Literature DB >> 11022346

Variability characteristics and test selection in herd-level nutritional and metabolic profile testing.

T H Herdt1.   

Abstract

Nutritional assessment based on animal response factors is the basis of essentially all dietary recommendations. Blood concentrations of nutrients, metabolites, and hormones are important animal response factors associated with nutriture, making blood analysis an important nutritional assessment technique. There are, however, numerous sources of variability, other than nutrition, affecting the concentration of blood analytes used in nutritional assessment. Minimizing the effects of non-nutrient sources of variability and maximizing the effects of nutritional variability is the objective in designing strategies for blood sampling and testing for nutritional assessment. Important non-nutrient sources of variability are age, sex, gestation stage, lactation stage and milk yield, and season. When interpreting test results, grouping animals by these characteristics is an important means of minimizing the effects of non-nutritional variability. Within these groups, it is important to take an adequate number of samples, generally starting out with at least seven. Finally, selecting appropriate tests is critical. Tests commonly used for clinicopathologic evaluations are not necessarily the best tests for nutritional assessment. Analytes should be chosen that are likely to have a large portion of their total variability caused by nutritional effects. This generally does not include those metabolites the blood concentrations of which are rigidly controlled by homeostatic forces.

Mesh:

Year:  2000        PMID: 11022346     DOI: 10.1016/s0749-0720(15)30111-0

Source DB:  PubMed          Journal:  Vet Clin North Am Food Anim Pract        ISSN: 0749-0720            Impact factor:   3.357


  21 in total

1.  Reference limits for biochemical and hematological analytes of dairy cows one week before and one week after parturition.

Authors:  Gerardo F Quiroz-Rocha; Stephen J LeBlanc; Todd F Duffield; Darren Wood; Ken E Leslie; Robert M Jacobs
Journal:  Can Vet J       Date:  2009-04       Impact factor: 1.008

2.  Relationship between ketosis and dairy cows' blood metabolites in intensive production farms of the periurban area of Dakar.

Authors:  Nongasida Yameogo; Georges Anicet Ouedraogo; Christine Kanyandekwe; Germain Jerome Sawadogo
Journal:  Trop Anim Health Prod       Date:  2008-01-23       Impact factor: 1.559

3.  Periparturition alterations to liver ultrasonographic echo-texture and fat mobilization parameters in clinically healthy Holstein cows.

Authors:  Saman Rafia; Taghi Taghipour-Bazargani; Farzad Asadi; Alireza Vajhi; Saied Bokaie
Journal:  Vet Res Commun       Date:  2011-09-02       Impact factor: 2.459

Review 4.  Significance of insulin resistance and oxidative stress in dairy cattle with subclinical ketosis during the transition period.

Authors:  Mohamed Youssef; Maged El-Ashker
Journal:  Trop Anim Health Prod       Date:  2016-12-15       Impact factor: 1.559

5.  FGF-21: promising biomarker for detecting ketosis in dairy cows.

Authors:  Chuang Xu; Qiushi Xu; Yuanyuan Chen; Wei Yang; Cheng Xia; Hongjiang Yu; Kuilin Zhu; Taiyu Shen; Ziyang Zhang
Journal:  Vet Res Commun       Date:  2016-01-04       Impact factor: 2.459

6.  Ivermectin treatment of bovine psoroptic mange: effects on serum chemistry, hematology, organ weights, and leather quality.

Authors:  S Rehbein; M Visser; M Meyer; T Lindner
Journal:  Parasitol Res       Date:  2015-12-19       Impact factor: 2.289

7.  Bovine subclinical ketosis in dairy herds in Iran.

Authors:  M Sakha; M Ameri; H Sharifi; I Taheri
Journal:  Vet Res Commun       Date:  2007-02-07       Impact factor: 2.459

8.  Compromised liver functions during the breeding period of clinically healthy Holstein cows.

Authors:  M Mohebbi-Fani; A Omidi; A Mirzaei; S Nazifi; E Pourtajabadi; M Badkoobeh
Journal:  Iran J Vet Res       Date:  2019       Impact factor: 1.376

9.  Blood biochemical values in Japanese Black breeding cows in Kagoshima Prefecture, Japan.

Authors:  Konosuke Otomaru; Hanae Shiga; Junko Kanome; Kouji Yanagita
Journal:  J Vet Med Sci       Date:  2015-05-12       Impact factor: 1.267

10.  Metabolic profiles in five high-producing Swedish dairy herds with a history of abomasal displacement and ketosis.

Authors:  Lena Stengärde; Madeleine Tråvén; Ulf Emanuelson; Kjell Holtenius; Jan Hultgren; Rauni Niskanen
Journal:  Acta Vet Scand       Date:  2008-08-07       Impact factor: 1.695

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