Metabolic Disorders in Transition Dairy Cows in a 500-Cow Herd—Analysis, Prevention and Follow-Up

Abstract

Managing transition cows and preventing diseases related to this period is challenging due to the latter’s multifactorial nature. The aim of this applied observational case study is to illustrate and discuss the different aspects involved and provide an approach to analysis and the resulting management solutions using a real-life case within a 500-cow herd. The initial assessment, involving the collection of data on the level of production, animal health and behaviour, and metabolic indicators, as well as management and housing key indicators, revealed key risk factors, including overcrowding, suboptimal feeding strategies, inadequate water supply, and insufficient disease monitoring. These factors contributed to increased cases of metabolic disorders such as hypocalcemia (annual incidence 7.8%), excessive lipomobilisation, and displaced abomasum (annual incidence 5.2%). A holistic approach combining feeding adjustments, disease monitoring, facility improvements, and long-term management strategies was implemented to address these challenges. Short-term interventions, such as optimizing the dietary cation–anion balance and enhancing disease detection protocols, led to noticeable improvements. However, structural constraints and external factors, such as extreme weather conditions (heat stress) and economic limitations, created significant hurdles in achieving immediate and sustained success. The farm ultimately opted for infrastructural improvements, including a new transition cow facility, to provide a long-term solution to these recurring issues. This case highlights the complexity of transition cow management, demonstrating that long-term success depends on continuous monitoring, interdisciplinary collaboration, and adaptability in response to evolving challenges in dairy production.

1. Introduction

The transition period is known to be the most challenging period in the production cycle of dairy cows, from the perspectives of animal physiology and the respective management requirements [1,2,3,4,5,6]. It is traditionally defined as the three weeks before to the three weeks after calving—though there is ongoing debate as to whether this period should be extended further [7,8]. It is the period with the highest disease and treatment rates, as well as the highest culling incidence [9,10,11,12,13,14], ascribing it high economic relevance [11,15,16,17]. The latter is not only due to the immediate costs and lost revenues from treatment expenses and decreased milk production, but also the long-term negative influence of peripartum diseases on lactation performance and reduced fertility [11,18]. Additionally, these diseases increase the risk of illness in future lactation [19,20]. The literature describes postpartum diseases in dairy cows as part of a multifactorial disease complex, with a diverse array of housing and management factors holding a central role as risk factors [3,11,21,22,23,24,25,26]. Different studies and reviews have investigated and discussed the interrelation of the diseases occurring in this period, as well as the related risk factors, recently challenging different traditional beliefs [7,8,27,28,29,30,31]. Furthermore, digital animal health monitoring systems have increased in relevance [32,33,34,35]. Under practical farm settings, however, data acquisition, integrative interpretation and the elaboration of problem solutions are, in many cases, very challenging [36,37], and the respective case reports are scarce (Google Scholar Search, 2.November 2024; key words: transition dairy cow, problem, metabolic disease, case report).

We hypothesize that a holistic, data-driven approach can effectively uncover interrelated risk factors for metabolic and digestive disorders in transition dairy cows. When applied under practical farm conditions, such an approach can generate targeted, farm-specific interventions that improve animal health outcomes, despite the inherent challenges in data collection and interpretation.

The aim of this case report is therefore to illustrate how data can be collected, analysed, interrelated and interpreted, resulting in practical recommendations and respective problem solutions under practical circumstances and highlighting the practical constraints. For this, one herd with metabolic and digestive disorders from our herd health service was used with a metabolic and digestive disorders problem in transition dairy cows of multifactorial origin.

The farm consulted us with respect to the management of metabolic and digestive disorders from the single-animal to herd level. In an initial single-animal case report, we describe the treatment, outcome, and economic evaluation of a dairy cow with a left displaced abomasum (DA) using the “blind-stitch” method on this farm, discussing risks associated with this method, alternative surgical approaches, and the importance of training staff and the consulting veterinarian in animal health management routines [38]. The current manuscript aims to provide a comprehensive herd-level analysis of the farm, describing multifactorial risk factors using herd-level metrics and discussing long-term preventive strategies for the entire herd and the resulting outcomes.

2. Case Presentation

2.1. Background

A 500-cow dairy farm in southern Brandenburg (Germany) approached us due to the increased occurrence of metabolic disorders in their transition cows.

The herd manager reported a doubling of metabolic and digestive disorders in his transition dairy cows over the course of the last three years, with clinical milk fever and DA as the main observed pathologies.

The farm is part of a five-year project in which in-depth farm analyses were performed, including a very broad assessment of the housing, management, feeding and animal health situation, giving access to detailed farm information [39].

2.2. Herd Assessment

The herd assessment was performed in September 2018. In the following section, a general description of the herd is given, and a special focus is put on aspects relevant to transition cow health. A summary of the most important aspects of the herd data is given in

Table 1. Overview of most relevant herd data from a 500-cow dairy farm recorded during the herd assessment.

Herd size and structure	504 cows, 131 calves, 100 heifers (6–12 m), 187 heifers (12–24 m), 24 heifers (>24 m); cow/young stock ratio: 0.88; mainly German Holstein breed
	The facility continuously increased its total number of cows between 2010 and 2015 from 430 to 494 cows and stayed constant at ~500 cows thereafter.
	35.4% 1st lactation, 25.5% 2nd lactation, 19.0% 3rd lactation, and 11.3% 4th lactation animals; average lactation: 2.3
Milk production and content	Milk production per cow and year (test-day data): 10,397 kg, Marketable milk per cow and year: 10,012 kg (of which 66 kg are fed to calves) = 96.3% of milk produced
	305 d milk production: 1st lactation: 8920 kg, 2nd lactation: 10,616 kg, ≥3rd lactation: 11,151 kg
	Test-data (average (±SD) of last 12 months): milk kg per cow and day (dry cows not included): 32.1 (±1.4) kg, fat%: 3.95 (±0.17)%, protein%: 3.34 (±0.11)%, urea: 200 (±17) mg/mL, SSC: 177 (±26) thousand cells/mL, average days in milk (DIM): 180 (±7)
	SCC analysis revealed high SCC at beginning of lactation, especially in older animals: 132, 137 and 349 thousand cells/mL in mean in the first 50 DIM in the 1st, 2nd and 3rd lactation, respectively. In the ≥3rd lactation animals 11% exhibited ≥750 thousand cells/mL in the first 50 DIM.
Culling (last 12 months)	Culling rate: 36.3%, a total of 181 animals of which 87% slaughtered, 7% died, 4% euthanized; 4% mortality rate (% of the rolling herd average that died on-site within one year)
	Culling reasons: 32% mastitis, 20% lameness, 16% fertility, 11% metabolic disorders, 21% other (low production, milkability, and other reasons)
	Percentage culled in the first 30 DIM: heifers: 4.3%, 2nd lactation: 4.9%, 3rd lactation: 14.0%
	Production of culled animals: 30,207 kg lifetime production
	Slaughter weight and revenue of cows sold for slaughter: 276 kg and 677 €; extrapolated on all animals that were culled (slaughter and mortalities on farm) in that period: 566 € per cow.
Fertility/Calvings (last 12 months)	Days between calvings: 395 d, voluntary waiting period: 78 d, first service conception rate: 35.6%, insemination index (cows): 2.6, pregnancy index (=insemination index excl. culled animals): 2.1
	Average dry cow period: 58 days (intended: 8 weeks, however high variation: many animals with a longer dry period in ≥3rd lactation, Figure A1)
	Number of calvings per month between October 2017 and September 2018 show a non-continuous calving pattern (Figure A2)
	Stillbirth rate: 6.7% (heifers: 4.8%, cows: 7.5%), excl. twins: 4.7%; highest stillbirth rates in 4th lactation animals (13.3%, excl. twins: 6.0%; 5.6% twins with a stillbirth rate of 75%; stillbirth defined as calf born dead or dying within 24 h after birth and born >240 d of gestation)
	Calving ease (and resp. stillbirth rate): 16.0% not observed (9.4%), 63.6% easy (1.2%), 17.4% medium (11.1%), 2.5% heavy (15.4%), 0.5% caesarean section (50.0%)
	Weights of stillbirths markedly lower than life born animals: 1st lactation: 35.5 vs. 39.4 kg (n = 8), 2nd lactation: 30.9 vs. 40.3 kg (n = 7), 3rd lactation: 20.0 vs. 41.3 kg (n = 2), 4th lactation: 24.8 vs. 42.6 kg (n = 4, twins excluded); in ≥2nd lactation animals, 6 of the stillbirths were born ≤260 d of gestation.

