In order to meet government supervision of pork production safety as well as consumer's right to know what they buy and protect the public safety of pork food, this study adopts animal identification, intelligent per...In order to meet government supervision of pork production safety as well as consumer's right to know what they buy and protect the public safety of pork food, this study adopts animal identification, intelligent personal digital assistant (PDA) reading and writing, general packet radio service (GPRS), and other information technologies, proposes a pork tracking and traceability inferstructure based on pork production substrace flow and data flow, designs the metadata structure and related datatbases for farming, slaughtering, and retailing sector based on intensive pig farming and smallhold pig farming, develops three different data-recording systems, and finally establishes a public network platform for the information inquiry in light of "the administrative rules on identification and rearing files for animal and poultry" in China. The farming process information system supplies early warning for the usage of drugs and feed additives based on data of every individual pig and timely uploading all events data to remote traceability database when pigs are sold; the PDA data collecting system can collect farming events data for pigs fed by farmers and submit to the center database by GPRS; the web-based Tianjin's pork traceability platform can integrate all identifications and related pork quality data from farming, slaughtering to marketing by online, and achieve pork tracking from product origin to consumption and tracing in the turnover direction. It is feasible to realize pork quality traceability by identification technologies developed and/or integrated, metadata specifications designed, three data-recording systems deyeloped, and web-inquiring platform established. Some individual technical bottlenecks will be resolved with the development of communication technologies. The full implementation in Tianjin, China, will supply technical support for guaranteeing the quality and safety of pork production and meeting consumer's demands.展开更多
Dry matter intake (DMI) prediction models of NRC (2001), Fox et aL (2004) and Fuentes-Pila et aL (2003) were targeted in the present study, and the objective was to evaluate their prediction accuracy with feed...Dry matter intake (DMI) prediction models of NRC (2001), Fox et aL (2004) and Fuentes-Pila et aL (2003) were targeted in the present study, and the objective was to evaluate their prediction accuracy with feeding trial data of 32 lactating Holstein cows fed two total mixed rations with different forage source. Thirty-two cows were randomly assigned to one of two total mixed ration groups: a ration containing a mixed forage (MF) of 3.7% Chinese wildrye, 28.4% alfalfa hay and 26.5% corn silage diet and another ration containing 33.8% corn stover (CS) as unique forage source. The actual DMI was greater in MF group than in CS group (P=0.064). The NRC model to predict DMI resulted in the lowest root mean square prediction error for both MF and CS groups (1.09 kg d-1 vs. 1.28 kg d-1) and the highest accuracy and precision based on concordance correlation coefficient for both MF and CS diet (0.89 vs. 0.87). Except the NRC model, the other two models presented mean and linear biases in both MF and CS diets when prediction residuals were plotted against predicted DMI values (P〈0.001). The DMI variation in MF was caused by week of lactation (55.6%), milk yield (13.9%), milk fat percentage (7.1%) and dietary neutral detergent fiber (13.3%), while the variation in CS was caused by week of lactation (50.9%), live body weight (28.2%), milk yield (8.4%), milk fat percentage (5.2%) and dietary neutral detergent fibre (3.8%). In a brief, the NRC model to predict DMI is comparatively acceptable for lactating dairy cows fed two total mixed rations with different forage source.展开更多
As a new feed additive,chitosan has been shown in recent years to have a certain role in reducing methane emissions from the gastrointestinal tracts of ruminants.However,the effects of chitosan with different molecula...As a new feed additive,chitosan has been shown in recent years to have a certain role in reducing methane emissions from the gastrointestinal tracts of ruminants.However,the effects of chitosan with different molecular weights on rumen ferme ntation,methane production and bacterial comm unity structure are not yet clear.A basal diet without chitosa n served as the control(CTL),and the treatment diets were supplemented with chitosan with different molecular weights:1000(1K),3000(3K),5000(5K),50000(5W)and 200000(20W)dry matter(DM).Six fermentation units per treatment were established.Gas chromatography was used to measure the co nee ntrations of metha ne,H2 and volatile fatty acids(VFAs).The bacterial 16S rRNA genes were sequeneed with an Illumina MiSeq platform and analysed to reveal the relative abunda nces of bacterial community taxa.The results showed that the propi onate proporti on was sign ifica ntly in creased by the addition of chitosan with different molecular weights(P<0.05),while methane production and the acetate proportion were significantly decreased(P<0.05).The relative mbundances of Rikenellaceae_RC9_gut_group and Prevotellaceae_UCG_003 were significa ntly in creased in the 3K chitosa n group compared with the CTL group,whereas the relative abunda nee of Ruminococcaceae_NK4A214_group was significantly decreased(P<0.05).Correlation analyses of the relative abundances of the bacterial genera showed that Prevotella was positively related to propionmte production(Pv0.05).In conclusion,3K chitosan could reduce methane production by replacing fibrolytic bacteria(Firmicutes and Fibrobacteres)with amylolytic bacteria(Bacteroidetes and Proteobacteria)in the bacterial community structure.展开更多
