Revista de la Facultad de Ciencias
Agrarias. Universidad Nacional de Cuyo. En prensa. ISSN (en línea) 1853-8665.
Original article
Transition
management and dairy cow performance: insights from dairy farms in Argentina
Manejo
de la Transición y Desempeño de las Vacas Lecheras: Perspectivas de
Establecimientos en Argentina
1Universidad Nacional de Río Cuarto (UNRC). Facultad de Agronomía
y Veterinaria (FAV). Ruta 36 km 601. Río Cuarto. C. P. 5800. Córdoba.
Argentina.
2Universidad Nacional de Villa María (UNVM). Instituto Académico
Pedagógico de Ciencias Sociales (IAPCBA). Arturo Jauretche 1555. Villa María.
C. P. 5248. Córdoba. Argentina.
3Instituto de Formación e Investigación en Nutrición Animal
(IFINA). Zona rural. Las Higueras. C. P. 5805. Córdoba. Argentina.
4Universidad Nacional de Río Cuarto (UNRC) Instituto para el
Desarrollo Agroindustrial y de la Salud CONICET. Ruta 36 km 601. Río Cuarto.
Córdoba. ARCP 5800. Argentina
*mpturiello@ayv.unrc.edu.ar
Abstract
This study aims to
describe nutritional strategies, management practices, and health events in
transitioning cows on 28 commercial dairy farms in Argentina, selected based on
their association with graduate students. During 2022, we surveyed herd management,
feeding, health events, and milk yield, based on local research and validated
recommendations. Most cows were housed in dry lots, with 97% of farms having
far-off and close-up groups, but only half had a fresh group. The average dry
period was 59±11.4 days. The mortality and culling rate were 1.2% and 1.4%,
respectively. The herd incidence rates were 1.8% for milk fever, 0.3% for
clinical mastitis, 2.7% for metritis, and 1.4% for retained placenta. All farms
used anionic diets and monitored urinary pH, with corn silage included in all
diets, and soybean meal/expeller as the main protein source. Lactating cows
produced an average of 33.8±10.43 kg of milk on the first test day and
38.2±10.05 kg at peak. Primiparous cows produced 75% of the milk of mature cows.
Bulk tank milk averaged 3.9±0.19% fat and 3.5±0.07% CP. This report highlights
strengths and areas for improvement in Argentina’s dairy transition programs.
Keywords: dry cow, prefresh,
dairy cow performance, health and nutrition
Resumen
El objetivo del
estudio fue describir estrategias nutricionales y de manejo, eventos de salud y
producción de vacas en transición en 28 establecimientos argentinos
seleccionados por su vinculación con estudiantes de posgrado. Durante el año
2022 se relevaron aspectos de manejo, alimentación, salud y producción, según
recomendaciones validadas y estudios locales. La mayoría de las vacas se
alojaban en dry-lots y 97% tenían rodeos de seca y preparto, pero solo la mitad
tenía rodeo de vacas frescas. La duración del período seco fue de 59±11,4 días.
La mortalidad y descarte fueron del 1,2% y 1,4%, respectivamente. Las
incidencia de hipocalcemia, mastitis, metritis y placenta retenida fueron 1,8%,
0,3%, 2,7% y 1,4%, respectivamente. Los establecimientos utilizaban sales
aniónicas y monitoreaban pH urinario preparto; incluían silaje de maíz, y
harina o expeller de soja como fuente proteica. La producción promedió
33,8±10,43 kg/vaca/día al primer control lechero y alcanzó un pico promedio de
38,2±10,05 kg/vaca/d. Las vacas primíparas produjeron el 75% de las vacas
adultas. La leche de tanque presentó 3,9±0,19% de grasa y 3,5±0,07% de
proteína. Este informe resalta los puntos fuertes y áreas de mejora en los
programas de transición lechera en Argentina.
