Model Plant Research Articles

Uncertainty and Sensitivity Analyses for Postulated Severe Accidents of Reference PWRs and SMRs in the Frame of the IAEA CRP and Relevant Insights

In 2019, the International Atomic Energy Agency (IAEA) launched the 5-year Cooperative Research Project (CRP) I31033 to advance the understanding and characterization of sources of uncertainty and to investigate their effects on the key figures of merit (FOMs: response parameters of interest) of the severe accident code predictions for water-cooled reactors. Twenty-two institutions from 18 member states participated in the CRP, and as a result, TECDOCs are being developed for the relevant benchmark exercises. The respective TECDOCs address a specific exercise and outline relevant research results pointing to best practices for the uncertainty and sensitivity analyses of the currently available severe accident codes. For the uncertainty analysis exercise, the CRP participants defined their own analysis scope and framework, including target plant, severe accident code, accident scenario, and relevant FOMs. According to each respective framework, participants independently carried out their own exercise, including plant modeling and nodalization, simulation of reference cases, and relevant uncertainty and sensitivity analyses. Finally, general conclusions were made based on an analysis of the results in view of the best-practice application of the uncertainty and sensitivity methods. Among them, this paper summarizes the main results of the uncertainty and sensitivity exercise performed for both pressurized water reactors and integral light water small modular reactors in the frame of the IAEA CRP with relevant insights.

Expression analysis of defense signaling marker genes in Capsicum annuum in response to phytohormones elicitation.

To tolerate biotic stress, plants employ phytohormones such as jasmonic acid (JA), salicylic acid (SA), and ethylene (ET) to regulate the immune response against different pathogens. Phytohormone-responsive genes, known as "Defense signaling marker genes," are used to evaluate plant disease resistance during pathogen infection. Most information on these marker genes derives from studies on the model plant Arabidopsis thaliana. The present study was aimed analyze the effect of hormonal elicitation at different concentrations at 24h pos-treatment in the transcript level of 8 traditional genes selected for molecular studies plant-pathogen interactions in Capsicum. Chemical treatment was achieved by spraying leaves of in vitro seedlings C. annuum L. with 0.1mM, 1mM or 2.5mM ET; 1mM, 2.5mM, or 5mM SA; 2.5mM BABA; or 0.150mM MeJA. Twenty-four hours after treatments were applied molecular analyses were carried out using qPCR to investigate the expression. Results revealed that 1mM of ET or 0.15mM of MeJA activated the expression CaPR1 (18--11.64-fold change), CaLOX2 (13.80-fold), CaAP2/ERF06 (22- 5.3- fold change), and CaPDF1.2 (2.3-1.5- fold). While, 5mM of SA present effect of negative regulation on the expression in most of these genes. Our results show that the expression profile induced by phytohormones in CaPR1 are particular in C. annuum, because were significantly induced for ET/MeJA, and dow-regulation with SA Contrary to Arabidopsis. Although, on both plants it is observed the cross talk between JA/ET and SA mediated signal pathways for the regulation of this gene.

The genus Paris: a fascinating resource for medicinal and botanical studies

Abstract The genus Paris, comprising a series of distinctive medicinal plants, has been utilized globally for its therapeutic properties over centuries. Modern pharmacological studies have demonstrated that secondary metabolites from Paris species exhibit significant pharmacological activities, including anticancer, hemostatic, anti-inflammatory, antimicrobial and other effects. Additionally, the unique morphological traits and large genome size of Paris species have continuously captivated the interest of botanists and horticulturalists. Nonetheless, the conservation of wild Paris populations is threatened due to the lengthy reproductive cycle and overexploitation, posing considerable challenges to their development and sustainable use. This review provides a comprehensive overview of the botanical characteristics, historical medicinal uses, pharmacological effects and toxicity evaluation of secondary metabolites in Paris species. It also covers the molecular biological research conducted on the genus Paris and proposes key research questions and important directions for future solutions. We advocate for the expansion and implementation of multi-omics approaches, as well as molecular and genetic technologies recently advanced in model plant research, to intensively study Paris species. This will facilitate the comprehensive understanding of gene function and molecular mechanisms underlying specialized metabolite formation in Paris.

