Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows.

Estrus in dairy cattle varies in duration and intensity, highlighting the need for accurate and continuous monitoring to determine optimal breeding time. The objective of this study was to evaluate precision dairy monitoring technologies (PDMT) for detecting estrus. Estrus was synchronized in lactating Holstein cows (n = 109) using a modified G7G-Ovsynch protocol (last GnRH injection withheld to permit expression of estrus) beginning at 45 to 85 d in milk. Resumption of ovarian cyclicity at enrollment was verified by transrectal ultrasonography for presence of a corpus luteum. Cows were observed visually during 30 min (4 times per day) for behavioral estrus on d -1 to 2 (d 0 = day of estrus). Periods peri-estrus were defined by the temporal blood plasma progesterone patterns on d -5, -4, -3, -2, -1, 0, 2, 4, 6, and 8. Estrous detection by PDMT, an estrous behavior scoring system, and by visual observation of standing estrus were compared with the reference (gold) standard. Only 56% of cows that ovulated were observed standing by visual observation. Sensitivity and specificity for estrous detection were not different among all PDMT. Devices in this study measuring activity in steps, neck movement, high activity of head movement, or a proprietary motion index increased on the day of estrus 69 to 170% from the baseline before estrus. The change in rumination time on the day of estrus decreased for both neck and ear-based technologies (-2 to -16%). Temperature of the reticulorumen, vagina, and ear skin were not different on the day of estrus than day peri-estrus. Daily lying times decreased on average to 24.6% on the day of estrus for IceQube (IceRobotics Ltd., Edinburgh, Scotland). In contrast, lying time increased 15.5 and 33.1% for AfiAct Pedometer Plus (Afimilk, Kibbutz Afikim, Israel) and Track a Cow (ENGS Systems Innovative Dairy Solutions, Rosh Pina, Israel), respectively. All PDMT tested were capable of detecting estrus at least as effectively as visual observation. Four of the 6 PDMT that reported estrous alerts correctly detected 15 to 35% more cows than visual observation 4 times per day. Use of temporal progesterone patterns correctly identified more cows than visual observation alone. Dairy producers considering PDMT should focus on (1) the reference (gold) standard used to test efficacy of a device's alerts and (2) the device that will have the fewest false readings in their operations.

Behavioral and physiological changes around estrus events identified using multiple automated monitoring technologies.

This study included 2 objectives. The first objective was to describe estrus-related changes in parameters automatically recorded by the CowManager SensOor (Agis Automatisering, Harmelen, the Netherlands), DVM bolus (DVM Systems LLC, Greeley, CO), HR Tag (SCR Engineers Ltd., Netanya, Israel), IceQube (IceRobotics Ltd., Edinburgh, UK), and Track a Cow (Animart Inc., Beaver Dam, WI). This objective was accomplished using 35 cows in 3 groups between January and June 2013 at the University of Kentucky Coldstream Dairy. We used a modified Ovsynch with G7G protocol to partially synchronize ovulation, ending after the last PGF2α injection (d 0) to allow estrus expression. Visual observation for standing estrus was conducted for four 30-min periods at 0330, 1000, 1430, and 2200h on d 2, 3, 4, and 5. Eighteen of the 35 cows stood to be mounted at least once during the observation period. These cows were used to compare differences between the 6h before and after the first standing event (estrus) and the 2wk preceding that period (nonestrus) for all technology parameters. Differences between estrus and nonestrus were observed for CowManager SensOor minutes feeding per hour, minutes of high ear activity per hour, and minutes ruminating per hour; twice daily DVM bolus reticulorumen temperature; HR Tag neck activity per 2h and minutes ruminating per 2h; IceQube lying bouts per hour, minutes lying per hour, and number of steps per hour; and Track a Cow leg activity per hour and minutes lying per hour. No difference between estrus and nonestrus was observed for CowManager SensOor ear surface temperature per hour. The second objective of this study was to explore the estrus detection potential of machine-learning techniques using automatically collected data. Three machine-learning techniques (random forest, linear discriminant analysis, and neural network) were applied to automatically collected parameter data from the 18 cows observed in standing estrus. Machine learning accuracy for all technologies ranged from 91.0 to 100.0%. When we compared visual observation with progesterone profiles of all 32 cows, we found 65.6% accuracy. Based on these results, machine-learning techniques have potential to be applied to automatically collected technology data for estrus detection.

Stall cleanliness and stall temperature of two different freestall bases.

