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Abstract The distinctive characteristics of nanoparticles and their potential applications have been given considerable attention by scientists across different fields, particularly agriculture. However, there has been limited effort to assess the impact of copper nanoparticles (CuNPs) in modulating physiological and biochemical processes in response to salt-induced stress. This study aimed to synthesize CuNPs biologically using Solenostemma argel extract and determine their effects on morphophysiological parameters and antioxidant defense system of barley (Hordeum vulgare) under salt stress. The biosynthesized CuNPs were characterized by (UV–vis spectroscopy with Surface Plasmon Resonance at 320 nm, the crystalline nature of the formed NPs was verified via XRD, the FTIR recorded the presence of the functional groups, while TEM was confirmed the shape (spherical) and the sizes (9 to 18 nm) of biosynthesized CuNPs. Seeds of barley plants were grown in plastic pots and exposed to different levels of salt (0, 100 and 200 mM NaCl). Our findings revealed that the supplementation of CuNPs (0, 25 and 50 mg/L) to salinized barley significantly mitigate the negative impacts of salt stress and enhanced the plant growth-related parameters. High salinity level enhanced the oxidative damage by raising the concentrations of osmolytes (soluble protein, soluble sugar, and proline), malondialdehyde (MDA) and hydrogen peroxide (H2O2). In addition, increasing the activities of enzymatic antioxidants, total phenol, and flavonoids. Interestingly, exposing CuNPs on salt-stressed plants enhanced the plant-growth characteristics, photosynthetic pigments, and gas exchange parameters. Furthermore, CuNPs counteracted oxidative damage by lowering the accumulation of osmolytes, H2O2, MDA, total phenol, and flavonoids, while simultaneously enhancing the activities of antioxidant enzymes. In conclusion, the application of biosynthesized CuNPs presents a promising approach and sustainable strategy to enhance plant resistance to salinity stress, surpassing conventional methods in terms of environmental balance.

Workable, environmentally friendly, sustainable sand concrete was reviewed to replace river sand for concrete production. The river ecology and the biological balance will be preserved with the help of the carefully chosen sustainable sand. A systematic literature review (SLR) methodology was employed to extract the data. The study examined the strength and durability characteristics of recycled and desert sand concrete from past published studies.Experimental results from published investigations indicate that the strength of concrete prepared with 30 % sustainable sand is the best result compared to concrete with 100 % river sand. There was an acceptable decrease in strength and durability at 50 % replacement, and a significant reduction was reported at 100 %. Compared to river sand, recycled and desert sand concrete was less durable. In addition, based on the example used in this study, at 50 % replacement of river sand with sustainable sand, approximately 735 × 106 tons of river sand was preserved. Finally, it concludes that using recycled and desert sand to make sustainable sand concrete would be economical and beneficial for the environment.

Video forgery detection is a critical aspect of digital forensics, addressing the challenges posed by the manipulation of video content. This paper presents a novel approach for video forgery detection using Deep Convolutional Neural Networks (DCNN). Leveraging the power of deep learning, our method aims to improve the accuracy and efficiency of object-based forgery detection in advanced video sequences. In the proposed approach, we build upon the foundation of an existing method, which utilizes Convolutional Neural Networks, and introduce innovative modifications to the DCNN architecture. These modifications include data preprocessing, network architecture, and training strategies that enhance the model’s ability to detect tampered objects in video frames. We conduct experiments on the SYSU-OBJFORG dataset, the largest object-based forged video dataset to date, with advanced video encoding standards. Our DCNN-based approach is compared with the existing method, demonstrating superior performance. The results show increased accuracy and robustness in detecting object-based video forgery. This paper not only contributes to the field of video forgery detection but also underscores the potential of deep learning, particularly DCNN, in addressing the evolving challenges of digital video manipulation. The findings open avenues for future research in the localization of forged regions and the application of DCNN in lower bitrate or lower resolution video sequences.

The adoption of cloud computing has become increasingly widespread across various domains. However, the inherent security vulnerabilities of cloud computing pose significant risks to its overall safety. Consequently, intrusion detection systems (IDS) play a pivotal role in identifying malicious activities within a cloud system. The considerable volume of network traffic data may contain redundant and irrelevant features that can impact the classification performance of the classifier. In addition, the complexity and time consumption increase while processing such a substantial volume of data in the cloud intrusion detection process. To enhance the performance of the IDS, this study proposes a hybrid feature selection approach, combining two bio-inspired algorithms, namely the grasshopper optimization algorithm (GOA) and the genetic algorithm (GA). The combination of these two algorithms ensures a more efficient search for optimal solutions. A random forest (RF) classifier is trained using those optimal features. Moreover, the proposal addresses the challenge of imbalanced data by employing a hybrid approach: over-sampling the minority classes using an adaptive synthetic (ADASYN) algorithm, while implementing random under-sampling (RUS) for the majority class as needed. This integrated strategy significantly influences each category, enhancing the true positive rate (TPR) while minimizing the false positive rate (FPR), thus improving the overall system performance. The proposed approach was evaluated using three datasets: UNSW-NB15, CIC-DDoS2019, and CIC Bell DNS EXF 2021. The recorded accuracies for these datasets were 98%, 99%, and 92%, respectively. The hybrid feature selection-based IDS demonstrated superior performance in multi-class classification, along with exemplary results for individual classes within the datasets. The proposed strategy exhibited a marked superiority with the random forest classifier, especially when compared to other classifiers including SVM, LR, FLN, LSTM, AlexNet, DNN, DBN, DT, and XGBoost. Moreover, this performance remained consistent and commendable even when benchmarked against contemporary state-of-the-art methodologies across multiple evaluation metrics.

In this research, sustainable sand was developed using desert sand with recycled fine aggregate. Developing sustainable sand can solve environmental issues caused by excessive river sand mining. For this purpose, four types of sustainable sand have been developed. The present study has developed a method to optimize desert sand by incorporating recycled crushed sand from demolished concrete. The developed sand properties were well within the ASTM and British standards recommendations. A chemical analysis of SEM-EDS and FTIR was also performed on the developed sand. The 50 % addition of desert sand separately with 50 % recycled crushed sand is effected to reach the fineness modulus well within the specified range (2.4–3.0) set by the standard code. Four concrete mixes were prepared with developed sand using the absolute volume method. The compressive strength increment was evaluated at 3, 7, 28, 56, 91, and 360 days of curing. The developed sand mixes with fineness modulus values 2.6, 2.7, and 2.8 successfully pass criteria 1 and 2 set for this study at 28 days of curing. The prepared mix with the lowest fineness modulus value of 2.4 successfully achieved criterion 1 and failed to reach criterion 2. It shows that the fineness modulus value significantly influences the concrete strength. The flexural strength of all mixes surpassed the standard requirement. The study concluded that desert sand is a useful fine aggregate with recycled crushed sand when utilized at the optimum value. Hence, the developed sustainable sand can replace river sand in concrete production.

Nanoparticles may serve as novel plant growth stimulators to improve plant growth as well as protect plants from abiotic stresses. In this study, biogenic silver nanoparticles (AgNPs) were synthesized using the aqueous extract of Fagonia bruguieri and characterized using UV-visible spectroscopy, Zeta potential, transmission electron microscopy (TEM) and Fourier Transform Infrared Spectroscopy (FTIR). The synthesized AgNPs were employed on Echinops macrochaetus as seeds priming, and plants grown in pots were exposed to salinity stress to assess the ameliorating effects based on various parameters. The growth parameters (shoot length) and biomass (shoot, root and leaves weight) decreased in E. macrochaetus exposed to salinity stress alone (40, 80 and 120 mmol/L NaCl) for 90 days. However, seed priming with a low concentration of AgNPs (40 µmol/L) improved the growth of the plant in terms of biomass, shoot length and chlorophyll content alone as well as ameliorated the toxic effect caused by salinity stress. The mitotic index measured by flowcytometry (FCM) indicated genotoxic effects in plants grown at high concentrations of NaCl (80 and 120 mmol/L) as well as plants obtained with 80 µmol/L AgNPs seed priming and exposed to 120 mmol/L NaCl. Thus, an optimum concentration of AgNPs could be used in E. macrochaetus for production of more biomass by modulating the chlorophyll content, proline and antioxidant enzyme activity.

