Intake profile, milk production and energy balance of early lactation spring calving Holstein Friesian and Jersey x Holstein Friesian dairy cows in high utilisation pasture-based systems

Early lactation is a critical period for dairy cows as energy requirements rapidly increase with the onset of lactation, however, early lactation dry matter intakes (DMI) in pasture-based systems are under-measured. The objectives of this study were 1) to measure and profile total DMI (TDMI) and animal performance of dairy cows during early lactation in a pasture-based system 2) to investigate early lactation energy balance in pasture-based systems and 3) to examine production efficiencies including TDMI and milk solids production per 100 kg bodyweight. Eighty spring-calving dairy cows were allocated to a grazing group as they calved over a 2 year period (2021 and 2022). Cows were offered a daily herb-age allowance to achieve a post-grazing sward height of 4 cm with silage supplementation when necessary due to inclement weather. Total DMI was measured using the n-alkane technique over a 12 week period from 1st of February to the 23rd of April. Total DMI and daily milk yield were significantly affected by parity with both variables being greatest for third parity animals (17.7 kg DM and 26.3 kg/cow/day, respectively), lowest for first parity (13.2 kg DM and 19.6 kg/cow/day, respectively) and intermediate for second parity animals (16.8 kg DM and 24.1 kg/cow/day, respectively). Peak TDMI was reached on wk 10 for first parity animals (14.6 kg DM), wk 11 for second parity animals (19.3 kg DM) and wk 12 for third parity animals (19.9 kg DM). Parity also had a significant effect on UFL (feed units for milk) feed balance as first parity animals experienced a greater degree of negative energy balance (−3.2 UFL) compared with second and third parity animals (−2.3 UFL). Breed and parity had an effect on production efficiencies during the first 12 weeks of lactation as Jersey x Holstein Friesian cows had greater TDMI/100 kg bodyweight and milk solids/100 kg bodyweight compared with Holstein


INTRODUCTION
A major objective of pasture-based dairy systems is to maintain high levels of both grazing utilization and milk production (Ganche et al., 2013).Grazed grass is the cheapest feed source available on Irish dairy farms (Doyle et al., 2022) and therefore maintaining sward quality and high levels of grass in the diet through high sward utilization is a key performance indicator of Irish grassland farms (O'Donovan et al., 2021).The seasonality of grass growth in Ireland, results in little growth over winter due to low temperatures and low levels of sunlight, while peak grass supply occurs in late spring and early summer (Hurtado-Uria et al., 2013).As a result, 73% of Irish dairy cows calve between January and March (ICBF, 2022), allowing for peak milk production to coincide with increasing grass growth rates (Dillon et al., 1995).Spring grass is a highly nutritious feed for dairy cows due to its high digestibility and crude protein (CP) content (Kennedy et al., 2005;Claffey et al., 2019a).Achieving high levels of dry matter intake (DMI) can be difficult in pasture-based systems in spring, due to inadequate spring grass availability (Claffey et al., 2019a), imposed grazing severity to ensure high quality grass in subsequent rotations (Ganche et al., 2013) and difficult grazing conditions (Kennedy et al., 2011) due to high levels of rainfall, all of which may contribute to limiting cows from achieving their potential production performance (Stockdale, 2004;Faverdin et al., 2011).
Meeting the early lactation nutritional requirements of dairy cows is essential to achieve high levels of production and ensure good health and fertility (Rodney et al., Intake profile, milk production and energy balance of early lactation spring calving Holstein Friesian and Jersey x Holstein Friesian dairy cows in high utilisation pasture-based systems 2018).Intake capacity (Wilkins et al., 2004;Faverdin et al., 2011) and DMI (McEvoy et al., 2008;Bargo et al., 2002) have been reported to have the largest impact on animal performance.Previous studies have reported high intakes in confinement systems (Kolver and Muller, 1998;O' Neill et al., 2011) (23.4 and 19.7 kg DM/ cow/day, respectively), however there is little research to date in pasture-based systems, particularly in early lactation as measuring DMI in pasture-based systems is more difficult than confinement systems (Coleman, 2005).Lewis et al. (2015) previously investigated early lactation DMI using measured intake data from various studies in Moorepark that were carried out from 2007 to 2011 and reported that DMI starts at 8 -10 kg DM/cow/ day after calving and increases by 1 kg DM/cow each week until wk 8, when peak milk yield was achieved, and then increases by 0.5 kg DM/cow/day until peak DMI is achieved on wk 12 of lactation.In pasture-based systems cows typically experience peak milk yields at wk 8 of lactation (Lewis et al., 2015) due to the seasonality of grass growth as the physiological needs of the dairy cow are synchronised with pasture supply (Wood et al., 1972), while cows in indoor systems typically reach peak milk production between wk 4 and 8 of lactation, after which daily milk yields decline until the pre-partum period (Keown et al., 1986).Measuring DMI during early lactation in a pasture-based system will lead to improved feeding management during early lactation and will allow for cows to achieve their potential milk production with reduced incidences of feed restriction.
Energy is the most limiting nutrient during early lactation (Bargo et al., 2002), however, animal performance can be increased with improved management and nutrition (Ingvartsen and Anderson, 2000).At the beginning of lactation cows enter a state of negative energy balance (NEB) (Collard et al., 2000) during which there is an increase in energy demand compared with the prepartum period (Ingvartsen and Anderson, 2000) as milk production increases rapidly (García and Holmes, 1999).Animal DMI is lower immediately postpartum compared with later in lactation due to reduced intake capacity (Mekuriaw, 2023) along with changes in reproductive status and metabolic changes to support the onset of lactation (Ingvartsen and Anderson, 2000).This difference in energy intake and energy output creates a NEB which leads to increased concentrations of nonesterified fatty acids and fat mobilisation which can result in bodyweight (BW) loss (Ingvartsen and Anderson, 2000).The severity and duration of the NEB is influenced by body condition score (BCS) at calving, DMI, milk production and feed quality (Mekuriaw, 2023;Gross et al., 2011) and NEB can also be more pronounced in pasture-based systems (Claffey et al., 2019b) as cows may be restricted due to low spring grass availability (Claffey et al., 2019a) and unfavorable grazing conditions (Kennedy et al., 2011).Kolver and Muller (1998) reported that dairy cows in a pasture-based system required supplementation with high energy feeds such as concentrates during early lactation to achieve their potential milk production.There is limited research which measures total DMI (TDMI) and energy balance during early lactation in pasturebased systems and profiling energy requirement may be beneficial in reducing the severity of NEB.Cows which are well suited to the pasture-based system are highly efficient at converting feed to milk and are able to maintain high levels of pasture intake throughout lactation (Buckley et al., 2005).Previous studies have reported greater production efficiencies with Jersey x Holstein Friesian (JeX) cows compared with Holstein Friesian (HF) cows in pasture-based systems (McClearn et al., 2022;O' Sullivan et al., 2019, Prendiville et al., 2009).
The objective of the current study was to quantify individual TDMI during the first 12 weeks of lactation to create an intake profile for dairy cows in pasture-based systems during early lactation, while maintaining high levels of herbage utilization which is an important objective of pasture-based systems in Ireland and internationally such as in New Zealand (Wilkinson et al., 2020).This study also aims to investigate animal performance, energy balance and production efficiencies during early lactation.The hypothesis of the current experiment is 1) milk production and total DMI would increase with parity, 2) HF and JeX cows would have similar total DMI during early lactation and 3) JeX cows would have greater MS production and improved production efficiencies compared with HF cows.

