Seasonal growth characteristics and shading ability of six sugarcane varieties were compared during the second production year. For each variety, trend analysis of data showed a significant linear trend. Differences in shoot emergence among the varieties were observed beginning in early April and as the season progressed, shoot production and shoot height increased for L 97-128, Ho 95-988, L 99-226, and L 99-233 but lagged for HoCP 96-540 and LCP 85-384. Beginning in mid-April ground cover increased most rapidly for L 99-233. In late May ground cover was around 60% for LCP 85-384 and HoCP 96-540; around 70% for L 97-128, Ho 95-988, and L 99-233; and was approaching 90% for L 99-226. Sugarcane canopy height across the growing season was consistently greater for L 97-128 and L 99-233 and averaged 21% more than for the other varieties in early June and 15% more in mid-July. Based on photosynthetically active radiation (PAR) data collected in the row middles, sunlight in the sugarcane canopy at ground level was reduced an average of 61% in early June for L 97-128 and L 99-226 compared with 29% for LCP 85-384 and HoCP 96-540. By late July PAR reduction was equal and averaged 90% for L 97-128, Ho 95-988, L 99-226 and L 99-233 compared with 78% for LCP 85-384 and HoCP 96-540. Shade studies were conducted in fields with natural infestations of bermudagrass and johnsongrass using enclosures (0.61 x 0.61 x 0.61m) covered with shade cloth providing 30, 50, 70 and 90% shade. At 55 days, bermudagrass ground cover under full sunlight was 88% compared with 10% for 90% shade; above ground biomass for 90% shade was reduced 95%. Exposure to 90% shade for 35 days decreased johnsongrass plant population 86% and above ground biomass 90%. With 30% shade, dry weight of bermudagrass was reduced 30% and johnsongrass biomass was reduced 45%. Based on this research the varieties L 97-128, L 99-226, and L 99-233 should be competitive with bermudagrass and johnsongrass. In contrast, the open canopy of HoCP 96-540 would be conducive to weed reinfestation.

Wetlands are important sinks for the atmospheric carbon (C) and play a major role in the global carbon cycle. However, factors impacting wetland soil C transformations and C gas production are not yet well understood. Elucidating these influences is especially important to Louisiana as wetlands are being impacted by salt water intrusion, subsidence and Mississippi river water diversion activities. This study evaluates, the effects of salinity, ions in river and sea water (K+, Ca2+) , clays and electron acceptors (NO3-, SO42-) on soil C transformations as well as C gas production from Louisiana coastal wetlands. Wetland soils were collected from forest swamp (FS), freshwater marsh (FM), and saline marsh (SM) and various characterizations were carried out. Aerobic incubations showed that addition of either K+ or Ca2+ chloride salts significantly increased CO2 production from FS soil, but had little effect on CO2 production from FM soil. Clay addition (2 and 5%) to FM soil significantly decreased CO2 production compared to unamended soil (P < 0.02). A combination of 5% clay and 5 mM Ca2+ further decreased the CO2 production in this soil. Increase in salinity decreased CO2 production from both FS and FM soils. In anaerobic incubations, addition of alternative electron acceptors, NO3- decreased CO2 production significantly whereas SO42- had little effect. Nitrate and SO42- decreased CH4 production but the NO3- almost completely inhibited CH4 production (>99%). Among the three wetland soils, FM exhibited the greatest denitrification potential (PDR), but it also tends to yield more N2O as compared to FS and SM soils. Soil organic C has significant effect on regulating PDR (P< 0.007). Among the different organic C mioties, polysaccharides positively influenced PDR (P< 0.003) while phenolics had negative effect (P < 0.03). Labile organic C as measured by aerobically mineralizable C was positively correlated with polysaccharides and carboxylic C. Further, characterization of humic acids (HA) in these wetland soils showed that FM HA had greater aromaticity whereas FS HA contained more aliphatic C. Increasing salinity tended to cause an increase in crystalline nature of aliphatics and guaicyl structural units in HA, suggesting more resistant HA formation.

