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Technological advancements have led to an increased use of the internet of things (IoT) to enhance the resource use efficiency, productivity, and cost-effectiveness of agricultural production systems, particularly under the current scenario of climate change. Increasing world population, climate variations, and propelling demand for the food are the hot discussions these days. Keeping in view the importance of the abovementioned issues, this manuscript summarizes the modern approaches of IoT and smart techniques to aid sustainable crop production. The study also demonstrates the benefits of using modern IoT approaches and smart techniques in the establishment of smart- and resource-use-efficient farming systems. Modern technology not only aids in sustaining productivity under limited resources, but also can help in observing climatic variations, monitoring soil nutrients, water dynamics, supporting data management in farming systems, and assisting in insect, pest, and disease management. Various type of sensors and computer tools can be utilized in data recording and management of cropping systems, which ensure an opportunity for timely decisions. Digital tools and camera-assisted cropping systems can aid producers to monitor their crops remotely. IoT and smart farming techniques can help to simulate and predict the yield production under forecasted climatic conditions, and thus assist in decision making for various crop management practices, including irrigation, fertilizer, insecticide, and weedicide applications. We found that various neural networks and simulation models could aid in yield prediction for better decision support with an average simulation accuracy of up to 92%. Different numerical models and smart irrigation tools help to save energy use by reducing it up to 8%, whereas advanced irrigation helped in reducing the cost by 25.34% as compared to soil-moisture-based irrigation system. Several leaf diseases on various crops can be managed by using image processing techniques using a genetic algorithm with 90% precision accuracy. Establishment of indoor vertical farming systems worldwide, especially in the countries either lacking the supply of sufficient water for the crops or suffering an intense urbanization, is ultimately helping to increase yield as well as enhancing the metabolite profile of the plants. Hence, employing the advanced tools, a modern and smart agricultural farming system could be used to stabilize and enhance crop productivity by improving resource use efficiency of applied resources i.e., irrigation water and fertilizers.

Rapid population growth, rising food demand, and climate change have created significant challenges to meet the water demands for agriculture. Effective irrigation water management is essential to address the world’s water crisis. The transition from conventional, frequently ineffective gravity-driven irrigations to contemporary, pressure-driven precision irrigation methods are explored in this article, addressing the difficulties associated with water-intensive irrigation, the possibility of updating conventional techniques, and the developments in smart and precision irrigation technologies. This study comprehensively analyses published literature of 150 articles from the year 2005 to 2024, based on titles, abstract, and conclusions that contain keywords such as precision irrigation scheduling, water-saving technologies, and smart irrigation systems, in addition to providing potential solutions to achieve sustainable development goals and smart agricultural production systems. Moreover, it explores the fundamentals and processes of smart irrigation, such as open- and closed-loop control, precision monitoring and control systems, and smart monitoring methods based on soil data, plant water status, weather data, remote sensing, and participatory irrigation management. Likewise, to emphasize the potential of these technologies for a more sustainable agricultural future, several smart techniques, including IoT, wireless sensor networks, deep learning, and fuzzy logic, and their effects on crop performance and water conservation across various crops are discussed. The review concludes by summarizing the limitations and challenges of implementing precision irrigation systems and AI in agriculture along with highlighting the relationship of adopting precision irrigation and ultimately achieving various sustainable development goals (SDGs).

Exploration of clean and renewable energy materials is necessary due to the coming energy crisis and environmental problems. Solar energy is one of the favorable energy sources because of the continuous energy reservoir and its affluence. Silicon-based solar devices are expensive due to their complicated production process, which limits this technology for urban and other commercial applications. Among the third generation of solar cells, Dye-Sensitized Solar Cells (DSSCs) have attracted widespread attention as potential cost-effective alternatives to silicon-based solar cells. In this paper, the commercializing potential of the DSSCs is investigated. A module is introduced where the materials, equipment, and distribution of direct manufacturing costs are calculated. The manufacturing costs and the Levelized Cost of Energy (LCOE) of these DSSCs for a system lifetime of 25 years were determined to be USD 22.40 per m2 and USD 0.0438 per kWh and the module price of this technology is USD 0.18 per W and the total installed system cost is USD 0.88 per W in Kansas which suggest that this PV technology could challenge other leading PV technologies.