A Short-Circuit Current Calculation Model for Renewable Power Plants Considering Internal Topology

With the large-scale integration of renewable energy into the grid, traditional short-circuit current (SCC) calculation methods for synchronous generators are no longer applicable to inverter-based non-synchronous machine sources (N-SMSs). Current SCC calculation methods for N-SMSs often use a single-machine multiplication method, which tends to overlook the internal variability of N-SMSs within power plants, leading to low calculation accuracy. To address this issue, this paper first derives an analytical expression for SCC in grid-connected inverters under low voltage ride through (LVRT) control strategies. Then, a single-machine steady-state SCC calculation model is proposed. Based on the classification of N-SMSs, a practical SCC calculation model for renewable power plants is introduced, balancing accuracy and computational speed. The feasibility of the model is validated through simulations. The proposed method enables simple calculations to obtain the steady-state voltage and SCC at the machine terminal, offering strong engineering practicality.

Enrichable Protein Footprinting for Structural Proteomics.

Protein footprinting is a useful method for studying protein higher order structure and conformational changes induced by interactions with various ligands via addition of covalent modifications onto the protein. Compared to other methods that provide single amino acid-level structural resolution, such as cryo-EM, X-ray diffraction, and NMR, mass spectrometry (MS)-based methods can be advantageous as they require lower protein amounts and purity. As with other MS-based proteomic methods, such as post-translational modification analysis, enrichment techniques have proven necessary for both optimal sensitivity and sequence coverage when analyzing highly complex proteomes. Currently used reagents for footprinting via covalent labeling, such as hydroxyl radicals and carbodiimide-based methods, do not yet have a suitable enrichment method, limiting their applicability to whole proteome analysis. Here, we report a method for enrichable covalent labeling built upon the GEE/EDC system commonly used to covalently label aspartic acid and glutamic acid residues. Novel labeling reagents containing alkynyl functionality can be "clicked" to any azido-containing molecule with copper-catalyzed azide-alkyne cycloaddition (CuAAC), allowing for enrichment or further labeling. Multiple azide- and alkyne-containing GEE-like molecules were tested, and the most efficient method was determined to be the EDC-facilitated coupling of glycine propargyl amide (GPA) to proteins. The pipeline we report includes clicking via CuAAC to a commercially available biotin-azide containing a photocleavable linker, followed by enrichment using a streptavidin resin and subsequent cleavage under ultraviolet light. The enrichment process was optimized through the screening of clickable amines, coupling reagents, and enrichment scaffolds and methods with pure model proteins and has also been applied to complex mixtures of proteins isolated from the model plant, Arabidopsis thaliana, suggesting that our method may ultimately be used to measure protein conformation on a proteomic scale.

Cloud point prediction model for polyvinyl alcohol production plants considering process dynamics

In polyvinyl alcohol (PVA) production plants, the cloud point is controlled as one of the product properties. The cloud point is the temperature at which the water solubility rapidly decreases because hydrogen bonds between PVA and water are broken. If the cloud point falls below a controlled value, the performance of the PVA as a product deteriorates, and thus it is necessary to monitor the cloud point in real time and ensure that it does not deviate from the controlled value. However, the cloud point cannot be analysed frequently in practical operations. In this study, a soft sensor that continuously predicts the cloud point from process variables that can be measured in real time was constructed using machine learning. Furthermore, the prediction accuracy of the model was improved by (1) increasing the number of samples using a data set of similar quality to the cloud point, considering that the number of samples near the control value of the cloud point is small, and (2) selecting the optimum process variable and time-delay range, considering the time delay of the process variable to accommodate the dynamic behaviour of the plant. Analysis was conducted using data measured from an actual PVA manufacturing plant. When comparing the conventional method with the proposed method, the coefficient of determination, used as an indicator to evaluate model performance, improved from 0.288 to 0.729. Furthermore, the root mean squared error decreased from 1.52 to 0.937. These results demonstrate that the proposed method contributes to improved prediction accuracy.

Combination of plant and soil water potential monitoring and modelling demonstrates soil-root hydraulic disconnection during drought

Combination of plant and soil water potential monitoring and modelling demonstrates soil-root hydraulic disconnection during drought

Analytical approach in designing PID controller for complex fractional order transfer function

