Minimized Bolus-Type Wireless Sensor Node with a Built-In Three-Axis Acceleration Meter for Monitoring a Cow's Rumen Conditions

Effects of 3-nitrooxypropanol (Bovaer10) and whole cottonseed on milk production and enteric methane emissions from dairy cows under Swiss management conditions

The objective of this study was to determine the potential effect and interaction of 3-nitrooxypropanol (3-NOP; Bovaer, DSM-Firmenich Nutrition Products Ltd.) and whole cottonseed (WCS) on lactational performance and enteric methane (CH4) emission of dairy cows. A total of 16 multiparous cows, including 8 Holstein Friesian (HF) and 8 Brown Swiss (BS; 224 ± 36 DIM, 26 ± 3.7 kg milk yield, mean ± SD), were used in a split-plot design, where the main plot was the breed of cows. Within each subplot, cows were randomly assigned to a treatment sequence in a replicated 4 × 4 Latin square design with 2 × 2 factorial arrangements of treatments with four 24-d periods. The experimental treatments were as follows: (1) control (basal TMR), (2) 3-NOP (60 mg/kg TMR DM), (3) WCS (5% TMR DM), and (4) 3-NOP + WCS. The treatment diets were balanced for ether extract, crude protein, and NDF contents (4%, 16%, and 43% of TMR DM, respectively). The basal diets were fed twice daily at 0800 and 1800 h. Dry matter intake and milk yield were measured daily, and enteric gas emissions were measured (using the GreenFeed System, C-Lock Inc.) during the last 3 d of each 24-d experimental period when animals were housed in tiestalls. There was no difference in DMI on treatment level, whereas the WCS treatment increased ECM yield and milk fat yield. No interaction of 3-NOP and WCS occurred for any of the enteric gas emission parameters, but 3-NOP decreased CH4 production (g/d), CH4 yield (g/kg DMI), and CH4 intensity (g/kg ECM) by 13%, 14%, and 13%, respectively. Further, an unexpected interaction of breed by 3-NOP was observed for different enteric CH4 emission metrics: HF cows had a greater CH4 mitigation effect compared with BS cows for CH4 production (g/d; 18% vs. 8%), CH4 intensity (g/kg milk yield; 19% vs. 3%), and CH4 intensity (g/kg ECM; 19% vs. 4%). Hydrogen production was increased by 2.85-fold in HF and 1.53-fold in BS cows receiving 3-NOP. Further, a 3-NOP × time interaction occurred for both breeds. In BS cows, 3-NOP tended to reduce CH4 production by 18% at approximately 4 h after morning feeding, but no effect was observed at other time points. In HF cows, the greatest mitigation effect of 3-NOP (29.6%) was observed immediately after morning feeding, and it persisted at around 23% to 26% for 10 h until the second feed provision, and 3 h thereafter, in the evening. In conclusion, supplementing 3-NOP at 60 mg/kg DM to a high-fiber diet resulted in 18% to 19% reduction in enteric CH4 emission in Swiss HF cows. The lower response to 3-NOP by BS cows was unexpected and has not been observed in other studies. These results should be interpreted with caution due to the low number of cows per breed. Finally, supplementing WCS at 5% of DM improved ECM and milk fat yield but did not enhance the CH4 inhibition effect of 3-NOP of dairy cows.

Innovations in Cattle Farming: Application of Innovative Technologies and Sensors in the Diagnosis of Diseases

Precision livestock farming has a crucial function as farming grows in significance. It will help farmers make better decisions, alter their roles and perspectives as farmers and managers, and allow for the tracking and monitoring of product quality and animal welfare as mandated by the government and industry. Farmers can improve productivity, sustainability, and animal care by gaining a deeper understanding of their farm systems as a result of the increased use of data generated by smart farming equipment. Automation and robots in agriculture have the potential to play a significant role in helping society fulfill its future demands for food supply. These technologies have already enabled significant cost reductions in production, as well as reductions in the amount of intensive manual labor, improvements in product quality, and enhancements in environmental management. Wearable sensors can monitor eating, rumination, rumen pH, rumen temperature, body temperature, laying behavior, animal activity, and animal position or placement. Detachable or imprinted biosensors that are adaptable and enable remote data transfer might be highly important in this quickly growing industry. There are already multiple gadgets to evaluate illnesses such as ketosis or mastitis in cattle. The objective evaluation of sensor methods and systems employed on the farm is one of the difficulties presented by the implementation of modern technologies on dairy farms. The availability of sensors and high-precision technology for real-time monitoring of cattle raises the question of how to objectively evaluate the contribution of these technologies to the long-term viability of farms (productivity, health monitoring, welfare evaluation, and environmental effects). This review focuses on biosensing technologies that have the potential to change early illness diagnosis, management, and operations for livestock.