Experimental site and design
This experiment was conducted at the Teagasc Animal & Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork (52°7′3′′N, 8°16′42′′W; 49m above sea level).A 2 year (2021 and 2022) experiment was carried out to develop a profile of DMI and milk production during the first 12 weeks of lactation (WOL).Eighty spring calving dairy cows (60 multiparous and 20 primiparous) were randomized and placed into one of 2 grazing groups once they calved based on the previous year's milk production for multiparous cows and dam's first lactation for primiparous, breed (HF and JeX), parity, calving date (12th February ± 17 d in Year 1 and 18th February ± 20 d in Year 2), economic breeding index (EBI; €184), BW (547 ± 69.9 kg) and BCS at calving (Table 1).Each year, cows were placed into one of 2 grazing groups (n = 40) and each grazing group had a farmlet of 15.3 ha with 23 paddocks per grazing group.Grazing began on the 1st of Walsh et al.: Early lactation intake profile of dairy cows February in both years.During the experimental period cows were offered an average daily herbage allowance (DHA) to achieve a post grazing sward height (postGSH) of 4 cm, to maintain high levels (>85%) of grass utilization, plus 3 kg concentrate/cow/day fresh weight with 1.5 kg fed at the morning and 1.5 kg fed at the evening milking.Daily herbage allowance was calculated each day using measured pre-grazing herbage mass (preGHM) to a target of 4 cm.Herbage allowance was adjusted daily based on the previous days postGSH as the DHA was increased when this was <4 cm to reduce restriction of DMI.In the current study, animals were allocated grass daily, and as such TDMI may have been limited as animals were not offered ad lib allowances, however, this was kept to a minimum by adjusting the DHA when postGSH was below 4 cm (average postGSH = 4.02 cm).
Fresh pasture was offered after morning and evening milking and back fences were used to avoid re-grazing previous allocations.On-off grazing as described by Kennedy et al. (2011) was implemented for 24 d in Year 1 and 23 d in Year 2 and cows were fully housed for 4 d in Year 1 and one day in Year 2. Silage supplementation was also offered when necessary due to climatic conditions and spring grass availability.On average, cows were offered a total of 187.8 kg DM silage/cow from wk 2 to wk 12 of lactation.A Keenan diet feeder (Keenan Holdings limited, Borris, Co. Carlow, Ireland) was used to allocate fresh silage to the cows to ensure the silage was evenly distributed along the feed barrier.The feed face allowed 0.3 m of head space for each cow as recommended by Teagasc (Teagasc, 2016).A silage sample was taken each week when silage was offered to determine DM content and this was used to calculate fresh weight to be fed using the following calculation; (Number of cows x kg DM offered)/DM %.
The soil type at the experimental site was a free draining, acid brown soil with a sandy loam to loam texture.Soils had a pH of 6.8 (±0.2),P Index of 3.8 (±0.4) and K Index of 3.3 (±0.8; scale 1-4; 1 = deficient, 4 = no response to application of nutrient; Alexander et al., 2008).Daily rainfall (mm), air temperature (ᵒC) and soil temperature to a depth of 100 mm (ᵒC) were recorded daily at the experimental site.The swards mainly consisted of perennial ryegrass (PRG) (Lolium perenne L; PRG >85%), while the remainder consisted of meadow grasses and white clover (Poa, festuca pratensis and trifolium repens L., cv.Chieftain).

