Search

Extended Abstract Background: Lentil (Lens culinaris Medik) is a cool season seed legume and a good source of nutrients needed by humans, including protein, carbohydrates, vitamins, and minerals. The production of high-yielding and high-plant-height varieties is one of the lentil improvement goals. For this purpose, it is necessary to collect and evaluate germplasm as a base population, along with identifying and utilizing lines with high potential and other desirable traits. The environment has a significant effect on the crop production of this plant. Therefore, direct selection is important for seed yield. Since seed yield depends on the yield components, the yield and its components must be regarded as a group at the selection time to improve the yield. To properly increase yield and economic efficiency, we need to collect desirable lines with desirable genes and transfer these genes to cultivated lines to produce desirable cultivars. Consequently, sufficient information is necessary on accessible genetic materials, which is possible by evaluating different traits. Methods: To assess the model of the simultaneous effect of traits on the lentil seed yield for determining the selection procedure in native lentil lines of Zanjan province, an experiment was conducted in the research farm of the Faculty of Agriculture, Zanjan University, during two cropping years 2017-2018 and 2018-2019. In both years of the experiment, improved cultivars, such as Kimia, Sabz Kohin, Gachsaran, Maragheh, and Bilehsavar, were used as control cultivars. The first-year experiment was conducted in an augmented design based on a randomized complete block design with 200 lines. Each experimental unit included a 1-m row. The distance between the rows was 25 cm, the distance between plants in a row was 5 cm, and the planting depth was 5 cm. Two rows of Kohin-Sabz lentils were planted as margins at the beginning and end of each block. Due to obtaining a sufficient amount of seeds from the first year, the second-year experiment was carried out as a simple lattice design with two replications and larger experimental units for the lines selected from the first year. Each experimental unit included two 1-m lines. The distance between the rows, the distance between plants in a row, and the planting depth were similar to the first-year experiment. Two rows of Kuhin green lentils were planted as margins at the beginning and end of each incomplete block. The measured traits included phenological and morphological traits, yield, and yield components per plant and unit area. Results: Among the studied traits, the highest coefficient of variation was obtained for the number of seeds, biomass, straw yield, and seed yield. The coefficient of correlation showed that the number of seeds and seed yield were positively and significantly correlated with phenological traits, such as the podding period, physiological maturity, and seed-filing period, as well as morphological traits such as plant height and first branching height, respectively. A positive and significant correlation was observed between the number of seeds and seed yield with the number of pods per plant and biomass per plant. In regression analysis by the stepwise method, plant height was the first trait entered into the model, which could explain 46.8% of the variation related to seed yield per plant. Then, the number of seeds per plant, 1000-seed weight (TSW), straw yield per plant, and the seed-filling period were entered into the model, respectively, which could totally explain 67.5% of the variation related to seed yield per plant. The results of the path analysis showed that the number of seeds per plant had the most considerable direct and positive effect on seed yield, followed by the direct effect of the TSW, plant height, and seed-filling period, respectively. Therefore, these traits would be recommended as the most important and significant traits in the indirect selection of seed yield in lentils. Most of the indirect effects of the traits on seed yield were positive, and the most indirect effects were related to seed-filling period, plant height, and straw yield through the number of seeds per plant. Besides, the seed-filling period through plant height and the plant height through the number of seeds had an indirect effect on seed yield. In factor analysis based on principal component analysis and varimax rotation, six factors explained about 76% of the data variation. The first three factors included the most considerable volume of data variation. The first factor was identified as phenology and height, and the second and third factors were identified as yield and yield components. Results showed that the selection based on these factors would lead to the genesis of the high-yield lines. Conclusion: The highest coefficient of variation belonged to these traits: the number of seeds, biomass, straw yield, and seed yield. Seed yield per plant had a positive and significant correlation with the phenological traits of the podding period, seed-filling period, and physiological maturity, as well as morphological traits, namely plant height and the height of the first branch. The number of seeds per plant had the most direct effect on seed yield, followed by TSW, plant height, and seed-filling period. Therefore, these traits can be considered the criteria for selecting superior lines. According to the factor analysis results, six factors could justify 77.306% of the data variations.

