Behavioral patterns as indicators of resilience after parturition in dairy cows.

During the transition phase, dairy cows are susceptible to develop postpartum diseases. Cows that stay healthy or recover rapidly can be considered to be more resilient in comparison to those that develop postpartum diseases. An indication of loss of resilience will allow for early intervention with preventive and supportive measures before the onset of disease. We investigated which quantitative behavioral characteristics during the dry period could be used as indicators of reduced resilience after calving, using noninvasive Smart Tag neck and Smart Tag leg sensors in dairy cows (Nedap N.V.). We followed 180 cows during 2 wk before until 6 wk after parturition at 4 farms in the Netherlands. Serving as proxy for loss of resilience, as defined by the duration and severity of disease, a clinical assessment was performed twice weekly and blood samples were taken in the first and fifth week after parturition. For each cow, clinical and serum value deviations were aggregated into a total deficit score (TDS total). We also calculated TDS values relating to inflammation, locomotion, or metabolic problems, which were further divided into macro-mineral and liver-related deviations. Smart Tag neck and leg sensors provided continuous behavioral activity signals of which we calculated the average, variance, and autocorrelation during the dry period. Diurnal patterns in the behavioral activity signals were derived by fast Fourier transformation and the calculation of the nonperiodicity. To select significant predictors of resilience, we first performed a univariate analysis with TDS as dependent variable and the behavioral characteristics that were measured during the dry period, as potential predictors with cow as experimental unit. We included parity group as fixed effect and farm as random effect. Next, we performed multivariable analysis with only significant predictors, followed by a variable selection procedure to obtain a final linear mixed model with an optimal subset of predictors with parity group as fixed effect and farm as random effect. The TDS total was best predicted by average inactive time, nonperiodicity ruminating, nonperiodicity of bouts standing up and fast Fourier transformation stand still. Average inactive time was negatively correlated with average eating time, and these 2 predictors could be exchanged with only little difference in model performance. Our best performing model predicted TDS total at a cutoff level of 60 points, with a sensitivity of 79.5% and a specificity of 73.2% with a positive predicted value of 0.69 and a negative predicted value of 0.83. The models to predict the other TDS categories showed a lower predictive performance as compared with the TDS total model, which could be related to the limited sample size and therefore, low occurrence of problems within a specific TDS category. Furthermore, more resilient dairy cows are characterized by high averages of eating time with high regularity in rumination and low averages of inactive time. They reveal high regularity in standing time and transitions from lying to standing, in the dry period. These behaviors can be used as indicators of resilience and allow for preventive intervention during the dry period in vulnerable dairy cattle. However, further examination is still required to find clues for adequate intervention strategies.

Size development of tomatoes growing in trusses: linking time of fruit set to diameter.

BACKGROUND: Size of fruit is an important issue in determining yield at harvest. Even under controlled conditions, variation between fruit and trusses can be considerable. As an easy to measure indication of size, the diameter of tomatoes growing in trusses was assessed in three experiments with different number of tomatoes per truss, as well as cultivars, and also by varying the level of ions in the recirculated drain water. RESULTS: By applying the von Bertalanffy growth model, more than 99% of the variation present could be explained by the time of fruit set for all tomatoes growing anywhere in the trusses. A linear relationship between time of fruit set and the biological shift factor, an indication of developmental age, was observed. Integrating this linear relationship in the analysis of the diameter data removed one stochastic variable (biological shift factor), effectively halving the number of parameters to be estimated. CONCLUSION: The results of the present study indicate that the major part of the variation present in the diameter of tomatoes growing in trusses is the result of variation in the time of fruit set of individual fruits. The position within the greenhouse (i.e. local differences in assimilates supply) exerted only a minor effect on diameter development. Accordingly, the time of fruit set largely determines fruit size. Likely, growing conditions before fruit set are crucial for final fruit size. The time of fruit set of each tomato in the truss and the local growing conditions within the greenhouse that affect assimilate supply need to be assessed accurately for a reliable size prediction.

Automated body condition scoring of dairy cows using 3-dimensional feature extraction from multiple body regions.

