Masters Theses in the Pure and Applied Sciences was first conceived, published, and disseminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS) * at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dissemination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all con cerned if the printing and distribution of the volumes were handled by an interna tional publishing house to assure improved service and broader dissemination. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Cor poration of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 34 (thesis year 1989) a total of 13,377 theses titles from 26 Canadian and 184 United States universities. We are sure that this broader base for these titles reported will greatly enhance the value of this important annual reference work. While Volume 34 reports theses submitted in 1989, on occasion, certain univer sities do report theses submitted in previous years but not reported at the time.

The objectives of this research were to: 1) express variation in DHIA herd performance measures by means of a limited number of factors; 2) determine the relationship of DHIA performance measures to profit score and their sensitivity to market price changes; and 3) identify which herd performance measures changes were associated with profit score changes over a five-year horizon. For the variability in DHIA herd performance measures, large variation among herds would indicate notable opportunity for changing management strategy. It was concluded that three independent factors offer the greatest opportunity for improvement within most production subsets. Notably, the reproductive measures of calving interval, days open, and percent cows bred> 3 times accounted for a large portion of variability among herds. Also, considerable variation among herds for percent cows with SCS 4-5 and cows with SCS> 5 suggests that management practices or their successful implementation at preventing mastitis differ greatly from farm to farm. Simple regression was used for determining the relationship of DHIA performance measures to profit score and the sensitivity of performance measures to market price changes. It was determined that 1) several measures were related to profit score by quadratic effects; 2) for measures with quadratic relationship to profit score, resulting changes in score for herds are dependent on the current herd performance for the respective measure, and 3) milk yield was not the only measure that significantly impacted profit score. Sensitivity analysis indicated that several of the performance measures were sensitive to milk price changes. These price sensitivities suggest that producers need to consider economic conditions when assessing the importance of different management changes. Lastly, herds which differed in realized changes for profit score over a five-year horizon were identified, characterized for performance measures, and performance changes that were associated with profit score changes were determined. Changes in milk yield were not associated with changes in profit score for herds that either significantly or consistently increase profit over time. Rather, it was shown that average annual changes in reproductive measures had a more important effect on changes in profit score for herds that were less profitable.

Today's dairy industry is complex and continuously improving. A producer's management of the operation is the most important item on the road to profitability. Since dairy farms are so complex, producers must master managing all of the areas of the business in order to achieve maximum profitability and productivity. Feed is the largest expense in producing milk. This makes proper management of feeding and nutrition pivotal to both profitability and productivity. Management of profit margins is necessary in order to make the best decisions for the dairy business. The effective use of different management tools, such as income over feed cost and dairy advisory teams, can lead to better profitability and productivity by helping dairy producers make the best management decisions. This thesis will discuss three studies that investigated 1) milk income and feed cost profit margins 2) current feed management on dairy farms, with an interest in by-product feed management 3) and the use of dairy advisory teams to improve overall farm success. With volatility in feed and milk markets, income over feed cost (IOFC) is a more advantageous measure of profit than simply feed cost per cow. The Pennsylvania State Extension Dairy Team IOFC tool was used to collect data from 95 Pennsylvania lactating dairy cow herds from 2009-2012 and to determine IOFC per cow per day. The data collected included average milk yield, milk income, purchased feed cost, ration ingredients, ingredient cost per ton, and amount of each ingredient fed. Feed costs for home-raised feeds for each ration were based on market values rather than on actual on-farm cost. Actual costs were used for purchased feed for each ration. Mean lactating herd size was 170 ±10.5 cows, and daily milk yield per cow was 31.7 kg ± 0.19kg. Mean IOFC was $7.71 ±$1.01 cost per cow ranging from -$0.33 in March, 2009 to $16.60 in September, 2011. Data was analyzed using a one-way ANOVA in SPSS. Values were grouped by quartiles and analyzed with all years combined as well as by individual year. Purchased feed cost per cow per day averaged $3.16 ± $1.07 for 2009-2012. For 2009-2012 combined, milk yield and IOFC did not differ with purchased feed cost. Intermediate levels (quartiles 2 and 3) of forage cost per cow per day between $1.45 and $1.97 per cow per day resulted in the greatest average IOFC of $8.19 and the greatest average milk yield of 32.3kg. Total feed costs in the fourth quartile ($6.27 or more per cow per day) resulted in the highest IOFC. Thus, minimizing feed cost per cow per day did not maximize IOFC. In 2010, the IOFC was highest at $8.09 for dairies that fed one or more commodity by-product feeds.Due to tight profit margins and volatility in feed costs, many producers incorporate by-product feeds into their rations. This study used an electronic survey to gather information about feeding management and the use of by-product feeds in rations for Pennsylvania dairy farms in 2013. The survey was sent to 200 dairy farms via email, and 41 surveys were completed. The survey was first sent out in November 2013 and the last response was received in April 2014. All data were collected for the month of September 2013. Survey responses showed that most (97.6%) of the responding Pennsylvania (PA) dairy producers fed a total mixed ration (TMR). Over half (58.5%) of the producers fed a 60:40 forage to concentrate ratio for the ration. Distillers grains and brewer's grains and yeasts were the most commonly used by-product feeds. Producers analyzed dry matter weekly or biweekly (60.9 %) or when switching feeds (34.1 %). Most TMR and forage nutrient testing was done when switching feeds, except for by-product commodity feeds, which most producers never nutrient tested. Most dairy producers used PC Dart as a management tool.Dairy producers continuously seek ways to improve their farm, and many choose to form a dairy advisory team (DAT) to improve management. The objectives were: (1) to compare key measures before and after the team in order to determine if the use of a DAT was effective and (2) to compare a group of 24 herds with a DAT to Pennsylvania (PA) averages for key measures. Teams were formed between May 2008 through January 2013. The range for herd size was 32-608 with a standard deviation of ± 13.96 cows. Herd size, milk yield, somatic cell score (SCS), peak milk yield, age at first calving (AFC), days in milk (DIM), pregnancy rate and cull and mortality rates were key measures analyzed. The changes in key measures, after using DAT for at least one year, were analyzed using a general liner model and contrasts. After DAT use for one year, herds had significantly (P

Includes its Reports.