High-integrity welds found in safety–critical industries require flaw-free joints, but automation is challenging due to low-volume, often-unique nature of the work, alongside high-uncertainty part-localisation. As such, robotic welding still requires tedious manually taught paths or offline approaches based on nominal Computer-Aided-Design (CAD). Optical and laser sensors are commonly deployed to provide online adjustment of pre-defined paths within controlled environments. This paper presents a sensor-driven approach for defect-free welding, based on the as-built joint geometry alongside the requirement for no-accurate part localisation or CAD knowledge. The approach a) autonomously localises the specimen in the scene without CAD requirement, b) adapts and generates accurate welding paths unique to the as-built workpiece and c) generates robot kinematics based on an external-control strategy. The proposed approach is validated through experiments of unconstrained placed joints, where the increased accuracy of the generated welding paths, with no common seam tracking, is validated with an average error of 0.12 mm, 0.4°. Coupling with a multi-pass welding framework, the deployment of fully automated robotic arc welding takes place for different configurations. Non-Destructive-Testing (NDT) in the form of Ultrasound-Testing (UT) inspection validates the repeatable and flaw-free nature of the sensory-driven approach, exploiting direct benefits in quality alongside reduced re-work.

Wire + Arc Additive Manufacture (WAAM) is an economical manufacturing technique to build components. To maintain the commercial and technical benefits, inspection is desired at each layer of the build. New conformable phased array roller-probes offer the potential to inspect the as-built sample in-process or on completion.A challenge with such inspections is the refraction of the ultrasonic waves at multiple interfaces. The Synthetic Aperture Focusing Technique (SAFT) and Total Focusing Method (TFM), combined with Full Matrix Capture (FMC) acquisition enabled imaging through the as-built WAAM surface. However, single-element firings, associated with FMC are a limiting factor due to the lower energy at transmission, while the high number of firings and subsequent larger data size negatively affect inspection speed.This work introduces the concept of Virtual Source Aperture (VSA) for ultrasonic roller-probe inspection, through modelling of VSA on custom-designed calibration WAAM block. The concept is then demonstrated on a mock as-built WAAM sample inspection with reference defects. The results demonstrate that a markedly lower number of transmissions are required to match the performance of the FMC counterpart while increasing the energy levels. Moreover, an almost 50% reduction in the data size enabled a doubling of the inspection speed.