Animal measurements
Animals were milked twice each day throughout the experiment at 7.00 h and 15.00 h.Milk yields (kg/cow/ day) were recorded each day at morning and evening milking for every cow (Dairymaster, Causeway, Co. Kerry).While fat and protein content was determined weekly by taking samples from one successive morning and evening milking before being analyzed using Milkoscan 203 (Foss Electric DK-3400, Hillerød, Denmark).Bodyweight and BCS were also measured weekly throughout the experimental period.Bodyweights were measured using an electronic portable weighing scales and Winweigh software package (Tru-test Limited, Auckland, New Zealand).Body condition score was recorded by an experienced independent observer using a scale ranging from 1 to 5, where 1 = emaciated and 5 = extremely fat, with 0.25 increments (Edmondson et al., 1989).
Individual TDMI (grass, silage and concentrate) was measured biweekly on 6 occasions (wk 2, 4, 6, 8, 10 and 12 of the experiment) in each year of the study from the 1st of February until the 23rd of April using the nalkane technique as described by Mayes et al. (1986) and modified by Dillon and Stakelum (1989).A recent study (Wright et al., 2019) evaluating the n-alkane technique for estimate of individual DMI was reported to provide a very appropriate measure, with a Lin's concordance correlation of 0.69 for the C31/C32 pair.The cows were dosed before morning and evening milking for 11 d using a paper bullet (Carl Roth, GmbH, Karlesruhe, Germany) containing 500 mg of dotriacontane (C32, alkane).On the final 5 d of dosing (d 7 -11) fecal samples were collected from each cow before morning and evening milking.Once fecal samples were collected they were stored at −20ᵒC and at the end of each sampling period these samples were thawed and bulked by cow (14.4 g/ sample, 144g/cow total).Bulked samples were dried at 60ᵒC for 72 h and milled through a 1 mm sieve before being stored for analysis of alkane concentration.During d 6 -10 of the sampling period herbage samples which were representative of the next grazing allocation were collected.Two herbage samples per grazing group were taken each day using Gardena hand shears.When silage was included in the diet during intake measurements, silage samples were also collected each morning on d 6 -10 before cows were allowed into the shed for silage.The herbage and silage samples were stored at −20ᵒC, bowl chopped (Muller, typ MKT 204 Special, Saabrücken, Germany) and freeze-dried at −50ᵒC for 72 h before being milled through a 1 mm sieve and stored for analysis of alkane concentration.Total DMI was estimated using the equation described by Mayes et al. (1986): where Fi is the concentration (mg/kg DM) of the C31 (odd number of carbon atoms) natural alkanes in feces, Fj is the concentration in feces of the C32 (even number of carbon atoms) from the dosed synthetic C32 alkane external marker, Hi is the concentration of C31 in herbage, Hj is the concentration of C32 in the herbage and Dj is the daily dose of C32 (mg/day).

Energy balance and production efficiencies
Energy balance for individual animals was calculated as the difference between estimated energy requirement and total energy intake.Energy expenditure was based on UFL required for milk production, maintenance, growth (cow <40 mo) and BW change (Faverdin et al., 2007;INRA, 2017).Energy balance for individual animals was calculated as the difference between estimated energy requirements (UFL used for growth, maintenance and milk production) and estimated total energy intake (UFL intake of grass, silage and concentrates) (INRA, 2017).
milk protein content g kg milk Energy intake was calculated based on TDMI measured using the n-alkane technique using the net energy system (Jarrige, 1989), where 1 unité fouragère lait (UFL) of energy is defined as the net energy content of 1 kg of standard barley for milk production which is equivalent to 1,700 kcal.The UFL supply for grass, silage and concentrate was calculated by multiplying the measured individual DMI for each feed by the UFL content of the feed e.g., grass DMI × UFL content of grass.The UFL supply for each feed was added together to give the total UFL intake.
Total DMI (kg DMI) per 100 kg BW was calculated by dividing measured TDMI by kg BW at the time of intake measurement and then multiplied by 100 to calculate per 100 kg BW.Milk solids (MS) produced per 100 kg BW was calculated by dividing daily average MS production for each week by measured BW for that week and multiplying it by 100 to calculate per 100 kg BW.

