herd approch nutrition health

Animal Reproduction Science 96 (2006) 331–353

A herd health approach to dairy cow nutrition andproduction diseases of the transition cow�

F.J. Mulligan a,∗, L. O’Grady a, D.A. Rice b, M.L. Doherty a

a School of Agriculture, Food Science and Veterinary Medicine, University College Dublin, Irelandb Nutrition Services International, Randalstown Co., Antrim, Northern Ireland, United Kingdom

Available online 8 August 2006

Abstract

This paper presents a practical, on-farm approach for the monitoring and prevention of production diseasein dairy cattle. This integrated approach, should be used in an interdisciplinary way by farmers, veterinarians,nutrition advisors and other relevant professionals for the improvement of animal health and welfare andproducer profitability. The key areas that form the basis for this approach are body condition score manage-ment, negative energy balance, hypocalcaemia, rumen health and trace element status. Monitoring criteriaare described for each of these key areas, which when considered collectively, will facilitate the assessmentof dairy cow health with regard to clinical and subclinical disease. The criteria, which are informed bypublished scientific literature, are based on farm management and environmental factors, clinical data, milkproduction records, dietary analysis, and assessment of blood and liver concentrations of various metabolitesor trace elements. The aim is to review the efficacy of production disease control measures currently in place,and if necessary to modify them or formulate new ones.© 2006 Elsevier B.V. All rights reserved.

Keywords: Dairy cow; Herd health; Production disease; Nutrition

1. Introduction

The nutritional status of dairy cattle has a significant influence on many of the transitioncow production diseases that result in financial losses and reduced welfare. From a financialperspective, producers are not only faced with the cost of treating dairy cows for specific productiondiseases, but they often incur additional consequential costs. For example, dairy cattle that develop

� This paper is part of the special issue entitled Nutrition and Fertility in Dairy Cattle, Guest Edited by A. Evans andF.J. Mulligan.

∗ Corresponding author.E-mail address: [email protected] (F.J. Mulligan).

0378-4320/$ – see front matter © 2006 Elsevier B.V. All rights reserved.doi:10.1016/j.anireprosci.2006.08.011

mailto:[email protected]

dx.doi.org/10.1016/j.anireprosci.2006.08.011

332 F.J. Mulligan et al. / Animal Reproduction Science 96 (2006) 331–353

clinical hypocalcaemia (milk fever) are eight times more likely to develop mastitis (Curtis etal., 1983). Similarly, cows with sub-clinical ketosis are eight times more likely to develop leftdisplaced abomasum (Le Blanc et al., 2005). Apart from the losses arising from the clinicaldiseases, the losses arising from insidious subclinical disease in herd mates, together with theproven deleterious consequences for reproductive performance, claw health and udder health,make the prevention of these nutritionally related production diseases of paramount importance,for financial and animal welfare reasons. Therefore the concept of a herd health or preventativeapproach to managing dairy cow nutrition and production diseases has great potential to assistfarmers by providing increased profitability and reassurance regarding the health status of thefarm livestock. This will increase transparency, trust and acceptability on issues of animal healthand welfare with the general public and consumers of dairy products.

Integrated herd health and production management programmes that would bring informationfrom various facets of dairy farming technology into one integrated dairy farming advisory servicehave been proposed (Brand et al., 1996; Kelly and Whitaker, 2001). This integrated multidisci-plinary or team approach in preventative dairy herd health is employed with the emphasis onprofitability and sustainability as opposed to increased production per se. Based on this principal,the recent development of the dairy herd health initiative in Ireland is a multi-stranded project,including efforts by a range of bodies to coordinate programmes of preventive animal health (Moreand Barrett, 2005). It includes at its core, a programme of continuing education for veterinariansbased on integrated modules such as bio-security, calf health, health economics, reproduc-tive performance, lameness, nutrition and production disease, parasite control, and vaccinationstrategies.

This article presents a practical, on-farm approach to preventing and monitoring productiondiseases of the dairy cow by the use of optimal nutrition and management throughout the wholelactation cycle but with specific focus on the transition period. The scientific basis for the method-ology used in this approach is presented.

This preventative and monitoring approach has been sub-divided into five key areas:

(1) Body condition score management (BCS).(2) Negative energy balance (NEB).(3) Milk fever and subclinical hypocalcaemia.(4) Rumen health.(5) Trace element and antioxidant status.

Table 1Target incidence rates for clinical production diseases

Clinical condition Target incidence rate Relevant literature

Milk fever 0–5% Houe et al. (2001)Downer cow syndrome <10% of milk feversHypomagnesaemic tetany 0%Ketosis 0–5% Ingvartsen (2006), Heuer et al. (1999)Left displaced abomasum 0–3% Heuer et al. (1999)Right displaced abomasum 1%Low milk fat syndrome (milk fat < 2.5%) <10% Nordlund et al. (2004)Retained placenta <10% Mee (2004c), Heuer et al. (1999)Lameness <15% Ingvartsen (2006), Heuer et al. (1999)

F.J. Mulligan et al. / Animal Reproduction Science 96 (2006) 331–353 333

2. A preventative approach

The objectives of herd health are achieved by application of the concept of target performance.The comparison of herd performance to target incidence rates for production diseases forms thebasis of preventive planning. The differences between the targets and performance in the contextof animal health are the shortfalls (Table 1). This facilitates the focusing of herd investigationsand serves to prioritise areas requiring immediate or extra attention. The reasons for the shortfallsmust then be investigated in detail, with a view to identifying risk factors contributing to diseaseoccurrence. The specific steps involved in the investigation are detailed below, along with thesupporting literature. When the causes of the shortfall have been identified, both short-term andlong-term control strategies can be formulated based on the risk factors involved. Subsequently,performance is monitored continuously to assess the efficacy of the actions taken. The cycle,including repeated monitoring and assessment of shortfalls is then repeated on a cyclical basis(Fig. 1). While the sensitivity, specificity and predictive value of many of the individual monitoringcriteria used may be rather low when considered alone, it is our contention that consideration ofthe relevant criteria collectively provides a strong basis for herd health evaluation.

