Influence of environmental factors and parity on milk yield dynamics in barn-housed dairy cattle

Air quality monitoring in dairy farms: Description of air quality dynamics in a tunnel-ventilated housing barn and milking parlor of a commercial dairy farm

This study aimed to describe air quality dynamics in a commercial dairy farm focusing on 2 locations: a tunnel-ventilated barn (TVB) and a milking parlor (MKP). Assessed air quality components included carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), ammonia (NH3), particulate matter 2.5 µg/m3 (PM2.5), total volatile organic compounds (VOC), and temperature-humidity index (THI), which were continuously monitored from August 16 to December 22, 2023, using a multiple air quality sensor platform. Descriptive analysis revealed significant hourly variability in the air quality dynamics during the study period. Mixed-effects models revealed no significant differences in the overall CO and THI measurements between the barn and milking parlor. However, the location significantly influenced overall concentrations of other air components including CO2, CH4, PM2.5, VOC, and NH3. Overall comparisons between TVB and MKP showed that the TVB had a higher overall CO2 concentration mean during the observation period compared with the MKP (LSM ± SEM; 640 ± 9.02 vs. 612 ± 9.01 ppm), while the MKP recorded highest CH4 levels (11.03 ± 0.52 vs. 8.87 ± 0.52 ppm). In the TVB, the NH3 levels ranged from 0.401 to 44.9 ppm, whereas no NH3 was detected in the MKP. The MKP recorded higher overall PM2.5 compared with the TVB (5.51 ± 0.31vs. 3.21 ± 0.31µg/m3). The VOC levels exhibited higher overall means in the TVB compared with the MKP (153 ± 2.18 vs. 144 ± 2.16 ppm) but were characterized by substantial variability in both locations. Temporal trends suggested that the monitored air components might be influenced by farm activities such as feeding, cleaning, and milking as identifiable peaks we observed at specific hours of the day. We identified hourly pattern dynamics of CO, CO2, CH4, NH3, PM2.5, VOC, and THI within the TVB and the MKP. Understanding these dynamics provides the opportunity to develop mitigation strategies for enhancing air quality within dairy facilities.

Effects of assisted calving and retained fetal membranes on milk production in the smallholder farming system

The impact of assisted calving, retained fetal membranes (RFM) and calf sex on milk production in small-scale dairy systems remains unknown. This study evaluated their impact on early lactation milk production and standardized 305-day yield (305MY) using 279 lactation records from 23 farms over 18 months. Variables analyzed included assisted calving, RFM, calf sex, and lactation number, with milk production at 30 days and 305MY as response variables. General Linear Models were used for statistical analysis, with significance at P < 0.05, and trends at P < 0.1. Lactation number significantly affected early lactation milk production (P = 0.023), with RFM showing a trend toward significance (P = 0.078). Cows without RFM produced 21.8 ± 0.8 kg/day, while those with RFM produced 18.6 ± 1.7 kg/day. Assisted calving significantly affected 305MY (P < 0.05), with cows not requiring assistance having higher yields compared to those needing assistance. Interactions between assisted calving and lactation number (P = 0.099), as well as RFM and calf sex (P = 0.060), approached significance. In cows that did not require assisted calving, no significant differences in 305MY were found based on lactation number (P ≥ 0.05). However, in cows that required assisted calving, significant differences in 305MY (P < 0.05) were observed between first and third or higher lactations, with second-lactation cows having average values. Additionally, cows without RFM that gave birth to female calves had higher 305MY compared to cows with RFM or those that gave birth to male calves with RFM or without RFM. In conclusion, RFM reduces early lactation milk production by approximately 3.2 kg/day, and assisted calving impacts 305MY by about 1,069 kg/lactation.

Revealing study and breeding implications for production traits and tail characteristics in Simmental cattle by GWAS

Simmental cattle are renowned for their dual purpose as meat and dairy breeds. The study recorded phenotype data from 183 Simmental cattle and performed a Genome-Wide Association Study (GWAS) analysis to elucidate the genetic mechanisms underlying milk production, body size traits, and tail characteristics. Statistical analysis of phenotype data showed that season, parity, and age at first calving (AFC) factors had a significant effect on milk production (P < 0.05). The results of GWAS on cattle linear traits revealed that the candidate genes SH3RF2, DCHS2, ADAMTS1, CAMK4, PPARGC1A, PRL, PRP6, and CORIN have been found to affect body circumference (BC) and cannon circumference (CC). Through GWAS analysis of tail traits, including Circumference over tail root (COTR) and Tail Length (TL) in Simmental cattle, candidate genes associated with tail length, such as KIF26B, ITPR2, SLC8A1, and SLIT3 were identified. Interestingly, candidate genes IL1RAP, AQP9, ITPR2, and PKD2 were also associated with metabolic inflammation in cattle tails. These genetic markers offer valuable insights into the traits of Simmental cattle, facilitating the development of molecular breeding strategies to enhance production value and provide references for breeding programs.

