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Milk production declines as dairy cows enter late lactation, resulting in reduced milk quality and negatively impacting milk processability, such as rennet coagulation time (RCT), milk pH and ethanol stability (ES), leading to seasonality issues for milk processors. Multispecies forages, containing grass, legume and herb species, require lower N inputs and are of interest to dairy farmers. However, little is known about the effect of grazing multispecies forages on milk processability characteristics in late lactation dairy cows. Forty-five autumn-calving dairy cows in late lactation were allocated to 1 of 3 grazing forages; perennial ryegrass (PRG; Lolium perenne), perennial ryegrass and white clover (Trifolium pratense) (PRGWC), and a 6 – species multispecies forage (MULTI) containing perennial ryegrass, timothy (Phleum pratense), white clover, red clover (Trifolium repens), chicory (Cichorium intybus) and plantain (Plantago lanceolata). Cows were allocated 12 kg DM grazed forage and supplemented with a grass – silage TMR and concentrate. Forage DMI was significantly lower for cows grazing PRG. Milk yield increased when cows grazed PRGWC (18.07 kg/d) and MULTI (17.84 kg/d) compared to PRG (16.08 kg/d). Milk RCT (mins) and ES (%) were unaffected by treatment. However, offering cows PRGWC and MULTI increased the concentration of C18:2 cis – 9, 12 and C18:3 cis – 9, 12, 15 in milk compared to PRG. Compared to PRG, grazing forages containing clover and herb species improved milk yield and beneficially altered milk fatty acid profile in late lactation dairy cows without negatively impacting milk processability. [ABSTRACT FROM AUTHOR]

Background This study investigated the factors relating to pasture chemical and fatty acid (FA) composition that influence the milk fat percentage of spring calving, grazing dairy cows. The relationship between milk fat percentage and FA composition of the milk in these herds was also investigated. Results Milk protein percentage, milk casein percentage and cheddar cheese yield were increased in milk from HMF herds. Cows from LMF herds did not have negatively altered milk processability including rennet coagulation time (RCT), pH and ethanol stability. Crude protein, NDF, ADF, ether extract and total FA content of pasture was not different between LMF and HMF herds. Milk fat concentration of conjugated linoleic acid (CLA) t10, c12 was not different between HMF and LMF herds. Pre-grazing herbage mass and pasture content of crude protein, neutral detergent fibre (NDF) and total FA were similar between HMF and LMF herds. Pasture offered to LMF herds had a higher concentration of monounsaturated fatty acids (MUFA). A strong negative relationship (r = -0.40) was evident between milk fat percentage and pasture crude protein content for MMF herds (3.31-3.94% milk fat). Conclusions This research reports improved milk protein percentage, milk casein percentage and cheddar cheese yield from HMF herds compared to LMF herds. Milk processability was not impacted by low milk fat percentage. Pasture NDF and total fatty acid content was similar in HMF herds and LMF herds. Milk fat percentage had a strong negative association (r = -0.40) with pasture crude protein content in MMF herds (MF 3.31-3.94%). Correlation values between pasture chemical and FA composition and milk fat percentage in LMF herds and HMF herds were low, indicating that diet is not the only causative factor for variation in milk fat of grazing dairy cows. Comparison of milk fatty acid composition from herds with and without milk fat depression suggests that there may be other fatty acids apart from CLA t10, c12 that contribute to the inhibition of milk fat synthesis during milk fat depression in grazing herds. [ABSTRACT FROM AUTHOR]

