Fiber quality data from five upland cotton (Gossypium hirsutum L.) genotypes, which were grown at College Station, TX during 2001 and 2002, were subjected to diallel and generation means analyses to determine the potential for improvement of fiber length and to determine the inheritance of length distribution data. Four near-long staple (NLS) upland cotton genotypes and one short-staple genotype were crossed in all combinations, excluding reciprocals. Estimates of general (GCA) and specific combining ability (SCA) for fiber length based on Griffing’s diallel Model I, Method 4 were calculated for high volume instrumentation (HVI) upper-half mean (UHM) fiber length and advance fiber information system (AFIS) mean fiber length by weight (FLw), mean fiber length by number (FLn), upper quartile length by weight (Uqlw), fiber length distribution cross entropy (using 3 different standard or check distributions - CEA, CEB, and CEC), fiber length distribution kurtosis (FLwKurt), and fiber length distribution skewness (FLwSkew) for FLw. Across environments, GCA effects were significant for fiber length measurements of UHM, FLw, FLn, Uqlw, and SFCw and distribution measurements of CEA, CEB, FLwKurt, and FLwSkew. On the basis of GCA effects, TAM 94L-25 was the best parent to be used in a cross to improve upland fiber length, while Acala 1517-99 was the parent of choice to improve distribution among the 4 parents tested. The inheritance of AFIS fiber length measurements and distribution data was estimated using parents, F1, F2, and backcross generations. The magnitude and significance of the estimates for non-allelic effects in the parental combinations suggest that epistatic gene effects are present and important in the basic mechanism of AFIS fiber length and length distribution inheritance for the populations studied. Gene effects and variances for all AFIS fiber length and distribution data measurements were inherited differently in different environments and specific parental combination, suggesting environmentally specific mechanisms. Developing genotypes with enhanced fiber length and an optimal fiber length distribution should be a priority to improve spinning performance and product quality of U.S. upland cotton.

Peanut (Arachis hypogaea L.) has the potential to become a major source of biodiesel but for market viability, peanut oil yields must increase and specific quality requirements must be met. Oil yield in peanut is influenced by many components, including oil concentration, seed mass, and mean oil produced per seed. All of these traits can be improved through selection as long as there is sufficient genetic variation. Thus, elucidating the genetics of oil concentration, seed mass, and mean oil produced per seed in peanut is essential to advancing the development of genotypes with high oil yields. Additive genetic effects were predominant for oil concentration in two generation means analyses involving a proprietary high oil breeding line and additive genetic variance was highly significant in a complete four-parent diallel analysis. Genetic variance for weight of 50 sound mature kernels (50 SMK) and mean oil produced per SMK (OPS) was additive the diallel analysis. Narrow-sense heritability estimates were high for oil concentration in both the diallel and generation means analyses. Narrow-sense heritability was also high for 50 SMK, but was low for OPS. The low OPS heritability estimate was caused by the negative correlation between oil concentration and seed mass. Consequently, oil concentration and seed mass can be improved through early-generation selection, but large segregating populations from high oil crosses will be needed to identify progeny with elevated oil concentrations that maintain acceptable seed sizes. Increasing the ratio of oleic to linoleic acid (O/L) in peanut oil and reducing the long chain saturated fatty acid concentration (which includes arachidic, behenic, and lignoceric acids) produces high quality, stable methyl esters for biodiesel. Therefore, elucidating the inheritance of these factors and their relationships in peanut populations segregating for high oil is critical. The results from generation means analysis confirm that the high-oleic trait is under simple genetic control and can be manipulated through selection. Oil concentration was negatively correlated with oleic acid concentration in the F2 generations of both crosses and positively correlated with arachidic acid in most of the segregating generations that were evaluated. Therefore, developing a peanut genotype high in oil and oleic acid concentration that has reduced long chain saturates will require the evaluation of large numbers of segregating progeny.

The tobacco cyst nematode [Globodera tabacum solanacearum (Miller & Gray, 1972) Behrens, 1975] is an important pathogen affecting flue-cured tobacco (Nicotiana tabacum L.) in Virginia, North Carolina, and Maryland. The resistant cultivars Coker 371 Gold and Kutsaga 110 were evaluated during 1999 and 2000 in the greenhouse to determine the mode of inheritance of resistance to the tobacco cyst nematode (TCN). Each cultivar was crossed to the susceptible cultivar K 326 and F1 progeny were backcrossed to each parent. Plants from each parent and F1, F2, BC1Ps, and BC1Pr progeny were evaluated for TCN resistance. Six-week-old transplants were inoculated with 6000 TCN eggs from crushed cysts. Eight weeks after inoculation, a 1-g sample of fibrous root was stained and vermiform, swollen, pyriform, and adult nematodes were counted. The number of cysts and eggs per 400 cm3 of soil were counted from each transplant. Generation means analyses were performed. Additive and dominance gene action play an important role in resistance to TCN in Coker 371 Gold and Kutsaga 110. F2 generation data from the Coker 371 Gold cross fit a 3:1 (resistant:susceptible) segregation ratio and BC1Ps generation data fit a 1:1 segregation ratio, indicating that resistance to TCN is conferred by a single dominant gene. A continuous range of variation was observed among the F2 progeny for the K 326 X Kutsaga 110 cross, indicating resistance in Kutsaga 110 is quantitative. TCN resistance in Coker 371 Gold and Kutsaga 110 may be derived from different sources. / Master of Science

La composition des parcs électriques nationaux est basée sur le classement des différents moyens de production par rapport à leur coût marginal de génération d’électricité. Ainsi, les réserves considérables d’hydrocarbure dans les pays producteurs de pétrole ont favorisé l’usage abusif du pétrole ou du gaz naturel dans le parc de production d’électricité. L’objectif de ce travail de recherche est d’analyser des parcs de production pour ces pays producteurs en construisant le parc optimal d’électricité concernant l’usage rationnel (du point de vue économique) des différents moyens de génération d’électricité. Dans ce travail, nous évaluons la situation actuelle et future de la production d’électricité en Arabie Saoudite, en Egypte et en Iran grâce à plusieurs approches de modélisation : linéaire, dynamique et statistique. Ensuite, nous allons mener une analyse de sensibilité afin d’évaluer l’optimalité et l’efficacité de la production d’électricité en tenant compte de l’intégration des autres ressources alternatives non-carbonées. / National power generation mix composition is based on the ranking (merit-order) of the various means of production from their marginal cost of electricity generation. Thus, significant reserves of hydrocarbons in oil-producing countries favoured the abusive use of oil or natural gas in the electricity mix. The purpose of this research is to analyze the power generation mix of these countries by constructing an optimal electricity mix based on the rational use (from an economic point of view) of various electricity production means. In this work, we assess the current and future situation of electricity production in Saudi Arabia, Egypt and Iran, thanks to linear, dynamic and statistical modeling efforts. Thereafter, we will conduct sensitivity analysis to measure the optimality and efficiency of electricity generation by taking into account the integration of alternative non-fossil-fuel based resources.