Introduction Drought is one of the most important environmental stresses and is one of the most common causes of plant growth retardation and yields, and usually decreases the productivity of plants along with other environmental stresses, including salinity and heat. One of the reasons that environmental stresses such as drought, reduces growth and plant photosynthesis ability, is a disturbance in the balance between the production of free oxygen radicals and the protective mechanisms that remedy these radicals which results in the accumulation of reactive oxygen species (ROS), induction of oxidative stress, damage to proteins, membrane lipids, and other cellular components. Under adverse environmental conditions, the role of antioxidant defense system in protecting cellular membranes and other growing organs against oxidative damage seems to be very important. Brassinosteroids (BRs) comprise a group of steroidal hormones that have been implicated in a wide range of physiological responses in plants, including stem elongation, growth of pollen tubes, ethylene biosynthesis, proton pump activation, the regulation of gene expression, activation of enzymes, response to different stresses, nucleic acid and protein synthesis, and photosynthesis. In addition, BRs can protect against damage from stresses such as drought, salinity, and high temperature by activating various mechanisms in plants and increasing the activity of enzymatic antioxidants such as catalase, superoxide dismutase, peroxidase, and glutathione reductase. The purpose of this study was to investigate the possibility of increasing the activity of some antioxidant enzymes, nitrate reductase, photosynthetic pigments, and finally, the seed yield of common beans with the use of Epibrassinolide under drought stress conditions. Materials & Methods A split factorial experiment was conducted based on randomized complete block design with three replications at the research farm of Faculty of Agriculture, the University of Zanjan during the 2016-2017 cropping season. In this experiment, two irrigation conditions included optimal irrigation and drought stress were applied to main plots and two common bean genotypes including Kusha cultivar and COS16 genotype, and four levels of brassinosteroid including of no-application (control), two, four, and six μM were allocated to subplots as factorial. Drought stress was applied at the flowering stage, and common bean plants were sprayed with brassinosteroid (Epibrassinolide) simultaneously with drought stress. In this study, the activity of catalase, guaiacol peroxidase, ascorbate peroxidase, and superoxide dismutase, nitrate reductase, chlorophyll and carotenoid contents, and seed yield were studied. Results & Discussion The results showed that drought stress increased the activity of catalase, guaiacol peroxidase, ascorbate peroxidase, and superoxide dismutase by 38.89%, 84.09%, 40.46%, and 27.37% in contrast with the optimal irrigation, respectively. The highest activity of catalase, guaiacol peroxidase, ascorbate peroxidase, and superoxide dismutase were obtained using different concentrations of Epibrassinolide under drought stress conditions. The application of 2, 4, and 6 μM of Epibrassinolide in drought stress conditions increased by 73.33%, 86.67%, and 113.33% in the catalase activity, increased by 56.36%, 71.82%, and 62.73% in the guaiacol peroxidase activity, increased by 12.82%, 46.15%, and 13.46% in the ascorbate peroxidase activity, and increased by 29.15%, 41.49%, and 47.11% in the superoxide dismutase activity in comparison with non-application of this hormone. It has been reported that the use of BRs significantly improves plant drought tolerance and reduces the accumulation of reactive oxygen species by increasing the activity of antioxidant enzymes. It has been reported that the application of BRs increased the antioxidant enzymes activity in maize, tomato, mustard, soybean, and barley. Also, nitrate reductase activity increased by using of Epibrassinolide, which can enhance plant tolerance to environmental stress. The highest activity of nitrate reductase was obtained by application of 4 μM of Epibrassinolide, which did not show any significant difference with other concentrations. Improvement in the activity of nitrate reductase can be attributed to the effect of BRs on translation or transcription of nitrate reductase, or nitrate absorption at the membrane surface. In optimal irrigation conditions, the use of different concentrations of Epibrassinolide has a slight increase in the contents of chlorophyll a, b, and total, and the use of 4 μM of this hormone resulted in the highest increase in the above traits compared to non-application of the hormone. However, under drought stress conditions, this increase was significant, and the use of 2 μM of this hormone resulted in the highest increase in the above traits compared to non-application of the hormone. In other words, the use of Epibrassinolide in drought stress conditions caused a higher increase in chlorophyll a, b, and total contents relative to optimal irrigation conditions. Application of Epibrassinolide increased the seed yield in both common bean genotypes by increasing the activity of antioxidant enzymes, nitrate reductase, and chlorophyll and carotenoid contents. The highest seed yield was obtained by application of 2 μM of Epibrassinolide with an average of 2068.2 kg/ha. Among the studied genotypes, the Kusha cultivar in optimal irrigation conditions (with an average of 3025.45 kg/ha) had the highest seed yield and the COS16 genotype in drought stress conditions (with an average of 980.89 kg/ha) had the lowest seed yield. Conclusion In general, the use of Epibrassinolide can be suggested as a solution to increase drought stress tolerance and enhance the growth and seed yield of common beans under optimal irrigation and drought stress conditions. In addition, the achievement of comprehensive information on the positive effects of Epibrassinolide requires a study of this hormone in different weather conditions and with other different bean genotypes.

