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Research on identity has provided key insights into the challenges individuals experience when their professional self-concept is disrupted. But there has been little consideration of individuals’ ...

The present case series reports the preliminary test of a rumination-focused cognitive-behavioral therapy (RFCBT) self-help program to reduce depressive rumination among Japanese female undergraduates. A workbook-type self-help program based on RFCBT was implemented with 39 participants showing a high tendency toward rumination/worry. Data from 30 participants who completed one or more modules were analyzed quantitatively. The results showed significant reductions of rumination, worry, and anxiety at post-intervention. Further, semistructured interviews were conducted with 13 participants who completed the program, and verbatim data were examined using content analysis. The contents found to be useful and difficult differed for each participant and each module. Based on these results, the future implementation and dissemination of RFCBT is discussed.

Ruminating behavior accompanies the development of the rumen and the intake of solid feed in calves. However, few studies have reported on the emergence and development of rumination. In this study, we observed ruminating behavior changes of 56 Holstein calves (body weight at birth = 40.1 ± 3.96 kg; mean ± standard deviation) from birth to 30 d of age under the feeding management of suckling calves that were only fed pelleted concentrate feed and milk. All calves were housed in individual pens equipped with infrared cameras. We explored feed intake within 30 d of age, body weight on 61 d of age, and other apparent indicators, including the age of first eating the bedding, duration of non-nutritive oral behavior at 25 and 30 d of age, total starter feed intake within 30 d of age, average daily starter feed intake within 30 d of age, and duration of ruminating behavior at 25 and 30 d of age for all calves, to further explore the effects of the age of first ruminating behavior (AFR). The AFR fitted the normal distribution and ranged from 15 to 20 d of age for 50% of the experimental population. The AFR was positively correlated with the age of first eating the bedding and duration of non-nutritive oral behavior at 30 d of age. Total starter feed intake within 30 d of age, average daily starter feed intake within 30 d of age, duration of ruminating behavior at 25 and 30 d of age, and duration of eating the bedding at 25 and 30 d of age were negatively correlated with AFR. Overall, to the best of our knowledge, this is the first study that has analyzed the correlation between AFR and other indicators. We found that earlier AFR was associated with shorter duration of non-nutritive oral behavior, longer durations of rumination and eating the bedding, and higher feed intake by 30 d of age.

Time spent ruminating is affected by diet and affects the rumen environment. The objective of the current study was to conduct a meta-regression to characterize the variation in rumination time and its relationship with milk and milk fat yields and variables mechanistically associated with milk fat synthesis, including rumen pH and total-tract digestibility. The analysis included 130 journal articles published between 1986 and 2018 that reported 479 treatment means from lactating Holsteins cows during established lactation. Milk yield averaged 34.3 kg/d (range 14.2–52.1 kg/d), milk fat averaged 3.47% (range 2.20–4.60%), and rumen pH averaged 6.1 (range 5.3–7.0). Rumination observation systems were categorized into 6 groups, but there was little difference in average rumination time among systems. The total time spent ruminating averaged 444 min/d (range 151–638 d) and occurred in 13.8 bouts/d (range 7.8–17.4 bouts/d) that averaged 32.7 min (range 20.0–48.1 min). Bivariate regressions were modeled to include the random effect of study, and correlations were evaluated through the partial R2 that excluded variation accounted for by the random effect. Rumination time was quadratically increased with increasing milk fat yield (partial R2 = 0.27) and milk fat percent (partial R2 = 0.17). Rumination was also increased with increasing milk yield, dry matter intake, and rumen pH, and was quadratically related to dietary neutral detergent fiber (NDF) and total-tract NDF digestibility (partial R2 = 0.10–0.27). Similar relationships were observed for rumination per unit of dry matter and NDF intake. The best-fit multivariate model predicting total rumination time included milk yield, milk fat yield, and concentration and accounted for 37% of the variation. Total-tract digestibility was available for 217 treatment means; when included in the model, the partial R2 increased to 0.41. Last, principal component analysis was conducted to explore the relationship among variables. The first 2 principal components in the broad analyses explained 36.7% of the 39 variables evaluated, which included rumination bouts and time spent ruminating. In conclusion, rumination time was related to milk fat across a large number of studies, although it explained only a limited amount of the variation in milk fat.