The study focuses on the fractional complex order plant model, which has gained popularity in applied mathematics, physics, and control systems. A significant contribution of this research lies in discussing the physical phenomena associated with complex plant models and their impact on system stability and robustness. The main purpose of the method presented in this paper is to tune the controller parameters to ensure the stability and robustness of the system. There are methods presented in the literature for this purpose. One of these methods is to keep the phase curve in the system frequency response flat within a certain range. However, this process is based on equating the derivative of the phase value to zero at a certain frequency and adds great mathematical complexity to the calculations. In this study, reliable analytical formulas are presented for the same purpose using a graphical approach. Since the fractional complex order plant model represents the most general mathematical form, it enables easy creation of other plant models, including integer order and fractional order plant. The reason why this plant is chosen is that this structure can be named as the universal plant, which all other structures can be built by making little variations. For instance, a transfer function having integer, real and/or complex number coefficients and/or orders can be obtained by proper determination of the parameters of the universal plant. A time delay can also be added towards researcher's desire. The main inspiration comes from studying on an inclusive plant. The method in this paper intends to tune the well‐known classical Proportional Integral Derivative controller. Thus, effectiveness of the integer order controller on various plants will be shown. This approach provides analytical calculation equations for the physical modifications of plants with integer, fractional, and/or complex coefficients and/or orders. The effectiveness of the method is demonstrated visually with different examples that include these different possible situations. The results observed in the changes of the parameters in the transfer functions were also examined. Thus, pros and cons of the variations of integer, fractional, and complex numbers on system parameters have been shown.

PlantView: Integrating deep learning with 3D modeling for indoor plant augmentation

Indoor plant recognition poses significant challenges due to the variability in lighting conditions, plant species, and growth stages. Despite the growing interest in applying deep learning techniques to plant data, there still needs to be more research focused on the automatic recognition of indoor plant species, highlighting the need for real-time, automated solutions. To address this gap, this study introduces a novel approach for real-time identification and visualization of indoor plants using a Convolutional Neural Network (CNN)-based model called PlantView, integrated with Augmented Reality (AR) for enhanced user interaction. The proposed PlantView model not only accurately classifies the plant species but also visualizes them in a 3D AR environment, allowing users to interact with virtual plant models seamlessly integrated into their real-world surroundings. We developed a custom dataset comprising over 28,000 images of 48 different plant species at various growth stages, captured under diverse lighting conditions and camera settings. Our proposed approach achieves an impressive accuracy of 98.20 %. To validate the effectiveness of PlantView model, we conduct extensive experiments and compared its performance against state-of-the-art methods, demonstrating its superior accuracy and processing speed. The results indicate that our method is not only highly effective for real-time indoor plant recognition but also offers practical applications for enhancing indoor plant care and visualization. This research offers a comprehensive solution for indoor plant enthusiasts and professionals, combining advanced computer vision techniques with immersive AR visualization to revolutionize the way indoor plants are identified, visualized, and integrated into living spaces.

SAGA1 and MITH1 produce matrix-traversing membranes in the CO2-fixing pyrenoid.

Approximately one-third of global CO2 assimilation is performed by the pyrenoid, a liquid-like organelle found in most algae and some plants. Specialized pyrenoid-traversing membranes are hypothesized to drive CO2 assimilation in the pyrenoid by delivering concentrated CO2, but how these membranes are made to traverse the pyrenoid matrix remains unknown. Here we show that proteins SAGA1 and MITH1 cause membranes to traverse the pyrenoid matrix in the model alga Chlamydomonas reinhardtii. Mutants deficient in SAGA1 or MITH1 lack matrix-traversing membranes and exhibit growth defects under CO2-limiting conditions. Expression of SAGA1 and MITH1 together in a heterologous system, the model plant Arabidopsis thaliana, produces matrix-traversing membranes. Both proteins localize to matrix-traversing membranes. SAGA1 binds to the major matrix component, Rubisco, and is necessary to initiate matrix-traversing membranes. MITH1 binds to SAGA1 and is necessary for extension of membranes through the matrix. Our data suggest that SAGA1 and MITH1 cause membranes to traverse the matrix by creating an adhesive interaction between the membrane and matrix. Our study identifies and characterizes key factors in the biogenesis of pyrenoid matrix-traversing membranes, demonstrates the importance of these membranes to pyrenoid function and marks a key milestone toward pyrenoid engineering into crops for improving yields.

