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Wheat is an important crop, used as staple food in numerous countries around the world. However, wheat productivity is low in the developing world due to several biotic and abiotic stresses, particularly drought stress. Non-availability of drought-tolerant wheat genotypes at different growth stages is the major constraint in improving wheat productivity in the developing world. Therefore, screening/developing drought-tolerant genotypes at different growth stages could improve the productivity of wheat. This study assessed seed germination and seedling growth of eight wheat genotypes under polyethylene glycol (PEG)-induced stress. Two PEG-induced osmotic potentials (i.e., -0.6 and -1.2 MPa) were included in the study along with control (0 MPa). Wheat genotypes included in the study were ‘KLR-16’, ‘B6’, ‘J10’, ‘716’, ‘A12’, ‘Seher’, ‘KTDH-16’, and ‘J4’. Data relating to seed germination percentage, root and shoot length, fresh and dry weight of roots and shoot, root/shoot length ratio and chlorophyll content were recorded. The studied parameters were significantly altered by individual and interactive effects of genotypes and PEG-induced osmotic potentials. Seed germination and growth parameters were reduced by osmotic potentials; however, huge differences were noted among genotypes. A reduction of 32.83 to 53.50% was recorded in seed germination, 24.611 to 47.75% in root length, 37.83 to 53.72% in shoot length, and 53.35 to 65.16% in root fresh weight. The genotypes, ‘J4’, ‘KLR-16’ and ‘KTDH-16’, particularly ‘J4’ better tolerated increasing osmotic potentials compared to the rest of the genotypes included in the study. Principal component analysis segregated these genotypes from the rest of the genotypes included in the study indicated that these can be used in the future studies to improve the drought tolerance of wheat crop. The genotype ‘J4’ can be used as a breeding material to develop drought resistant wheat genotypes.

Wheat ( Triticum aestivum L.) is an important staple food crop for one third of global population and important crop for securing future food security. Rapid changes in the climate on global scale could be a threat for future food security. This situation urges plant breeders to explore the genetic potential of existing wheat germplasm. This study screened forty diverse wheat genotypes for their yield under two different agroclimatic conditions, i.e., Layyah and Dera Ghazi Khan, Pakistan. Data relating to plant height, peduncle length, flag leaf area, spike length, number of spikelets, number of grains per spike, thousand grain weight, chlorophyll content and grain yield were recorded. The tested wheat genotypes significantly differed for grain yield and related traits. Grain yield was positively correlated with plant height, spike length, spike number, flag leaf length, number of grains per spike, and 1000-grain weight. Biplot obtained from the cluster analysis by Euclidean method grouped the studied genotypes in 3 different groups. The genotypes exhibited 10.77% variability within quadrants, whereas 72.36% variability was recorded between quadrants according to clustering. Dendrogram grouped the tested genotypes into two main clusters. The main cluster “I” comprised of 2 genotypes, i.e., ‘Seher-2006’ and ‘AS-2002’. The cluster “II” contained 38 genotypes based on Euclidian values. Genotypes within same cluster had smaller D 2 values compared to those belonging to other clusters. The genetic relationships of genotypes provide useful information for breeding programs. Overall, the results revealed that genotypes ‘Line 9733’, ‘Bhakar-2002’, ‘Line A9’ and ‘SYN-46’ had better yield and yield stability under climatic conditions of southern Punjab. Therefore, these genotypes could be recommended for general cultivation in the study region.

