James W Oltjen

Research and Extension Programs

Livestock quality assurance programs, natural resource monitoring and modeling, specific research trials, and simultaneous development of computer decision aids describe my research efforts. These programs assist in cattle performance prediction to improve beef quality and reduce product variation, dairy cow culling and replacement decision making, cowherd health and breeding management, prediction of water use for beef production, economic analysis of cow-calf enterprises, and improved supplementation strategies to complement forage resources for beef cow herds.

Our previously developed growth and composition simulation models have been used to predict performance and predicted days on feed of incoming feedlot cattle. In trials we conducted recently, cattle were sorted by predicted days on feed to reach low choice, and variation in carcass grades and feedlot costs were observed and reported. Ultrasonic back fat and frame score, along with breed type and body weight, were identified as needed inputs to precisely model future performance. These predictions are now available in TAURUS, our beef cattle rations formulation and performance prediction software. I am also continuing work to refine specific nutrient needs and growth responses for cattle.

I have extended my previously developed expert system for beef cattle for reproduction and production projection of dairy cattle. We have used California data to rank cows based on value. As California’s contribution to NC-119 data has been collected on dairy cow parameters necessary for the model, including death rates and forced removal due to injury or disease. Also, season of calving and lactation number had a significant influence on time to conception assessed by survival analysis, but level of milk production did not. Product limit estimates of days open showed that conventional analysis markedly over-estimated reproductive performance by excluding data from censored cows. Lactation number and milk production level also had a significant influence on culling risk. The results of these studies are being used for supplying herd life, reproductive, and mastitis parameters needed for the development of an improved dairy culling decision support systems. The model is currently implemented on EXCEL 5.0, and a module which can be directly used in commercial software is under development.

“Back In The Black” is a two part course that helps ranchers assess the economic health of their business and determine the profitability of management decisions. In session one a facilitator guides ranchers through a workbook as they assess the condition of a hypothetical, but typical ranch. In the second part of the course participants enter their ranch data into an EXCEL 5.0 template with multiple input, report, and analysis sheets An option for easily changing any input data is included, allowing rapid evaluation of changing management options on profitability. Attendees report increased confidence in understanding effects of strategic management decisions for their ranch and the ability to investigate more options.

I am testing management strategies to optimize forage use and cow productivity, including developing supplementation protocols and utilizing varied grazing intensities for profitable production, with long-term stability of the grazing resource. This long-term experiment, conducted at the Sierra Foothill Research and Extension Center, is aimed at examination of interactions between cow condition, time of year, grazing intensity (stocking rate) and feed supplementation. To this end, three supplementation strategies (none, standard and strategic) are being used in conjunction with two stocking rates ( moderate and heavy). Supplementation is provided during all dry-feed seasons for the standard group, and strategic treatment cows with low condition score are grouped with standard cows during the next period. Stocking rates are maintained during the critical green forage availability time of year, late Fall and Winter. Results of the first two years have been reported; further data is needed and will be used for definition of a response surface to improve a computer model used to project cow performance.