BackgroundLarge language models (LLMs) have revolutionized natural language processing with their ability to generate human-like text through extensive training on large data sets. These models, including Generative Pre-trained Transformers (GPT)-3.5 (OpenAI), GPT-4 (OpenAI), and Bard (Google LLC), find applications beyond natural language processing, attracting interest from academia and industry. Students are actively leveraging LLMs to enhance learning experiences and prepare for high-stakes exams, such as the National Eligibility cum Entrance Test (NEET) in India. ObjectiveThis comparative analysis aims to evaluate the performance of GPT-3.5, GPT-4, and Bard in answering NEET-2023 questions. MethodsIn this paper, we evaluated the performance of the 3 mainstream LLMs, namely GPT-3.5, GPT-4, and Google Bard, in answering questions related to the NEET-2023 exam. The questions of the NEET were provided to these artificial intelligence models, and the responses were recorded and compared against the correct answers from the official answer key. Consensus was used to evaluate the performance of all 3 models. ResultsIt was evident that GPT-4 passed the entrance test with flying colors (300/700, 42.9%), showcasing exceptional performance. On the other hand, GPT-3.5 managed to meet the qualifying criteria, but with a substantially lower score (145/700, 20.7%). However, Bard (115/700, 16.4%) failed to meet the qualifying criteria and did not pass the test. GPT-4 demonstrated consistent superiority over Bard and GPT-3.5 in all 3 subjects. Specifically, GPT-4 achieved accuracy rates of 73% (29/40) in physics, 44% (16/36) in chemistry, and 51% (50/99) in biology. Conversely, GPT-3.5 attained an accuracy rate of 45% (18/40) in physics, 33% (13/26) in chemistry, and 34% (34/99) in biology. The accuracy consensus metric showed that the matching responses between GPT-4 and Bard, as well as GPT-4 and GPT-3.5, had higher incidences of being correct, at 0.56 and 0.57, respectively, compared to the matching responses between Bard and GPT-3.5, which stood at 0.42. When all 3 models were considered together, their matching responses reached the highest accuracy consensus of 0.59. ConclusionsThe study’s findings provide valuable insights into the performance of GPT-3.5, GPT-4, and Bard in answering NEET-2023 questions. GPT-4 emerged as the most accurate model, highlighting its potential for educational applications. Cross-checking responses across models may result in confusion as the compared models (as duos or a trio) tend to agree on only a little over half of the correct responses. Using GPT-4 as one of the compared models will result in higher accuracy consensus. The results underscore the suitability of LLMs for high-stakes exams and their positive impact on education. Additionally, the study establishes a benchmark for evaluating and enhancing LLMs’ performance in educational tasks, promoting responsible and informed use of these models in diverse learning environments.

The present study aims to develop 4 types of sustainable modified sand using various proportions of desert sand, natural crushed sand, and recycled crushed sand. The physicochemical characteristics of modified sand have been evaluated. Newly developed modified sand was used to prepare 4 concrete mixes. Further, ordinary Portland cement (OPC) was partially replaced by silica fume (SF), and 4 mixes were made using 12.5% of SF. Experimental results show that all 8 mixes fulfilled the requirements of the ACI 318-08 code. The compressive strength significantly increased with the SF combination at later ages beyond 28 days. It can be concluded that the proposed sustainable modified sand successfully replaced the river sand in concrete manufacturing. Furthermore, 12.5% OPC replacement with SF helps to enhance the concrete strength and reduce the carbon footprint. Detail study must be carried out for the durability of the same design mix concrete.

Effective cooling solutions become increasingly crucial as micro-electrical devices advance in complexity and miniaturization. Microchannel heat sinks (MCHSs) are one of the solutions, and researchers are continuously exploring innovative designs and optimization techniques to ensure that these cooling solutions meet the evolving demands of modern electronics. In the current research, a novel disk-shaped MCHS with strategically positioned baffles was selected to be investigated. Total thermal resistance (Rt) and pressure drop (ΔP) were scrutinized to assess the role of the baffle’s structural parameters (length of baffles in the first row (L), with the values of 500 μm–1500 μm, space between the baffles (S), with the values of 1700 μm–2500 μm, and angle of baffles (θ), with the values of 45°–90°). Firstly, various combinations of structural parameters of the baffles were selected as study designs, and each was numerically simulated. Artificial neural network (ANN) models and a genetic algorithm were employed to predict the data and identify the optimal designs. Based on the obtained results, higher R2 values (0.9940 for Rt Model and 0.9996 for ΔP model) indicated the accurate performance of both ANN models. Two optimal designs of optimal thermal performance (OTP) and optimal hydraulic performance (OHP) with separate objectives of minimizing Rt and minimizing ΔP were recommended. The utilization of baffles with the dimensions of L = 1500 μm, S = 2500 μm, and θ = 90° in the disk-shaped MCHS led to the attainment of the OTP. While to acquire the OHP, it was necessary to use the baffles with dimensions of L = 500 μm, S = 1700 μm, and θ = 81.8325°. In the OTP design, Rt was reduced by about 49.47 %, while in the OHP design, it decreased by approximately 30.36 % compared to the reference design.

Shared mobility services furnish convenient transportation alternatives for individuals without vehicle ownership or a preference against driving. Shared mobility could benefit developing countries by providing a cost-effective alternative, enhancing accessibility, reducing congestion, and creating multiple job opportunities. In this study, a comprehensive analysis to assess shared mobility options as an avenue to sustainable transportation in Amman, Jordan, is presented. The study employs a multifaceted methodology, including a survey questionnaire, preliminary analysis, Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis, and Structural Equation Model (SEM). The data were collected from a diverse group of Amman residents using a survey composed of 29 questions. The survey included demographic information, travel behavior, willingness to adopt shared mobility, perceived benefits, and possible barriers. These data were analyzed using Structural Equation Modeling (SEM), providing an in-depth understanding of the interrelationships among the variables studied. This study concludes by contributing to the ongoing discussion on sustainable urban transportation in Jordan and providing a road map for policymakers, urban planners, and transportation service providers. The presented findings provide an empirical basis for guiding future strategies and interventions toward sustainable urban development in Amman and potentially other urban contexts with comparable characteristics. Key findings reveal a significant potential for shared mobility to enhance urban transportation sustainability. Specifically, a notable positive perception among Amman residents was observed, with an average willingness to switch to shared mobility for daily commuting scoring 4.68 on a 7-point Likert scale. Moreover, a statistical analysis indicates that factors such as reduced costs, improved service reliability, and better environmental sustainability, notably influence the adoption of shared mobility services.

Waste management is a complex research domain. While the domain is challenging in terms of content, it is also a diverse and cross-disciplinary research subject. One of its important components includes efficient decision-making at various levels and stages. Therefore, Multi-criteria decision-making (MCDM) techniques have found decent applications in this domain. The field of MCDM techniques-based waste management has been examined using bibliometric analysis in this paper in order to report a systematic overview of the trends and advancements in this area of study. The Scopus database provided 216 publications on the aforementioned subject written between 1992 and 2022. The 216 articles include 56 countries, 158 institutions, and 160 authors. Furthermore, Asian countries, including India, Iran, and China, dominate this field of study. The geographical disparity in the output of publications is visible. Journal of cleaner production, Waste Management and Waste Management and Research are the major journals publishing on MCDM techniques-based waste management research. Given that majority of the articles include multiple authors, it can be said that there is a lot of collaborative research in this area. Overall, the current study provides a thorough analysis of the development in the domain of waste management using MCDM techniques. The trend suggests that it will continue to be a focus of research for academicians, environmentalists and policymakers in the future.