Development and evaluation of predictive models for pregnancy risk in UK dairy cows

One suggested approach to improve the reproductive performance of dairy herds is through the targeted management of subgroups of biologically similar animals, such as those with similar probabilities of becoming pregnant, termed pregnancy risk. We aimed to use readily available farm data to develop predictive models of pregnancy risk in dairy cows. Data from a convenience sample of 108 dairy herds in the UK were collated and each herd was randomly allocated, at a ratio of 80:20, to either training or testing data sets. Following data cleaning, there were a total of 78 herds in the training data set and 20 herds in the testing data set. Data were further split by parity into nulliparous, primiparous, and multiparous subsets. An XGBoost model was trained to predict the insemination outcome in each parity subset, with predictors from farm records of breeding, calving and milk recording. Training data comprised 74,511 inseminations in 45,909 nulliparous animals, 86,420 inseminations in 39,439 primiparous animals, and 158,294 inseminations in 32,520 multiparous animals. The final models were evaluated by predicting with the testing data, comprising 31,740 inseminations in 19,647 nulliparous animals, 38,588 inseminations in 16,215 primiparous animals, and 65,049 inseminations in 12,439 multiparous animals. Model discrimination was assessed by calculating the area under receiver operating characteristic curves (AUC); model calibration was assessed by plotting calibration curves and compared across test herds by calculating the expected calibration error (ECE) in each test herd. The models were unable to discriminate between insemination outcomes with high accuracy, with an AUC of 0.63, 0.59 and 0.62 in the nulliparous, primiparous and multiparous subsets, respectively. The models were generally well-calibrated, meaning the model-predicted pregnancy risks were similar to the observed pregnancy risks. The mean (SD) ECE in the test herds was 0.038 (0.023), 0.028 (0.012) and 0.020 (0.008) in the nulliparous, primiparous and multiparous subsets respectively. The predictive models reported here could theoretically be used to identify subgroups of animals with similar pregnancy risk to facilitate targeted reproductive management; or provide information about cows' relative pregnancy risk compared with the herd average, which may support on-farm decision-making. Further research is needed to evaluate the generalizability of these predictive models and understand the source of variation in ECE between herds; however, this study demonstrates that it is possible to accurately predict pregnancy risk in dairy cows using readily available farm data.

Association between days post-conception and lactation persistency in dairy cattle

Determining the optimal insemination moment for individual cows is complex, particularly when considering the effects of pregnancy on milk production. The effect of pregnancy on the absolute milk yield has already been reported in several studies. Currently, there is limited quantitative knowledge about the association between days post-conception (DPC) and lactation persistency, based on a lactation curve model, and, specifically, how persistency changes during pregnancy and relates to the days in milk at conception (DIMc). Understanding this association might provide valuable insights to determine the optimal insemination moment. This study, therefore, aimed to investigate the association between DPC and lactation persistency, with an additional focus on the influence of DIMc. Available milk production data from 2005 to 2022 were available for 23,908 cows from 87 herds located throughout the Netherlands and Belgium. Persistency was measured by a lactation curve characteristic decay, representing the time taken to halve milk production after peak yield. Decay was calculated for 8 DPC (0, 30, 60, 90, 120, 150, 180, and 210 d after DIMc) and served as the dependent variable. Independent variables included DPC, DIMc (≤60, 61-90, 91-120, 121-150, 151-180, 181-210, >210), parity group, DPC × parity group, DPC × DIMc, and variables from 30 d before DIMc as covariates. The results showed an increase in decay, which is to say, a decrease in persistency, during pregnancy for both parity groups, albeit in different ways. Specifically, from DPC 150 to DPC 210, multiparous cows showed a greater decline in persistency compared with primiparous cows. Furthermore, a later DIMc (cows conceiving later) was associated with higher persistency. Except for the early DIMc groups (DIMc <90), DIMc does not affect the change in persistency by gestation. The findings from this study contribute to a better understanding of how DPC and DIMc during lactation influence lactation persistency, enabling more informed decision-making by farmers who wish to take persistency into account in their reproduction management.