Novel molecular and statistical approaches are needed for identification of DNA markers associated with complex traits in rice. The first research objective was to evaluate mixed-model and multiple regression approaches for their ability to identify molecular markers associated with complex traits in rice. A combined mixed model and multiple regression approach was optimal for selecting the smallest number of DNA markers associated with relatively high R2 values and for consistency with previous mapping studies. Support Vector Regression (SVR) was evaluated in the second research objective for the ability to generate high levels of accuracy and power for markers associated with complex traits. High levels of prediction accuracy and power were observed for the selected markers. SVR produced greater model accuracy and ability to explain trait variation than multiple linear regression. Single nucleotide polymorphic (SNP) markers for aroma, amylose content and gelatinization temperature were evaluated in the third research objective for marker-assisted improvement of breeding lines. This strategy increased frequency of desired alleles by an average of 26 percent in only two generations. Genetic analysis of pollen sterility was conducted in the fourth research objective for an F2 population derived from an outcross between a weedy biotype and a commercial variety. Segregation analyses revealed that seed fertility was governed by two dominant genes, a result similar to the cytoplasmic male sterile (CMS)-WA system used to develop commercial hybrids. Pollen sterility was controlled by two recessive genes. The pollen sterility trait could be exploited as a new source of CMS for hybrid rice breeding. Additional research is needed to confirm if lines developed from this natural outcross represent a new source of CMS. Overall results show that both standard and new data mining approaches can be used to successfully identify candidate genes and DNA markers associated with complex agronomic traits. In addition, the SNP markers were shown to rapidly enrich frequency of desired alleles associated with rice grain and cooking quality traits. All results demonstrated that a combination of molecular, statistical, and genetic approaches created an effective strategy to advance our understanding of factors that govern complex traits in rice.

Low silicon (Si) content in rice, sugarcane and other Si-accumulating crops can adversely affect crop performance due to reduced tolerance to both abiotic and biotic stresses. This research had two specific objectives relative to Si in Louisiana rice: develop a digestion procedure for Si tissue analysis that is robust, accurate, precise, and requires equipment commonly found in most agricultural laboratories; and survey the Si status of rice plants at mid-tiller (Y-leaf) and after harvest (straw) throughout the rice-growing regions of Louisiana. Assessing the Si status of a crop typically depends upon accurately measuring Si accumulation in plant tissue. While wet-digestion methods have several advantages for Si analysis, the accuracy and precision of these methods are doubtful. A systematic study showed that control of excessive foaming during digestion of plant tissue significantly reduced variability and increased recovery. The inclusion of ammonium fluoride to facilitate the release of polysilicic acid prior to colorimetric determination results in reproducible readings that stabilize within 60 min and remain stable for at least 5 h. With this modification, the accuracy and precision of values obtained colorimetrically are comparable or superior to those obtained by ICP-OES analysis. A detailed survey of the Si status of rice grown in the Major Land Resource Areas (MLRA) throughout Louisiana was created to identify areas where possible Si deficiencies occur and where responses to Si fertilization would most likely result in economic responses. Low early season uptake occurred in nearly all rice fields included in this study, though by harvest, only 36% of the fields contained less than 50 g Si kg-1. Parishes showing the lowest seasonal Si uptake were located within the Gulf Coast Prairies MLRA in the southwest corner of Louisiana. Significant correlations (p>0.05) were found between air dry pH and tissue Si at both early and late season, but no relationships were evident between dissolved Si in irrigation flood water or soil pore water and Si uptake by rice.

Early generation selection of sugarcane families using means is inadequate while visual seedling selection is subjective and inefficient. Data from advanced variety trials (yield, quality and agronomic traits) are collected over several crop-years to determine yield potential and ratooning ability of genotypes follow a multivariate repeated measures structure. In Louisiana, the sugarcane borer and recently the Mexican rice borer are major insect pests of sugarcane. Both borers have similar feeding habits, providing an opportunity for investigating if genotypes resistant to one species would provide resistance to the other (cross-resistance). The objectives of the study were to identify statistical methods to evaluate family yield potential and repeatability, enhance seedling selection for yield, analyze advanced variety trials data and prove cross resistance between the sugarcane borer and the Mexican rice borer. Random coefficient models (RCM) identified elite families with higher cane yield potential and higher repeatability between seedlings and clones. These elite families comprised a larger proportion of higher yield seedlings that produced high yielding clones. Logistic regression models (LRM) provided an objective statistical decision support tool for selecting high yielding seedlings and were more flexible at adjusting the number of seedlings to advance than visual selection. The LRM can be used to identify important traits in breeding populations as well as directionally shifting population trait values during selection. Neural network models can be used to automate the LRM. The multivariate repeated measures analysis (MRM) reduced Type I errors associated with univariate analysis by including covariance to compute experimental errors. The MRM showed greater statistical differences among genotypes for yield traits than univariate analysis. Cross resistance between the sugarcane and Mexican rice borer was proved using log linear models, and using a population with known sugarcane borer resistance status. Using RCM will significantly increase the efficiency of early generation selection by identifying families with high yield potential and repeatability while LRM will increase efficiency of identifying high yielding seedlings from these elite families. MRM will increase the accuracy of evaluating genotypes for yield and ratooning ability. Cross-resistance will allow breeders to take advantage of parents from the sugarcane borer recurrent selection program.

