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Pregnancy loss and calf death can cost dairy producers more than $230 million annually. While methods involving nutrition, climate, and health management to mitigate pregnancy loss and calf death have been developed, one potential influence that has not been well examined is the reproductive microbiome. I hypothesized that the microbiome of the reproductive tract would influence heifer fertility and calf gut microbial development. The objectives of this dissertation were: 1) to examine differences in phenotypes related to reproductive physiology in virgin Holstein heifers based on outcome of first insemination, 2) to characterize the uterine microbiome of virgin Holstein heifers before insemination and examine associations between uterine microbial composition and fertility related phenotypes, insemination outcome, and season of breeding, and 3) to characterize the various maternal and calf fecal microbiomes and predicted metagenomes during peri-partum and post-partum periods and examine the influence of the maternal microbiome on calf gut development during the pre-weaning phase. In the first experiment, virgin Holstein heifers (n = 52) were enrolled over 12 periods, on period per month. On -3 d before insemination, heifers were weighed and the uterus was flushed. Flush pH and glucose concentration were measured. Blood was collected from coccygeal vessels on d -3, 15, 18, 21, 24, 27, and 30 relative to insemination and serum progesterone concentration was measured. Ultrasound measurements of dominant follicle diameter and corpus luteum volume. Insemination outcome was determined on d 30 using ultrasound and pregnancy was checked on d 42, 56, 70, and 84. Heifers were clustered based on outcome of insemination at d 30 (not pregnant, NP30, n = 24; pregnant, PS30, n = 28), d 84 (not pregnant, NP84, n = 24; pregnant but lost before d 84, PL84, n = 2; successfully pregnant through d 84, PS84, n = 26). Differences in phenotypes were assessed based on insemination outcome at d 30 and d 84. Weight was greater in NP30 heifer than PS30 heifers. Progesterone was greater in PS30 and PS84 heifers than NP30 or NP84 heifers on d -3 and 18 to 30 and CL volume was greater in PS30 and PS84 heifers than NP30 and NP84 heifers on d 21 and 30. To summarize, traits related to pregnancy maintenance were different in virgin Holstein heifers based on first insemination outcomes and might be able to be used to predict heifer reproductive performance. Uterine flushes were examined in a subset of heifers (n = 28) based on insemination outcome and period. This subset was also clustered based on season (spring, n = 3; summer, n = 12; fall, n = 8; winter, n = 5). From this subset of heifers, DNA was extracted from uterine flush and 16S amplicons of the V4 region underwent 250 paired-end sequencing via Illumina NovaSeq 6000. Filtered reads were clustered into operational taxonomic units using a 97% similarity and assigned taxonomy using the SSURNA Silva reference version 132. Alpha and beta diversity were measured and differences in alpha and beta diversity measurements were analyzed based on insemination outcome at d 30 or d 84 and season of breeding. Differential abundance analyses were performed at the phylum and genus taxonomic ranks based on insemination outcome at d 30 or d 84 and season of breeding. Bacterial richness was reduced in PL84 heifers than NP84 and PS84 heifers and reduced in heifers bred in spring than those bred in other seasons. Bacterial community structure was different based on insemination outcome at d 30 and d 84 using unweighted Unifrac distances and was different based on season of breeding using weighted Unifrac distances. We observed an increase of Bacteroidetes in PS30 and PS84 heifers compared to NP30 and NP84 heifers. Ureaplasma and Ruminococcus had an increased abundance in PS30 and PS84 heifers than NP30 and NP84 heifers, while Afipia and Gardnerella had an increased abundance in NP30 and NP84 heifers than PS30 and PS84 heifers. Prevotella and Ruminococcus had a reduced abundance in summer bred heifers than winter bred heifers. Proteobacteria had a moderate negative correlation with -3 d progesterone (rp = -0.42) and Actinobacteria had a moderate negative correlation with fetal growth rate (rp = -0.66). Uterine microbiome of virgin Holstein heifers differed based on insemination outcomes and season of breeding and might be a new phenotype to indicate heifer fertility. In the second experiment, multiparous Holstein cows (n = 12) were placed in individual box stalls 14 d before expected calving. Sterile swabs were used to collect samples from the posterior vagina of the dam approximately 24 h before calving, dam feces, dam oral cavity, and colostrum within 1 h after calving, and cotyledonary placenta within 6 h after calving. Calves (n = 12; bulls = 8, heifers = 4) were isolated immediately after parturition to prevent environmental contamination. Colostrum was fed to calves using a clean bottle that was assigned to the calf for the duration of the study. Calves were individually housed for 60 d until weaning. Sterile swabs were used to collect calf fecal samples at birth, 24 h, 7 