M. O'Donovan

Microbiome analysis of dairy cows fed pasture or total mixed ration diets.

Understanding rumen microbial ecology is essential for the development of feed systems designed to improve livestock productivity, health and for methane mitigation strategies from cattle. Although rumen microbial communities have been studied previously, few studies have applied next-generation sequencing technologies to that ecosystem. The aim of this study was to characterize changes in microbial community structure arising from feeding dairy cows two widely used diets: pasture and total mixed ration (TMR). Bacterial, archaeal and protozoal communities were characterized by terminal restriction fragment length polymorphism of the amplified SSU rRNA gene and statistical analysis showed that bacterial and archaeal communities were significantly affected by diet, whereas no effect was observed for the protozoal community. Deep amplicon sequencing of the 16S rRNA gene revealed significant differences in the bacterial communities between the diets and between rumen solid and liquid content. At the family level, some important groups of rumen bacteria were clearly associated with specific diets, including the higher abundance of the Fibrobacteraceae in TMR solid samples and members of the propionate-producing Veillonelaceae in pasture samples. This study will be relevant to the study of rumen microbial ecology and livestock feed management.

Grazing cows are more efficient than zero-grazed and grass silage-fed cows in milk rumenic acid production.

Six rumen-cannulated Holstein cows in early lactation were assigned to 3 treatments: grazing (G), zero-grazing (ZG), and grass silage (GS) harvested from the same perennial rye grass sward in a 3 x 3 Latin square design with three 21-d periods. The objectives of this study were to investigate the underlying mechanisms for the reported elevation in milk rumenic acid (RA) concentration associated with G compared with ZG and GS, and to identify the important variables contributing to the milk RA response. Grazing animals were offered 20 kg of dry matter/cow per day; indoor animals were offered ad libitum grass or silage. A concentrate at a rate of 3 kg/d was also offered to all cows. Rumen, plasma, and milk samples were collected in the third week of each period. Data were analyzed by the MIXED procedure of SAS. Dry matter intakes were less for GS with no difference between G and ZG. Milk yield was greater for G than for ZG or GS. Milk fat and protein contents were less for GS with no difference between G and ZG. The combined intake (g/d) of linoleic and linolenic (18:3n-3) acids was different across the treatments (G: 433; ZG: 327; and GS: 164). Rumen pH was less for G with no difference between ZG and GS. Concentrations of volatile fatty acids and ammonia nitrogen in rumens were not different across the treatments. Wet rumen fill was less for G with no difference between ZG and GS. Vaccenic acid concentrations were different across the treatments in rumen (G: 12.30%, ZG: 9.31%, and GS: 4.21%); plasma (G: 2.18%, ZG: 1.47%, and GS: 0.66%) and milk (G: 4.73%, ZG: 3.49%, and GS: 0.99%). Milk RA concentrations were greater for G (2.07%) than for ZG (1.38%) and GS (0.54%). Milk desaturase index based on the ratio cis-9-14:1/14:0 was not different across the treatments. Milk RA yield per 100 g of linoleic acid and linolenic acid intake (efficiency) was 2.23, 1.50, and 0.62 g in G, ZG, and GS, respectively, suggesting that G cows were more efficient than ZG and GS cows in milk RA production. Stepwise regression analysis of a group of variables revealed that plasma vaccenic acid accounted for 95% of the variation in milk RA production. Milk desaturase index did not enter into the model. Overall findings suggest that substrate intake influenced milk RA production but it was not the only factor involved. There were differences in efficiency of milk RA production, which appears to depend on the factors regulating ruminal vaccenic acid production and its supply to the mammary tissue.

Effect of perennial ryegrass ( Lolium perenne L.) cultivars on the milk yield of grazing dairy cows

The objective of this experiment was to investigate the effect of four perennial ryegrass cultivars: Bealey, Astonenergy, Spelga and AberMagic on the milk yield and milk composition of grazing dairy cows. Two 4 × 4 latin square experiments were completed, one during the reproductive and the other during the vegetative growth phase of the cultivars. Thirty-two Holstein-Friesian dairy cows were divided into four groups, with each group assigned 17 days on each cultivar during both experiments. Within each observation period, milk yield and milk composition, sward morphology and pasture chemical composition were measured. During the reproductive growth phase, organic matter digestibility (OMD) was greater for Bealey and Astonenergy (P < 0.001; +1.6%). AberMagic contained a higher stem proportion (P < 0.01; +0.06) and a longer sheath height (P < 0.001; +1.9 cm). Consequently, cows grazing AberMagic recorded a lower milk yield (P < 0.001; -1.5 kg/day) and a lower milk solids yield (P < 0.001; -0.13 kg/day). During the vegetative growth phase, OMD was greater (P < 0.001; +1.1%) for Bealey, whereas the differences between the cultivars in terms of sward structure were smaller and did not appear to influence animal performance. As a result, cows grazing Bealey recorded a higher milk yield (P < 0.001; +0.9 kg/day) and a higher milk solids yield (P < 0.01; +0.08 kg/day). It was concluded that grass cultivar did influence milk yield due to variations in sward structure and chemical composition.