The increased demand for cost-efficient manufacturing and metrology inspection solutions for complex-shaped components in High-Value Manufacturing (HVM) sectors requires increased production throughput and precision. This drives the integration of automated robotic solutions. However, the current manipulators utilizing traditional programming approaches demand specialized robotic programming knowledge and make it challenging to generate complex paths and adapt easily to unique specifications per component, resulting in an inflexible and cumbersome teaching process. Therefore, this body of work proposes a novel software system to realize kinesthetic guidance for path planning in real-time intervals at 250 Hz, utilizing an external off-the-shelf force–torque (FT) sensor. The proposed work is demonstrated on a 500 mm2 near-net-shaped Wire–Arc Additive Manufacturing (WAAM) complex component with embedded defects by teaching the inspection path for defect detection with a standard industrial robotic manipulator in a collaborative fashion and adaptively generating the kinematics resulting in the uniform coupling of ultrasound inspection. The utilized method proves superior in performance and speed, accelerating the programming time using online and offline approaches by an estimate of 88% to 98%. The proposed work is a unique development, retrofitting current industrial manipulators into collaborative entities, securing human job resources, and achieving flexible production.

Inspection of components with surface discontinuities is an area that volumetric Non-Destructive Testing (NDT) methods, such as ultrasonic and radiographic, struggle in detection and characterisation. This coupled with the industrial desire to detect surface-breaking defects of components at the point of manufacture and/or maintenance, to increase design lifetime and further embed sustainability in their business models, is driving the increased adoption of Eddy Current Testing (ECT). Moreover, as businesses move toward Industry 4.0, demand for robotic delivery of NDT has grown. In this work, the authors present the novel implementation and use of a flexible robotic cell to deliver an eddy current array to inspect stress corrosion cracking on a nuclear canister made from 1.4404 stainless steel. Three 180-degree scans at different heights on one side of the canister were performed, and the acquired impedance data were vertically stitched together to show the full extent of the cracking. Axial and transversal datasets, corresponding to the transmit/receive coil configurations of the array elements, were simultaneously acquired at transmission frequencies 250, 300, 400, and 450 kHz and allowed for the generation of several impedance C-scan images. The variation in the lift-off of the eddy current array was innovatively minimised through the use of a force–torque sensor, a padded flexible ECT array and a PI control system. Through the use of bespoke software, the impedance data were logged in real-time (≤7 ms), displayed to the user, saved to a binary file, and flexibly post-processed via phase-rotation and mixing of the impedance data of different frequency and coil configuration channels. Phase rotation alone demonstrated an average increase in Signal to Noise Ratio (SNR) of 4.53 decibels across all datasets acquired, while a selective sum and average mixing technique was shown to increase the SNR by an average of 1.19 decibels. The results show how robotic delivery of eddy current arrays, and innovative post-processing, can allow for repeatable and flexible surface inspection, suitable for the challenges faced in many quality-focused industries.

Automated in-process Non-Destructive Testing (NDT) systems are rapidly gaining traction within the manufacturing industry as they reduce manufacturing time and costs. When considering calibration and verification of such systems, creating defects of known geometry and nature during the deposition of a weld can: (I) help examine the capability of the automated system to detect and characterise defects, (II) be used to form a database of signals associated with different defect types to train intelligent defect classification algorithms, and (III) act as a basis for in-process gain calibration during weld inspection at high temperatures, where the ultrasound beam can be skewed as a result of velocity gradients. In view of this, this paper investigates two unique methodologies for introducing: (a) lack of fusion weld defects by embedding tungsten in the weld and (b) creating artificial weld cracks by quenching to imitate the real cracking scenarios. According to the results of Phased Array Ultrasound Testing (PAUT) inspections, the methodologies used for embedding the artificial defects were successful. The validity of inspections was also verified by extracting micrographs from the defective sections of the welds, and model-based simulations were carried out to gain a better understanding of the wave propagation path and interaction with the generated defects.