d, 42 d, and 60 d of age. A subset of calf-dam pairs (n = 6; bulls = 3, heifers = 3) were selected and DNA was extracted from all samples. Amplicons covering V4-V5 16S rDNA regions were generated using extracted DNA and sequenced using 300 bp paired end sequencing via Illumina MiSeq. Sequences were aligned into operational taxonomic units using the 97% Greengenes reference database. Spearman correlations were performed between maternal and calf fecal microbiomes. Negative binomial regression models were created for genera in calf fecal samples at each time point using genera in maternal microbiomes. Metagenomes were predicted, collapsed into gene pathways and differences in predicted metagenomes were analyzed within STAMP (Statistical Analysis of Metagenomic Profiles). We determined that Bacteroidetes dominated the calf fecal microbiome at all time points (relative abundance ≥ 42.55%) except for 24 h post-calving, where Proteobacteria were the dominant phylum (relative abundance = 85.10%). Colostrum and placenta had low diversity within samples and clustered independently from fecal samples. Each maternal microbiome was a significant predictor for calf fecal microbiome during at least 2 time points. Genes for infectious disease and neurodegenerative disease were greater in colostrum and 24 h calf fecal samples compared to other samples. Results indicated that no one maternal microbiome was a major influence on calf fecal microbiome inoculation and development. Instead, calf fecal microbial development stems from various maternal microbial sources. Overall, the reproductive microbiome was predictive of heifer pregnancy outcomes and calf fecal microbial development. The virgin heifer uterine microbiome could be used to predict fertility and adaptation to heat stress, but further research including a larger group of pregnancy loss is needed. Maternal microbiomes from the reproductive tract, colostrum, oral cavity, and feces could all be used to predict calf microbial development, but more research including other maternal microbiomes and environmental microbial contributions is needed. However, the results from this dissertation indicate reproductive microbiome composition is a trait that might be predictive of dairy cattle performance. / Doctor of Philosophy / The ability of a cow to become pregnant and a calf to thrive after birth are crucial to successful dairy farm operations. Recent evidence in humans has shown bacteria in the reproductive tract can influence maternal fertility and the bacterial community of newborns, an indicator of early health. This same relationship might exist in dairy cattle. I propose that specific traits related to fertility and the bacterial community in the reproductive tract of dairy cattle influences their ability to become pregnant and influences the bacterial community developing in calves after their birth. In my first experiment, I collected samples of uterine fluid from cattle that had never been pregnant before the first time they would be bred. I also collected blood samples before and after breeding to measure hormone levels as well as measurements of portions of reproductive tract using an ultrasound. Using a specific portion of DNA that is similar across all bacteria, I identified the bacterial community in the collected uterine fluid. Cattle were grouped based on breeding outcome (not pregnant, pregnant but lost, or kept pregnancy) and season of breeding. Differences in various traits and bacterial communities were examined based on breeding outcome and season. I found that traits like hormone levels in the blood and size of structures on the reproductive tract, and uterine bacterial community all differed based on breeding outcome. We also found that uterine bacterial community also differed based on season of breeding. These results could be used to predict if a cow will become pregnant before they are ever bred, but more research is needed. In our second experiment, we collected samples from the reproductive tract, milk, mouth, and feces of cows immediately after they gave birth. We then collected samples from their calves right at birth as well as at various time points during their early life. Using the same section of DNA used during the first experiment, we identified the bacterial community composition from the various maternal and calf samples. We then identified correlations between maternal and calf bacteria and used a mathematical model to see if the maternal bacteria could predict bacteria in the calf. We found that the various maternal bacteria could predict calf bacteria throughout the calves early life. While an experiment using a larger group of cows and calves is needed, our results indicate that the maternal bacteria could be used to predict calf bacteria and may help determine which calves are more likely to become sick than others. Overall, we found that the bacteria in the reproductive tract could be used to predict ability to become pregnant and calf bacterial development. The incorporation of this bacterial community as a trait on farms could help reduce pregnancy loss and calf illness, but further research examining how the bacteria interact with the animal is needed.