Restricting dairy cow access time to pasture in early lactation: the effects on milk production, grazing behaviour and dry matter intake

One of the main aims of pasture-based systems of dairy production is to increase the proportion of grazed grass in the diet. This is most easily achieved by increasing the number of grazing days. However, periods of inclement weather conditions can reduce the number of days at pasture. The two objectives of this experiment were: (i) to investigate the effect of restricting pasture access time on animal production, grazing behaviour and dry matter intake (DMI) of spring calving dairy cows in early lactation; and (ii) to establish whether silage supplementation is required when cows return indoors after short grazing periods. In all, 52 Holstein-Friesian spring calving dairy cows were assigned to a four-treatment study from 25 February to 26 March 2008. The four treatments were: full-time access to pasture (22H; control); 4.5-h- pasture access after both milkings (2 × 4.5H); 3-h pasture access after both milkings (2 × 3H); 3-h pasture access after both milkings with silage supplementation by night (2 × 3SH). All treatments were offered 14.4 kg DM/cow per day herbage from swards, with a mean pre-grazing yield of 1739 kg DM/ha above 4 cm, - and were supplemented with 3 kg DM/cow per day of concentrate. The 2 × 3SH treatment was offered an additional 4 kg DM/cow of grass silage by night. Restricting pasture access time (2 × 3H, 2 × 3SH and 2 × 4.5H) had no effect on milk (28.3 kg/cow per day) and solids-corrected milk (27.2 kg/cow per day) yield when compared with the treatment grazing full time. Supplementing animals with grass silage did not increase milk production when compared with all other treatments. Milk protein concentration tended to be lower (P = 0.08; 32.2 g/kg) for the 2 × 3SH animals when compared with the 22H animals (33.7 g/kg). The grass DMI of the 2 × 3SH treatment was significantly lower (-2.3 kg DM/cow per day) than all other treatments (11.9 kg DM/cow per day), yet the total DMI of these animals was highest (16.6 kg DM/cow per day). The 22H cows grazed for 481 min/cow per day, which is significantly longer than all other treatments. The 2 × 3H animals grazed for 98% of the time, whereas the 2 × 3SH grazed for 79% of their time at pasture. Restricting pasture access time did not affect end body weight or body condition score. The results of this study indicate that restricting pasture access time of dairy cows in early lactation does not affect milk production performance. Furthermore, supplementing cows with grass silage does not increase milk production but reduces grazing efficiency.

Direct and carryover effect of post-grazing sward height on total lactation dairy cow performance.

Grazing pastures to low post-grazing sward heights (PGSH) is a strategy to maximise the quantity of grazed grass in the diet of dairy cows within temperate grass-based systems. Within Irish spring-calving systems, it was hypothesised that grazing swards to very low PGSH would increase herbage availability during early lactation but would reduce dairy cow performance, the effect of which would persist in subsequent lactation performance when compared with cows grazing to a higher PGSH. Seventy-two Holstein-Friesian dairy cows (mean calving date, 12 February) were randomly assigned post-calving across two PGSH treatments (n = 36): 2.7 cm (severe; S1) and 3.5 cm (moderate; M1), which were applied from 10 February to 18 April (period 1; P1). This was followed by a carryover period (period 2; P2) during which cows were randomly reassigned within their P1 treatment across two further PGSH (n = 18): 3.5 cm (severe, SS and MS) and 4.5 cm (moderate, SM and MM) until 30 October. Decreasing PGSH from 3.5 to 2.7 cm significantly decreased milk (-2.3 kg/cow per day), protein (-95 g/day), fat (-143 g/day) and lactose (-109 g/day) yields, milk protein (-1.2 g/kg) and fat (-2.2 g/kg) concentrations and grass dry matter intake (GDMI; -1.7 kg dry matter/cow per day). The severe PGSH was associated with a lower bodyweight (BW) at the end of P1. There was no carryover effect of P1 PGSH on subsequent milk or milk solids yields in P2, but PGSH had a significant carryover effect on milk fat and lactose concentrations. Animals severely restricted at pasture in early spring had a higher BW and slightly higher body condition score in later lactation when compared with M1 animals. During P2, increasing PGSH from 3.5 to 4.5 cm increased milk and milk solids yield as a result of greater GDMI and resulted in higher mean BW and end BW. This study indicates that following a 10-week period of feed restriction, subsequent dairy cow cumulative milk production is unaffected. However, the substantial loss in milk solid yield that occurred during the period of restriction is not recovered.