In multi-pass welding, there is increasing motivation to move towards in-process defect detection to enable real-time repair; thus avoiding deposition of more layers over a defective weld pass. All defect detection techniques require a consistent and repeatable approach to calibration to ensure that measured defect sizing is accurate. Conventional approaches to calibration employ fixed test blocks with known defect sizes, however, this methodology can lead to incorrect sizing when considering complex geometries, materials with challenging microstructure, and the significant thermal gradients present in materials during the inter-pass inspection period. To circumvent these challenges, the authors present a novel approach to calibration and introduce the concept of in-process calibration applied to ultrasonic Non-Destructive Testing (NDT). The new concept is centred around the manufacturing of a second duplication sample, containing intentionally-embedded tungsten inclusions, with identical process parameters as the main sample. Both samples are then inspected using a high-temperature robotic NDT process to allow direct comparative measurements to be established between the real part and the calibration sample. It is demonstrated that in-process weld defect detection using the in-process calibration technique can more reliably identify defects in samples which would otherwise pass the acceptance test using a traditional calibration.

Automated weld deposition coupled with the real-time robotic Non-Destructive Evaluation (NDE) is used in this paper. For performance verification of the in-process inspection system, an intentionally embedded defect, a tungsten rod, is introduced into the multi-pass weld. A partially-filled groove (staircase) sample is also manufactured and ultrasonically tested to calibrate the real-time inspection implemented on all seven layers of the weld which are deposited progressively. The tungsten rod is successfully detected in the real-time NDE of the deposited position. The same robotic inspection system was then used to continuously monitor an intentionally-manufactured crack for 20 h. The crack was initiated 22 min after the weld ended and it grew quickly within the next 1.5 h. The crack growth stopped approximately after 2 h and no considerable change in the reflection signal was detected for the next 18 h of monitoring.

The demand for cost-efficient manufacturing of complex metal components has driven research for metal Additive Manufacturing (AM) such as Wire + Arc Additive Manufacturing (WAAM). WAAM enables automated, time- and material-efficient manufacturing of metal parts. To strengthen these benefits, the demand for robotically deployed in-process Non-Destructive Evaluation (NDE) has risen, aiming to replace current manually deployed inspection techniques after completion of the part. This work presents a synchronized multi-robot WAAM and NDE cell aiming to achieve (1) defect detection in-process, (2) enable possible in-process repair and (3) prevent costly scrappage or rework of completed defective builds. The deployment of the NDE during a deposition process is achieved through real-time position control of robots based on sensor input. A novel high-temperature capable, dry-coupled phased array ultrasound transducer (PAUT) roller-probe device is used for the NDE inspection. The dry-coupled sensor is tailored for coupling with an as-built high-temperature WAAM surface at an applied force and speed. The demonstration of the novel ultrasound in-process defect detection approach, presented in this paper, was performed on a titanium WAAM straight sample containing an intentionally embedded tungsten tube reflectors with an internal diameter of 1.0 mm. The ultrasound data were acquired after a pre-specified layer, in-process, employing the Full Matrix Capture (FMC) technique for subsequent post-processing using the adaptive Total Focusing Method (TFM) imaging algorithm assisted by a surface reconstruction algorithm based on the Synthetic Aperture Focusing Technique (SAFT). The presented results show a sufficient signal-to-noise ratio. Therefore, a potential for early defect detection is achieved, directly strengthening the benefits of the AM process by enabling a possible in-process repair.