Colostrum quality is critical to calf health as colostrum provides immunoglobulins (Ig) that are critical for a calf's immune system. Despite close management of factors known to affect colostrum production, 23% of dairy cows are still producing inadequate volume or quality of colostrum, which causes calf death and poor performance. Therefore, the objectives of this dissertation are to investigate factors that affect colostrum production and methods to improve colostrum yield and quality. Based on previous literature showing that photoperiod impacts milk yield post-calving in dry cows and that light intensity and temperature-humidity index (THI) impact colostral Ig content, I hypothesized that photoperiod and THI during the dry period impact colostrum yield and quantity in Holstein and Jersey cows. The first study evaluated the isolated effect of photoperiod on colostrum production. Dry cows were housed in a temperature-controlled barn and exposed to either short-day photoperiod (SDPP) of 8 h of light per day or long-day photoperiod (LDPP) of 16 h of light per day for the entire dry period until calving. Altered photoperiod had no effect on colostrum yield, Ig content or other components of colostrum. However, Jersey cows had a higher Brix score, fat, protein, IgA and IgM. After calving, milk production was not affected by photoperiod treatment, likely due to cows being exposed to an irregular lighting scheme. The second study evaluated the combined effects of photoperiod and THI during the dry period on colostrum production and broke cows into a bottom (1), middle (2) and top (3) third based on their photoperiod exposure. Holstein cows produced more colostrum than Jersey cows in each photoperiod category. For both breeds, photoperiod category 1 cows produced less colostrum than cows in photoperiod category 2 and 3. Brix score did not differ by breed but differed by farm and photoperiod category with farm 1, photoperiod category 3 cows having increased Brix score compared to farm 2, photoperiod category 1 and 2 cows. Colostrum components for Jersey cows did not differ by photoperiod category. However, colostrum volume, Brix score, protein and SNF were all impacted by THI and (or) photoperiod variables in predictive modeling. This indicates that colostrum yield and quality in Holstein and Jersey cows are similarly impacted by both photoperiod exposure and THI exposure during the last two months of pregnancy. Therefore, farmers can utilize short-day photoperiod during the dry period during times of moderate THI to improve milk production post-calving without negatively impacting colostrum production. However, future studies are needed to tease out THI and photoperiod impact on colostrum on a large scale in order to improve dry cow management and colostrum production. / Doctor of Philosophy / Cows do not transfer antibodies or immunoglobulins to their offspring during gestation and calves are born deficient in antibodies that are critical for a healthy immune system. Instead, cows transfer antibodies into the first milk that they produce, termed colostrum. After calves ingest the colostrum, the antibodies are absorbed by the small intestine and enter circulation where they can traverse the body to identify and neutralize pathogens. To ensure adequate immune system function, calves must ingest 150 – 200 g of antibodies within 6 h of birth. However, around 23% of cows do not produce enough antibodies in their colostrum or have low colostrum yield overall. 19% of calves do not ingest enough antibodies and will die or have negative health effects that persist into adulthood as a result. Therefore, the objective of this dissertation is to investigate methods to improve colostrum production in cows to improve calf health and reduce calf deaths. While several factors that affect colostrum production have been identified and are managed for optimum colostrum production, there is still high variation in colostrum production from cow to cow. Based on previous research showing that colostrum yield varies seasonally and that daily light exposure, or photoperiod, can impact milk production, I hypothesized that photoperiod and temperature-humidity index (THI) during the last two months of pregnancy impact