3. Key area 1: body condition score management

The maintenance of an optimal body condition score relative to lactation stage, milk yield,nutrition and health status, throughout the lactation cycle is perhaps the most important aspectof dairy cow management that facilitates a healthy transition from pregnancy to lactation. Thesystem of body condition scoring dairy cattle proposed by Edmondson et al. (1989), which isbased on a five-point scale (1 = emaciated; 5 = over-fat), is used in this preventative approach forproduction diseases. The BCS targets recommended in the present approach are shown in Table 2.

3.1. Body condition score target at drying-off and at calving

Hayirli et al. (2002) demonstrated that dairy cattle that were over-conditioned (BCS > 4.0; usinga scale of 1–5) in the last 3 weeks of gestation had a much greater depression in feed intake inthe period immediately pre-calving when compared to cows with lower BCS. Those authors alsoreported a linear reduction in feed intake in the immediate pre-calving period as BCS increased.This phenomenon of feed intake reduction together with the mobilisation of adipose tissue andits accumulation in the liver has in some cases been associated with fatty liver syndrome, difficultcalving, retained placenta and displaced abomasum (Cameron et al., 1998; Kaneene et al., 1997;Zamet et al., 1979a,b). Furthermore, It has been reported that dairy cattle with a BCS of ≥4 in thedry period (scale 1–5) have an increased likelihood of developing milk fever (Heuer et al., 1999).It is noteworthy that Cavestany et al. (2005) reported lower levels of BCS loss for cows calving

Table 2Target BCS for dairy cattle (Holstein/Friesian) at different points of the lactation cycle

BCS at drying off 2.75BCS at calving 3.0BCS at breeding >2.5BCS at 150 DIM 2.75BCS at 200 DIM 2.75BCS at 250 DIM 2.75


Fig. 1. Monitoring and preventing production disease Adapted from Noordhuizen (2001).

with a BCS of <3 in comparison to those calving with a BCS > 3.0. In addition, Garnsworthy(1988) concluded that any BCS between 2 and 3 was adequate for dairy cattle at calving.

The negative consequences of over-conditioning at calving are not confined to the periodimmediately around parturition. Garnsworthy and Webb (1999) summarised several experimentsto demonstrate that body condition score loss in early lactation is almost linearly related tobody condition score at calving. Similarly, Dechow et al. (2002) reported that management andenvironmental factors that increased BCS at calving resulted in more BCS loss in early lactation,


while Kokkonen et al. (2005) demonstrated that fatter cows initiated more extensive mobilisationof body fat before calving and this continued during the first weeks of lactation. Furthermore,cows with a BCS of 4.3 at drying off lost more condition in the dry period and up to 1 monthinto the following lactation, had a higher incidence of abomasal displacement, milk fever, ketosis,endometritis and an increased number of days to first ovulation than cows with a BCS of 3.8 (Kimand Suh, 2003). In addition, Mayne et al. (2002) reported that dairy cows with a BCS of 3.0 inthe dry period had a higher reproductive efficiency in the following lactation in comparison todairy cows with a BCS of 3.3. Much of the available data point to health and reproductive benefitsfor cows with lower BCS at drying off and at calving with few adverse effects reported on milkproduction (Contreras et al., 2004), reproduction or health.

3.2. Body condition score target in early lactation

The association between BCS loss in early lactation and subsequent reproductive performanceis now well accepted (Mayne et al., 2002; Buckley et al., 2003; Shrestha et al., 2005). However, itis unclear whether or not body condition score at breeding per se has any influence on reproductiveefficiency. Horan et al. (2005a) reported no significant difference in the BCS at first AI for cowsthat had normal and abnormal ovarian activity. While Heuer et al. (1999) has reported that theconception rate to first service of thin cows (BCS ≤ 2) was similar to that of cows with normal bodycondition (BCS > 2 or <4), even though cows with a low BCS, experienced more endometritis.Pryce et al. (2001) reported that reproductive performance was strongly related to an absolute BCSvalue recorded once in early lactation. Therefore, apart from the importance of considering BCSloss in early lactation, Pryce et al. (2001) and the reports of Buckley et al. (2003) and Shrestha etal. (2005) emphasise the importance of achieving some minimal threshold value of BCS in earlylactation. Since Buckley et al. (2003) have indicated that a BCS of more than 2.5 is required toavoid reduced odds of reproductive success, the BCS of >2.5 at breeding will be used as the targetin this preventative approach.

The targets in Table 2 imply that BCS loss in early lactation of 0.25–0.50 units is achievablewhere BCS at calving is 3.0. This is lower than the average BCS loss reported by Buckley et al.(2003) of 0.51 units for cows with an average 305-day milk yield of 6557 kg. However, Buckleyet al. (2003) have reported that only 30% of cows with a pre-calving BCS of 3.25 lost 0.5 unitsof BCS or more. This level of BCS loss is also in keeping with the average condition score lossreported by Pryce et al. (2001) for cows yielding on average 28 kg/day in the first 26 weeksof lactation. However, higher rates of BCS loss have been reported by Horan et al. (2005b) forgrazing cows with a pre-calving BCS in the region of 3.25–3.5 and with a 305-day milk yield ofbetween 6000 and 7900 kg. In particular, cows fed lower levels of concentrate supplementationat pasture, and higher milk production line cows, lost more BCS in early lactation.

3.3. On farm approach

On farm records of BCS for all cows at key stages in the lactation cycle should be comparedto the targets in Table 2. It is recommended that cows at drying-off, calving, breeding, 150days in milk (DIM), 200 and 250 DIM, should be scored according to Edmondson et al. (1989).Scoring is best performed with the appropriate scale describing individual scores at hand, witheach individual being palpated and not relying on visual assessment. Apart from calculatingthe average condition score for relevant groups of cows at key stages in the lactation cycle, theproportion of each group that deviate markedly from the target should be noted.


4. Key area 2: negative energy balance

It is well known that negative energy balance is a problem of early lactation cows arising fromhigh milk energy output and relatively low feed intake. However, negative energy balance is alsoa problem for late gestation cows (Grummer et al., 2004) and may predispose them to manytransition cow disorders such as displaced abomasum (Le Blanc et al., 2005), retained placenta(Cameron et al., 1998; Kaneene et al., 1997), dystocia (Zamet et al., 1979a,b), fatty liver andketosis (Doherty, 2002; Bertics et al., 1992), reduced feed intake after calving (Doepel et al.,2002) and immuno-suppression (Goff, 2003). In particular, a large reduction in energy balancearound calving may cause periparturient health disorders of dairy cattle (Grummer et al., 2004).