Graphene has unique properties for improving soil health properties such as nutrient availability, soil physical and chemical properties, and controlled release of essential elements. This research aimed at determining the impact of graphene amendment on the decomposition of oil palm frond mulching and on soil health status. The study was conducted using a factorial experiment in completely randomized design with two main factors: (i) covering conditions: cover with plastic sheet and no cover, and (ii) graphene application that included T1 (control): oil palm frond mulching (OFM), T2: OFM + graphene (G), T3: OFM + G + chemical fertilizer, and T4: OFM + G + goat manure. The results indicated that there were significant differences among graphene applications, between cover conditions, and in interactions between graphene applications and cover conditions for all soil characteristics in the most observed month. In the third month of soil analysis, the treatment of graphene applications showed higher electrical conductivity (T2: 151.7 ± 6.8 µS cm −1 ), available phosphorus (T3: 9.0 ± 6.7 mg kg −1 ), exchangeable potassium (T2: 67.1 ± 24.9 mg kg −1 ), and exchangeable calcium (T3: 95.4 ± 5.1 mg kg −1 ), compared to control. The cover condition showed suitable soil pH (5.0 ± 0.2), higher soil available phosphorus (7.1 ± 5.0 mg kg −1 ), and exchangeable calcium (599.1 ± 235.2 mg kg −1 ), but the no-cover condition presented higher soil organic matter (0.7% ± 0.2%), exchangeable potassium (60.3 ± 19.1 mg kg −1 ), and exchangeable magnesium (96.7 ± 11.4 mg kg −1 ). Correlation results indicated that most soil characteristics were correlated under graphene applications. Principal component analysis showed that the treatments of graphene application dominated most soil characteristics. The results suggest that graphene has potential for improving soil health properties and can be applied as an alternative sustainable amendment to accelerate the decomposition of oil palm frond mulch and enhance nutrient availability for oil palm. In addition, the authors suggest that further investigations should consider more soil health parameters in long-term field studies for a better understanding and to provide recommendations to farmers.

SARS-CoV-2 (severe acute respiratory syndrome causing coronavirus 2) caused an epidemic that swept the globe and resulted in large number of casualties. It is still sporadically causing cases and has a long-term impact on the health of once infected individuals. Molnupiravir binds RNA dependent RNA polymerase (RdRp) of SARS-CoV-2 as well as spike protein. In this study, we assessed the mutated spike protein of BA.5 variant and BQ.1.1 subvariant of COVID-19 and tested their binding with it. Multiple sequence and structural alignment of homologous structures revealed highly conserved amino acid residues at the active site of the domain. The molecular docking of Molnupiravir with the active site of the domain, comprised conserved motifs (motif A-G), and exhibited considerable binding affinity against variant and subvariant protein targets. Molnupiravir exhibited stability in its interactions with the Omicron and BQ.1.1 spike proteins, preserving constant engagement within the active site. The protein and Ligand reached An equilibrium with An RMSD of 10.46 Å after 100 nanoseconds, whereas the Ligand measured 8.0 Å. Fluctuations were noted between 40 And 75 nanoseconds, stabilizing from 80 to 100 ns. In simulations including the BQ.1.1 subvariant, the RMSD values demonstrated considerable stability, exhibiting Little variations. The ligand demonstrated flexibility, altering its binding orientation over time, resulting in An average RMSD of 18.72 Å. Herein, investigation of molecular dynamics trajectories elucidated the conformational stability of Molnupiravir, emphasizing its interactions with active residues and the hydrogen bond acceptor and donor environments. The results highlighted the crucial function of protein loops in offering flexibility and enabling ligand binding within the active site. It is concluded that Molnupiravir has the potential to function as an inhibitor of both omicron and its subvariant BQ.1.1.