Enhancing the energy and environmental efficiency of the city's infrastructure based on optimizing its fuel and energy balance

The article considers the direction of increasing the energy and environmental efficiency of the city's energy infrastructure through the modernization of existing thermal power plants (TPP) and combined heat and power (CHP) plants using combined-cycle gas turbine (CCGT) plants. Fuel and energy balances of electric power plants have been constructed, and the energy and environmental effects of the use of CCGT have been assessed. The modeling of energy and environmental indicators for the thermal circuits of the CCGT was conducted using the Thermoflex, GT PRO software (Thermoflow) and the ISC Manager program developed at the National Research University "Moscow Power Engineering Institute (MPEI)". The analysis of CCGT efficiency in urban energy applications is based on modeling and optimizing the city’s fuel and energy balance (FEB). For this purpose, the OptiTEB program developed at the Department of PTS at the National Research University "MРEI" is used. Constructing fuel and energy systems in cities and regions is a pressing task that enables the planning of a strategy for the development of the urban fuel and energy complex (FEC), with an assessment of the magnitude of harmful emissions, including greenhouse gases. The article presents the results of work on establishing scientific foundations for modern heat supply systems, exemplified by a mathematical model of the Moscow thermal power plant and its optimization, taking into account the projected development of electric transport infrastructure over the coming decades, improving the thermal protection characteristics of newly constructed buildings, and the potential increase in the use of renewable energy sources (RES). The growth in the share of electric transport should be linked to an increase in the share of renewable energy sources (RES). Simply increasing the number of electric vehicles without a significant rise in renewable energy usage in the city's energy balance will not result in a reduction of carbon dioxide and harmful substance emissions. Expanding electricity generation through CCGT, alongside the growth of renewable energy use in the city, can lead to a significant decrease in carbon dioxide emissions.

Local geometry of NAE-SAT solutions in the condensation regime

AbstractThe local behavior of typical solutions of random constraint satisfaction problems (csp) describes many important phenomena including clustering thresholds, decay of correlations, and the behavior of message passing algorithms. When the constraint density is low, studying the planted model is a powerful technique for determining this local behavior which in many examples has a simple Markovian structure. The work of Coja-Oghlan, Kapetanopoulos, Müller (Comb Prob Comput 29:346-422, 2020) showed that for a wide class of models, this description applies up to the so-called condensation threshold. Understanding the local behavior after the condensation threshold is more complex due to long-range correlations. In this work, we revisit the random regular nae-sat model in the condensation regime and determine the local weak limit which describes a random solution around a typical variable. This limit exhibits a complicated non-Markovian structure arising from the space of solutions being dominated by a small number of large clusters. This is the first description of the local weak limit in the condensation regime for any sparse random csps in the one-step replica symmetry breaking (1rsb) class. Our result is non-asymptotic and characterizes the tight fluctuation $$O(n^{-1/2})$$ O ( n - 1 / 2 ) around the limit. Our proof is based on coupling the local neighborhoods of an infinite spin system, which encodes the structure of the clusters, to a broadcast model on trees whose channel is given by the 1rsb belief-propagation fixed point. We believe that our proof technique has broad applicability to random csps in the 1rsb class.

Screening method and metabolic analysis of plant anti-aging microorganisms via ammonia-induced senescence in the duckweed Wolffia microscopica.

Ammonium is the preferred N nutrition over nitrate for some plant species, but it is toxic to many other plant species and induces senescence at high concentrations. The duckweed Wolffia microscopica (Griff.) Kurz is the smallest and fast-growing angiosperm. It is highly sensitive to ammonium and has a short lifespan on media containing 0.5 mM or higher ammonia. This feature makes it a potential model plant to screen for anti-aging microorganisms. By co-culturing W. microscopica with endophytic microorgainisms isolated from rubber tree, we screened out an Aspergillus sclerotiorum strain ITBB2-31 that significantly increased the lifespan and the biomass of W. microscopica. Interestingly, both filter-sterilized and autoclaved exudates of ITBB2-31 increased the lifespan of W. microscopica cultures from 1 month to at least 7 months. Meanwhile, the exudates also showed strong anti-aging effects on cassava and the rubber tree leaves and increased chlorophyll contents by 50% - 350%. However, high contents of filter-sterilized exudates inhibited the growth of W. microscopica while extending its lifespan, indicating that there were heat-sensitive growth-inhibiting agents in the exudates as well. Comparative metabolome analysis of the filter-sterilized and autoclaved exudates revealed multiple heat-stable anti-aging and heat-sensitive growth-inhibiting compounds. Our results suggest that W. microscopica can be served as a rapid and efficient model plant to screen for plant anti-aging microorganisms.