Sward measurements
Before grazing pre-grazing herbage mass (PreGHM) was measured in each paddock (>4 cm) using an Etesia mower (Etesia UK Ltd., Warwick, UK).Two 1.2 × 10 m strips were cut in each paddock and a rising plate meter (Jenquip rising plate meter, New Zealand) was used to measure grass height before and after each strip was cut, which was used to calculate sward density.All of the mown herbage was collected and weighed and a 300 g sample were collected from which a 100 g sub-sample was taken.Dry matter was determined by drying a 100 g sub-sample at 90ᵒC for 16 h.Pre-grazing herbage mass was calculated using the following equation (O' Donovan et al., 2002): Area Length 1 1 2 10 000 100 ., % .
( ) Sward density was then calculated using the following equation: A rising plate meter (Jenquip Rising Plate Meter, New Zealand) was used to measure pre-grazing sward height (preGSH) (>4 cm) before cows grazed each paddock.Forty measurements were taken diagonally across each allocation before grazing.The same measurement was taken each day after grazing to determine post grazing sward height (postGSH).A 100 g sample was taken from the silage offered to the cows each week and dried at 90ᵒC for 16 h to determine the DM of the silage.The DM content was then used to calculate the fresh weight allocation each week as described previously.A second 100 g sample was taken and dried at 40ᵒC for 48 h before being milled through a 1 mm sieve and stored for analysis.
Wet chemistry was used to determine the chemical composition of the grazed herbage and silage offered to the cows throughout the experiment.Herbage samples were collected from each paddock before grazing and dried at 60ᵒC for 48 h before being milled through a 1 mm sieve and stored for chemical analysis.Samples were bulked for each treatment by week, and were subsequently analyzed for DM, ash, CP, NDF, ADF and OMD.Ash concentration was estimated by burning a sub-sample in a muffle furnace at 500ᵒC for 12 h (AOAC, 1995, method 942.05).Crude protein concentration was determined using an N-analyzer (Leco FP-428; Leco Australia Pty Ltd., Baulkham Hills, NSW, Australia).The NDF and ADF concentrations were determined using a fiber analyzer (AOAC, 1995, method 973.18) based on the method described by Van Soest et al. (1991).Organic matter digestibility was determined in vitro with the neutral detergent cellulose method (Morgan et al., 1989) (FibertecTM Systems; Foss, Ballymount, Dublin) and calculated with the equation as described by Garry et al. (2018).Silage samples were also bulked by week for both treatments, and analyzed using wet chemistry for DM, OMD, ADF, NDF, CP and ash concentrations as described previously.The UFL content of grass, silage and concentrates was based on chemical composition of the feedstuff.The chemical composition was used to calculate gross energy of the feedstuff and the metabolisable energy was calculated based on the digestible energy of the forage.The milk net energy is calculated by applying the efficiency of the metabolisable energy and gross energy, and finally, the energy content of the forage is expressed as feed units for milk (UFL) by dividing the milk net energy by 1700 (Faverdin et al., 2011).

Statistical analysis
Statistical analysis was carried out using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA, 2002).Total DMI, daily yield, weekly fat and protein content, MS and BW as analyzed from wk 1 to 12 of lactation using PROC MIXED in SAS.The week number was the repeated measure, with individual cow as subject and included as random effect.The EBI predicted transmitting ability (PTA) for milk yield (kg) was used as co-variates in the model.The model contained terms associated with production including breed, parity, WOL, year, week of experiment within year and grazing group.Week of lactation by breed and by parity interactions were analyzed along with breed by parity interactions.All nonsignificant interactions were removed from the model.Data was analyzed using the following model: Where; Y hijklm is the response of the animal m of breed h, in parity i, in year j, in week of experiment k and week of lactation l; • μ = mean; • B h = breed (h = 1 or 2); • P i = parity (i = 1, 2 or 3); • Y j = year (l = 1 or 2); • W k(j) = week of experiment within year (k = 1 -19 in year 1 or 2) • L l = Week of lactation (l = wk 1 -12) • G m = Grazing group (m = 1 or 2) • L l x P i = interaction between week of lactation and parity • L l x B h = interaction between week of lactation and breed • B h x P i = interaction between breed and parity.
• X hijklmn = milk production co-variate • e hijklmn = the residual error term

