The effect of level of feeding, genetic merit, body condition score and age on biological parameters of a mammary gland model

Bryant, Jeremy; López‐Villalobos, N.; Holmes, C. W.; Pryce, J.E.; Pitman, Graeme; Davis, Stephen R.

doi:10.1017/s1751731107657747

Cited by 10 publications

(8 citation statements)

References 31 publications

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“…The mathematical representation of MS concentration was based on over 100 000 daily lactation records (Bryant et al 2007a). Further independent datasets are needed to justify major changes to the mammary gland functions and representations of the effects of genetic merit, feeding level, BCS and age developed in the study carried out by Bryant et al (2007c).…”

Section: Discussionmentioning

confidence: 99%

Description and evaluation of the Farmax Dairy Pro decision support model

Bryant

Ogle²,

Marshall³

et al. 2010

New Zealand Journal of Agricultural Research

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Decision support models have been developed to assist management in dairy systems. This paper describes Farmax Dairy Pro (a pastoral grazing model of a dairy farm) and presents an evaluation of it using two independent farmlet studies carried out in Hamilton and Palmerston North, New Zealand with spring-calving dairy cows. Farmax Dairy Pro predicted, to a high degree of accuracy, mean annual yields (per cow and per hectare) for milk, fat, protein and milksolids (MS; fat'protein) and mean annual concentrations of MS. Monthly predictions were predicted with less accuracy than whole lactation values, but still with moderate degrees of accuracy compared with other comparable models. The general trajectory over time of yield and MS concentration was predicted well for all datasets, but in some instances the model over or under predicted the degree of variation between months. The trajectory of body condition score over time was reliably simulated in early lactation but with some discrepancies in late lactation. The model was then used to determine if it was possible to achieve 1750 kg MS/cow per ha using forages grown within the milking area for the Hamilton study. Managerial changes represented in the model, which included earlier calving dates, use of a chicory crop and additional intakes of pasture in summer, predicted increases in performance of 50Á190 kg MS/ha, still at least 81 kg MS/ha short of the target level of production. Farmax Dairy Pro can be used to predict animal, farm and financial performance for different management scenarios.

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Section: Discussionmentioning

confidence: 99%

Description and evaluation of the Farmax Dairy Pro decision support model

Bryant

Ogle²,

Marshall³

et al. 2010

New Zealand Journal of Agricultural Research

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“…As the ability to quantify physiological differences between animals on a large scale increases, it seems clear that there will be benefits in combining biological and biometric approaches. This has been demonstrated for growth (Doeschl-Wilson et al, 2007), and initial steps in relation to BCS change have been made (Bryant et al, 2007;Roche et al, 2007a;Martin and Sauvant, 2009). The phase transition model of Roche et al (2007a) can be seen as incorporating both genetically driven and environmentally driven BCS change in the same parametric model, although in the case of grazing cows, the 2 occur at different stages of lactation.…”

mentioning

confidence: 83%

“…The phase transition model of Roche et al (2007a) can be seen as incorporating both genetically driven and environmentally driven BCS change in the same parametric model, although in the case of grazing cows, the 2 occur at different stages of lactation. Bryant et al (2007) incorporated genetic patterns of BCS change in a model that is sensitive to the nutritional environment and allows for some degree of genotype × environment interaction. Likewise, implicit recognition of genetically regulated mobilization is being incorporated into more mechanistic models of nutrient partitioning that allow the prediction of dietary requirements (Martin and Sauvant, 2009).…”

mentioning

confidence: 99%

Invited review: Body condition score and its association with dairy cow productivity, health, and welfare