There has been little evolutionarily oriented empirical research on the intense, repetitive thoughts—ruminations—that often occur during grief. We used evolutionary theory to develop a new instrument for evaluating grief-related rumination titled the Bereavement Analytical Rumination Questionnaire (BARQ) operationalized by two dimensions: root cause analysis (RCA), the analysis of the cause of the loss; and reinvestment analysis (RIA), the analysis of how to reinvest time and effort in meaningful (presumably fitness enhancing) activities. We administered the BARQ to a sample of people seeking help for grief from non-profit organizations (619 completers) and tested several evolutionary predictions about grief-related rumination. The sample had several signs of severe grief, making it clinically relevant (sleep disturbances, chronicity, psychotropic drug use). Rumination was higher among antidepressant users, suggesting that rumination is related to depression. We also found evidence that grief-related rumination is modulated by circumstances (e.g., type of loss, age and gender of the participant, age of the deceased, traumatic death), which suggests adaptive regulation. Our most important results are consistent with inclusive fitness theory. Specifically, the pattern suggests that as people grow older, they spend less time ruminating about the causes of direct fitness losses (the loss of their own children), and they spend more time ruminating about the causes of indirect fitness losses (e.g., the loss of young non-parental, non-offspring relatives). We also found a sex or gender difference in grief-related rumination that is consistent with other evidence that women have a greater impact on the survival of close relatives (particularly, children and grandchildren), as well as evidence that women have more to lose with the loss of a close social partner. Overall, we found little support for the hypothesis that grief-related rumination is disordered.

Virtual fencing technology uses a neckband-mounted device to deliver an audio cue when an animal nears a virtual boundary that is set via a global positioning system, followed by an electrical stimulus if it crosses the boundary. The flexibility offered by this technology could revolutionize grazing management on dairy farms, but its application and effects on lactating dairy cattle have not been assessed. This experiment reports on the effects of an electric or a virtual front-fence on dairy cow behavior and welfare. Two temporally separated treatments were applied to a herd of 30 multiparous cows. Cows were provided an estimated 14 to 15 kg of dry matter/cow of fresh pasture in a new paddock every 24 h. From d 1 to 10 cows were grazed using a conventional electric front-fence (control treatment) and from d 14 to 23 they were grazed using a virtual front-fence (eShepherd, Agersens Pty Ltd.). Cows were trained to the technology from d 11 to 13. The milk production and live weight of individual cows were recorded daily. Cortisol concentrations were obtained from milk samples collected from individual cows on 3 d during each of the control and the virtual fence grazing periods, plus the first day of training. From d 6 of the experiment, 6 focal cows were fitted with a RumiWatch (Itin + Hoch GmbH) noseband sensor to monitor grazing and ruminating time, and 8 focal cows were fitted with an IceTag (IceRobotics Ltd.) sensors to monitor activity. Milk production, live weight, and the time cows spent standing and lying did not differ between the electric and virtual fence periods. Milk cortisol concentrations, activity, and the times spent ruminating and grazing were comparable between the electric and early virtual fence periods (i.e., d 1–3 with a virtual fence). However, at d 4 to 6 with a virtual fence, activity (steps taken and motion index) and time spent grazing were lower, and time spent ruminating was greater, compared with an electric fence. Further, least significant difference tests suggest milk cortisol concentrations were higher at d 5 with a virtual fence than at d 8 with an electric fence and d 1 with a virtual fence. We conclude there is no evidence of behavioral and welfare effects of virtual fencing on dairy cows in the days immediately following implementation of the technology in a simple intensive grazing regimen, but a longer study is required to fully elucidate effects beyond this period.

Making negative inferences for negative events, ruminating about them, and retrieving negative aspects of memories have all been associated with depression. However, the causal mechanisms that link negative inferences to negative mood and the interplay between inferences, rumination, and memory have not been explored. In the current study, we used a cognitive-bias modification (CBM) procedure to train causal inferences and assessed training effects on ruminative thinking, memory, and negative mood among people with varying levels of depression. Training had immediate effects on negative mood and rumination but not after recall of a negative autobiographical memory. Note that training affected memory: Participants falsely recalled inferences presented during the training in a training-congruent manner. Moreover, among participants with high levels of depression, training also affected causal inferences they made for an autobiographical memory retrieved after training. Our findings shed light on negative cognitive cycles that may contribute to depression.

