No description available.

In 2003-2004, the Texas A&M University Ranch to Rail South program evaluated 430 steers in Edroy, TX. Data were analyzed on several traits, but feeder calf frame and muscle grades and health status were emphasized. Muscle thickness grade (M), frame size grade (F), muscle thickness by frame size interaction (M*F), sire breed type classification (SIRECODE), lung score (LUNG), ranch of origin (RANCH), and level of treatment (LVLTRT) were evaluated as independent variables as affecting ribeye area (REA), marbling score (MARB), fat thickness (FAT), hot carcass weight (HCW), average daily gain (ADG), medicine costs (MED), days on feed (DOF), initial value (VALUE), carcass value (CARVAL), and initial weight (INWT). M (P < .0001), F (P < .0001), M*F (P < .0001), SIRECODE (P < .0001), RANCH (P < .0001), LVLTRT (P = .0016), and INWT (P < .0001) were all significant influences on initial value upon arrival. SIRECODE (P = .0344), RANCH (P = .0571), and INWT (P < .0001) were significant in impacting carcass value. RANCH (P = .0045) and INWT (P < .0001) were very significant influences upon ribeye area when the steers were harvested. RANCH (P < .0001) was also influential on marbling score, and LVLTRT (P = .1096) was slightly significant for MARB. M (P = .0659), F (P = .0721), and M*F (P = .0722) were moderately significant in influencing fat thickness. However, SIRECODE (P = .0148) and RANCH (P < .0001) were significant in impacting FAT. HCW was significantly affected by SIRECODE (P = .0056), RANCH (P < .0001), and INWT (P < .0001). For live performance, SIRECODE (P = .0120) and RANCH (P < .0001) were significant influences upon average daily gain. SIRECODE (P < .0001), RANCH (P < .0001), LVLTRT (P < .0001), and INWT (P < .0001) were significant influences on days on feed for the steers. Finally, RANCH (P < .0001) and LVLTRT (P < .0001) were significant in affecting medicine costs. These findings suggest ranch of origin and breed type play major roles in affecting live and carcass performance.

No description available.

According to the USDA, there were 52.7 million marketings of cattle through live and internet auction markets and other venues in 2005. With the national average herd size at 43 head, most producers have limited bargaining power when it comes to marketing and auctioning their cattle. This has led to the birth of numerous value added cattle programs in the U.S. Value added programs are named as such, because they add additional value to the cattle before they are sold, but this value is difficult to quantify. The objective of this research was to measure the value of characteristics of feeder cattle sold through auction markets and special source verified feeder cattle sales, specifically the value of participating in these value added programs. Data over seven years from regular and special feeder cattle sales at Joplin Regional Stockyards were used. The effects of explanatory variables on sale price were analyzed using ordinary least squares regression hedonic model. Type of sale, seasonality, cyclical effects, lot size, weight, breed type, sex, commingling, fed cattle futures price, and corn price were all found to have an impact on the sale price of feeder cattle. Feeder calves sold through MFA Health Track Beef Alliance and other value added programs received a premium over those calves that sold through regular sales and the premiums for MFA and other value added programs were statistically different. Commingled lots of feeder cattle received a discount in comparison with non-commingled lots, but a lot size of 17 head would offset the negative effect of commingling. The predictive power of the hedonic model was tested using out of sample forecasting. The mean absolute percent error and root mean square error are indicators of the ability of the model to forecast sale price based on the measured impact of the explanatory variables. When the hedonic model was used for forecasting the out of sample data, the MAPE was 7.84 and the RMSE was 10.48.