Palabras clave: vaca seca,
preparto, performance de vaca lechera, salud y nutrición
Originales: Recepción: 15/03/2025- Aceptación: 08/09/2025
Introduction
The transition
period in dairy cows spans from the last 3 weeks prepartum to the first 3 weeks
postpartum (10). This critical phase has
been emphasized as pivotal in the lactation cycle by Drackley
(1999), primarily due to its influence on health disorders, production
outcomes, and subsequent profitability. This latter author highlights several
essential aspects, including nutritional strategies to support dry matter
intake and metabolic adaptation, environmental comfort to reduce stress,
monitoring of body condition to avoid excessive reserve mobilization, and
timely detection of clinical and subclinical health issues.
Recent literature
has highlighted various aspects of transition cow management in commercial
settings. Heuwieser et al. (2010) surveyed
German farmers on fresh cow management practices, while Espadamala
et al. (2016) examined methods for identifying postpartum health
disorders in California dairy farms. Both studies underscored the challenge of
implementing specific and objective observation systems in fresh groups to
enhance transition cow care. More recently, Kerwin et
al. (2022) investigated the management and herd characteristics of the
transition period in freestall dairy herds in the northeastern United States.
Their findings highlighted the industry’s adherence to prevailing
recommendations from both academia and practical experience.
Effective
management and nutrition during the transition period aim to reduce metabolic
disorders, enhance milk yields, lower culling rates, and improve reproductive
performance throughout lactation (8).
However, while numerous dietary and management recommendations exist, their
implementation varies based on practical considerations (2). Furthermore, Kerwin et
al. (2023) noted that not all recommendations are equally adopted,
often due to financial constraints or insufficient research support.
Understanding the influence of nutritional and management factors on commercial
dairy farms can shed light on how these elements contribute to transition cow
success across diverse farm practices (15).
This study aims to
describe nutritional and management strategies, as well as the productive
performance and health events of transitioning cows in commercial dairy farms
in Argentina. By identifying areas for improvement within these transition
programs, this research seeks to enhance overall herd health and productivity.
In Argentina, there is limited available information on the nutritional and
management strategies applied during the transition period, making this type of
research essential for designing evidence-based interventions to improve animal
performance and farm profitability during this critical stage.
As has been highlighted for cow-calf systems, the systematic
characterization of management practices and the identification of areas for
improvement are key steps to increase efficiency and profitability in livestock
production (10).
Materials
and methods
Study
Design
A cohort of
graduate students specializing in bovine nutrition at the National University
of Villa Maria facilitated the selection of 28 dairy farms across the provinces
of Cordoba (19%), Santa Fe (50%), and Buenos Aires (31%), Argentina. These
farms primarily housed Holstein cows, averaging 470 milking cows each, with
herd sizes ranging from 180 to 1,200.
Farm visits
conducted in August involved interviews with farm owners or managers,
supplemented by observational assessments. The survey was developed based on
nutritional and management recommendations from the literature, expert
opinions, and insights gleaned from local studies (27,
29). It encompassed risk factors affecting milk yield and health
during the transition period, drawing on recent research (1, 6, 7). Data collection focused on health
events during the first 21 days in milk (DIM) and milk yield and quality
metrics from cows calved between April and May 2022 due to operational and
logistical limitations. Body condition scores in dry-off, close-up and fresh
(< 30 DIM) cows and ketonemia in fresh cows (3-14 DIM) were evaluated in a
stratified sample of cows based on group size: 20% of the cows in groups with
more than 60 cows, 12 cows in groups with 12 to 60 cows, or all cows in smaller
groups where the number was insufficient.
All animals
involved in this investigation were cared for in accordance with the
International Guiding Principles for Biomedical Research Involving Animals (CIOMS-ICLAS,
2012).
Survey
Structure
The survey
comprehensively addressed four main areas:
Herd Management:
This section focused on dry cow and fresh cow programs, including criteria for
grouping, frequency of management interventions, facilities, and cow comfort.
Consultants also assessed the duration of the dry period for cows calved
between April and May 2022. Body condition scores (BCS) were evaluated using a
1 to 5 scale (31) at different stages of
the transition period.
Feeds and Feeding
Management: Information regarding feed formulations for far-off, close-up, and
fresh cow diets was collected. The survey also gathered data on feed sample
frequency, feed bunk management practices, intake estimations, and monitoring
of urinary pH when formulating acidogenic diets in pre-fresh stages.
