Livestock Research for Rural Development 31 (6) 2019 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Reproductive performance under intensive heat stress management on a large dairy farm in central Thailand

Suppada Kananub, John VanLeeuwen and Pipat Arunvipas

Department of Large Animals and Wildlife Clinical Science, Faculty of Veterinary Medicine, Kasetsart University, Nakhon Pathom, Thailand (73140)


The objective of this study was to determine factors associated with calving-to-conception interval (CCI) through a Cox proportional hazard analysis on a large commercial farm in central Thailand having an intensive management system to reduce heat stress, including 9 water sprinklings per day and high capacity fans. There were 184 cows calving between October 2015 and July 2017 available for the analyses. Breeding and conception started at 60 days post-partum, and 50% of the sample became pregnant within 150 days post-partum. The final model only identified milk yield as associated with the hazard of conception (p<0.0001), with an increasing hazard as milk yield rose, but only until 25 kg/cow/day. In conclusion, the large proportion of cows getting pregnant in the early post-partum period, within the oppressive environmental heat of Thailand, demonstrated that the intensive cooling management program was able to keep well-functioning reproductive systems in early lactation.

Keywords: dairy cow, cox proportional hazard, hazard of conception, heat and humid area


Reproductive problems of dairy cattle have multifactorial causes related to reproductive management and uterine and ovarian health. Nutritional factors include dry matter intake (DMI), dietary protein content, and negative-energy balance. Non-nutritional factors include stage of lactation, milk production, and environmental factors (Campanile et al 2003; National Research Council 2001; Suadsong 2012; LeBlanc 2013; Ghavi et al 2013). Regarding nutritional factors, several studies have shown that an imbalance in protein and energy feeding lead to excess urea in the body, having an impact on reproduction (Arunvipas et al 2008; National Research Council, 2001). Monitoring and controlling MUN could be helpful to adjust nutritional measures to improve reproductive performance (Arunvipas et al 2007; Melendez et al 2000).

High urea concentration in blood directly impairs the sperm, oocyte, and uterine environment, and indirectly causes an energy deficiency, exacerbating reproduction problems (Butler 1998; Nourozi et al 2010; Walsh et al 2011). Low concentration of urea also has a negative relationship to reproduction due to insufficient protein intake (Miettinen 1990; Nourozi et al 2010). Urea effects on reproduction have already been investigated in many geographic areas with diverse climatic conditions around the world, however a limited number of studies have been performed in the tropical countries such as Thailand where it is continuously humid and hot. There has been recent research on the relationship between the likelihood of conception and various risk factors, including MUN, among smallholder dairy farmers in Thailand where management of heat stress is often absent due to limited resources (Kananub et al 2018).

Regarding non-nutritional factors of reproductive success, milk yield, lactation status, breed, management practices, reproductive disorders, and environmental stress influence the reproductive performance (Samal 2013; Regassa and Ashebir 2016). Environmental heat stress is an important nutritional and reproductive concern for cattle in the tropical areas of the world (Dash et al 2016; Pongpiachan et al 2003; Suadsong, 2012). Increased body temperature is related to the impairment of ovarian function, heat expression, and embryo development (Samal 2013). Milk production is also negatively influenced by high temperatures, with reductions of 40-60% reported (Usman et al 2013). Shade, fans, misters, and sprinklers are reported to diminish the effects of heat on reproduction (Fournel et al 2017; Hansen and Arechiga 1999). However, there is limited information on the effects of heat abatement strategies among developing countries such as Thailand. The current study objective was to determine factors associated with calving-to-conception interval (CCI) in a large commercial Thai herd where there are systematic intensive procedures to reduce heat stress.

Materials and methods

This project obtained the permission of the Animal Ethics Committee by the Laboratory Animals, Veterinary Technology, Kasetsart University (ACKU 59-VET-031). The study was conducted on one commercial farm where the average herd size was approximately 100 milking cows in central Thailand. The weather in this area of Thailand is quite hot and humid because it is near the Gulf of Thailand; average daily temperature is 28.4 ̊C and never goes below 27 ̊C, with average humidity never below 73% (Meteorological Development Bureau 2015).