Roche

Friggens

Kay

et al. 2009

Journal of Dairy Science

937

829

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The body condition score (BCS) of a dairy cow is an assessment of the proportion of body fat that it possesses, and it is recognized by animal scientists and producers as being an important factor in dairy cattle management. The scale used to measure BCS differs between countries, but low values always reflect emaciation and high values equate to obesity. The intercalving profile of BCS is a mirror image of the milk lactation profile. Cows lose condition for 50 to 100 d postcalving, because of homeorhetic changes that occur in the somatotropic axis and the sensitivity of peripheral tissues to insulin, and the upregulation of lipolytic pathways in adipose tissue. Management and feeding have little effect on early postcalving BCS loss (wk 1 to 4 postcalving) until the natural period of insulin resistance has passed and the somatotropic axis has recoupled. There is evidence, however, that management and diet can influence the timing of recoupling of the somatotropic axis and the sensitivity of peripheral tissues to insulin, and gene expression differences in adipose tissue 30 d in milk confirm an effect of energy intake on lipogenic enzymes. The BCS in which a cow calves, nadir BCS, and the amount of BCS she loses postcalving are associated with milk production, reproduction, and health. Body condition score may also be a valid indicator of animal welfare, but further research is required to determine the effect of BCS and BCS change on how a cow "feels." Although the actual strength of the association may vary, there is relative consistency in the associations among calving and nadir BCS, and BCS change on milk production, postpartum anestrous, the likelihood of a successful pregnancy and days open, the risk of uterine infection, and the risk of metabolic disorders. For many production and health variables, the association with BCS is nonlinear, with an optimum calving BCS of 3.0 to 3.25 (5-point scale); lower calving BCS is associated with reduced production and reproduction, whereas calving BCS >/=3.5 (5-point scale) is associated with a reduction in early lactation dry matter intake and milk production and an increased risk of metabolic disorders. Ongoing research into the automation of body condition scoring suggests that it is a likely candidate to be incorporated into decision support systems in the near future to aid producers in making operational and tactical decisions.

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“…The results obtained were sufficiently accurate to permit this approach to form the basis of a herd-level model (Brun-Lafleur, 2011). They also provide proof-of-principal for deriving operational estimates of genotype-specific potential yields by extending this approach (see also Bryant et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Advances in predicting nutrient partitioning in the dairy cow: recognizing the central role of genotype and its expression through time

Friggens

Brun-Lafleur

Faverdin

et al. 2013

Animal

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In recent years, it has become increasingly clear that understanding nutrient partitioning is central to a much broader range of issues than just being able to predict productive outputs. The extent to which nutrients are partitioned to other functions such as health and reproduction is clearly important, as are the efficiency consequences of nutrient partitioning. Further, with increasing environmental variability, there is a greater need to be able to predict the ability of an animal to respond to the nutritional limitations that arise from the environment in which it is placed. How the animal partitions its nutrients when resources are limited, or imbalanced, is a major component of its ability to cope, that is, its robustness. There is mounting evidence that reliance on body reserves is increased and that robustness of dairy cows is reduced by selection for increased milk production. A key element for predicting the partition of nutrients in this wider context is to incorporate the priorities of the animal, that is, an explicit recognition of the role of both the cow's genotype (genetic make-up), and the expression of this genotype through time on nutrient partitioning. Accordingly, there has been a growing recognition of the need to incorporate in nutritional models these innate driving forces that alter nutrient partitioning according to physiological state, the genetically driven trajectories. This paper summarizes some of the work carried out to extend nutritional models to incorporate these trajectories, the genetic effects on them, as well as how these factors affect the homeostatic capacity of the animal. At present, there are models capable of predicting the partition of nutrients throughout lactation for cows of differing milk production potentials. Information concerning genotype and stage of lactation effects on homeostatic capacity has not yet been explicitly included in metabolic models that predict nutrient partition, although recent results suggest that this is achievable. These developments have greatly extended the generality of nutrient partitioning models with respect to the type of animal and its physiological state. However, these models remain very largely focussed on predicting partition between productive outputs and body reserves and, for the most part, remain research models, although substantial progress has been made towards developing models that can be applied in the field. The challenge of linking prediction of nutrient partitioning to its consequences on health, reproduction and longevity, although widely recognized, is only now beginning to be addressed. This is an important perspective for future work on nutrient partitioning.

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The effect of level of feeding, genetic merit, body condition score and age on biological parameters of a mammary gland model

Cited by 10 publications

References 31 publications

Description and evaluation of the Farmax Dairy Pro decision support model

Description and evaluation of the Farmax Dairy Pro decision support model

Invited review: Body condition score and its association with dairy cow productivity, health, and welfare

Advances in predicting nutrient partitioning in the dairy cow: recognizing the central role of genotype and its expression through time

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