colostrum production in cows. The first study was designed to isolate the effect of photoperiod on colostrum, by housing Holstein and Jersey cows in a temperature-controlled barn during the last two months of pregnancy and exposing them to varying daylengths. Cows were exposed to either a short-day photoperiod of 8 h of light per day or a long-day photoperiod of 16 h of light per day. When the cows gave birth, they were milked and the amount of colostrum produced and the components of the colostrum were evaluated. A Brix refractometer, which is widely used by farmers to estimate colostrum quality as it is an on-farm tool that estimates colostrum antibody content, was also used in this study. Cows were returned to ambient photoperiod and milk, fat and protein production were tracked for 15 weeks. I found that altered photoperiod had no effect on colostrum yield, antibody content or other components of colostrum. However, Jersey cows had a higher Brix score, fat, protein, antibody IgA and antibody IgM. After calving, milk production was not affected by photoperiod treatment, likely because of irregular lighting exposure after calving. These data indicate that photoperiod alone may not be causing the seasonal variations associated with colostrum production. Therefore, a second study was conducted to evaluate the effects of photoperiod and THI together on subsequent colostrum production in Holstein and Jersey cattle by month. Colostrum production and weather data were collected for cows housed in ambient photoperiod and THI for the last two months of pregnancy from two different farms. Cows were divided into a bottom (1), middle (2) and top (3) third based on their photoperiod exposure. Holstein cows produced more colostrum than Jersey cows in each photoperiod category. For both breeds, photoperiod category 1 cows produced less colostrum than cows in photoperiod category 2 and 3. Brix score did not differ by breed but differed by farm and photoperiod category with farm 1, photoperiod category 3 cows having increased Brix score compared to farm 2, photoperiod category 1 and 2 cows. Colostrum components for Jersey cows did not differ by photoperiod category. However, colostrum volume, Brix score, protein and SNF were all impacted by THI and (or) photoperiod variables in predictive modeling. This indicates that colostrum yield and quality in Holstein and Jersey cows are similarly impacted by both photoperiod exposure and THI exposure during the last two months of pregnancy. Data from these studies are the first to show the isolated effect of photoperiod on colostrum production in Jersey cows and the second showing data on Holstein cows. Recommendations have already been made to dairy producers to limit photoperiod exposure during the last two months of pregnancy in order to increase milk production post-calving. This study shows that limiting photoperiod will not compromise colostrum production in cows. However, I also found that colostrum production is also impacted by THI exposure and that colostrum yield and quality have inverse relationships with photoperiod and THI exposure. Whereas colostrum yield increases with increased photoperiod and THI, Brix score decreases. Therefore, managing for increased colostrum quality is compromised by colostrum yield. This study also found that the widely accepted indirect measure of antibody content, the Brix score, was not a reliable estimate of antibody content and instead, a better indicator of solids content of colostrum. In conclusion, these data show that photoperiod alone does not impact colostrum production, rather a combined effect of photoperiod and THI are responsible for seasonal variation in colostrum and differences between breeds of cow are also evident. In addition, Brix score may not be the best indicator of colostrum quality and could be replaced by more reliable methods by dairy farmers to ensure that adequate colostrum is fed to calves. Future studies will need to explore differences in response to photoperiod vs. THI alteration and explore genetic associations with colostrum production, to identify which genes are associated with increased colostrum quality in Jersey cows so that we may genetically select for increased colostrum quality.