Studies were conducted to evaluate growth and reproductive capabilities of creeping rivergrass in response to flood depth, burial depth, desiccation, herbicide programs and interference with rice. Seed production of a natural population of creeping rivergrass was 0.8 seeds per panicle. Germination was 45% and seedling vigor was poor. Flowers from surviving seedlings were male sterile. A 5 and 10 cm flood depth increased fresh weight, stolon length, and node production of creeping rivergrass compared with non-flooded plants. However, depths at 15 and 20 cm did not differ from no-flood; therefore permanent flooding should be delayed until rice can survive a deep flood. Burial of stolons 10 to 20 cm deep prevented emergence and reduced viability. Deep burial of rhizomes prevented emergence but did not reduce viability. Stolon fragmentation due to deep tillage and burial greater than 5 cm, or placement of rhizomes on the soil surface decreases emergence and viability of creeping rivergrass vegetative structures. Desiccating stolons from 35 to 25% of initial fresh weight reduced germination, growth, and potential colonization rate of creeping rivergrass. In competition studies creeping rivergrass above ground biomass was reduced when grown with rice seeded at >45 kg/ha. Rice grain yield was reduced 17 and 29% when creeping rivergrass was planted at densities of 26 and 52 plants/ha, respectively. Emergence of creeping rivergrass was 98% at 31 C and less than 2% at 15 and 11 C suggesting that planting of rice in cooler temperatures may allow a competitive advantage for rice. Creeping rivergrass grown from single node stolon segments, multiple node stolon segments, and rhizomes were treated with various herbicides to evaluate efficacy. A herbicide program for the management of creeping rivergrass should include glyphosate as a burndown treatment prior to planting or during fallow periods. A Clearfield rice variety or hybrid should be selected which allows the use of two applications of imazethapyr, and cyhalofop used as needed throughout the season. Employing a herbicide program coupled with integrated management strategies such as tillage, planting date, and increased rice seeding rates decreases the competitiveness of creeping rivergrass.

Soil compaction is a primary impediment to vegetation regeneration on military land used for M1A1 Abrams tank training. As such, there is a need to identify soil compaction thresholds and develop guidelines with which military range managers can determine appropriate timing and intensity of training exercises using the 63-ton M1A1 tank. A study was initiated at the Camp Minden Louisiana Training Site (CMTS) to develop guidelines which will allow for maximum utilization of the land resource with minimum degradation. The study was designed to evaluate soil moisture content and traffic rates as experimental variables using a replicated 3 x 3 x 3 factorial design with 3 soil moisture ranges (< 20%; 20 to 30%, and > 30% water fraction by volume, wfv) and 3 traffic load rates (3, 6, or 9 passes) on 5 m2 plots. Comparison of pre- and post-trafficked soil bulk density (BD), soil penetration resistance (PR), and soil-moisture retention characteristics (SMR) were used to evaluate the effects of soil moisture and traffic rates on relative compaction. Post-trafficked BD increased in all treatment combinations with root-limiting thresholds of 1.65 g/cm3 exceeded at the 20 cm depth in the Mid (20% to 30%) moisture range plots with as few as 6 passes and in the Hi (>30%) moisture range plots with as few as 3 passes. SMR curve data indicate a reduction in total porosity from 0.44 to 0.38 cm3/cm3 in soil cores from Hi moisture treatment plots with a corresponding shift in pore size distribution toward a predominance of smaller pores across the range of pressures investigated to 12.5 bars. We conclude that training exercises are best when moisture contents for silty and loamy soils are at or below 20% on a volume basis. Furthermore, training exercises should be avoided at moisture contents above 30% to prevent root limiting compaction levels. Soil moisture levels exceeding the recommended thresholds commonly occur between December and April at CMTS annually. Suspending training maneuvers for this period is impractical. Therefore, we recommend range management plans include disking operations to loosen soil in tank trafficked areas when compaction levels exceed 1.65 g/cm3.

Four studies were conducted at the LSU AgCenter Rice Research Station near Crowley, Louisiana to evaluate the effects of simulated herbicide drift on Cocodrie rice. Herbicides were applied at 6.3 and 12.5% of the labeled usage rate of 863 g ae/ha of glyphosate, 70 g ai/ha of imazethapyr, 493 g ai/ha of glufosinate, and 44 g ai/ha of imazamox. Herbicides were applied to rice at the 1-tiller, panicle differentiation (PD), boot, and physiological maturity growth stages. Spray volume varied proportionally to herbicide dosage and was 15 L/ha for the 6.3% rate and 29 L/ha for the 12.5% rate using 234 L/ha as the target spray volume and were applied with a tractor-mounted CO2-pressurized sprayer. Glyphosate reduced plant height and primary and total crop yield, with the greatest reduction in primary crop yield resulting from glyphosate applied at boot. Primary crop rice seed germination was reduced by glyphosate. Glyphosate reduced ratoon crop rice seed weight; however, ratoon crop seed germination was not reduced. Imazethapyr reduced plant height and primary and total crop yield, with the greatest reduction in primary crop yield resulting from imazethapyr applied at boot. Primary crop rice seed weight was reduced by imazethapyr applied at boot. Primary crop rice seed germination was reduced by imazethapyr. Ratoon crop rice seed germination was reduced by imazethapyr applied at PD. Glufosinate reduced rice plant height and, when applied at boot, reduced primary and total crop yield. Primary crop rice seed germination and primary crop seedling vigor were reduced by glufosinate. Imazamox reduced plant height and primary and total crop yield with the greatest reduction in yield observed from rice treated at boot. Primary crop rice seed germination was reduced by imazamox. Primary crop seedling vigor was reduced with imazamox applied at boot. Ratoon crop rice seed weight and germination was not affected by imazamox. Simulated glyphosate, imazethapyr, glufosinate, and imazamox drift applications did not affect rice when applied at maturity. The greatest reduction in primary crop yield was observed when glyphosate, imazethapyr, glufosinate, and imazamox were applied to rice at boot and they all reduced primary crop rice seed germination.