Milk production and composition
Year had a significant effect on daily yield and MS which were greater in Year 1 (+ 1.6 and 0.12 kg/cow/ day, respectively) and milk protein content which was greater in Year 2 (+ 0.5 g/kg milk).Week of lactation and parity had a significant effect on daily yield.First parity animals had the lowest yield (19.6 ± 0.64 kg/cow/ day), followed by second parity animals (24.1 ± 0.61 kg/ cow/day) and third parity animals had the greatest daily Walsh et al.: Early lactation intake profile of dairy cows yield (26.3 ± 0.45 kg/cow/day).There was a significant interaction present between parity and breed for daily milk yield, with the JeX animals having the greatest yield among the first and third parity animals while HF had the greatest yield for second parity animals.There was also a significant interaction between WOL and parity, parity 2 and 3 animals were the same for wk 1 and 2 of lactation, while third parity animals had a greater daily yield from wk 3 of lactation onwards (Figure 1).
Week of lactation, parity and breed had a significant effect on MS production.First parity animals had the lowest MS (1.65 ± 0.065 kg/cow/day), followed by second parity animals (2.07 ± 0.06 kg/cow/day) and third parity animals had the greatest (2.25 ± 0.044 kg/cow/ day).Holstein Friesian animals had significantly lower MS (1.95 ± 0.052 kg/cow/day) compared with JeX (2.03 ± 0.052 kg/cow/day).There was a significant interaction between WOL and parity for MS, whereby second and third parity animals had the same MS production for wk 1 and 2 of lactation and third parity animals were significantly greater thereafter (+ 0.2 kg/cow/day) (Figure 2).There was also a significant interaction between WOL and breed for MS as all animals were the same for wk 1 to 3 of lactation and JeX were greater from wk 4 of lactation (+ 0.12 kg/cow/day).
There was a significant interaction between WOL and parity for milk protein content (Table 2) as parity 2 animals had a significantly greater milk protein content (35.2 ± 0.38 g/kg milk) for wk 9 to 12 of lactation compared with parity 1 and 3 animals (34.3 ± 0.31 g/ kg milk).Milk protein content was significantly affected by WOL.There was a significant interaction between WOL and breed for milk fat content as JeX had a greater milk fat content (49.5 ± 0.84 g/kg milk) for wk 9 to 12 of lactation compared with HF (47.2 ± 1.04 g/kg milk).Week of lactation also had a significant effect on milk fat concentration.Breed and parity had no effect on milk protein and fat concentrations.

Total Dry Matter Intake
Breed did not have an effect on TDMI, however, WOL and parity had an effect (P < 0.05) on TDMI (Figure 3).Average TDMI was lowest for first parity animals (13.2 ± 0.56 kg DM/cow/day) followed by second parity animals (16.8 ± 0.56 kg DM/cow/day) and greatest for third parity animals (17.7 ± 0.38 kg DM/cow per day) (Table 2).On average, TDMI increased by 0.48 kg/cow/week from wk 2 to 12 of lactation.There was a significant interaction between WOL and parity for TDMI as second and third parity animals were the same for wk 2, 7, 11 and 12 and had significantly different TDMI for every other week (Figure 3).

Bodyweight and BCS
Week of lactation and parity had a significant effect on BW.Third parity animals had the greatest BW (526 ± 7.3 kg) compared with first and second parity animals (488 and 505 ± 9.4 kg, respectively).There was a significant interaction between WOL and parity for BW as all animals had the same BW for wk 1, 10, 11 and 12, and third parity animals had a greater BW compared with first and second parity for all other weeks (Figure 4).Body condition score was also significantly affected by WOL and parity (data not presented).Second parity animals had significantly lower BCS (3.05 ± 0.03) compared with first and third parity animals (3.19 and 3.14 ± 0.03, respectively).Breed had no effect on BW or BCS.