It is the aim of this investigation to determine through routine checks if the bacterial count in the milk from Brooks Dairy Company is high and if so to determine the source. If it is found that the laboratory plate counts are unnecessarily high, it is the further purpose of this paper to make recommendations for improvements in the quality of milk produced by this dairy plant.

Milk quality has continued to improve over the last several decades in the US, but still remains to be a problem for dairy producers in the southeast (SE) US. The purpose of these analyses was to evaluate associations between parlor equipment function, milking procedures, and bulk tank somatic cell count (BTSCC) and bulk tank standard plate count (BTSPC) on SE US dairy farms. Data from dairies in Virginia (n = 96), Kentucky (n = 96), Tennessee (n = 84), and Mississippi (n = 7) were collected at a single visit for each farm. Monthly BTSCC and BTSPC data were retrieved from state regulatory offices for (n = 263) farms, and averaged over the 12 months prior to each farm visit and used as the dependent variables in each analysis in a backwards elimination regression model. Increased herd size was associated with lower BTSCS, but higher BTSPC. Utilization of an internal teat sealant was associated with lower BTSCS. Farms that housed cows exclusively on pasture had greater BTSCS than farms that keep lactating cows in confinement with no pasture access. Utilization of a freestall for lactating cow housing was associated with lower BTSCS. The likelihood of future dairy operation in 10 years as reported by the farm owner or manager influenced BTSPC. Beginning water temperature of the detergent wash cycle was found to influence BTSCS. These findings suggest that the most influential variables explaining milk quality are herd demographic information and farmer perceptions as well as a few management variables such as the use of an internal teat sealant and beginning water temperature of the detergent wash cycle. These findings suggest that farmer perceptions and attitudes may be influencing milk quality more than previously thought. Further research is needed to evaluate social factors that could be influencing milk quality. Milking equipment function has improved substantially over the last several decades and was not found to significantly influence milk quality among the evaluated SE US dairies in these analyses. Milking procedures such as pre- and post-milking teat disinfection are widely accepted by most dairies in the US. Minimal differences were found between milking procedures such as teat disinfectant active ingredient or using paper towels versus cloth towels suggesting that these factors may not be the most influential factors influencing milk quality. / MS / Milk quality has continued to improve over the last several decades in the US, but still remains to be a problem for dairy producers in the southeast (SE) US. Milk quality can be measured by somatic cell count and bacteria counts in raw bulk tank milk. Several factors influence these measures, but some of the most important factors are associated with properly functioning milking equipment and milking procedures. The purpose of these analyses was to evaluate farm demographics, parlor equipment function, and milking procedures, and their association with bulk tank somatic cell count (BTSCC) and standard plate count (BTSPC) on SE US dairy farms. Data from dairies in Virginia (n = 96), Kentucky (n = 96), Tennessee (n = 84), and Mississippi (n = 7) were collected at a single visit for each farm. Monthly BTSCC and BTSPC data were retrieved (n = 263) from state regulatory offices and averaged over the 12 months prior to each farm visit and used as the dependent variables in each analysis in a backwards elimination regression model. Increased herd size was associated with lower BTSCS, but higher BTSPC. Utilization of an internal teat sealant was associated with lower BTSCS. Farms that housed cows exclusively on pasture had greater BTSCS than farms that keep lactating cows in confinement with no pasture access. Utilization of a freestall for lactating cow housing was associated with lower BTSCS. The likelihood of future dairy operation in 10 years as reported by the farm owner or manager influenced BTSPC. Beginning water temperature of the detergent wash cycle was found to influence BTSCS. These findings suggest that the most influential variables explaining milk quality are herd demographic information and farmer perceptions as well as a few management variables such as the use of an internal teat sealant and beginning water temperature of the detergent wash cycle. These findings suggest that farmer perceptions and attitudes may be influencing milk quality more than previously thought. Further research is needed to evaluate social factors that could be influencing milk quality. Milking equipment function has improved substantially over the last several decades and was not found to significantly influence milk quality among the evaluated SE US dairies in these analyses. Milking procedures such as pre- and post-milking teat disinfection are widely accepted by most dairies in the US. Minimal differences were found between milking procedures such as teat disinfectant active ingredient or using paper towels versus cloth towels suggesting that these factors may not be the most influential factors influencing milk quality.