Machine vision technology has been used in automated body condition score (BCS) classification of dairy cows. The current vision-based classifications use information acquired from a limited number of body regions of the cow. Our study aimed to improve automated BCS classification by including multiple body condition-related features extracted from 3 viewpoints in 8 body regions. The data set of this study included 44 lactating cows with their BCS evenly distributed over the scale of BCS from 1.5 to 4.5 units. The body images of these cows were recorded over 2 consecutive days using 3-dimensional cameras positioned to view the cow from the top, right side, and rear. Each image was automatically processed to identify anatomical landmarks on the body surface. Around these anatomical landmarks, the bony prominences and body surface depressions were quantified to describe 8 body condition-related features. A manual BCS of each cow was independently assigned by 2 trained assessors using the same predefined protocol. With the extracted features as inputs and manual BCS as the reference, we built a nearest-neighbor classification model to classify BCS and obtained an overall classification sensitivity of 0.72 using a 10-fold cross-validation. We conclude that the sensitivity of automated BCS classification has been improved by expanding the selection of body condition-related features extracted from multiple body regions.

Automated body weight prediction of dairy cows using 3-dimensional vision.

The objectives of this study were to quantify the error of body weight prediction using automatically measured morphological traits in a 3-dimensional (3-D) vision system and to assess the influence of various sources of uncertainty on body weight prediction. In this case study, an image acquisition setup was created in a cow selection box equipped with a top-view 3-D camera. Morphological traits of hip height, hip width, and rump length were automatically extracted from the raw 3-D images taken of the rump area of dairy cows (n = 30). These traits combined with days in milk, age, and parity were used in multiple linear regression models to predict body weight. To find the best prediction model, an exhaustive feature selection algorithm was used to build intermediate models (n = 63). Each model was validated by leave-one-out cross-validation, giving the root mean square error and mean absolute percentage error. The model consisting of hip width (measurement variability of 0.006 m), days in milk, and parity was the best model, with the lowest errors of 41.2 kg of root mean square error and 5.2% mean absolute percentage error. Our integrated system, including the image acquisition setup, image analysis, and the best prediction model, predicted the body weights with a performance similar to that achieved using semi-automated or manual methods. Moreover, the variability of our simplified morphological trait measurement showed a negligible contribution to the uncertainty of body weight prediction. We suggest that dairy cow body weight prediction can be improved by incorporating more predictive morphological traits and by improving the prediction model structure.

Indicators of resilience during the transition period in dairy cows: A case study.

The transition period is a demanding phase in the life of dairy cows. Metabolic and infectious disorders frequently occur in the first weeks after calving. To identify cows that are less able to cope with the transition period, physiologic or behavioral signals acquired with sensors might be useful. However, it is not yet clear which signals or combination of signals and which signal properties are most informative with respect to disease severity after calving. Sensor data on activity and behavior measurements as well as rumen and ear temperature data from 22 dairy cows were collected during a period starting 2 wk before expected parturition until 6 wk after parturition. During this period, the health status of each cow was clinically scored daily. A total deficit score (TDS) was calculated based on the clinical assessment, summarizing disease length and intensity for each cow. Different sensor data properties recorded during the period before calving as well as the period after calving were tested as a predictor for TDS using univariate analysis of covariance. To select the model with the best combination of signals and signal properties, we quantified the prediction accuracy for TDS in a multivariate model. Prediction accuracy for TDS increased when sensors were combined, using static and dynamic signal properties. Statistically, the most optimal linear combination of predictors consisted of average eating time, variance of daily ear temperature, and regularity of daily behavior patterns in the dry period. Our research indicates that a combination of static and dynamic sensor data properties could be used as indicators of cow resilience.

Erratum to "Automatic assessment of dairy cows' rumen function over time and links to feed changes and milk production" (JDS Commun. 3:126-131).

[This corrects the article DOI: 10.3168/jdsc.2021-0165.].

Automatic assessment of dairy cows' rumen function over time and links to feed changes and milk production.