4.1. Preventing negative energy balance

Since negative energy balance is a product of low energy input and high energy output, allattempts to try and prevent this problem in the pregnant or lactating cow should consider thestrategies available to ensure that feed intake is least compromised during the last 3 weeks ofgestation and the early period of lactation (Grummer et al., 2004). One of the most importantaspects of ensuring adequate feed intake in the 3 weeks immediately prior to calving is to avoidthe over-conditioning of dry cows (Hayirli et al., 2002). Grummer et al. (2004) implicated severalmanagement or environmental factors that are likely to be important for feed intake pre-partum,they are: overcrowding, group changes, diet changes, trough space, water quality and hamperedcow comfort. The failure to feed lactating cows truly ad libitum (feed refusals of 5–15% areaccepted) has been shown by Robinson (1989) to restrict feed intake. However, after consideringpracticality at farm level, Grant and Albright (1995) have recommended a feed refusal rate of2–3%. It is the experience of the present authors that removing the refused feed and offering it toless critical animals (e.g. late lactation cows, but not heifers) can pay dividends. Furthermore, thelatter authors suggested that reduced feed availability and or reduced trough space may lead toincreased feed consumption and competition during the first 2–6 h after feeding, with the possibleconsequences of increased digestive disorders and aggressive behaviour. Apart from restriction infeed availability and trough space, limited water availability and quality, poor grouping strategy,slippery floors, excess time standing in holding areas and excess time spent at milking will alllimit feed intake (Grant and Albright, 1995).

For farmers using grass silage as their conserved forage, large differences in voluntary feedintake potential (Steen et al., 1998) should be recognised and only those silages with a highintake potential should be used where avoiding feed restriction is critical. For grazing dairy cattle,it has been reported that once post-grazing sward height is less than 7 cm feed intake will becompromised (Gibb et al., 1997). Kolver and Muller (1998) indicated that feed DM intake ishigher, and the degree of negative energy balance experienced in early lactation is lower, forTMR fed cows in comparison to grazing cows. The use of total mixed ration also facilitates theuse of palatable feedstuffs such as molasses, which have been shown to improve energy balancein transition cows (Shah et al., 2004). Horan et al. (2005b) reported higher levels of BCS lossin early lactation for cows fed pasture with low levels of concentrate supplement (up to 0.85units of BCS), versus cows fed pasture with higher levels of concentrate supplementation. This issupported by Mulligan et al. (2004) and Kennedy et al. (2002) who observed an increase in feedintake as concentrate supplementation rate increased at pasture.

Cows with periparturient health disorders, such as retained placenta, fat cow syndrome andmilk fever have been reported to have a lower feed intake in the early postpartum period (Zamet


et al., 1979a,b). Several cytokines, including tumor-necrosis factor, interleukin 1 and interleukin8, released as a component of the immune response to inflammatory conditions such as mastitisand endometritis, may reduce feed intake (Ingvartsen and Andersen, 2000). Furthermore, Goff(2003) has extrapolated that the energy cost of an inflammatory response for a dairy cow of 600 kgbody weight may amount to 4 Mcal per day, and that this has deleterious consequences for cowsalready in negative energy balance. So conditions of ill health in the transition period are likelyto be associated with reduced feed intake and possibly with increased energy requirement.

4.2. Monitoring energy balance: milk data

Several authors have investigated the relationship between energy balance in the early lactationperiod and milk protein percentage (Von Tavel et al., 2005; Duchateau et al., 2005). Buckley etal. (2003) demonstrated that higher milk protein and milk lactose percentage were positivelycorrelated with pregnancy rates early in the breeding season. These findings are supported byDuchateau et al. (2005) in Belgian dairy cattle and by Von Tavel et al. (2005) in Swiss herds.Therefore milk protein percentage is one of the key evaluation criteria for monitoring energybalance in this article. However, milk protein percentage should be considered collectively withother criteria, as it is predictive value for energy balance when considered alone is likely to below.

The ratio of milk fat:milk protein percentage is a useful predictor of dairy cattle with a highrisk of negative energy balance, ketosis, displaced abomasum, ovarian cyst, lameness, mastitisand higher likelihood of condition score loss of greater than 0.5 units (Heuer et al., 1999; Hamannand Kromker, 1997; Buckley et al., 2003). Although Heuer et al. (1999) used the milk fat:proteinratio of 1.5 for early lactation cows to indicate problem cows, other studies suggest that a lowervalue closer to 1.3 should be used (Buckley et al., 2003; Hamann and Kromker, 1997). Heueret al. (2000) described cut-off points for energy balance in early lactation using milk variablesas—milk fat:protein ratio > 1.4, milk protein < 2.9%, milk fat > 4.8% and milk lactose < 4.5%.

The key monitoring criteria for assessment of early lactation cow energy balance in this articleare for a nadir milk protein percentage of >3.05 (Von Tavel et al., 2005) and for a milk fat:proteinratio of <1.5. Furthermore, with the use of data such as concentrate feeding strategy, weeks post-partum, parity, energy corrected milk yield, and milk component data, energy balance can bepredicted quite accurately (Reist et al., 2002). Such equations and prediction methods shouldbe evaluated for use by nutrition advisors, farmers and veterinarians. It is important to reiteratethat these criteria may be useful indicators when used collectively, and that lower standards ofstatistical association are assumed relevant for herd investigations than for research trials. Theaim is to assess energy balance at herd not individual cow level.