Several lactic acid bacteria (LAB) of the Lactococcus, Lactobacillus, Leuconostoc and Pediococcus genera were screened for inhibition of food-borne pathogens and spoilage microorganisms in raw milk and dairy products. Listeria monocytogenes was killed by Lactococcus lactis subsp. lactis and Pediococcus pentosaceus due to their production of bacteriocin-type inhibitors. Staphylococcus aureus was not able to grow in raw milk at temperatures below 5°C even without LAB being present. Gram negative Salmonella enteritidis. Salmonella typhimurium and Escherichia coli, along with spoilage bacteria of the genus Pseudomonas were dramatically inhibited by a Lactobacillus species, designated AS-1, in raw and pasteurized milk as well as in cottage cheese. However, other LAB were not able to inhibit these organisms. Lactobacillus AS-1, did not produce hydrogen peroxide but carbon dioxide was produced. The AS-1 strain was a gram positive coccobacillus, catalase and oxidase negative and produced DL-lactic acid. It deaminated arginine and grew over a temperature range of 5°C to 45°C. It was also able to ferment glucose, galactose, fructose and lactose in addition to 17 other carbohydrates. High numbers (107 CFU/ml) of AS-1 were required to obtain complete inhibition of gram negative bacteria. A selective medium (ASLM) for Listeria monocytogenes was developed to follow the fate of this particular pathogen in association with LAB in raw milk; other selective media were not able to inhibit the growth of background flora of raw milk. ASLM was superior to four other media in allowing only the growth of the target pathogen. For the Lactococcus genus, a selective and differential agar medium (Alsan) was formulated to selectively allow growth of Lactococcus spp. and to differentiate between Lactococcus lactis subsp. lactis and the biovariety diacetylactis, based on citrate utilization. / Graduation date: 1993

The unique flavor of high quality Swiss cheese is difficult to reproduce in commercial market cheese. Swiss cheese flavor has never been duplicated or thoroughly understood. New techniques and advances in flavor research have enabled better definition and understanding of food flavors. Therefore, it was desirable to make a detailed investigation of Swiss cheese flavor. Neutral volatile flavor compounds were isolated from Swiss cheese fat by low-temperature low-pressure distillation. The compounds were separated by temperature programmed gas chromatography. Direct analysis of cheese fat and whole cheese from four domestic and two imported good flavored cheeses by gas entrainment and on-column trapping provided a further means of isolation of volatile flavor compounds in Swiss cheese. Gas chromatography in conjunction with rapid scan mass spectrometry and relative retention time data were used to identify compounds. Compounds positively identified by the distillation and on-column trapping techniques were as follows: methanol, ethanol, 1-propanol, 1-butanol, 2-pentanol, trans-2-hexene-1-ol, 2-phenylethanol, acetaldehyde, 2-methyl propanal, 2-methyl butyraldehyde, benzaldehyde, phenylacetaldehyde, acetone, butanone, 2-pentanone, 2-hexanone, 2-heptanone, 2-nonanone, 2-undecanone, 2-tridecanone, 2-pentadecanone, hexane, octane, 1-octene, nonane, 1-nonene, dodecane, pentadecane, toluene, α-pinene, methyl acetate, methyl hexanoate, methyl octanoate, methyl decanoate, ethyl propionate, ethyl butanoate, ethyl hexanoate, ethyl octanoate, ethyl decanoate, ethyl dodecanoate, butyl acetate, 3-methyl butyl acetate, γ-valerolactone, γ-dodecalactone, δ-octalactone, δ-decalactone, δ-dodecalactone, dimethyl sulfide, diacetyl, benzothiazole, o-dichlorobenzene, 1, 2, 4-trichlorobenzene, di-isobutyl adipate, and chloroform. Compounds tentatively identified include an aromatic hydrocarbon, pinane, α-fenchene, ethyl benzene, a di-methyl benzene, methyl benzoate, 2-phenyl-2-methyl butane, 5-methyl-5-ethyl decane, 3-methyl butyl octanoate, 2, 5-dimethyl tetra decane, methyl vinyl ether and 2-methyl propenal. The concentration of selected volatile compounds identified by the on-column trapping technique were determined by relating their peak heights to known quantities of compound. Average concentrations calculated from the mean values for all the six cheeses and expressed in parts per million were as follows: dimethyl sulfide. 