A 3-dimensional (3D) vision-based system was previously designed to automatically estimate the rumen motility of individual cows. This longitudinal study aimed to explore the associations between 3D vision-based rumen function assessment and dairy cow feed changes and milk production on a commercial farm. The 3D vision system was attached to an automatic milking robot to estimate the ruminal contraction frequency and rumen fill in 42 lactating cows during each milking event for 66 d. Additionally, we collected data on milk production, milk composition, general health, and changes in feeding practices. The 3D vision system showed that half the cows displayed a drastic decrease in the estimated rumen fill when all cows began grazing. The grazing and decreased rumen fill were also associated with herd-level milk fat depression. Over the 66 d, one cow was detected with reduced milk production and suspected rumen dysfunction by the farmer. The 3D vision system, however, identified this cow as having sudden decreases in estimated ruminal contraction frequency and rumen fill 4 d before detection by the farmer. In this longitudinal study, the 3D vision-based rumen function assessment system showed potential as a useful management-supporting tool for dairy farmers. The system, however, requires further validation with more cows of various breeds and ages. We suggest validating the 3D vision system with rumen boluses, quantified adjustments in feeding practices, more cases with ruminal dysfunction, and systematic health assessments for future studies.

Performance analysis method for model-based irrigation strategies under uncertainty.

There is a necessity to increase the performance of food production in agriculture, this means, that precise management support in farming systems is required to reduce water use and drainage while avoiding crop stress. Management support based on model predictions is used to increase the performance of food production. However, sources of uncertainty affect the model predictions. Uncertainty in soil properties and uncertain evapotranspiration translate into uncertain predictions, and consequently in risk of performance loss. This paper presents the code and method to analyze performance uncertainty (and risk of performance loss) due to uncertain circumstances. The method is based on using the De Graaf evapotranspiration model and the EMMAN3G model, a Richards equation-based soil water model, as modules to conduct a performance uncertainty study.

Predicting hairline fractures in eggs of mature hens.

Eggshell damage poses a serious problem for the consumption egg industry. Increasing the maximum age of laying hens will increase eggshell damage due to loss of shell strength. This poses a serious problem for automatic collection, packing, and transport. We performed a model based study focused on hairline fractures in eggs of 88-week-old hens, and simulated side collisions on 1,235 eggs using a specially designed pendulum. The kinetic energy at the moment of impact was related to the accelerations measured by an electronic egg going through the transport chain. Further, several egg mechanical properties were measured.For collisions with a realistic impact, fracture occurrence correlated negatively with dynamic stiffness (14%), mass (15%), shape index (9%), and damping ratio (12%). We manipulated the data set to investigate the influence of improving egg properties. Removing the least favorable 50% of the eggs based on stiffness and mass resulted in a moderate reduction of fracture occurrence, from 7.7% down to 4.4%.The peak acceleration of an egg running through the transport chain lies typically in the range of 15 to 45 g. Our model predicts that a moderate decrease from 30 g down to 20 g will result in a drastic reduction of fracture occurrence from 7.7% down to 0.3 to 1% (95% confidence region), whereas an increase to 40 g will increase fracture occurrence to 42 to 55%.The model predicts that severe collisions pose a relatively high risk for eggshell damage, which suggests that a reduction of collision severity is of first priority when increasing the age of laying hens.

The effect of immobilizing drugs on adrenal responsiveness to ACTH in Rusa deer.

Resting cortisol values in a fully tame Rusa deer (Cervus rusa timorensis) and the influence of two anaesthetics, Rompun and Fentaz, on cortisol levels as well as the response to synthetic ACTH were investigated. The mean level of cortisol in a completely tame Rusa deer was found to be 2.22 ng/ml (SD 1.45 ng/ml n = 36; minimal level recorded was 0.96 ng/ml, maximal level recorded was 9.21 ng/ml). No circadian rhythm of cortisol in plasma was detected. Rompun (xylazine hydrochloride) and/or Fentaz (fentanyl citrate) alone or in combination can be used for immobilization of Rusa deer. Neither Rompun nor Fentaz alone or in combination influences the cortisol response to synthetic ACTH administration. Because of the narrow range for safe dosage for Fentaz the use of Rompun for immobilizing deer is recommended.

Adrenal response to ACTH stimulation in Rusa deer (Cervus rusa timorensis).

Resting cortisol values in immobilized mature Rusa stags (Cervus rusa timorensis) and the response to synthetic ACTH were investigated. The mean level of cortisol in mature Rusa stags was found to be 3.80 ng/ml (SD = 0.87, N = 18). Over the range 0.37-6.0 i.u. the adrenal response to ACTH challenge was linearly related to the log dose ACTH administered (r = 0.998). More than 6 i.u. of ACTH caused maximal stimulation of the adrenal gland. Rusa deer appear to be much more sensitive to ACTH administration than other species.

