Predicting growth rates of adult working boars in a commercial boar stud

There is almost no information on ideal growth rates for adult boars, but estimates can be made if the relationship between boar weight and age is known. Therefore, this study was aimed to predict growth rates in adult working boars in a commercial boar stud. A total of 214 adult working boars from two genetic lines in a commercial boar stud were individually weighed on a platform scale. Age of the boar was recorded at the time of weighing. A regression equation to predict boar weight as a function of age was developed by using PROC REG of SAS. The model was used to predict BW on a daily basis, and ADG was derived as the difference between two predicted BW values. Factorial estimates of daily ME requirement and feeding rates were determined. The energy requirement for weight gain was computed by using the predicted ADG as a guide in setting target weight gains. Results showed a positive curvilinear response (P<0.01) to describe the relationship between boar weight and age. Predicted ADG decreased in a curvilinear manner as the boars aged. In conclusion, on-farm growth rates can be predicted effectively by relating weight with age, taken from a representative number of boars in a given farm population. These data can then be used to develop farm specific feeding programs or to set different growth curves for experimental purposes

Effects of different feeding regimens on growth, longevity, and semen characteristics of working boars in a commercial AI stud

The objective of the study was to determine the effects of 2 different feeding regimens on growth performance, semen production and quality, and longevity of boars in a commercial AI stud. A total of 30 replacement boars (PIC TR4, 375 lb and 14.2 mo of age) were randomly selected and allotted to 1 of 2 treatments. The control feeding program was the normal feeding program of the stud; boars were fed 6.7 lb/d for the first 8 wk, and then feeding was adjusted according to body condition of the individual boar. For the treatment feeding program, boars were fed 5.8 lb/d in the first 4 wk until boars reached 400 lb; afterward, boars were fed 6.0 lb/d for the duration of the study. Boars were weighed periodically to determine periodic and overall ADG. Semen was collected from each boar once a week for a total duration of 16 mo. Semen production and quality was determined for each ejaculate. Overall, treatment boars were consistently heavier than the control boars throughout the duration of the study because of their higher periodic and overall daily gains. At the end of the test, treatment boars were 32 lb heavier (P 0.35) average days in the stud (345 vs. 279 d), semen collections (58 vs. 49), and doses produced (1,238 vs. 1,077). There were no differences (P > 0.28) in the volume, sperm cell concentration, sperm cell count, and doses produced per ejaculate between boars fed the two feeding programs. Likewise, motility rates and proportion of normal cells in ejaculates were similar (P > 0.33) between boars fed the control and treatment feeding program. In conclusion, AI boars can be fed to a set feeding level to achieve targeted weight gains to influence longevity without affecting semen production and quality

Validation of flank-to-flank measurements for predicting boar weight

Allometric relationships, in which linear body dimensions are expressed as a function of body weight, are commonly used in growth studies. Previous work at Kansas State University showed a positive correlation between flank-to-flank measurement and sow body weight. Prediction equations were developed to estimate sow weight, but it is not known if the same equation will be valid in estimating body weight among other groups of pigs, such as boars. The objective of this study was to validate the use of flank-to-flank measurement in predicting boar weight, and to determine if the allometric equation for gestating sows can also be used for adult boars. A total of 100 adult working boars in a commercial A.I. stud were selected for this study. Flank-to-flank measurement and body weight were measured on each individual boar. Flank-to-flank measurement was positively correlated to boar body weight (R2 = 0.84, P<0.01). The fit of the model improved slightly (R2 = 0.86, P<0.01) when body weight was expressed as BW0.333. The boar equation was: BW0.333, kg = 0.0458 × flank-to-flank, cm + 1.1838. The comparison of residuals indicated that all three equations accurately predicted boar weight. The sow equation was also shown to be as accurate as the boar equations in estimating boar weight. Therefore, the sow allometric equation can be used as the final model to predict both sow and boar body weight

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins

Molecular basis of virus replication, viral pathogenesis and antiviral strategie

Pines

Pinus is the most important genus within the Family Pinaceae and also within the gymnosperms by the number of species (109 species recognized by Farjon 2001) and by its contribution to forest ecosystems. All pine species are evergreen trees or shrubs. They are widely distributed in the northern hemisphere, from tropical areas to northern areas in America and Eurasia. Their natural range reaches the equator only in Southeast Asia. In Africa, natural occurrences are confined to the Mediterranean basin. Pines grow at various elevations from sea level (not usual in tropical areas) to highlands. Two main regions of diversity are recorded, the most important one in Central America (43 species found in Mexico) and a secondary one in China. Some species have a very wide natural range (e.g., P. ponderosa, P. sylvestris). Pines are adapted to a wide range of ecological conditions: from tropical (e.g., P. merkusii, P. kesiya, P. tropicalis), temperate (e.g., P. pungens, P. thunbergii), and subalpine (e.g., P. albicaulis, P. cembra) to boreal (e.g., P. pumila) climates (Richardson and Rundel 1998, Burdon 2002). They can grow in quite pure stands or in mixed forest with other conifers or broadleaved trees. Some species are especially adapted to forest fires, e.g., P. banksiana, in which fire is virtually essential for cone opening and seed dispersal. They can grow in arid conditions, on alluvial plain soils, on sandy soils, on rocky soils, or on marsh soils. Trees of some species can have a very long life as in P. longaeva (more than 3,000 years)