Estimation of genetic parameters of the productive and reproductive traits in Iranian Holstein cattle using single and repeated records

This study estimated the genetic parameters of productive and reproductive traits of Iranian Holstein cattle from data recorded between 2006 and 2018. The data analysis was performed using animal model, including the record of the first parity and the first three lactation records. Heritability values for milk, fat, and protein using a single record animal model were 0.29 ± 0.005, 0.22 ± 0.005, and 0.24 ± 0.005, respectively. The heritability of these traits based on a repeated model was estimated to be 0.19 ± 0.001, 0.15 ± 0.005, and 0.17 ± 0.006, respectively. Furthermore, the heritability of age at first calving (AFC) and length of lactation (LL) traits were 0.16 ± 0.004 and 0.02 ± 0.002, respectively. Repeatability for milk, fat, and protein yield was 0.38 ± 0.002, 0.34 ± 0.002, and 0.36 ± 0.002, respectively. Positive genetic trend was observed over the years of the study for production traits. Evaluation of the effect of herd-year-season (HYS) on the productive traits revealed that the management and environmental conditions of the farms including feed quality and disease control have been improved. The average heritability for milk, fat, and protein yield and AFC indicates the possibility of genetic improvement for these traits. Furthermore, the repeatability values show that the selection process can be performed based on the first lactation record. The positive genetic trend of productive traits demonstrates the improvement of breeding values in Iranian Holstein cattle.

The Challenge of Global Warming in Water Buffalo Farming: Physiological and Behavioral Aspects and Strategies to Face Heat Stress

Water buffaloes have morphological and behavioral characteristics for efficient thermoregulation. However, their health, welfare, and productive performance can be affected by GW. The objective of this review was to analyze the adverse effects of GW on the productive behavior and health of water buffaloes. The physiological, morphological, and behavioral characteristics of the species were discussed to understand the impact of climate change and extreme meteorological events on buffaloes' thermoregulation. In addition, management strategies in buffalo farms, as well as the use of infrared thermography as a method to recognize heat stress in water buffaloes, were addressed. We concluded that heat stress causes a change in energy mobilization to restore animal homeostasis. Preventing hyperthermia limits the physiological, endocrine, and behavioral changes so that they return to thermoneutrality. The use of fans, sprinklers, foggers, and natural sources of water are appropriate additions to current buffalo facilities, and infrared thermography could be used to monitor the thermal states of water buffaloes.

Maternal Age, Parity and Nursing Status at Fertilization Affects Postpartum Lactation Up to Weaning in Horses

Nulliparity is associated with intra-uterine growth retardation and foal delayed catch-up growth. Older mares produce larger/taller foals than the precedents. Nursing at conception on foal growth had not been investigated yet. In any case, milk production conditions the foal's growth. This study aimed to determine effects of mare parity, age and nursing on subsequent lactation quantity and quality. Saddlebred mares and their foals (N = 43) run as a single herd over the same year were: young (6-7-year-old) primiparous, young multiparous, old (10-16-year-old) multiparous nursing at insemination time or old multiparous barren the previous year. No young nursing nor old multiparous mares were available. Colostrum was collected. Milk production and foal weight were monitored at 3-, 30-, 60-, 90- and 180-days postfoaling. The foal average daily weight gain (ADG) was calculated for each period between two measurements. Milk fatty acid (FA), sodium, potassium, total protein and lactose contents were determined. The primiparous versus multiparous colostrum was richer in immunoglobulin G, with lower production but greater FA contents in milk. The primiparous foals had a lower ADG for 3 to 30 days postpartum period. Old mares' colostrum contained more SFA and less polyunsaturated FA (PUFA) whereas their milk was richer in proteins and sodium and poorer in short-chain-SFA with a reduced PUFA/SFA ratio at 90 days. Nursing mares' colostrum was richer in MUFA and PUFA and late-lactation milk production was reduced. In conclusion, parity, age and nursing at conception affect mare's colostrum and milk production and foal growth and should be considered for broodmares' management.