To overcome grass supply shortages on the main grazing block, some pasture-based dairy farmers are using zero-grazing (also known as 'cut and carry'), whereby cows are periodically housed and fed fresh grass harvested from external land blocks. To determine the effect of zero-grazing on cow performance, two early-lactation experiments were conducted with autumn and spring-calving dairy cows. Cows were assigned to one of two treatments in a randomized complete block design. The two treatments were zero-grazing (ZG) and grazing (G). The ZG group were housed and fed zero-grazed grass, while the G group grazed outdoors at pasture. Both treatments were fed perennial ryegrass (Lolium perenne L.) from the same paddock. In experiment 1, 24 Holstein Friesian cows (n = 12) were studied over a 35-day experimental period in autumn and offered fresh grass, grass silage, ground maize and concentrates. In experiment 2, 30 Holstein Friesian cows (n = 15) were studied over a 42-day experimental period and offered fresh grass and concentrates. Average dry matter intake and milk yield was similar for ZG and G in both experiments. Likewise, ZG did not have an effect on milk composition, body condition or locomotion. Zero-grazing had no effect on total nitrogen excretion or nitrogen utilization efficiency in either experiment, or on rumen pH and ammonia concentration in experiment 1. While zero-grazing may enable farmers to supply fresh grass to early-lactation cows in spring and autumn, results from this study suggest that there are no additional benefits to cow performance in comparison to well-managed grazed grass. [ABSTRACT FROM AUTHOR]

A scanning radiometer deployed at Davis Station, Antarctica (68 °S, 78 °E), has been recording infrared (1.10-1.65 μm) images of a small region (24 km × 24 km) of the zenith night sky once per minute each austral winter night since February 1999. These images have been processed to extract information on the passage of gravity waves (GWs) (horizontal wavelength, λh > 15 km) and ripples ( λh ≤ 15 km) over the observing station. Phase speeds, periods, horizontal wavelengths, and predominant propagation directions have been deduced. Observed speeds were found to be highly correlated with horizontal wavelengths as has been reported in previous studies. Reverse ray tracing of the detected GWs only enabled us to identify four distinct groups. On average, only 15% of waves detected can be traced back to the troposphere, and a large proportion ( ~45%) were not successfully reverse traced substantially below the airglow layer. Two smaller groups were found to reach a termination condition for reverse ray tracing at altitudes near 50 km and 75 km. Of those that reached the termination altitude in the troposphere (10 km), most of the end points fell within a radius of 300 km of the station, with a very pronounced concentration of wave initiation to the northwest of the observing point. The predominant direction of propagation was southward, and they were observed throughout the year. Recent reports suggest the interaction of planetary waves with the background wind field as a potential source for these waves. [ABSTRACT FROM AUTHOR]

Disparities between nutrient intake and demand often result in a state of negative energy balance (EB) in the early-lactation dairy cow. Reducing dietary crude protein (CP) content and providing glucogenic nutrients may overcome this issue. This study evaluates whether or not offering a diet lower in CP and higher in nonfiber carbohydrates (LP-NFC) can improve EB and the metabolic status of the early-lactation dairy cow compared with a diet higher in CP and fibrous carbohydrates (HP-FC). Twenty Holstein-Friesian dairy cows were assigned to 1 of 2 dietary treatments in a randomized block design. Diets were isoenergetic (6.57 MJ of net energy for lactation) and formulated to contain 15% CP and 6% starch (HP-FC), or 12% CP and 28% starch (LP-NFC) and were offered for the first 63 d of lactation. Intake and milk yield were determined daily, whereas milk and blood samples, weights, and body condition scores were collected weekly. Intakes (mean ± standard errors of the mean, SEM) of dry matter (17.4 ± 0.6 kg/d) and energy (113.0 ± 4.6 MJ of net energy for lactation) were not different between treatments. However, the HP-FC group had a higher milk yield (31.8 vs. 28.9 ± 1.4 kg/d) and a lower EB compared with the LP-NFC group. Blood urea N concentration (3.5 vs. 1.8 ± 0.2 mmol/L) was higher, whereas bilirubin (6.0 vs. 6.7 ± 0.2 mmol/L) and ß-hydroxybutyrate concentrations (0.7 vs. 0.8 ± 0.05 mmol/L) were lower in the HP-FC group compared with the LP-NFC group. These data suggest that EB can be improved during early lactation through the manipulation of milk output by offering a lower CP, higher NFC diet. [ABSTRACT FROM AUTHOR]