.

2.2.1. Housing and Cow Behaviour

The main herd (cows and calves) and heifers were located at two different locations in housing systems typical for this region: a total-confinement system with manure scrapers (concrete flooring) and cubicles with either deep straw–lime bedding (colostral phase and fresh cows) or rubber mattresses with a thin layer of sawdust and lime (all other milking cows). The dry cows and calving area were on a deep-bedded pack with a trafficable feed bunk. Notable was the overstocking in the dry cow area (paved area: 5.7 m², defined as the area in the housing environment where the cow can move freely except in the cubicles) as well as the fresh cow pen (

Table A1. Cow groups/pens, paved area, feed bunk space and water trough spacing.

Pen/Group	Number of Animals	Number of Cubicles	Animals/Cubicles	Paved Area/Animal (m2) 1	Feed Bunk Space/Animal (cm)	Number of Troughs	Animals/ Trough	Trough Space/Animal (cm)
barn1: dry cows	50	*	*	5.7	42	3	17	7
barn1: springing heifers	27	*	*	6.3	46	3	9	6
barn1: close-up cows	3	*	*	51.1	373	3	1	119
barn1: calving cows	5	*	*	16.7	122	2	3	27
barn1: calving heifers	4	*	*	23.3	170	1	4	8
barn2: DNB cows	8	12	0.7	5.4	185	2	4	5
barn2: mastitis pen	8	12	0.7	4.4	189	2	4	8
barn2: colostral phase	12	19	0.6	4.9	187	4	3	11
barn2: fresh cows	22	38	0.6	4.8	214	4	6	6
barn3: first lactation heifers	80	83	1.0	6.1	53	5	16	8
barn3: high yielding 1	99	100	1.0	6.5	67	4	25	8
barn4: high yielding 2	75	77	1.0	6.2	53	5	15	9
barn4: mid yielding/lactation	81	84	1.0	4.5	45	4	20	7
barn4: late lactation	50	70	0.7	5.9	60	4	13	8

* on deep-bedded pack, no cubicles, ¹ area where the cow can move freely expect the resting areas [40]; DNB = do not breed.

) [40,41,42]. The latter area is designed as the “feeding-and-lying-cubicle” with only one narrow (2.05 m) alley behind the cows. The high stocking density was not apparent on the day of data acquisition (0.6 cow/free-stall, paved area per cow: 4.8 m²). The herd manager, however, pointed out that the stocking density regularly increases to one cow/free stall, leading to a paved area per cow of 2.8 m², in this group. In almost all groups, an insufficient water supply was noted, described by an insufficient number of troughs in several groups and a trough length of <10 cm per animal (Table A1) [43,44]. Furthermore, the cubicles were short (190–200 cm) and narrow (110 cm) in the colostral-phase and fresh cow groups [45]. The hygiene scoring of the cubicles revealed insufficient cubicle management, especially in the colostral phase pen (

Table A2. Bedding hygiene in different pens in % [46].

Group	N Scored	Dry and Clean	Moderatly Dirty and/or Wet	Highly Dirty and/or Wet	Plentiful and Even	Moderatly Covered and/or Uneven	Ground Visible/Highly Uneven
barn2: DNB cows	12	0	33	67	42	42	17
barn2: mastitis pen and colostral phase *	29	0	31	69	21	52	28
barn2: fresh cows	38	87	13	0	87	13	0
barn3: first lactation heifers	80	3	63	35	9	45	46
barn3: high yielding 1	69	10	58	32	23	46	30
barn4: high yielding 2	97	0	71	29	0	73	27
barn4: mid yielding/lactation	79	0	59	41	0	68	32
barn4: late lactation	70	0	64	36	0	73	27
Summary	474	9	57	34	14	57	29

* groups in one line on one side of the barn, only separated by a gate; DNB = do not breed.

) [46]. The hygiene of the deep-bedded packs of the close-up and dry cow pen was considered insufficient (wet and dirty). The calving area was considered clean and dry. The scoring and documentation of the lying and rising behaviour reflects some issues in the cubicle design (e.g., wall or pillar at the head part) in mainly the milking groups [46]. In the colostral-phase and fresh cow pen, minor hindrances to normal lying and rising behaviour were observed due to the small size of the cubicles. The indices CCQ (Cow Comfort Quotient), PEL (Proportion-Eligible Lying) and CCI (Cud-Chewing-Index, recorded 4 h after feeding and milking in the morning) described an overproportioned number of standing animals, as well as a low number of ruminating animals in the close-up and dry cow pens (

Table A3. Cow-comfort indices (in %).

Group	CCQ >85%	PEL >75%	CCI >50%
barn1: dry cows	-	33	31
barn1: close-up cows	-	21	18
barn1: springing heifers	-	25	37
barn1: calving heifers	-	33	33
barn2: DNB cows	75	38	25
barn2: mastitis pen and colostral phase *	56	23	56
barn2: fresh cows	50	18	63
barn3: first lactation heifers	78	49	42
barn3: high yielding 1	92	60	47
barn4: high yielding 2	88	72	41
barn4: mid yielding/lactation	95	75	48
barn4: late lactation	94	57	46

* Groups in one line on one side of the barn, only separated by a gate; DNB = do not breed. CCQ (Cow Comfort Quotient) = (cows lying correctly in a cubicle: all cows lying or standing/perching in a cubicle) × 100, PEL (Proportion-Eligible Lying, also known as Stall Usage Index) = (cows lying correctly in a cubicle: all cows in group) × 100, CCI (Cud Chewing Index) = (ruminating cows: all cows lying or standing/perching in a cubicle) × 100. Source: [44] adapted from [47,48].

[44]; adapted from [47,48]).

