Molecular characterization of genetic resistance to soybean cyst nematode in soybean line SS97-6946

Title from PDF of title page (University of Missouri--Columbia, viewed on Feb. 12, 2010 ).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Dr. David A. Sleper, Thesis advisorM.S. University of Missouri--Columbia 2008.Soybean Cyst Nematode (SCN) (Heterodera glycine) is the most damaging pest of soybean and estimated annual yield losses are 1.5 billion dollars in USA. Breeding resistant cultivars is the most efficient means to control SCN but the nematode has adapted and overcomes resistance of developed soybean cultivars due to a narrow genetic base. A study was initiated in summer 2007 to investigate the genetics of resistance to SCN and identify Quantitative Trait Loci (QTL) conferring broad-spectrum SCN resistance in SS97-6946. Leaves of 160 F2 individuals from the cross PI 567476 X SS97-6946 were collected to isolate DNA in summer 2007. Three hundred forty seven polymorphic Single Sequence Repeat primer pairs out of 547 were used to genotype the F2 plants. Seeds from 160 F2:3 families were evaluated against races 1, 2, 3 and 5 for SCN bioassay following standard protocol. The ratio observed between resistant to susceptible F2:3 families revealed that SCN resistance involved three recessive genes for both race 1 and 2; two dominant and one recessive for race 3; one dominant and two recessive for race 5. Three markers mapped on linkage groups (LG) A2, E, and G and accounted for 33.8% of the total phenotypic variance for resistance to SCN race 1. One resistant QTL was detected on LG A1 accounted for 18.8% of the total phenotypic variance of race 2. Three markers mapped on LGs A2, G, and M to be associated with resistance to SCN race 3 and shared 24.9% of total phenotypic variance. Three markers on LG G alone and four markers on LGs A1, B2, M, and O were mapped and shown to be linked with SCN resistance to race 5 and accounted for 70.8% of the total phenotypic variance.Includes bibliographical reference

A Model-Free Control System Based on the Sliding Mode Control with Automatic Tuning Using as On-Line Parameter Estimation Approach

The sliding mode control algorithm and Lyapunov-based methods, have received much attention recently due to their ability to directly handle nonlinear systems while guaranteeing closed-loop tracking stability. In this work, a unique model-free sliding mode control technique has developed solely based on previous control inputs. The new method requires only knowledge of the system order and state measurements and does not require a theoretical model of the dynamic system. Lyapunov’s stability theorem is used in the controller formulation process to ensure closed-loop asymptotic stability. High frequency chattering of the control effort is reduced by using a smoothing boundary layer into the control law. Parameters variation during control operating and noise effect cannot be handled by the model-free controller if the controller tuning parameters are chosen arbitrarily since tracking performance becomes unacceptable. In addition, in previous work, the bounds of the input influence gain parameters were assumed to be known to derive the model-free controller. Therefore, in this work, a new approach is proposed for estimating the increment to the switching gain in real-time to ensure the sliding condition (which guarantees closed-loop tracking stability) is satisfied using a control law form that assumes a strictly unitary input influence gain. In formulation of estimation law, an exponential forgetting factor is combined with the least-squares estimator to ensure the updated data are used and past data are excluded. An automatic bounded forgetting tuning technique is developed to maintain the benefits of data forgetting while avoiding the possibility of gain unboundedness in absence of persistent excitation. The tuning estimator is assured that the resulting gain matrix is upper bounded regardless of the persistent excitation by suspending the data forgetting if the gain matrix reaches the specified upper bound. Simulations are performed on a series of linear and nonlinear SISO and MIMO systems with and without including actuator time-delay effects. Finally, a model is developed to simulate a quadcopter as a real-world application case. In all cases, the controller achieved perfect or near-perfect tracking performance using updated controller and on-line estimator tuning process

Evaluation of predicted loss of different land use and land cover (LULC) due to coastal erosion in Bangladesh