4.3. Negative energy balance monitoring: blood metabolites

This strategy is based on the use of betahydroxybutyrate (BHB) for the monitoring of subclinicalketosis in lactating cows with suggested optimal sampling times between 5 and 50 days in milkand the use of non-esterified fatty acids (NEFA) testing for the detection of prepartum negativeenergy balance and fatty liver in cows that are from 2 to 14 days pre-calving. In the case of bothmetabolites, it is suggested that 12 cows should be sampled from the ‘at-risk or ‘eligible’ groupwith an alarm level threshold reached if 10% of lactating cows have a BHB concentration in excessof 1.4 mmol/l or if 10% of pre-fresh cows have a NEFA concentration in excess of 0.400 mmol/l(Oetzel, 2004). Nielan et al. (1994) have used the BHB cut-off of 1.2 mmol/l as an indication


of hyperketonemia. Whitaker (1997) has described cut-off points for plasma NEFA at the endof pregnancy as 0.4 mmol/l and for lactating cows in early lactation as 0.7 mmol/l. For BHB,Whitaker (1997) has described cut-off values for milking cows as 1.0 mmol/l and for cows at theend of gestation as 0.6 mmol/l, while glucose concentrations should remain above 3.0 mmol/l fortransition cows. It is the present authors experience that using a cut-off for lactating cow BHBconcentration of 1.0 mmol/l identifies to many false positives, and that assessing blood glucoseconcentrations is not very useful. Oetzel (2004) has suggested that the time of sampling withina day has a critical influence on the outcome of blood metabolite analysis. For BHB, the idealtime for sampling is suggested as 4–5 h after feeding, while for NEFA just before feeding wasrecommended. Oetzel (2004) also indicates that for cows suffering from type II ketosis (resultingfrom pre-existing fatty liver) testing the 5–15 DIM group should prove useful, while for cows withtype I ketosis (primary lactational ketosis) they typically do not become ketotic until 21–42 DIM.So the optimal time for sampling cows for BHB may depend on whether negative energy balanceand over-conditioning existed in the dry period that may have given rise to fatty liver. It is alsoworth noting that there are several cow-side tests available that rely on detecting high levels ofketones in urine or milk.

4.4. Negative energy balance monitoring: dietary evaluation

The calculation of dietary energy balance for the lactating cow is facilitated by firstly predictingfeed intake. Several equations are available in the literature that account for concentrate feedinglevel, live weight, week of lactation and milk yield (Vadiveloo and Holmes, 1979; NRC, 2001).The key monitoring criteria for dietary energy balance is that ≥95% of energy requirements shouldbe supplied by the diet at 8 weeks post-partum (McNamara et al., 2002; Sutter and Beever, 2000).In practice, the key monitoring criteria for energy balance may be built from the most preliminaryand easily available criteria (such as BCS and milk data) to the more difficult to attain or costly(such as blood metabolites or dietary energy balance estimation). Using this system, the cost ofherd investigations only arises where initial suspicions are raised.

4.5. On farm approach (Table 3)

Shortfalls for the incidence of ketosis, retained placenta and displaced abomasum; high milk fatto protein ratios, low milk protein and milk yields, and poor reproductive performance, necessitatethe investigation of energy balance. It is important to appreciate that farm records are oftenincomplete and sometimes unavailable:

• Compare on farm records of BCS to suggested targets.• Inspect individual cow milk recording data to assess energy balance by days in milk within

early lactation or age. Ideally, this may be done before any farm visit.• Evaluate feed trough space.• Evaluate potential of feed management to restrict intake.• Evaluate amount of feed offered and refused amount. Are cows really fed ad libitum?• Evaluate the intake potential of the diet particularly home grown forages.• Assess post-grazing sward height. In practice, the ability of farm advisors and veterinarians

to recognise the ‘over-grazed’ pasture is of critical importance. Furthermore, local soil andclimatic conditions that may lead to reduced pasture intake should always be considered.


Table 3Key monitoring criteria for negative energy balance in dairy herds

Reference

Percentage of energy requirements supplied 8 weeks aftercalving

≈95% McNamara et al. (2002), Sutter andBeever (2000)

BCS at drying off 2.75 Domecq et al. (1997)BCS at calving 3.0 Mayne et al. (2002), Hayirli et al.

(2002), Buckley et al. (2003)% of cows with >0.5 units BCS loss in early lactation <25% Buckley et al. (2003), Pryce et al.

(2001)BCS at breeding >2.5 Pryce et al. (2001), Buckley et al.

(2003)% of early lactation cows with milk/milk protein > 1.5 <10% Heuer et al. (1999, 2000)% of early lactation cows with nadir milk protein < 3.05% <15% Heuer et al. (2000), Mayne et al.

(2002)% of early lactation cows with nadir milk lactose < 4.5% <15% Heuer et al. (2000), Buckley et al.

(2003)Weekly decline in milk yield (%) post-peak ≤2.5% Chamberlain and Wilkinson (2002)Trough space for transition cows 0.6 m Grant and Albright (1995), Shaver

(1993)Percentage refusals accepted in transition cow trough ≥3% Grant and Albright (1995), Robinson

(1989)Post-grazing sward height for early lactation cows 7 cm Gibb et al. (1997)% cows 2–14 days pre-calving with blood BHB > 0.6 mmol/ ≤10% Oetzel (2004), Whitaker (1997)% cows 2–14 days pre-calving with blood

NEFA > 0.4 mmol/l≤10% Oetzel (2004), Whitaker (1997)

% early lactating cows with blood BHB > 1.4 mmol/l ≤10% Oetzel (2004)% early lactating cows with blood NEFA > 0.7 mmol/l ≤10% Oetzel (2004), Whitaker (1997)

• Take blood samples from 12 cows due to calve within 14 days to measure BHB and NEFA.• Take blood samples from 12 cows 10–15 DIM or 15–50 DIM (depending on if over-conditioned)

for BHB and NEFA.• Evaluate dry cow and early lactation cow diets for adequacy of energy supply by firstly pre-

dicting feed intake.

5. Key area 3: milk fever and subclinical hypocalcaemia

Milk fever and subclinical hypocalcaemia (total blood Ca ≤2.0 mmol/l) are the most importantmacromineral disorders that affect transition dairy cows. On average 5–10% of dairy cows suc-cumb to clinical milk fever, with the incidence rate in individual herds reaching as high as 34%(Houe et al., 2001). The incidence rate of subclinical hypocalcaemia has been recorded at 30–40%on the day of calving for grazing New Zealand dairy cattle (Roche et al., 2002), while Houe etal. (2001) reviewed several studies that recorded an incidence rate for subclinical hypocalcaemiaof between 23 and 39%. The occurrence of milk fever or subclinical hypocalcaemia is relatedto increased incidences of mastitis (Goff, 2003) dystocia (Correa et al., 1993), uterine prolapse(Risco et al., 1984), retained placenta (Curtis et al., 1983), endometritis (Erb et al., 1985) sloweruterine involution and delayed first ovulation after calving (Borsberry and Dobson, 1989; Jonssonet al., 1999), ketosis and displaced abomasum (Ostergaard and Grohn, 1999; Massey et al., 1993).Subclinical hypocalcaemia has also been associated with impaired gastrointestinal motility (Goff,