Recent Advances on Early Detection of Heat Strain in Dairy Cows Using Animal-Based Indicators: A Review

In pursuit of precision livestock farming, the real-time measurement for heat strain-related data has been more and more valued. Efforts have been made recently to use more sensitive physiological indicators with the hope to better inform decision-making in heat abatement in dairy farms. To get an insight into the early detection of heat strain in dairy cows, the present review focuses on the recent efforts developing early detection methods of heat strain in dairy cows based on body temperatures and respiratory dynamics. For every candidate animal-based indicator, state-of-the-art measurement methods and existing thresholds were summarized. Body surface temperature and respiration rate were concluded to be the best early indicators of heat strain due to their high feasibility of measurement and sensitivity to heat stress. Future studies should customize heat strain thresholds according to different internal and external factors that have an impact on the sensitivity to heat stress. Wearable devices are most promising to achieve real-time measurement in practical dairy farms. Combined with internet of things technologies, a comprehensive strategy based on both animal- and environment-based indicators is expected to increase the precision of early detection of heat strain in dairy cows.

Evaluation of ruminal motility using an indwelling 3-axis accelerometer in the reticulum in cattle

Attempts to increase production and improve farm environments have been made for several years. Rumen motility (RM) is one of the biological parameters that provides essential information of individuals in ruminants, and it is usually evaluated by auscultation. The study was aimed to examine RM using the 3-axis accelerometer (3XA) in cattle. The manufactured 3XA were placed in the reticulum (3XA-R) and implanted in the subcutaneous layer of the brisket (3XA-SC), respectively, and the accelerations were compared following intramuscular injection of xylazine (0.05 mg/kg) or saline in experiment 1 and of xylazine (0.05 mg/kg) or atropine (0.04 mg/kg) in experiment 2. In experiment 3, the dose-dependent decrease of RM was evaluated following xylazine administration (0, 0.05, 0.1 mg/kg) in the 3XA-R equipped cows via a 3 × 3 Latin square method. In experiment 1, saline-treated animals showed a continuous fluctuation while the frequency and amplitude of 3XA-R in xylazine-injected cows were reduced after administration. The acceleration of 3XA-SC was changed after administration, but not abruptly. Among the motion parameters, V2 was calculated only using X- and Z-axis acceleration in consideration of the cylindrical shape, and it showed the apparent difference between pre- and post-xylazine administration. In experiment 2, the V2 of 3XA-R was decreased after atropine administration while that of 3XA-SC was maintained. In experiment 3, a dose-dependent V2 decrement of 3XA-R after xylazine administration was observed and lasted for 40 and 80 min in doses of 0.05 mg/kg and 0.1 mg/kg, respectively. In conclusion, The 3XA detected the decrease in RM efficiently and processed the data wirelessly without interference from body movement. This technology will help detect problems early and prevent a decline in cattle productivity.

Mitigation of greenhouse gases in dairy cattle via genetic selection: 1. Genetic parameters of direct methane using noninvasive methods and proxies of methane

