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Advancements in technology have ushered in a new era of sensor-based measurement and management of livestock production systems. These sensor-based technologies have the ability to automatically monitor feeding, growth, and enteric emissions for individual animals across confined and extensive production systems. One challenge with sensor-based technologies is the large amount of data generated, which can be difficult to access, process, visualize, and monitor information in real time to ensure equipment is working properly and animals are utilizing it correctly. A solution to this problem is the development of application programming interfaces (APIs) to automate downloading, visualizing, and summarizing datasets generated from precision livestock technology. For this methods paper, we develop three APIs and accompanying processes for rapid data acquisition, visualization, systems tracking, and summary statistics for three technologies (SmartScale, SmartFeed, and GreenFeed) manufactured by C-Lock Inc (Rapid City, SD). Program R markdown documents and example datasets are provided to facilitate greater adoption of these techniques and to further advance precision livestock technology. The methodology presented successfully downloaded data from the cloud and generated a series of visualizations to conduct systems checks, animal usage rates, and calculate summary statistics. These tools will be essential for further adoption of precision technology. There is huge potential to further leverage APIs to incorporate a wide range of datasets such as weather data, animal locations, and sensor data to facilitate decision-making on times scales relevant to researchers and livestock managers. [ABSTRACT FROM AUTHOR]

SmartWater is an automatic watering station that measures the volume of water consumed by individual animals when visiting the system. The self-contained, portable system is constructed of a steel frame, two load cells, and a stainless-steel water trough that measures 0.1 m3 with a water capacity of 113 L. SmartWater refills automatically when the water mass is below 55 L, refilling for 120 s, or until the water mass reaches 70 L. The flow rate of water entering the system and the weight of the bin are measured every second in L/s and L, respectively. When the bin is being refilled, animals are still able to drink from the system. Animal water intake during a visit is measured by summing the amount of water dispensed into the bin and the difference in bin weight at the start and end of the visit. Water intake days are considered valid if the unknown percentage is less than 5% of the total daily water intake, where unknown intake is defined as feed mass disappearance that cannot be assigned to an EID. Invalid days are excluded from final datasets. System performance was evaluated using 17 Angus heifers (body weight = 248 ± 37 kg) in a 55-d trial period. Animals were given ad libitum access to two SmartWater systems, and all animals successfully adapted to the system. Mean daily visitation was 2.7 ± 0.4 and average visit length was 87 ± 175 s. Mean water consumption over the trial period was 13.7 ± 1.8 L. The coefficient of variance of water consumption between animals was 12.8%. The average standard deviation water consumption within animals between days was 5.9%. SmartWater provides an accurate and efficient way to measure water intake of animals in extensive and intensive systems, eliminating the need to manually monitor water levels and refill watering stations. [ABSTRACT FROM AUTHOR]

Although some research has explored emerging adults' motives for using mobile dating applications, no studies have investigated motives for in-person (or offline) meetings with dating app matches. A sample of 267 U.S. college students completed an online survey, 138 of whom were dating app users and 80 of those had met at least one match in person. Contrary to the popular view that dating apps promote casual sex, love was the top motive for in-person meeting with matches. Our findings are consistent with the idea that dating apps are used to connect with others, not just for hookups. [ABSTRACT FROM AUTHOR]

Alternative management strategies with no cows and all heifers may improve biological and economic efficiency of beef production. The All Heifer, No Cow (AHNC) beef production system involves insemination of nulliparous heifers with female sex-selected semen (FSS) to produce primarily female calves that are early weaned at 3 mo of age. Dams are finished on a high concentrate diet and harvested before 30 mo of age. The objectives of this research were to: 1) build a dynamic model of an AHNC beef production system to quantify system biological and economic efficiency; 2) compare effects of utilizing FSS vs. conventional semen on biological and economic efficiency; 3) evaluate what-if scenarios to determine the effects on biological and economic efficiency of changing variables ±5%, 10%, 15%, and 20% from initial observed values; and 4) evaluate the effects on biological and economic efficiency of changing variables ±10% from initial observed values. A model was built over a 21-yr horizon using Stella Architect. Biological parameter values in the model were based on the 6 yr of data collected from the management of an AHNC demonstration herd. In the model animal, total digestible nutrients (TDN) intake, hot carcass weight (HCW), and age at harvest were randomized. Feed, animal, and carcass prices included in the model were based on 10 yr of historical U.S. price data. Key response variables were biological and economic efficiency (mean ± SD). Biological efficiency was defined as the ratio of output (kilograms of HCW produced) to input (lifetime kilograms of feed TDN consumed), and economic efficiency was measured using a benefit–cost ratio (BCR) and unit variable cost (UVC). Over 40 simulation runs, the predicted mean biological efficiency was 0.0714 ± 0.0008. Economic efficiency was 0.95 ± 0.02 and US $445.41 ± 0.06 for BCR and UVC, respectively. Biological and economic efficiency was improved in the conventional semen scenario; biological efficiency was 0.0738 ± 0.0008, and BCR and UVC were 0.99 ± 0.04 and US $407.24 ± 0.006, respectively. Under this parameterization and market conditions, the AHNC beef production system failed to achieve profitability under any scenario that was evaluated. However, this review did not account for the potential increased genetic benefit from a decreased generation interval and the reduction in feed energy in comparison to a conventional cow/calf system. [ABSTRACT FROM AUTHOR]

