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- OBI_0500014 BFO_0000051 BFO_0000001 @default.
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- OBI_0500014 BFO_0000051 IAO_0000104 @default.
- OBI_0500014 BFO_0000051 OBI_0000272 @default.
- OBI_0500014 COB_0000047 BFO_0000001 @default.
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- OBI_0500014 COB_0000047 IAO_0000104 @default.
- OBI_0500014 COB_0000047 OBI_0000272 @default.
- OBI_0500014 IAO_0000112 "PMID: 17582121-Our objective was to examine the effects of dietary cation-anion difference (DCAD) with different concentrations of dietary crude protein (CP) on performance and acid-base status in early lactation cows. Six lactating Holstein cows averaging 44 d in milk were used in a 6 x 6 Latin square design with a 2 x 3 factorial arrangement of treatments: DCAD of -3, 22, or 47 milliequivalents (Na + K - Cl - S)/100 g of dry matter (DM), and 16 or 19% CP on a DM basis. Linear increases with DCAD occurred in DM intake, milk fat percentage, 4% fat-corrected milk production, milk true protein, milk lactose, and milk solids-not-fat. Milk production itself was unaffected by DCAD. Jugular venous blood pH, base excess and HCO3(-) concentration, and urine pH increased, but jugular venous blood Cl- concentration, urine titratable acidity, and net acid excretion decreased linearly with increasing DCAD. An elevated ratio of coccygeal venous plasma essential AA to nonessential AA with increasing DCAD indicated that N metabolism in the rumen was affected, probably resulting in more microbial protein flowing to the small intestine. Cows fed 16% CP had lower urea N in milk than cows fed 19% CP; the same was true for urea N in coccygeal venous plasma and urine. Dry matter intake, milk production, milk composition, and acid-base status did not differ between the 16 and 19% CP treatments. It was concluded that DCAD affected DM intake and performance of dairy cows in early lactation. Feeding 16% dietary CP to cows in early lactation, compared with 19% CP, maintained lactation performance while reducing urea N excretion in milk and urine." @default.
- OBI_0500014 IAO_0000114 IAO_0000125 @default.
- OBI_0500014 IAO_0000115 "factorial design is_a study design which is used to evaluate two or more factors simultaneously. The treatments are combinations of levels of the factors. The advantages of factorial designs over one-factor-at-a-time experiments is that they are more efficient and they allow interactions to be detected. In statistics, a factorial design experiment is an experiment whose design consists of two or more factors, each with discrete possible values or levels, and whose experimental units take on all possible combinations of these levels across all such factors. Such an experiment allows studying the effect of each factor on the response variable, as well as the effects of interactions between factors on the response variable." @default.
- OBI_0500014 IAO_0000117 "Philippe Rocca-Serra" @default.
- OBI_0500014 IAO_0000119 "http://www.stats.gla.ac.uk/steps/glossary/anova.html#facdes And from wikipedia (01/03/2007): http://en.wikipedia.org/wiki/Factorial_experiment)" @default.
- OBI_0500014 IAO_0000136 BFO_0000001 @default.
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- OBI_0500014 IAO_0000136 COB_0000502 @default.
- OBI_0500014 IAO_0000136 PATO_0000001 @default.
- OBI_0500014 RO_0002131 BFO_0000001 @default.
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- OBI_0500014 RO_0002131 OBI_0000272 @default.
- OBI_0500014 RO_0002323 BFO_0000001 @default.
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- OBI_0500014 RO_0002323 IAO_0000005 @default.
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- OBI_0500014 RO_0002323 IAO_0000104 @default.
- OBI_0500014 RO_0002323 OBI_0000272 @default.
- OBI_0500014 normalizedInformationContent "90.826665450122817" @default.
- OBI_0500014 referenceCount "4" @default.
- OBI_0500014 type Class @default.
- OBI_0500014 isDefinedBy obi.owl @default.
- OBI_0500014 label "factorial design" @default.
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