Heifers with positive genetic merit for fertility traits reach puberty earlier and have a greater pregnancy rate than heifers with negative genetic merit for fertility traits.

This study investigated the hypothesis that dairy heifers divergent in genetic merit for fertility traits differ in the age of puberty and reproductive performance. New Zealand's fertility breeding value (FertBV) is the proportion of a sire's daughters expected to calve in the first 42 d of the seasonal calving period. We used the New Zealand national dairy database to identify and select Holstein-Friesian dams with either positive (POS, +5 FertBV, n = 1,334) or negative FertBV (NEG, -5% FertBV, n = 1,662) for insemination with semen from POS or NEG FertBV sires, respectively. The resulting POS and NEG heifers were predicted to have a difference in average FertBV of 10 percentage points. We enrolled 640 heifer calves (POS, n = 324; NEG, n = 316) at 9 d ± 5.4 d (± standard deviation; SD) for the POS calves and 8 d ± 4.4 d old for the NEG calves. Of these, 275 POS and 248 NEG heifers were DNA parent verified and retained for further study. The average FertBV was +5.0% (SD = 0.74) and -5.1% (SD = 1.36) for POS and NEG groups, respectively. Heifers were reared at 2 successive facilities as follows: (1) calf rearing (enrollment to ∼13 wk of age) and (2) grazier, after 13 wk until 22 mo of age. All heifers wore a collar with an activity sensor to monitor estrus events starting at 8 mo of age, and we collected weekly blood samples when individual heifers reached 190 kg of body weight (BW) to measure plasma progesterone concentrations. Puberty was characterized by plasma progesterone concentrations >1 ng/mL in at least 2 of 3 successive weeks. Date of puberty was defined when the first of these samples was >1 ng/mL. Heifers were seasonally bred for 98 d starting at ∼14 mo of age. Transrectal ultrasound was used to confirm pregnancy and combined with activity data to estimate breeding and pregnancy dates. We measured BW every 2 wk, and body condition and stature at 6, 9, 12, and 15 mo of age. The significant FertBV by day interaction for BW was such that the NEG heifers had increasingly greater BW with age. This difference was mirrored with the significant FertBV by month interaction for average daily gain, with the NEG heifers having a greater average daily gain between 9 and 18 mo of age. There was no difference in heifer stature between the POS and NEG heifers. The POS heifers were younger and lighter at puberty, and were at a lesser mature BW, compared with the NEG heifers. As a result, 94 ± 1.6% of the POS and 82 ± 3.2% of the NEG heifers had reached puberty at the start of breeding. The POS heifers were 20% and 11% more likely to be pregnant after 21 d and 42 d of breeding than NEG heifers (relative risk = 1.20, 95% confidence interval of 1.03-1.34; relative risk = 1.11, 95% confidence interval of 1.01-1.16). Results from this experiment support an association between extremes in genetic merit for fertility base on cow traits and heifer reproduction. Our results indicate that heifer puberty and pregnancy rates are affected by genetic merit for fertility traits, and these may be useful phenotypes for genetic selection.

Environmental sensitivity in New Zealand dairy cattle.

This study quantifies the extent of within-breed sire reranking for milk production traits in a range of environments encountered within New Zealand. Character states of herds were formed within the environmental ranges of herd fat plus protein (MS) yield, summer heat load index (HLI), herd size, and altitude. Single-trait and bivariate sire models across breeds were then applied for estimation of genetic parameters and genetic correlations between extreme character states. A low degree of sire reranking occurred, as measured by genetic correlations around 0.9, between herd environments that differed widely in MS yield (227 vs. 376 kg of MS per cow), and HLI (61.4 vs. 69.6). The HLI of 61.4 and 69.6 are approximately equivalent to average summer maximum temperatures of 19 and 25 degrees C at 80% humidity. Correlations of sire estimated breeding values in extreme character states were low, but only one was below an expected correlation accounting for the reliability of prediction. The results show the environment in New Zealand is not sufficiently diverse to warrant separate breeding schemes for different environments.

Short communication: Effect of environment on the expression of breed and heterosis effects for production traits.

Character states of New Zealand herds were formed within the environmental ranges of herd average total lactation yield of fat plus protein (MS), which is a proxy for feeding level, summer heat load index (HLI), herd size, and altitude. A univariate multibreed sire model was applied to first-lactation (2 yr old) records of milk, fat, and protein within each environmental character state to estimate breed and heterosis effects. A scaling effect was observed for MS yield between overseas Holstein-Friesian (OHF) and New Zealand Jersey (NZJ) animals when comparing breed performance in extreme MS character states. For example, differences for milk, fat, and protein yield between these breeds were 561, 1.3, and 9.3 kg, respectively, in the character state averaging 227 kg of MS/cow, much smaller than the differences of 1,151, 3.1, and 23.0 in the character state averaging 376 kg of MS/cow. Heterosis levels for milk, fat, and protein yields were highest for OHF x NZJ, followed by New Zealand Friesian (NZF) x NZJ and OHF x NZF with average heterosis for all traits of 7.3, 5.7, and 2.7%, respectively. Heterosis levels for OHF x NZF were suppressed in very low MS yield environments and in many cases were not significantly different from zero. Heterosis was suppressed in crosses with OHF in the high HLI environment. Crossbred animals (OHF x NZJ, NZF x NZJ, and OHF x NZF) generally achieved higher fat yields than any of the straight-bred animals.

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

An evolutionary algorithm was applied to a mechanistic model of the mammary gland to find the parameter values that minimised the difference between predicted and actual lactation curves of milk yields in New Zealand Jersey cattle managed at different feeding levels. The effect of feeding level, genetic merit, body condition score at parturition and age on total lactation yields of milk, fat and protein, days in milk, live weight and evolutionary algorithm derived mammary gland parameters was then determined using a multiple regression model. The mechanistic model of the mammary gland was able to fit lactation curves that corresponded to actual lactation curves with a high degree of accuracy. The senescence rate of quiescent (inactive) alveoli was highest at the very low feeding level. The active alveoli population at peak lactation was highest at very low feeding levels, but lower nutritional status at this feeding level prevented high milk yields from being achieved. Genetic merit had a significant linear effect on the active alveoli population at peak and mid to late lactation, with higher values in animals, which had higher breeding values for milk yields. A type of genetic merit × feeding level scaling effect was observed for total yields of milk and fat, and total number of alveoli produced from conception until the end of lactation with the benefits of increases in genetic merit being greater at high feeding levels. A genetic merit × age scaling effect was observed for total lactation protein yields. Initial rates of differentiation of progenitor cells declined with age. Production levels of alveoli from conception to the end of lactation were lowest in 5- to 8-year-old animals; however, in these older animals, quiescent alveoli were reactivated more frequently. The active alveoli population at peak lactation and rates of active alveoli proceeding to quiescence were highest in animals of intermediate body condition scores of 4.0 to 5.0. The results illustrate the potential uses of a mechanistic model of the mammary gland to fit a lactation curve and to quantify the effects of feeding level, genetic merit, body condition score, and age on mammary gland dynamics throughout lactation.

Open systems.

This paper describes the nature of open systems, how they arose and their relevance to HIS. A working definition is presented followed by reasons for adopting the open systems approach. The paper concludes with the identification of current barriers to the successful introduction of an open systems HIS.