Energy balance and production efficiencies
Year had a significant effect on UFL supply and UFL requirement both of which were greater in Year 1 (+ 0.7 and + 0.9 UFL, respectively).Week of lactation and parity also had a significant effect on UFL requirement and UFL supply.The UFL requirement was greatest for third parity animals (19.0 ± 0.17 UFL/cow/day), followed by second parity (17.8 ± 0.26 UFL/cow/day) and first parity animals had the lowest UFL requirement (15.9 ± 0.28 UFL/cow/day).The UFL supply followed the same trend with 16.4, 15.4 and 12.0 ± 0.25 UFL/cow/day for third, second and first parity animals, respectively.The UFL balance (difference between UFL requirement and UFL supply) was significantly affected by WOL and parity (Figure 5).First parity animals had a significantly greater negative energy balance (−3.2 ± 0.27 UFL) compared with second and third parity animals (−2.3 ± 0.24 UFL) up to wk 12 of lactation.For the 3 parities, energy balance increased week by week.First parity animals also remained in a NEB for the first 12 weeks of lactation whereas second and third parity animals experienced NEB until wk 10 of lactation.
Week of lactation, parity and breed all had a significant effect on TDMI/100 kg BW.First parity animals had significantly lower TDMI/100 kg BW (3.0 ± 0.12 kg DM/100 kg BW) compared with second and third parity animals (3.5 and 3.4 ± 0.10 kg DM/100 kg BW, respectively).Holstein Friesian animals had a lower TDMI/100 kg BW compared with JeX (3.2 and 3.4 ± 0.09 kg DM/100 kg BW, respectively) (Figure 6).There was a significant interaction between WOL and parity for TDMI/100 kg BW which was the same for all animals during wk 2 and 3 of lactation and first parity animals were significantly lower than second and third parity animals thereafter (data not shown).
Year had a significant effect on kg MS/100 kg BW which was greater in Year 1 compared with Year 2 (0.41 and 0.39 ± 0.007 kg MS/100 kg BW, respectively).Week of lactation, parity and breed all had a significant effect on kg MS/100 kg BW.First parity animals had significantly lower kg MS/100 kg BW (0.36 ± 0.013 kg MS/ kg BW) compared with second and third parity animals (0.42 and 0.43 ± 0.011 kg MS/100 kg BW, respectively).The JeX animals had greater MS/100 kg BW (0.41 ± 0.009 kg MS/100 kg BW) compared with HF (0.39 ± 0.011 kg MS/100 kg BW) (Figure 7).There was a significant interaction between WOL and parity as first parity There was also an interaction between WOL and breed (Figure 7) as the JeX animals had a significantly greater kg MS/100 kg BW (0.42 ± 0.008 kg MS/100 kg BW) compared with HF (0.38 ± 0.010 kg MS/100 kg BW) from wk 4 until wk 12 of lactation.