Health Events:
Defined health events included milk fever, retained placenta, mastitis, and
metritis as they are among the most common and impactful health disorders
during the transition period (2).
Diagnosis criteria were standardized, with milk fever diagnosed based on
symptoms and response to treatment, retained placenta noted if not expelled
within 12 hours postpartum, mastitis identified through mammary gland
inflammation or milk changes, and metritis detected via abnormal vaginal
discharge and clinical signs. Blood samples from the coccygeal vessels assessed
ketonemia, with hyperketonemia defined as blood BHB concentrations ≥1.2 mmol/L,
measured by the consultant the day of the visit using handheld devices
following manufacturer guidelines (23).
Milk Yield and
Quality: Data on milk yield during startup (10 to 30 days in milk, DIM) and
peak lactation (75 to 105 DIM) were obtained from individual cow records. Bulk
tank milk quality parameters, including fat and protein content, somatic cell
count (SCC), and colony-forming units (CFU), as reported primarily by industry
standards, were documented.
Data
Analysis
Descriptive statistics were employed to characterize general
management practices during the transition period across the surveyed farms.
Incidence rates of health events during early lactation were calculated as the
proportion of new cases relative to the total number of calvings in April and
May. Dietary composition, feeding management practices, and milk yield and
quality traits were analyzed using positional and dispersion statistics to
identify trends and variations across the surveyed farms.
Results
and discussion
A total of 28 dairy
farms across the provinces of Cordoba, Santa Fe, and Buenos Aires, Argentina,
were selected for the study based on the availability and willingness of
farmers to participate. The study encompassed all cows calved in these farms
during April and May 2022, totaling 3,267 animals (1,223 multiparous and 2,044
primiparous cows). The median of calvings per farm was 32 for multiparous cows
(range: 10 to 120) and 64 for primiparous cows (range: 12 to 204).
Herd
Management
Most cows (85.7% groups)
in the study were housed in dry-lots, the remaining groups were grazing.
Ninety-seven percent of the farms had separate far-off and close-up groups.
Yet, only half of them had fresh group, in line with observations reported by Heuwieser et al. (2010). Nearly all herds (27
out of 28) segregated far-off cows from close-up dry cows, with regrouping
occurring at varying frequencies: monthly (1 farm), bi-weekly (13 farms), and
weekly (13 farms). This two-group strategy during the dry period is commonly associated
with nutritional management practices, particularly the use of anionic diets in
the close-up group. While regrouping can affect feeding behavior and intake,
studies indicate minimal impact under favorable conditions of feed access and
resting areas (4, 26). Primiparous cows
were housed together with multiparous cows in most herds (n = 22) for more than
20 days; only 6 herds separated primiparous from multiparous cows in the
close-up period.
Regarding
facilities, most farms allocated far-off and close-up dry cows in dry-lots (21
and 26 farms, respectively), with the remainder on pasture. Dry-lots generally
provided adequate space without significant cost implications. They were in
good condition, with a low depth of mud and good access to feed bunks and
waterers, although it is highly dependent on rain events. Thirty-six percent of
the farms did not provide shade to their far-off cows, whereas 93% of the
close-up groups ensured shade provision. As demonstrated by Laporta et al. (2020), heat abatement provision
to dry cows is important to prevent milk losses in the subsequent lactation and
in the progeny.
A common practice
is to have fresh cow groups to identify sick cows (9),
considering that 30% to 50% of dairy cows affected by metabolic and infectious
diseases are detected around parturition (18).
The intensive monitoring of fresh cows to detect disorders at an early stage
and to treat the cows if necessary is an important factor in promoting good
performance of the cow during future lactation (28).
In this context, accounting with fresh cow groups and daily management
protocols can optimize fresh cow management efficiency.
Concerning
consultancy, most herds (n = 27/28) were assessed by feed company consultants,
and some by private consultants (n = 20/28) on weekly visits. Farmers prefer to
act in response to information provided to their contexts. Referents may vary
for each producer, but veterinarians often influence farmers’ decision-making
about infectious disease prevention (24).