The auxin-like effect of substrate and auxin sensitivity of plant modulate the PGPR activity of Lysinibacillus pinottii sp. nov. PB211

BackgroundBacterial auxin production is a mechanism that promotes plant growth. However, it can also be linked to deleterious rhizobacteria and plant-pathogenic bacteria. High levels of auxins have the potential to impede plant growth. Additionally, certain environmental factors can enhance auxin activity and impact the activity of plant growth-promoting rhizobacteria (PGPR).ResultsIn this work, we boarded how the auxin-like effect in the soil–plant system modulates the plant growth-promoting activity of Lysinibacillus pinottii sp. nov. PB211. The effect of humified organic matter (HOM) soil was simulated with humic acids (HA) coming from vermicompost; the spectral configuration (13C-CP-TOSS-NMR and FTIR) and coleoptile elongation test indicated its bioactivity. Cucumber exhibits a PGP effect of PB211 and HA at a lower concentration compared to corn. This disparity agrees with the differential sensitivity to auxins of both plant models. Monocot plants, such as corn, generally exhibit greater resistance to exogenous auxin activity compared to eudicot plants, such as cucumber. The presence of HA in the growth substrate (sand) is found to modulate the PGPR activity of PB211, resulting in a loss of PGPR activity.ConclusionsThe findings highlight the importance of considering the cumulative auxin-like effects in the soil–plant system when utilizing bacterial inoculants for plant growth promotion in agriculture.Graphical

Evaluation of Microplastic Toxicity in Drinking Water Using Different Test Systems

Microplastic pollution poses a significant threat to environmental and human health. This study investigated the toxicological and genotoxic effects of various microplastic types (polystyrene (PS), polyethylene terephthalate (PET), polypropylene (PP), and polyethylene (PE)) on plant and animal models. Aqueous extracts of microplastics in different size fractions (0.175 mm, 0.3 mm, 1 mm, 2 mm, and 3 mm) were evaluated for their impact on barley seed germination and cell division. Results indicated that smaller microplastic fractions exhibited higher toxicity, particularly for PP and PE. Significant reductions in germination rates and root growth were observed, along with increased chromosomal aberrations in barley cells. Furthermore, the migration of formaldehyde, a known toxicant, from microplastics exceeded permissible limits. These findings highlight the potential risks associated with microplastic pollution, particularly in drinking water sources. Future research should focus on the long-term health impacts of microplastic exposure, including carcinogenic potential, and explore the synergistic effects with other pollutants. Stricter regulations on microplastic pollution and advancements in water treatment technologies are urgently needed to mitigate these risks.

SlSPA3 regulates the nuclear abundance of SlUVR8 in tomato.

Tomato (Solanum lycopersicum L.) is an important model plant species in photomorphogenesis research. Ultraviolet B (UV-B) induces the dissociation of homodimers of the photoreceptor UV RESISTANCE LOCUS8 (UVR8) into monomers, which translocate into the nucleus. Nuclear accumulation of UVR8 is a prerequisite for its signaling function. Previous studies have reported that SUPPRESSOR OF PHYTOCHROME A-105 (SPA) family members may regulate UV-B signaling in Arabidopsis (Arabidopsis thaliana); however, the underlying mechanism is unknown. Here, we show that the tomato genome encodes four SPA (SlSPA) orthologs. Genome-edited Slspa3 mutants exhibited enhanced photomorphogenic responses in white light, suggesting that SlSPA3 inhibits general photomorphogenesis. By contrast, UVR8-mediated gene expression in response to UV-B was compromised in Slspa3 mutants, suggesting that SlSPA3 promotes UV-B signaling. UV-B-induced nuclear accumulation of UVR8, which is essential for UV-B signaling, was reduced in the Slspa3 mutants. Moreover, UV-B-induced nuclear accumulation of UVR8 was also reduced in the Arabidopsis spa1 spa2 spa3 and spa1 spa2 spa4 triple mutants, indicating a conserved mechanism in these two species. Notably, spa1 spa2 spa4 exhibited normal UV-B-induced interaction between UVR8 and the plant morphogenesis repressor CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1). This suggests that the well-established mechanisms of UVR8 nuclear retention remained unaffected in spa1 spa2 spa4. Thus, our work uncovered a potentially unrecognized mechanism by which SPA proteins regulate UV-B signaling through the promotion of UVR8 nuclear abundance in land plants.