PastureBase Ireland

PastureBase Ireland is a web-based grassland management decision support tool for farmers, which incorporates a dual function of decision support and the development of a centralized database to collate grassland data.PastureBase Ireland will enhance the decision making process around grassland management at farm level, while unlocking the potential of commercial farm grassland research.This web-based tool has shown a relatively high level of accuracy around annual dry matter yield with a relative prediction error of 15.4%.An analysis of 75 commercial farms that use the system has shown greater within farm than across farm variability in individual paddock grass growth. PastureBase Ireland (PBI) is a web-based grassland management application incorporating a dual function of grassland decision support and a centralized national database to collate commercial farm grassland data. This database facilitates the collection and storage of vast quantities of grassland data from grassland farmers. The database spans across ruminant grassland enterprises dairy, beef and sheep. To help farmers determine appropriate actions around grassland management, we have developed this data informed decision support tool to function at the paddock level. Individual farmers enter data through the completion of regular pasture cover estimations across the farm, allowing the performance of individual paddocks to be evaluated within and across years. To evaluate the PBI system, we compared actual pasture cut experimental data (Etesia cuts) to PBI calculated outputs. We examined three comparisons, comparing PBI outputs to actual pasture cut data, for individual DM yields at defoliation (Comparison 1), for cumulative annual DM yields including silage data (Comparison 2) and, for cumulative annual DM yields excluding silage data (Comparison 3). We found an acceptable accuracy between PBI outputs and pasture cut data when statistically analyzed using relative prediction error and concordance correlation coefficients for the measurement of total annual DM yield (Comparison 2), with a relative prediction error of 15.4% and a concordance correlation coefficient of 0.85. We demonstrated an application of the PBI system through analysis of commercial farm data across two years (20142015) for 75 commercial farms who actively use the system. The analysis showed there was a significant increase in DM yield from 2014 to 2015. The results indicated a greater variation in pasture growth across paddocks within farms than across farms.

Inter-relationships among alternative definitions of feed efficiency in grazing lactating dairy cows.

International interest in feed efficiency, and in particular energy intake and residual energy intake (REI), is intensifying due to a greater global demand for animal-derived protein and energy sources. Feed efficiency is a trait of economic importance, and yet is overlooked in national dairy cow breeding goals. This is due primarily to a lack of accurate data on commercial animals, but also a lack of clarity on the most appropriate definition of the feed intake and utilization complex. The objective of the present study was to derive alternative definitions of energetic efficiency in grazing lactating dairy cows and to quantify the inter-relationships among these alternative definitions. Net energy intake (NEI) from pasture and concentrate intake was estimated up to 8 times per lactation for 2,693 lactations from 1,412 Holstein-Friesian cows. Energy values of feed were based on the French Net Energy system where 1 UFL is the net energy requirements for lactation equivalent of 1kg of air-dry barley. A total of 8,183 individual feed intake measurements were available. Energy balance was defined as the difference between NEI and energy expenditure. Efficiency traits were either ratio-based or residual-based; the latter were derived from least squares regression models. Residual energy intake was defined as NEI minus predicted energy to fulfill the requirements for the various energy sinks. The energy sinks (e.g., NEL, metabolic live weight) and additional contributors to energy kinetics (e.g., live weight loss) combined, explained 59% of the variation in NEI, implying that REI represented 41% of the variance in total NEI. The most efficient 10% of test-day records, as defined by REI (n=709), on average were associated with a 7.59 UFL/d less NEI (average NEI of the entire population was 16.23 UFL/d) than the least efficient 10% of test-day records based on REI (n=709). Additionally, the most efficient 10% of test-day records, as defined by REI, were associated with superior energy conversion efficiency (ECE, i.e., NEL divided by NEI; ECE=0.55) compared with the least efficient 10% of test-day records (ECE=0.33). Moreover, REI was positively correlated with energy balance, implying that more negative REI animals (i.e., deemed more efficient) are expected to be, on average, in greater negative energy balance. Many of the correlations among the 14 defined efficiency traits differed from unity, implying that each trait is measuring a different aspect of efficiency.