2.2.2. Scoring of Cows

Body condition scoring (BCS, n = 470, [49]) showed that throughout the lactation, the proportion of animals exhibiting a too-low BCS was too high, regardless of lactation number (1st, 2nd and >3rd), with averages of 53% (0–80 days in milk, DIM), 33% (81–160 DIM), 51% (161–250 DIM) and 54% (>250 DIM, Figure A3) of animals exhibiting a lower BCS than recommended for a given stage of lactation [44]. An extreme was observed in the first-lactation animals at 161–250 DIM, with 72% of animals exhibiting a too-low BCS (n = 29, according to the reference line depicted in Figure A3). The herd was considered clean based on the results of hygiene scoring adapted from [44,50] (scale 0–2, n = 437, Figure A4). However, in the close-up, dry cow and colostral-phase groups, the number of animals considered dirty was higher compared to that in the other groups. The number of animals with runny manure was considered too high, with 40% (n = 15) of animals in the colostral-phase group exhibiting this, as assessed in accordance with [51]. Minor decubital lesions at the tarsal joints were present throughout the herd [44]. Severe decubital lesions were rare (2%, n = 476). Lameness scores were within industry averages [52,53,54]: half of the herd (50%, n = 444) was considered not lame, whereas 18% of animals showed mild lameness, with only 12 animals exhibiting moderate to severe lameness [54]. The proportion of lame animals was highest in the close-up and dry cow groups (Figure A5). The interrelation of the BCS and lameness score showed that animals with visible lameness exhibited a lower BCS (

Table A4. Interrelation between lameness grade [54] and low body condition score (BCS) [49]. BCS ↓ (%) = proportion of cows with a BCS lower than the reference value for their stage of lactation (see Figure A3 for the reference line [44]).

	Total		1st Lactation		2nd Lactation		3rd Lactation
Lameness-Grade	N	BCS ↓ (%)	N	BCS ↓ (%)	N	BCS ↓ (%)	N	BCS ↓ (%)
1 (not lame)	220	47.9	104	54.5	61	46.4	55	37.0
2 (uneven gait)	144	46.2	42	43.9	36	50.0	66	45.5
3+ (mild to severe)	80	56.4	16	75.0	15	57.1	49	50.0

). Digital dermatitis lesions were considered present in ~50% of animals during the scoring of animals in the milking parlour (no differentiation was made between acute or chronic lesions, only their absence/presence was scored) [54].

2.2.3. Husbandry and Management Routines

The harmonisation or synchronisation of the work processes of milking, feeding, pushing feed, and cubicle and bedding maintenance were evaluated (partially depicted in Figure A6) and generally considered good [55], with one exception: feeding in the colostral-phase, fresh cow, do not breed (DNB) and mastitis pens occurred several hours before morning milking. The milking routines were evaluated using a questionnaire and protocol [54]. No considerable risk factors were observed. Considering the animal health control and treatment routines, positive outcomes were observed regarding the following points evaluated: daily visual screening of all groups for suspicious animals, the use of alarm lists for milk production decline, detailed electronic documentation of symptoms, diagnoses, and treatments, and the transferral of complicated cases to a clinic; the following aspects had negative outcomes: the veterinarian was only present once per week and in case of emergency, the diagnosis and treatment of single-diseased animals was mainly carried out by the herd manager, and there were no standardized fresh cow control protocols due to a lack of possibilities to fix and control the animals (there were no headgates in this area).

The lameness situation and control plan will not be reflected upon in detail as this is not the scope of this case report. Briefly, the control plan was considered satisfactory, as lame cows were identified by personnel and the herd manager and then referred for treatment by two certified hoof trimmers, present twice weekly. Treatment included trimming, the excision of lesions, and the application of bandages and hoof blocks. Complicated cases were referred to a clinic. Hoof baths were performed twice weekly with either formalin, salicylic acid or peracetic acid. However, the high number of cows with a disproportionate amount of non-healing lesions or recurrent requirement of the hoof trimmer were striking, pointing towards a problem with adequate treatment and aftercare.

2.2.4. Feeding

The rations were fed as a total mixed ration (TMR) with the following main ingredients: corn silage, grass silage, concentrates, straw and additives (

Table A5. Ration ingredients (in kg of fresh matter) provided by the farm’s nutritionist.

Ingredient (in kg Fresh Matter)	Fresh Cows	First Lactation Heifers	High Yielding	Mid-Yielding/Lactation	Late Lactation	Dry Cows	Close-Up
Corn silage	17.50	21.00	22.00	19.50	16.50	12.00	14.00
Grass silage no. 1	12.00	14.00	15.00	7.50	-	-	6.00
Grass silage no. 2	-	-	-	7.50	15.00	15.00	-
Carrot pomache	4.00	4.00	6.00	-	-	-	-
Peas	-	-	-	-	-	-	0.50
Corn	1.50	1.70
Barley	-	-	-	4.80	4.60	-	1.30
Rapeseed extraction meal	-	-	-	-	-	-	0.50
Concentrate and mineral mix no. 1 *	6.50	7.70	-	-	-	-	-
Concentrate and mineral mix no. 2 *	-	-	11.20	-	-	-	-
Concentrate and mineral mix no. 3 *	-	-	-	3.00	3.00	-	-
Barley straw	0.30	0.30	0.30	-	-	-	1.30
Molasses	0.70	0.80	1.00	0.50	-	-	-
Propyleneglycol	0.25	-	-	-	-	-	-
Glycerin	-	-	-	-	-	-	0.30
Feed lime	-	-	-	-	-	0.10	0.15
Mineral feed dry cows *	-	-	-	-	-	0.13	0.13
Concentrate no. 1 *	-	-	-	-	-	-	0.40
Salt	-	-	-	-	-	-	0.03
Sodiumbicarbonate	-	-	-	-	-	0.10	-
Sum kg fresh matter	42.75	49.50	55.50	42.80	39.10	27.33	24.61

* Ingredients of concentrate and mineral mix: no. 1: concentrate no.1 (26%), Distillers’ Dried Grains with Solubles (DDGS, 29% XP; 11%, ProtiGrain, CropEnergies AG, Mannheim, Germany), peas (15%), lupines (5%), barley (20%), rapeseed extraction meal (14.8%), sodium bicarbonate (2.2%), rumen protected fat (REKAPAC, Rekasan GmbH, Kaulsdorf, Germany, 2.6%), feeding lime (1.2%), mineral feed (RRK 20/7 Nr. 0788/19, Rekasan GmbH, 2.2%); no. 2: concentrate no.1 (15%), DDGS (29% XP; 8%), peas (10%), lupines (7%), barley (22%), rapeseed extraction meal (13%), sodium bicarbonate (1,2%), rumen protected fat (REKAPAC, Rekasan GmbH, 2.3%), feeding lime (1.0%), corn (19%), mineral feed (RRK 20/7 Nr. 0788/19, Rekasan GmbH, 1.5%); no. 3: DDGS (10% fresh matter), rapeseed extraction meal (24%), lupine meal (8%), pea meal (25%), grain meal (22.2%), feeding lime (2.8%), salt (0.5%), urea (2%), mineral feed (RRK 20/7 Nr. 0788/19, Rekasan GmbH, 5.5%); mineral feed dry cows: RR 9/6 Nr, 4537/02 (Rekasan GmbH, Kaulsdorf, Germany); concentrate no. 1: REKA-Kraft AGF 121 (Rekasan GmbH, no details on ingredients available).