Effective residue management is crucial for maintaining soil organic carbon (SOC) in upland rice systems, particularly under diverse fertilization and planting management practices. This study investigates the impacts of residue management in upland rice fields using the CQESTR model through simulation of SOC dynamics over a 20-year period. The first 10 years served as a spin-up period for carbon pool stabilization in the model, followed by simulations under varying nitrogen (N) application rates and planting date management strategies. Experiments for various N application rates and planting times were conducted during 2018–2019 and 2019–2020. In 2019, 30% and in 2020, 100% of the residue was returned, and these data were used for evaluating model performance. Subsequently, we modeled predictions for residue retention levels of 100%, 70%, 50%, and 30% to assess their effects on SOC. The results indicated a good agreement between the simulated and observed data for model performance evaluation with an MSD value of 9.13. Lack of correlation (0.44) accounted for 5% of MSD, indicating a good agreement between the simulated and observed SOC values. The highest change in SOC was observed at 100% residue return under moderately delayed planting, potentially due to higher crop productivity and residue retention, and moderate climatic conditions. Reduced residue retention gradually declined the SOC stocks, especially under low N input. Delays in planting exacerbated negative impacts, possibly due to low crop productivity and reduced residue return. Despite the limited number of years of data and inconsistent management practices, the overall trends highlight the importance of residue retention under different N fertilization and planting management strategies. This research serves as a preliminary study for sustainable management practices to enhance long-term soil carbon sequestration in upland rice systems in southern Thailand. Long-term evaluations are necessary using the observed data and the CQESTR model application for applicable recommendations.

We investigate the mechanism associated with the severity of COVID-19 in men with TLR7 mutation. Men with loss-of-function (LOF) mutations in TLR7 had severe COVID-19. LOF mutations in TLR7 increased the risk of critical COVID by 16.00-fold (95% confidence interval 2.40–106.73). The deleterious mutations affect the binding of SARS-CoV2 RNA (− 328.66 ± 26.03 vs. − 354.08 ± 27.70, p  = 0.03) and MYD88 (β: 40.279, p  = 0.003) to TLR7 resulting in the disruption of TLR7-MyD88-TIRAP complex. In certain hypofunctional variants and all neutral/benign variants, there is no disruption of TLR7-MyD88-TIRAP complex and four TLR7 agonists showed binding affinity comparable to that of wild protein. N-acetylcysteine (NAC) also showed a higher binding affinity for the LOF variants ( p  = 0.03). To conclude, TLR7 LOF mutations increase the risk of critical COVID-19 due to loss of viral RNA sensing ability and disrupted MyD88 signaling. Majority of hypofunctional and neutral variants of TLR7 are capable of carrying MyD88 signaling by binding to different TLR7 agonists and NAC.

Rice is an important cereal and drought stress is a critical abiotic stress that negatively influences the performance and productivity of rice crop, particularly under a changing climate scenario. The objectives of this study were to evaluate the impacts of drought stress on grain productivity and water use efficiency of rice cultivars and to assess the genotypic variability among the tested cultivars. Two irrigation treatments including a control and drought stress were applied to the experiments during 2018–2019 and 2019–2020. The statistical evaluation included a comparison of means, genotypic and phenotypic coefficients of variation, path analysis, correlation assessment, hierarchical clustering of tested cultivars and principal component analysis. The results indicated that drought stress negatively affected the grain productivity of the rice cultivars. The grain productivity of the cultivars decreased, ranging between 21–45% and 21–52% in the first and second season, respectively. Similarly, water use efficiency was significantly decreased ranging between 7–53% and 21–55% during the first and the second season, respectively. The broad-sense heritability for grain productivity was differed under control and drought stress treatment, indicating that the chances of the transfer of grain-productivity-related traits could be affected during selection for stress tolerance. The correlation assessment indicated that the intensity of association among the evaluated parameters was higher under the control treatment. A maximum direct effect was observed by water consumption (1.76) under control whereas, by water use efficiency (1.09) under drought stress treatment on grain productivity in path analysis. Considering the water use efficiency as a desired trait for selection in path analysis, a maximum direct effect was observed by grain productivity under the control (0.68) and under drought treatment (0.88). Hom Pathum and Pathum Thani−1 were identified as highly tolerant cultivars in the hierarchical clustering and principal component analysis. It was concluded that the results obtained for the assessment of drought stress on grain productivity, water use efficiency and genotypic variability among these cultivars could be utilized in selection program for stress tolerance and the stress tolerant cultivars could be used for sustaining grain productivity to reduce the impacts of climate change.