Previous research suggests that ruminating on social media content is associated with greater mental distress (Yang et al., 2018). This study examined whether materialistic value orientation (MVO)—prioritizing values and goals related to consumerism, consumption, and social status—predicted social media rumination in a sample of diverse adolescents in a two-wave cross-lagged design. A cross-lagged analysis among 119 adolescents indicated that MVO at Wave 1 predicted greater social media rumination 4 months later at Wave 2, but social media rumination at Wave 1 did not predict MVO at Wave 2. Cross-lagged results suggested that MVO may lead to greater social media rumination over time for diverse adolescents. Adolescents with MVO could benefit from interventions to reduce the effects of their need for external validation and maladaptive rumination, as external validation and maladaptive rumination are linked to behaviors and thoughts that can be harmful to mental health.

Ingestive-related behaviors including feeding and ruminating are important indexes to measure the health and welfare of dairy cows. The purpose of this study is to develop a method based on triaxial acceleration to automatically recognize feeding and ruminating of dairy cows. During the experiment, five diary cows raised in a barn were used as experimental subjects. A triaxial acceleration sensor was used as the device to collect jaw-movement data of dairy cows, and the behaviors of dairy cows were classified into three categories: feeding, ruminating and other behavior. The features of time-domain and frequency-domain were extracted from the raw acceleration data. Three machine learning algorithms including k-nearest neighbor, support vector machine and probabilistic neural network were used for the classification and the results based on four different data segment lengths were compared. The results show that the three algorithms can be used for recognition of feeding and ruminating with high accuracy. Under the condition that the sampling frequency of the sensor is 5 Hz, the combination of data segment length of 256 and k-nearest neighbor algorithm is the best scheme for recognition of feeding and ruminating in this study. The precision and recall of recognition for feeding were 92.8% and 95.6% respectively, and those of recognition for ruminating were 93.7% and 94.3% respectively. The specificity and AUC of recognition for feeding were 96.1% and 0.959 respectively, and those of recognition for ruminating were 97.5% and 0.959 respectively. This will provide an effective method for real-time monitoring of ingestive-related behaviors of dairy cows and lay a foundation for prediction of dairy cows’ health status and welfare to further achieve the purpose of disease prediction and adjusting feeding and management methods.

Worldwide, there is a trend towards increased herd sizes, and the animal-to-stockman ratio is increasing within the beef and dairy sectors; thus, the time available to monitoring individual animals is reducing. The behaviour of cows is known to change in the hours prior to parturition, for example, less time ruminating and eating and increased activity level and tail-raise events. These behaviours can be monitored non-invasively using animal-mounted sensors. Thus, behavioural traits are ideal variables for the prediction of calving. This study explored the potential of two sensor technologies for their capabilities in predicting when calf expulsion should be expected. Two trials were conducted at separate locations: (i) beef cows (n = 144) and (ii) dairy cows (n = 110). Two sensors were deployed on each cow: (1) Afimilk Silent Herdsman (SHM) collars monitoring time spent ruminating (RUM), eating (EAT) and the relative activity level (ACT) of the cow, and (2) tail-mounted Axivity accelerometers to detect tail-raise events (TAIL). The exact time the calf was expelled from the cow was determined by viewing closed-circuit television camera footage. Machine learning random forest algorithms were developed to predict when calf expulsion should be expected using single-sensor variables and by integrating multiple-sensor data-streams. The performance of the models was tested using the Matthew’s correlation coefficient (MCC), the area under the curve, and the sensitivity and specificity of predictions. The TAIL model was slightly better at predicting calving within a 5-h window for beef cows (MCC = 0.31) than for dairy cows (MCC = 0.29). The TAIL + RUM + EAT models were equally as good at predicting calving within a 5-h window for beef and dairy cows (MCC = 0.32 for both models). Combining data-streams from SHM and tail sensors did not substantially improve model performance over tail sensors alone; therefore, hour-by-hour algorithms for the prediction of time of calf expulsion were developed using tail sensor data. Optimal classification occurred at 2 h prior to calving for both beef (MCC = 0.29) and dairy cows (MCC = 0.25). This study showed that tail sensors alone are adequate for the prediction of parturition and that the optimal time for prediction is 2 h before expulsion of the calf.