Objective: To evaluate coagulation abnormalities and their relationship with bleeding manifestations among patients with dengue. Methods: This observational study was conducted on 292 adult dengue patients who were admitted to a tertiary care hospital of Western India from July 2021 to June 2022. Coagulation tests including prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (aPTT), fibrinogen, and D-dimer were performed. Patients were monitored for bleeding manifestations. Results: Coagulation abnormalities were reported in 42.8% of the patients. Overall, prolonged aPTT was the most common coagulation abnormality (40.8%), followed by low fibrinogen (38.7%), raised D-dimer (31.2%), raised INR (26.0%) and prolonged PT (19.2%). Bleeding manifestations were present in 19.9% patients. PT, INR, aPTT and D-dimer levels were significantly higher (P

Cognitive Radio Ad-hoc Networks (CRAHNs) combines characteristics of ad-hoc networks with cognitive radios to facilitate a variety of communication scenarios. However, these networks are subject to persistent attacks from internal and external adversaries, such as Masquerading, Spoofing, Spying, and Distributed Denial of Service (DDoS). Existing deep learning models proposed to counter these attacks suffer from complexity, real-time processing limitations, and a lack of network scalability. In addition, their limited IP tracing capabilities make them unsuitable for real-time deployments. To address these issues, this paper proposes a novel blockchain-based model for deep traffic pattern analysis and mitigation of malicious attacks in CRAHNs. The proposed model employs a multi-step methodology. The collected traffic patterns are then used to train a deep Convolutional Neural Network (dCNN) model. This trained model permits the temporal classification of incoming real-time traffic packets. The packets are stored on a distributed network based on blockchain technology to ensure data integrity, transparency, and traceability. This blockchain implementation renders the packets immutable and easily accessible, while also facilitating the recommendation of improved mitigation strategies. The blockchain employs a Proof-of-Trust (PoT) consensus mechanism and is managed via a Genetic Algorithm (GA)-based sidechaining model, which significantly reduces access and writing delays for various packets. The proposed model achieves a significant reduction in communication delay in comparison to existing models, with decreases of 35.4%, 19.5%, and 23.5% for BIDS, BIST WM, and GAN, respectively. Additionally, energy consumption is reduced by 18.5%, 18.3%, and 24.5%, respectively. In addition, the model exhibits an increase in throughput of 14.5%, 16.4%, and 15.5%, respectively. Lastly, it improves the accuracy of attack detection during various communications by 8.3%, 23.2%, and 8.3%, respectively. This paper presents a promising solution for enhancing the security of CRAHNs by providing a robust defense against malicious attacks and real-time protection for dynamic ad hoc networks. The integration of deep learning, blockchain technology, and optimization techniques results in significant improvements in performance metrics, demonstrating the potential of the proposed model for ensuring the security and integrity of CRAHNs.

Chat Generative Pre-trained Transformer (ChatGPT) has gained significant interest and attention since its launch in November 2022. It has shown impressive performance in various domains, including passing exams and creative writing. However, challenges and concerns related to biases and trust persist. In this work, we present a comprehensive review of over 100 Scopus-indexed publications on ChatGPT, aiming to provide a taxonomy of ChatGPT research and explore its applications. We critically analyze the existing literature, identifying common approaches employed in the studies. Additionally, we investigate diverse application areas where ChatGPT has found utility, such as healthcare, marketing and financial services, software engineering, academic and scientific writing, research and education, environmental science, and natural language processing. Through examining these applications, we gain valuable insights into the potential of ChatGPT in addressing real-world challenges. We also discuss crucial issues related to ChatGPT, including biases and trustworthiness, emphasizing the need for further research and development in these areas. Furthermore, we identify potential future directions for ChatGPT research, proposing solutions to current challenges and speculating on expected advancements. By fully leveraging the capabilities of ChatGPT, we can unlock its potential across various domains, leading to advancements in conversational AI and transformative impacts in society.

In this study, we explore the dyeing properties of the extract of sappan wood natural dye for coloration of wool yarn to find the potential use of natural dyed wool yarn in the development of eco-friendly textiles. Different characterizations were used to know the chemistry of sappan wood dye and its interaction with metal salts and wool. Interestingly, we found that metal salts, which are called as mordants in reference to unmordanted dyed sample, play an important role in fixing the dye molecule on wool as well as in creating different shades with a variety of hues and tones. The typical color of fabric dyed with extracts of sappan wood without mordant varies from yellowish to red. Light yellowish shades were obtained in case of aluminum sulfate-mordanted samples, whereas yellowish shades were obtained in case of ferrous sulfate mordant. Light colorfastness of the premordanted dyed samples was relatively better than that of the unmordanted dyed samples. The wash fastness of all samples mordanted as well as unmordanted shows color change fairly good to good level, whereas the color staining on wool and cotton was found to be negligible.

This review article has attempted to address the problems associated with river sand mining and the adverse impacts of CO2 emissions from the construction sector. The PRISMA framework employed a systematic literature review (SLR) methodology for the data extraction. The various strength parameters, such as relative compressive strength, relative splitting tensile strength, and relative flexural strength of concrete made from recycled aggregates (RAs) and silica fume (SF), were examined. The experimental results from various past studies have shown that 30% of RAs achieve a similar strength compared to concrete made by natural aggregates (NAs). At 50%, the compressive strength was merely reduced, and at 100%, a significant reduction in strength was seen. The positive variation in the strength was seen when SF incorporated from 5 to 20%. However, the best outcome in compressive strength was reported at a 10% ordinary Portland cement (OPC) replacement. The durability of concrete made by RAs was slightly lower, and SF-based concrete was higher than regular concrete. The sample calculations for China from (2011 to 2013) showed that by replacing 10% of OPC with SF, 3.96 × 107 tons of CO2 emission could be reduced, and by replacing 50% of river sand with recycled fine aggregate (RFA), 7.35 × 108 tons of river sand can be saved annually. It can be concluded from this review study that the combination of RFA and SF waste would be environmentally friendly in association with more sustainable concrete.

Hearing-impaired people use sign language to express their thoughts and emotions and reinforce information delivered in daily conversations. Though they make a significant percentage of any population, the majority of people can’t interact with them due to limited or no knowledge of sign languages. Sign language recognition aims to detect the significant motions of the human body, especially hands, analyze them and understand them. Such systems may become life-saving when hearing-challenged people are in desperate situations like heart attacks, accidents, etc. In the present study, deep learning-based hand gesture recognition models are developed to accurately predict the emergency signs of Indian Sign Language (ISL). The dataset used contains the videos for eight different emergency situations. Several frames were extracted from the videos and are fed to three different models. Two models are designed for classification, while one is an object detection model, applied after annotating the frames. The first model consists of a three-dimensional convolutional neural network (3D CNN), while the second comprises of a pre-trained VGG-16 and a recurrent neural network with a long short-term memory (RNN-LSTM) scheme. The last model is based on YOLO (You Only Look Once) v5, an advanced object detection algorithm. The prediction accuracies of the classification models were 82% and 98%, respectively. YOLO based model outperformed the rest and achieved an impressive mean average precision of 99.6%.