Table 4Key monitoring criteria for the prevention of milk fever in dairy herd

Reference

BCS at 250 DIM 2.75BCS at drying off 2.75 Domecq et al. (1997)BCS at calving 3.0 Buckley et al. (2003), Mayne

et al. (2002)Intake of Ca (g/day) ≤30 Horst et al. (1997), Goff

(2004)Diet P% ≤0.3% of DM Lean et al. (2006), Goff

(2004)Diet Mg% 0.3–0.4% of DM Lean et al. (2006)Diet K% <1.8% of DM Goff (2004)DCAB −100 to −200 mequiv./kg DM Goff and Horst (1997)Blood Ca concentration, 12–24 h

post-calving>2.0 mmol/l Oetzel (2004)

Blood Mg concentration, 24–48 hpre-calving

0.8–1.3 mmol/l Whitaker (1997)

Blood P (inorganic P) concentration, 12–24 hpost-calving

1.4–2.5 mmol/l Whitaker (1997)

Incidence of retained placenta in multiparouscows

<10% Mee (2004c), Heuer et al.(1999)

Incidence of LDA in multiparous cows ≤3%Incidence of dystocia in multiparous cows <10% Mee (2004c)Incidence of clinical milk fever <5% Houe et al. (2001)Urine pH (if DCAB strategy used) 6.2–6.8 (Holstein cows) Goff (2004)

2003), which will reduce feed DM intake. Several criteria that may be useful in the monitoringof hypocalcaemia on-farm are presented in Table 4.

5.1. Monitoring and preventing milk fever: body condition

It has been reported that dairy cattle, which are over-conditioned at calving have an increasedodds ratio for the development of milk fever (Ostergaard et al., 2003). Sorensen et al. (2002)reported that body condition score management in the dry cow is a regularly used control strategyfor the prevention of milk fever. Similarly, cows experiencing subclinical hypocalcaemia have beenfound to have a higher mean body weight over the first 60 days post-partum in comparison to cowswith higher blood calcium concentration (Kamgarpour et al., 1999). Therefore, the recording andmanagement of body condition score at drying off and at calving, forms part of the key monitoringcriteria for assessing the risk of and preventing milk fever and subclinical hypocalcaemia in dairyherds.

5.2. Monitoring and preventing milk fever: dietary calcium concentration

Low calcium diets fed prepartum are commonly used as a control strategy for the preventionof milk fever (Sorensen et al., 2002). The use of low Ca diets pre-partum causes the activation ofCa homeostatic mechanisms including the secretion of parathyroid hormone and the activationof 1,25-dihydroxyvitamin D3, which increase Ca absorption from the gut and Ca resorbtion frombone (Chamberlain and Wilkinson, 2002). However, for this strategy to work successfully, the


calcium intake for pre-calving cows needs to be limited to between 10 and 30 g of total Ca/day (Horst et al., 1997; Goff, 2004). This level of calcium intake is quite difficult to achieveand has led to the development of calcium binders such as zeolite and vegetable oils (Thilsing-Hansen and Jorgensen, 2002; Wilson, 2003). The key monitoring criteria for dietary Ca contentif this low Ca feeding strategy pre-partum is used is that Ca intake should be ≤30 g/day. Incomparison, cool-season grasses, grass silage, grass hay, wheaten straw, maize silage, legumesilage and legume hay contain approximately: 5.6, 5.5, 5.8, 3.1, 2.8, 13.4 and 15.2 g of Ca/kgof DM (NRC, 2001). Therefore, for many forage types it will be difficult to meet this targetof Ca intake ≤30 g/day, and if this strategy is used to control hypocalcaemia, additional Casupplementation prepartum from mineral mixes and compounds or Ca-rich by-products shouldnot be fed. Roche (2003) has highlighted this problem for New Zealand pasture, which is too high inCa prepartum, and too low in Ca postpartum, to effectively control hypocalcaemia. Furthermore,Roche (2003) has pointed out that great variation exists in the macromineral concentration ofpasture from farm to farm and even from paddock to paddock, complicating milk fever controlstrategies.

5.3. Monitoring and preventing milk fever: dietary cation anion balance (DCAB) and K

The concept of dietary cation anion balance has focused attention on the level of K that iscontained in the feed of precalving dairy cattle (Horst et al., 1997). It is now widely acceptedthat the homeostatic mechanisms that result in milk fever prevention work more efficiently whenDCAB is negative (Block, 1996). The most common strategy employed to achieve this negativeDCAB is the addition of anionic salts to the diet of pre-calving cattle (Goff, 2004). Horst et al.(1997) concluded that it is almost impossible to achieve this negative DCAB if the DCAB offorages or feeds (including by-products) used in this period is >250 mequiv./kg of DM whileGoff (2004) has stated it is very difficult to control hypocalcaemia if total ration K is >1.8%.Furthermore, it has been concluded, by Goff and Horst (1997) that dietary K% is more importantthan dietary Ca in the prevention of milk fever. Therefore, as a key monitoring criteria for milkfever and hypocalcaemia a diet K% of ≤1.8% has been used in this preventative strategy. Forthose using the addition of anionic salts to try and prevent milk fever and hypocalcaemia, threekey monitoring criteria have been suggested (1) that DCAB for dry cows is between −100 and−200 mequiv./kg DM (Goff and Horst, 1997), that urine pH for cows fed using the DCAB strategyis 6.0–6.8 and that dietary Ca concentration is 1.2% of the diet (Oetzel et al., 1988). The monitoringof urine pH for eight or more close-up cows fed using this DCAB strategy is extremely useful todetermine if optimal dietary acidification has been achieved (Oetzel, 2004).

5.4. Monitoring and preventing milk fever: dietary Mg concentration

The daily intake of dietary Mg is of critical importance in the control of milk fever andsubclinical hypocalcaemia (Chamberlain and Wilkinson, 2002; Goff, 2004). The strategy of milkfever and subclinical hypocalcaemia prevention by ensuring that Mg supplementation levels areoptimal in the periparturient period has been suggested by Roche (2003) and is used extensivelyin practice (Sorensen et al., 2002). In a recent review, increasing Mg supplementation was foundto have the greatest influence amongst dietary strategies for the prevention of milk fever (Leanet al., 2006). Therefore, one of the key monitoring criteria for the prevention of milk fever isthat dietary Mg concentration for pregnant dairy cattle should be in the region of 0.4% of dietaryDM (Lean et al., 2006; Goff, 2004). To identify herds where Mg feeding strategy is not optimal,


blood Mg concentration may be determined in cows that are expected to calve in the next 24–48 h(Whitaker, 1997). The ideal range has been reported as 0.8–1.3 mmol/l (Whitaker, 1997).