The average length
of the last dry period for multiparous cows was 59 days (SD = 11.4). This
duration aligns closely with recommendations from previous studies advocating a
60-day dry period, aimed at optimizing milk production income and minimizing
metabolic disorders (12). However, recent
research suggests potential benefits in shortening or even customizing dry
period strategies to balance milk yield and metabolic health (3, 16). In this study, although intentions behind
these shorter periods were not explicitly confirmed, 20% of the farms
implemented shorter dry periods, averaging 50 days or less.
Evaluations of BCS across far-off, close-up, and fresh cows
revealed average scores of 3.2 (SD = 0.38), 3.6 (SD = 0.32), and 3.6 (SD =
0.37), respectively. While far-off cows exhibited similar average BCS as
reported in previous studies (14), 25% of
them scored 3.5 or higher, potentially impacting metabolic health outcomes (5). More on, close-up cows were evidently fatter
than far-off cows. Although controlled energy diets were meant to be fed to the
latter (see nutrient composition in Feeds and feeding management section),
maybe the net energy for lactation (NEL)
content should be even lower (1.4 Mcal/kg) (2).
According to these authors, a greater decrease in BCS after calving is expected
in these cows, increasing metabolic disorders and impairing reproductive
performance. Probably, shortening the dry period to 45 d could improve energy
balance in the transition period.
Feeds
and Feeding Management
Considering the
initial 28 farms, diet composition data were successfully gathered for far-off
dry cows from 22 farms, close-up cows from 26 farms, and fresh or lactating
cows from 27 farms. However, some farms were excluded due to missing data,
particularly those using pasture diets exclusively.
Far-off cow diets, excluding those on pasture, generally
contained lower dry matter (DM), crude protein (CP), starch, and ether extract
(EE) compared to close-up and fresh/lactating cow diets (table 1).
This difference primarily stems from higher forage inclusion in far-off diets,
with most being total mixed rations (TMRs) featuring corn silage. In contrast,
a subset of farms utilized pasture-based diets for far-off cows, resulting in
lower DM content. Close-up diets maintained similar NEL levels to far-off diets
but included higher starch and EE content, often supplemented with high-fiber
ingredients such as wheat straw to mitigate health disorders during the fresh
period. Notably, far-off diets exhibited higher NEL than those reported by Kerwin et al. (2023), potentially contributing
to an increased BCS during this period. Excessive energy consumption is known
to accumulate in adipose tissue, increasing the risk of metabolic issues (2). Regarding dietary cation-anion difference
(DCAD), all close-up diets included anionic salts as a strategy to reduce the
incidence of hypocalcemia, an important practice supported by regular urinary
pH measurements in these farms. In fresh/lactating diets, carbohydrate balances
were maintained to achieve 15-28% of fNDF, 15-19% CP and 20-32% starch levels
across diets. In these diets, DCAD values were generally positive, with a few
farms achieving values greater than 350 mEq/kg, which is recommended to enhance
dry matter intake and fat-corrected milk (20).
Table 1. Nutrient
composition means (SD) of far-off, close-up and fresh or lactating groups in
dairy farms in Argentina.
Tabla
1. Composición nutricional promedio
(DE) de vacas secas, preparto y frescas o en lactancia en establecimientos
lecheros de Argentina.
*Far-off
groups fed only pasture were not included.
DM=
dry matter; CP= crude protein; NEL= net energy for lactation; NDFom=
neutral detergent fiber, organic matter-based; fNDF= forage NDF; DCAD= dietary
cation-anion difference.
*No
se incluyeron los rodeos de vacas secas en pastoreo.
DM=
materia seca; CP= proteína cruda; NEL= energía neta de lactancia; NDFom=
fibra detergente neutro base materia orgánica; fFDN=FDN de forraje; DCAD=
diferencia catiónica-aniónica dietaria.
All farms fed
different diets during the dry period (far-off and close-up diets). Table 2 summarizes the ingredient compositions for far-off,
close-up and lactating cow diets.
Table 2. Ingredient
composition means (SD) of far-off, close-up and fresh or lactating groups in
dairy farms in Argentina.
Tabla
2. Inclusión promedio (DE) de
ingredientes de dietas de vacas secas, preparto y frescas o en lactancia en
establecimientos lecheros de Argentina.