A comprehensive characterization of longevity and culling reasons in Canadian Holstein cattle based on various systematic factors

The decision of premature culling cows directly impacts the profitability of dairy farms. A comprehensive characterization of the primary causes of culling reasons would greatly improve both management and selection objectives in dairy cattle breeding programs. Therefore, this study aimed to analyze the temporal frequencies of 34 culling reasons in Canadian Holstein cows. After data editing and quality control, records from 3,096,872 cows culled from 9,683 herds spread across Canada were used for the analyses covering the periods from 1996 to 2020. Reproductive issues were the main culling reason accounting for 23.02%, followed by milk production (20.82%), health (20.39%), conformation problems (13.69%), economic factors (13.10%), accidents (5.67%), age-related causes (1.67%), and workability (1.63%). Nearly fifty-eight percent of cows were culled after 47 months of age. The observed frequencies of culling due to economic factors were lower than expected from 1996 to 2014 and higher than expected between 2015 and 2020. Reproduction issues had the highest culling frequencies during fall (24.54%), winter (24.02%), and spring (22.51%), while health issues were the most frequent (22.51%) culling reason in the summer season. Health issues (25.50%) and milk production (27.71%) were the most frequent culling reasons in the provinces of Quebec and Ontario, respectively. Reproductive issues showed the highest frequency across climates based on the Köppen climate classification, except for Csb (Dry-summer subtropical or Mediterranean climate) and Bsk (Middle latitude steppe climate), which correspond to small regions in Canada, where production was the most frequent culling reason (29.42% and 21.56%, respectively). Reproductive and milk performance issues were the two main culling reasons in most ecozones, except in Boreal Shield and Atlantic Marine, where health issues had the highest frequencies (25.12 and 23.75%, respectively). These results will contribute to improving management practices and selective decisions to reduce involuntary culling of Holstein cows.

Evaluation of the Metabolic Relationship between Cows and Calves by Monitoring Calf Health and Cow Automatic Milking System and Metabolic Parameters

With this study, we investigated the relationship between a cow's and calf's metabolic state, and its effect on health status. To achieve this, 20 calves of primiparous and 20 calves of multiparous cows were selected. The calves were monitored for 30 days and scored for signs of disease, as described in McQuirk (2008); according to score, they were divided into healthier calves; the Low calf score group (LCS, 5-8), Medium calf score group (MCS, 9-12) and High calf score group (HCS, 14-17); or calves most prone to disease. Their mothers were monitored for the same period with a Lely Astronaut 3 herd management system (Lely, Maassluis, The Netherlands) for rumination time, milk yield, milk fat, protein, lactose concentrations and milk fat to protein ratio. Both cows and calves were sampled for blood, and concentrations of glucose with β-hydroxybutyrate were registered. The results indicate that primiparous cows had a 16% higher blood glucose concentration (3.03 mmol/L SE = 0.093) compared with multiparous cows (2.61 mmol/L, SE = 0.102) (p < 0.01), but no difference in calf glucose was recorded. Β-hydroxybutyrate levels did not differ significantly between cows and calves by parity group. Rumination time was longest in the HCS group at 550.79 min/d. and was 16% longer compared with the LCS group (461.94 min/d.; p < 0.001) and 8% longer compared with the MCS group (505.56 min/d.; p < 0.001). The MCS group rumination time mean was statistically significantly higher compared with the LCS group by 8% (p < 0.001). Milk yield was also highest in the HCS group (44.8 kg/d.): 19% higher compared with the MCS group (36.31 kg/d., p < 0.001) and 13% higher than the LCS group (38.83 kg/d., p < 0.001). There was also a significant difference between the MCS and LCS groups of 6% (p < 0.001). The HCS group had the highest milk fat concentration (4.47%): it was 4% higher compared with the LCS group (4.28%, p < 0.001) and 5% higher than the MCS group (4.25%, p < 0.001). Milk fat to protein ratio was highest in the HCS group (1.21) and was 7% higher than in the MCS group (1.12, p < 0.001) and 8% higher than in the LCS group (1.11, p < 0.001). The LCS group was determined to have the highest concentration of milk lactose (4.66%). It was 1% higher compared with the MCS group (4.62%, p < 0.001) and 1.07% higher than the HCS group (4.61%, p < 0.001). We can conclude that parity did not affect calf health status and that cows of the HCS group showed symptoms of negative energy balance expressed through higher milk yield, higher milk fat concentration and higher milk fat to protein ratio, with lower milk lactose concentration. Further and more thorough research is needed to evaluate the relationship between pregnant cows and calves.