The prediction of grass dry matter intake (GDMI) and milk yield (MY) are important to aid sward and grazing management decision making. Previous evaluations of the GrazeIn model identified weaknesses in the prediction of GDMI and MY for grazing dairy cows. To increase the accuracy of GDMI and MY prediction, GrazeIn was adapted, and then re-evaluated, using a data set of 3960 individual cow measurements. The adaptation process was completed in four additive steps with different components of the model reparameterised or altered. These components were: (1) intake capacity (IC) that was increased by 5% to reduce a general GDMI underprediction. This resulted in a correction of the GDMI mean and a lower relative prediction error (RPE) for the total data set, and at all stages of lactation, compared with the original model; (2) body fat reserve (BFR) deposition from 84 days in milk to next calving that was included in the model. This partitioned some energy to BFR deposition after body condition score nadir had been reached. This reduced total energy available for milk production, reducing the overprediction of MY and reducing RPE for MY in mid and late lactation, compared with the previous step. There was no effect on predicted GDMI; (3) The potential milk curve was reparameterised by optimising the rate of decrease in the theoretical hormone related to secretory cell differentiation and the basal rate of secretory cell death to achieve the lowest possible mean prediction error (MPE) for MY. This resulted in a reduction in the RPE for MY and an increase in the RPE for GDMI in all stages of lactation compared with the previous step; and (4) finally, IC was optimised, for GDMI, to achieve the lowest possible MPE. This resulted in an IC correction coefficient of 1.11. This increased the RPE for MY but decreased the RPE for GDMI compared with the previous step. Compared with the original model, modifying this combination of four model components improved the prediction accuracy of MY, particularly in late lactation with a decrease in RPE from 27.8% in the original model to 22.1% in the adapted model. However, testing of the adapted model using an independent data set would be beneficial and necessary to make definitive conclusions on improved predictions. [ABSTRACT FROM PUBLISHER]

This study evaluated the prediction accuracy of grass dry-matter intake ( GDMI) and milk yield predicted by the model Graze In using a database representing 522 grazing herds. The Graze In input variables under consideration were fill value ( FV), grass energy content [ Unité Fourragère Lait ( UFL)], grass protein value [true protein absorbable in the small intestine when rumen fermen energy is limiting microbial protein synthesis in the rumen ( PDIE)], pre-grazing herbage mass ( PGHM), daily herbage allowance ( DHA) and concentrate supplementation. Graze In was evaluated using the relative prediction error ( RPE). The mean actual GDMI and milk yields of grazing herds in the database ranged from 9·9-22·0 kg DM per cow d−1 and 8·9-41·8 kg per cow d−1, respectively. The accuracy of predictions for the total database estimated by RPE was 12·2 and 12·8% for GDMI and milk yield, respectively. The mean bias (predicted minus actual) for GDMI was −0·3 kg DM per cow d−1 and for milk yield was +0·9 kg per cow d−1. Graze In predicted GDMI with a level of error <13·4% RPE for spring, summer and autumn. Graze In predicted milk yield in autumn ( RPE = 17·6%) with a larger error in comparison with spring ( RPE = 10·4%) and summer ( RPE = 11·0%). Future studies should focus on the adaptation of Graze In to correct and improve the prediction of milk yield in autumn. [ABSTRACT FROM AUTHOR]

This study evaluated the prediction accuracy of grass dry-matter intake (GDMI) and milk yield predicted by the GrazeIn model using a large database representing 8787 per cow GDMI measurements. In this study, the animal input variables (age, parity, week of lactation, potential peak milk yield, milk fat content, milk protein content, bodyweight, body condition score (BCS), week of conception, BCS at calving and calf birth weight) were investigated. The mean actual GDMI of the database was 15·9 kg DM per cow d−1 and GrazeIn predicted a mean GDMI for the database of 15·5 kg DM per cow d−1. The mean bias was −0·4 kg DM per cow d−1. GrazeIn predicted GDMI for the total database with an RPE of 15·5% at cow level. The mean actual daily milk yield of the database was 21·3 kg per cow d−1 and GrazeIn predicted a daily milk yield for the database of 22·2 kg per cow d−1. The mean bias was +0·9 kg per cow d−1. GrazeIn predicted milk yield for the total database with an RPE of 16·7% at cow level. From the evaluation, GrazeIn predicted milk yield of all cows in late lactation with a larger level of error than in early and mid-lactation. This error appears to be due to the persistency of the lactation curve used by the model, which results in a higher predicted milk yield in late lactation compared with the actual milk yield. [ABSTRACT FROM AUTHOR]

