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Christopher K Wikle - One of the best experts on this subject based on the ideXlab platform.
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a bayesian adaptive ensemble kalman filter for sequential state and parameter estimation
Monthly Weather Review, 2017Co-Authors: Jonathan R Stroud, Matthias Katzfuss, Christopher K WikleAbstract:AbstractThis paper proposes new methodology for sequential state and parameter estimation within the ensemble Kalman filter. The method is fully Bayesian and propagates the joint Posterior Distribution of states and parameters over time. To implement the method, the authors consider three representations of the Marginal Posterior Distribution of the parameters: a grid-based approach, a Gaussian approximation, and a sequential importance sampling (SIR) approach with kernel resampling. In contrast to existing online parameter estimation algorithms, the new method explicitly accounts for parameter uncertainty and provides a formal way to combine information about the parameters from data at different time periods. The method is illustrated and compared to existing approaches using simulated and real data.
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a bayesian adaptive ensemble kalman filter for sequential state and parameter estimation
arXiv: Methodology, 2016Co-Authors: Jonathan R Stroud, Matthias Katzfuss, Christopher K WikleAbstract:This paper proposes new methodology for sequential state and parameter estimation within the ensemble Kalman filter. The method is fully Bayesian and propagates the joint Posterior density of states and parameters over time. In order to implement the method we consider two representations of the Marginal Posterior Distribution of the parameters: a grid-based approach and a Gaussian approximation. Contrary to existing algorithms, the new method explicitly accounts for parameter uncertainty and provides a formal way to combine information about the parameters from data at different time periods. The method is illustrated and compared to existing approaches using simulated and real data.
Giuseppe Massimo Vacca - One of the best experts on this subject based on the ideXlab platform.
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phenotypic and genetic relationships between indicators of the mammary gland health status and milk composition coagulation and curd firming in dairy sheep
Journal of Dairy Science, 2018Co-Authors: Michele Pazzola, Giovanni Bittante, Claudio Cipolatgotet, Maria Luisa Dettori, A Cecchinato, Giuseppe Massimo VaccaAbstract:ABSTRACT The present study investigated the effect of somatic cell count, lactose, and pH on sheep milk composition, coagulation properties (MCP), and curd firming (CF) parameters. Individual milk samples were collected from 1,114 Sarda ewes reared in 23 farms. Milk composition, somatic cell count, single point MCP (rennet coagulation time, RCT; curd firming time, k 20 ; and curd firmness, a 30 , a 45 , and a 60 ), and CF model parameters were achieved. Phenotypic traits were statistically analyzed using a mixed model to estimate the effects of the different levels of milk somatic cell score (SCS), lactose, and pH, respectively. Additive genetic, herd, and residual correlations among these 3 traits, and with milk composition, MCP and CF parameters, were inferred using a Bayesian approach. From a phenotypic point of view, higher SCS levels caused a delayed gelification of milk. Lactose concentration and pH were significant for many milk quality traits, with a very intense effect on both coagulation times and curd firming. These traits (RCT, RCT estimated using the curd firming over time equation, and k 20 ) showed an unfavorable increase of about 20% from the highest to the lowest level of lactose. Milk samples with pH values lower than 6.56 versus higher than 6.78 were characterized by an increase of RCT (from 6.00 to 14.3 min) and k 20 (from 1.65 to 2.65 min) and a decrease of all the 3 curd firmness traits. From a genetic point of view, the Marginal Posterior Distribution of heritability estimates evidenced a large and exploitable variability for all 3 phenotypes. The mean intra-farm heritability estimates were 0.173 for SCS, 0.418 for lactose content, and 0.206 for pH. Lactose (favorably), and SCS and pH (unfavorably), at phenotypic and genetic levels, were correlated mainly with RCT and RCT estimated using the curd firming over time equation and scarcely with the other curd firming traits. The SCS, lactose, and pH were significantly correlated with each other's. In conclusion, results reported in the present study suggest that SCS, pH, and lactose affect, contemporarily and independently, milk quality and MCP. These phenotypes, easily available during milk recording schemes measured by infrared spectra prediction, could be used as potential indicators traits for improving cheese-making ability of ovine milk.