This study farm had a systemic intensive management program to reduce the effect of the heat stress on the cows throughout the year. While being fan-cooled, the cows were misted for 1.5 minutes out of each 5 minute block over a 45 minute period. This 45 minute cooling program occurred 9 times daily at 2 AM, 4 AM, 8 AM, 11 AM, 1.30 PM, 4 PM, 6 PM, 8 PM, and 10 PM. Cows from this farm were milked two times a day at 12 hour intervals. The study population on the farm was all cows calving during October 2015 to July 2017. After parturition, 30 ml of milk was taken one time per month from each cow until conception was confirmed, or the sample collection time came to one full year post-partum. Cow-level exclusion criteria were: 1) discarded (died or culled) cows before first milk sample collection; and 2) cows with an incomplete set of milk samples over the year post-partum or until they were confirmed pregnant.

At monthly herd health visits, questionnaires were completed and utilized for defining farm- and cow-level parameters through semi-structured questions about demographics, nutritional data, farm management, and reproductive indices. At these herd visits, pregnancy status was determined through ultrasound after 30 days post-breeding, and recheck examinations through rectal palpation occurred after 60 days post-breeding. There were differences in feed formulations depending on the milk yield of the heifers and cows: two rations were provided for the heifer group (<25 and ≥25 kg of milk) and three rations were provided for the cow group (<20; 20-30; and >30 kg of milk), as demonstrated in Table 1.

While monthly nutritional management data were available, budget restrictions allowed for only one analysis per formula during the study. The farm manager indicated that there was limited variation in ration formulations over the study period due to good feed inventory control. From the ration analyses, the following variables were included in the study dataset: crude protein, crude fiber, crude fat, energy, neutral detergent fiber (NDF), calcium, and phosphorus. Milk samples were sent to the laboratory of the Kasetsart University Veterinary Teaching Hospital in Nong Pho, Thailand. Milk constituents were determined by the CombiFoss ® and included: percent of fat, protein, lactose, total solids (TS), and solids not fat; somatic cell count (SCC); and MUN.

Table 1. Feed component percentages (on a dry matter basis) and specific nutrient assessments for heifer (H1 & H2) and cow (C1, C2 & C3) diets on one large dairy farm in Thailand in 2015-2017a






Feed component percentages

Total Mixed Ration












Mixed feed












Chopped corn






Specific nutrient assessments

Diet crude protein (kg/day)






Diet crude energy (Mcal/day)






a H1: heifers with <25 kg of milk; H2: heifers with ≥25 kg of milk; C1: cows with <20 kg of milk; C2: cows with 20-30 kg of milk; and C3: cows with >30 kg of milk

The calving-to-conception interval, the number of days from calving to last service diagnosed positive to pregnancy, was calculated and utilized as the outcome of interest for statistical analyses. Cows not confirmed pregnant after one year post-parturition were considered as censored in the dataset. A Cox proportional hazards model was used for statistical analysis, assessing factors associated with the hazard of conception. Both non-nutritional data and nutritional data were examined for their associations with the hazard of conception. Non-nutritional independent variables comprised of milk constituents on the test day closest to the insemination day, and included individual cow information, and farm management factors. The continuously distributed parameters (e.g. milk constituents) were included in the form of centered values, and they were checked for linear and non-linear associations by fractional polynomial analysis.

The process for building the final model included two steps. Each variable was first tested for significance individually, and a P-value of 0.2 was applied for variables to be eligible for full model analyses in the second multivariable modeling step. Manual backward elimination removed variables not associated with the hazard of conception. A P-value of 0.05 was used to assess the significant parameters remaining in the final model. Testing of biologically plausible 2-way interactions and confounding effects were performed as well. In the final steps of model comparisons, the best fitting model was considered using Akaike’s Information Criteria (AIC).

For model diagnostics, Schoenfeld residuals were used to prove the assumption of proportional hazards of continuous variables. Breeding season was graphed out by Kaplan-Meier survival curves. Cox-Snell residuals (CS) were utilized for evaluating the overall fit for the final model. In the interpretation part, the results present hazard ratios of significant parameters relating to the hazard of conception, a function of both conception and time (Dohoo et al 2009).