DISCUSSION
Increasing productivity on pasture-based dairy farms depends on high pasture growth, sward quality and herbage utilization while also ensuring cows have adequate grass DMI (Delaby et al., 2018) which will reduce the severity of NEB that dairy cow's experience postpartum (Claffey et al., 2019b).There are limited studies to date which regularly measure early lactation DMI as intake measurements can be more difficult in pasture-based dairy systems (Coleman, 2005), however, more recently Wright et al. (2019) reported that the n-alkane technique provided an accurate measure of TDMI.The objective of the current study was to measure and profile early lactation DMI and energy balance during the first 12 weeks of lactation in a pasture-based system while ensuring high levels of herbage utilization.
The current study measured an average daily TDMI across the herd (with 27% primiparous cows) of 13.2 kg DM/cow/day on wk 2 of lactation, and increased by 38% to 17.7 kg DM/cow/day on wk 12 of lactation.On average, the weekly increase in TDMI was 0.48 kg DM/ cow/week from wk 2 to 12 of lactation.This increase in TDMI was greater from wk 2 to wk 6 of lactation at 0.8 kg DM/cow/week compared with wk 7 to 12 of lactation when DMI increased by 0.3 kg DM/cow/week.The rate of increase across parity was not the same, with first parity animals increasing by an average of 0.41 kg DM/ cow/week, compared with the second and third parity animal's, which increased by an average of 0.49 and 0.55 kg DM/cow/week, respectively, similar to Marquardt et al. (1977) and McClearn et al. (2022).Early lactation TDMI in the current study started higher than previously reported by Lewis et al. (2015) (+3.2 kg DM/cow/ week) and also increased at a slower rate as Lewis et al. (2015) reported DMI increasing by 1 kg/cow/week, however, Lewis et al. (2015) reported a similar effect of parity on DMI.Genetic improvements over the last number of years and greater milk production potential of dairy cows (Berry et al., 2016;INRA, 2018) could be a reason for greater TDMI reported in the current study compared with Lewis et al. (2015).It is possible that early lactation TDMI could also be greater than reported in the current study if cows were offered ad lib grass and silage, however, a key objective of this study was to maintain herbage utilization as is common in pasturebased systems both in Ireland and internationally.In the current study second and third parity animal's TDMI was 22 and 26% greater than first parity animals similar to the findings of McClearn et al. (2022).The increase in TDMI for multiparous cows compared with primiparous cows may be partially due to the greater BW and larger rumen capacity of multiparous cows (Bines et al., 1976;Beauchemin et al., 2002 andReshalaitihan et al., 2020), however these studies are from indoor systems and there is limited data on this in grazing systems to date.In the current study TDMI/100 kg BW was the same for second (3.48 kg DM/100 kg BW) and third parity animals (3.44 kg DM/100 kg BW), however, first parity animals were significantly lower (2.98 kg DM/100 kg BW) due to the lower BW (−28 kg/cow) of primiparous animals.
The physiological state of an animal can reduce intake capacity, with young, fat and pregnant animals having a lower intake capacity compared with older, thinner and non-pregnant animals (Bines et al., 1976;Broster and Broster, 1998).Reshalaitihan et al. (2020) reported that primiparous animals had reduced serum TP concentrations and higher serum NEFA concentrations before calving compared with multiparous animals which can reduce intake before calving and, therefore, may have indirectly reduced DMI after parturition.Similar to the findings of McClearn et al. (2022), Vance et al. (2012) and Prendiville et al. (2010), breed did not influence TDMI or the rate of DMI increase across early lactation which may be as a result of similar daily milk yield and BW for the 2 breeds throughout the current experiment.
The current study reported that peak TDMI was reached on wk 11 of lactation (17.9 kg DM/cow/day), 6 weeks after peak milk production was achieved on wk 5 of lactation (25.1 kg/cow/day) and 8 weeks after peak MS production was reached on wk 3 of lactation (2.22 kg/cow/day).Daily milk yield increased by 1.36 kg/cow/ week from wk 1 until wk 5 of lactation and decreased by 0.55 kg/cow/week from wk 5 until wk 12 of lactation as milk yield decreases after peak yield is achieved (García and Holmes, 2001).Previous studies (Knight and Wilde, 1987;Boutinaud et al., 2004;Gross and Bruckmaier, 2019) have reported that the increase in milk production in early lactation is caused by the rate of cell differentiation which increases the number of milk secreting cells and after peak yield is achieved a decline is milk yield is attributed to the rate of cell apoptosis.The number of milk secretory cells declines by 17% between d 90 and 240 of lactation which leads to a 23% reduction in milk production (Boutinaud et al., 2004) similar to the current study as milk yield declined by 15% from d 35 to d 84.Similar to previous studies (Horan et al., 2005;Lee and Kim, 2006;McClearn et al., 2022) daily milk yield increased with parity.Second and third parity animals in the current study had 19 and 25% greater daily milk yields compared with first parity animals, respectively.This difference in yield can be accounted for due to the lower TDMI (McClearn et al., 2022), lower peak milk production which leads to a lower cumulative milk production (Wood et al., 1972) and the effect of energy partitioned for growth in primiparous animals (Coffey et al., 2006;Wathes et al., 2007).The mammary gland of multiparous cows is also more metabolically active and has a greater density of secretory cells compared with Walsh et al.: Early lactation intake profile of dairy cows Figure 3.Total dry matter intake consisting of grazed grass, grass silage and concentrate of first, second and third parity dairy cows in a spring calving pasture-based system from wk 2 to wk 12 of lactation measured using the n-alkane technique primiparous cows, particularly in early lactation, both of which are a cause of the differences in milk production seen among parities in early lactation (Miller et al., 2006).
Previous studies have reported significantly greater milk yields of up to 1.4 kg/cow/day in HF cows compared with JeX cows (Prendiville et al., 2011;Coffey et al., 2017;McClearn et al., 2022), however, there was no difference between HF and JeX cows in the current study (22.9 and 23.7 kg/cow/day, respectively).The greater MS production (+0.08 kg MS/cow/day) from JeX cows in the current experiment is consistent with previous studies (Prendiville et al., 2009;Vance et al., 2012) which is as a result of the higher milk composition (+2.2 and +0.42 g/ kg milk, fat and protein concentration) which is associated with the Jersey breed (Prendiville et al., 2011;Vance et al., 2012).The study reiterates the ability of JeX cows to produce similar milk yields to HF cows while producing significantly higher MS.
It has been widely reported that dairy cows' BW decreases during early lactation (Coffey et al., 2017;Poncheki et al., 2015;Gross et al., 2011), and this loss in BW can be more pronounced in pasture-based systems due to lower DMI at grazing (Bargo et al., 2002;Vance et al., 2012).Gross et al. (2011) reported BW decreased from calving until wk 7 of lactation and remained similar from wk 7 to 12.In the current study BW loss was greatest from wk 1 to wk 4 of lactation at −14.4 kg/cow/week and this decreased to -4.4 kg/cow/week from wk 5 to wk 12 of lactation.This decrease in BW loss after wk 4 of lactation is a result of greater TDMI as WOL increases and reductions in energy partitioned to milk production as production reduced after peak yield on wk 5 of lactation.Bodyweight was greater for animals as parity increased which is similar to previous studies (Horan et al., 2005;Roche et al., 2007;McClearn et al. 2022).Greater BW is associated with higher milk yield (Macdonald et al., 2005;Handcock et al., 2019) which is consistent with the results of the current study as BW had a positive linear relationship with daily milk yield (R 2 = 0.74).This is similar to the findings of Ertuğrul et al. (2021) who reported a moderate to high positive correlation between BW and milk yield ranging from 0.45 to 0.59.
Similar to Friggens et al. (2007) cows experienced the greatest degree of NEB on wk 2 of lactation as TDMI is lowest at this time.The rate of change for energy balance was lower for first parity animals (+ 0.54 UFL/cow/ week) compared with second and third parity animals (+ 0.89 and 0.76 UFL/cow/week), therefore, second and third parity animals spent less time in a NEB at 10 weeks compared with first parity animals who were in NEB for the duration of the 12 week study.Similar to Grummer and Rastani (2003) there was no correlation between energy balance and daily milk yield in the current study, however, there was a strong positive correlation between energy balance and TDMI (R 2 = 0.84) an also between energy balance and energy intake (R 2 = 0.84).The relationship between energy balance and TDMI may explain  (2007) who reported that first parity animals mobilised less body reserves compared with second and third parity animals, resulting in first parity animals spending a shorter duration in NEB.The differences between these 2 studies may be as a result of different diets as cows were offered a normal or high energy TMR diet in the study by Friggens et al. (2007).The subsequent effects of grazing behavior in the current study may have caused differences as first parity animals take smaller bites and spend longer grazing compared with multiparous cows (Iqbal et al., 2022), which may increase NEB for first parity animals if smaller grazing areas are offered during spring.The different breeds used may also have caused the difference as Friggens et al. (2007) used Danish Red, Danish Holstein and Jersey cows.Negative energy balance was not calculated after wk 12 of lactation in the current study, therefore, it is possible that first parity animals remained in a state of NEB for longer than 12 weeks.
The pasture-based system requires a cow that can achieve high levels of intake and milk production per unit of BW and also an animal that can meet most of their nutritional requirements from grazed grass through high levels of DMI relative to their genetic potential for milk production (Buckley et al., 2005).The current study compared the efficiency of HF and JeX animals during early lactation using TDMI/100 kg BW and MS/100 kg BW, both of which were greater for JeX animals which highlights the suitability of the JeX breed to pasturebased systems with increased production efficiency with greater intakes and MS/100 kg of BW.The JeX cows in the current study had a greater TDMI/100 kg BW compared with the HF cows (+ 5.9%), which is similar to the findings of McClearn et al. (2022) and Coffey et al. (2017).Prendiville et al. (2009) andBeecher et al., (2014) reported that JeX cows had a higher intake capacity, due to a greater gastrointestinal tract weight and reticulorumen compared with HF cows.Coffey et al. (2017) reported HF cows utilize a greater proportion of energy for maintenance, and therefore, have a lower feed conversion efficiency compared with JeX cows, however, in the current study there was no difference in UFL required for maintenance between HF and JeX cows.The JeX cows did have a higher UFL requirement for milk production compared with HF cows (12.2 and 11.6 UFL, respectively) which may have allowed for the JeX cows to have a greater MS/100 kg BW as they partitioned more energy toward milk production compared with the HF cows which was achievable due to greater TDMI/100 kg BW.