Every farm included
corn silage in at least one of their diets. Concentrates predominantly
comprised corn and soybean meal, aligning closely with nutrient compositions
reported by Kerwin et al. (2022) from dairy
herds in the northeastern United States.
Far-off and close-up cow diets were typically delivered once
daily, with most farms (93%) monitoring feed bunk refusals in close-up groups
but less in far-off (74%). Most fresh/lactating cows were fed twice daily, with
daily monitoring of feed bunks. Sampling and analysis practices for forages and
concentrates varied significantly across farms. Forages were sampled and
analyzed only when a new bag or ingredient was used on most farms. Wet
concentrates were not sampled and analyzed in most farms (64%), although wet
forages were sampled and analyzed every 3 months (24%) or when a new ingredient
was used or a new bag opened (62%). Dry concentrates were not sampled in
one-third of the cases, and hays were sampled when a new lot came to the farm
or every 3 months in 2 thirds of the farms. Sampling schedules often fall short
of optimal frequencies recommended for small and large herds (30).
Health
Events
Data on milk fever, clinical mastitis, metritis, retained
placenta, culling, and death events were recorded across 2,957 cows that calved
during April and May 2022 (table 3).
Table 3. Incidence
of health events during the first 21 days in milk at cow- and herd-level in
dairy farms in Argentina.
Tabla 3. Incidencia
de eventos de salud durante los primeros 21 días en lactancia a nivel de vaca y
de rodeo en establecimientos lecheros de Argentina.
In our study, we
observed lower herd incidences and reduced variability in specific health
events such as milk fever, metritis, culling, and death compared to recent data
published by Kerwin et al. (2022). Our data
fall below the achievable prevalence levels determined by Caixeta
and Omontese (2021), which could be attributed to the selection process of
these farms. Additionally, at the cow level, our data indicate higher
incidences compared to those reported by Masia et al.
(2022) and Ruprechter et al. (2018)
in farms located in Argentina and Brazil. In the case of Masia
et al. (2022), the database was provided by DairyComp - Clientes
Ciale Alta, whose farms are generally considered well-managed or at least
benefit from professional advice. Ruprechter et al. (2018)
included data from only one farm. On the other hand, our data suggest
significantly lower incidences of mastitis and retained placenta compared to
the findings in other studies, which could indicate underreporting of these
events, although this could also be the case in those other studies.
Blood sample
results from 310 analyzed cows showed that 28 had hyperketonemia, representing
a 9% overall incidence, with the majority being multiparous cows (n = 24). At
the herd level, we found a median incidence of 8% (range: 0 - 30%). Similarly, Kerwin et al. (2022) reported that nearly half
of the farms in their study had less than 15% of cows with values >1.2
mmol/L of BHB.
Our study, similar
to surveys of German farmers (13) and
farms in California (9), included
assessments of fresh cows. However, both studies noted that the evaluation of
fresh cows primarily relied on nonspecific observations, suggesting potential
benefits from implementing more objective practices to identify health
disorders.
Milk
Yield and Quality
We recorded milk yield at start-up (10 to 30 DIM) and peak (75
to 105 DIM) from 2,064 and 2,084 cows, respectively, that calved during April
and May 2022 (table 4).
Table 4. Milk
yield at start-up and peak average (SD) for cows calved during April and May
2022 in dairy farms in Argentina.
Tabla 4. Promedio
(DE) de producción de leche al inicio y al pico en vacas paridas durante abril
y mayo de 2022 en establecimientos lecheros de Argentina.
Our results show
that primiparous cows produced 75% of the milk yield of mature cows (≥3
lactations) at the beginning of lactation. This proportion is slightly higher
than the 71.3% reported by Kerwin et al. (2023),
although absolute milk yield in our study was 1.5 kg lower. A greater disparity
is evident in milk yield among mature cows, with almost a 4 kg difference,
though standard deviations are similar. This highlights a clear opportunity to
increase individual milk yield, particularly among primiparous cows.