While 217 cows calved during the study period and were enrolled in the study, only 184 cows met the inclusion/exclusion criteria and were used in the statistical analysis of the study. A total of 751 observations from the 184 cows remained in the final dataset. For this study population of 184 cows, the average lactation number (SD) was 2.25 (1.57) with nearly 50% of the sampling group being in first parity. Average milk yield was 22 kg per cow per day.

Table 2. Parameters analyzed in the univariable Cox proportional
hazards analysis of calving-to-conception interval from 184 cows
of one large dairy farm in Thailand in 2015-2017





Body condition score




Lactation number




Milk yield (kg/day)




Calving season: Summer









Breeding season: Summer









 Illness a:No







Milk fat (%)




Milk protein (%)




Milk urea nitrogen (mg/dl)




Somatic cell counts b




F:P ratio c




P:E ratio d




aIllness during the breeding period ;b Dietary protein:energy ratio

Feed rations provided to the five cattle groups are presented in Table 1. The two heifer rations and two highest cow rations (by milk production) used total mixed ration (TMR) as the main nutritive source. Conversely, the main source of feed was mixed feed, cassava, and chopped corn for the lowest producing cow group. The TMR contained the following feeds: corn husk, corn silage, urea ensiled rice straw, sesame seed residual, cassava chip, and soybean meal.

Table 3. Final model of parameters associated with calving-to-conception
interval from 184 cows of one large dairy farm in Thailand in 2015-2017






Milk yield










About 90% (n=168) of the 184 cows were bred during the two-year study period, with 58% getting pregnant during the study period. More than 50% succeeded in conceiving before four months after parturition. About 45% of sampled cows calved in winter, another 25% in summer, and the rest in the rainy season. The percent of fat, protein, lactose, and TS in milk averaged (SD) 3.45 (0.91), 2.95 (0.32), 4.93 (0.37), and 12.1 (1.04), respectively. The geometric mean of SCC after back-transformation was slightly less than 100,000 cells/ml, while the mean (SD) of MUN was 17.5 (5.83) mg/dl.

Figure 1. Baseline hazard function of conception during the first year of lactation after
calving from 184 cows of one large dairy farm in Thailand in 2015-2017

Figure 1 demonstrates that the hazard of conception increased from 60 to 100 days post-partum. After 100 days, the hazard of conception had little change until 150 days post-partum when the hazard of conception reduced. The hazard of conception was erratic after 150 days post-parturition. The following variables were univariably associated with the hazard of conception: lactation number, milk yield, and protein:energy ratio in the feed (Table 2).

Figure 2. Hazard ratios associated with conception for milk yield (kg/day) in the final
model of 184 cows of one large dairy farm in Thailand in 2015-2017

Milk yield was the only variable linearly related to hazard of conception in the final model (p<0.0001). In addition, milk yield was transformed to a curvi-linear association with the addition of a quadratic milk variable and this added variable was also found to be meet the significance level. The AIC results for the linear model was 941.0, while the AIC for the curvi-linear model was 922.3, showing that the curvi-linear model was a better fit and explained more of the data variation.(Table 3). Cows producing 20-25 kg of milk per day were more likely to achieve success in breeding than cows producing lower and higher volumes milk (Figure 2). However, the error bars, representing 95%CI of the estimated hazards, were larger among cows producing the highest milk volumes compared to moderate and low milk volumes.


There has been recent research on the relationship between the likelihood of conception and various risk factors, including MUN, among smallholder dairy farmers in Thailand where management of heat stress is often absent due to limited resources (Kananub et al 2018). The current study aimed to determine these relationships on a large Thai farm with the intensive cooling program for abating the oppressive environmental heat affecting cows in Thailand. As expected, the likelihood of conception increased quite quickly during the first three months of the breeding period, leveled off for a couple of months, and then fluctuated after that period, likely due to small numbers of cows getting bred after 150 days post-partum and a number of those cows being repeat breeders. The large number of cows getting pregnant in the early post-partum period demonstrated that the intensive cooling management program was able to keep well-functioning reproductive systems. In Israel, where a cooling system with sprinkling and fanning was performed for reducing heat stress, not only did the production level increase, but also reproduction was improved (Flamenbaum and Galon, 2010; Thatcher et al 2010).