Seasonal variation in plasma testosterone, luteinizing hormone concentrations and LH-RH responsiveness in mature, male rusa deer (Cervus rusa timorensis).

Plasma testosterone and luteinizing hormone (LH) concentrations in immobilized or yarded rusa stags (Cervus rusa timorensis) were investigated over a two-year period. Testosterone concentrations showed a minor elevation in autumn (May) and reached maximal levels in late winter-early spring (August) coinciding with the rut. Luteinizing hormone in plasma was only detectable from January to May. Maximal responsiveness of the pituitary-gonadal axis to LH-RH stimulation was recorded in August. The combination of Fentaz (fentanylcitrate and azaperone) and Rompun (xylazine hydrochloride) for immobilizing deer influences hypothalamic function.

Changes in plasma levels of cortisol and corticosterone after acute ACTH stimulation in rusa deer (Cervus rusa timorensis).

Resting cortisol and corticosterone levels in immobilized mature rusa stags (Cervus rusa timorensis) and the influence of synthetic ACTH on the cortisol/corticosterone ratio (F/B ratio) were investigated. The basal concentration of cortisol was found to be 14.07 nmol/l (SD = 9.3, N = 15) and corticosterone was 3.79 nmol/l (SD = 2.3, N = 15). The cortisol/corticosterone ratio for the basal level was 5.31 (SD = 3.9, N = 15). After ACTH administration the cortisol/corticosterone ratio increased to 11.41 (SD = 5.4, N = 147) regardless of doses of ACTH administered to individual stags. The adrenal response to ACTH administration has a potential application for selection of deer most suitable for deer farming.

Plasma prolactin in the rat during suckling without prior separation from pups.

The relation between suckling and plasma prolactin (Prl) was studied in the rat, without prior separation of the dam from its pups. When the pups were replaced by a hungry foster litter, upon renewed suckling plasma Prl showed episodic increases and decreases in individual rats. When, subsequent to litter removal, similar rats were injected with perphenazine, a significant increase of plasma Prl was observed. This indicates that a decline of plasma Prl during suckling was not caused by exhaustion of Prl stores in the pituitary. In 22 individual rats blood was sampled every other minute while observations were made on nursing behaviour of the dams. During apparent suckling, increases as well as decreases of plasma Prl occurred. However, in most cases suckling did not affect plasma Prl, i.e. it remained stable at a high or a relatively low level. On the other hand, a considerable rise of plasma Prl was frequently observed when a dam was away from the nest. The data indicate that in the physiological situation Prl secretion from the pituitary is not directly related suckling activity, though episodes of suckling are essential to maintain a high Prl secretory capacity of the pituitary gland.

Incidence of a heterosis effect in adrenal responsiveness to ACTH stimulation in the chicken.

No differences exist between basal plasma corticosterone concentrations of broilers ferals and first generation large crossbreds (White leghorn x New Hampshire). Crossbreds show near double adrenal responsiveness to synthetic ACTH administration, indicating a heterosis effect for this characteristic. Extraction of chicken plasma with 30% aqueous polyethylene glycol solution eliminates the need for tedious and expensive pre-assay purification of plasma.

Daily energy budgets of avian embryos: the paradox of the plateau phase in egg metabolic rate.

The metabolic rate of precocial bird eggs reaches a plateau when about 80% of the incubation period has passed. This is unexpected, as in many species the embryo continues to grow and maintenance costs must therefore increase. To investigate this paradox, daily energy budgets were constructed for embryos of four galliform species according to two models that used empirical data on egg metabolic rate and embryo growth. In the first model, embryonic synthesis costs were estimated, with an assumed synthesis efficiency, before calculating the maintenance costs. In the second model, embryonic maintenance was calculated first, and no assumptions were made on the synthesis efficiency. The calculations show that assumptions of the synthesis efficiency had a major impact on the energy budget calculations, because embryonic growth rate was high. During the plateau phase, a galliform embryo allocated energy in favor of its maintenance costs in three ways: by decreasing growth rate, by increasing synthesis efficiency, and by depressing the formation of glycogen. Our study suggests that a reduction in growth rate plays a minor role. An increase of synthesis efficiency is more likely to explain the plateau in energy expenditure, since small increases in synthesis efficiency can lead to great savings on synthesis costs.