5.5. Monitoring and preventing milk fever: dietary P concentration

Lean et al. (2006), has also reported that dairy cow dietary P concentration is closely related tothe risk of developing milk fever. The latter authors have reported that increasing dietary P from0.3 to 0.4% for pregnant dairy cattle would increase the risk of developing milk fever by 18%.Similarly Goff (2004) has suggested that a diet supplying more than 80 g/day of P to pregnantdairy cattle may block the production of 1,25-dihydroxyvitamin D3. Goff (2004) has indicatedthat the NRC requirement of 0.4% P may be excessive and Lean et al. (2006) has shown thatincreasing dietary P from 0.3 to 0.4% will increase the incidence rate of milk fever. Therefore, akey monitoring criteria for the development of milk fever and subclinical hypocalcaemia is thatdietary P is ≤0.3%.

5.6. Monitoring and preventing milk fever: blood calcium concentration

Monitoring of dairy herds for subclinical hypocalcaemia has been described by Oetzel (2004).This monitoring approach involves blood-sampling cows about 12–24 h after calving. The totalblood calcium concentration of 2.0 mmol/l has been suggested by Oetzel (2004) as a target forsubclinical hypocalcaemia.


Shortfalls in the target incidence of milk fever, retained placenta, displaced abomasums, dys-tocia, downer cows, poor feed intake or poor reproductive efficiency in early lactation necessitatethe consideration of milk fever and subclinical hypocalcaemia as contributing factors.

• BCS management is critical for the prevention of milk fever with the target BCS at calving of3.0 being suggested in this article. The BCS of all cows should be assessed at calving and atdrying-off.

• The specific strategy for milk fever control on the farm should be identified. All farms shouldhave some pre-determined strategy for milk fever control.

• The calculation of Ca intake in the close up dry period, from added Ca and estimates or actualvalues for the forages and by-products used, needs to yield a value of ≤30 g/day if this strategyis to prevent milk fever.

• A key monitoring criteria for milk fever and hypocalcaemia is that calculated diet K concen-tration should be ≤1.8% in the close-up dry period.

• The DCAB of forages used in close-up dry period should be <250 mequiv./kg of DM, with thetarget DCAB after addition of anions being −100 to −200 mequiv./kg DM.

• Target urine pH for cows fed using the DCAB strategy is 6.0 to 6.8. It is essential to monitorthe urine pH of eight close up dry cows if using the dietary DCAB strategy.

• A dietary Mg concentration of close to 0.4% should be achieved after consideration of the Mgin home grown forages and added Mg.

• The authors of this review have found it useful to assess blood Mg concentration in cows thatare within 7 days of calving.


• It is important that dietary P is limited to 0.3% or less after considering forages and addeddietary P.

• It is vital that all cows have access to the minerals fed and that only palatable anionic saltsare fed if they are to be used. Adequate feed availability is of importance in the immediatepre-calving period (last 5 days) if for example a substantial amount of the Mg allowance fordairy cattle is supplied by the forages or mix fed.

• The authors of this article have encountered many herd problems of milk fever that were relatedto the grazing of cows on relatively high quality pasture in the close-up dry period.

• All milk fever control strategies may be assessed by taking blood samples from cows calvedwithin the previous 24 h. Blood Ca levels should be >2.0 mmol/l.

6. Key area 4: rumen health

Garrett et al. (1997) reported a 40% incidence rate of low rumen pH within one-third ofherds studied. Subacute ruminal acidosis has been linked to laminitis (Enemark et al., 2002;Oetzel, 2000), decreased DMI (Garrett, 1996), erratic feed intake, reduced rumination behaviour(Chamberlain and Wilkinson, 2002), poor condition score in lactating animals (Oetzel, 2000),loose faecal consistency (Nordlund et al., 1995; Oetzel, 2000), low milk fat syndrome (Nordlundet al., 1995; Oetzel, 2000), caudal vena cava syndrome (Nordlund et al., 1995) and abomasaldisplacement/ulceration (Olson, 1991) and immuno-suppression (Kleen et al., 2003). Nordlundet al. (1995) stated that early transition cows and cows at peak dry matter intake are most at riskfrom SARA. Early transition cows are at higher risk due to reduced absorptive capacity of therumen (Dirksen et al., 1985), poorly adapted rumen flora, and the rapid introduction to high-energydense diets. However, Oetzel (2005) reported a higher prevalence of SARA in cows from 80 to150 DIM than for cows of less than 80 DIM for TMR fed herds. Others have raised concerns overthe occurrence of SARA in pasture fed dairy cattle (Bramley et al., 2005).

6.1. Preventing and monitoring of SARA

Nordlund (2003) suggested monitoring cows for lameness, displaced abomasum, body condi-tion score loss, caudal vena cava syndrome, low milk fat syndrome, ration formulation and rumenfluid analysis as part of a herd investigation for SARA.

6.2. Monitoring of SARA

Donovan et al. (2004) demonstrated an increase in the incidence rate of subclinical lamini-tis in cows subjected to a rapid change from a low energy diet precalving to a high energydiet postcalving. Nordlund et al. (2004) suggested that an incidence rate of lameness of greaterthan 15% warrants further investigation. On assessment of hoof lesions, Nordlund et al. (1995)suggested that an incidence rate of laminitis greater than 10% would arouse suspicion ofSARA.