The implementation of nanotechnology in the field of plant tissue culture has demonstrated an interesting impact on in vitro plant growth and development. Furthermore, the plant tissue culture accompanying nanoparticles has been showed to be a reliable alternative for the biosynthesis of secondary metabolites. Herein, the effectiveness of zinc oxide nanoparticles (ZnONPs) on the growth of Delonix elata calli, as well as their phytochemical profiles, were investigated. Delonix elata seeds were collected and germinated, and then the plant species was determined based on the PCR product sequence of ITS1 and ITS4 primers. Afterward, the calli derived from Delonix elata seedlings were subjected to 0, 10, 20, 30, 40, and 50 mg/L of ZnONPs. The ZnONPs were biologically synthesized using the Ricinus communis aqueous leaf extract, which acts as a capping and reducing agent, and zinc nitrate solution. The nanostructures of the biogenic ZnONPs were confirmed using different techniques like UV–visible spectroscopy (UV), zeta potential measurement, Fourier transform infrared spectra (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM). Adding 30 mg/L of ZnONPs to the MS media (containing 2.5 µM 2,4-D and 1 µM BAP) resulted in the highest callus fresh weight (5.65 g) compared to the control and other ZnONP treatments. Similarly, more phenolic accumulation (358.85 µg/g DW) and flavonoid (112.88 µg/g DW) contents were achieved at 30 mg/L. Furthermore, the high-performance liquid chromatography (HPLC) analysis showed significant increments in gallic acid, quercetin, hesperidin, and rutin in all treated ZnONP calli compared to the control. On the other hand, the gas chromatography and mass spectroscopy (GC-MS) analysis of the calli extracts revealed that nine phytochemical compounds were common among all extracts. Moreover, the most predominant compound found in calli treated with 20, 30, 40, and 50 mg/L of ZnONPs was bis(2-ethylhexyl) phthalate, with percentage areas of 27.33, 38.68, 22.66, and 17.98%, respectively. The predominant compounds in the control and in calli treated with 10 mg/L of ZnONPs were octadecanoic acid, 2-propenyl ester and heptanoic acid. In conclusion, in this study, green ZnONPs exerted beneficial effects on Delonix elata calli and improved their production of bioactive compounds, especially at a dose of 30 mg/L.

In this work optimization of the parabolic trough (PT) based concentrated solar power (CSP) system is analyzed for solar energy export from Saudi Arabia to European and Asian countries based on their peak load hours. Initially, Al-Ahsa, in east, and Tabuk, in the west, are compared for a PT based CSP plant for electrical energy generation as these locations are used to export solar energy from Saudi Arabia to Pakistan, India, and China in east and Greece, Germany and UK in the west. The analysis is performed to sell electrical energy generated by the CSP plant to the customers in their peak load hours to reduce their load factor and keep the capital cost minimum. A high voltage direct current (HVDC) transmission system is employed for this study as an undersea cable for Asian or European countries. The feasibility of 2 GW solar energy export by PT based CSP system transmitted by 2 GW bipolar 660 kV HVDC transmission line is based on the net present value of the project (NPV), real levelized cost of energy (LCOE), and the payback period of the project where Karachi, Pakistan has the highest NPV of 1866 MUSD with LCOE of 10.76 cents/kWh and a payback period of 12.7 years.

Abstract Biosynthesized nanoparticles have played vital role recently, as suggested to be alternative to physical and chemical methods. In this study, biosynthesis of zinc oxide nanoparticles (ZnO NPs) were carried out using leaf extracts of Phoenix dactylifera L. and Zinc nitrate. The effect of ZnO nanoparticles on biomass and biochemical parameters was investigated. Biosynthesized ZnO nanostructure was characterized using X-ray diffraction (XRD), transmission electron microscopy (TEM), UV–visible spectrophotometer and Fourier transform infrared spectroscopy (FTIR). Which resulted in spherical shape with size ranging between 16 to 35 nm of Biosynthesized ZnO nanoparticles and UV absorption beak at 370.5 nm with clear peaks of functional groups. The impact of different concentrations (0.0 mg/L, 80 mg/L and 160 mg/L) of biosynthesized ZnO nanoparticles on biomass and bioactive compounds production of Juniperus procera in vitro was investigated. The results showed that, biosynthesized ZnO NPs (80 mg/L and 160 mg/L) concentrations were boosted the growth of J. Procera with significantly compared to non-treated plants in vitro. The highest concentration (160 mg/L) of ZnO NPs was enhanced the growth of plant at beginning period, one month later shoots became yellow and callus turned to be brownish. Moreover, the influence of ZnO NPs on phytochemical compounds in callus of Juniperus procera was examined using GC–MS analysis. The differences among treatments were recoded. Overall, zinc oxide nanoparticles substantially improved the growth of shoots and callus with increasing of biochemical parameters such as chlorophyll a, total phenolic and flavonoids contents, besides the total protein and, SOD, CAT and APX activity. ZnO NPs might be induced some phytochemical compounds as well as inhibit.

Bioactive compounds of medicinal plants present as natural ingredients provide health benefits beyond the basic nutritional value of these products. However, the availability of bioactive compounds in the current natural sources is limited. Hence, the induction of bioactive compound production from medicinal plants through nanoparticles (NPs) might play a vital role in industrially important medicinal compounds. Therefore, this study aimed to synthesize silver nanoparticles (AgNPs) biologically and to investigate their effect on phytochemical compound production from the callus of Juniperus procera. AgNPs were synthesized biologically using aqueous leaf extract of Phoenix dactylifera, which acted as a reducing and capping agent, and silver nitrate solution. The formation of AgNPs has been confirmed through different analytical techniques such as UV-Visible spectroscopy (UV), Fourier-transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), and scanning electron microscope (SEM). The impact of different concentrations (0.0, 5, 20, and 50 mg/L) of AgNPs on enzymatic and non-enzymatic antioxidants of the callus of J. procera was investigated. The obtained results showed a significant effect of AgNPs on biomass accumulation and non-enzymatic antioxidants (phenol, tannin, and flavonoid content). Additionally, total protein content and superoxide dismutase (SOD) activity were increased in response to AgNPs. Furthermore, bioactive compounds like gallic acid, tannic acid, coumarin, hesperidin, rutin, quercetin, and ferruginol were chromatographically separated and quantified using high-performance liquid chromatography (HPLC) with reference standards. These compounds were increased significantly in response to AgNPs treatments. We concluded that AgNPs could be a promising elicitor for improving the production of phytochemical compounds in medicinal plants. This work can serve asa good model for improving the production of bioactive compounds from medicinal plants in vitro. This molecular investigation should be done to understand better the metabolic mechanism leading to bioactive compound production scaling.

Among biological methods, green synthesis of the nanomaterials using plant extracts was shown to be an environmentally friendly, economical, and simple approach. In the current study, the biogenic synthesis of silver nanoparticles (AgNPs) was achieved using the leaf extract of Hibiscus tiliaceus, in order to prevent the contamination of the tissue culture media and induce callus growth. The nanostructures of the fabricated AgNPs were characterized using UV–visible spectroscopy, Fourier transform infra-red spectra (FTIR), X-ray diffraction (XRD), transmission electron microscopy (TEM), zeta size, and zeta potential techniques. Our results indicate that The UV–vis spectrum of AgNPs exhibited an absorption band at 415 nm. The FTIR analysis identified the functional groups which could involve in the reduction of silver ions to AgNPs, this was also confirmed by the (hkl) diffraction peaks in the XRD diffractogram. Moreover, the TEM analysis showed a spherical nanoparticle with a size ranging from 21 and 26 nm. Thereafter, the potential antibacterial and antifungal activity of the biogenic AgNPs was evaluated against Bacillus pumilus and Alternaria alternata which were isolated from the in vitro culture media and identified based on 16S rDNA and ITS rDNA sequences, respectively. The results showed that the AgNPs significantly inhibited the growth of Alternaria alternata and Bacillus pumilus at all applied concentrations (5, 10, 20 and 40 mg/L). Compared to the control more fungal radial growth reduction (42.59%,) and bacterial inhibition (98.12%) were registered in the plates containing high doses of AgNPs (40 mg/L). Using Rumex nervosus explants, the biosynthesized AgNPs were tested for their impact to promote callus growth. The obtained results showed a significant effect of AgNPs on callus fresh weight at all applied doses. Moreover, AgNPs treatments showed a polymorphism of 12.5% which was detected by RAPD markers. In summary, the results revealed that AgNPs (40 mg/L) can be effectively added to the in vitro culture media for reducing microbial contamination and improving callus growth while greatly maintaining its genetic stability.