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genetic analysis of coagulation properties curd firming modeling milk yield composition and acidity in sarda dairy sheep
Journal of Dairy Science, 2017Co-Authors: Giovanni Bittante, Claudio Cipolatgotet, Michele Pazzola, Maria Luisa Dettori, Giuseppe Massimo Vacca, A CecchinatoAbstract:Sheep milk is an important source of food, especially in Mediterranean countries, and is used in large part for cheese production. Milk technological traits are important for the sheep dairy industry, but research is lacking into the genetic variation of such traits. Therefore the aim of this study was to estimate the heritability of traditional milk coagulation properties and curd firmness modeled on time t (CFt) parameters, and their genetic relationships with test-day milk yield, composition (fat, protein, and casein content), and acidity in Sarda dairy sheep. Milk samples from 1,121 Sarda ewes from 23 flocks were analyzed for 5 traditional coagulation properties by lactodynamographic tests conducted for up to 60min: rennet coagulation time (min), curd-firming time (k20, min), and 3measures of curd firmness (a30, a45, and a60, mm). The 240 curd firmness observations (1 every 15 s) from each milk sample were recorded, and 4 parameters for each individual sample equation were estimated: rennet coagulation time estimated from the equation (RCTeq), the asymptotic potential curd firmness (CFP), the curd firming instant rate constant (kCF), and the syneresis instant rate constant (kSR). Two other derived traits were also calculated (CFmax, the maximum curd firmness value; and tmax, the attainment time). Multivariate analyses using Bayesian methodology were performed to estimate the genetic relationships of milk coagulation properties and CFt with the other traits; statistical inference was based on the Marginal Posterior Distributions of the parameters of concern. The Marginal Posterior Distribution of heritability estimates of milk yield (0.16±0.07) and composition (0.21±0.11 to 0.28±0.10) of Sarda ewes was similar to those often obtained for bovine species. The heritability of rennet coagulation time as a single point trait was also similar to that frequently obtained for cow milk (0.19±0.09), whereas the same trait calculated as an individual equation parameter exhibited larger genetic variation and a higher heritability estimate (0.32±0.11). The other curd firming and syneresis traits, whether as traditional single point observations or as individual equation parameters and derived traits, were characterized by heritability estimates lower than for coagulation time and for the corresponding bovine milk traits (0.06 to 0.14). Phenotypic and additive genetic correlations among the 11 technological traits contribute to describing the interdependencies and meanings of different traits. The additive genetic relationships of these technological traits with the single test-day milk yield and composition were variable and showed milk yield to have unfavorable effects on all measures of curd firmness (a30, a45, a60, CFP, and CFmax) and tmax, but favorable effects on both instant rate constants (kCF and kSR). Milk fat content had a positive effect on curd firmness traits, especially on those obtained from CFt equations, whereas the negative effects on both coagulation time traits were attributed to the milk protein and casein contents. Finally, in view of the estimated heritabilities and additive genetic correlations, enhancement of technological traits of sheep milk through selective breeding could be feasible in this population.
A Cecchinato - One of the best experts on this subject based on the ideXlab platform.
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Heritability estimates of enteric methane emissions predicted from fatty acid profiles, and their relationships with milk composition, cheese-yield and body size and condition
'Informa UK Limited', 2020Co-Authors: Giovanni Bittante, A CecchinatoAbstract:In the present study we estimated the genetic parameters of enteric methane emissions (EME) traits predicted from milk fatty acid profile (FA) and those of their predictors in 1,091 Brown Swiss cows reared on 85 farms in order to assess the potential of using EME-related phenotypes in selective breeding. Univariate and bivariate genetic models were fitted in a Bayesian framework. The means of the Marginal Posterior Distribution of intra-herd heritability ranged from 0.12 for estimated methane production (g/d/cow) to 0.24 for estimated methane yield (g/kg dry matter intake [DMI]), with intermediate values for estimated methane intensity, increasingly higher when expressed per kg of corrected milk (0.13), fresh cheese (0.16), or cheese solids (0.20). Regarding the correlations, the milk quality traits and percentage cheese yields were generally moderately correlated with the estimated EME traits, and were variable in terms of sign. Daily milk and cheese yield traits were, as expected, all highly positively correlated with estimated daily methane production. In contrast, they were negatively