Thesis (Ph. D.)--University of Tennessee, Knoxville, 2008. / Title from title page screen (viewed on Mar. 10, 2009). Thesis advisor: Kurt H. Lamour. Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Adelaide, Dept. of Crop Protection, 1996. / Includes bibliographical references (leaves 207-220).

Thesis (M.S.) in Plant, Soil and Environmental Sciences--University of Maine, 2008. / Includes vita. Includes bibliographical references (leaves 88-93).

Fusarium root rot is one of the most important diseases of pulse crops, with numerous Fusarium spp. comprising the disease complex. Fusarium solani and F. avenaceum have been reported to be major pathogens in the pea root rot complex, and all commonly grown varieties are susceptible. Greenhouse methods to evaluate peas for resistance to Fusarium root rot resulted in inconsistent disease severity across varieties. In 2015, F. avenaceum infested field plots were more heavily damaged based on emergence and yield than F. solani infested plots, and opposite trends were observed in 2016. Differences in root rot severity between years could be due to F. solani infestation causing more damage under warmer temperatures, while plots infested with F. avenaceum caused more damage under cooler temperatures. These results highlight the difficulties observed when screening for soil-borne pathogens, and the increased difficulties when a pathogen complex and changing environmental conditions are involved.

Thesis (M.A. Agricultural Management (Plant Production)) -- University of Limpopo, 2015 / Tomato (Solanum lycopersicum L.) production had been ranked as the most important commodity in terms of job and wealth creation within the auspices of the National Development Plan (NDP) framework in Limpopo Province. However, soil-borne diseases including plant-parasitic nematodes preclude the successful monoculturing of this commodity and therefore inducing instability in job creation. Generally, after growing a tomato crop for one season in commercial tomato-production systems, the land is being fallowed for 3-5 years under natural grasses. Attempts are being initiated to ensure that during the 3-5 years the land be occupied by an economic alternative crop in order to level off job instability as broadly articulated in the NDP framework. The production of sweet stem sorghum (Sorghum bicolor L.) for ethanol production during the 3-5 years fallowing period could potentially be attractive to commercial tomato-producing famers. Preliminary agronomic evaluations demonstrated that sweet stem sorghum var. ndendane-X1 had attributes to fulfil the identified need. However, the degree of nematode resistance of the variety to Meloidogyne incognita race 2 and M. javanica, which are dominant in Limpopo Province, along with the compatibility of var. ndendane-X1 to phytonematicides used in tomato production had not been documented. The objectives of the study were, therefore, to determine whether sweet stem sorghum var. ndendane-X1: (1) had any degree of nematode resistance to M. incognita race 2 under both greenhouse and microplot conditions, (2) had any degree of nematode resistance to M. javanica under greenhouse conditions, and (3) would be compatible with phytonematicides used in suppression of population densities of xiv Meloidogyne species in tomato production under field conditions. In the greenhouse trials, seeds were sown in 20-cm-diameter plastic pots and each seedling inoculated with 0, 600, 1 000, 1 400, 1 800 and 2 200 eggs and second-stage juveniles (J2s) of M. incognita race 2 or M. javanica. Treatments were arranged in a randomised complete block design (RCBD), with 10 replicates (n = 60). In the microplot trial, seeds were sown in 30-cm-diameter plastic pots and buried 75% deep in a 0.30-m intra-row and 0.25-m inter-row spacing. Treatments, namely, 0, 200, 600, 1 000, 1 400, 1 800 and 2 200 J2s of M. incognita race 2 were arranged in RCBD, with 14 replications (n = 98). In a Meloidogyne-infested field trial, seeds were sown at 0.2-m inter-row and 0.3-m intra-row spacing, with treatments 0, 2, 4, 6, 8 and 10 g nemafric-BG phytonematicide/plant, arranged in RCBD, with 13 replications (n = 78). The degree of nematode resistance was measured using host-status and host-sensitivity, which provide information on reproduction of the target nematode and plant damage due to nematode infection, respectively. Nematode reproduction was measured through the reproductive factor (RF), which is a proportion of final nematode population density (Pf) to initial nematode population density (Pi), summarised as RF = Pf/Pi. In all nematode resistance trials, RF was equivalent to zero, which implied that var. ndendane-X1 was a non-host to both M. incognita race 2 and M. javanica. Additionally, in both greenhouse and microplot trials, sweet stem sorghum var. ndendane-X1 did not suffer any significant damage due to infection by Meloidogyne species. Using nematode-plant relation concepts, sweet stem sorghum var. ndendane-X1 was resistant to M. incognita race 2 and M. javanica under greenhouse and microplot conditions. Under field conditions, nemafric-BG phytonematicide reduced eggs and J2s of Meloidogyne species in root and soil samples xv by 76-85% and 24-65%, respectively, without nematode effect on plant growth, suggesting that nemafric-BG could be integrated with nematode resistance in var. ndendane-X1 to manage nematode population densities. In conclusion, pilot projects where sweet stem sorghum var. ndendane-X1 could be used during the 3-5 years fallowing period in a tomato-sweet stem sorghum crop rotation system should be established to assess: (i) the economics of the proposed cropping system, (ii) the effect of the cropping system on soil-borne diseases, including plant-parasitic nematodes, and (iii) the effect of the cropping system on soil health.

Thesis: M.Sc. (Hons.)--University of Western Sydney, Macarthur. Faculty of Business and Technology. 1997. / References: 141-153.

No description available.