The association of milk yield with the hazard of conception was curvi-linear, with the lowest fertility occurring in lower and higher milk yields. The result of lower milk yield being associated with lower hazard of conception was primarily a function of repeat breeder cows in late lactation that had a low milk yield. Elsewhere, there are reports of an adverse influence of milk yield on fertility (Ansari-Lari et al 2010; Madouasse et al 2010). Stadnik et al (2017) stated that a long days open was found in the cows producing high milk production. However, Buckley et al (2003) found a positive linear association between milk yield and pregnancy rate, with the achievement of a positive-energy balance during the breeding period suggested as the cause of that relationship. High milk production, especially in the range above 25 kg per cow per day, usually leads to negative-energy balance, resulting in reproductive problems (Ansari-Lari et al 2010; Fulkerson et al 2001). Good management of nutrition, breeding, and environmental comfort have crucial effects on fertility. TMR can provide consistent CP levels compared to other methods of feeding, leading to less fluctuation of MUN and its potential impact on reproduction (Bargo et al 2002). Moreover, it was likely that NEB had an effect on reproduction in our study, as shown through the lower likelihood of conception among high producing cows (Amundson et al 2016; Tamminga 2006; Van Saun 2014).



Amundson O L, Larimore E L, McNeel A K, Chase C C, Cushman R A, Freetly H C and Perry G A 2016 Uterine environment and pregnancy rate of heifers with elevated plasma urea nitrogen. Animal Reproduction Science, 173, 56-62.

Ansari-Lari M, Kafi M, Sokhtanlo M and Ahmadi H 2010 Reproductive performance of Holstein dairy cows in Iran. Tropical Animal Health and Production, 42, 1277-1283.

Arunvipas P, VanLeeuwen J A, Dohoo I R, Keefe G P, Burton S A and Lissemore K D 2008 Relationships among milk urea-nitrogen, dietary parameters, and fecal nitrogen in commercial dairy herds. Canadian Journal of Veterinary Research, 72, 449-453.

Arunvipas P, VanLeeuwen J A, Dohoo I R, Leger E R, Keefe G P, Burton A S and Lissemore K D 2007 Milk urea-nitrogen negatively affected first-service breeding success in commercial dairy cows in Prince Edward Island, Canada. Preventive Veterinary Medicine, 82, 42-50.

Bargo F, Muller L D, Delahoy J E and Cassidy T W 2002 Performance of high producing dairy cows with three different feeding systems combining pasture and total mixed rations. Journal of Dairy Science, 85, 2948-63.

Buckley F, O’Sullivan K, Mee J F, Evans R D and Dillon P 2003 Relationships among milk yield, body condition, cow weight, and reproduction in spring-calved holstein-friesians. Journal of Dairy Science, 86, 2308-2319.

Butler W R 1998 Review: Effect of protein nutrition on ovarian and uterine physiology in dairy cattle. Journal of Dairy Science, 81, 2533-2539.

Campanile G, Di Palo R, Infascelli F, Gasparrini B, Neglia G, Zicarelli F and D'Occhio M J 2003 Influence of rumen protein degradability on productive and reproductive performance in buffalo cows. Reproduction Nutrition Development, 43, 557-566.

Dash S, Chakravarty A K, Singh A, Upadhyay A, Singh M and Yousuf S 2016 Effect of heat stress on reproductive performances of dairy cattle and buffaloes: A review. Veterinary World, 9, 235-244.

Dohoo I R, Martin S W and Stryhn H 2009 Veterinary epidemiologic research. VER, Inc.

Flamenbaum I and Galon N 2010 Management of heat stress to improve fertility in dairy cows in Israel. Journal of Reproduction and Development, 56, 36-41.

Fournel S, Ouellet V and Charbonneau E 2017 Practices for Alleviating Heat Stress of Dairy Cows in Humid Continental Climates: A Literature Review. Animals, 7, 1-23.