correlated with estimated methane yield and intensity, the estimates being large in the case of phenotypic and herd correlations, and low in the case of additive genetic and residual correlations. With the exception of the negative correlations with daily methane production, EME traits exhibited trivial correlations with body size and BCS of cows, which, in turn, were negatively correlated with milk yield. Although the results should be validated on a larger population and different breeds, our study demonstrate the presence of additive genetic variation of EME traits, which could be exploited in breeding programmes for the improvement in both milk production and the ecological footprint of dairy farming.Highlights Enteric methane emissions (EME) of dairy cows can be estimated on the basis of milk fatty acid profile. EME exhibited exploitable genetic variation. Genetic selection could be preferentially based on predicted methane intensity per kg of milk, or per kg of cheese in countries where milk production is used mainly for cheese-making
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phenotypic and genetic relationships between indicators of the mammary gland health status and milk composition coagulation and curd firming in dairy sheep
Journal of Dairy Science, 2018Co-Authors: Michele Pazzola, Giovanni Bittante, Claudio Cipolatgotet, Maria Luisa Dettori, A Cecchinato, Giuseppe Massimo VaccaAbstract:ABSTRACT The present study investigated the effect of somatic cell count, lactose, and pH on sheep milk composition, coagulation properties (MCP), and curd firming (CF) parameters. Individual milk samples were collected from 1,114 Sarda ewes reared in 23 farms. Milk composition, somatic cell count, single point MCP (rennet coagulation time, RCT; curd firming time, k 20 ; and curd firmness, a 30 , a 45 , and a 60 ), and CF model parameters were achieved. Phenotypic traits were statistically analyzed using a mixed model to estimate the effects of the different levels of milk somatic cell score (SCS), lactose, and pH, respectively. Additive genetic, herd, and residual correlations among these 3 traits, and with milk composition, MCP and CF parameters, were inferred using a Bayesian approach. From a phenotypic point of view, higher SCS levels caused a delayed gelification of milk. Lactose concentration and pH were significant for many milk quality traits, with a very intense effect on both coagulation times and curd firming. These traits (RCT, RCT estimated using the curd firming over time equation, and k 20 ) showed an unfavorable increase of about 20% from the highest to the lowest level of lactose. Milk samples with pH values lower than 6.56 versus higher than 6.78 were characterized by an increase of RCT (from 6.00 to 14.3 min) and k 20 (from 1.65 to 2.65 min) and a decrease of all the 3 curd firmness traits. From a genetic point of view, the Marginal Posterior Distribution of heritability estimates evidenced a large and exploitable variability for all 3 phenotypes. The mean intra-farm heritability estimates were 0.173 for SCS, 0.418 for lactose content, and 0.206 for pH. Lactose (favorably), and SCS and pH (unfavorably), at phenotypic and genetic levels, were correlated mainly with RCT and RCT estimated using the curd firming over time equation and scarcely with the other curd firming traits. The SCS, lactose, and pH were significantly correlated with each other's. In conclusion, results reported in the present study suggest that SCS, pH, and lactose affect, contemporarily and independently, milk quality and MCP. These phenotypes, easily available during milk recording schemes measured by infrared spectra prediction, could be used as potential indicators traits for improving cheese-making ability of ovine milk.
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genetic analysis of coagulation properties curd firming modeling milk yield composition and acidity in sarda dairy sheep
Journal of Dairy Science, 2017Co-Authors: Giovanni Bittante, Claudio Cipolatgotet, Michele Pazzola, Maria Luisa Dettori, Giuseppe Massimo Vacca, A CecchinatoAbstract:Sheep milk is an important source of food, especially in Mediterranean countries, and is used in large part for cheese production. Milk technological traits are important for the sheep dairy industry, but research is lacking into the genetic variation of such traits. Therefore the aim of this study was to estimate the heritability of traditional milk coagulation properties and curd firmness modeled on time t (CFt) parameters, and their genetic relationships with test-day milk yield, composition (fat, protein, and casein content), and acidity in Sarda dairy sheep. Milk samples from 1,121 Sarda ewes from 23 flocks were analyzed for 5 traditional coagulation properties by lactodynamographic tests conducted for up to 60min: rennet coagulation time (min), curd-firming time (k20, min), and 3measures of curd firmness (a30, a45, and a60, mm). The 240 curd firmness observations (1 every 15 s) from each milk sample were recorded, and 4 parameters for each individual sample equation