Breeding values for feed intake and feed efficiency in beef cattle are generally derived indoors on high-concentrate (HC) diets. Within temperate regions of north-western Europe, however, the majority of a growing beef animal's lifetime dietary intake comes from grazed grass and grass silage. Using 97 growing beef cattle, the objective of the current study was to assess the repeatability of both feed intake and feed efficiency across 3 successive dietary test periods comprising grass silage plus concentrates (S+C), grazed grass (GRZ) and a HC diet. Individual DM intake (DMI), DMI/kg BW and feed efficiency-related parameters, residual feed intake (RFI) and gain to feed ratio (G : F) were assessed. There was a significant correlation for DMI between the S+C and GRZ periods (r = 0.32; P < 0.01) as well as between the S+C and HC periods (r = 0.41; P < 0.001), whereas there was no association for DMI between the GRZ and HC periods. There was a significant correlation for DMI/kg BW between the S+C and GRZ periods (r = 0.33; P < 0.01) and between the S+C and HC periods (r = 0.40; P < 0.001), but there was no association for the trait between the GRZ and HC periods. There was a significant correlation for RFI between the S+C and GRZ periods (r = 0.25; P < 0.05) as well as between S+C and HC periods (r = 0.25; P < 0.05), whereas there was no association for RFI between the GRZ and HC periods. Gain to feed ratio was not correlated between any of the test periods. A secondary aspect of the study demonstrated that traits recorded in the GRZ period relating to grazing bite rate, the number of daily grazing bouts and ruminating bouts were associated with DMI (r = 0.28 to 0.42; P < 0.05 - 0.001), DMI/kg BW (r = 0.36 to 0.45; P < 0.01 - 0.001) and RFI (r = 0.31 to 0.42; P < 0.05 - 0.001). Additionally, the number of ruminating boli produced per day and per ruminating bout were associated with G : F (r = 0.28 and 0.26, respectively; P < 0.05). Results from this study demonstrate that evaluating animals for both feed intake and feed efficiency indoors on HC diets may not reflect their phenotypic performance when consuming conserved forage-based diets indoors or when grazing pasture.

Metastarševstvo je razmeroma nov, večdimenzionalen konstrukt, ki pod skupen pojem združuje namerne misli starša o svojem otroku in vzgoji. Gre za zavesti dostopne misli, ki jih posameznik lahko obvladuje in prilagaja, zato metastarševstvo predstavlja pomembno miselno orodje starša, s katerim lahko uspešnejše uravnava svoje vedenje in ga prilagaja nenehno spreminjajočemu se kontekstu vzgoje. V magistrskem delu me je zanimalo, kako se metastarševstvo izraža na vzorcu slovenskih mam, katere demografske značilnosti ga napovedujejo in ali je metastarševstvo pomemben napovednik vzgojnih vedenj starša. V študiji je sodelovalo 210 slovenskih mam otrok, starih od tri do šest let. Izpolnile so slovenski prevod vprašalnika metastarševstva (MPPQ) in slovenski prevod lestvice multidimenzionalne ocene starševstva (MAPS). Rezultati so pokazali, da je izraznost metastarševstva na slovenskem vzorcu nizka do srednje visoka. Pokazalo se je tudi, da so starejše mame poročale o nekoliko nižji, a pomembno različni meri izraženosti metastarševstva kakor mlajše mame. Med pomembnimi napovedniki pozitivnih vzgojnih vedenj se je pokazala le komponenta reševanje problemov, med napovedniki negativnih vzgojnih vedenj pa kombinacija komponent ruminacija, ocenjevanje, refleksija in nove ideje. Kaže se, da je za izraženost vzgojnih vedenj bolj pomembna izraženost kombinacije več komponent kakor izraženost ene same komponente metastarševstva. Slednje je še posebej pomembno pri načrtovanju intervencij za razvijanje metastarševstva, ki staršu omogoča uspešnejše uravnavanje lastnega vedenja in s tem prilagajanje nenehno spreminjajočemu se kontekstu vzgoje. Meta-parenting is a relatively new, multidimensional construct that brings together a parent's intentional thoughts about the development of their child and upbringing under a common concept. It describes thoughts that are consciously accessible and that everyone can control and adapt. In that regard, meta-parenting is a cognitive tool for parents with which they can more successfully regulate their behavior and adapt it to the constantly changing context of upbringing. In my master thesis, I was interested in how meta-parenting is expressed in a sample of Slovenian mothers, which demographic characteristics predict it, and whether meta-parenting is an important predictor of parental educational behaviors. In the study participated 210 Slovenian mothers of children between 3 and 6 years of age. They completed the Slovenian translation of the meta-parenting profile questionnaire (MPPQ) and the Slovenian translation of the multidimensional assessment parenting scale (MAPS). The results showed that the expression of meta-parenting, in the sample of Slovenian mothers, is low to medium-high. It has also been shown that older mothers reported slight, but significantly lower expression of meta-parenting, than younger mothers. Among the important predictors of positive parenting behaviors, only the component of problem-solving was found, and among the predictors of negative parenting behaviors, a combination of components ruminating, assessment, reflecting, and new ideas were found. It seems that a combination of several components is more important for the expression of parenting behaviors, than is a high expression of only one meta-parenting component. This finding is especially important in the planning of interventions for the development of meta-parenting, which enables the parent to regulate their behavior more successfully and thus adapt to the constantly changing context of education.