We studied new micro-perforated diffuser concepts for the aeration process in wastewater treatment plants and evaluated their aeration efficiency. These are micro-perforated plate diffusers with orifice diameters of 30 µm, 50 µm and 70 µm and a micro-perforated tube diffuser with an orifice diameter of 50 µm. The oxygen transfer of the diffuser concepts is tested in clean water, and it is compared with commercial aerators from the literature. The micro-perforated tube diffuser and micro-perforated plate diffusers outperform the commercial membrane diffusers by up to 44% and 20%, respectively, with regard to the oxygen transfer efficiency. The most relevant reason for the improved oxygen transfer is the fine bubble aeration with bubble sizes as small as 1.8 mm. Furthermore, the more homogenous cross-sectional bubble distribution of the micro-perforated tube diffuser has a beneficial effect on the gas mass transfer due to less bubble coalescence. However, the pressure drop of micro-perforated diffusers seems to be the limiting factor for their standard aeration efficiencies due to the size and the number of orifices. Nevertheless, this study shows the potential for better aeration efficiency through the studied conceptual micro-perforated diffusers.

The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs.

The present study aims to investigate the impact of thermal energy storage aggregate (TESA) and nano-titanium (NT) on properties of structural concrete. TESA was made of scoria encapsulated with phase change materials (PCMs). Coarse aggregates were replaced by TESA at 100% by volume of aggregate and NT was added at 5% by weight of cement. Compressive strength, probability of corrosion, thermal performance, and microstructure properties were studied. The results indicated that the presence of TESA reduced the compressive strength of concrete, although the strength was still high enough to be used as structural concrete. The use of TESA significantly improved the thermal performance of concrete, and slightly improved the resistance of corrosion in concrete. The thermal test results showed that TESA concrete reduces the peak temperature by 2 °C compared to the control. The addition of NT changed the microstructure of concrete, which resulted in higher compressive strength. Additionally, the use of NT further enhanced the thermal performance of TESA concrete by reducing the probability of corrosion remarkably. These results confirmed the crucial role of NT in improving the permeability and the thermal conductivity of mixtures containing PCM. In other words, the charging and discharging of TESA was enhanced with the presence of NT in the mixture.

BACKGROUND:Drought stress is one of the most important abiotic stresses and the main constraint to rice agriculture. MicroRNA-mediated post-transcriptional gene regulation is one of the ways to establish drought stress tolerance in plants. MiRNAs are 20-24-nt regulatory RNAs that play an important role in regulating plant gene expression upon exposure to biotic and abiotic stresses. METHODOLOGY/PRINCIPAL FINDINGS:In this study, we applied a partial root drying system as well as a complete root drying system to identify miRNAs involved in conditions of drought stress, drought signaling and wet signaling using high-throughput sequencing. To this end, we produced four small RNA libraries: (1) fully-watered (WW), (2) fully-droughted (WD), and split-root systems where (3) one-half was well watered (SpWW) and (4) the other half was water-deprived (SpWD). Our analysis revealed 10,671 and 783 unique known and novel miRNA reads in all libraries, respectively. We identified, 65 (52 known + 13 novel), 72 (61 known + 11 novel) and 51 (38 known + 13 novel) miRNAs that showed differential expression under conditions of drought stress, drought signaling and wet signaling, respectively. The results of quantitative real-time PCR showed expression patterns similar to the high-throughput sequencing results. Furthermore, our target prediction led to the identification of 244, 341 and 239 unique target genes for drought-stress-, drought-signaling- and wet-signaling-responsive miRNAs, respectively. CONCLUSIONS/SIGNIFICANCE:Our results suggest that miRNAs that are responsive under different conditions could play different roles in the regulation of abscisic acid signaling, calcium signaling, detoxification and lateral root formation.

Concrete shrinkage and volume reduction happens due to the loss of moisture, which eventually results in cracks and more concrete deformation. In this study, the effect of polypropylene (PP), steel, glass, basalt, and polyolefin fibers on compressive and flexural strength, drying shrinkage, and cracking potential, using the ring test at early ages of high-strength concrete mixtures, was investigated. The restrained shrinkage test was performed on concrete ring specimens according to the ASTM C1581 standard. The crack width and age of restrained shrinkage cracking were the main parameters studied in this research. The results indicated that the addition of fiber increases the compressive strength by 16%, 20%, and 3% at the age of 3, 7, and 28 days, respectively, and increases the flexural toughness index up to 7.7 times. Steel and glass fibers had a better performance in flexural strength, but relatively poor action in the velocity reduction and cracking time of the restrained shrinkage. Additionally, cracks in all concrete ring specimens except for the polypropylene-containing mixture, was developed to a full depth crack. The mixture with polypropylene fiber indicated a reduction in crack width up to 62% and an increasing age cracking up to 84%.

