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Worldwide, nitrogen (N) deficiency is the main yield limiting factor owing to its losses via leaching and volatilization. Urease inhibitors slow down urea hydrolysis in soil by inhibiting urease enzyme activities whereas gibberellic acid is growth regulator. That is why, we evaluated the role of urease inhibitor [N-(n-butyl)thiophosphorictriamide (NBPT)] and gibberellic acid (GA 3 ) in improving nitrogen uptake and yield of maize under different N levels (120 and 150 kg ha −1 ) along with control. Both N levels alone and in combination with GA 3 and NBPT significantly increased yield and yield components of maize over control. In addition, 150 kg N ha −1 + NBPT + GA 3 produced highest biological, grain, and stover yields, 1000 grain weight, plant height, and N uptake exhibiting 33.15%, 56.46%, 27.56%, 19.56%, 23.24%, and 78% increase over 150 kg N ha −1 , respectively. The sole use of gibberellic acid or NBPT with each level of N also improved the yield and yield components of maize compared to sole N application and control. Furthermore, application of 120 kg N ha −1 along with NBPT and GA 3 performed at par to 150 kg N ha −1 + NBPT + GA 3 but it was superior than sole applied 150 kg N ha −1 for all the studied traits. These results imply that application of GA 3 and/or NBPT can reduce dependence on urea and improve the yield and N uptake in maize by slowing urea hydrolysis in calcareous soils and shall be practiced.

Phosphate-solubilizing bacteria (PSB) reduce the negative effects of soil calcification on soil phosphorus (P) nutrition. In this incubation study, we explored the ability of PSB (control and inoculated) to release P from different P sources [single super phosphate (SSP), rock phosphate (RP), poultry manure (PM) and farm yard manure (FYM)] with various soil lime contents (4.78, 10, 15 and 20%) in alkaline soil. PSB inoculation progressively enriched Olsen extractable P from all sources compared to the control over the course of 56 days; however, this increase was greater from organic sources (PM and FYM) than from mineral P sources (SSP and RP). Lime addition to the soil decreased bioavailable P, but this effect was largely neutralized by PSB inoculation. PSB were the most viable in soil inoculated with PSB and amended with organic sources, while lime addition decreased PSB survival. Our findings imply that PSB inoculation can counteract the antagonistic effect of soil calcification on bioavailable P when it is applied using both mineral and organic sources, although organic sources support this process more efficiently than do mineral P sources. Therefore, PSB inoculation combined with organic manure application is one of the best options for improving soil P nutrition.

Research in industrial grid energy management is essential due to increasing energy demands, rising costs, and the integration of renewable sources. Efficient energy management can reduce operational costs, enhance grid stability, and optimize resource allocation. Addressing these challenges requires advanced techniques to balance supply, demand, and storage in dynamic industrial settings. In this study, a new hybrid algorithm is used for system modelling and low-cost, optimal management of Micro Grid (MG) networked systems. Optimizing micro-sources to reduce electricity production costs through hourly, day-ahead, and real-time scheduling was the process’ primary goal.This research proposes a Quadratic Interpolation and New Local Search for Greylag Goose Optimisation (QI-NLS-G2O) and Gaussian Radius Zone Perceptron Net (GRZPNet) technique based energy management scheme for Multi-Energy Microgrids (MEMG) to help the Energy Management System (EMS) formulate optimal dispatching strategies under Renewable Energy Source (RES) uncertainty. To precisely represent the MEMG’s operational state, the scheduling process incorporates an off-design performance model for energy conversion devices. Utilising MG inputs such as Wind Turbines (WT), Photovoltaic arrays (PV), and battery storage with associated cost functions, the GRZPNet learning phase based on QI-NLS-G2O is utilised to forecast load demand. The QI-NLS-G2O optimises the MG configuration according to the load demand. The MATLAB/Simulink working platform is used to implement the suggested hybrid technique, which is then contrasted with alternative approaches to solving problems.The proposed model significantly improves dispatching accuracy, reducing RES uncertainty impacts by approximately 15% and enhancing MEMG performance efficiency by up to 20% in simulations.