). Noticeable were the low dietary cation–anion difference (DCAD) values in the milking groups: fresh cows: 108 mEq/kg; first-lactation heifers: 108 mEq/kg; high-yielding cows: 89 mEq/kg; mid-yielding/-lactation cows: 1 mEq/kg; late-lactation cows: −41 mEq/kg (representing a possible risk factor for decreasing the dry matter intake (DMI) [56,57,58];

Table A6. Ration composition, provided by the farm’s nutritionist.

Ingredient (DM Basis)	Unit	Fresh Cows	First Lactation Heifers	High Yielding	Mid Yielding/Lactation	Late Lactation	Dry Cows	Close-Up
Dry matter	G	19,365	22,418	25,172	20,214	19,184	11,185	11,231
Dry matter from roughages	g	10,829	12,802	13,517	12,969	12,498	10,869	8304
% roughages	%	56	57	54	64	65	-	-
% dry matter	%	45.3	45.3	45.4	47.2	49.1	40.9	45.6
Crude fibre	g	2492	2934	3096	3123	3224	2868	2095
NEL/kg DM	MJ	7.18	7.14	7.21	6.67	6.44	5.55	6.45
Predicted milk from NEL	L	31.5	37.9	46.6	30.2	24.2	-	-
Predicted milk from protein	L	30.8	37.2	43.4	29.7	25.9	-	-
Predicted milk from nXP	L	31.9	38.4	42.3	29	23.8	-	-
Crude protein (CP) in DM	%	16.5	16.7	16.5	15.2	14.7	12.7	13.3
nXP in DM	%	15.7	15.9	15.9	14.5	14.1	12.3	13.7
% UDP per kg CP	%	27	27	26.2	18.6	18.4	-	-
Ruminal Nitrogen Balance (RNB)	g	24	30	27	21	20	8	-6
% sugar per kg DM	%	6.2	6.3	6.4	5.4	4.5	5	3.9
% starch per kg DM	%	16.1	16.3	17.6	20	19.8	5.5	14.7
% starch and sugar per kg DM	%	22.4	22.6	24	25.5	24.3	10.5	18.6
% crude fibre in DM	%	16.2	16.4	15.9	17.9	19.4	-	-
% fat in DM	%	4.4	4.5	4.4	2.7	2.6	2.6	2.8
Calcium	g	134.6	159	175	123.2	128.5	99	100.9
Phosphorous	g	75.7	89.1	94.2	61.7	55.9	27	36.8
Sodium	g	69.1	81.4	76.3	49	56.1	71.7	32.8
Magnesium	g	47.1	55.5	59.4	47.8	47.2	33.2	31.3
Potassium per kg DM	g	13.3	13.4	13.2	11.7	10	12.2	11.8
Chloride per kg DM	g	7.2	7.3	6.9	9	9.7	14.1	8.6
Sulphur per kg DM	g	3	3	3	2.4	2.4	2	2.4
DCAD per kg DM	meq	108	108	89	1	-41	66	37
Calcium:Phosphorous		1.78	1.78	1.86	2	2.3	3.67	2.74
Potassium:Sodium		3.72	3.69	4.36	4.82	3.41	1.91	4.04
Vitamine A	I.E.	128,700	152,460	151,200	148,500	148,500	100,000	100,000
Vitamine D	I.E.	18,590	22,022	21,840	21,450	21,450	25,000	25,000
Vitamine E	mg	501	593	588	578	578	625	625
Copper per kg DM	mg	16	16	15	18	18	18	17
Magnesium per kg DM	mg	68	70	65	78	85	93	87
Iodine per kg DM	mg	0.84	0.86	0.77	0.92	0.98	0.99	0.98
Selenium per kg DM	mg	0.45	0.46	0.42	0.49	0.52	0.49	0.51
Zinc per kg DM	mg	-	-	-	-	-	115	111
Cobalt per kg DM	mg	0.29	0.3	0.28	0.33	0.36	0.32	0.29

). The comparatively relatively high DCAD values in the dry and close-up cows were 66 and 37 mEq/kg, with a concomitant medium supply of calcium of 99 and 101 g per cow and day (8.9 and 9.0 g/kg DM). This unusual change from a negative DCAD in the late-lactation cows to a low but positive DCAD in the dry cows was seen as critical, as the consequences of these metabolic changes, especially for the calcium metabolism around calving, are difficult to appraise [56,57]. The reason for the low DCAD of the TMR was the low DCAD values of the grass silages fed at the time, which was due to the high concentrations of minerals, especially chloride (analyses only available for one of the two grass silages fed (Table A5): 20.2 g/kg DM chloride and a DCAD of −192 meq/kg DM, respectively). Furthermore, comparing the calculated rations and the results of silage sample analysis (of two grass silages and one corn silage), a large discrepancy (between 3 and 5 percentage points) between the % DM assessed and that used for calculation was revealed.

2.2.5. Disease Incidence

Diseases were diagnosed by either the veterinarian or the herd manager himself. Claw disorders were diagnosed by the claw trimmers. Diagnoses were recorded by the herd manager using the herd management software HerdeW (dsp Agrosoft GmbH, Ketzin, Germany), and the respective incidences are shown in Figure 1. Striking is the high number of lameness cases/treatments and the high incidence of metabolic, reproductive and digestive disorders, represented by 49 (9.8%) diagnosed cases of retained placentas (RP), 187 (37,4%) cases of endometritis, 39 (7.8%) cases of milk fever (including non-downer cows), and 26 (5.2%) cases of a displaced abomasum (DA) per 500 animals in one year [21,22,59].

The documented disease incidence remained relatively constant over the preceding three years, except for the incidence of metabolic and digestive disorders, which increased from 37, 36, to 58 and 31, 49 to 75 cases per year, respectively, with a constant herd size of approximately 500 cows. Furthermore, the local veterinary reported that, in his observation, the metabolic diseases mainly occurred not around calving but when the cows were between one and three weeks of lactation and located in the fresh cow pen.

2.2.6. Metabolic Profile

Pooled blood and urine samples were analysed to generate a metabolic profile for the herd (the method is described in [60,61,62]; details are in

Table A7. Clinical examination and scoring.

Group	No. Animals	Lameness (No. of Animals Per Grade)						No. Scored for Lameness *	Hock Lesions (Mean)	BCS			Rumen		Rectal T° (Mean)
		1	2	3	4	5	6			Mean	Min	Max	Filling (Mean)	Layering (Mean)
dry cows (dry)	10	0	5	4	1	0	0	10	2.4	3.38	2.25	5.00	2.5	2.6	38.5
close-up (cl-up)	10	3	3	3	1	0	0	10	2.9	3.33	2.25	4.75	2.4	2.2	38.8
colostral phase (col)	7	1	2	1	2	0	0	6	3.0	3.20	2.00	4.00	1.6	1.4	38.8
fresh cows (fresh)	10	2	8	0	0	0	0	10	2.9	2.70	2.00	3.50	1.7	2.0	38.9
high yielding (high)	10	2	6	2	0	0	0	10	2.7	2.67	2.25	3.50	2.4	2.3	38.6

* Lameness scoring was not always possible due to practical reasons. Lameness score [54]: 1: normal; 2: uneven gait, possibly with shorter steps—not possible to assign the lameness to a limb; 3: mild lameness, assignable to a limb; 4: lameness prominent, assignable to a limb; 5: lameness very prominent, only puts weight on the affected limb during a short moment; 6: extreme lameness—does not put weight on the affected limb. Hock lesions according to [44] were as follows: 1: no alterations, no lameness; 2: hairless patches, no lameness; 3: hyperkeratosis and/or swelling of the bursa without inflammation, no lameness; 4: profound perforating skin lesions, inflammation such as phlegmonous swelling, minor lameness; 5: the same as 4 with an affected joint, medium to severe lameness. BCS = body condition score [49]. Rumen fill/stratification was assessed according to [91]: 0: poor; 1: moderate; 2: good; 3: very good.

