Keywords: Arabidopsis thaliana, phytoremediation, abiotic stress, ibuprofene, doxorubicin, two-dimensional electrophoresis Nowadays, develop of the pharmaceutical industry is very fast. Reason of this trend is ever-increasing number of diseases, lifestyle and still increasing demand for the drugs. With this trend growing interest in the analysis of the residues of pharmaceuticals in the environment which is result of incomplete wastewater treatment. This diploma thesis is studying effect of cytostatic drugs, specifically doxorubicin and one of the most widely used analgesics - ibuprofen, at the proteome level of the model plant Arabidopsis thaliana. Proteins isolated from plants exposed to the drugs were separated by two-dimensional electrophoresis. Comparing of protein maps by PDQest program (Bio-Rad, USA) was found several proteins whose expression was affected by the presence of drugs in the culture medium. Selected proteins were identified by LC - MS / MS.

Arid and semi-arid regions, mostly found in developing countries with exponentially increasing populations, are in chronic lack of water thereby severely limiting agricultural production. Irrigation with saline water, which is available in large quantities, could be an obvious solution, but current crops are all salt sensitive. Although major efforts are underway to breed salt tolerant crops, no breakthrough results have yet been obtained. One alternative could rely on plant-interacting microbiota communities. Indeed, rhizophere and endosphere microbial communities are distinct from those of the surrounding soils, and these specific communities contribute to plant growth and health by increasing nutrient availability or plant resistance towards abiotic and biotic stresses. Here we show that plant microbe interactions induce plant tolerance to multiple stresses. From a collection of strains isolated from the desert plant Indigofera argentea, we could identify at least four different strategies to induce salt stress tolerance in Arabidopsis thaliana. A deep analysis of Enterobacter sp. SA187 showed that it induces Arabidopsis tolerance to salinity through activation of the ethylene signaling pathway. Interestingly, although SA187 does not produce ethylene as such, the association of SA187 with plants induces the expression of the methionine salvage pathway in SA187 resulting in the conversion of bacterially produced 2-keto-4-methylthiobutyric acid (KMBA) to ethylene. In addition, a metabolic network characterization of both SA187 and Arabidopsis in their free-living and endophytic state revealed that the sulfur metabolic pathways are strongly upregulated in both organisms. Furthermore, plant genetic experiments verified the essential role of the sulfur metabolism and ethylene signaling in plant salt stress tolerance. Our findings demonstrate how successful plant microbes of a given community can help other plants to enhance tolerance to abiotic stress, and reveal a part of the complex molecular communication process during beneficial plant-microbe interaction.

Abiotic stresses significantly reduce crop yield, causing serious problems in agriculture. Understanding the mechanisms of plant stress responses could contribute to the improvement of their stress tolerance. Phytohormones play an important role in plant stress defence as well as in regulation of growth and development. This thesis summarizes the results published in four articles focused on the evaluation of the effects of phytohormones during abiotic stresses, namely salinity, drought, ZnO nanoparticle treatment and cold stress. The main emphasis is put on abscisic acid as the key regulator of water status and stress defence, and on cytokinins, which regulate plant growth and stabilize photosynthetic machinery. Cytokinins act antagonistically to abscisic acid. Our results showed that abscisic acid is a general abiotic stress response regulator. Stress- tolerant plants (halophyte Thellungiella salsuginea or winter line of einkorn wheat Triticum monococcum) had a higher basal level of this hormone, especially in shoot meristematic tissues (apices, crowns), than stress-sensitive plants. Stress-tolerant plants reacted faster and in a more flexible way to stress. Active cytokinins were negatively affected by stress, which was associated with growth suppression. The drought stress study showed that...