According to the USDA, there were 52.7 million marketings of cattle through live and internet auction markets and other venues in 2005. With the national average herd size at 43 head, most producers have limited bargaining power when it comes to marketing and auctioning their cattle. This has led to the birth of numerous value added cattle programs in the U.S. Value added programs are named as such, because they add additional value to the cattle before they are sold, but this value is difficult to quantify. The objective of this research was to measure the value of characteristics of feeder cattle sold through auction markets and special source verified feeder cattle sales, specifically the value of participating in these value added programs. Data over seven years from regular and special feeder cattle sales at Joplin Regional Stockyards were used. The effects of explanatory variables on sale price were analyzed using ordinary least squares regression hedonic model. Type of sale, seasonality, cyclical effects, lot size, weight, breed type, sex, commingling, fed cattle futures price, and corn price were all found to have an impact on the sale price of feeder cattle. Feeder calves sold through MFA Health Track Beef Alliance and other value added programs received a premium over those calves that sold through regular sales and the premiums for MFA and other value added programs were statistically different. Commingled lots of feeder cattle received a discount in comparison with non-commingled lots, but a lot size of 17 head would offset the negative effect of commingling. The predictive power of the hedonic model was tested using out of sample forecasting. The mean absolute percent error and root mean square error are indicators of the ability of the model to forecast sale price based on the measured impact of the explanatory variables. When the hedonic model was used for forecasting the out of sample data, the MAPE was 7.84 and the RMSE was 10.48.

This thesis is to study the distribution system loss by applying artificial neural networks(ANN). To enhance the efficiency of loss analysis, the distribution system network has been obtained by retrieving that component information for the automated mapping and facility management system (AM/FM). The topology process and node reduction has also been applied to identify the network configuration and the input data for load flow analysis. The load survey study is used to derive the typical load patterns of various customer losses. The monthly energy consumption of customers by each transformer, which has been retrieved for the customer information system(CIS), is used to derive the hourly loading of each distribution transformer. The three phase load flow analysis has been performed for different types of distribution feeders to solve feeder loss to generate the data set for the training and testing of neural networks. The ANN for distribution loss analysis, which has been obtained after network training, can solve the distribution system loss very efficiently according to the feeder load demand, length, transformer capacity and voltage level. With short feeder length and voluminous customers served by the distribution feeders in urban area, the transformer core loss and secondary line loss contribute most of the distribution feeder loss. On the other hand, the line loss of rural distribution feeder is more significant because of the longer distribution lines to serve more scattering customers. With the neural based distribution system loss modeling, the distribution system loss can be estimated very easily, which can provide Taipower a good reference to enhance the operation efficiency of distribution system.

The design and regulation of power equipments which installed in distribution system are based on single direction power flow. When distributed generators (DG) are added into distribution system, it may cause some technical problems such as two-way current, fault capacity and power quality. In general, the utility should make sure that its power system could be operated safely and reliably before integrating DG into the system. If there are no complete measurements for DG, the capacity of DG would be restricted by fault current, short circuit capacity, feeder voltage or other problems. In this research, the focus is on the influence of DG operations in distribution system and the increase of DG integration capacity. The impacts of different combinations of DG generation profiles and control strategies are first analyzed, followed by the use of particle swarm optimization (PSO) technique to search for better feeder reconfigurations in order to increase DG integration capacity.

No description available.

Master of Science / Department of Animal Sciences and Industry / Robert D. Goodband / A study was conducted on a commercial sow farm to determine the effects of parity and stage of gestation on growth and feed efficiency of gestating sows. These data were also used to model changes in composition of maternal weight gain and products of conceptus throughout gestation. Feed intake and BW were measured daily from d 5 to 112 of gestation for 712 females. From d 5 to 39 of gestation, ADFI was lowest for parity 3+ sows compared to the other periods of gestation. Parity 2 sows, although provided the same feed allowance, had greater ADFI during the first period than parity 3+ sows. Average daily gain was lowest and G:F was the poorest from d 5 to 39 for each parity group compared with d 40 to 109 of gestation. Parity 1 and 2 sow ADG increased following d 39 of gestation but decreased from d 75 to 109. Parity 3+ sow ADG increased in each subsequent period of gestation. Parity 1 sows had the greatest ADG and G:F in comparison to parity 2 and 3+ sows in each period of gestation. Energy available for maternal growth was estimated after accounting for the energy needed to meet the sow’s maintenance requirement and the energy required for the growth of the conceptus. Following d 39 of gestation, energy available for maternal growth decreased at the expense of maintenance and conceptus requirements in each subsequent period of gestation for each parity group. After accounting for the weight of the conceptus, maternal ADG decreased from d 39 to 74, and increased d 74 to 109 of gestation, regardless of parity. Maternal G:F was greatest for parity 1 sows in most gestation periods. In conclusion, parity and stage of gestation impact sow feed efficiency and maternal growth with parity 1 sows having the greatest weight gain and best feed efficiency.

No description available.