,

Table A8. Blood variables.

Group	No. AnimaLs	AST (U/L)	BHB (mmoL/L)	BiLi (µmoL/L)	Ca (mmoL/L)	CK (U/L)	CL (mmoL/L)	Crea (µmoL/L)	Fe (µmoL/L)	FFS (µmoL/L)	GGT (U/L)
		<80	<0.6–0.7	<5.3	2.3–2.8	<200	95–110	55–155	13–33	*	<50
dry	10	62.3	0.64	1.2	2.42	215	101.3	69	26.0	75	22.4
cL-up	10	70.7	0.67	0.9	2.40	254	103.2	80	31.7	59	26.4
coL	7	171.1	0.89	7.0	2.17	543	99.1	74	18.1	635	24.1
fresh	10	93.2	1.15	3.4	2.42	129	97.1	70	20.5	1000	25.9
high	10	75.4	0.73	0.8	2.49	152	96.8	56	26.1	114	31.8
Group	No. AnimaLs	K (mmoL/L)	Mg (mmoL/L)	Na (mmoL/L)	Phos (mmoL/L)	TP (g/L)	Urea (mmoL/L)	Se (µg/L)	Cu (µmoL/L)	Vit. A (mg/L)	Vit. E (mg/L)
		3.5–4.5	0.9–1.32	135–157	1.6–2.3	60–80	3.3–5.0	31.6–69.5	8.0–32.5	0.20–0.40	3.0–10.0
dry	10	4.50	0.90	135	2.03	74.7	3.01	49.2	11.6	0.23	5.7
cL-up	10	4.59	0.89	142	2.05	73.1	3.81	60.9	14.3	0.26	4.4
coL	7	4.73	0.85	137	1.71	67.4	3.93	75.4	18.3	0.15	3.2
fresh	10	4.73	1.05	135	1.73	76.0	2.13	63.9	13.1	0.2	5
high	10	4.66	1.02	133	1.67	78.7	3.06	63.2	15.4	0.29	8.1

AST = aspartat-aminotransferase; BHB = beta-hydroxybutyrate. * antepartum < 150; 1st week postpartum < 620; >1 week postpartum < 340. Bili = bilirubin; Ca = calcium; CK = creatinkinase; Cl = chloride; Crea = creatinine; Fe = iron; FFS = free fatty acids; GGT = gamma-glutamyltransferase; K = potassium; Mg = magnesium; Na = sodium; P = phosphorus; TP = total protein; Se = selenium; Cu = copper. Reference values of the Laboratory of Large Animal Clinics, Faculty of Veterinary Medicine, University of Leipzig, chosen according to [63].

and

Table A9. Urine variables.

Group	No. AnimaLs	Ca (mmoL/L)	CL (mmoL/L)	Crea (mmoL/L)	K (mmoL/L)	Mg (mmoL/L)	Na (mmoL/L)	Phos (mmol/L)
		<2.5	40–160	2.2–7	150–300	3.7–16	>8.2	0.1–3.3
dry	10	3.80	242.1	10.13	330.6	15.0	60	0.24
cL-up	10	2.78	144.9	10.31	286.8	12.9	58	0.24
coL	7	1.60	59.2	7.73	196.2	7.0	55	1.40
fresh	10	0.06	59.2	4.49	179.6	4.6	103	n.n.
high	10	0.76	111.3	6.01	266.0	15.8	116	1.22
Group	No. AnimaLs	pH	Bases (mmoL/L)	Acids (mmoL/L)	NH4+(mmoL/L)	Fract. NABE (mmoL/L)	BAQ
		7.0–8.4	150–250	50–100	<10	80–220	1.5–4.5
dry	10	8.11	143	75	5.8	62.2	1.8
cL-up	10	8.40	187	80	5.6	101.4	2.2
coL	7	8.46	191	59	6.3	125.7	2.9
fresh	10	8.50	272	75	6.8	190.2	3.3
high	10	8.53	235	46	4.3	184.7	4.7

Ca = calcium; Cl = chloride; Crea = creatinine; K = potassium; Mg = magnesium; Na = sodium; P = phosphorus; NH₄⁺ = ammonium; fract. NABE = fractional net acid-base excretion; BAR = bases-acid-ratio. Reference values of the Laboratory of Large Animal Clinics, Faculty of Veterinary Medicine, University of Leipzig, chosen according to [63].

[60,61]). Ten samples from each of the five groups were used and included cows from the dry, close-up, colostral-phase, fresh and high-producing groups. The cows were selected randomly according to their lactation stage and underwent a short clinical exam. Only healthy cows were chosen; exceptions were made for mild to moderate lameness, due to the high lameness prevalence in the herd. The clinical examination of the sampled animals (Table A7) showed a low rumen fill and insufficient stratification in colostral and fresh cows, a strong decrease in BCS between the close-up and fresh cow group (from an average of 3.33 to 2.70), and a high number of lame cows in the dry cow and close-up groups. The blood serum samples, the following characteristics were obvious [63]:

• The level of postpartum lipomobilisation was too high. There were high BHB (1.15 mmol/L in fresh cow group) and FFS (635 and 1000 µmol/L in colostral and fresh cow group) concentrations, resulting in increased metabolic strain on the liver and, consequently, liver damage, reflected by increases in AST (171 and 93 U/L in the colostral-phase and fresh cow groups) and bilirubin (7.0 µmol/L in the colostral phase).
• Postpartum subclinical hypocalcaemia was observed in the colostral group (2.17 mmol/L).
• The antepartum period shown increased amounts of creatine kinase (slightly, possibly due to overcrowding and lameness).
• The postpartum period exhibited an increased amount of potassium (possibly due to the high potassium concentrations in the rations).

In the urine sample, the following aspects were noted:

• During the antepartum period, there was an increase in calcium, chloride, and potassium, reflecting the high mineral load in the rations fed, as well as antepartum calcium excretion
• The antepartum period also saw high levels of creatinine, possibly indicating an insufficient water supply.
• The close-up group exhibited a relatively high net acid–base excretion and acid–base quotient, reflecting the relatively high DCAD diets fed to this group. The lowest base-acid–ratio (BAR) was observed in the dry cow group.

2.3. List of Initial Problems

The interrelations between the results from the analysis of the environment, animal-related indicators and the risk factors identified are summarized in Figure 2. The aggregated list of final problems, mainly regarding metabolic problems, consists of the following:

• Housing: Overcrowding and insufficient bedding hygiene in the transition cow facility [64], due to the following:

  -

  Insufficient facility design;

  -

  Non-continuous calving patterns;

  -

  A high number of preterm dried-off cows;

  -

  Insufficient implementation of the cleaning routines.

• Feeding: Problematic DCAD [56,57,58], due to the following:

  -

  Low DCAD in grass silage.

  -

  Ration composition.

  -

  Insufficient water supply [65], due to the following:

  ○

  A lack of sufficient water supply (volume).