<p>  </p> <p>Modern agriculture must address the massive challenge of providing food for the increasing population. The challenge lies in increasing crop yield and reducing losses caused by abiotic and biotic stresses. In fact, for some crops, such as wheat and maize, over 40% of the production is lost due to environmental conditions (abiotic stresses) or pests and pathogens (biotic stresses). Specialists in the area are suggesting a need for a second green revolution to meet the increasing demand in food production. While in the first green revolution was focused on breeding and genetics to produce crops' genetic lines with a higher yield. The second green revolution will utilize cutting-edge technologies to increase yield and reduce crop losses. The development of remote sensing technologies and their applications is the main driving force of modern agricultural practices. Currently, farmers are relying more on automation, data collection, and data analysis to manage farming operations. The reliance on remote sensor technologies is a game-changer for traditional agricultural practices, and it is contributing tremendously to increasing production and avoiding yield losses. Hyperspectral phenotyping is an emerging remote sensing technology that utilizes the light's reflectance to provide insightful information about plant traits. For several years, research groups have been applying hyperspectral phenotyping techniques to detect plant traits information, such as nitrogen content, photosynthesis rates, pests infestation, and abiotic stress detection. Although this is not a novel approach to plant traits detection, this technology application is not mature yet. Several challenges are associated with using hyperspectral information for phenotyping, such as model transferability, data collection scalability, and the heritability of plant traits retrieved using hyperspectral data. In my thesis dissertation, I addressed some of those challenges contributing to advances in hyperspectral phenotyping. My results demonstrate that using full-range hyperspectral reflectance data (400-2400nm) to retrieve nitrogen in winter wheat increases the model transferability across years and genotypes. Predicting nitrogen content using hyperspectral data can be used as a surrogate to calculate nitrogen use efficiency traits. My research highlights the hurdles associated with spectral detection of stresses interaction, such as drought stress, which can mask western corn rootworm detection in maize. Finally, I explored the correlation among spectral, functional, and field traits in a soybean NAM (Nested Association Mapping) population to understand the relationship among those traits' variability and how that information can be used for soybean breeding programs. The outcomes of my thesis dissertation advance the knowledge in the hyperspectral phenotyping field and its application to modern agriculture. Consequently, my study also contributes to food security programs by providing insightful information about the hyperspectral assessment of plant health status, which is essential to increase yield production and reduce crop losses. </p>

Biotic and abiotic stresses are signifi cant factors limiting the production of food and other supporting materials required to sustain increasing world population. Plant health is directly related to human health and is increasingly becoming signifi cant and demands more attention towards limiting the damages caused by biotic and abiotic stresses. Signifi cant progress has been made towards our understanding of the processes, which mediate both biotic and abiotic stress signaling in plants. Signifi cant role is played by various plant hormones, e.g., salicylic acid (SA) and jasmonic acid (JA) in biotic stress and abscisic acid (ABA) in abiotic stress (Annu Rev Cell Dev Biol 28:489-521, 2012). Other hormones with minor role include the cytokinins (CK), auxins (indole 3 acetic acid. IAA), and the brassinosteroids (BR) (Annu Rev Cell Dev Biol 28:489-521, 2012). Cross talk between these plant hormones is signifi cant and may result in either synergistic or antagonistic effect on stress responses (Annu Rev Cell Dev Biol 28:489-521, 2012). In recent years, extensive research carried out in various laboratories has implicated cross talk between the ABA and the SA in abiotic stress response. This is signifi cant in light of SA being key player in biotic stress responses in plants. This review will discuss the role of SA in biotic and abiotic stress signaling and its cross talk with other hormones in mediating abiotic stress signaling in plants.

Doctor Educationis / Maize (Zea mays L.) is grown globally as an important grain crop in South Africa, United States, China and Brazil and plays a major role in the worldwide economy. In South Africa, the grain is utilised for food consumption, livestock feed, for malting purposes and bioethanol production. Maize contains approximately 72% starch, 10% protein, 4% fat and supplying an energy density of 365 Kcal/100 g. The production of grain crops in South Africa is restricted by various factors such as abiotic and biotic stresses. The fungal genus Aspergillus is one of the most important biotic stresses affecting maize in the country. Aspergillus flavus can contaminate a wide range of agricultural commodities either in storage or field. Hydrogen sulfide appears to have a potential in the mechanism of resistance against pathogen attack by Aspergillus flavus. / 2023

Abiotic stresses such as drought, salt and exposure to toxic metals adversely affect the growth and productivity of crop plants and are serious threats to agriculture. We are currently working with an Arabidopsis family of proteins known as Stress Associated Proteins (SAPs). There are a total of 14 proteins in the Arabidopsis SAP family whose members have been suggested to provide tolerance to abiotic stresses in plants. For this project, we aim to characterize AtSAP13, which codes for a protein of 249 amino acid residues. Through overexpression, we investigated the sensitivity or tolerances provided by the overexpressed protein in comparison to wild-type plants. Our preliminary results showed that Arabidopsis plants overexpressing SAP13 showed strong tolerance to arsenite, cadmium, and zinc. A semi-quantitative RT-PCR was performed to analyze SAP13’s mRNA levels in wild type plants exposed to the same set of stresses. Tissue specific expression was analyzed using a GUS histochemical assay. Sub-cellular localization of AtSAP13 was analyzed by creating an in-frame fusion of SAP13 and enhanced GFP (eGFP). We set out to optimize growth conditions for Crambe abyssinica in order to determine if Crambe could be grown as a biofuel crop in New England. We have determined that Crambe can be grown successfully in the New England climate. We tested three fertilizer application rates, two different cultivars, and two different soil types for changes in yield. In the end, we observed the greatest increase in yield when planted on well drained soil.