Records of methane emissions from 1,501 cows on 14 commercial farms in 4 regions of Spain were collected from May 2018 to June 2019. Methane concentrations (MeC) were measured using a nondispersive infrared methane detector installed within the feed bin of the automatic milking system during 14- to 21-d periods. Rumination time (RT; min/d) was collected using collars with a tag that registered time (minutes) spent eating and ruminating. The means of MeC and methane production (MeP) were 1,254.28 ppm and 182.49 g/d, respectively; mean RT was 473.38 min/d. Variance components for MeC, MeP, and RT were estimated with REML using pedigree and genomic information in a single-step model. Heritabilities for MeC and MeP were 0.11 and 0.12, respectively. Rumination time showed a slightly larger heritability estimate (0.17). The genetic correlation between MeP and MeC was high (>0.95), suggesting that selection on either trait would lead to a positive correlated response on the other. Negative correlations were estimated between RT and MeC (-0.24 ± 0.38) and MeP (-0.43 ± 0.35). Methane concentration and MeP had slightly positive correlations with milk yield (0.17 ± 0.39 and 0.21 ± 0.36), protein percentage (0.08 ± 0.32 and 0.30 ± 0.45), protein yield (0.22 ± 0.41 and 0.31 ± 0.35), fat percentage (0.02 ± 0.40 and 0.27 ± 0.36), and fat yield (0.27 ± 0.28 and 0.29 ± 0.28) from bivariate analyses. Rumination time had positive correlations with milk yield (0.41 ± 0.75) and protein yield (0.26 ± 0.57) and negative correlations with fat yield (-0.45 ± 0.32), protein percentage (-0.15 ± 0.38), and fat percentage (-0.40 ± 0.47). A positive approximated genetic correlation was estimated between fertility and MeC (0.10 ± 0.05) and MeP (0.18 ± 0.05), resulting in slightly higher CH₄ production when selecting for better fertility [days open estimated breeding values (EBV) are expressed with mean 100 and SD 10, inversely related to days from calving to conception; that is, greater days open EBV implies better fertility]. Positive correlations were also estimated for stature with MeC and MeP (0.30 ± 0.04 and 0.43 ± 0.04, respectively). Other type traits (chest width, udder depth, angularity, and capacity) were positively correlated with methane traits, possibly because of higher milk yield and higher feed intake from these animals. Rumination time showed positive EBV correlations with production traits and type traits, and negative correlations with somatic cell count and body condition score. Based on the genetic correlations and heritabilities estimated in this study, methane is measurable and heritable, and estimates of genetic correlations suggest no strong opposition to current breeding objectives in Spanish Holsteins.

An Automatic Head Surface Temperature Extraction Method for Top-View Thermal Image with Individual Broiler

Surface temperature variation in a broiler’s head can be used as an indicator of its health status. Surface temperatures in the existing thermograph based animal health assessment studies were mostly obtained manually. 2185 thermal images, each of which had an individual broiler, were captured from 20 broilers. Where 15 broilers served as the experimental group, they were injected with 0.1mL of pasteurella inoculum. The rest, 5 broilers, served as the control group. An algorithm was developed to extract head surface temperature automatically from the top-view broiler thermal image. Adaptive K-means clustering and ellipse fitting were applied to locate the broiler’s head region. The maximum temperature inside the head region was extracted as the head surface temperature. The developed algorithm was tested in Matlab^® (R2016a) and the testing results indicated that the head region in 92.77% of the broiler thermal images could be located correctly. The maximum error of the extracted head surface temperatures was not greater than 0.1 °C. Different trend features were observed in the smoothed head surface temperature time series of the broilers in experimental and control groups. Head surface temperature extracted by the presented algorithm lays a foundation for the development of an automatic system for febrile broiler identification.

Evaluation of ruminal motility in cattle by a bolus-type wireless sensor

We evaluated the relationship between ruminal motility measured by a force transducer and acceleration measured by bolus sensor, and we assessed the detection of ruminal motility in cattle by a bolus-type wireless sensor. The bolus sensor can be orally administered to cattle and was placed in the reticulum for continuous measurements. The probe was almost horizontal to the longitudinal axis. The bolus sensor's basic y-axis acceleration movement appeared to have a very distinct vertical pattern, occurring roughly 1-1.5 times/min with a duration of approximately 8 sec, displaying at around 500 mG. A significant positive correlation was observed between the ruminal contraction revealed by the force transducer and the acceleration shown by the bolus sensor (P<0.01). The contraction of the dorsal sac of the rumen and the acceleration signals in the reticulum occurred at practically the same time. The frequency and amplitude of ruminal contraction demonstrated by the bolus sensor and the force transducer in feeding were significantly higher than those at rest (P<0.01). The bolus sensor could also detect ruminal atony in the cattle after the administration of xylazine. A bolus-type wireless sensor may thus be useful for the measurement of ruminal motility in cattle and for detecting rumen dysfunction (e.g., ruminal atony).

