk of bias. Thus, pens should be selected at random. Results may serve as an educational tool on how to reduce errors in pig weights. More accurate data will lead to improved interpretability of growth records.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The aim of this observational study was to identify performance parameters, which can be used to predict market weight of a batch of pigs on commercial farms. Weekly retro- and prospective production records were obtained from three New Zealand pig farms. Observation periods on farms A, B, and C were 140, 127 and 90 weeks. Two modelling approaches were used for multivariable analysis to account for autocorrelation: An autoregressive (AR) and an ordinary least squares (OLS) regression model ('naive approach'). Each farm was analysed separately. Using an AR-model, four production parameters (weaning age, two sample weights and days to market) were identified across all farms that were effective in predicting market weight with accuracies greater than 70%. All AR-models yielded stationary and normally distributed residuals. In contrast, residuals of the OLS-models showed remaining autocorrelation on two farms indicating biased model estimates. Using an AR-model also has the advantage that immediate future observations can be forecasted. This is particularly useful as predictor variables (apart from 'Days to market') could be obtained a month prior to marketing.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 168 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The aim of this observational study was to identify performance parameters, which can be used to predict market weight of a batch of pigs on commercial farms. Weekly retro- and prospective production records were obtained from three New Zealand pig farms. Observation periods on farms A, B, and C were 140, 127 and 90 weeks. Two modelling approaches were used for multivariable analysis to account for autocorrelation: An autoregressive (AR) and an ordinary least squares (OLS) regression model ( naive approach ). Each farm was analysed separately. Using an AR-model, four production parameters (weaning age, two sample weights and days to market) were identified across all farms that were effective in predicting market weight with accuracies greater than 70%. All AR-models yielded stationary and normally distributed residuals. In contrast, residuals of the OLS-models showed remaining autocorrelation on two farms indicating biased model estimates. Using an AR-model also has the advantage that immediate future observations can be forecasted. This is particularly useful as predictor variables (apart from 'Days to market') could be obtained a month prior to marketing.