Original papersPastureBase Ireland: A grassland decision support system and national database

PastureBase Ireland is a web-based grassland management decision support tool for farmers, which incorporates a dual function of decision support and the development of a centralized database to collate grassland data.PastureBase Ireland will enhance the decision making process around grassland management at farm level, while unlocking the potential of commercial farm grassland research.This web-based tool has shown a relatively high level of accuracy around annual dry matter yield with a relative prediction error of 15.4%.An analysis of 75 commercial farms that use the system has shown greater within farm than across farm variability in individual paddock grass growth. PastureBase Ireland (PBI) is a web-based grassland management application incorporating a dual function of grassland decision support and a centralized national database to collate commercial farm grassland data. This database facilitates the collection and storage of vast quantities of grassland data from grassland farmers. The database spans across ruminant grassland enterprises dairy, beef and sheep. To help farmers determine appropriate actions around grassland management, we have developed this data informed decision support tool to function at the paddock level. Individual farmers enter data through the completion of regular pasture cover estimations across the farm, allowing the performance of individual paddocks to be evaluated within and across years. To evaluate the PBI system, we compared actual pasture cut experimental data (Etesia cuts) to PBI calculated outputs. We examined three comparisons, comparing PBI outputs to actual pasture cut data, for individual DM yields at defoliation (Comparison 1), for cumulative annual DM yields including silage data (Comparison 2) and, for cumulative annual DM yields excluding silage data (Comparison 3). We found an acceptable accuracy between PBI outputs and pasture cut data when statistically analyzed using relative prediction error and concordance correlation coefficients for the measurement of total annual DM yield (Comparison 2), with a relative prediction error of 15.4% and a concordance correlation coefficient of 0.85. We demonstrated an application of the PBI system through analysis of commercial farm data across two years (20142015) for 75 commercial farms who actively use the system. The analysis showed there was a significant increase in DM yield from 2014 to 2015. The results indicated a greater variation in pasture growth across paddocks within farms than across farms.

Predicting grass dry matter intake, milk yield and milk fat and protein yield of spring calving grazing dairy cows during the grazing season

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.

Genetics of alternative definitions of feed efficiency in grazing lactating dairy cows

The objective of the present study was to estimate genetic parameters across lactation for measures of energy balance (EB) and a range of feed efficiency variables as well as to quantify the genetic inter-relationships between them. Net energy intake (NEI) from pasture and concentrate intake was estimated up to 8 times per lactation for 2,481 lactations from 1,274 Holstein-Friesian cows. A total of 8,134 individual feed intake measurements were used. Efficiency traits were either ratio based or residual based; the latter were derived from least squares regression models. Residual energy intake (REI) was defined as NEI minus predicted energy requirements [e.g., net energy of lactation (NEL), maintenance, and body tissue anabolism] or supplied from body tissue mobilization; residual energy production was defined as the difference between actual NEL and predicted NEL based on NEI, maintenance, and body tissue anabolism/catabolism. Energy conversion efficiency was defined as NEL divided by NEI. Random regression animal models were used to estimate residual, additive genetic, and permanent environmental (co)variances across lactation. Heritability across lactation stages varied from 0.03 to 0.36 for all efficiency traits. Within-trait genetic correlations tended to weaken as the interval between lactation stages compared lengthened for EB, REI, residual energy production, and NEI. Analysis of eigenvalues and associated eigenfunctions for EB and the efficiency traits indicate the ability to genetically alter the profile of these lactation curves to potentially improve dairy cow efficiency differently at different stages of lactation. Residual energy intake and EB were moderately to strongly genetically correlated with each other across lactation (genetic correlations ranged from 0.45 to 0.90), indicating that selection for lower REI alone (i.e., deemed efficient cows) would favor cows with a compromised energy status; nevertheless, selection for REI within a holistic breeding goal could be used to overcome such antagonisms. The smallest (8.90% of genetic variance) and middle (11.22% of genetic variance) eigenfunctions for REI changed sign during lactation, indicating the potential to alter the shape of the REI lactation profile. Results from the present study suggest exploitable genetic variation exists for a range of efficiency traits, and the magnitude of this variation is sufficiently large to justify consideration of the feed efficiency complex in future dairy breeding goals. Moreover, it is possible to alter the trajectories of the efficiency traits to suit a particular breeding objective, although this relies on very precise across-parity genetic parameter estimates, including genetic correlations with health and fertility traits (as well as other traits).