Literature DB >> 14594233

Modeling the effect of energy status on mammary gland growth and lactation.

I Vetharaniam1, S R Davis, M Upsdell, E S Kolver, A B Pleasants.   

Abstract

The impact of nutrition on lactation can be separated into acute effects, affecting day-to-day yield, and chronic effects, which govern the persistency of lactation and rate of decline of the lactation curve. A mathematical model of the mammary gland was constructed to investigate both acute and chronic effects. Mammary growth is expressed in terms of the dynamics of populations of active (secreting) and quiescent (engorged) alveoli. The secretion rate of active alveoli is expressed in terms of the energy status of the dam. The model was fitted to data from a 2 x 2 factorial trial in which lactation curves were measured for heifers of two different genotypes (North American and New Zealand Holstein-Friesians) fed two different diets [grass and total mixed rations (TMR)]. Total formation of alveoli during pregnancy and lactation was statistically the same across all groups despite differences between diets, in the rate of formation of alveoli at parturition. The senescence rate of alveoli was significantly higher for heifers fed grass compared with heifers fed TMR, which corresponds to better persistency for heifers fed TMR. Heifers fed TMR had a higher rate of reactivation of quiescent alveoli than heifers fed grass, which also contributes to increased persistence for heifers fed TMR. There was a genotype x diet interaction in the rate of quiescence of active alveoli: the North American-Grass group had a higher rate of quiescence than the other three groups, perhaps reflecting differences in selection pressures between the New Zealand and North American genotypes.

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Year:  2003        PMID: 14594233     DOI: 10.3168/jds.S0022-0302(03)73916-2

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  2 in total

1.  ASN-ASAS SYMPOSIUM: FUTURE OF DATA ANALYTICS IN NUTRITION: Mathematical modeling in ruminant nutrition: approaches and paradigms, extant models, and thoughts for upcoming predictive analytics1,2.

Authors:  Luis O Tedeschi
Journal:  J Anim Sci       Date:  2019-04-29       Impact factor: 3.159

2.  Relationships between Selected Physiological Factors and Milking Parameters for Cows Using a Milking Robot.

Authors:  Marian Kuczaj; Anna Mucha; Alicja Kowalczyk; Ryszard Mordak; Ewa Czerniawska-Piątkowska
Journal:  Animals (Basel)       Date:  2020-11-07       Impact factor: 2.752

  2 in total

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