Predicting the grass dry matter intake (GDMI), milk yield (MY) or milk fat and protein yield (milk solids yield (MSY)) of the grazing dairy herd is difficult. Decisions with regard to grazing management are based on guesstimates of the GDMI of the herd, yet GDMI is a critical factor influencing MY and MSY. A data set containing animal, sward, grazing management and concentrate supplementation variables recorded during weeks of GDMI measurement was used to develop multiple regression equations to predict GDMI, MY and MSY. The data set contained data from 245 grazing herds from 10 published studies conducted at Teagasc, Moorepark. A forward stepwise multiple regression technique was used to develop the multiple regression equations for each of the dependent variables (GDMI, MY, MSY) for three periods during the grazing season: spring (SP; 5 March to 30 April), summer (SU; 1 May to 31 July) and autumn (AU; 1 August to 31 October). The equations generated highlighted the importance of different variables associated with GDMI, MY and MSY during the grazing season. Peak MY was associated with an increase in GDMI, MY and MSY during the grazing season with the exception of GDMI in SU when BW accounted for more of the variation. A higher body condition score (BCS) at calving was associated with a lower GDMI in SP and SU and a lower MY and MSY in all periods. A higher BCS was associated with a higher GDMI in SP and SU, a higher MY in SU and AU and a higher MSY in all periods. The pre-grazing herbage mass of the sward (PGHM) above 4 cm was associated with a quadratic effect on GDMI in SP, on MY in SP and SU and on MSY in SU. An increase in daily herbage allowance (DHA) above 4 cm was associated with an increase in GDMI in AU, an increase in MY in SU and AU and MSY in AU. Supplementing grazing dairy cows with concentrate reduced GDMI and increased MY and MSY in all periods. The equations generated can be used by the Irish dairy industry during the grazing season to predict the GDMI, MY and MSY of grazing dairy herds. [ABSTRACT FROM PUBLISHER]

Four primiparous and 4 multiparous midlactation dairy cows were stratified by pre-experimental milk yield (23.5 ± 2.3 kg/d), protein yield (0.75 ± 0.066 kg/d), parity, and days in lactation (121 ± 10 d) into 4 groups of 2 in a 2 × 2 factorial, Latin square design (n = 8) to assess the effect of forage source and a supplementary methionine hydroxy analog on nitrogen (N) balance where low crude protein (CP) diets (13.3%) are offered. Diets contained either predominantly grass silage [GS (G- and G+)] or corn silage [CS (C- and C+)] as the forage source and were offered with (G+ and C+) or without (G- and C-) the isopropyl ester of 2-hydroxy-4 methylthio butanoic acid (HMBi). The G- and G+ contained 46% GS and 10% CS in the dry matter (DM), whereas C- and C+ contained 12% GS and 52% CS in the DM. Supplementary HMBi was included at a rate of 0.2% of DM in G+ and C+ diets. Diets were isonitrogenous (9.8 ± 0.4% protein truly digested in the small intestine) and isoenergetic (0.96 ± 0.01 units of energy for lactation; kg/DM). Each of the 4 experimental periods lasted 24 d: 14 d for dietary adaptation, followed by 10 d of housing in individual metabolism stalls; N balance was conducted on the last 5 d of each experimental period. Intake of DM was higher for CS-based vs. GS-based diets (20.23 vs. 18.41 kg/d). No effect of dietary treatment was found on milk yield or yields of milk fat, protein, and lactose. Supplementing with HMBi tended to improve milk solids yield (1.69 vs. 1.59 kg/d), casein yield (0.59 vs. 0.55 kg/d), and concentrations of casein (2.89 vs. 2.73%) and protein (3.58 vs. 3.49%) in the milk. Dietary N intake was higher for CS-based vs. GS-based diets (0.460 vs. 0.422 kg/d). However, forage source or supplementary HMBi had no effect on N excretion in the feces, urine, or milk. Excretion of urinary urea was positively related to N intake. Concentrations of urea N in the plasma (2.34 vs. 1.72 mmol/L), milk (2.54 vs. 2.24 mmol/L), and urine (123.32 vs. 88.79 mmol/L), and total excretion of urinary urea N (40.23 vs. 35.09 g/d) were higher for animals offered CS-based vs. GS- based diets. Corn silage improved N intake through improved DM intake. However, neither forage source nor HMBi supplementation affects N output in the feces, urine, or milk. [ABSTRACT FROM AUTHOR]