Witches' broom disease of Mexican lime (Citrus aurantifolia L.), which is associated to the phytoplasma 'Candidatus Phytoplasma aurantifolia', is a devastating disease that results in significant economic losses. Plants adapt to biotic stresses by regulating gene expression at the transcriptional and post-transcriptional levels. MicroRNAs (miRNAs) are a recently identified family of molecules that regulate plant responses to environmental stresses through post-transcriptional gene silencing.Using a high-throughput approach to sequence small RNAs, we compared the expression profiles of miRNAs in healthy Mexican lime trees and in plants infected with 'Ca. P. aurantifolia'.Our results demonstrated the involvement of different miRNAs in the response of Mexican lime trees to infection by 'Ca. P. aurantifolia'. We identified miRNA families that are expressed differentially upon infection with phytoplasmas. Most of the miRNAs had variants with small sequence variations (isomiRs), which are expressed differentially in response to pathogen infection.It is likely that the miRNAs that are expressed differentially in healthy and phytoplasma-infected Mexican lime trees are involved in coordinating the regulation of hormonal, nutritional, and stress signalling pathways, and the complex interactions between them. Future research to elucidate the roles of these miRNAs should improve our understanding of the level of diversity of specific plant responses to phytoplasmas.

Background: Lentil (Lens culinaris Medik) is a cool season seed legume and a good source of nutrients needed by humans, including protein, carbohydrates, vitamins, and minerals. The production of high-yielding and high-plant-height varieties is one of the lentil improvement goals. For this purpose, it is necessary to collect and evaluate germplasm as a base population, along with identifying and utilizing lines with high potential and other desirable traits. The environment has a significant effect on the crop production of this plant. Therefore, direct selection is important for seed yield. Since seed yield depends on the yield components, the yield and its components must be regarded as a group at the selection time to improve the yield. To properly increase yield and economic efficiency, we need to collect desirable lines with desirable genes and transfer these genes to cultivated lines to produce desirable cultivars. Consequently, sufficient information is necessary on accessible genetic materials, which is possible by evaluating different traits. Methods: To assess the model of the simultaneous effect of traits on the lentil seed yield for determining the selection procedure in native lentil lines of Zanjan province, an experiment was conducted in the research farm of the Faculty of Agriculture, Zanjan University, during two cropping years 2017-2018 and 2018-2019. In both years of the experiment, improved cultivars, such as Kimia, Sabz Kohin, Gachsaran, Maragheh, and Bilehsavar, were used as control cultivars. The first-year experiment was conducted in an augmented design based on a randomized complete block design with 200 lines. Each experimental unit included a 1-m row. The distance between the rows was 25 cm, the distance between plants in a row was 5 cm, and the planting depth was 5 cm. Two rows of Kohin-Sabz lentils were planted as margins at the beginning and end of each block. Due to obtaining a sufficient amount of seeds from the first year, the second-year experiment was carried out as a simple lattice design with two replications and larger experimental units for the lines selected from the first year. Each experimental unit included two 1-m lines. The distance between the rows, the distance between plants in a row, and the planting depth were similar to the first-year experiment. Two rows of Kuhin green lentils were planted as margins at the beginning and end of each incomplete block. The measured traits included phenological and morphological traits, yield, and yield components per plant and unit area. Results: Among the studied traits, the highest coefficient of variation was obtained for the number of seeds, biomass, straw yield, and seed yield. The coefficient of correlation showed that the number of seeds and seed yield were positively and significantly correlated with phenological traits, such as the podding period, physiological maturity, and seed-filing period, as well as morphological traits such as plant height and first branching height, respectively. A positive and significant correlation was observed between the number of seeds and seed yield with the number of pods per plant and biomass per plant. In regression analysis by the stepwise method, plant height was the first trait entered into the model, which could explain 46.8% of the variation related to seed yield per plant. Then, the number of seeds per plant, 1000-seed weight (TSW), straw yield per plant, and the seed-filling period were entered into the model, respectively, which could totally explain 67.5% of the variation related to seed yield per plant. The results of the path analysis showed that the number of seeds per plant had the most considerable direct and positive effect on seed yield, followed by the direct effect of the TSW, plant height, and seed-filling period, respectively. Therefore, these traits would be recommended as the most important and significant traits in the indirect selection of seed yield in lentils. Most of the indirect effects of the traits on seed yield were positive, and the most indirect effects were related to seed-filling period, plant height, and straw yield through the number of seeds per plant. Besides, the seedfilling period through plant height and the plant height through the number of seeds had an indirect effect on seed yield. In factor analysis based on principal component analysis and varimax rotation, six factors explained about 76% of the data variation. The first three factors included the most considerable volume of data variation. The first factor was identified as phenology and height, and the second and third factors were identified as yield and yield components. Results showed that the selection based on these factors would lead to the genesis of the high-yield lines. Conclusion: The highest coefficient of variation belonged to these traits: the number of seeds, biomass, straw yield, and seed yield. Seed yield per plant had a positive and significant correlation with the phenological traits of the podding period, seed-filling period, and physiological maturity, as well as morphological traits, namely plant height and the height of the first branch. The number of seeds per plant had the most direct effect on seed yield, followed by TSW, plant height, and seed-filling period. Therefore, these traits can be considered the criteria for selecting superior lines. According to the factor analysis results, six factors could justify 77.306% of the data variations. [ABSTRACT FROM AUTHOR]