Allen (1997) summarised data from several trials demonstrating a weak relationship betweenmilk fat percentage and ruminal pH, while Garrett (1996) showed poor correlation between milkfat percentage and the presence of SARA on farm. However, Cook et al. (2005) suggested if 10%of cows in a herd have a milk fat percentage of ≤2.5%, then SARA may be suspected. Faecalconsistency/fibre and rumen fill have also been suggested as cow level assessments of fibre withinthe diet and rumen function (Zaaijer and Noordhuizen, 2003; Garry, 2002). Several practical


Table 5Key monitoring criteria for rumen health

Targets Reference

Lameness incidence <15% with locomotion score 3+ Nordlund et al. (2004)Laminitis incidence ≤10% Nordlund et al. (1995)Incidence of displaced abomasums ≤3%

Rumination% resting cows ruminating >80% Chamberlain and Wilkinson

(2002)Chews per bolus in resting cows 70

Erratic feed intake: yes/no No Oetzel (2005)Faecal consistency score 3 Zaaijer and Noordhuizen

(2003)Faecal sieve test All particles < 0.5 cm Kleen et al. (2003)Caudal vena cava syndrome 0%

Milk fat depression mid-lactation animalsGroups <10% animals milk fat ≤2.5% Oetzel (2000) and Cook et al.

(2005)Individual Milk protein % − fat % < 0.4%

% concentrates in diet <65%% cereals in concentrate ≤40%% diet starch and sugars <20–25% Shaver (1993)

Dietary fibre tableCrude fiber 15–17%ADF 19–21%NDF 27–30%NDF from forage 21–22% Shaver (1993)% forage length

>13 mm 30%>40 mm 5–10%

Long fibre in the ration 1–2 kg

Component fed herdskg of concentrate fed at milking ≤6 kgRate of increase in concentrates after calving ≤0.75 kg/day

Feed space available per animal 0.6 m Grant and Albright (1995)

criteria that may be useful for monitoring rumen health on dairy farms when used collectively arepresented in Table 5.

6.3. Monitoring of SARA: diagnostic sampling

Factors related to low rumen pH are total dry matter intake, sorting of TMR feeds, irregularfeeding patterns, feeding forage and concentrate separately (Oetzel, 2005), meal size (componentfeeding versus TMR), feed particle size, dietary fibre and starch concentrations (Nordlund, 2003).Nordlund and Garret (1994) described rumenocentesis as a technique for consistently samplingrumen pH on-farm. Duffield et al. (2004) demonstrated that samples collected by rumenocentesiscorrelated well with actual rumen pH in comparison to samples collected via oral stomach tubeas the buffering effect of saliva was avoided. Because of the daily fluctuations in pH, Nordlund


and Garret (1994) recommended sampling cows at 2–5 h after component feeding or 5–8 h afterintroduction to TMR to detect the daily nadir in ruminal pH. Oetzel (2003) suggested the samplingof 12 cows at risk with a positive herd diagnosis if 3 or more have a rumen pH of less than 5.5.


The clinical picture may vary greatly between farms with no one sign confirming the presenceof SARA, meaning a closer assessment of the problem is needed.

SARA is suspected as a problem at herd level if:

• Higher incidence of lameness (laminitis mainly), displaced abomasum, body condition scoreloss, caudal vena cava syndrome, erratic feed intake or milk yield.

• More than 15% of dairy cows with a locomotion score of ≥3.• Less than 80% of resting cows are ruminating.• Faecal consistency for lactating cows is extremely loose (score < 3).• Ten percent of the mid-lactation cows have milk fat concentrations of ≤2.5% or if 10% of the

mid-lactation cows have a milk fat concentration less than the milk protein concentration by0.4%.

• Dietary levels of effective fibre are not adequate.• High levels of total concentrate or cereals are being fed.• Feed trough space and management are not ideal.

7. Key area 5: trace element and antioxidant status

Although trace element status is thought to be of less importance than other nutritional riskfactors for periparturient health problems and reproductive performance, trace element deficiencymay be linked to conditions such as retained foetal membranes (Gupta et al., 2005), abortion (Mee,2004a) and weak calf syndrome (Logan et al., 1990; Van Wuijckhuise et al., 2003). Husband(2006) has recently reported combined selenium and iodine deficiency in a dairy herd with a highincidence of retained foetal membranes, milk fever and vulval discharge. Furthermore, differencesin reproductive performance have been demonstrated in cattle and sheep when comparing traceelement supplementation strategies (Black and French, 2004; Hemmingway, 2003). Other authorshave reported differences in the incidence of mastitis after supplementation with high levels ofVitamin E in the dry period and in early lactation (Weiss et al., 1997) but results of supplementationdiffer between trials (Moyo et al., 2005). Xin et al. (1991) emphasised that the amount of copperneeded for optimal immune function may exceed that amount which will prevent more classicaldeficiency signs. Consequently the assessment of trace element status should form part of all herdhealth nutritional monitoring strategies.

7.1. Key monitoring criteria for trace element and antioxidant status

The prevalence of herd health problems including mastitis, weak calf syndrome, retained foetalmembranes, ill thrift, poor reproductive performance and myoptahies, can often form the initialbasis for assessing trace element status. In addition, for many of the nutrients under consideration,classical deficiency signs may be observed, although in the authors’ experience these can cause amisdiagnosis. For example, a spectacled appearance around the eyes of cattle arising from light-ening of the coat colour has been suggested as a classical sign of copper deficiency (Chamberlain


Table 6Key monitoring criteria for dairy cow trace element status

Reference

Cu >10–11 �mol/l of plasma Kincaid (1999), Mee (2004b), Whitaker (1997)>20 mg/kg liver DM NRC (2001)

Se 210–1200 ng/ml whole blood Kincaid (1999)1.25–2.5 �g/g liver DM (adult) Kincaid (1999)2.3–8.0 �g/g liver DM (newborn) Kincaid (1999)

GSPx >50 iu/g of Hb Whitaker (1997), Mee (2004b)

Inorganic iodine >50 �g/l of plasma Mee (2004b), Kincaid (1999)

T4 >20 mmol/L plasma Whitaker (1997)

Zn >0.4 �g/ml of plasma NRC (2001)0.8–1.4 �g/ml of serum Kincaid (1999)>100 mg/kg dry liver NRC (2001)

Mn 70–200 ng/ml of whole blood Kincaid (1999)6–70 ng/ml of serum

MMA ≤2.0 �mol/l Paterson and MacPherson (1990), Rice et al. (1981)