In comparison to the national average milk yield in 2022, which
was 24 kg/cow/day (21), these farms
generally exhibit higher milk yields. Similarly, mean fat and crude protein
content (3.9% and 3.5%, respectively) on these farms were greater than national
average values (3.7% ± 0.18 and 3.4% ± 0.07 for fat and crude protein in milk,
respectively) according to OCLA (2023), but lower
than those reported by Kerwin et al. (2023)
from farms in northeastern United States. While most industries in our country
pay based on volume, some farms trade directly with factories, presenting
different challenges in terms of milk composition.
The study has some
limitations that warrant consideration. Firstly, dairy farms were chosen based
on their receipt of professional consultancy from graduate students specialized
in nutrition, indicating a likelihood of better-than-average management
practice. Additionally, the herds surveyed had more cows per farm than the
national average of 158 cows per farm (22),
which may result in management practices and performance indicators that differ
from those observed in smaller-scale operations. Secondly, measurements and
records were gathered over a short period, which may not fully capture seasonal
variations that could influence study outcomes. Thirdly, health event records
relied on reports from farm personnel, potentially leading to variability in
data accuracy and completeness. These limitations underscore the need for
cautious interpretation of the findings, particularly regarding the
generalizability and temporal applicability of the results. However, this study
provides valuable insights into transition cow management practices, feeding
regimes, health outcomes, and milk production characteristics across a sample
of dairy farms in Argentina. Overall, while the studied farms generally
exhibited good management practices, opportunities exist to enhance feeding
management, health monitoring protocols, and data recording practices. Future research
could explore the economic implications of implementing more intensive health
monitoring and feeding strategies, focusing on milk yield and composition.
Conclusions
This study
contributes valuable data on transition cow management and performance metrics
in Argentine dairy farms, highlighting areas of strength and opportunities for
refinement to support sustainable dairy production practices.
On the positive
side, a key strength observed across the farms was the routine separation of
far-off and close-up dry cows, which enables targeted nutritional and health
management strategies during this critical period. Notably, the implementation
of negative DCAD diets in close-up groups reflects a proactive approach to
preventing hypocalcemia. Frequent bunk monitoring during the transition period
also suggests a high level of attention to feed access and intake, which likely
contributes to the low incidence of metabolic disorders, culling, and mortality
recorded in these systems. In addition, milk composition data revealed
higher-than-average solids content compared to national data, indicating
effective nutritional strategies and potential for improved milk quality and
value.
However, the study
also identified several opportunities for refinement. One important area is the
grouping strategy in the prepartum phase: primiparous and multiparous cows are
often housed together, which may negatively affect younger animals due to social
stress and competition. Additionally, the lack of shade for dry cows in some
farms may compromise animal comfort, health and productivity, especially in
warmer seasons. A second key issue is the length of the dry period, which in
several cases exceeded 50 days. This extended duration, in combination with
increased energy density in prepartum diets, was associated with undesirable
increases in body condition, highlighting the need for more precise energy
balance management during the transition. Moreover, the frequency of forage and
wet feed sampling was often lower than recommended, limiting the accuracy of
ration formulation and monitoring. On the production side, individual milk
yield, particularly among primiparous cows, and milk solids content were identified
as areas with potential for further improvement, suggesting that refinements in
feeding, grouping, or overall cow comfort could yield better performance
outcomes.
In summary, while transition cow management in the surveyed
Argentine dairy farms shows solid foundational practices, the study underlines
the importance of continued attention to grouping strategies, environmental
aspects, feed monitoring, and precision nutrition to optimize both animal
welfare and productive efficiency during this critical period of the lactation
cycle.
1. Caixeta, L. S.;
Omontese, B. O. 2021. Monitoring and improving the metabolic health of dairy
cows during the transition period. Animals 11: 1-17.
https://doi.org/10.3390/ani11020352
2. Cardoso, F. C.;
Kalscheur, K. F.; Drackley, J. K. 2020. Symposium review: Nutrition strategies
for improved health, production, and fertility during the transition period. J.
Dairy Sci. 103:5684-5693. https://doi.org/10.3168/jds.2019-17271
3. Cermakova, J.;
Kudrna, V.; Simeckova, M.; Vyborna, A.; Dolezal, P.; Illek, J. 2014. Comparison
of shortened and conventional dry period management strategies. J. Dairy Sci.