were estimated: rennet coagulation time estimated from the equation (RCTeq), the asymptotic potential curd firmness (CFP), the curd firming instant rate constant (kCF), and the syneresis instant rate constant (kSR). Two other derived traits were also calculated (CFmax, the maximum curd firmness value; and tmax, the attainment time). Multivariate analyses using Bayesian methodology were performed to estimate the genetic relationships of milk coagulation properties and CFt with the other traits; statistical inference was based on the Marginal Posterior Distributions of the parameters of concern. The Marginal Posterior Distribution of heritability estimates of milk yield (0.16±0.07) and composition (0.21±0.11 to 0.28±0.10) of Sarda ewes was similar to those often obtained for bovine species. The heritability of rennet coagulation time as a single point trait was also similar to that frequently obtained for cow milk (0.19±0.09), whereas the same trait calculated as an individual equation parameter exhibited larger genetic variation and a higher heritability estimate (0.32±0.11). The other curd firming and syneresis traits, whether as traditional single point observations or as individual equation parameters and derived traits, were characterized by heritability estimates lower than for coagulation time and for the corresponding bovine milk traits (0.06 to 0.14). Phenotypic and additive genetic correlations among the 11 technological traits contribute to describing the interdependencies and meanings of different traits. The additive genetic relationships of these technological traits with the single test-day milk yield and composition were variable and showed milk yield to have unfavorable effects on all measures of curd firmness (a30, a45, a60, CFP, and CFmax) and tmax, but favorable effects on both instant rate constants (kCF and kSR). Milk fat content had a positive effect on curd firmness traits, especially on those obtained from CFt equations, whereas the negative effects on both coagulation time traits were attributed to the milk protein and casein contents. Finally, in view of the estimated heritabilities and additive genetic correlations, enhancement of technological traits of sheep milk through selective breeding could be feasible in this population.
Claudio Cipolatgotet - One of the best experts on this subject based on the ideXlab platform.
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phenotypic and genetic relationships between indicators of the mammary gland health status and milk composition coagulation and curd firming in dairy sheep
Journal of Dairy Science, 2018Co-Authors: Michele Pazzola, Giovanni Bittante, Claudio Cipolatgotet, Maria Luisa Dettori, A Cecchinato, Giuseppe Massimo VaccaAbstract:ABSTRACT The present study investigated the effect of somatic cell count, lactose, and pH on sheep milk composition, coagulation properties (MCP), and curd firming (CF) parameters. Individual milk samples were collected from 1,114 Sarda ewes reared in 23 farms. Milk composition, somatic cell count, single point MCP (rennet coagulation time, RCT; curd firming time, k 20 ; and curd firmness, a 30 , a 45 , and a 60 ), and CF model parameters were achieved. Phenotypic traits were statistically analyzed using a mixed model to estimate the effects of the different levels of milk somatic cell score (SCS), lactose, and pH, respectively. Additive genetic, herd, and residual correlations among these 3 traits, and with milk composition, MCP and CF parameters, were inferred using a Bayesian approach. From a phenotypic point of view, higher SCS levels caused a delayed gelification of milk. Lactose concentration and pH were significant for many milk quality traits, with a very intense effect on both coagulation times and curd firming. These traits (RCT, RCT estimated using the curd firming over time equation, and k 20 ) showed an unfavorable increase of about 20% from the highest to the lowest level of lactose. Milk samples with pH values lower than 6.56 versus higher than 6.78 were characterized by an increase of RCT (from 6.00 to 14.3 min) and k 20 (from 1.65 to 2.65 min) and a decrease of all the 3 curd firmness traits. From a genetic point of view, the Marginal Posterior Distribution of heritability estimates evidenced a large and exploitable variability for all 3 phenotypes. The mean intra-farm heritability estimates were 0.173 for SCS, 0.418 for lactose content, and 0.206 for pH. Lactose (favorably), and SCS and pH (unfavorably), at phenotypic and genetic levels, were correlated mainly with RCT and RCT estimated using the curd firming over time equation and scarcely with the other curd firming traits. The SCS, lactose, and pH were significantly correlated with each other's. In conclusion, results reported in the present study suggest that SCS, pH, and lactose affect, contemporarily and independently, milk quality and MCP. These phenotypes, easily available during milk recording schemes measured by infrared spectra prediction, could be used as potential indicators traits for improving cheese-making ability of ovine milk.
