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.

Management, nutrition, production, and genetics are the main reasons for the decline in fertility in the modern dairy cow. Selection for the single trait of milk production with little consideration for traits associated with reproduction in the modern dairy cow has produced an antagonistic relationship between milk yield and reproductive performance. The outcome is a multi-factorial syndrome of subfertility during lactation; thus, to achieve a better understanding and derive a solution, it is necessary to integrate a range of disciplines, including genetics, nutrition, immunology, molecular biology, endocrinology, metabolic and reproductive physiology, and animal welfare. The common theme underlying the process is a link between nutritional and metabolic inputs that support complex interactions between the gonadotropic and somatotropic axes. Multiple hormonal and metabolic signals from the liver, pancreas, muscle, and adipose tissues act on brain centers regulating feed intake, energy balance, and metabolism. Among these signals, glucose, fatty acids, insulin-like growth factor-I, insulin, growth hormone, ghrelin, leptin, and perhaps myostatin appear to play key roles. Many of these factors are affected by changes in the somatotropic axis that are a consequence of, or are needed to support, high milk production. Ovarian tissues also respond directly to metabolic inputs, with consequences for folliculogenesis, steroidogenesis, and the development of the oocyte and embryo. Little doubt exists that appropriate nutritional management before and after calving is essential for successful reproduction. Changes in body composition are related to the processes that lead to ovulation, estrus, and conception. However, better indicators of body composition and measures of critical metabolites are required to form precise nutritional management guidelines to optimize reproductive outcomes. The eventual solution to the reduction in fertility will be a new strategic direction for genetic selection that includes fertility-related traits. However, this will take time to be effective, so, in the short term, we need to gain a greater understanding of the interactions between nutrition and fertility to better manage the issue. A greater understanding of the phenomenon will also provide markers for more targeted genetic selection. This review highlights many fruitful directions for research, aimed at the development of strategies for nutritional management of reproduction in the high-producing subfertile dairy cow.

Scoring body condition and assessing changes in the body condition of dairy cattle have become strategic tools in both farm management and research. Consequently, body condition score (BCS) is being researched extensively throughout the world. However, international sharing, comparing, and use of data generated are limited because different BCS systems exist. In the United States and Ireland a 5-point BCS system is used for dairy cows, whereas Australia and New Zealand use 8- and 10-point scales, respectively. The New Zealand 10-point scale was compared with the scoring systems in the United States, Ireland, and Australia by trained assessors. Cows were assessed visually in the United States and Australia, and in Ireland, cows were assessed by palpating key areas of the cow's body (n = 154, 110, and 120, respectively). Data were analyzed by regression. Significant positive linear relationships were found between the New Zealand 10-point scale and the other scoring systems: US 5-point scale, r(2) = 0.54; Irish 5-point scale, r(2) = 0.72; and Australian 8-point scale, r(2) = 0.61. Those relationships must be interpreted cautiously because respective BCS within a given country were by just one experienced evaluator in each country in comparison to a separate evaluator scoring all cows in all counties using the New Zealand 10-point scale. Also, few very thin or very fat cows limit evaluation across extremes of BCS. However, differences between systems were not accurately predicted by simple mathematical calculations. The relationship may be closer for New Zealand and Ireland (r(2) = 0.72) because both of those scoring systems include palpation of individual body parts, whereas visual evaluation is done in Australia and the United States. The current study is the first to examine relationships among differing BCS systems. These results may be useful for comparing/extrapolating research findings from different countries.

The objective of the present study was to identify and quantify relationships between body condition score (BCS) and body weight (BW) in dairy cows with reproduction variables in pasture-based, seasonal-calving dairy herds. Over 2,500 lactation records from 897 spring-calving Holstein-Friesian dairy cows were used in the analyses. Eleven BCS- and 11 BW-related variables were generated, including observations at calving, nadir, planned start of mating (PSM), and first service, as well as days to nadir and the amount and rate of change between periods. The binary reproductive variables were cycling by PSM, mated in the first 21 d from PSM, pregnant to first service, and pregnant in the first 21, 42, and 84 d of the seasonal mating period. Generalized estimating equations were used to identify BCS and BW variables that significantly affected the probability of a successful reproductive outcome. After adjusting for the fixed effect of year of calving, parity (for cycling by PSM only), and the interval from calving to either first service or PSM, reproductive performance was found to be significantly affected by BW or BCS at key points, and by BCS and BW change during lactation. All reproductive response measures were negatively affected when BCS and BW measures indicated an increased severity and duration of the postpartum negative energy balance. In particular, cycling by PSM was positively associated with calving BCS, whereas pregnancy at 21, 42, and 84 d post-PSM were positively associated with nadir BCS and BW gain post-PSM, and negatively associated with BCS loss between calving and nadir. The results highlight the important role that BCS and BW loss has on reproductive performance, especially in seasonal-calving dairy systems because of the short period between calving and PSM.

Ninety-four cows were randomly allocated to 1 of 5 stocking rates (2.2, 2.7, 3.1, 3.7, and 4.3 cows/ha) in a completely randomized design for 3 years. Herds were seasonal calving, with only minor differences in grazing management to optimize the profitability of each stocking rate (SR). Pasture production and quality data, milk and milk component data, and reproduction data were collected, averaged for SR treatment, and linear and quadratic contrasts on SR were evaluated. In addition, the Wilmink exponential model (y(t) = a + b x e((-0.05t) )+ c x t) was fitted to milk yield within lactation, and the parameters were averaged by SR treatment and analyzed as above. The median variation explained by the function for individual lactations was 84%. The amount of pasture grown tended to increase, and the quality of the pasture on offer increased linearly with increasing SR, reducing some of the negative impact of SR on the availability of pasture per cow. Milk production per cow declined linearly with increasing SR, although there was a tendency for most production variables to decline quadratically, with the negative effect of SR declining with increasing SR. The effect on milk production per cow was primarily because of a lower peak milk yield and a greater post-peak decline (less persistent milk profile), although a decline in lactation length with increasing SR was responsible for 24% of the effect of SR on milk yield. Milk production per hectare increased linearly with increasing SR, and there was only a small difference (approximately 3%/cow per ha) in the efficiency of converting feed dry matter into milk energy. Stocking rate did not affect reproductive success. The data are consistent with the need for a more robust measure of SR than cows per hectare because farms will differ in the genetic merit of their cows and in the potential to produce pasture. We introduce the concept of a comparative SR, whereby the carrying capacity of the farm is defined by the BW of the cows, the potential of the land to produce pasture, and the amount of supplement purchased (kg of BW/t of feed dry matter). The adoption of such a measure would facilitate the extrapolation and transfer of research findings among systems.

Perennial ryegrass (Lolium perenne L.) is an important pasture and turf crop. Biotechniques such as gene expression studies are being employed to improve traits in this temperate grass. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is among the best methods available for determining changes in gene expression. Before analysis of target gene expression, it is essential to select an appropriate normalisation strategy to control for non-specific variation between samples. Reference genes that have stable expression at different biological and physiological states can be effectively used for normalisation; however, their expression stability must be validated before use.