The objective of this study was to describe the differences in freestall cleanliness and stall temperature between a barn with Dual Chamber Cow Waterbeds (DCCW; Advanced Comfort Technology, Reedsburg, WI) and a barn with rubber-filled mattresses at the University of Kentucky Coldstream Dairy Research Farm from January 18, 2012, to May 3, 2013. Stall cleanliness was measured twice weekly (n=134) by the same 2 observers using a 0.91 m×0.91 m wire grid containing 128 equally sized rectangles (10.16 cm×5.08 cm). This grid was centered at the rear portion of the stall; a rectangle that was visibly wet or had any amount of feces present was defined as a dirty rectangle. Weekly stall temperature (n=66) was measured by the same observer during a.m. milkings in the same predetermined stalls. Feces and wet sawdust were removed from the stalls before stall temperatures were acquired. Temperatures were obtained using a handheld thermometer at 30.48 cm above the stall base as determined via dual laser measurements. Stall temperature was measured on the front, middle, and back of the stall first with clean sawdust and then with the sawdust removed from the stall and wiped clean with a towel. Daily temperature-humidity index (THI) was calculated using Kentucky climate data calculated through the University of Kentucky College of Agriculture via a data logger, located 5.63 km from the Coldstream Dairy Farm. Stall cleanliness was not different between the DCCW barn (26.09±0.89 rectangles) and the rubber-filled mattress barn (23.70±0.89 rectangles). Mean THI throughout the study was 64.39±0.82. Stall temperature was different among THI categories. Temperature-humidity index categories 1 (coldest), 2, 3, and 4 (warmest) had THI ranges of 22.94 to 50.77, 50.77 to 64.88, 64.88 to 78.75, and 78.75 to 101.59, respectively. Stall temperatures (°C; least squares means±SE) were 2.26±0.30, 8.86±0.30, 15.52±0.30, and 20.95±0.30 for THI categories 1 to 4, respectively. Stalls with rubber-filled mattresses had a lower temperature (°C) than DCCW with least squares means±SE of 10.52±0.21°C and 13.29±0.21°C, respectively. The DCCW were probably significantly warmer because water holds heat well. The DCCW may have more of a heat-insulating effect compared with rubber-filled mattresses.

Bio-effects of non-ionizing electromagnetic fields in context of cancer therapy.

Bio-effects mediated by non-ionizing electromagnetic fields (EMF) have become a hot topic of research in the last decades. This interest has been triggered by a growing public concern about the rapid expansion of telecommunication devices and possible consequences of their use on human health. Despite a feasibility study of potential negative impacts, the therapeutic advantages of EMF could be effectively harnessed for the treatment of cancer and other diseases. This review aims to examine recent findings relating to the mechanisms of action underlying the bio-effects induced by non-ionizing EMF. The potential of non-thermal and thermal effects is discussed in the context of possible applications for the induction of apoptosis, formation of reactive oxygen species, and increase of membrane permeability in malignant cells. A special emphasis has been put on the combination of EMF with magnetic nano-particles and ultrasound for cancer treatment. The review encompasses both human and animal studies.

Influence of breed, milk production, season, and ambient temperature on dairy cow reticulorumen temperature.

Automatic monitoring of core body temperature in dairy cattle could be useful for identification of illness, heat stress, general physiological stress, and estrus. The SmartBolus (TenXSys Inc., Eagle, ID) system used a reticulorumen bolus to automatically record and transmit dairy cow temperatures. The objective of this research was to characterize the influence of milk yield (MY), time of day, breed, ambient temperature (AT), and season on reticulorumen temperatures (RT) in lactating dairy cows. Continuous RT and AT were collected by SmartBolus transponders every 15 min (96 records per d) from 93 cows (65 Holstein, 18 crossbred, and 10 Jersey) for 615 d. Mean (±SD) daily RT, AT, and MY were 40.14±0.32°C, 12.20±10.61°C, and 33.85±8.67 kg, respectively. The maximum and minimum RT were recorded at 2330 and 1000 h, respectively. Ambient temperature increased RT. Summer RT was significantly greater than spring, fall, or winter RT. The effect of MY on RT varied by breed, season, and AT. Crossbred RT was significantly lower than Holstein RT after adjusting for MY. Crossbred RT responded less to increasing AT than did Holstein RT, potentially indicating improved heat tolerance among these crossbred dairy cows. Reticulorumen temperature increased more dramatically for cows with greater milk yield as AT increased, demonstrating that high-producing cows are more susceptible to heat stress than low-producing cows. These results could be useful in interpretation of automatic temperature system data, heat stress management, and genetic selection of heat-tolerant cows.