Lettuce is a highly nutritional crop that is sensitive to multiple stresses, including salt stress. The decreasing availability of salt-free water is posing a major challenge to growing nutritious lettuce in hydroponic systems. Despite evidence that salt stress affects yield and nutrition, its impacts on economically important growth stages are overlooked. This study addressed the knowledge gaps regarding the salt stress impact on romaine lettuce. Four independent experiments were conducted in controlled environment conditions using 2-38 lettuce genotypes, to assess the effects of salt stress at rosette or head formation. An increase in sodium chloride (NaCl) levels (0 to 150 mM) linearly decreased lettuce biomass. A positive association was observed between NaCl and sodium to potassium ion ratio. Lettuce was found to be sensitive to salt above 40 mM NaCl. The phenotyping of 38 lettuce genotypes revealed significant variability in salt stress tolerance. Genotype, Green forest exhibited a higher decline in fresh and dry biomass compared to Burgundy delight, indicating its higher sensitivity to salt stress. Sodium accumulation was significantly higher in both genotypes under salt stress, while potassium decreased in Green forest but remained relatively stable in Burgundy Delight. Hydro-primed lettuce had higher photosynthetic efficiency and oxidative stress tolerance than the control. Hydro-priming seed treatment could be used as a cost-effective priming technique to boost economic efficiency under stress. In addition, the low sodium: potassium ratio and high biomass can be used as indicators for selecting salt-tolerant genotypes.

The physiological responses to salt stress were measured in Chenopodium quinoa. In a greenhouse experiment, salt water was applied to the quinoa varieties, Chipaya and KU-2, and to the model halophyte Thellungiella halophila to assess their relative responses to salt stress. Height and weight data from a seven-week time course demonstrated that both cultivars exhibited greater tolerance to salt than T. halophila. In a growth chamber experiment, three quinoa cultivars, Chipaya, Ollague, and CICA 17 were hydroponically grown and physiological responses were measured with four salt treatments. Tissues collected from the growth chamber treatments were used to obtain leaf succulence data, tissue ion concentrations, compatible solute concentrations, and RNA for real-time PCR. Stomatal conductance and fresh weight were measured to determine the degree of stress and recovery. The expression profiles of SOS1, NHX1, and TIP2, genes involved in salt stress, showed constitutive expression in root tissue and up-regulation in leaf tissue in response to salt stress. These data suggest that quinoa tolerates salt through a combination of exclusion and accumulation mechanisms.

Corn is one of American agriculture's greatest success stories, where we have witnessed incredible increases in yield potential over the last half-century. However, abiotic stress is still the primary limiting factor preventing plants from reaching their true yield potential. In addition, agriculture is not exempt from the deleterious effects of changing weather patterns and the altered climate our world will face as time progresses. Thus, increasing our understanding of how crops interact with their environment both above and below the soil will be crucial to increasing production on a global scale while maximizing profitability at a local level. Five studies were carried out to quantify the relationship between corn and multiple abiotic factors, including temperature, moisture, and nitrogen. In study one, Corn seed germination as a function of temperature was quantified, and the effects were compared between soybean and cotton, both major agronomic crops in Mississippi. Study two determined the effects of osmotic stress on corn seed germination, and commercial corn hybrids' variability was explored. In study three, functional relationships between temperature and early season growth and development were quantified, and the concept of a simple mathematical model for predicting growth as a function of temperature was explored. Study four exemplified the effects of increasing waterlogging durations from 0 to 14 days and determined critical limits for above and below-ground growth. Finally, in study five, growth, development, and physiology were determined as a function of nitrogen concentration. In addition, optimum concentrations to maximize vigor were estimated. Data generated from these studies exemplify how abiotic stress significantly affects corn during germination and early season growth and development. These datasets will be valuable foundations to build on as we explore how abiotic stress affects all growth stages of corn and other important agronomic crops. Functional relationships generated from these studies will be useful to update crop simulation models. Both simple and complex mathematical models have promising implications in emerging and developing precision and predictive agricultural technologies.