Simple Summary Monitoring animal activity in production systems is an important tool for obtaining information on health, production, and reproduction. In this study, we evaluated the use of accelerometers with different strategies to predict the grazing behavior of Nelore cattle. This research was conducted in an environment both more challenging and representative of the practices adopted in livestock production systems in Brazil. The results of this study showed that the use of the Random Forest algorithm, together with techniques for resampling the training data of the models, classified the studied behaviors with high accuracy, especially for important, and less frequent activities such as water consumption frequency. Abstract Knowledge of animal behavior can be indicative of the well-being, health, productivity, and reproduction of animals. The use of accelerometers to classify and predict animal behavior can be a tool for continuous animal monitoring. Therefore, the aim of this study was to provide strategies for predicting more and less frequent beef cattle grazing behaviors. The behavior activities observed were grazing, ruminating, idle, water consumption frequency (WCF), feeding (supplementation) and walking. Three Machine Learning algorithms: Random Forest (RF), Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC) and two resample methods: under and over-sampling, were tested. Overall accuracy was higher for RF models trained with the over-sampled dataset. The greatest sensitivity (0.808) for the less frequent behavior (WCF) was observed in the RF algorithm trained with the under-sampled data. The SVM models only performed efficiently when classifying the most frequent behavior (idle). The greatest predictor in the NBC algorithm was for ruminating behavior, with the over-sampled training dataset. The results showed that the behaviors of the studied animals were classified with high accuracy and specificity when the RF algorithm trained with the resampling methods was used. Resampling training datasets is a strategy to be considered, especially when less frequent behaviors are of interest.

Understanding cattle behavior is important for discerning their health and management status. However, manual observations of cattle are time-consuming and labor-intensive. Moreover, during manual observations, the presence or position of a human observer may alter the normal behavior of the cattle. Wearable cameras are small and lightweight; therefore, they do not disturb cattle behavior when attached to their bodies. Thus, this study aimed to evaluate the suitability of wearable cameras for monitoring and analyzing cattle behavior. From December 18 to 27, 2017, this study used four 2-month-old, group-housed Holstein calves at the Field Science Center of the Obihiro University of Agriculture and Veterinary Medicine, Japan. Calf behavior was recorded every 30 s using a wearable camera (HX-A1H, Panasonic, Japan) from 10:00 to 15:30 and observed directly from 11:00 to 12:00 and 14:00 to 15:00. In addition, the same observer viewed the camera recordings corresponding to the direct observation periods, and the results were compared. The correlation coefficients of all behavioral data from direct and wearable camera video observations were significant (p < 0.01). For the wearable cameras used in our experiment, there is an entrapment risk as the halter expands around the cameras. Therefore, considering their welfare, calves need to be regularly welfare-checked by an individual. We conclude that wearable cameras are suitable for observing calf behavior, particularly their posture (standing or lying), as well as their ruminating and feeding behaviors.

Understanding cattle behavior is important for discerning their health and management status. However, manual observations of cattle are time-consuming and labor-intensive. Moreover, during manual observations, the presence or position of a human observer may alter the normal behavior of the cattle. Wearable cameras are small and lightweight, therefore, they do not disturb cattle behavior when attached to their bodies. Thus, this study aimed to evaluate the suitability of wearable cameras for monitoring and analyzing cattle behavior. From December 18 to 27, 2017, this study used four 2-month-old, group-housed Holstein calves at the Field Science Center of the Obihiro University of Agriculture and Veterinary Medicine, Japan. Calf behavior was recorded every 30 s using a wearable camera (HX-A1H, Panasonic, Japan) from 10:00 to 15:30 and observed directly from 11:00 to 12:00 and 14:00 to 15:00. In addition, the same observer viewed the camera recordings corresponding to the direct observation periods, and the results were compared. The correlation coefficients of all behavioral data from direct and wearable camera video observations were significant (p &lt, 0.01). We conclude that wearable cameras are suitable for observing calf behavior, particularly their posture (standing or lying), as well as their ruminating and feeding behaviors.