Differential regulation of estrous behavior and luteinizing hormone secretion by estradiol-17ß in ovariectomized dairy cows.

Holstein cows (n = 9) were used in an experiment to characterize the behavioral and endocrine responses to estradiol-17ß when administered at rates designed to maintain peripheral concentrations within a physiological range. Cows were pretreated with progesterone for 3 d. Three days after progesterone treatment was completed, each cow was assigned to one of five estradiol-17ß treatment groups (Doses 0 to 4), calculated to produce and maintain 0, 3, 6, 9, or 12 pg/mL in peripheral blood for 8 h. The experiment was conducted in eight replicates (with 3 to 7 cows each), with no dose repeated in any replicate. In each replicate, at least one additional cow was given an injection of estradiol-17ß (500 µg im, in a corn oil vehicle) to facilitate estrus detection. Estrus was detected by visual observation for 30 min at 4 h intervals. Estrus was defined as a cow that stood to be mounted at least twice during the 50 h interval over which estrus was observed. Jugular venous blood samples were collected at 2 h intervals throughout the infusion and observation periods for quantification of luteinizing hormone (LH). Cows that received the highest dose (Dose 4, n = 7) all showed estrus, whereas those that received the two lowest doses (Dose 0, n = 5; Dose 1, n = 6) did not. Over the course of the experiment, five cows received each dose at least once. Of these, three showed estrus at Doses 2, 3, and 4, whereas the other two showed estrus only at Dose 4. Therefore, individual cows differed in the amount of estradiol-17ß needed to induce estrus. There was a linear effect of dose on duration of estrus (P < 0.01). Estrus was shorter for Dose 2 (8.0 h) than for Dose 4 (18.4 h). The onset of estrus (after start of infusion) tended to be later for Dose 2 (20.0 h) than for Doses 3 and 4 (14.0 and 13.4 h, respectively; P = 0.15). Preovulatory-like surges of LH were induced in all cows at Doses 2, 3, and 4. Surges also were detected in 3 of 5 cows receiving Dose 1. The magnitude of the LH surge was less for Doses 1, 2, and 3 than for Dose 4 (P = 0.06). In contrast to the timing of estrus, the timing of the LH surge (after start of infusion) was not different among doses (P = 0.88). Thus, the hypothalamic centers responsible for regulating expression of estrus and secretion of LH responded differently to estradiol-17ß.

Effect of subluteal concentrations of progesterone on luteinizing hormone and ovulation in lactating dairy cows.

Two experiments were conducted to determine if administration of progesterone within a low, subluteal range (0.1-1.0 ng/mL) blocks the luteinizing hormone (LH) surge (experiments 1 and 2) and ovulation (experiment 2) in lactating dairy cows. In experiment 1, progesterone was administered to cycling, lactating dairy cows during the luteal phase of the estrous cycle using a controlled internal drug release (CIDR) device. CIDRs were pre-incubated in other cows for either 0 (CIDR-0), 14 (CIDR-14) or 28 days (CIDR-28). One group of cows received no CIDRs and served as controls. One day after CIDR insertion, luteolysis was induced by two injections of prostaglandin (PG) F(2alpha) (25 mg) at 12 h intervals. Two days after the first injection, estradiol cypionate (ECP; 3 mg) was injected to induce a LH surge. Concentrations of progesterone after luteolysis were 0.11, 0.45, 0.78 and 1.20 ng/mL for cows treated with no CIDR, CIDR-28, CIDR-14, and CIDR-0, respectively. LH surges were detected in 4/4 controls, 4/5 CIDR-28, 2/5 CIDR-14 and 0/5 CIDR-0 cows following ECP. In experiment 2, progesterone was administered to cycling, lactating, Holstein cows during the luteal phase of the estrous cycle as in experiment 1. Luteolysis was induced as in experiment 1. The occurrence of an endogenous LH surge and ovulation were monitored for 7 days. Concentrations of progesterone after luteolysis were 0.13, 0.30, 0.70 and 1.20 ng/mL for cows treated with no CIDR, CIDR-28, CIDR-14 and CIDR-0, respectively. LH surges and ovulation were detected in 5/5 controls, 3/7 CIDR-28, 0/5 CIDR-14 and 0/5 CIDR-0 cows. It was concluded that low concentrations of progesterone can reduce the ability of either endogenous or exogenous estradiol to induce a preovulatory surge of LH and ovulation.