Stem rot of peanut (Arachis hypogaea L.), caused by a soilborne fungus Athelia rolfsii (Curzi) C. C. Tu and Kimbr. (anamorph: Sclerotium rolfsii Sacc.), is one of the most important diseases in peanut production worldwide. Though new varieties with increased partial resistance to this disease have been developed, there is still a need to utilize fungicides for disease control during the growing season. Fungicides with activity against A. rolfsii are available, and several new products have been recently registered for control of stem rot in peanut. However, fungicides are most effective when applied before or during the early stages of infection. Current scouting methods can detect disease once signs or symptoms are present, but to optimize the timing of fungicide applications and protect crop yield, a method for early detection of soilborne diseases is needed. Previous studies have utilized optical sensors combined with machine learning analysis for the early detection of plant diseases, but these studies mainly focused on foliar diseases. Few studies have applied these technologies for the early detection of soilborne diseases in field crops, including peanut. Thus, the overall goal of this research was to integrate sensor technologies, modern data analytic tools, and properties of standard and newly registered fungicides to develop improved management strategies for stem rot control in peanuts. The specific objectives of this work were to 1) characterize the spectral and thermal responses of peanut to infection with A. rolfsii under controlled conditions, 2) identify optimal wavelengths to detect stem rot of peanut using hyperspectral sensor and machine learning, and 3) evaluate the standard and newly registered peanut fungicides with different modes of action for stem rot control in peanuts using a laboratory bioassay. For Objective 1, spectral reflectance and leaf temperature of peanut plants were measured by spectral and thermal sensors in controlled greenhouse experiments. Differences in sensor-based responses between A. rolfsii-infected and non-infected plants were detected 0 to 1 day after observation of foliar disease symptoms. In addition, spectral responses of peanut to the infection of A. rolfsii were more pronounced and consistent than thermal changes as the disease progressed. Objective 2 aimed to identify specific signatures of stem rot from reflectance data collected in Objective 1 utilizing a machine learning approach. Wavelengths around 505, 690, and 884 nm were repeatedly selected by different methods. The top 10 wavelengths identified by the recursive feature selection methods performed as well as all bands for the classification of healthy peanut plants and plants at different stages of disease development. Whereas the first two objectives focused on disease detection, Objective 3 focused on disease control and compared the properties of different fungicides that are labeled for stem rot control in peanut using a laboratory bioassay of detached peanut tissues. All of the foliar-applied fungicides evaluated provided inhibition of A. rolfsii for up to two weeks on plant tissues that received a direct application. Succinate dehydrogenase inhibitors provided less basipetal protection of stem tissues than quinone outside inhibitor or demethylation inhibitor fungicides. Overall, results of this research provide a foundation for developing sensor/drone-based methods that use disease-specific spectral indices for scouting in the field and for making fungicide application recommendations to manage stem rot of peanut and other soilborne diseases. / Doctor of Philosophy / Plant diseases are a major constraint to crop production worldwide. Developing effective and economical management strategies for these diseases, including selection of proper fungicide chemistries and making timely fungicide application, is dependent on the ability to accurately detect and diagnose their signs and/or symptoms prior to widespread development in a crop. Optical sensors combined with machine learning analysis are promising tools for automated crop disease detection, but research is still needed to optimize and validate methods for the detection of specific plant diseases. The overarching goal of this research was to use the peanut-stem rot plant disease system to identify and evaluate sensor-based technologies and different fungicide chemistries that can be utilized for the management of soilborne plant diseases. The specific objectives of this work were to 1) characterize the temporal progress of spectral and thermal responses of peanut to infection and colonization with Athelia rolfsii, the causal agent of peanut stem rot 2) identify optimal wavelengths to detect stem rot of peanut using hyperspectral sensor and machine learning, and 3) evaluate standard and newly registered peanut fungicides with different modes of action for stem rot control in peanuts using a laboratory bioassay. Results of this work demonstrate that spectral reflectance measurements are able to distinguish between diseased and healthy plants more consistently than thermal measurements. Several wavelengths were identified using machine learning approaches that can accurately differentiate between peanut plants with symptoms of stem rot and non-symptomatic plants. In addition, a new method was developed to select the top-ranked, non-redundant wavelengths with a custom distance. These selected wavelengths performed better than using all wavelengths, providing a basis for designing low-cost optical filters to specifically detect this disease. In the laboratory bioassay evaluation of fungicides, all of the foliar-applied fungicides provided inhibition of A. rolfsii for up to two weeks on leaf tissues that received a direct application. Percent inhibition of A. rolfsii decreased over time, and the activity of all fungicides decreased at a similar rate. Overall, the findings of this research provide a foundation for developing sensor-based methods for disease scouting and making fungicide application recommendations to manage stem rot of peanut and other soilborne diseases.

Bibliography: leaves 207-220. Pseudomonas corrigata strain 2140 (Pc2140), isolated from wheat field soil in Australia, antagonises the take-all fungus, Gaeumannomyces graminis var. tritici (Ggt) in vitro and significantly reduces take-all symptoms on wheat in pot trials. This study investigates the mechanisms by which the biocontrol agent reduces the disease symptoms. Biochemical analysis of metabolites of P. corrugata 2140 reveal a number of compounds potentially antagonistic to Ggt and which may play a role in disease control. These include water-soluble antibiotics, siderophores, proteases, peptides and volatiles including hydrogen cyanide.

Bibliography: leaves 207-220. / 220 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Pseudomonas corrigata strain 2140 (Pc2140), isolated from wheat field soil in Australia, antagonises the take-all fungus, Gaeumannomyces graminis var. tritici (Ggt) in vitro and significantly reduces take-all symptoms on wheat in pot trials. This study investigates the mechanisms by which the biocontrol agent reduces the disease symptoms. Biochemical analysis of metabolites of P. corrugata 2140 reveal a number of compounds potentially antagonistic to Ggt and which may play a role in disease control. These include water-soluble antibiotics, siderophores, proteases, peptides and volatiles including hydrogen cyanide. / Thesis (Ph.D.)--University of Adelaide, Dept. of Crop Protection, 1996