Sequence related amplification polymorphism (SRAP) marker technique was used to assess genetic relationships and diversity among genotypes of Saccharum and allied genera. In the SRAP technique, the primers were arbitrarily designed with an AT- and GC-rich motif to anneal introns and exons, respectively. The level of polymorphism observed proved that the SRAP system was robust and amplified markers across species and genera and established evolutionary history interconnecting members of the Saccharum complex. The resolving power of the SRAP markers coupled with the fact that some of the amplicons could be amplifying gene-rich regions from diverse loci of the genome, was indicative of its potential usefulness for linkage and quantitative trait loci (QTLs) mapping in sugarcane. S. spontaneuam has been the most important source of wild germplasm for sugarcane cultivar development in Louisiana. Genetic diversity and structure of 51 S. spontaneum genotypes in the local collection (USDA, Houma, LA) was assessed using amplified fragment length polymorphism (AFLP) markers. Fifty-one genotypes grouped largely according to their geographical origins namely Central and East zones. The contribution of alleles from the S. spontaneum collection in the modern cultivars was low and about equal. This study also allowed us to realize that S. spontaneum germplasm representing the west zone was not present in the collection. A framework genetic linkage map of LCP 85-384 was constructed using 300 selfed progeny based on 773 single-dose (SD) markers generated by 64 AFLP, 12 TRAP and 19 SSR markers. Out of 773 SD markers, 717 markers were assigned onto 108 co-segregation groups (CGs) with a cumulative map length of 5,384 cM. With the estimated genome size of 12,720 cM, the map covered an estimated 42% of the genome. Of the 108 CGs, 31 CGs were assigned into 12 homo(eo)logous groups (HGs) based on the SSRs and information from the parental maps. Repulsion phase linkages studied suggested the preponderance of disomic segregation between CGs within the homo(eo)logus chromosomes. The framework map established in this study will provide an important background for mapping QTLs associated with sugar related traits and thus, information will be useful for crossing and selection of clones in the breeding program.

Cotton (Gossypium spp.) is the most extensively used natural fiber in the textile industry. Understanding the genetic diversity, population structure and marker trait associations are of great importance in marker assisted selection. Microsatellite, AFLP and TRAP markers were used to construct a linkage map with 94 F2 diploid individuals derived from a cross between G. arboreum x G. herbaceum. A total of 606 polymorphic markers gave rise to 37 linkage groups covering a total of 1109cM with an average distance of 7.92cM between each loci. Discriminant analysis identified three markers each for petal color and seed fuzziness, and four markers for petal spot. For quantitative traits, a total of 19 QTLs were identified and linked with five fiber traits using composite interval mapping. Markers such as qFL4-1, qFS4-2, qELO1-1 and qSI2-1 were found to be significantly linked with fiber length, strength, elongation and seed index respectively. Association mapping principles were applied to upland cotton genotypes in order to examine population structure and marker trait associations. A set of 232 genotypes were genotyped using AFLP markers. The molecular diversity was in the range of 0.48-0.574 with molecular variance found to be 10% among the groups. Bayesian and MCMC based population structure analysis, there existed six subpopulations, in accordance with their geographical origin. The mixed and mixed-multiple regression (MMR) models identified significant markers for lint yield and fiber traits, showing low AICC, BIC and SBC values and high adj. R2. Two way epistatic interaction analyses further confirmed their strong association. In the similar study, a set of 75 upland cotton genotypes were analyzed for seed quality traits such as seed protein, oil and fiber content. Population structure based mixed models showed 32 significant markers, associated with these seed quality traits. MMR models identified several markers, notably E4M3_440, E4M3_200 and E5M7_195 for seed protein, oil and fiber content respectively. Finally, 60 upland genotypes from RBTN program were screened with AFLP markers. The pairwise kinship estimates were ranging between 0.1-0.88 accounting for most of the shared ancestral alleles. The MMR models improved the efficiency of marker selection with 38 markers associated with eight traits.