Synchronizing nitrogen (N) fertilization with planting date (PD) could enhance resource use efficiency and profitability of upland rice ( Oryza sativa L.) production in Thailand. The objective of the study was to assess upland rice responses to four N fertilization rates (NFRs) and three planting dates. Field experiments were conducted during two growing seasons under four NFRs, no N applied (N 0 ), 30 (N 30 ), 60 (N 60 ), and 90 kg N ha −1 (N 90 ), and NFR were applied at the initiation of tillering and panicle emergence stages. The planting dates selected were early (PD1), intermedium (PD2), and late planting (PD3) between September and December of each season. The NFRs and planting dates had a significant influence on N uptake, N use efficiency (NUE), crop water productivity, yield and yield attributes, and profitability of upland rice production. A linear relationship among NFRs, agronomic traits of upland rice, N uptake, and crop water productivity was observed, and a significant seasonal effect was indicated. Fertilization at N 90 under PD2 enhanced yields, yield attributes, and grain yields, as well as crop water productivity by 56 and 105% during the second and first seasons, respectively. Grain N, total N, and straw N were increased by 159, 159, and 160%, and by 90, 114, and 153%, during the first and second seasons, respectively. Enhanced N efficiencies, including agronomic efficiency, recovery efficiency, partial factor productivity, and N harvest index, at varying NFRs were observed under PD2 during both seasons. Highly significant ( p < 0.001) and positive associations were observed among agronomic attributes, N uptake, NUE, and crop water productivity of upland rice in correlation assessment. Profitability from grain yields was observed with N fertilization and N 90 resulted in maximum profit under all the PDs. However, the highest marginal benefit-cost ratio was observed at N 60 under PD2 during both seasons. The results suggest that the NFR of 90 kg N ha −1 and planting at the end of September or start of October would enhance resource use efficiency and productivity, and maximize profitability. Furthermore, long–term field investigations with a range of NFRs and adopting forecasting measures to adjust the planting date for upland rice are recommended.

Background In November 2019, the world faced a pandemic called SARS-CoV-2, which became a major threat to humans and continues to be. To overcome this, many plants were explored to find a cure. Methods Therefore, this research was planned to screen out the active constituents from Artemisia annua that can work against the viral main protease Mpro as this non-structural protein is responsible for the cleavage of replicating enzymes of the virus. Twenty-five biocompounds belonging to different classes namely alpha-pinene, beta-pinene, carvone, myrtenol, quinic acid, caffeic acid, quercetin, rutin, apigenin, chrysoplenetin, arteannunin b, artemisinin, scopoletin, scoparone, artemisinic acid, deoxyartemisnin, artemetin, casticin, sitogluside, beta-sitosterol, dihydroartemisinin, scopolin, artemether, artemotil, artesunate were selected. Virtual screening of these ligands was carried out against drug target Mpro by CB dock. Results Quercetin, rutin, casticin, chrysoplenetin, apigenin, artemetin, artesunate, sopolin and sito-gluside were found as hit compounds. Further, ADMET screening was conducted which represented Chrysoplenetin as a lead compound. Azithromycin was used as a standard drug. The interactions were studied by PyMol and visualized in LigPlot. Furthermore, the RMSD graph shows fluctuations at various points at the start of simulation in Top1 (Azithromycin) complex system due to structural changes in the helix-coil-helix and beta-turn-beta changes at specific points resulting in increased RMSD with a time frame of 50 ns. But this change remains stable after the extension of simulation time intervals till 100 ns. On other side, the Top2 complex system remains highly stable throughout the time scale. No such structural dynamics were observed bu the ligand attached to the active site residues binds strongly. Conclusion This study facilitates researchers to develop and discover more effective and specific therapeutic agents against SARS-CoV-2 and other viral infections. Finally, chrysoplenetin was identified as a more potent drug candidate to act against the viral main protease, which in the future can be helpful.