The effects on the performance of dairy cows offered kale, swedes, and perennial ryegrass in situ and perennial ryegrass silage fed indoors to dairy cows pre-partum during winter in Ireland was examined. Eighty-eight spring-calving dairy cows were randomly assigned to one of four offered treatments; (i) 8 kg of dry matter (DM) of kale leaf and stem + 4 kg DM of perennial ryegrass silage (treatment K), (ii) 8 kg DM of the root and leaf of swedes + 4 kg DM of perennial ryegrass silage (treatment S), (iii) 12 kg DM of perennial ryegrass herbage (treatment G) offered in situ and (iv) perennial ryegrass silage offered ad libitum indoors (treatment ID). Cows on treatments K, S and ID had a greater ( P < 0·001) increase in body condition score (0·20, 0·14 and 0·50 units respectively) pre-partum than cows on treatment G which lost 0·22 units. Pre-partum treatment had no effect on variables of milk production in the following lactation. In the first 100 d of lactation, cows on treatment G pre-partum had a lower milk fat concentration (35·6 g kg−1) compared with cows on treatments S and ID (38·3 and 39·3 g kg−1 respectively). There was no effect of treatment on the intervals between parturition and first insemination (mean 74·6 d) and conception (mean 96·1 d). The results suggest that offering kale and swedes to dairy cows pre-partum resulted in a similar lactation performance to dairy cows grazing a perennial ryegrass sward or offered perennial ryegrass silage indoors. [ABSTRACT FROM AUTHOR]

The article presents information on the fertility and the nutritional factors affecting fertility in dairy herds. It is diagnosed that negative energy balance in lactation is associated with reduced fertility performance. The type of energy fed has a significant influence on dairy cow fertility. It is reported that glucogenic nutrients in addition to the diet of dairy herds improves the fertility of cattle.

These experiments were designed to investigate nutritional means of reducing urine N excretion by grazing cows. In experiment 1, 36 Holstein-Friesian cows averaging 92 d in milk were fed either 1 or 6 kg of a high protein concentrate or 6 kg of a low protein concentrate. Pasture dry matter (DM) intake was higher for cows fed 1 kg of high protein concentrate (15.4 ± 0.62 kg/d) than for cows fed 6 kg of low protein concentrate (13.4 ± 0.55) but not for cows fed 6 kg of high protein concentrate (13.9 ± 0.96). The reduction in pasture intake per kg of concentrate DM ingested amounted to 0.35 and 0.47 kg of pasture DM for cows fed 6 kg of high protein and 6 kg of low protein concentrate, respectively. Milk yield and milk protein yield were higher for cows fed 6 kg of high protein concentrate than for cows fed 1 kg of high protein concentrate. Cows fed 6 kg of high protein concentrate had the highest levels of N intake, total N excretion, and urine N excretion. The proportion of N excreted in the urine was lowest for cows fed 6 kg of low protein concentrate. Milk N excretion as a proportion of ingested N was higher for cows fed 6 kg of low protein concentrate than for cows fed 6 kg of high protein concentrate but not for cows fed 1 kg of high protein concentrate. In experiment 2, 24 Holstein-Friesian cows averaging 211 d in milk were supplemented with 4 kg of rolled barley or 4.32 kg of NaOH-treated barley. Milk yield and milk protein yield tended to be higher for cows fed rolled barley than for cows fed NaOH-treated barley. There was no difference in N intake, fecal N excretion, urinary N excretion, or milk N output between diets. Milk urea N concentration was lower for cows fed rolled barley. Significant positive linear relationships were found between N intake and fecal N excretion, urine N excretion, and milk N excretion in experiment 1. In experiment 2, the relationships between N intake and fecal N excretion... [ABSTRACT FROM AUTHOR]