Coastal erosion is one of the most significant environmental threats to coastal communities globally. In Bangladesh, coastal erosion is a regularly occurring and major destructive process, impacting both human and ecological systems at sea level. The Lower Meghna estuary, located in southern Bangladesh, is among the most vulnerable landscapes in the world to the impacts of coastal erosion. Erosion causes population displacement, loss of productive land area, loss of infrastructure and communication systems, and, most importantly, household livelihoods. With an aim to assess the impacts of historical and predicted shoreline change on different land use and land cover, this study estimated historical shoreline movement, predicted shoreline positions based on historical data, and quantified and assessed past land use and land cover change. Multi-temporal Landsat images from 1988–2021 were used to quantify historical shoreline movement and past land use and land cover. A time-series classification of historical land use and land cover (LULC) were produced to both quantify LULC change and to evaluate the utility of the future shoreline predictions for calculating amounts of lost or newly added land resources by LULC type. Our results suggest that the agricultural land is the most dominant land cover/use (76.04% of the total land loss) lost over the studied period. Our results concluded that the best performed model for predicting land loss was the 10-year time depth and 20-year time horizon model. The 10-year time depth and 20-year time horizon model was also most accurate for agricultural, forested, and inland waterbody land use/covers loss prediction. We strongly believe that our results will build a foundation for future research studying the dynamics of coastal and deltaic environments

Assessment of Spatio-Temporal Variations in PM\u3csub\u3e2.5\u3c/sub\u3e and Associated Long-Range Air Mass Transport and Mortality in South Asia

Fine particulate matter (PM2.5) is associated with adverse impacts on ambient air quality and human mortality; the situation is especially dire in developing countries experiencing rapid industrialization and urban development. This study assessed the spatio-temporal variations of PM2.5 and its health impacts in the South Asian region. Both satellite and station-based data were used to monitor the variations in PM2.5 over time. Additionally, mortality data associated with ambient particulate matter were used to depict the overall impacts of air pollution in this region. We applied the Mann–Kendall and Sen’s slope trend analysis tool to investigate the trend of PM2.5. At the same time, clustering of backward trajectories was used for identifying the long-range air mass transport. The results revealed that the mean annual PM2.5 mass concentration was the highest (46.72 µg/m3) in Bangladesh among the South Asian countries during 1998–2019, exceeding the national ambient air quality standards of Bangladesh (i.e., 15 µg/m3) and WHO (10 µg/m3), while lower PM2.5 was observed in the Maldives and Sri Lanka (5.35 µg/m3 and 8.69 µg/m3, respectively) compared with the WHO standard. The trend analysis during 1998–2019 suggested that all South Asian countries except the Maldives experienced an increasing trend (p \u3c 0.05) of PM2.5. The study showed that among the major cities, the mean annual PM2.5 value was the highest in New Delhi (110 µg/m3), followed by Dhaka (85 µg/m3). Regarding seasonal variation, the highest PM2.5 was found during the pre-monsoon season in all cities. The findings of this research would help the concerned governments of South Asian countries to take steps toward improving air quality through policy interventions or reforms. Moreover, the results would provide future research directions for studying the trend and transport of atmospheric PM2.5 in other regions

Assessment of household-level adaptation strategies to water stress in southwestern coastal Bangladesh: a counter-factual analysis

Despite the growing emphasis and global initiatives to ensure safe drinking water and sanitation for all (Sustainable Development Goal 6), households in the coastal area are at risk of growing water stress across the globe. However, little is known about households' adaptation strategies to water stress in the coastal area. This study explores the determinants and impacts of adaptation strategies to household-level water stress (both drinking and non-drinking), considering the behaviors of adopters and non-adopters in the southwestern coastal area of Bangladesh. We applied an endogenous switching regression model by analyzing questionnaire survey datasets (n=502) to estimate the effect of adopting adaptation strategies on household-level water stress in eight saline-prone coastal districts of Bangladesh. Results reveal six commonly-practiced adaptation strategies: reducing vegetable production, reducing livestock production, paying more to access water, increasing time for water collection, preserving water, and using reservoirs to collect water. Determinants such as migration, support from government and non-government agencies, age, gender, literacy, occupation, income, access to tube wells, and distance from drinking water sources play a significant role in adopting adaptation strategies. Results from the endogenous switching regression model denote that adopting all six adaptation strategies appears to significantly reduce household-level water stress. Through counter-factual analysis, results demonstrate that, on average, households that did not adopt adaptation strategies would have encountered less water stress if they had. Therefore, determinants that stimulate adaptation strategies will indirectly reduce household water stress

Willingness to pay for improved safe drinking water in a coastal urban area in Bangladesh

Discontentment with a piped supply system of drinking water has become a significant concern in Bangladesh's urban areas in recent years, necessitating the improvement of different aspects of the system in question. Therefore, by conducting a discrete choice experiment on 115 households out of a systematically selected 161 households, this study aims to estimate the willingness to pay (WTP) for an improved safe drinking water supply by considering the trade-offs made by urban dwellers for the proposed improvements to an existing water supply system in the Khulna City Corporation (KCC) area of Bangladesh. The primary results show that the total WTP of households is estimated at BDT 243.6 (≈US$ 2.87) per month, implying that respondents are ready to pay for improvements to the water supply attributes of water quality, regularity of supply, water pressure in taps, and filtering. A revenue stream for an improved water supply system is also being developed, suggesting that investment in improving the system would be a ‘no-regret’ decision and economically sustainable