WSMS: Wearable Stress Monitoring System based on IoT Multi-Sensor Platform for Living Sheep Transportation

Farming herdsmen, sheep dealers, and veterinarians are increasingly interested in continuously monitoring sheep basic physiological characteristics (such as the heart rate and skin temperature) outside the laboratory environment, with the aim of identifying the physiological links between stress, uncomfortable, excitement, and other pathological states. This paper proposes a non-invasive Wearable Stress Monitoring System (WSMS) with PhotoPlethysmoGram (PPG), Infrared Temperature Measurement (ITM), and Inertial Measurement Units (IMU) that aimed to remotely and continuously monitor the stress signs of sheep during transportation. The purpose of this study was implemented by following the multi-dimensional sensing platform to identify more pressure information. The designed WSMS showed sufficient robustness in recording and transmitting sensing data of physiology and environment during transport. The non-contact and non-destructive monitoring method that was proposed in this paper was helpful in minimizing the effects of sheep stress load.

Identification of the Rumination in Cattle Using Support Vector Machines with Motion-Sensitive Bolus Sensors

The reticuloruminal function is central to the digestive efficiency in ruminants. For cattle, collar- and ear tag-based accelerometer monitors have been developed to assess the time spent ruminating on an individual animal. Cattle that are ill feed less and so ruminate less, thus, the estimation of the time spent ruminating provides insights into the health of individual animals. pH boluses directly provide information on the reticuloruminal function within the rumen and extended (three hours or more) periods during which the ruminal pH value remains below 5.6 is an indicator that dysfunction and poor welfare are likely. Accelerometers, incorporated into the pH boluses, have been used to indicate changes in behaviour patterns (high/low activity), utilised to detect the onset of oestrus. The paper demonstrates for the first time that by processing the reticuloruminal motion, it is possible to recover rumination periods. Reticuloruminal motion energy and the time between reticuloruminal contractions are used as inputs to a Support Vector Machine (SVM) to identify rumination periods with an overall accuracy of 86.1%, corroborated by neck mounted rumination collars.

Invited review: Current perspectives on eating and rumination activity in dairy cows

Many early studies laid the foundation for our understanding of the mechanics of chewing, the physiological role of chewing for the cow, and how chewing behavior is affected by dietary characteristics. However, the dairy cow has changed significantly over the past decades, as have the types of diets fed and the production systems used. The plethora of literature published in recent years provides new insights on eating and ruminating activity of dairy cows. Lactating dairy cows spend about 4.5 h/d eating (range: 2.4-8.5 h/d) and 7 h/d ruminating (range: 2.5-10.5 h/d), with a maximum total chewing time of 16 h/d. Chewing time is affected by many factors, most importantly whether access to feed is restricted, intake of neutral detergent fiber from forages, and mean particle size of the diet. Feed restriction and long particles (≥19 mm) have a greater effect on eating time, whereas intake of forage neutral detergent fiber and medium particles (4-19 mm) affects rumination time. It is well entrenched in the literature that promoting chewing increases salivary secretion of dairy cows, which helps reduce the risk of acidosis. However, the net effect of a change in chewing time on rumen buffing is likely rather small; therefore, acidosis prevention strategies need to be broad. Damage to plant tissues during mastication creates sites that provide access to fungi, adhesion of bacteria, and formation of biofilms that progressively degrade carbohydrates. Rumination and eating are the main ways in which feed is reduced in particle size. Contractions of the rumen increase during eating and ruminating activity and help move small particles to the escapable pool and into the omasum. Use of recently developed low-cost sensors that monitor chewing activity of dairy cows in commercial facilities can provide information that is helpful in management decisions, especially when combined with other criteria. Although accuracy and precision can be somewhat variable depending on sensor and conditions of use, relative changes in cow behavior, such as a marked decrease in rumination time of a cow or sustained low rumination time compared with a contemporary group of cows, can be used to help detect estrus, parturition, and some illnesses. This review provides a comprehensive understanding of the dietary, animal, and management factors that affect eating and ruminating behavior in dairy cows and presents an overview of the physiological importance of chewing with emphasis on recent developments and practical implications for feeding and managing the modern housed dairy cow.