  ○

  The high mineral loads in the rations.

• Animal health: High lameness prevalence [66].
• Management: Insufficient timely detection and treatment of animals at risk [26,67].

These risk factors lead to an increase in metabolic disorders, such as postpartum (sub)clinical hypocalcaemia and excessive lipomobilisation, and their clinical sequelae, e.g., downer cows, displaced abomasum and reproductive disorders (RP, metritis and subsequently endometritis) [9,10,68]. The cases of indigestion are indicative of cases of displaced abomasa that were detected during the transition phase (a similar case is described in [69]).

This summary illustrates that the transition cow area forms a severe risk factor (bottleneck) on this farm, promoting a vicious cycle: the disorders acquired in the transition phase led to a poor health status, for which the cows were not able to compensate in the lactating phase before re-entering the transition cow facility for the next cycle. The problems present then became aggravated in the next transition phase. This scenario may be one reason for the increase in diagnosed metabolic, reproductive, and digestive diseases in the last three years (the facility was only running at a capacity of 500 cows for three years (see above)).

2.4. Problem Solution and Follow-Up

2.4.1. Feeding

As a short-term solution for the unfavourable DCAD in the rations of the lactating groups, the local nutritionist suggested to add bicarbonate, which was implemented from February 2019 onwards (a timeline of interventions is given in Figure 3). Before and after the implementation of the ration changes, blood and urine samples were collected from the late-lactation and dry cows to obtain insights into the metabolic consequences in these target groups

Table A10. Clinical examination and scoring.

Group *	No. Animals	Lameness (No. of Animals Per Grade)						No. Scored for Lameness	Hock Lesions (Mean)	BCS			Rumen		Rectal T (Mean)
		1	2	3	4	5	6			Mean	Min	Max	Filling (Mean)	Layering (Mean)
late (1)	10	4	4	1	1	0	0	10	2.7	3.06	2.25	4.50	2.6	2.8	38.4
late (2)	10	1	5	4	0	0	0	10	3.1	3.75	3.25	4.50	2.7	2.7	39.3
dry (1)	10	2	8	2	1	0	0	10	2.6	3.53	2.00	5.00	2.9	2.8	38.5
dry (2)	10	2	7	1	0	0	0	10	2.6	3.50	2.50	4.50	2.4	2.6	39.1

* late = late lactation animals; dry = dry cows. (1) = sampled February 2019; (2) = sampled June 2019. Lameness score [54]: 1: normal; 2: uneven gait, possibly with shorter steps—not possible to assign the lameness to a limb; 3: mild lameness, assignable to a limb; 4: lameness prominent, assignable to a limb; 5: lameness very prominent, only puts weight on the affected limb during a short moment; 6: extreme lameness—does not put weight on the affected limb. Hock lesions according to [44]: 1: no alterations, no lameness; 2: hairless patches, no lameness; 3: hyperkeratosis and/or swelling of the bursa without inflammation, no lameness; 4: profound perforating skin lesions, inflammation: phlegmonous swelling, minor lameness; 5: the same as 4 with a joint affected, medium to severe lameness. BCS = body condition score [49]. Rumen fill/stratification was assessed according to [91]: 0: poor; 1: moderate; 2: good; 3: very good.

,

Table A11. Blood variables.

Group *	No. Animals	AST (U/L)	BHB (mmoL/L)	BiLi (µmoL/L)	Ca (mmoL/L)	CK (U/L)	CL (mmoL/L)	Crea (µmoL/L)	Fe (µmoL/L)	FFS (µmoL/L)	GGT (U/L)
		<80	<0.6–0.7	<5.3	2.3–2.8	<200	95–110	55–155	13–33	*	<50
late (1)	10	122.7	0.89	0.2	2.46	320	95.5	71	35.6	130	24.3
late (2)	10	74.3	1.19	0.4	2.45	118	94.8	84	31.7	90	29.0
dry (1)	10	83.5	0.91	0.3	2.30	420	95.8	74	29.7	106	18.4
dry (2)	10	71.3	0.62	1.1	2.37	223	96.7	95	29.1	186	25.2
Group *	No. Animals	K (mmoL/L)	Mg (mmoL/L)	Na (mmoL/L)	Phos (mmoL/L)	TP (g/L)	Urea (mmoL/L)	Se (µg/L)	Cu (µmoL/L)	Vit. A (mg/L)	Vit. E (mg/L)
		3.5–4.5	0.9–1.32	135–157	1.6–2.3	60–80	3.3–5.0	31.6–69.5	8.0 –32.5	0.20–0.40	3.0–10.0
late (1)	10	4.21	0.94	136	1.68	73.8	3.65	64.4	10.4	0.27	6.8
late (2)	10	4.04	0.95	139	1.81	77.3	4.19	59.8	11.2	0.25	5.3
dry (1)	10	4.30	0.85	136	1.85	72.4	2.88	51	8.5	0.22	5.9
dry (2)	10	4.52	0.98	135	1.85	75.4	3.44	54.1	9.3	0.22	5.2

* late = late lactation animals; dry = dry cows. (1) = sampled February 2019; (2) = sampled June 2019. AST = aspartat-aminotransferase; BHB = beta-hydroxybutyrate. * antepartum < 150; 1st week postpartum < 620; >1 week postpartum < 340. Bili = bilirubin; Ca = calcium; CK = creatinkinase; Cl = chloride; Crea = creatinine; Fe = iron; FFS = free fatty acids; GGT = gamma-glutamyltransferase; K = potassium; Mg = magnesium; Na = sodium; P = phosphorus; TP = total protein; Se = selenium; Cu = copper. Reference values of the Laboratory of Large Animal Clinics, Faculty of Veterinary Medicine, University of Leipzig, chosen according to [63].

and

Table A12. Urine variables.

Group *	No. Animals	Ca (mmoL/L)	CL (mmoL/L)	Crea (mmoL/L)	K (mmoL/L)	Mg (mmoL/L)	Na (mmoL/L)	Phos (mmol/L)
		<2.5	40–160	2.2–7	150–300	3.7–16	> 8.2	0.1-3.3
late (1)	7	26.0	209	5.9	162	11.0	78	0.8
late (2)	10	37.2	99	10.0	128	0.60	107	2.4
dry (1)	10	2.8	205	7.7	132	11.5	112	0.1
dry (2)	10	6.8	142	10.2	137	18.5	57	2.4
Group *	No. Animals	pH	bases (mmoL/L)	acids (mmoL/L)	NH4+ (mmoL/L)	fract. NABE (mmoL/L)	BAR
		7.0–8.4	150–250	50–100	<10	80–220	1.5–4.5
late (1)	7	8.52	142	60	6.7	75.3	2.1
late (2)	10	8.58	234	100	10.6	123.4	2.1
dry (1)	10	8.47	132	65	4.4	62.6	1.9
dry (2)	10	8.70	194	70	8.0	116.0	2.5

* late = late-lactation animals; dry = dry cows. (1) = sampled February 2019; (2) = sampled June 2019. Ca = calcium; Cl = chloride; Crea = creatinine; K = potassium; Mg = magnesium; Na = sodium; P = phosphorus; NH₄⁺ = ammonium, fract. NABE = fractional net acid-base excretion; BAR = bases-acid-ratio. Reference values of the Laboratory of Large Animal Clinics, Faculty of Veterinary Medicine, University of Leipzig, chosen according to [63].