97: 5623-5636. https:// doi.org/10.3168/jds.2013-7499
4. Chebel, R. C.;
Silva, P. R. B.; Endres, M. I.; Ballou, M. A.; Luchterhand, K. L. 2016. Social
stressors and their effects on immunity and health of periparturient dairy
cows. J. Dairy Sci. 99: 3217-3228. https://doi.org/10.3168/jds.2015-10369
5. Contreras, L.
L.; Ryan, C. M.; Overton, T. R. 2004. Effects of dry cow grouping strategy and
prepartum body condition score on performance and health of transition dairy
cows. J. Dairy Sci. 87: 517-523.
https://doi.org/10.3168/jds.S0022-0302(04)73191-4
6. Couto Serrenho,
R.; Church, C.; McGee, D.; Duffield, T. F. 2022. Environment, nutrition, and
management practices for far-off, close-up, and fresh cows on Canadian dairy
farms-A retrospective descriptive study. J. Dairy Sci. 105: 1797-1814.
https://doi.org/10.3168/ jds.2021-20919
7. Daros, R. R.;
Weary, D. M.; von Keyserlingk, M. A. G. 2022. Invited review: Risk factors for
transition period disease in intensive grazing and housed dairy cattle. J.
Dairy Sci. 105: 4734-4748. https://doi.org/10.3168/jds.2021-20649
8. Drackley, J. K.
1999. ADSA foundation scholar award: Biology of dairy cows during the
transition period: The final frontier? J. Dairy Sci. 82: 2259-2273.
https://doi.org/10.3168/jds.s0022- 0302(99)75474-3
9. Espadamala, A.;
Pallarés, P.; Lago, A.; Silva-del-Río, N. 2016. Fresh-cow handling practices
and methods for identification of health disorders on 45 dairy farms in
California. J. Dairy Sci. 99: 9319-9333. https://doi.org/10.3168/jds.2016-11178
10. Gregoretti, G.;
Baudracco, J.; Dimundo, C.; Lazzarini, B.; Scarel, J.; Alesso, A.; Machado, C.
2024. Traditional cow-calf systems of the northern region of Santa Fe,
Argentina: current situation and improvement opportunities. Revista de la
Facultad de Ciencias Agrarias. Universidad Nacional de Cuyo. Mendoza.
Argentina. 56(1): 106-116. DOI: https://doi. org/10.48162/rev.39.127
11. Grummer, R. R.
1995. Impact of changes in organic nutrient metabolism on feeding the
transition dairy cow. J. Anim. Sci. 73(9): 2820-2933.
https://doi.org/10.2527/1995.7392820x
12. Grummer, R. R.;
Rastani, R. R. 2004. Why reevaluate dry period length? J. Dairy Sci. 87:
E77-E85. https://doi.org/10.3168/jds.S0022-0302(04)70063-6
13. Heuwieser, W.;
Iwersen, M.; Gossellin, J.; Drillich, M. 2010. Short communication: Survey of
fresh cow management practices of dairy cattle on small and large commercial
farms. J. Dairy Sci. 93: 1065-1068. https://doi.org/10.3168/jds.2009-2783
14. Kerwin, A. L.;
Burhans, W. S.; Mann, S.; Tetreault, M.; Nydam, D. V.; Overton, T. R. 2022.
Transition cow nutrition and management strategies of dairy herds in the
northeastern United States: Part I-Herd description and performance
characteristics. J. Dairy Sci. 105: 5327-5348.
https://doi.org/10.3168/jds.2021-20862
15. Kerwin, A. L.;
Burhans, W. S.; Nydam, D. V.; Overton, T. R. 2023. Transition cow nutrition and
management strategies of dairy herds in the northeastern United States: Part
III-Associations of management and dietary factors with analytes, health, milk
yield, and reproduction. J. Dairy Sci. 106: 1246-1266.
https://doi.org/10.3168/jds.2022-21876
16. Kok, A.; van
Hoeij, R. J.; Kemp, B.; van Knegsel, A. T. M. 2021. Evaluation of customized
dry-period strategies in dairy cows. J. Dairy Sci. 104: 1887-1899. https://doi.org/10.3168/
jds.2020- 18719
17. Laporta, J.;
Ferreira, F. C.; Ouellet, V.; Dado-Senn, B.; Almeida, A. K.; De Vries, A.;
Dahl, G. E. 2020. Late-gestation heat stress impairs daughter and granddaughter
lifetime performance. J. Dairy Sci. 103: 7555-7568.
https://doi.org/10.3168/jds.2020-18154
18. Leblanc, S.
2010. Monitoring metabolic health of dairy cattle in the transition period
introduction-metabolic challenges in peripartum dairy cows and their
associations with reproduction. J. Reprod. Dev. 56: 29-35.