Obesity, disability and self-perceived health outcomes in Australian adults: a longitudinal analysis using 14 annual waves of the HILDA cohort

Background: Both obesity and disability have been widely recognised as major public health challenges because they play significant roles in determining self-perceived general and mental health. Longitudinal studies of the relationship between obesity and disability with self-reported health outcomes are scarce. Therefore, the objective of the present study is to examine the relationship between obesity and disability with self-perceived general and mental health among Australian adults aged 15 years and above. Methods: Data were extracted from the most recent 14 waves (waves 6 through 19) of the annual individual person dataset of the Household, Income and Labour Dynamics in Australia (HILDA) survey. The longitudinal random-effects logistic regression model was adopted to investigate the relationships between obesity and disability with self-reported health outcomes. Results: The results revealed that obese individuals and adults with some form of disability are more likely to report poor or fair general and mental health. The odds of self-reporting poor or fair general health were 2.40 and 6.07 times higher among obese (aOR: 2.40, 95% CI: 2.22– 2.58) and adults with some form of disability (aOR: 6.07, 95% CI: 5.77– 6.39), respectively, relative to adults with healthy weight and those without disability . The results also showed that self-rated poor or fair mental health were 1.22 and 2.40 times higher among obese adults (aOR: 1.22, 95% CI: 1.15– 1.30) and adults with disability (aOR: 2.40, 95% CI: 2.30– 2.51), respectively, compared to their healthy weight peers and peers without disability. Conclusion: As governmental and non-governmental organisations seek to improve the community’s physical and mental well-being, these organisations need to pay particular attention to routine health care prevention, specific interventions, and treatment practices, especially for obese and/or people with disabilities

A MAGIC population-based genome-wide association study reveals functional association of GhRBB1_A07 gene with superior fiber quality in cotton

Title: Quantile-quantile (Q-Q) Plot of six fiber traits generated from GWAS analysis following mixed linear model (MLM) using GAPIT software. A) Fiber elongation (ELO), B) Micronaire (MIC), C) Short fiber content (SFC), D) Fiber strength (STR), E) Upper half mean fiber length (UHM), and F) Uniformity index (UI). Description of data: Q-Q plots of six fiber traits generated from GWAS analysis following MLM are included in this figure. The X and Y axis have the expected and observed negative logarithm 10 of p value, respectively generated during GWAS analysis. (DOCX 207 kb

Quantitative trait loci analysis of four components of Fusarium head blight resistance in the soft red winter wheat cultivar Truman

Title from PDF of title page (University of Missouri--Columbia, viewed on June 11, 2014).[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Fusarium head blight (FHB) mainly caused by Fusarium graminearum Schwabe [telomorph: Gibberella zeae Schw. (Petch)] causes devastating losses in wheat globally. Host-plant resistance provides the best hope for reducing economic losses but sources of resistance are limited. "Truman" soft red winter wheat, developed and released by the University of Missouri has excellent broad-based FHB resistance. This research was conducted to identify QTL associated with five components of resistance in Truman. Two years (2 replications per year) of phenotypic data were collected on these components of resistance on a set of 167 F9 recombinant inbred lines developed from the cross Truman/MO 94-317. Genetic linkage maps were constructed using 160 single sequence repeat and 530 diversity array technology polymorphic markers. Across years, QTL for type II resistance were identified on chromosomes 1BSc, 2BL, 2DS and 3BSc; for disease incidence on 2ASc, 2DS, and 3DS; for disease severity on 2DS, and 3BSc; for Fusarium damage kernels (FDK) on 2ASc, 2DS, and 3BLc; and for low DON on 2ASc, 2DS, and 3BLc. Additional QTL for FDK were identified on 1BLc, 2ASc, and 3BLc; and for DON on 2ASc, 2DS, and 6ALc were identified from phenotypic data collected in Kentucky. The effects of identified QTL ranged from 5.0 to 30.7 % of the total phenotypic variation. Several of these QTL appear to be potentially novel and therefore should enhance FHB resistance in programs attempting to pyramid unique FHB resistance genes through marker-assisted-selection