. As expected, we observed an increase in the net acid–base excretion (NABE) to physiological levels between the two samplings. Furthermore, many of the grassland fields of the farm are on high moor soils, predisposing the grass silages to having low DCAD values [70]. As an option for future harvests, the application of more suitable fertilizers for these sorts of soils, for example potassium-sulphate- instead of chloride-containing fertilizers were suggested [71].

Concerning the rations of the close-up dry cows, we suggested to either choose a low-calcium/medium-DCAD or high-calcium/low-DCAD strategy [72,73], as the situation was somewhere in between these conditions. We thereafter aimed for a medium–low-to-normal DCAD (~150 mEq/kg) and a low calcium concentration in the close-up ration, with the farm manager collecting TMR samples on a regular basis to control for consistency and possible deviations. The farm, however, experienced recurrent periods of milk fever cases (non-downer cows included; annual no. of cases from 2018 to 2021: 39/34/34/40). To exclude other differential diagnoses, blood samples were collected from three cows by the local veterinarian, confirming severe hypocalcaemia (serum, 0.8, 0.7 and 1.1 mmol/L calcium). The TMR samples showed that implementing any sort of continuous DCAD and Ca level in the dry cow ration was challenging due to temporal changes in mineral concentrations in the grass silage from different silo bunkers; the farm manager and nutritionist therefore decided to opt for a corn silage-based and anionic salt acidified close-up ration, without any grass silage from March 2022 onwards.

Overall, it was advised to focus on feeding control regarding the loading precision of the feed mixer and regular silage DM estimation, as well as the corresponding adjustments to rations. Furthermore, the importance of promoting the DMI of cows by regular feed pushing and allowing for sufficient refusals was highlighted. It was recommended to monitor the DMI of all groups on a regular basis. During this project the DMI was recorded monthly from January 2019 onwards, using the loading protocols for the feed mixer and via the bi-weekly DM determination of the silages by the farm manager. In all groups, a potential for increase was observed, with the dry cows (constantly including approx. 30% springing heifers), close-up and fresh cows especially showing DMIs that were too low (

Table 2. Dry matter intake of the cows of the different groups in a 500-cow dairy farm (kg DM/cow/d).

	Dry Cows	Close-Up	Fresh Cows	First Lactation Heifers	High- Yielding 1	High- Yielding 2	Mid Yielding/Lactation
Jan 2019—Jun 2019	10.8	9.8	17.3	20.6	23.9	23.9	17.9
Jul 2019—Dec 2021	12.4	16.7	19.3	20.6	24.2	24.0	19.3
Jan 2022—Jun 2022	13.4	18.7	21.3	21.6	24.8	25.5	22.5

[74,75,76]). In the next six months, a substantial increase in DMI in the close-up group was observed (July–December 2019: 15.2 kg DM/cow/d), this most likely being attributable to more professional feeding and grouping management. In the following 30 months, the DMI remained constant and was slightly higher in all groups. For the first half of 2022, another increase in the DMI in all groups was observed, most likely due to good feed quality (see Section 2.4.3).

2.4.2. Disease Monitoring and Animal Health Management Protocols

We suggested implementing fresh cow control routines on a daily basis (principles explained in [21,26,77]) to guarantee the timely detection and treatment of diseased animals and to monitor and anticipate the risk factors in transition cow health. Despite not having the possibility to fixate cows for routine controls, the herd manager planned to focus on the timely detection of diseased animals and animals at risk of developing transition cow diseases, as well as their timely referral to the local veterinarian or clinic for appropriate treatment. His preventative work was mirrored by a substantial decrease in the number of cows with a DA case (2018–2022: 26, 10, 6, 8, 2) and by the referral of 53 cows for treatment to the clinic between January 2018 and December 2021, of which 78% could be sent home after treatment in a productive state. He furthermore reported that, in his experience, his focus on preventing overcrowding in the close-up and fresh cow pens was an important measure in this regard as well, as supported by the good DMI in these groups (see above) as well as the decrease in lipomobilisation shown in the annual metabolic profile of the fresh cow group (serum-free fatty acids from 1000 (2018) to 332 (2019), 360 (2020), and 654 (2021) µmol/L).

The lameness problem was addressed by training personnel in lameness detection and via encouraging regular visits to treat complicated cases, as well as by training the local veterinarian in surgical orthopaedic procedures. In 2022, a state-of-the-art treatment area with a conventional trimming chute for routine trimming and a tilt table chute for orthopaedic procedures was built to support this process.

2.4.3. Housing and Management

As a short-term solution to decreasing the stocking rate in the transition cow area, we suggested relocating the far-off dry cows to the young stock facility, where barns with deep-bedded packs were not in use. This was, however, not considered feasible by the farm manager due to the necessity to transport the animals (approximately 6 km).

Increasing the water supply in the dry cow and calving barn was not possible, as all potential locations for placing water troughs had already been utilized.

Furthermore, the herd manager communicated that he had put a focus on enforcing better cleaning routines for the bedding and on evening out the non-continuous calving pattern by decreasing insemination peaks (e.g., by only inseminating a certain amount of heifers and cows in a time period). Also, he wanted to anticipate high stocking densities in the dry cow pen by careful consideration of the necessity of preterm drying-off cows.

The total number of cows on the farm increased in the following years by 5.2% (with a total of 530 cows on 1 May 2021) and decreased thereafter again to 517 cows (31 December 2022). The farm experienced several summers (2018, 2019, 2020 and 2022 [78,79]) of extreme weather conditions with substantial heat stress on the cows, exacerbated by old and insufficiently ventilated barns. The heat and drought caused the silage harvest to be of low quality. This presumably caused a decrease in the milk production of the herd (2018–2021: 32.2 kg, 30.8 kg, 30.8 kg, 31.7 kg per cow and day; 12-month test-day herd average of lactating cows), an increased culling rate (2018–2022: 38.6%, 38.3%, 33.9%, 33.6%, 33.2%) and a decrease in lifetime production (2018–2022: 33,166 kg, 31,321 kg, 27,874 kg, 27,671 kg, 29,891 kg). In 2021, the better weather conditions allowed for better silage quality, and corresponding positive alterations in the milk production were observed in 2022, with a 33.4 kg/cow/d 12-month test-day average.

The extreme weather conditions also hampered the efforts of the herd manager to even out the non-continuous calving pattern (Figure A2). Heat stress causes decreased fertility during summer months and counteracts any temporally even distribution of conceptions [80].

The farm manager decided to tackle the various problems in the transition cow area via the construction of a new facility to guarantee sufficient space, comfort, ventilation, water supply and the possibility to perform routine animal controls and treatments. Different meetings were held in which aspects of the possible allocation of the different production/lactation groups and the design of a new facility were discussed. By the end of 2019, the building application was approved, but due to the tense economic market situation, the plans were postponed by several months. The first step in building the new transition cow facility started 4 years after the initial visit by extending the dry cow barn.