Effect of Parity, Body Condition Score at Calving, and Milk Yield on the Metabolic Profile of Gyr Cows in the Transition Period

This study aimed to evaluate the effects of parity, body condition score (BCS) at calving, and milk yield on the metabolic profile of Gyr (Zebu) cows. Healthy cows in late pregnancy were grouped according to parity (primiparous, biparous, and multiparous); to BCS scale at calving (high-HBCS and normal-NBCS); and to milk yield (high-HP and moderate-MP production). BCS was assessed, and blood samples were collected on -21, -7, 0, 7, 21, and 42 days relative to parturition. The concentrations of non-esterified fatty acids (NEFA), beta-hydroxybutyrate (BHB), cholesterol, glucose, total protein (TP), albumin, total calcium (Ca), phosphorus (P), and magnesium (Mg); and activities of aspartate aminotransferase and gamma-glutamyltransferase were measured. Data were analyzed by two-way repeated measures ANOVA. The frequencies of high lipomobilization, subclinical ketosis, subclinical hypocalcemia (SCH), and the occurrence of diseases during early lactation were established. Regardless of grouping, NEFA, BHB, and cholesterol increased during early lactation; glucose showed higher values at calving; TP and albumin were higher at 21 and 42 DIM; and Ca, P, and Mg were lower at calving. Parity had little effect on the metabolic profile, HBCS did not differ from NBCS cows, and HP did not differ from MP cows in most metabolites. High lipomobilization in early lactation and SCH at calving were the most common imbalances but were not related to postpartum diseases. High-yielding Gyr cows have a balanced metabolic profile during the transition period, with few biologically relevant effects of parity, BCS at parturition, or milk yielded.

Heat stress effects on milk yield traits and metabolites and mitigation strategies for dairy cattle breeds reared in tropical and sub-tropical countries

Heat stress is an important problem for dairy industry in many parts of the world owing to its adverse effects on productivity and profitability. Heat stress in dairy cattle is caused by an increase in core body temperature, which affects the fat production in the mammary gland. It reduces milk yield, dry matter intake, and alters the milk composition, such as fat, protein, lactose, and solids-not-fats percentages among others. Understanding the biological mechanisms of climatic adaptation, identifying and exploring signatures of selection, genomic diversity and identification of candidate genes for heat tolerance within indicine and taurine dairy breeds is an important progression toward breeding better dairy cattle adapted to changing climatic conditions of the tropics. Identifying breeds that are heat tolerant and their use in genetic improvement programs is crucial for improving dairy cattle productivity and profitability in the tropics. Genetic improvement for heat tolerance requires availability of genetic parameters, but these genetic parameters are currently missing in many tropical countries. In this article, we reviewed the HS effects on dairy cattle with regard to (1) physiological parameters; (2) milk yield and composition traits; and (3) milk and blood metabolites for dairy cattle reared in tropical countries. In addition, mitigation strategies such as physical modification of environment, nutritional, and genetic development of heat tolerant dairy cattle to prevent the adverse effects of HS on dairy cattle are discussed. In tropical climates, a more and cost-effective strategy to overcome HS effects is to genetically select more adaptable and heat tolerant breeds, use of crossbred animals for milk production, i.e., crosses between indicine breeds such as Gir, white fulani, N'Dama, Sahiwal or Boran to taurine breeds such as Holstein-Friesian, Jersey or Brown Swiss. The results of this review will contribute to policy formulations with regard to strategies for mitigating the effects of HS on dairy cattle in tropical countries.

Can meteorological data improve the short-term prediction of individual milk yield in dairy cows?