The glycoside hydrolase family contains enzymes that break the glycosidic bonds of carbohydrates by hydrolysis. Inulinase is one of the most important industrial enzymes in the family of Glycoside Hydrolases 32 (GH32). In this study, to identify and classify bacterial inulinases initially, 16,002 protein sequences belonging to the GH32 family were obtained using various databases. The inulin‐effective enzymes (endoinulinase and exoinulinase) were identified. Eight endoinulinases (EC 3.2.1.7) and 4318 exoinulinases (EC 3.2.1.80) were found. Then, the localization of endoinulinase and exoinulinase enzymes in the cell was predicted. Among them, two extracellular endoinulinases and 1232 extracellular exoinulinases were found. The biochemical properties of 363 enzymes of the genus Arthrobacter, Bacillus, and Streptomyces (most abundant) showed that exoinulinases have an acid isoelectric point up to the neutral range due to their amino acid length. That is, the smaller the protein (336 aa), the more acidic the pI (4.39), and the larger the protein (1207 aa), the pI is in the neutral range (8.84). Also, a negative gravitational index indicates the hydrophilicity of exoinulinases. Finally, considering the biochemical properties affecting protein stability and post‐translational changes studies, one enzyme for endoinulinase and 40 enzymes with desirable characteristics were selected to identify their enzyme production sources. To screen and isolate enzyme‐containing strains, now with the expansion of databases and the development of bioinformatics tools, it is possible to classify, review and analyze a lot of data related to different enzyme‐producing strains. Although, in laboratory studies, a maximum of 20 to 30 strains can be examined. Therefore, when more strains are examined, finally, strains with more stable and efficient enzymes were selected and introduced for laboratory activities. The findings of this study can help researchers to select the appropriate gene source from introduced strains for cloning and expression heterologous inulinase, or to extract native inulinase from introduced strains. [ABSTRACT FROM AUTHOR]