Wheat is an important crop, used as staple food in numerous countries around the world. However, wheat productivity is low in the developing world due to several biotic and abiotic stresses, particularly drought stress. Non-availability of drought-tolerant wheat genotypes at different growth stages is the major constraint in improving wheat productivity in the developing world. Therefore, screening/developing drought-tolerant genotypes at different growth stages could improve the productivity of wheat. This study assessed seed germination and seedling growth of eight wheat genotypes under polyethylene glycol (PEG)-induced stress. Two PEG-induced osmotic potentials (i.e., -0.6 and -1.2 MPa) were included in the study along with control (0 MPa). Wheat genotypes included in the study were 'KLR-16', 'B6', 'J10', '716', 'A12', 'Seher', 'KTDH-16', and 'J4'. Data relating to seed germination percentage, root and shoot length, fresh and dry weight of roots and shoot, root/shoot length ratio and chlorophyll content were recorded. The studied parameters were significantly altered by individual and interactive effects of genotypes and PEG-induced osmotic potentials. Seed germination and growth parameters were reduced by osmotic potentials; however, huge differences were noted among genotypes. A reduction of 32.83 to 53.50% was recorded in seed germination, 24.611 to 47.75% in root length, 37.83 to 53.72% in shoot length, and 53.35 to 65.16% in root fresh weight. The genotypes, 'J4', 'KLR-16' and 'KTDH-16', particularly 'J4' better tolerated increasing osmotic potentials compared to the rest of the genotypes included in the study. Principal component analysis segregated these genotypes from the rest of the genotypes included in the study indicated that these can be used in the future studies to improve the drought tolerance of wheat crop. The genotype 'J4' can be used as a breeding material to develop drought resistant wheat genotypes.

Wheat (Triticum aestivum L.) is an important staple food crop for one third of global population and important crop for securing future food security. Rapid changes in the climate on global scale could be a threat for future food security. This situation urges plant breeders to explore the genetic potential of existing wheat germplasm. This study screened forty diverse wheat genotypes for their yield under two different agroclimatic conditions, i.e., Layyah and Dera Ghazi Khan, Pakistan. Data relating to plant height, peduncle length, flag leaf area, spike length, number of spikelets, number of grains per spike, thousand grain weight, chlorophyll content and grain yield were recorded. The tested wheat genotypes significantly differed for grain yield and related traits. Grain yield was positively correlated with plant height, spike length, spike number, flag leaf length, number of grains per spike, and 1000-grain weight. Biplot obtained from the cluster analysis by Euclidean method grouped the studied genotypes in 3 different groups. The genotypes exhibited 10.77% variability within quadrants, whereas 72.36% variability was recorded between quadrants according to clustering. Dendrogram grouped the tested genotypes into two main clusters. The main cluster “I” comprised of 2 genotypes, i.e., ‘Seher-2006’ and ‘AS-2002’. The cluster “II” contained 38 genotypes based on Euclidian values. Genotypes within same cluster had smaller D2 values compared to those belonging to other clusters. The genetic relationships of genotypes provide useful information for breeding programs. Overall, the results revealed that genotypes ‘Line 9733’, ‘Bhakar-2002’, ‘Line A9’ and ‘SYN-46’ had better yield and yield stability under climatic conditions of southern Punjab. Therefore, these genotypes could be recommended for general cultivation in the study region.

The plastid genomes of different plant species exhibit significant variation, thereby providing valuable markers for exploring evolutionary relationships and population genetics. Glycine soja (wild soybean) is recognized as the wild ancestor of cultivated soybean (G. max), representing a valuable genetic resource for soybean breeding programmes. In the present study, the complete plastid genome of G. soja was sequenced using Illumina paired-end sequencing and then compared it for the first time with previously reported plastid genome sequences from nine other Glycine species. The G. soja plastid genome was 152,224 bp in length and possessed a typical quadripartite structure, consisting of a pair of inverted repeats (IRa/IRb; 25,574 bp) separated by small (178,963 bp) and large (83,181 bp) single-copy regions, with a 51-kb inversion in the large single-copy region. The genome encoded 134 genes, including 87 protein-coding genes, eight ribosomal RNA genes, and 39 transfer RNA genes, and possessed 204 randomly distributed microsatellites, including 15 forward, 25 tandem, and 34 palindromic repeats. Whole-plastid genome comparisons revealed an overall high degree of sequence similarity between G. max and G. gracilis and some divergence in the intergenic spacers of other species. Greater numbers of indels and SNP substitutions were observed compared with G. cyrtoloba. The sequence of the accD gene from G. soja was highly divergent from those of the other species except for G. max and G. gracilis. Phylogenomic analyses of the complete plastid genomes and 76 shared genes yielded an identical topology and indicated that G. soja is closely related to G. max and G. gracilis. The complete G. soja genome sequenced in the present study is a valuable resource for investigating the population and evolutionary genetics of Glycine species and can be used to identify related species.