Many farms document daily milk yields of individual cows because these are a good indicator of cow well-being. It is established that extreme meteorological conditions influence the milk yields by causing heat and cold stress, whereas less is known about the effects of moderate changes in meteorological conditions. Thus, the aim of the present study was to evaluate whether individual daily milk yield predictions can be improved by considering such changes. We evaluated 8 years of milking and meteorological data from Eastern Switzerland with a total of 33,938 daily milkings from 145 Brown Swiss and 64 Swiss Fleckvieh cows. The cows were aged between 1.9 and 13.5 years at parturition. The data set was split into 7 periods according to the days in milk (DIM) and subsequently filtered into subsets by breed and parity. We applied Gaussian process regression to predict individual daily milk yield. We compared different models including DIM, lagged milk yield, and meteorological variables as features and found that models including the lagged milk yield performed best. Within the period of 5 to 90 DIM, we were able to predict individual next-day milk yield from the cow's last milkings with a root mean squared error (RMSE) of 2.1 kg. In contrast, without information on the previous milk yield, accuracy of milk yield prediction was lower, with an RMSE close to 8 kg. The models holding information about previous milk yields showed a substantial increase in performance. Within a more homogeneous data subset filtered by breed or parity or both, predictions were even better, with a relative RMSE of 4.3% for first-parity Fleckvieh cows. However, we found that including meteorological features, such as temperature, rainfall, wind speed, temperature humidity index, cooling degree, and barometric pressure, did not improve the predictions in any of the evaluated periods. This finding indicates that considering meteorological features in daily milk yield prediction models is not useful in moderate climates; considering lagged milk yield is sufficient. We hypothesize that this meteorological information, among other influences, is indirectly contained in the lagged milk yield.

Relationship between microclimate and cow behavior and milk yield under low-temperature and high-humidity conditions

This study aimed to evaluate the relationship between temperature (T), relative humidity (RH), and temperature and humidity index (THI), milk yield (MY), rumination time (RT), and activity (AT) of dairy cows in different parities under low temperature and high humidity (LTHH). In this study, the number of samples each day was determined by all healthy cows in the barn with parity and days in milk (DIM) within 5 and 305, respectively. The box plot method was used for screening and removing outliers of dairy cow indicators after classification according to parity and DIM. To remove the effect of DIM on MY, a bivariate regression model was used to standardize the MY in milk yield index (MYI). The best bivariate regression model based on the lowest Akaike information criterion was used to analyze the relationship between behavioral parameters, MYI, and microclimate indicators for each parity. In the barn with the microclimate at a low temperature above 0°C, high RH was negatively correlated with MYI in primiparous and multiparous cows but positively correlated with AT in primiparous and multiparous cows and RT in multiparous cows (p &lt; 0.05), so RH was a significant factor related to MYI, RT, and AT of cows. The 2-day lagged daily average T and THI were correlated with MYI in primiparous cows (p &lt; 0.05). The inflection point value of 71.9 between AT and RH in the multiparity as the upper limit of RH was beneficial for improving comfort and MY in all parity dairy cows. Compared with MYI and RT, AT had a higher R2 with a microclimate indicator, so it could be used as a better indicator for assessing the LTHH. Comparing the R2 of multiparous cows to T (R2 = 0.0807) and THI (R2 = 0.1247), primiparous cows had higher R2 in MYI to T (R2 = 0.2833) and THI (R2 = 0.3008). Therefore, primiparous cows were more susceptible to T and THI. The inflection point values for MYI to T and THI were greater in primiparous cows than in multiparous cows, indicating that primiparous cows had a smaller tolerance range to T and THI than multiparous cows. Thus, parity should be considered when studying the relationship between MY, T, and THI under LTHH.

Effects of Heat Stress in Dairy Cows Raised in the Confined System: A Scientometric Review

Due to climate change, heat stress is a growing problem for the dairy industry. Based on this, annual economic losses in the dairy sector are verified mainly on a large scale. Despite several publications on thermal stress in lactating dairy cows in confinement systems, there need to be published reviews addressing this issue systematically. Our objective was to scientometrically analyze the effects of heat stress in dairy cows managed in a confinement system. Based on PRISMA guidelines, research articles were identified, screened, and summarized based on inclusion criteria for heat stress in a confinement system. Data was obtained from the Web of Science. A total of 604 scientific articles published between 2000 and April 2022 were considered. Data was then analyzed using Microsoft Excel and CiteSpace. The results pointed to a significant increase in studies on heat stress in lactating cows housed in confinement systems. The main research areas were Agriculture, Dairy Animal Science and Veterinary Sciences. The USA showed the highest concentration of studies (31.12%), followed by China (14.90%). Emerging themes included heat stress and behavior. The most influential journals were the Journal of Dairy Science and the Journal of Animal Science. The top authors were L. H. Baumgard and R. J. Collier. The leading institutions were the Chinese Academy of Agricultural Sciences, followed by the State University System of Florida and the University of Florida. The study maps the significant research domains on heat stress of lactating cows in confinement systems, discusses implications and explanations and highlights emerging trends.