TDOF PID Controller for Enhanced Disturbance Rejection with MS-Constraints for Speed Control of Marine Diesel Engine

This study proposes a two-degree-of-freedom PID controller design and tuning method based on a simple pole placement approach to enhance servo and regulatory performance while ensuring the stability of diesel engines. In the modeling of the control target, the actuator is analytically modeled. In contrast, the type of model for the diesel engine is derived analytically, and its parameter estimation uses operational data from naval ships. The proposed controller consists of a PID controller to improve regulatory performance and a set-point filter to enhance servo response. PID controller parameters consist of the parameters of the controlled plant model and a single tuning variable. At the same time, the set-point filter comprises the controller parameters and a single weighting factor. To ensure the robust stability of the controller, the controller parameters are tuned based on the maximum sensitivity. To verify the effectiveness of this study, simulations for the speed control of a diesel engine with inherent nonlinearity were conducted under three scenarios. Performance was quantitatively analyzed using the integral of time-weighted absolute error, 2% settling time, 2% recovery time, specified maximum sensitivity, and maximum peak response value, and was compared with Skogestad’s IMC and Lee’s IMC. Based on evaluation indices, the proposed controller demonstrated superior performance in both servo and regulatory responses compared to the two existing control techniques while ensuring stability.

Interplays of Cuticle Biosynthesis and Stomatal Development: From Epidermal Adaptation to Crop Improvement.

Crop production is limited by environmental stresses such as a water deficit, salinity, and extreme temperature. Lipophilic cuticle and stomatal pore govern plant transpirational water loss and photosynthetic gas exchange and contribute to plant adaptation to stressful environments. Intricate interplays between cuticle biosynthesis and stomatal development are supported by increasing evidence from phenotypic observations. Several mutants, initially identified as being deficient in cuticle development, have exhibited altered phenotypes in terms of stomatal ridges, numbers, patterns, and shapes. Similarly, mutants with abnormal stomatal patterning have shown defective cuticle formation. Recently, signaling components and transcription factors orchestrating cuticle biosynthesis and stomatal formation have been characterized in both model and crop plants. In this review, we summarize the genetic interplay between cuticle biosynthesis and stomata formation. Current strategies and future perspectives on exploiting the intertwined cuticle biosynthesis and stomatal development for crop stress resistance improvement are discussed.

Tracing the evolutionary and genetic footprints of atmospheric tillandsioids transition from land to air

Plant evolution is driven by key innovations of functional traits that enables their survivals in diverse ecological environments. However, plant adaptive evolution from land to atmospheric niches remains poorly understood. In this study, we use the epiphytic Tillandsioideae subfamily of Bromeliaceae as model plants to explore their origin, evolution and diversification. We provide a comprehensive phylogenetic tree based on nuclear transcriptomic sequences, indicating that core tillandsioids originated approximately 11.3 million years ago in the Andes. The geological uplift of the Andes drives the divergence of tillandsioids into tank-forming and atmospheric types. Our genomic and transcriptomic analyses reveal gene variations and losses associated with adaptive traits such as impounding tanks and absorptive trichomes. Furthermore, we uncover specific nitrogen-fixing bacterial communities in the phyllosphere of tillandsioids as potential source of nitrogen acquisition. Collectively, our study provides integrative multi-omics insights into the adaptive evolution of tillandsioids in response to elevated aerial habitats.

Genetic diversity assessment of cucumber landraces using molecular signatures

Genetic profiling of the biodiversity in cultivated crop plants is necessary to preserve important genes and utilize them in a breeding program. Cucumber is used as a model plant to study various characteristics of Cucurbitaceae. Its adaptation to a wide range of climatic conditions suggested analyzing the landraces. The present study was conducted to evaluate the differences, at the genetic level, among landraces spanning five continents. DNA extracted from fifty-six landraces selected from USDA germplasm bank to cover a global representative sample of world cucumber landraces was used for polymerase chain reaction using twenty-eight polymorphic expressed sequence tags simple sequence repeat (EST-SSR) markers. Twenty-eight EST-SSR markers covering all seven chromosomes yielded 98 bands with an average of 3.42 bands per marker. Polymorphic information content ranged from 0.00 (EC35) to 0.74 (EC17) with an average of 0.34. Six clusters provided an appropriate summary of the variation among the landraces, with the two largest groups including 32 (Asiatic) and 17 (European and American) landraces, respectively. Four small groups, three with two members, and one with one member (PI 525155-Egypt) were dissimilar to the two main groups. Landraces from the same region were often clustered together. Genetic similarity of the landraces was revealed by marker banding patterns. The locations of genetic diversity for cucumber landraces can be identified from this study.