Oklahoma!

Oklahoma! is the first musical written by the team of composer Richard Rodgers and Oscar Hammerstein. The musical is set in Oklahoma Territory outside the town of Claremore in 1906, it tells the story of cowboy Curly McLain and his romance with farm girl Laurey Williams. A secondary romance concerns cowboy Will Parker and his flirtatious fiancée, Ado Annie. The original Broadway production opened on March 31, 1943. It was a box-office smash and ran for an unprecedented 2,212 performances. Oklahoma!. (2017, April 24). In Wikipedia, The Free Encyclopedia. Retrieved 21:06, May 23, 2017, from https://en.wikipedia.org/w/index.php?title=Oklahoma!&oldid=776919771https://digitalcommons.otterbein.edu/production_1958-1959/1003/thumbnail.jp

Supporting the development and adoption of automatic lameness detection systems in dairy cattle : effect of system cost and performance on potential market shares

Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was (sic)2.57 per % less missed lame cows, (sic)1.65 per % less false alerts, and (sic)12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system's potential adoption rate

Benefits of spatio-temporal modelling for short term wind power forecasting at both individual and aggregated levels

The share of wind energy in total installed power capacity has grown rapidly in recent years around the world. Producing accurate and reliable forecasts of wind power production, together with a quantification of the uncertainty, is essential to optimally integrate wind energy into power systems. We build spatio-temporal models for wind power generation and obtain full probabilistic forecasts from 15 minutes to 5 hours ahead. Detailed analysis of the forecast performances on the individual wind farms and aggregated wind power are provided. We show that it is possible to improve the results of forecasting aggregated wind power by utilizing spatio-temporal correlations among individual wind farms. Furthermore, spatio-temporal models have the advantage of being able to produce spatially out-of-sample forecasts. We evaluate the predictions on a data set from wind farms in western Denmark and compare the spatio-temporal model with an autoregressive model containing a common autoregressive parameter for all wind farms, identifying the specific cases when it is important to have a spatio-temporal model instead of a temporal one. This case study demonstrates that it is possible to obtain fast and accurate forecasts of wind power generation at wind farms where data is available, but also at a larger portfolio including wind farms at new locations. The results and the methodologies are relevant for wind power forecasts across the globe as well as for spatial-temporal modelling in general

Comparison of performance and fitness traits in German Angler, Swedish Red and Swedish Polled with Holstein dairy cattle breeds under organic production

Although the use of local breeds is recommended by organic regulations, breed comparisons performed under organic production conditions with similar production intensities are scarce. Therefore, we compared data of local and widely used Holstein dairy cattle breeds from 2011 to 2015 regarding production, fertility and health from German and Swedish organic farms with similar management intensities within country. In Germany, the energy-corrected total milk yield tended to be lower in the local breed Original Angler Cattle (AAZ, 5193 kg) compared to the modern German Holstein Friesian breed (HO, 5620 kg), but AAZ showed higher milk fat and protein contents (AAZ v. HO: 5.09% v. 4.18% and 3.61% v. 3.31%, respectively). In Sweden, the widely used modern Swedish Holstein (SH) breed had the highest milk yield (9209 kg, fat: 4.10%, protein: 3.31%), while the local Swedish Polled (SKB) showed highest milk yield, fat and protein contents (6169 kg, 4.47%, 3.50%, respectively), followed by the local breed Swedish Red (SRB, 8283 kg, 4.33%, 3.46%, respectively). With regard to fertility characteristics, the German breeds showed no differences, but AAZ tended to have less days open compared to HO (−17 days). In Sweden, breeds did not differ with regard to calving interval, but both local breeds showed a lower number of days open (−10.4 in SRB and −24.1 in SKB compared to SH), and SKB needed fewer inseminations until conception (−0.5 inseminations) compared to SH. Proportion of test day records with a somatic cell count content of ≥100 000 cells per ml milk did not reveal breed differences in any of the two countries. German breeds did not differ regarding the proportion of cows with veterinary treatments. In Sweden, SRB showed the lowest proportion of cows with general veterinary treatment as well as specific treatment due to udder problems (22.8 ± 6.42 and 8.05 ± 2.18, respectively), but the local breed SKB did not differ from SH in either of the two traits. In Sweden, we found no breed differences regarding veterinary treatments due to fertility problems or diagnosis of claw or leg problems during claw trimming. Our results indicate a stronger expression of the antagonism between production and functional traits with increasing production intensity. Future breed comparisons, therefore, need to consider different production intensities within organic farming in order to derive practical recommendations as to how to implement European organic regulations with regard to a suitable choice of breeds

Co-designing climate-smart farming systems with local stakeholders: A methodological framework for achieving large-scale change

The literature is increasing on how to prioritize climate-smart options with stakeholders but relatively few examples exist on how to co-design climate-smart farming systems with them, in particular with smallholder farmers. This article presents a methodological framework to co-design climate-smart farming systems with local stakeholders (farmers, scientists, NGOs) so that large-scale change can be achieved. This framework is based on the lessons learned during a research project conducted in Honduras and Colombia from 2015 to 2017. Seven phases are suggested to engage a process of co-conception of climate-smart farming systems that might enable implementation at scale: (1) “exploration of the initial situation,” which identifies local stakeholders potentially interested in being involved in the process, existing farming systems, and specific constraints to the implementation of climate-smart agriculture (CSA); (2) “co-definition of an innovation platform,” which defines the structure and the rules of functioning for a platform favoring the involvement of local stakeholders in the process; (3) “shared diagnosis,” which defines the main challenges to be solved by the innovation platform; (4) “identification and ex ante assessment of new farming systems,” which assess the potential performances of solutions prioritized by the members of the innovation platform under CSA pillars; (5) “experimentation,” which tests the prioritized solutions on-farm; (6) “assessment of the co-design process of climate-smart farming systems,” which validates the ability of the process to reach its initial objectives, particularly in terms of new farming systems but also in terms of capacity building; and (7) “definition of strategies for scaling up/out,” which addresses the scaling of the co-design process. For each phase, specific tools or methodologies are used: focus groups, social network analysis, theory of change, life-cycle assessment, and on-farm experiments. Each phase is illustrated with results obtained in Colombia or Honduras

Occurrence of preterm calving in Great Britain and associations with milk production and reproductive performance in dairy cattle

This study describes the occurrence of preterm calving in Great Britain and evaluates its associations with subsequent milk production and reproductive performances and survival on farm of dairy cows. A total of 53 British dairy farms and 5759 animals with detailed breeding and milk recording data available were used to form two study groups: preterm calving (calving occurring between days 266 and 277 of gestation) and full-term calving (calving occurring at 278 days of gestation and over). Mixed effects models were implemented to compare milk production, clinical cases of mastitis and number of services per conception between groups. Kaplan-Meier curves and Cox regression analyses compared time from calving to conception, calving interval and survival on farm between groups. Preterm calving cows showed significantly lower milk yield (P<0.01) and butter fat per cent (P=0.02), increased milk protein per cent (P=0.01), longer survival on farm (P<0.01), and a tendency for shorter calving to conception intervals and fewer services per conception, although other factors were involved in the reproduction outcomes. Experiencing a preterm calving is associated with lower milk production and longer survival times on farm. Potential risk factors for preterm calving, such as infectious diseases, diet and husbandry practices, should be further investigated