Research and application of a new multilevel fuzzy comprehensive evaluation method for cold stress in dairy cows

Effective and comprehensive evaluation of cold stress is critical for healthy dairy cow breeding in the winter. Previous studies on dairy cow cold stress have considered thermal environmental factors but not physiological factors or air quality. Therefore, this study aimed to propose a multilevel fuzzy comprehensive evaluation (FCE) method for cold stress in dairy cows based on the analytic hierarchy process (AHP) and a genetic algorithm (GA). First, the AHP was used to construct an evaluation index system for cold stress in dairy cows from 3 dimensions: thermal environment (temperature, relative humidity, wind speed, and illumination), physiological factors (respiratory rate, body surface temperature), and air quality [NH₃, CO₂, inhalable particulate matter (PM₁₀)]. Second, the consistency test of the judgment matrix was transformed into a nonlinear constrained optimization problem and solved using the GA. Next, based on fuzzy set theory, the comment set and membership function were established to classify the degree of cold stress into 5 levels: none, mild, moderate, high, and extreme. Then, the degree of cold stress in cows was obtained using multilevel fuzzy comprehensive judgment. To investigate the effect of illumination indicators on cold stress in dairy cows, 24 prelactation cows from the south and north sides were selected for a 117-d comprehensive cold stress evaluation. The results showed that the mean mild cold stress durations were 605.3 h (25.22 d) and 725.5 h (30.23 d) and the moderate cold stress durations were 67.2 h (2.8 d) and 96 h (4.0 d) on the south and north sides, respectively. Simultaneously, generalized linear mixed model showed that there were significant correlations between the daily cold stress duration and milk yield, feeding time, lying time, and active steps in the cows on both sides. This method can reasonably indicate cow cold stress conditions and better guide cold protection practices in actual production.

Heat stress in a temperate climate leads to adapted sensor-based behavioral patterns of dairy cows

Most research on heat stress has focused on (sub)tropical climates. The effects of higher ambient temperatures on the daily behavior of dairy cows in a maritime and temperate climate are less studied. With this retrospective observational study, we address that gap by associating the daily time budgets of dairy cows in the Netherlands with daily temperature and temperature-humidity index (THI) variables. During a period of 4 years, cows on 8 commercial dairy farms in the Netherlands were equipped with neck and leg sensors to collect data from 4,345 cow lactations regarding their daily time budget. The time spent eating, ruminating, lying, standing, and walking was recorded. Individual cow data were divided into 3 data sets: (1) lactating cows from 5 farms with a conventional milking system (CMS) and pasture access, (2) lactating cows from 3 farms with an automatic milking system (AMS) without pasture access, and (3) dry cows from all 8 farms. Hourly environment temperature and relative humidity data from the nearest weather station of the Dutch National Weather Service was used for THI calculation for each farm. Based on heat stress thresholds from previous studies, daily mean temperatures were grouped into 7 categories: 0 = (<0°C), 1 = (0-12°C, reference category), 2 = (12-16°C), 3 = (16-20°C), 4 = (20-24°C), 5 = (24-28°C), and 6 = (≥28°C). Temperature-humidity index values were grouped as follows: 0 = (THI <30), 1 = (THI 30-56, reference category), 2 = (THI 56-60), 3 = (THI 60-64), 4 = (THI 64-68), 5 = (THI 68-72) and 6 = (THI ≥72). To associate daily mean temperature and THI with sensor-based behavioral parameters of dry cows and of lactating cows from AMS and CMS farms, we used generalized linear mixed models. In addition, associations between sensor data and other climate variables, such as daily maximum and minimum temperature, and THI were analyzed. On the warmest days, eating time decreased in the CMS group by 92 min/d, in the AMS group by 87 min/d, and in the dry group by 75 min/d compared with the reference category. Lying time decreased in the CMS group by 36 min/d, in the AMS group by 56 min/d, and in the dry group by 33 min/d. Adaptation to daily temperature and THI was already noticeable from a mean temperature of 12°C or a mean THI of 56 or above, when dairy cows started spending less time lying and eating and spent more time standing. Further, rumination time decreased, although only in dry cows and cows on AMS farms. With higher values for daily mean THI and temperature, walking time decreased as well. These patterns were very similar for temperature and THI variables. These results show that dairy cows in temperate climates begin to adapt their behavior at a relatively low mean environmental temperature or THI. In the temperate maritime climate of the Netherlands, our results indicate that daily mean temperature suffices to study the effects of behavioral adaptation to heat stress in dairy cows.