3. Discussion

This case shows how multi-layered and complex transition cow diseases are, not only on the level of the influencing factors, but also when it comes to finding appropriate solutions [10,21,36,81]. Comparisons of the disease incidences in the initial assessment with those in the literature show that the incidences of metabolic and digestive disorders were in the range of alarm rates found in relevant reviews of comparable production systems [12,26]. Caixeta and Omontese [26], for example, stated an alarm rate ≥5% for clinical hypocalcaemia and ≥6% for DA. We see especially the latter critically, as practice shows that DA are in many cases underdiagnosed. This has for example been described in a case report from a 1200-cow dairy farm comparable to the farm we worked on [69]. This was anticipated in our case, and we highlighted this to the herd manager and local veterinarian after the first assessment. Furthermore, the successful treatment of DA may be a challenge [38,69]. This was also the situation in the present case, this being the reason for the cows being transferred to a clinic for treatment. This aspect, as well as the successful solution of this specific problem on this farm, is elaborately detailed and published in a separate case report, along with an economic evaluation [38].

In most health-related problems, knowledge and advice from different specialists/experts of different disciplines need to be considered together to identify risk factors as well as to elaborate suitable solutions [21]. In many cases, the know-how of veterinarians, nutritionists, and herd managers, as well as that of crop farmers, structural engineers, and agricultural economists in cases, is needed. In a practical setting, resources, such as available specialists, the time needed for consultation, problem identification resources and formulation concepts for the solution of problems, are not always given [23].

In the present case, even though a team of different specialists formulated problem solutions, of which most were readily applicable, an immediate change in the animal health situation was not observed at all levels. This is in line with the literature and the authors’ personal experience, which indicated that farmers/herd managers are, in many cases, aware of the risk factors as well as possible solutions, but practical implementation is a longer-lasting process [23,82]. This can be ascribed to different aspects, which are detailed below.

In larger-scaled dairy farms in particular, a major challenge is the organisation of workflows and employees, as well as the latter’s training [83,84,85]. The education of employees and the implementation of routines is time consuming. The presence of controlling and feedback mechanisms is of major importance [83]. An analysis the authors conducted on 10 project farms shows that farms where the herd manager spends more time on control are more successful [86]. The proficiency of the herd manager and his/her employees in personnel management is essential for a successful process management [87]. This needs to be taken into account when problem solutions are created, as for successful consulting, measures need to be formulated in a way that not only leads them to be accepted by the herd manager but also makes them likely to be implemented by the workers [84,85]. The disagreement of the herd manager with the authors’ suggestion to decrease overstocking in the dry cow pen by transporting them to a different location, due to the feasibility regarding the daily routines, is a good negative example of how measures may not always be formulated in a way that leads to their acceptance and implementation. In the present case, the proficiency of the personnel was not considered a risk factor, as the farm and herd manager were considered experienced, skilled and open to new suggestions. This was also mirrored by the relatively fast implementation of practical suggestions in terms of feeding and transition cow control, as well as by the corresponding results. This also shows that suboptimal housing structures may be compensated for with additional expenses for elaborate animal husbandry routines, animal monitoring and metaphylactic treatment [82].

On a longer-term basis, farms should aim to overcome structural bottlenecks to free up labour resources [23,37,41]. Also, in the present farm, given that the structural conditions constituted major risk factors for cow comfort, the farm management opted for re-building parts of the facility. Such measures need to be both practically and financially well planned and due to other, different constraints (e.g., receiving a building permit; finding an appropriate construction company); their implementation, such as in the present case, most often takes several months to years.

A third constraint on the implementation and success of measures is the subjection of dairy production systems to climatic and other biological dynamic factors. In the present case, the impact of the emerging climate change [78] interfered with several aspects of measures taken, such as the evening out of the non-homogenous calving pattern, and heavily impacted the feed quality and production level of the herd. The imminent increase in days with heat stress expected in the future demands a rethinking and restructuring of many dairy farms [88,89].

However, major challenges, e.g., the presently tense economic situation, finding skilled labour and the politically uncertain situation regarding regulations [23,89], make it even harder for dairy farmers to deliberately take the risk of investment. The present case shows that if animal health and welfare, as well as profitability, in the dairy sector should be increased, while keeping pace with vast structural changes, major investments in education, workplace attractiveness and product pricing are a necessity.

The case also shows that problems like the ones presented are not solved in a single visit and need more time. Many interrelated factors and need to be prioritized, and specialists (nutritionists, local and consulting veterinarians, and farm managers) from different areas need to work continuously together. This is especially evident when combining the insights obtained from the detailed investigation into a single animal’s left DA case on this farm [38], regarding surgical methods and veterinary animal health routines, with the farm level analysis results presented in this manuscript, which underline the necessity of a holistic approach. To enforce the necessary interdisciplinary and multi-level work, local and national cooperative structures, such as governmental and educational training and consulting centres, need to be implemented and enforced, and interaction between them needs to be encouraged.

In practice, such elaborate assessments as shown in this report are mostly not possible due to practical, labour, time and financial constraints. Depending on the focus and the results of an initial screening of the situation, certain key indicators (e.g., production indicators, scoring of cows and the environment) can be chosen for primary analyses, and researchers should follow-up on the success of the measures taken. The aim of this case report was to show the possible portfolio of analyses that can be carried out, encouraging practitioners as well as persons in teaching to implement aspects of it. The depicted set of analysis methods is, however, not complete. Additionally, complete clinical examinations of the affected cows conducted by the investigating team, as well as necropsies, analyses of sensor data, video analyses or the monitoring of cow behaviour using sensors [33], could have been included. Furthermore, we did not apply the approach of depicting the economic potential represented by an increase in transition cow health, an aspect that has a high potential in motivating farmers to implement changes, as described in a case report by Middleton and Overton [90].

As this is a single-case (one-farm) observation, its representativeness and the observer bias possibly present must be seen as critical factors, especially as there are few similar cases to compare this one to. This, however, highlights that there is an urgent need for the detailed elaboration and publication of such practical examples, encouraging detailed work on problem analyses and interdisciplinary work in practice.

4. Conclusions

The findings of this case report underscore the complexity of managing metabolic disorders in transition dairy cows and the necessity of a multidisciplinary approach. While short-term nutritional and management interventions can yield immediate benefits, structural and environmental factors require long-term planning and investment. The success of such measures depends on effective collaboration among veterinarians, nutritionists, and farm managers, as well as the ability to adapt to external challenges such as climate change and economic pressures. This case highlights the need for continuous monitoring, flexible problem-solving, and investment in farm infrastructure to enhance both animal health and overall farm productivity. This case study may be used as a practical model for farms and consultants facing similar transition-related issues.

5. Practical Suggestions for Practice

Practitioners should adopt a holistic and interdisciplinary approach when addressing metabolic disorders in transition dairy cows. Key actions include the following:

• Implementation of structured fresh cow checks to ensure early detection and treatment.
• Thorough evaluation of DCAD and calcium levels in dry cow diets, with consistent ration analysis to prevent hypocalcaemia.
• Monitoring of dry matter intake (DMI) and adjusting feeding strategies to encourage adequate intake.
• Adequate clinical examination and blood analysis in downer cows to verify the cause of disease.
• Metabolic profiling to monitor subclinical imbalances, particularly around calving, especially in herds with an increased risk of experiencing transition cow problems.
• Avoidance of overcrowding in close-up and fresh cow pens by managing calving distribution and dry-off timing.
• Improvements in water access and cubicle comfort, especially in high-risk pens.
• Engagement of all stakeholders—including veterinarians, nutritionists, and farm staff—in regular reviews of herd health data and housing conditions.