Decreasing variation in a pen of feedlot cattle reduces overfeeding, increases carcass quality and uniformity, and improves economic returns. The objective of this study was to evaluate the effect of sorting by body weight (BW) or expected days on feed (DOF) on pen performance and profitability. Ninetysix Angus-cross steers (initial BW = 360 ± 28 kg) were randomly assigned to sorting by BW or DOF determined using the Davis Growth Model and initial body measurements for BW, hip height, back fat thickness (BF), and ribeye area. Steers within BW and DOF sort groups were randomly assigned to one of two replicates. Within replicate, BW groups were divided into light and heavy pens (initial BW = 323 and 366 kg, respectively), and DOF groups were divided into short and long pens (DOF = 119 and 160 d, respectively), for a total of 8 pens with 12 steers in each pen. Pen feeding was managed using the slick bunk method and time of marketing was determined based on observation of an average pen BF of 1.1 cm. Steers were harvested at a commercial abattoir and individual carcass characteristics were recorded. Profit was calculated as carcass value minus feed costs. For comparison of sorting treatments, pen was the experimental unit, and treatment means and variances were compared using a t-test and F-test, respectively. Steers were harvested in three groups: both heavy-BW sort pens and both short-DOF sort pens were harvested after 84 d, both long-DOF sort pens and one light-BW sort pen were harvested after 104 d, and the final light-BW sort pen was harvested after 116 d on the finishing ration. There were no differences in mean initial BW (P = 0.95) or initial percent empty body fat (EBF; P = 0.28), but variation in initial BW was reduced (P < 0.01) for the BW sort group. Final mean BW did not differ between sort groups (P = 0.54), but variance in final BW and hot carcass weight was less (P < 0.01) for the group sorted by BW. Final percent EBF also did not differ between groups (P = 0.41), but percent EBF variance was 2.4 %-units for DOF and 2.9 %-units for BW sorted pens, although differences were not statistically significant. There were no differences in average daily gain or feed conversion rate between sort groups. Variation in yield grade, BF, and marbling score were numerically reduced for the DOF group; however, differences were not statistically significant (P > 0.10). Average profit per steer was $ 321.42 and $ 235.05 for DOF and BW sorted groups, respectively. Sorting by DOF increased profitability by 26% by increasing harvest BW, improving uniformity, and decreasing overweight carcasses. [ABSTRACT FROM AUTHOR]

The Beef Improvement Federation recommends repeated body weight (BW) measures in a 70-d test period for accurate assessment of average daily gain (ADG) in growing animals. In-pen automated scale systems enable daily monitoring of BW and ADG without the additional labor, time, and animal stress that is associated with recording static chute BW. The objective of the current study was to determine the utility of partial body weight (pBW) for estimating full BW and average daily gain (ADG) in growing steers. SmartScales (C-Lock Inc.) were positioned in front of water troughs and used to measure front-quarter pBW while animals were drinking. Partial body weight was used to estimate full BW using an internally developed slope-intercept equation. The dataset consisted of pBW, estimated BW, and recorded BW for 300 steers in a 50-d feed performance test. Single-day chute BW were recorded on days 14, 28, 35, and 50. Relationships and errors between estimated BW and recorded BW were evaluated. Individual animal ADG estimates were calculated and compared using estimated and recorded BW measurements. Steers in the study visited the water trough an average of 4.3 ± 2.6 times per day. On average, pBW explained 96.1% variation in recorded BW. Average predicted BW and recorded BW differed by 8.3 ± 6.4 kg, or 0.15 ± 3.0 %-units. Average daily gain calculated from pBW and recorded BW were strongly correlated (r = 0.83). On average, ADG calculated using pBW and recorded BW differed by 0.14 ± 0.12 kg, or 8.8 ± 8.0 %-units. Real-time pBW collected using in-pen weighing systems can be used to accurately estimate full BW and ADG. [ABSTRACT FROM AUTHOR]

The Davis Growth Model is a dynamic model used to estimate body composition and growth in beef cattle by simulating total body DNA and protein turnover. Since model development and parametrization in the 1980s, the model has been re-structured to account for previous rate of protein accretion and prior nutrition. Original parameter estimates for alpha (maintenance constant, where net energy for maintenance is alpha x shrunk body weight0.75; 0.08406) and K2 (protein synthesis rate constant; 0.0444) may not fit modern, heavier, more productive cattle. Angus-cross steers (n = 24; initial body weight 402 ± 12 kg) were fed using automated feed weight stations in group pens (8 steers/pen). Steers were fed a high energy ration twice daily, at 10% greater than the intake from the previous day. Steers were measured for hip height, body weight (BW), and ultrasonic measurements for ribeye area and back fat every 28 d until harvest (d 128). These measurements were used to calculate empty BW, empty body fat, and empty percent body fat for alpha and K2 estimates. Parameter estimates (± SD) were 0.12661 (0.01587) and 0.04919 (0.00220) for alpha and K2, respectively. Parameter estimates in the current study reflect a large increase in apparent maintenance. Maintenance requirements were moderately correlated with back fat thickness and feed conversion efficiency. Protein turnover had very strong correlations with ribeye area and feed conversion efficiency. Average feed conversion efficiency in the current study was 0.17. To evaluate parameter estimates, the model was re-run using the new values for alpha and K2. On average, the model underpredicted final empty body weight by 0.08 kg and empty body fat percent by 0.01%-units. Considering the relatively large variation among observed alpha values and the magnitude of increase compared with those previously reported, further research is required to determine an accurate alpha. [ABSTRACT FROM AUTHOR]