CONCLUSION
Ensuring adequate energy intake during early lactation is essential to reduce the effects of NEB and also to allow cows to meet their milk production potential as milk production increases rapidly during the first 5 weeks of lactation until peak yield is achieved.The intake profile quantified in the current study illustrates high TDMI from the beginning of lactation and a rapid increase in intakes with + 0.8 kg DM/cow/week until wk 6 of lactation and + 0.3 kg DM/cow/week from wk 7 to 12 of lactation.While both the HF and JeX cows had similar TDMI and daily milk yield, the JeX cows had greater MS production compared with the HF cows.The greater production efficiency of the JeX cows allowed for greater TDMI/ 100 kg BW and greater MS/ 100 kg BW.The JeX cows allowed for improved production efficiency with greater MS production.Improving efficiency in pasture-based systems during early lactation is difficult as maintaining high pasture intakes can be a challenge with reduced growth and difficult grazing conditions.The results of the current study allow for a better understanding of the intake profile and energy requirements of dairy cows during early lactation which allow for more informed decisions and improved management for pasture-based systems both in Ireland and internationally.

Figure 1 .
Figure 1.Daily milk yield for first, second and third parity animals in a spring calving pasture-based system from wk 1 to wk 12 of lactation.

Figure 2 .
Figure 2. Milk solids production for first, second and third parity dairy cows in a spring calving pasture-based system from wk 1 to wk 12 of lactation Walsh et al.:  Early lactation intake profile of dairy cows Table2.The effect of parity and breed on daily milk yield, protein and fat content, milk solids, total dry matter intake and bodyweight from wk 1 to wk 12 of lactation in first second and third parity Holstein Friesian and Jersey x Holstein Friesian animals Means within a row with different superscripts are significantly different (P > 0.05).

Figure 4 .
Figure 4. Bodyweight for first, second and third parity dairy cows from wk 1 to wk 12 of lactation

Figure 5 .
Figure5.Energy balance (UFL/cow/day) for first, second and third parity dairy cows from wk 2 to wk 12 of lactation measured as the difference between energy requirement based on UFL needed for milk production, maintenance and growth (animals <40 mo) and energy intake based on dry matter intake of grazed grass, grass silage and concentrate and the energy content of the feeds

Figure 7 .
Figure 7. kg milk solids produced/ 100 kg bodyweight for Holstein Friesian (HF) and Jersey x Holstein Friesian (JeX) dairy cows from wk 1 to wk 12 of lactation calculated using milk solids production and the measured bodyweight each week

Table 1 .
Walsh et al.:Early lactation intake profile of dairy cows Initial herd characteristics for the animals used in the experiment in Year 1 (2021) and Year 2 (2022)