Echinops macrochaetus is a medicinal plant that can be used to cure various diseases. In the present study, plant-mediated zinc oxide nanoparticles (ZnO-NPs) were synthesized using an aqueous leaf extract of the medicinal plant Heliotropium bacciferum and characterized using various techniques. E. macrochaetus was collected from the wild and identified using the internal transcribed spacer sequence of nrDNA (ITS-nrDNA), which showed the closeness to its related genus in a phylogenetic tree. The effect of synthesized biogenic ZnO-NPs was studied on E. macrochaetus in a growth chamber for growth, bioactive compound enhancement and antioxidant system response. The irrigation of plants at a low concentration of ZnO-NPs (T1 = 10 mg/L) induced more growth in terms of biomass, chlorophyll content (273.11 µg/g FW) and carotenoid content (135.61 µg/g FW) than the control and other treatments (T2-20 mg/L and T3-40 mg/L). However, the application of a high concentration of ZnO-NPs (20 and 40 mg/L) increased the level of antioxidant enzymes (SOD, APX and GR), total crude and soluble protein, proline and TBARS contents. The accumulations of the compounds quercetin-3-β-D-glucoside, luteolin 7-rutinoside and p-coumaric acid were greater in the leaf compared to the shoot and root. A minor variation was observed in genome size in treated plants as compared to the control group. Overall, this study revealed the stimulatory effect of phytomediated ZnO-NPs, which act as bio-stimulants/nano-fertilizers as revealed by more biomass and the higher production of phytochemical compounds in different parts of the E. macrochaetus.

Self-Compacting Concrete (SCC) that flows by its own weights without compaction or vibration, thereby no external energy from mechanical equipment. In addition to this, cement replacement with silica fume and the introduction of steel fibers have allowed the improvements in durability and hardened properties of SCC. These materials are very important to prevent segregation, bleeding, and increase flow-ability. However, the addition of fibers to SCC may lead to a decline in the workability but in other way helps to improve hardened concrete properties. This paper discusses the results of an experimental investigation onto fresh and hardened properties of the self-compacting concrete mixes with four different percentages of steel fibers (0.25, 0.50, 0.75, and 1.0%) and 20% cement replacement rate with silica fume was incorporated. The workability of fresh concrete was assessed using three tests (slump flow, slump flow T50, L-box, and V-funnel tests) according to EFNARC specification and one visual test (segregation resistance) as per ASTM C 1611. The results showed that using fibers layers led to reduced workability with improved hardened concrete properties, especially toughness. However, the improved tensile and flexural toughness in SCC counteract the reduction in workability. The toughness tests are compared by introducing quadruplicate patterns containing four layers (each layer is 25 mm height) and having seven combinations of fiber laying patterns to quantify the impact in prism specimens. The quadruplicate patterns of steel fibers provide good predictions of impacts of fiber orientation on hardened properties of concrete. The results of this study indicate that the use of silica fume as a replacement for cement and incorporation of steel fiber produces more economically feasible and durable SCC.

Abstract Background Juniperus procera Hoechst. ex Endl. is a medicinal tree in Saudi Arabia, primarily in the Enemas region, but it is locally threatened due to die-back disease and difficulties regarding seed reproduction (seed dormancy and underdeveloped embryonic anatomy, and germination rate

Objective: To isolate and characterize a novel phytocystatin from walnut and investigate it for biopesticide development. Methods: A battery of methodology was employed. Initially, phytocystatin was extracted and purified from walnut using ammonium sulfate saturation (60–80%), followed by gel filtration chromatography on the Sephacryl S-100 HR column. Further characterization studies including pH and temperature stability, molecular weight, secondary structure, protease inhibitory assay and antimicrobial activity were carried using various techniques viz: spectroscopy, electrophoresis, and circular dichroism (CD) techniques. Results: Thiol protease inhibitor from walnut (WCPI) was isolated and purified with high (71.4%) yield and 184-fold purification. The molecular weight of the purified inhibitor was found to be around 11.2 kDa. Kinetic tests revealed that the inhibitor competitively inhibited papain and other cysteine proteases such as ficin and bromelain. It also exhibited significant antimicrobial activity against bacterial species. Conclusion: Walnut cysteine protease inhibitor (WCPI) from Juglans regia (Kashmiri walnut) was isolated to homogeneity and had features of other members of the phytocystatin family. It demonstrated potential antimicrobial activity and may serve as an initial step towards developing enhanced pest control methods based on natural molecules.

Salinity is one of the most limiting constraints of crop production. Nevertheless, highly-tolerant crop plants (e.g. ‘Guar’ Cyamopsis tetragonoloba) can thrive well under salinity conditions. RNA-Seq plays a central role in identifying genes involved in the response mechanisms to salt stress in plant species. High-quality RNA, free of genomic DNA is a critical determinant for success in subsequent downstream experiments to shed light on tolerance mechanisms. In this research, an inspection of two different total RNA isolation protocols was employed for preparing highly pure and intact RNAs with good yield from Guar tissue under both high salinity and control conditions. The extracted RNA appeared in all quality metrics to be of adequate quantity and quality for most downstream applications, including high-throughput transcriptome sequencing and expression analysis. However, the outcomes showed that the most widely used RNA quality measurement, the RNA Integrity Number (RIN), is a poor indicator with a weak correlation to the integrity of RNA from this plant. In contrast to human and animal cells, plants have various ribosomal RNA species. Consequently, whenever the RNA was separated on an agarose gel, several RNA bands did appear, which gives the false impression of being unable to analyze the results of the bioanalyzer integrity. Low RIN number RNA samples were further processed by RNA-sequencing RNA-seq experiments from guar. RNA-seq analysis via Illumina’s paired-end method was carried out to trace back and evaluate the extracted total RNA, resulting in high-quality data for subsequent stress tolerance research.

Ochradenus arabicus is a significant therapeutic plant which grows in desert zones of Saudi Arabia. It has antimicrobial, anticancer, cancer prevention, antidiabetic, allopathic and pabulum properties. The present study evaluated the biosynthesis of silver nanoparticles (AgNPs) utilizing the leaf concentrate of plant O. arabicus having novel ethnomedicinal potential. The incorporated AgNPs were visualized utilizing UV-Visible spectroscopy, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and transmission electron microscopy (TEM). The antimicrobial impact of AgNPs delivering O. arabicus was considered utilizing distinctive pathogenic microorganisms, for example, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa and Streptococcus mutans. From the plate dispersion results, the incorporated silver nanoparticles demonstrated potent antibacterial properties and high antimicrobial action contrasted with the ionic silver. Supplemental data for this article is available online at https://doi.org/10.1080/13102818.2021.1961609 .

The cryostoring of embryogenic tissue of the date palm (Phoenix dactylifera L. cv. Sagai) was examined through dehydrated-encapsulation, vitrification, and vitrification-encapsulation. The most extreme regeneration rate (53.33%) of epitomized, cryostored liquid nitrogen (+LN) treated embryos was observed when pre-embryonic masses were hatched with 0.5 M sucrose for 48 h pursued by 6 h air drying out. The most noteworthy survival rate (80.0%) of epitomized, cryopreserved embryonic cluster came about when calli were hatched with 0.3 or 0.7 M sucrose for 48 h pursued by four hours of lack of hydration, or with 0.5 M sucrose for 48 h without air drying out or with 2 h of air drying out. Following cryopreservation utilizing the embodiment vitrification convention, the most astounding survival (86.7%) as well as the greatest growth (46.7%) was accomplished when the typified vitrified, cryopreserved calli were treated with Vitrification Solution 2 for plants (PVS2) for 60 min at 25 °C. Cryopreservation utilizing the vitrification convention brought about the most extreme recuperation of 53.3%, when vitrified-cryopreserved calli were subjected to PVS2 solution for 30 min at 25 °C. Most extreme (40%) regeneration of vitrified, cryopreserved embryonic calli was seen when these calli were treated with PVS2 solution for 60 min at 25 °C. The outcome got amid this investigation of regrowth after cryopreservation of the cv. Sagai was over the base suitable for a cryo-germplasm bank. Recovery and regrowth were above 30% for all the techniques developed for the cv. Sagai. Keywords: Cryopreservation, Date palm, Embryogenesis, Vitrification, Encapsulation, Dehydration

The systematic behavior of porous asphalt pavement (PAP) under normal traffic conditions has been studied in detail in the present work. In the first phase, an observation program measured the stability by Marshall Test for all the prepared design mix samples with normal bitumen (60/70). For the permeability test in the second phase of observation, a model is developed in the laboratory on the same falling head permeability test. The maximum permeability reaches 0.394 cm/sec for a fresh sample and 0.245 cm/sec after one year of environmental exposure. The maximum stability was 26.9 kN, and the average value obtained was 21 kN. The present work approach provides effectively reliable results in terms of stability and permeability of porous asphalt mix. The primary goal of this research is to reduce the possibility of floods and increase driver protection during inclement weather. A particular emphasis was placed on the mix ratio differences between aggregates to achieve the desired permeability while maintaining the necessary stability. The findings indicate that the checked sample looked excellent in terms of permeability.