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genetic analysis of coagulation properties curd firming modeling milk yield composition and acidity in sarda dairy sheep
Journal of Dairy Science, 2017Co-Authors: Giovanni Bittante, Claudio Cipolatgotet, Michele Pazzola, Maria Luisa Dettori, Giuseppe Massimo Vacca, A CecchinatoAbstract:Sheep milk is an important source of food, especially in Mediterranean countries, and is used in large part for cheese production. Milk technological traits are important for the sheep dairy industry, but research is lacking into the genetic variation of such traits. Therefore the aim of this study was to estimate the heritability of traditional milk coagulation properties and curd firmness modeled on time t (CFt) parameters, and their genetic relationships with test-day milk yield, composition (fat, protein, and casein content), and acidity in Sarda dairy sheep. Milk samples from 1,121 Sarda ewes from 23 flocks were analyzed for 5 traditional coagulation properties by lactodynamographic tests conducted for up to 60min: rennet coagulation time (min), curd-firming time (k20, min), and 3measures of curd firmness (a30, a45, and a60, mm). The 240 curd firmness observations (1 every 15 s) from each milk sample were recorded, and 4 parameters for each individual sample equation were estimated: rennet coagulation time estimated from the equation (RCTeq), the asymptotic potential curd firmness (CFP), the curd firming instant rate constant (kCF), and the syneresis instant rate constant (kSR). Two other derived traits were also calculated (CFmax, the maximum curd firmness value; and tmax, the attainment time). Multivariate analyses using Bayesian methodology were performed to estimate the genetic relationships of milk coagulation properties and CFt with the other traits; statistical inference was based on the Marginal Posterior Distributions of the parameters of concern. The Marginal Posterior Distribution of heritability estimates of milk yield (0.16±0.07) and composition (0.21±0.11 to 0.28±0.10) of Sarda ewes was similar to those often obtained for bovine species. The heritability of rennet coagulation time as a single point trait was also similar to that frequently obtained for cow milk (0.19±0.09), whereas the same trait calculated as an individual equation parameter exhibited larger genetic variation and a higher heritability estimate (0.32±0.11). The other curd firming and syneresis traits, whether as traditional single point observations or as individual equation parameters and derived traits, were characterized by heritability estimates lower than for coagulation time and for the corresponding bovine milk traits (0.06 to 0.14). Phenotypic and additive genetic correlations among the 11 technological traits contribute to describing the interdependencies and meanings of different traits. The additive genetic relationships of these technological traits with the single test-day milk yield and composition were variable and showed milk yield to have unfavorable effects on all measures of curd firmness (a30, a45, a60, CFP, and CFmax) and tmax, but favorable effects on both instant rate constants (kCF and kSR). Milk fat content had a positive effect on curd firmness traits, especially on those obtained from CFt equations, whereas the negative effects on both coagulation time traits were attributed to the milk protein and casein contents. Finally, in view of the estimated heritabilities and additive genetic correlations, enhancement of technological traits of sheep milk through selective breeding could be feasible in this population.
Jonathan R Stroud - One of the best experts on this subject based on the ideXlab platform.
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a bayesian adaptive ensemble kalman filter for sequential state and parameter estimation
Monthly Weather Review, 2017Co-Authors: Jonathan R Stroud, Matthias Katzfuss, Christopher K WikleAbstract:AbstractThis paper proposes new methodology for sequential state and parameter estimation within the ensemble Kalman filter. The method is fully Bayesian and propagates the joint Posterior Distribution of states and parameters over time. To implement the method, the authors consider three representations of the Marginal Posterior Distribution of the parameters: a grid-based approach, a Gaussian approximation, and a sequential importance sampling (SIR) approach with kernel resampling. In contrast to existing online parameter estimation algorithms, the new method explicitly accounts for parameter uncertainty and provides a formal way to combine information about the parameters from data at different time periods. The method is illustrated and compared to existing approaches using simulated and real data.
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a bayesian adaptive ensemble kalman filter for sequential state and parameter estimation
arXiv: Methodology, 2016Co-Authors: Jonathan R Stroud, Matthias Katzfuss, Christopher K WikleAbstract:This paper proposes new methodology for sequential state and parameter estimation within the ensemble Kalman filter. The method is fully Bayesian and propagates the joint Posterior density of states and parameters over time. In order to implement the method we consider two representations of the Marginal Posterior Distribution of the parameters: a grid-based approach and a Gaussian approximation. Contrary to existing algorithms, the new method explicitly accounts for parameter uncertainty and provides a formal way to combine information about the parameters from data at different time periods. The method is illustrated and compared to existing approaches using simulated and real data.