基金supported by the National High-Tech R&D Program of China (2006AA-10Z266)the Key Technologies R&D Program of China during the 11th Five-Year Plan period (2006BAD14804,2006BAK02A16)
文摘In order to meet government supervision of pork production safety as well as consumer's right to know what they buy and protect the public safety of pork food, this study adopts animal identification, intelligent personal digital assistant (PDA) reading and writing, general packet radio service (GPRS), and other information technologies, proposes a pork tracking and traceability inferstructure based on pork production substrace flow and data flow, designs the metadata structure and related datatbases for farming, slaughtering, and retailing sector based on intensive pig farming and smallhold pig farming, develops three different data-recording systems, and finally establishes a public network platform for the information inquiry in light of "the administrative rules on identification and rearing files for animal and poultry" in China. The farming process information system supplies early warning for the usage of drugs and feed additives based on data of every individual pig and timely uploading all events data to remote traceability database when pigs are sold; the PDA data collecting system can collect farming events data for pigs fed by farmers and submit to the center database by GPRS; the web-based Tianjin's pork traceability platform can integrate all identifications and related pork quality data from farming, slaughtering to marketing by online, and achieve pork tracking from product origin to consumption and tracing in the turnover direction. It is feasible to realize pork quality traceability by identification technologies developed and/or integrated, metadata specifications designed, three data-recording systems deyeloped, and web-inquiring platform established. Some individual technical bottlenecks will be resolved with the development of communication technologies. The full implementation in Tianjin, China, will supply technical support for guaranteeing the quality and safety of pork production and meeting consumer's demands.
基金financially supported by the National Natural Science Foundation of China(31572435)the National Key Research and Development Plan(2016YFD0700205,2016YFD0700201)
文摘Dry matter intake (DMI) prediction models of NRC (2001), Fox et aL (2004) and Fuentes-Pila et aL (2003) were targeted in the present study, and the objective was to evaluate their prediction accuracy with feeding trial data of 32 lactating Holstein cows fed two total mixed rations with different forage source. Thirty-two cows were randomly assigned to one of two total mixed ration groups: a ration containing a mixed forage (MF) of 3.7% Chinese wildrye, 28.4% alfalfa hay and 26.5% corn silage diet and another ration containing 33.8% corn stover (CS) as unique forage source. The actual DMI was greater in MF group than in CS group (P=0.064). The NRC model to predict DMI resulted in the lowest root mean square prediction error for both MF and CS groups (1.09 kg d-1 vs. 1.28 kg d-1) and the highest accuracy and precision based on concordance correlation coefficient for both MF and CS diet (0.89 vs. 0.87). Except the NRC model, the other two models presented mean and linear biases in both MF and CS diets when prediction residuals were plotted against predicted DMI values (P〈0.001). The DMI variation in MF was caused by week of lactation (55.6%), milk yield (13.9%), milk fat percentage (7.1%) and dietary neutral detergent fiber (13.3%), while the variation in CS was caused by week of lactation (50.9%), live body weight (28.2%), milk yield (8.4%), milk fat percentage (5.2%) and dietary neutral detergent fibre (3.8%). In a brief, the NRC model to predict DMI is comparatively acceptable for lactating dairy cows fed two total mixed rations with different forage source.
基金This study was financimlly supported by the projects of the National Natural Science Foundation of China(31802091,31702302 and 31772629)and the National Key Research and Development Plan of China(2016YFD0700205,2016YFD0700201 and 2017YFD0701604).
文摘As a new feed additive,chitosan has been shown in recent years to have a certain role in reducing methane emissions from the gastrointestinal tracts of ruminants.However,the effects of chitosan with different molecular weights on rumen ferme ntation,methane production and bacterial comm unity structure are not yet clear.A basal diet without chitosa n served as the control(CTL),and the treatment diets were supplemented with chitosan with different molecular weights:1000(1K),3000(3K),5000(5K),50000(5W)and 200000(20W)dry matter(DM).Six fermentation units per treatment were established.Gas chromatography was used to measure the co nee ntrations of metha ne,H2 and volatile fatty acids(VFAs).The bacterial 16S rRNA genes were sequeneed with an Illumina MiSeq platform and analysed to reveal the relative abunda nces of bacterial community taxa.The results showed that the propi onate proporti on was sign ifica ntly in creased by the addition of chitosan with different molecular weights(P<0.05),while methane production and the acetate proportion were significantly decreased(P<0.05).The relative mbundances of Rikenellaceae_RC9_gut_group and Prevotellaceae_UCG_003 were significa ntly in creased in the 3K chitosa n group compared with the CTL group,whereas the relative abunda nee of Ruminococcaceae_NK4A214_group was significantly decreased(P<0.05).Correlation analyses of the relative abundances of the bacterial genera showed that Prevotella was positively related to propionmte production(Pv0.05).In conclusion,3K chitosan could reduce methane production by replacing fibrolytic bacteria(Firmicutes and Fibrobacteres)with amylolytic bacteria(Bacteroidetes and Proteobacteria)in the bacterial community structure.