Secondary plant metabolites and their derivatives play a significant role in human health. Ferruginol is a diterpene phenol that has recently received attention for its pharmacological properties, including antibacterial, antitumor, antimalarial, and cardioprotective effects. Recently, we detected the ferruginol compound in the leaf and seed extracts of Juniperus procera using different analytical approaches. The present work aims at detecting phytochemical compounds in a root extract of J. procera and estimating the amount of ferruginol compound in different parts of Juniperus procera. To screen the phytochemical compounds present in the root extract of J. procera, Gas chromatography/mass spectrometry (GC/MS) was performed. For ferruginol identification and estimation, high-performance liquid chromatography (HPLC) with the ferruginol reference standard and high-resolution direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) (DART-TOF-MS) analysis were used. GC/MS analysis revealed more than 20 bioactive compounds related to secondary plant metabolites in the root extract of J. procera with biological activity. The DART-TOF-MS result showed the typical positive ion spectra of ferruginol, and the HPLC result confirmed that the root extract of J. procera contains the ferruginol compound. In contrast, the root extract of J. procera contained a significant amount of ferruginol compared to that in the leaf and seed extracts. All parts of the J. procera contained the ferruginol compound and proved that ferruginol might be accumulated in the roots, leaves, and seeds of J. procera.

Acacias are widely distributed in tropical and subtropical regions of the world and have both economic as well as medicinal value. The estimation of genome size is very important as it changes due to the change in noncoding DNA sequence as well as genome duplication among organisms for their evolutionary aspects. Three potential species of the genus Acacia including Acacia etbaica, Acacia johnwoodii and Acacia origena, which are threatened and nearly endemic to Saudi Arabia, were collected. The present study was carried out to determine the genome size (2C DNA contents), total phenolic content (TPC), total flavonoid (TFC) and some bioactive compounds in these species for their comparison. The genome size ranged from 1.91 pg (A. etbaica) to 2.45 pg/2C (A. origena) among the Acacia species, which correspond to genome sizes 1843.15–2364.25 Mbp, respectively. The variation was observed in genome size within Acacia species as nuclei were extracted using different extraction buffers except for GB and MB01 buffers. The FTIR analysis revealed the presence of various functional groups in compounds that might be responsible for different types of phytochemicals in these Acacia species. Total flavonoid content (TFC) ranged from 0.647 (A. origena) to 1.084 mg QE/g DW (A. etbaica), whereas the total phenolic f content (TPC) ranged between 15.322 (A. origena) to 28.849 (A. johnwoodii) mg/g DW of GAE. HPLC analysis revealed the presence of quercetin 3-β-D-glucoside and luteolin 7-rutinoside in the leaves of all three Acacia species in considerable amounts, and these might have good health-promoting effects. This is our first study on genome size (2C DNA content) using flow cytometry and phytochemical profiling on these Acacias. Thus, estimated genome size and phytochemical study of these species could help to understand the biosynthesis of secondary metabolites under various genes and the evolutionary relationships among them.

Maerua oblongifolia (Forssk.) is a rare medicinal plant in Saudi Arabia that is threatened with extinction owing to overexploitation, climate change, and poor seed germination. This study aimed to identify, for the first time, the phytochemical compounds existing in M. oblongifolia leaves’ extract using gas chromatography and mass spectroscopy (GC-MS). In addition, it aimed to determine the plant growth and genetic uniformity of the plant under the exposure of in vitro biogenic silver and zinc oxide nanoparticles. The GC-MS analysis detected 28 phytochemical compounds. The main compounds obtained from the leaf extracts were triphenylphosphine oxide and 4,5-Dihydrooxazole-5-one, 2-methyl-4-[2,3,4-methozxybenzylidnen]-. The supplementation of AgNPs and ZnO NPs to the culture media significantly enhanced the plant biomass, shoot length, and shoot regeneration of M. oblongifolia. The genetic stability of the plant material was evaluated using inter-simple sequence repeat (ISSR) markers. The application of Ag and ZnO NPs showed genetic stability among treated plants. However, the higher concentration of both nanoparticles induced minor genetic variations recorded as 4.4 and 2.2% in Ag and ZnO NPs, respectively. This work focused on the detection of phytochemical active constituents from M. oblongifolia shoot cultures, and it will be useful for the large-scale manufacturing of these compounds for pharmaceutical and commercial purposes. In addition, it confirmed that the exposure of silver and zinc oxide nanoparticles to the in vitro culture media of plant tissues might be a secure technique with which to produce true-to-type plants.

Salinity is one of the major abiotic stresses that affect the plant’s growth and development. Recently, the contribution of nanoparticles (NPs) to ameliorating salinity stresses has become the new field of interest for scientists due to their special physiochemical properties in the biological system. This study is designed to examine the effects of biosynthesized silver nanoparticles (AgNPs) spherical in shape (size range between 9 and 30 nm) on morphophysiological characteristics and the antioxidant defense system of in vitro raised Maerua oblongifolia under four levels of salt stress (0, 50, 100, and 200 mM NaCl). Our findings reveal that the application of AgNPs (0, 10, 20, and 30 mg/L) to M. oblongifolia shoots significantly alleviates the adverse effects of salt stress and ameliorates plant developmental-related parameters and defense systems. High salinity elevates the oxidative damage by over-accumulation of the levels of total soluble sugars, proline, hydrogen peroxide (H2O2), and malondialdehyde (MDA). In addition, enhancing the activity of the antioxidant enzymes, total phenolic, and flavonoid content over the control. Interestingly, the application of AgNPs to salinized plants improved the growth traits and photosynthetic pigment production and caused higher enhancement in antioxidant enzyme activities. Furthermore, mitigating the oxidative damage by lowering the accumulation of proline, soluble sugars, H2O2, MDA, and total phenolic and flavonoid contents in salt-stressed plants. In general, AgNPs augmented the growth of M. oblongifolia shoots under saline conditions through different strategies; thus, AgNPs can be used as an appropriate eco-friendly approach that enhances salinity tolerance in plants.

Abrus precatorius is considered to be a valuable source of natural products for the development of drugs against various diseases. Herein, the genome size and phytochemical compounds in the leaves and callus of A. precatorius were evaluated. The endangered A. precatorius was collected from the Al-Baha mountains, Saudi Arabia and identified based on the phylogenetic analysis of a DNA sequence amplified by ITS1 and ITS4 primers. The callus was induced by the culture of stem explants onto Murashige and Skoog medium (MS) supplemented with various combinations of 2,4-dichlorophenoxyacetic acid (2,4D) and 6-Benzylaminopurine (BAP). The callus with the highest fresh weight (2.03 g) was obtained in the medium containing 0.5µM BA and 5 µM 2,4-D after 8 weeks of culture; thus, the callus of this combination was selected for the genome estimation and phytochemical compound extraction. The genetic stability of the leaves from the donor as well as in the regenerated callus was analyzed by flow cytometry with optimized tomato (2C = 1.96 pg) as an external reference standard. The 2C DNA content was estimated to 1.810 pg ± 0.008 and 1.813 pg ± 0.004 for the leaves and callus, respectively. Then, the total phenol and total flavonoid contents in the methanol extract of the callus and leaves were measured using a spectrophotometer and the High-performance liquid chromatography (HPLC ) methods. The results showed that the methanolic extract of the leaves was higher in total phenols and total flavonoids than the callus extract. Finally, the extracts of callus and leaves were analyzed for phytochemical compound through the Gas chromatography and Mass spectroscopy (GC-MS). A total of 22 and 28 compounds were detected in the callus and leaves, respectively. The comparative analysis showed that 12 compounds of the secondary metabolites were present in both extracts.