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution.

Global warming is impacting the growth and development of economically important but sensitive crops, such as soybean (Glycine max L.). Using pleiotropic signaling molecules, melatonin can relieve the negative effects of high temperature by enhancing plant growth and development as well as modulating the defense system against abiotic stresses. However, less is known about how melatonin regulates the phytohormones and polyamines during heat stress. Our results showed that high temperature significantly increased ROS and decreased photosynthesis efficiency in soybean plants. Conversely, pretreatment with melatonin increased plant growth and photosynthetic pigments (chl a and chl b) and reduced oxidative stress via scavenging hydrogen peroxide and superoxide and reducing the MDA and electrolyte leakage contents. The inherent stress defense responses were further strengthened by the enhanced activities of antioxidants and upregulation of the expression of ascorbate–glutathione cycle genes. Melatonin mitigates heat stress by increasing several biochemicals (phenolics, flavonoids, and proline), as well as the endogenous melatonin and polyamines (spermine, spermidine, and putrescine). Furthermore, the positive effects of melatonin treatment also correlated with a reduced abscisic acid content, down-regulation of the gmNCED3, and up-regulation of catabolic genes (CYP707A1 and CYP707A2) during heat stress. Contrarily, an increase in salicylic acid and up-regulated expression of the defense-related gene PAL2 were revealed. In addition, melatonin induced the expression of heat shock protein 90 (gmHsp90) and heat shock transcription factor (gmHsfA2), suggesting promotion of ROS detoxification via the hydrogen peroxide-mediated signaling pathway. In conclusion, exogenous melatonin improves the thermotolerance of soybean plants and enhances plant growth and development by activating antioxidant defense mechanisms, interacting with plant hormones, and reprogramming the biochemical metabolism.

Melatonin is a multifunctional signaling molecule that is ubiquitously distributed in different parts of a plant and responsible for stimulating several physio-chemical responses to adverse environmental conditions. In this review, we show that, although plants are able to biosynthesize melatonin, the exogenous application of melatonin to various crops can improve plant growth and development in response to various abiotic and biotic stresses (e.g., drought, unfavorable temperatures, high salinity, heavy metal contamination, acid rain, and combined stresses) by regulating antioxidant machinery of plants. Current knowledge suggests that exogenously applied melatonin can enhance the stress tolerance of plants by regulating both the enzymatic and non-enzymatic antioxidant defense systems. Enzymic antioxidants upregulated by exogenous melatonin include superoxide dismutase, catalase, glutathione peroxidase, and enzymes involved in the ascorbate–glutathione cycle (ascorbate peroxidase, monodehydroascorbate reductase, dehydroascorbate reductase, and glutathione reductase), whereas levels of non-enzymatic antioxidants such as ascorbate, reduced glutathione, carotenoids, tocopherols, and phenolics are also higher under stress conditions. The enhanced antioxidant system consequently exhibits lower lipid peroxidation and greater plasma membrane integrity when under stress. However, these responses vary greatly from crop to crop and depend on the intensity and type of stress, and most studies to date have been conducted under controlled conditions. This means that a wider range of crop field trials and detailed transcriptomic analysis are required to reveal the gene regulatory networks involved in the between melatonin, antioxidants, and abiotic stress.