The use of sensor technologies to monitor cows’ behavior is becoming commonplace in the context of dairy production. This study aimed at validating a commercial collar-based sensor system, the AFICollar® (Afimilk, Kibbutz Afikim, Israel), designed to monitor dairy cattle feeding and ruminating behavior. Additionally, the performances of two versions of the software for behavior classification, the current software AFIfarm® 5.4 and the updated version AFIfarm® 5.5, were compared. The study involved twenty Holstein-Friesian cows fitted with the collars. To evaluate the sensor performance under different feeding scenarios, the animals were divided into four groups and fed three different types of feed (total mixed ration, long hay, animals allowed to graze). Recordings of hourly rumination and feeding time produced by the sensor were compared with visual observation by scan sampling at 1 minute intervals using Spearman correlation, concordance correlation coefficient (CCC), Bland–Altman plots and linear mixed models for assessing the precision and accuracy of the system. The analyses confirmed that the updated software version V5.5 produced better detection performance than the current V5.4. The updated software version produced high correlations between visual observations and data recorded by the sensor for both feeding (r = 0.85, CCC = 0.86) and rumination (r = 0.83, CCC = 0.86). However, the limits of agreement for both behaviors remained quite wide (feeding: −19.60 min/h, 17.46 min/h, rumination: −15.80 min/h, 15.00 min/h). Type of feed did not produce significant effects on the agreement between visual observations and sensor recordings. Overall, the results indicate that the system can provide farmers with adequately accurate data on feeding and rumination time, and can be used to support herd management decisions. Despite all this, the precision of the system remained relatively limited, and should be improved with further developments in the classification algorithm.

The objective of this study was to determine whether associations exist between position while ruminating (lying vs. standing) and milk and component production in dairy cows. Data from 30 lactating Holstein cows were assembled from 2 studies in which cows were milked by automated milking system (AMS) and fed a partial mixed ration (PMR) in feed bins that recorded intake behavior. Rumination and lying behavior were monitored using automated neck- and leg-based sensors, respectively. Each cow was monitored over 2 separate 2-wk treatment periods. To estimate position while ruminating for each 2-h period of the day for each cow, a conditional probability was calculated to determine the probability that any rumination time and lying time were occurring at the same time in any 2-h period. These probabilities (RwL), and all behavioral data, were summarized per cow per 2-h interval, and then averaged per day and per 2-wk period, along with milk yield and component data. Cows averaged (mean ± standard deviation) 1.9 ± 1.1 lactations and 85.5 ± 55.2 d in milk, and weighed 668.5 ± 96.0 kg. Data included rumination time (557.7 ± 41.1 min/d), lying time (703.9 ± 65.3 min/d), idle standing time (520.1 ± 83.2 min/d), PMR feeding time (204.7 ± 48.5 min/d), PMR dry matter intake (DMI; 21.8 ± 4.6 kg/d), AMS pellet provision (4.6 ± 1.6 kg/d), total DMI (26.4 ± 4.5 kg/d), milk yield (42.4 ± 7.2 kg/d), milk fat content (3.75 ± 0.51%), and milk protein content (3.21 ± 0.32%). Greater rumination time and lying time were associated with greater RwL probability (mean = 0.19 ± 0.02; range = 0.14 to 0.23). The RwL probability tended to be positively associated with total DMI and milk fat content, was associated with milk protein content, but was not associated with any measures of milk yield. The results indicate that in a free-traffic AMS, cows who have greater probability of ruminating while lying down spend more time ruminating and lying, and tend to consume more total dry matter and produce milk with greater components.