The threat of heat stress on crop production increased dramatically due to global warming leading to the rise on the demand of heat-tolerant crops and understanding their tolerance. The leguminous forage crop Guar [Cyamopsis tetragonoloba (L.) Taub] is a high-temperature tolerant plant with numerous works on its tolerance at morph-physiological levels but lack on molecular thermotolerance level. In the current study, the differential gene expression and the underlying metabolic pathways induced by heat treatment were investigated. An RNA-Seq study on Guar leaves was carried out to estimate gene abundance and identify genes involved in heat tolerance to better understand the response mechanisms to heat stress. The results uncovered 1551 up- and 1466 downregulated genes, from which 200 and 72 genes with unknown function could be considered as new genes specific to guar. The upregulated unigenes were associated with 158 enzymes and 102 KEGG pathways. Blast2GO, InterProScan, and Kyoto Encyclopaedia of Genes and Genomes packages were utilized to search the functional annotation, protein analysis, enzymes, and metabolic pathways and revealed hormone signal transduction were enriched during heat stress tolerance. A total of 301 protein families, 551 domains, 15 repeats, and 3 sites were upregulated and matched to those unigenes. A batch of heat-regulated transcription factor transcripts were identified using the PlantTFDB database, which may play roles in heat response in Guar. Interestingly, several heat shock protein families were expressed in response to exposure to stressful conditions for instance small HSP20, heat shock transcription factor family, heat shock protein Hsp90 family, and heat shock protein 70 family. Our results revealed the expressional changes associated with heat tolerance and identified potential key genes in the regulation of this process. These results will provide a good start to dissect the molecular behaviour of plants induced by heat stress and could identify the key genes in stress response for marker-assisted selection in Guar and reveal their roles in stress adaptation in plants.

Drought remains one of the most serious environmental stresses because of the continuous reduction in soil moisture, which requires the improvement of crops with features such as drought tolerance. Guar [Cyamopsis tetragonoloba (L.) Taub], a forage and industrial crop, is a nonthirsty plant. However, the information on the transcriptome changes that occur under drought stress in guar is very limited; therefore, a gene expression analysis is necessary in this context. Here, we studied the differentially expressed genes (DEGs) in response to drought stress and their metabolic pathways. RNA-Seq via an expectation-maximization algorithm was used to estimate gene abundance. Subsequently, an Empirical Analysis of Digital Gene Expression Data in the R Bioconductor package was used to identify DEGs. Blast2GO, InterProScan, and the Kyoto Encyclopedia of Genes and Genomes were used to explore functional annotation, protein analysis, enzymes, and metabolic pathways. Transcription factors were identified using the PlantTFDB database. Our study identified 499 upregulated and 191 downregulated genes in response to drought stress. Of those, 32 upregulated and six downregulated genes were deemed as novel genes exclusive to guar. An aggregate of 137 protein families, 306 domains, 12 repeats, and two sites were upregulated. The proton-dependent oligopeptide transporter family and transferase, aquaporin transporter, calcium/calmodulin-dependent/calcium-dependent protein kinase, aspartic peptidase A1 family, UDP-glucuronosyl/UDP-glucosyltransferase, and major intrinsic protein were the most upregulated protein families. The upregulated unigenes were associated with 88 enzymes and 77 KEGG pathways. Finally, the MYB-related, MYB, and ERF transcription factor families were upregulated. These data may be useful for understanding the plant molecular response to drought stress.

Reseda pentagyna is the only endemic species among the seven species of the genera Reseda found in Saudi Arabia. Probably no information is available on regeneration by conventional method of regeneration through seeds or cuttings. Therefore, alternative method of tissue culture was attempted to regenerate and multiply the plant. High shoot regeneration (14.44 shoots/explant) was obtained after four weeks, when shoot cuttings cultured on MS containing BA at 1.0 µM. Other cytokinins e.g., Kn, 2iP and TDZ found to be less effective in bud induction and shoot multiplication. Individual shoots were rooted on MS medium supplemented with various auxins at 0.5–5.0 µM concentrations. The IBA (1.5 µM) supplemented MS media induced maximum (83.3%) rooting. The plantlets were acclimatized and hardened under greenhouse conditions in plastic pots containing soil and farm yard manure with 95.0% success. The protocol developed would help to multiply the plant as well as conserve them in natural habitat. This can also be utilized to obtain active constituents for pharmaceutics and genetic manipulations.

Juniperus procera is a natural source of bioactive compounds with the potential of antitumor, antimicrobial, insecticidal, antifungal, and antioxidant activities. An optimization method was developed for total phenolic content (TPC), total flavonoid content (TFC), and total tannin content (TTC) in leaf and seed extract of Juniperus procera. Organic solvents (methanol (99.8%), ethanol (99%), and acetone (99.5%)), and deionized water (DI) were used for extraction. The estimation of TPC, TFC, and TTC in plant materials was carried out using UV-spectrophotometer and HPLC with the standards gallic acid, quercetin, and tannic acid. Recovery of TPC in leaf extract ranged from 2.9 to 9.7 mg GAE/g DW, TFC from 0.9 to 5.9 mg QE/g DW, and TTC ranged from 1.5 to 4.3 mg TA/g DW while the TPC value in the seed extract ranged from 0.53 to 2.6 mg GAE/g DW, TFC from 0.5 to 1.6 mg QE/g DW, and TTC ranged from 0.5 to 1.4 mg TA/g DW. This result revealed that methanol is the best solvent for recovery of the TPC value (9.7 mg) from leaf extract in comparison to other solvents. Ethanol recorded the highest result of TFC (5.9 mg) in leaf extract among the solvents whereas acetone was the best for TTC yield recovery from leaf extract (4.3 mg). In the case of the seed extract, ethanol was the best solvent for both TPC (2.6 mg), and TFC (1.6 mg) recovery in comparison to other solvents. Total tannin content in methanol resulted in significant recovery from seed extract (1.4 mg). Separation and quantification of gallic acid, quercetin, and tannic acid in plant materials were undertaken using HPLC. Gallic acid in leaf and seed of J. procera ranged from 6.6 to 9.2, 6.5 to 7.2 µg/g DW, quercetin from 6.3 to 18.2, 0.9 to 4.2 µg/g DW, and tannic acid from 16.2 to 29.3, 6.6 to 9.3 µg/g DW, respectively. Solvents have shown a significant effect in the extraction of phenolic compounds. Moreover, phytochemicals in plant materials were identified using GC-MS and resulted in very important bioactive compounds, which include anti-inflammatory, antibacterial, and antitumor agents such as ferruginol, phenanthrene, and n-hexadecanoic acid. In conclusion, the optimal solvent for extraction depends on the part of the plant material and the compounds that are to be isolated.