Fulkerson W J, Wilkins J, Dobos R C, Hough G M, Goddard M E and Davison T 2001 Reproductive performance in Holstein-Friesian cows in relation to genetic merit and level of feeding when grazing pasture. Animal Science, 73, 397-406.

Ghavi H-Z N, Mohit A and Azad N 2013 Effect of temperature -humidity index on productive and reproductive performances of Iranian Holstein cows. Iranian Journal of Veterinary Research, 14, 106-112.

Hansen P J and Are´chiga C F 1999 Strategies for Managing Reproduction in the Heat-Stressed Dairy Cow. Journal of Animal Science, 77, 36-50.

Kananub S, VanLeeuwen J and Arunvipas P 2018 Association between milk urea nitrogen and first service conception in smallholder dairy farms under heat and humidity stress. Veterinary World, 11, 1604–1608.

LeBlanc S J 2013 Is a high level of milk production compatible with good reproductive performance in dairy cows? Animal Frontier, 3, 84-91.

Madouasse A, Huxley J N, Browne W J, Bradley A J, Dryden I L and Green M J 2010 Use of individual cow milk recording data at the start of lactation to predict the calving to conception interval. Journal of Dairy Science, 93, 4677-4690.

Melendez P, Donovan A and Hernandez J 2000 Milk urea nitrogen and infertility in florida holstein cows. Journal of Dairy Science, 83, 459-463. Meteorological Development Bureau 2015 The Climate of Thailand, Bangkok, Thailand.

Miettinen P V 1990 Metabolic balance and reproductive performance in Finnish dairy cows. Zentralblatt Fur Veterinarmedizin. Reihe A, 37, 417-424.

National Research Council 2001 Nutrient Requirements of Dairy Cattle (7th ed.). Washington, D.C.: National Academies Press. 2001.pdf

Nourozi M, Moussavi A H, Abazari M and Zadeh M R 2010 Milk urea nitrogen and fertility in dairy farms. Journal of Animal and Veterinary Advances, 9, 1519-1525.

Pongpiachan P, Rodtian P and Ōta K 2003 Effects of Tropical Climate on Reproduction of Cross- and Purebred Friesian Cattle in Northern Thailand. Asian-Australasian Journal of Animal Sciences, 16, 952-961.

Regassa T and Ashebir G 2016 Major factors influencing the reproductive performance of dairy farms in Mekelle City, Tigray, Ethiopia. Journal of Dairy, Veterinary & Animal Research, 3, 145-149.

Samal L 2013 Heat Stress in Dairy Cows - Reproductive Problems and Control Measures. International Journal of Livestock Research, 3, 14-23.

Stadnik L, Atasever S and Ducháček J 2017 Effects of body condition score and daily milk yield on reproduction traits of Czech Fleckvieh cows. Animal Reproduction, 14, 1264-1269.

Suadsong S 2012 Alleviating Heat Stress Leads to Improved Cow Reproductive Performance. In Milk Production - An Up-to-Date Overview of Animal Nutrition, Management and Health. InTech.

Tamminga S 2006 The effect of the supply of rumen degradable protein and metabolisable protein on negative energy balance and fertility in dairy cow. Animal Reproduction Science, 96, 227-239.

Thatcher W W, Flamenbaum I, Block J and Bilby T R 2010 Interrelationships of heat stress and reproduction in lactating dairy cows In High Plains Dairy Conference, 45-60.

Usman T, Qureshi M S, Yu Y and Wang Y 2013 Influence of various environmental factors on dairy production and adaptability of Holstein cattle maintained under tropical and subtropical conditions. Advances in Environmental Biology, 7, 366-372.

Van Saun R J 2014 Dairy nutrition. In R J Van Saun (Eds.), The Veterinary clinics of North America. Food animal practice, Elsevier

Walsh S W, Williams E J and Evans A C O 2011 A review of the causes of poor fertility in high milk producing dairy cows. Animal Reproduction Science, 123, 127-138.

Received 6 February 2019; Accepted 4 May 2019; Published 4 June 2019

Go to top