Melatonin is an indolamine bioactive molecule that regulates a wide range of physiological processes during plant growth and enhances abiotic stress tolerance. Here we examined the putative role of exogenous melatonin application (foliar or root zone) in improving drought stress tolerance in soybean seedlings. Pre-treatment of soybean seedlings with melatonin (50 and 100 µM) was found to significantly mitigate the negative effects of drought stress on plant growth-related parameters and chlorophyll content. The beneficial impacts against drought were more pronounced by melatonin application in the rhizosphere than in foliar treatments. The melatonin-induced enhanced tolerance could be attributed to improved photosynthetic activity, reduction of abscisic acid and drought-induced oxidative damage by lowering the accumulation of reactive oxygen species and malondialdehyde. Interestingly, the contents of jasmonic acid and salicylic acid were significantly higher following melatonin treatment in the root zone than in foliar treatment compared with the control. The activity of major antioxidant enzymes such as superoxide dismutase, catalase, polyphenol oxidase, peroxidase and ascorbate peroxidase was stimulated by melatonin application. In addition, melatonin counteracted the drought-induced increase in proline and sugar content. These findings revealed that modifying the endogenous plant hormone content and antioxidant enzymes by melatonin application improved drought tolerance in soybean seedlings. Our findings provide evidence for the stronger physiological role of melatonin in the root zone than in leaves, which may be useful in the large-scale field level application during drought. Melatonin is an indolamine bioactive molecule that regulates a wide range of physiological processes during plant growth and enhances abiotic stress tolerance. Here we examined the putative role of exogenous melatonin application (foliar or root zone) in improving drought stress tolerance in soybean seedlings. Pre-treatment of soybean seedlings with melatonin (50 and 100 µM) was found to significantly mitigate the negative effects of drought stress on plant growth-related parameters and chlorophyll content. The beneficial impacts against drought were more pronounced by melatonin application in the rhizosphere than in foliar treatments. The melatonin-induced enhanced tolerance could be attributed to improved photosynthetic activity, reduction of abscisic acid and drought-induced oxidative damage by lowering the accumulation of reactive oxygen species and malondialdehyde. Interestingly, the contents of jasmonic acid and salicylic acid were significantly higher following melatonin treatment in the root zone than following foliar application as compared to the control. The activity of major antioxidant enzymes such as superoxide dismutase, catalase, polyphenol oxidase, peroxidase and ascorbate peroxidase was largely stimulated by melatonin application. In addition, melatonin counteracted the drought-induced increase in proline and sugar content. These findings revealed that modifying the endogenous plant hormone content and antioxidant enzymes by melatonin improved drought tolerance in soybean seedlings. Our findings provide evidence for the stronger physiological role of melatonin in the root zone rather than foliar zone, which may be useful in the large-scale field level application during drought.

Highlighting the importance of artificial intelligence and machine learning approaches in engineering and fluid mechanics problems, especially in heat transfer applications is main goal of the presented article. With the advancement in Artificial Intelligence (AI) and Machine Learning (ML) techniques, the computational efficiency and accuracy of numerical results are enhanced. The theme of the study is to use machine learning techniques to examine the thermal analysis of MHD boundary layer flow of Eyring-Powell Hybrid Nanofluid (EPHNFs) passing a horizontal cylinder embedded in a porous medium with heat source/sink and viscous dissipation effects. The considered base fluid is water (H2O) and hybrid nanoparticles titanium oxide (TiO2) and Copper oxide (CuO). The governing flow equations are nonlinear PDEs. Non-similar system of PDEs are obtained with efficient conversion variables. The dimensionless PDEs are truncated using a local non-similarity approach up to third level and numerical solution is evaluated using MATLAB built-in-function bvp4c. Artificial Neural Networks (ANNs) simulation approach is used to trained the networks to predict the solution behavior. Thermal boundary layer improves with the enhancement in the value of Rd. The accuracy and reliability of ANNs predicted solution is addressed with computation of correlation index and residual analysis. The RMSE is evaluated [0.04892, 0.0007597, 0.0007596, 0.01546, 0.008871, 0.01686] for various scenarios. It is observed that when concentration of hybrid nanoparticles increases then thermal characteristics of the Eyring-Powell Hybrid Nanofluid (EPHNFs) passing a horizontal cylinder.