AFLP analysis of genetic differentiation in CpGV resistant and susceptible Cydia pomonella (L.) populations

The codling moth, Cydia pomonella (Lep., Tortricidae), is a significant pest of orchard crops such as apple and pear in Southern Germany, and can cause severe economic damage to apple crops. Due to resistance to conventional pesticides and the growing market for organic fruit, Cydia pomonella Granulovirus (CpGV) has been used to control C. pomonella in Germany for over 10 years. Recently, populations exhibiting resistance to CpGV have been reported. In this study, we have used amplified fragment length polymorphism (AFLP) markers to estimate genetic variations between eight different C. pomonella populations, which were obtained from different locations exhibiting varying levels of resistance to CpGV. Three different AFLP primer combinations generated a total of 194 AFLP fragments, ranging from 57.84 to 424.11 bp, with an average of 59.23 amplified fragments per primer combination. The total number of segregating fragments ranged from 181 to 115 and resulted in a high loci polymorphism of 100% in most cases, except for two populations, where it was found to be 88.1% and 93.3%. An analysis of genetic variation based on the obtained AFLP markers resulted in high gene diversity (Hj) values, ranging between 0.2884 to 0.3508. Hj values also indicated a loss in gene diversity within a population over time. The Wright Fixation Index (FST) values indicated a low to moderate genetic differentiation in the populations. The cluster analysis (UPGMA), based on genetic distance values, showed that the majority of C. pomonella populations from different locations were clearly distributed into distinct groups and showed a large genetic variability

FACTORS AFFECTING REGIONAL SHIFTS OF U.S PORK PRODUCTION

The U.S. pork industry in the recent past has transferred into fewer, larger and specialized operations. Inputs availability, developments of transportation systems, technological changes, government regulations and the consumer preferences have been driving changes in the pork industry. Spatial inequalities affect the competitiveness of one region relative to other regions. This paper is focused on how these forces affect the regional competitiveness of the pork industry and movement towards larger, specialized and geographically concentrated operations. A mathematical programming model is used to analyze the effect of market forces on the pork industry structure. The results of this study show that although raising hogs in larger operations is less costly, small-sized operations in some regions still need to produce hogs to meet the demand for consumption and export. Environmental compliance cost is considered one of the major factors of industry relocation; the analysis showed that the effect of such costs was minimal. Feed costs and transportation costs play a greater role in location of production and processing. Pork operations tend to locate near the populous areas to meet the consumer demand and to minimize the transportation cost. Pressures from current and future environment regulations, moratoria and scarcity of agricultural land for manure management tend to keep the hog operations away from high population areas. A future scenario analysis suggested that the Western region of the U.S. would experience higher growth in pork production. The current trend of fewer and larger production units and location change in the pork industry will continue.Livestock Production/Industries,

Fitting theories of nuclear binding energies

In developing theories of nuclear binding energy such as density-functional theory, the effort required to make a fit can be daunting due to the large number of parameters that may be in the theory and the large number of nuclei in the mass table. For theories based on the Skyrme interaction, the effort can be reduced considerably by using the singular value decomposition to reduce the size of the parameter space. We find that the sensitive parameters define a space of dimension four or so, and within this space a linear refit is adequate for a number of Skyrme parameters sets from the literature. We do not find marked differences in the quality of the fit between the SLy4, the Bky4 and SkP parameter sets. The r.m.s. residual error in even-even nuclei is about 1.5 MeV, half the value of the liquid drop model. We also discuss an alternative norm for evaluating mass fits, the Chebyshev norm. It focuses attention on the cases with the largest discrepancies between theory and experiment. We show how it works with the liquid drop model and make some applications to models based on Skyrme energy functionals. The Chebyshev norm seems to be more sensitive to new experimental data than the root-mean-square norm. The method also has the advantage that candidate improvements to the theories can be assessed with computations on smaller sets of nuclei.Comment: 17 pages and 4 figures--version encorporates referee's comment