19. Masia, F.;
Molina, G.; Vissio, C.; Balzarini, M.; de la Sota, R. L.; Piccardi, M. 2022.
Quantifying the negative impact of clinical diseases on productive and
reproductive performance of dairy cows in central Argentina. Livest. Sci. 259:
104894. https://doi.org/10.1016/j. livsci.2022.104894
20. NASEM (National
Academies of Sciences, Engineering, and Medicine). 2021. Nutrient Requirements
of Dairy Cattle. 8th rev.
ed. Washington, DC: National Academies Press.
21. OCLA
(Observatorio de la Cadena Láctea Argentina). Informe Anual de la Cadena Láctea
Argentina 2022. Buenos Aires. Argentina.
22. OCLA (Observatorio de la Cadena Láctea Argentina). Informe
Anual de la Cadena Láctea Argentina 2023. Buenos Aires, Argentina.
23. Oetzel, G.;
McGuirkl, S. 2010. Fact Sheet - Cowside Blood BHBA Testing with a Hand-Held
“Ketometer.” University of Wisconsin-Madison. School of Veterinary Medicine
1-4.
24. Ritter, C.;
Jansen, J.; Roche, S.; Kelton, D. F.; Adams, C. L.; Orsel, K.; Erskine, R. J.;
Benedictus, G.; Lam, T. J. G. M.; Barkema, H. W. 2017. Invited review:
Determinants of farmers’ adoption of management-based strategies for infectious
disease prevention and control. J. Dairy Sci. 100: 3329-3347.
https://doi.org/10.3168/jds.2016-11977
25. Ruprechter, G.;
Adrien, M. de L.; Larriestra, A.; Meotti, O.; Batista, C.; Meikle, A.; Noro, M.
2018. Metabolic predictors of peri-partum diseases and their association with
parity in dairy cows. Res. Vet. Sci. 118: 191-198.
https://doi.org/10.1016/j.rvsc.2018.02.005
26. Schirmann, K.;
Chapinal, N.; Weary, D. M.; Heuwieser, W.; von Keyserlingk, M. A. G. 2011.
Short-term effects of regrouping on behavior of prepartum dairy cows. J. Dairy
Sci. 94: 2312-2319. https://doi.org/10.3168/jds.2010-3639
27. Schuenemann, G.
M.; Piñeiro, J. M.; Turiello, P. 2016. Association between management practices
and reproductive performance of lactating dairy cows. Page 600 in Proc. 2016
JAM.
28. Silva, M. A.;
Veronese, A.; Belli, A.; Madureira, E. H.; Galvão, K. N.; Chebel, R. C. 2021.
Effects of adding an automated monitoring device to the health screening of
postpartum Holstein cows on survival and productive and reproductive
performances. J. Dairy. Sci. 104: 3439-3457.
https://doi.org/10.3168/jds.2020-18562
29. Turiello, P.;
Piñeiro, J. M.; Schuenemann, G. M. 2016. Association between management
practices and dairy herd performance. Page 600 in Proc. 2016 JAM.
30. Weiss, W. P.;
St-Pierre, N. R. 2009. Impact and Management of Variability in Feed and Diet
Composition. Pages 83-96 in Proc. 18th Annual
Tri-State Dairy Nutrition Conference.
31. Wildman, E. E.; Jones, G. M.; Wagner, P. E.; Boman, R. L.;
Troutt, H. F.; Lesch, T. N. 1982. A Dairy Cow Body Condition Scoring System and
Its Relationship to Selected Production Characteristics. J. Dairy Sci. 65:
495-501. https://doi.org/10.3168/jds.S0022-0302(82)82223-6