0.107; diacetyl, 0.8; acetaldehyde, 1.4; acetone, 1.6; butanone, 0.3; 2-methyl butyraldehyde, 0.42; 2-pentanone, 0.98; 2-heptanone, 0.45; ethanol, 16.3; 2-butanol, 0.3; 1-propanol, 2.9; 1-butanol, 0.7; methyl hexanoate, 1.5; and ethyl butanoate, 0.6. Liquid-liquid partition chromatography and gas chromatography were utilized to determine quantitatively the major free, fatty acids in the six Swiss cheeses. 2-Methyl butyric acid was detected in all cheeses and varied from 9.0 to 100.0 mg/kg cheese. The other isomeric acid, 3-methyl butyric, was detected in only two cheeses. Formic acid was detected in only one cheese. No n-valeric or 2-methyl propionic acids were detected. A synthetic Swiss cheese flavor was prepared utilizing the data obtained in this investigation and that available in the literature for free amino acids. A satisfactory reproduction of Swiss cheese flavor could be achieved only if the mixture contained free fatty acids, volatile constituents, and free amino acids and was adjusted to the pH of natural cheese. / Graduation date: 1966

An experiment was conducted to study the effect of prolonged nutritional stress on the reproductive performance of twelve Holstein dairy heifers. Energy intake was reduced to 60% NE(m). The animals lost 20% of their body weight during energy restriction (97 days) and gained 29% during the high energy feeding (44 days). Estrous cycles were irregular, delayed, or ceased completely. The conception rate was only 25% during energy reduction. Cycles were reestablished and conception rate improved (67%) during the high energy feeding. Heifers were designated as fertile or infertile according to their success or failure to conceive during the energy reduction period. Serum thyroxine (T₄) levels were slightly decreased (P > .05) while triiodothyronine (T₃) levels were significantly depressed (P < .01) during energy restriction in both fertile and infertile heifers. Serum thyroxine levels were slightly increased (P > .05) in the fertile heifers, but significantly increased (P < .01) in the infertile heifers during high energy feeding. Serum triiodothyronine levels were significantly increased during high energy feeding in both fertile (P < .05) and infertile (P < .01) heifers. Concentrations of blood cortisol were relatively higher in the fertile than in the infertile heifers during the ad libitum and energy restriction periods. This suggests that the fertile heifers possessed elevated adrenal activity that the infertile heifers did not have. Concentrations of blood progesterone of the infertile heifers were severely depressed (P < .01) during the submaintenance feeding while those of the fertile group were not affected (P > .05). Blood glucose levels were significantly reduced during energy reduction and significantly increased during high energy feeding in both groups of heifers (P < .01 for infertile heifers). Blood glucose levels of the infertile heifers at time of insemination (period of energy restriction) were as low as their average levels of the period. Glucose levels of the fertile heifers at time of breeding (period of energy restriction) were greater than their mean concentration during that period and were similar to the mean levels of glucose during the ad libitum period. Low progesterone levels are indicative of ovarian inactivity under such stressful conditions. Adrenal inactivity, (as reflected by low cortisol secretion) and low blood glucose levels at time of insemination of the infertile heifers are probably associated with infertility during submaintenance feeding in dairy heifers.