Zincoxide nanoparticles (ZnO NPs) are among the most produced and used nanomaterials worldwide, and in recent times these nanoparticles have also been incorporate in plant science and agricultural research. The present study was planned to synthesize ZnO NPs biologically using Ochradenus arabicus leaves and examine their effect on the morphology and physiology properties of Maerua oblongifolia cultured in vitro. ZnO NPs were characterized by UV–visible spectroscopy (UV–vis), X-ray diffractometer (XRD), Fourier transform infrared spectroscopy (FT-IR), and transmission electron microscopy, which demonstrated hexagonal shape nanoparticles of size ranging from 10 to 50 nm. Thus, the study uncovered an efficient, eco-friendly and simple technique for biosynthesis of multifunctional ZnO NPs using Ochradenus arabicus following growth of Maerua oblongifolia shoots in different concentrations of ZnO NPs (0, 1.25, 2.5, 5, 10, or 20 mg L−1) in Murashige and Skoog medium. Remarkable increases in plant biomass, photosynthetic pigments, and total protein were recorded up to a concentration of 5 mg L−1; at the same time, the results demonstrated a significant reduction in lipid peroxidation levels with respect to control. Interestingly, the levels of proline and the antioxidant enzyme catalase (CAT), superoxide dismutase (SOD), and glutathione reductase (GR) activities were increased significantly in response to all ZnO NP treatments. These findings indicate that bioengineered ZnO NPs play a major role in accumulation of biomass and stimulating the activities of antioxidant enzymes in plant tissues. Thus, green-synthesized ZnO NPs might be of agricultural and medicinal benefit owing to their impacts on plants in vitro.

Genome size is one of the fundamental cytogenetic features of a species, which is critical for the design and initiation of any genome sequencing projects and can provide essential insights in studying taxonomy, cytogenetics, phylogenesis, and evolutionary studies. However, this key cytogenetic information is almost lacking in the endemic species Reseda pentagyna and the locally rare species Reseda lutea in Saudi Arabia. Therefore, genome size was analyzed by propidium iodide PI flow cytometry and compared to k-mer analysis methods. The standard method for genome size measures (flow cytometry) estimated the genome size of R. lutea and R. pentagyna with nuclei isolation MB01 buffer were found to be 1.91 ± 0.02 and 2.09 ± 0.03 pg/2 °C, respectively, which corresponded approximately to a haploid genome size of 934 and 1.022 Mbp, respectively. For validation, K-mer analysis was performed on both species’ Illumina paired-end sequencing data from both species. Five k-mer analysis approaches were examined for biocomputational estimation of genome size: A general formula and four well-known programs (CovEST, Kmergenie, FindGSE, and GenomeScope). The parameter preferences had a significant impact on GenomeScope and Kmergenie estimates. While the general formula estimations did not differ considerably, with an average genome size of 867.7 and 896. Mbp. The differences across flow cytometry and biocomputational predictions may be due to the high repeat content, particularly long repetitive regions in both genomes, 71% and 57%, which interfered with k-mer analysis. GenomeScope allowed quantification of high heterozygosity levels (1.04 and 1.37%) of R. lutea and R. pentagyna genomes, respectively. Based on our observations, R. lutea may have a tetraploid genome or higher. Our results revealed fundamental cytogenetic information for R. lutea and R. pentagyna, which should be used in future taxonomic studies and whole-genome sequencing.

In the title compound, C14H14N2O4S, the benzene and thiazolidine rings are almost coplanar with a dihedral angle of 2.98 (14)°. The butyl chain is directed almost perpendicular to the plane of the rest of the molecule. In the crystal, a combination of C—H...O hydrogen bonds and offset π–π interactions leads to the formation of a three-dimensional structure.

The forage crop Guar (Cyamopsis tetragonoloba (L.) Taub.) has the ability to endure heat, drought, and mild salinity. A complete image on its genic architecture will promote our understanding about gene expression networks and different tolerance mechanisms at the molecular level. Therefore, whole mRNA sequence approach on the Guar plant was conducted to provide a snapshot of the mRNA information in the cell under salinity, heat, and drought stresses to be integrated with previous transcriptomic studies. RNA-Seq technology was employed to perform a 2×100 paired-end sequencing using an Illumina HiSeq 2500 platform for the transcriptome of leaves of C. tetragonoloba under normal, heat, drought, and salinity conditions. Trinity was used to achieve a de novo assembly followed by gene annotation, functional classification, metabolic pathway analysis, and identification of SSR markers. A total of 218.2 million paired-end raw reads (~44 Gbp) were generated. Of those, 193.5M paired-end reads of high quality were used to reconstruct a total of 161,058 transcripts (~266 Mbp) with N50 of 2552 bp and 61,508 putative genes. There were 6463 proteins having >90% full-length coverage against the Swiss-Prot database and 94% complete orthologs against Embryophyta. Approximately, 62.87% of transcripts were blasted, 50.46% mapped, and 43.50% annotated. A total of 4715 InterProScan families, 3441 domains, 74 repeats, and 490 sites were detected. Biological processes, molecular functions, and cellular components comprised 64.12%, 25.42%, and 10.4%, respectively. The transcriptome was associated with 985 enzymes and 156 KEGG pathways. A total of 27,066 SSRs were gained with an average frequency of one SSR/9.825 kb in the assembled transcripts. This resulting data will be helpful for the advanced analysis of Guar to multi-stress tolerance.

Ziziphus spina-christi (sidr) is a shrub, sometimes a tree, native to a vast area of Africa stretching from Mauritania to West Africa. In the Kingdom of Saudi Arabia, it is an exotic medicinal plant for many diseases. The aim of this study was to assess the genetic diversity within and among 34 accessions of Z. spina-christi collected from different regions of Saudi Arabia. The amplification of genomic DNA with 11 inter-simple sequence repeat (ISSR) primers yielded 105 scorable loci, of which 93.4% were found to be polymorphic. The observed number of alleles (na), effective number of alleles (ne), Nei's gene diversity (h) and genetic diversity estimated by Shannon's information index (I) were 1.93, 1.44, 0.26 and 0.41, respectively. The total genetic diversity, Ht (0.266 ± 0.0289) was close to the average intrapopulation genetic diversity, Hs (0.2199 ± 0.0216). A high level of gene flow (Nm = 2.37) between populations, reflecting high genetic differentiation (Gst = 0.1739). The analysis of molecular variance showed that the maximum value of genetic variation was found within populations (90%), whereas a low value of genetic variance was observed among populations. The analysis using the unweighted pair-group method with arithmetic averages clustered the population from Farasan Island as an out-group due to its geographical origin. The obtained results demonstrate that the ISSR markers may be used for evaluation of the genetic diversity due to their efficiency in revealing polymorphism even in closely related germplasm and may help in Ziziphus genome analysis.

Date palm (Phoenix dactylifera L.) is cultivated in arid and semiarid regions worldwide. Given the dioecious nature of this plant, gender identification is very important at the seedling stage. Molecular markers are very effective tools that help in gender identification at this stage. A sequence characterized amplified region (SCAR) marker linked to sex-specific regions in the genome of date palm was developed. Of the 300 tested randomly amplified polymorphic DNA (RAPD) primers, only one primer (OPC-06) produced reproducible band (294 bp) in male plants. The PCR product of this primer was cloned and sequenced. The specific primers were synthesized for amplification of a 186 bp fragment in male date palm plants. These primers were validated in male and female date palm plants, wherein the designed SCAR marker was reported only in male plants and no amplification was observed in female plants. The developed SCAR marker was used with seedlings of date palm and proved very effective in identification of gender.

Many Phoenix dactylifera (date palm) cultivars are grown in the arid and semiarid regions of the world, including Saudi Arabia. P. dactylifera is highly tolerant to salinity stress. To investigate the response of Khalas cultivar of P. dactylifera, two-month-old plants were treated with sodium chloride (50, 100, and 150 mM NaCl) for three months. Our result showed that proline content was higher in all treated plants compared to control plants. Thiobarbituric acid reactive substances (TBARS) were increased at 100 and 150 mM NaCl treatments; however, the result was found nonsignificant between control and plants treated at 50 mM NaCl. Similarly, enzyme activities of catalase (CAT) and superoxide dismutase (SOD) were 0.805 and 0.722 U/mg protein/min, respectively, and were greater at 100 and 150 mM NaCl treatments compared to the control plants. Total chlorophyll content and fresh weight of shoots and roots decreased substantially with the increase of salinity. A cDNA start codon-targeted (cDNA-SCoT) marker showed a variation in different gene expressions profiling between treated and untreated plants under various NaCl concentrations.