�-Tocopherol 3–3.5 �g/ml periparturient cows Weiss (1998)

and Wilkinson, 2002; NRC, 2001). However, such an appearance may also be caused by ill-thrift.Furthermore, Underwood (1981) has described anaemia, fragile bones, cardiac failure in younganimals and reproductive inefficiency characterised by depressed expression of oestrus behaviourin cows as a result of copper deficiency. In the experience of the present authors, lameness asso-ciated with physitis in weaned dairy calves has been a common manifestation of Cu deficiency.Other trace elements such as selenium and Vitamin E exhibit classical deficiency signs such asnutritional muscular dystrophy (NRC, 2001), while iodine deficiency results in the classical defi-ciency symptoms of enlarged thyroid glands in the calf together with weak or dead hairless calves(NRC, 2001; Van Wuijckhuise et al., 2003). It should be noted that while classical deficiency signsmay be used to implicate trace element or antioxidant deficiency, herd health problems related totrace element deficiency are often reported in their absence; the amount of trace elements neededfor optimal immune responses may exceed the amounts required to prevent classical deficiencysigns (Xin et al., 1991) and the addition of organically complexed trace elements to diets withalready adequate levels has shown beneficial effects on reproductive performance (Campbell etal., 1999).

7.2. The use of animal tissue samples for assessment of Cu, I and Se status

The diagnosis of trace element deficiency is often reliant on blood or liver analysis (Table 6).Whitaker (1997) described optimal values for plasma Cu of 9.4 �mol/l and for serum of 7.5 �mol/l.However, Mee (2004b) and Husband (2006) have reported higher reference ranges for plasmaCu concentration and it is known that liver copper stores may be depleted whilst plasma orserum Cu concentrations are maintained. Therefore the measurement of liver Cu concentrationsby liver biopsy may be required to detect subclinical deficiency (Chamberlain and Wilkinson,2002; Whitaker, 1997). NRC (2001) described liver Cu concentrations of below 20 mg/kg on a


DM basis or 5 mg/kg wet weight as the cut-off value for Cu deficiency. Apart from blood andliver Cu concentrations, the concentrations of ceruloplasmin and superoxide dismutase in bloodhave also been used to assess Cu status (Ward and Spears, 1997).

For the assessment of Se status in dairy cattle, blood, milk and liver Se concentration are oftenused along with glutathione peroxidase (GSPx) (Knowles et al., 1999; Mee, 2004b; Whitaker,1997). Grace et al. (2001) have shown close relationships between blood Se and milk Se andbetween milk Se and GSPx status of New Zealand dairy cows treated with Se injection. SinceKnowles et al. (1999) reported that the response patterns of dairy cattle to Se intake in terms ofwhole blood GSPx and Se are very similar it is likely that both are equally accurate criteria forassessing dairy cow Se status. However, Chamberlain and Wilkinson (2002) suggested that themeasurement of serum GSPx may be more accurate than red blood cell GSPx as serum GSPx isreflective of a recent change in Se status whereas red blood cell GSPx is not, as it is dependenton the rate of erythropoesis and erythrocyte turnover. Whitaker (1997) described an optimal levelof GSPx of more than 50 units/g of haemoglobin, whereas Mee (2004b) has reported a referencerange for GSPx of 42–161 iu/g of haemoglobin.

The assessment of iodine status in dairy cattle is often based on the concentration of thyrox-ine (T4) or plasma inorganic iodine (PII) (Chamberlain and Wilkinson, 2002). Both the latterauthors and Kincaid (1999) questioned the usefulness of T4 for assessing iodine status of dairycattle. Kincaid (1999) pointed out that low iodine intake during pregnancy can result in goitreeven when serum T4 in the dam was apparently normal (Azoulas and Caple, 1984). Further-more, Rhandawa and Rhandawa (2001) reported no difference in the concentrations of plasmatriiodothyronine (T3) and T4 between iodine deficient and normal cows. However, significantlylower PII concentrations were found in iodine deficient cows in this study. It is also notable thatRhandawa and Rhandawa (2001) concluded that the response to iodine supplementation wasthe most reliable index of thyroid dysfunction associated with iodine deprivation. The authorsof this paper agree with this statement, but also feel that the assessment of PII is extremelyuseful.


Key monitoring criteria for trace element status have been suggested based on dietary concen-trations or daily supplies as well as blood concentrations of trace elements and or metabolites.Although care has been taken to ensure only values derived in the same way are used to informthese criteria, it is important to use these suggested values carefully as reference ranges can varywidely between laboratories both nationally and internationally.

Initial suspicions of trace element deficiency are often reliant on the occurrence of classicaldeficiency signs on the farm being investigated or in that locality.

• An assessment of dietary trace element supply should be made based on what trace elementshave been added to the diet and compared to suggested targets.

• The investigators should consider local trace element deficiencies or excesses (e.g. high molyb-denum areas).

• Interactions with other mineral sources like concentrates should always be considered.• Blood samples may be taken from ‘marker animals’, that are fed the home-grown forage or

pasture only (e.g. maiden heifers), for assessment of farm-specific trace element status.• Blood samples may be taken from eligible groups within the herd (e.g. early lactation cows or

close-up dry cows) for assessment of trace element status.


• For trace element problems of the dairy cow and calf that occur close to parturition, traceelement status in dry cows, not lactating cows should be assessed.

• The use of liver analysis from fallen animals or liver biopsy may prove useful for the detectionof some trace element deficiencies (e.g. subclinical Cu deficiency).

• Assessing the response to supplementation for specific trace elements or mixes in the eligiblegroup of cows is often invaluable. It is important that only a proportion of the eligible groupare treated to truly diagnose deficiencies.

8. Conclusions

The development of a strategy for the prevention of production diseases in dairy cattle reliesupon the use of optimal nutritional and management strategies, as well as the close monitoring ofclinical and subclinical disease. Criteria have been presented that may be used in the monitoringand prevention of production diseases that are associated with body condition score, energybalance, hypocalcaemia, rumen function and health and trace element status. Ideally herds shouldbe assessed using the suggested monitoring criteria in each key area, facilitating the assessmentof the preventative measures currently being employed. This exercise will also facilitate thediagnosis of subclinical conditions and characterise the overall prevalence of production disease.Where shortfalls are identified, the monitoring criteria suggested will allow the identification ofthe primary risk factors involved. The aim is to review the efficacy of control measures currently inplace, and if necessary to modify them or formulate new ones. The integrated approach describedhas been used effectively in many herd investigations in Ireland, and opportunities exist to assessits impact in terms of animal health and welfare and profitability in detail.

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