Sheep are exposed to numerous stressors and environments during the pre-export phase of the live export industry. Establishing how animal behavior, health and demeanor reflect their experiences prior to sea transport is the first step toward testing the suitability and practicality of animal welfare measures. A total of 240 merino wethers originating from four farms were assessed at four locations in the live export chain: on farm, upon arrival to the registered export feedlot (Fe1), prior to departing the feedlot (Fe2) and 30 min post loading onto a live export vessel. Each of these locations and time points represent relevant assessment points as part of the commercial live export process. Pen-side behavioral and health measures were collected. Video footage was collected and edited to provide 48 30–45 s duration clips that were then scored by 12 assessors against 10 demeanor terms using a Qualitative Behavioral Assessment (QBA) methodology; data were analyzed using Principal Components (PC) analysis. Repeated Measures ANOVAs tested for variation in each dependent measure across each location and time point. There were low levels of health issues recorded overall; however, seven health and behavior measures significantly varied across the locations and time points. Most vocalizing was recorded on farm; most drinking, eating and resting behaviors were recorded at Fe1 and ruminating at Fe2; while the highest percentage of wethers with ocular discharge and lameness was on the vessel. For QBA, PC1 explained 30.5% of the variability, with agitated and nervous loaded to one end of the axis and calm and relaxed loaded to the opposing end. PC2 explained 24.5% of the variability, with interested, alert and sociable loaded to one end of the axis and lethargic loaded to the opposing end. Spearman's rank correlations between behavior, health and PC scores indicated that wethers eating, ruminating and resting were scored as more calm/relaxed, while those scored as more agitated/nervous or/ lethargic were also likely to vocalize. Determining how wethers respond to the different environments in the immediate pre-export phase of the journey informs on their welfare and the practicality of using a behavior tool to assess animal welfare.

Made available in DSpace on 2020-12-12T00:56:30Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-11-01 The aim was to evaluate the performance, feeding behavior and nutrient digestibility of lambs ranked according to residual feed intake (RFI) and residual intake and gain (RIG). A total of 102 male lambs (½ Dorper ½ Santa Inês; 70 d; 24.6 ± 3.71 kg) were used. The mean values of the RFI classes were -0.101, 0.0, and 0.091, and those of the RIG classes were 1.980, -0.032 and -2.369, for efficient, medium and inefficient lambs, respectively. Average daily gain was not correlated to RFI, but was correlated to RIG. Physiological parameters (i.e., respiratory frequency and heart rate), ruminal movement and rectal temperature were similar between efficient and inefficient lambs (i.e., for RFI and RIG; P > 0.05). Efficient RFI and RIG lambs spent less time ruminating and drinking water and more time eating (P < 0.05). Rumination time is a good feeding behavior marker to distinguish efficient and inefficient lambs (i.e., RFI and RIG). Inefficient feedlot lambs exhibited greater dry matter intake; this difference was not reflected in digestibility traits. These results may assist in the identification of more efficient animals to lower production costs and mitigate the environmental impact of lamb production systems. Department of Animal Science Veterinary School Federal University of Minas Gerais (UFMG) Department of Animal Science São Paulo State University (UNESP) School of Agricultural and Veterinarian Sciences Department of Animal Science Federal University of Lavras (UFLA) Department of Animal Science Environmental and Rural Science University of New England Department of Animal Science São Paulo State University (UNESP) School of Agricultural and Veterinarian Sciences

Rumination behavior in cattle is important for health and reproduction management of herd. The aim of presented paper was to evaluate change in rumination behavior in dairy cattle after changing total mixed ration (TMR) composition. Twenty-eight multiparous Red Holstein dairy cows were observed during rumination in first month after calving and in fourth month after calving. Cows were fed different total mixed ratio at beginning of lactation in first month after calving (TMR1) and in mid of lactation period in fourth month after calving (TMR2). TMR2 has higher content of roughage. Length of the single rumination period and number of jaw movements during rumination one bolus were recorded. Frequency of jaw movement per minute was calculated from recorded rumination characteristics. Rumination of one bolus TMR2 was longer (TMR1 = 53.97 ±8.241 sec, TMR2 = 57.57 ±6.290 sec) and cow perform more jaw movements (TMR1 = 61.0 ±10.674, TMR2 = 65.99 ±9.682) than ruminating bolus TMR1. Difference in duration of rumination one bolus as well as number of jaw movement was significant (P < 0.001). Frequency of jaw movement was not significantly affected (P > 0.05) and seem to be intra-individual stable. Rumination evaluated by correlation of rumination characteristics for TMR1 and TMR2 was intra-individual stable despite of changes in times of jaw movement and duration of one bolus rumination.

Livestock production has migrated to the Midwest region of Brazil; however, these regions are environmentally unsuitable for livestock specializing in milk production, due to high temperatures. This environment can be improved using inserting trees into the pastures. The objective was to evaluate the effects of adding grazing trees on the behavior of dairy heifers in the Midwest region of Brazil. Piata grass was managed in: open pasture system, OPS (shade level 0%), the worst treatment for animal production since the solar radiation and temperature are deleterious to animal welfare; moderate shade system (shade level 20%), the supposed adequate system where the animals find shady areas, but there is light available for photosynthesis; and intensive shade system (shade level 70%), the worst treatment for vegetal production since the light is limited for grass growth. Shade was provided by Eucalyptus trees. Heifer behavior was evaluated from 08:30 to 16:00 over three periods. In the OPS, the heifers searched for cow drinkers and remained there for a long time, refreshing themselves by floating in water and muddy places. Heifers demonstrated a behavior of attempting to return to grazing activity under the OPS during the hottest time of the day, but without success. Ruminating activity was not affected by any factor. The shade level affected the distribution of time spent on an activity and the time of day at which each activity happened. The moderate shade level is enough to ensure stability in the daily behavior of dairy heifers.

Background Calf stress at weaning and during transition to group pens represents a concern in dairy operations. Favoring natural behaviors, such as grooming, may help on reducing this challenge. Our objective was to evaluate the effect of a mechanical grooming brush on behavior and health of recently weaned calves, after transferring from individual to group housing. Two treatment groups (control [CON, n = 81]; automated brush [AB, n = 81]) were compared enrolling Holstein heifers (94 ± 7 d old) that were monitored for 20 days. Four cohorts, considering one CON and one AB group (19–20 calves/pen/cohort) were enrolled sequentially. Each calf was weighed, clinically evaluated, and affixed with a 3-D accelerometer sensor attached to the ear at enrolment. Continuous measurements (min/h) were generated for the following behaviors: Not-active, active, highly active, eating, and ruminating. Cameras for continuous video recording were installed in each pen, and calves were weighted at the last day of the study (d 20). Behavioral data were summarized as daily averages (min/h). Data was examined using repeated measures analysis for nested factors, with day as the time unit. Results Overall, calves had their first interaction with the brush within 2.5 days with a mean (SE) of 7 (±9.6) h after being transferred to group pens. A significant effect was determined for the interaction day by treatment on the time spent not-active and eating. Average not-active time was greater in CON compared to AB (22.8 ± 0.82 min/h vs. 21.7 ± 0.82 min/h), while eating time was greater in AB compared with CON (7.01 ± 0.40 min/h vs. 6.43 ± 0.40 min/h). Treatment groups had a similar weight gain and time to the first disease. Conclusions We concluded that the use of a mechanical brush influenced behavior, reducing not-active time, while increasing eating time. The consequences of this change in activity require further investigation.

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The use of automated sensors, that record feeding and locomotion behaviour in livestock, become more and more prominent, for example for the early detection of diseases in dairy cows. Their application may be also significant in extensive beef cattle production systems, where there is an infrequent farmer-to-animal contact. The aim of the present study was to determine the ability of a three dimensions accelerometer, compiled by a halter and a pedometer, to accurately discriminate and estimate behavioural activities in grazing beef cattle using direct observations (DO) as the golden standard. Eight beef cattle grazing in a vineyard were used in the present study, six animals were at the age of one year (283 ± 42 kg), and two above two years of age (643 ± 35 kg). The animals were equipped with halters and pedometers for an experimental period of 8 consecutive days. During that period, DO were also performed for 6 days for 6 h per day to estimate the accuracy of the sensors to correctly define and determine feeding, ruminating, drinking, walking, standing and lying. The instantaneous scan sampling technique with 10-minute intervals was used to record the mentioned behavioural parameters. Spearman correlation coefficients between accelerometer data and DO were calculated for each behavioural activity. Correlation coefficients (rs) between accelerometers and DO for feeding, ruminating, standing and lying were high (rs > 0.68), while for drinking and walking they were moderate and weak, respectively. In conclusion, the use of sensors is a promising method to predict feeding, ruminating, standing and lying behaviours of grazing beef cattle, while further research is needed to improve their ability to accurately estimate all behavioural activities and possibly evaluate their further use as health indicators.