The change in transportation efficiency in the last several years has seen several new engine technologies like EVs and HEVs being more prevalent. Integration of RES wind energy technique, solar photovoltaics, and bio-energies becomes a requirement during the transition from conventional houses to smart houses and from conventional cars for energy efficient electric or hybrid vehicles. The battery of an HEV can only be charged to a certain level and similarly it should not be discharged beyond a certain limit, hence the battery state of charge (SOC) in HEVs has to be supervised by a smart battery management system (BMS). However, the current method requires improvement of the performance of SOC estimate on HEVs. Therefore, development of new SOC estimation method with DL for safe renewable energy management (REM) framework for Hybrid EV (Electric vehicles) is the prime focus of this paper is developed as DLSOC-REM. For more accurate SOC estimate, the proposed approach employs a Quaternion Generative Adversarial Network (QGAN) model. When hyper parameter tuning, the prototype is invigorated employing the Tyrannosaurus optimization algorithm (TOA) to fine-tune SOC estimate outcomes of the QGAN model. Using the QGAN model simplifies the modeling process and gives a correct representation of the battery model’s input–output relationship. The work’s originality is demonstrated by the design of the TOA-based QGAN model for SOC estimation. The suggested approach shows excellent accuracy with few errors for various drive cycles and temperatures: for US06, the RMSE stabilizes at about 0.05%, the MAE drops to 0.1%, and the MSE reaches 0.0025%.

Extreme environmental conditions seriously affect crop growth and development, resulting in substantial reduction in yield and quality. However, chitin-binding proteins (CBP) family member plays a crucial role in eliminating the impact of adverse environmental conditions, such as cold and salt stress. Here, for the first time it was discovered that (Capana08g001237) gene of pepper ( L.) had a role in resistance to heat stress and physiological processes. The full-length open-reading frame (ORF) of (606-bp, encoding 201-amino acids), was cloned into TRV2: vector for silencing. The gene carries heat shock elements (HSE, AAAAAATTTC) in the upstream region, and thereby shows sensitivity to heat stress at the transcriptional level. The silencing effect of in pepper resulted in increased susceptibility to heat and infection. This was evident from the severe symptoms on leaves, the increase in superoxide (O ) and hydrogen peroxide (H O ) accumulation, higher malondialdehyde (MDA), relative electrolyte leakage (REL) and lower proline contents compared with control plants. Furthermore, the transcript level of other resistance responsive genes was also altered. In addition, the -overexpression in showed mild heat and drought stress symptoms and increased transcript level of a defense-related gene ( ), indicating its role in the co-regulation network of the plant. The -overexpressed plants also showed a decrease in MDA contents and an increase in antioxidant enzyme activity and proline accumulation. In conclusion, the results suggest that gene plays a decisive role in heat and drought stress tolerance, as well as, provides resistance against by reducing the accumulation of reactive oxygen species (ROS) and modulating the expression of defense-related genes. The outcomes obtained here suggest that further studies should be conducted on plants adaptation mechanisms in variable environments.

Drought stress restricts the growth of okra (Abelmoschus esculentus L.) primarily by disrupting its physiological and biochemical functions. This study evaluated the role of Ascophyllum nodosum extract (ANE) in improving the drought tolerance of okra. Drought stress (3 days (control), 6 days (mild stress), and 9 days (severe stress)) and 4 doses of ANE (0, 0.1%, 0.2%, and 0.3%) were imposed after 30 days of cultivation. The results indicate that drought stress decreases the chlorophyll content (total chlorophyll, chlorophyll a, chlorophyll b, and carotenoid) but increases the activity of anthocyanin, proline, and antioxidant enzymes such as ascorbate peroxidase (APX), peroxidase (POD), and catalase (CAT). Physiological and biochemical plant disturbances and visible growth reduction in okra under drought stress were significantly decreased by the application of ANE foliar spray. ANE spray (0.3%) significantly increased the chlorophyll abundance and activity of anthocyanin, proline, and antioxidants (APX, POD, and CAT). ANE regulated and improved biochemical and physiological functions in okra under both drought and control conditions. The results of the current study show that ANE foliar spray may improve the growth performance of okra and result in the development of drought tolerance in okra.

A High step-up modified SEPIC converter is proposed in this research work with Sun Flower Optimization (SFO) based maximum power tracing controller under dynamic operating condition to trace maximum power from solar PV. The proposed converter is designed to perform under various working conditions like steady state condition, variable solar irradiance condition and variable load condition. The proposed converter is designed to handle a 100W, 24 V solar panel. The maximum voltage conversion ratio achieved by this converter is 7.92 and output voltage yielded is 190 V. The maximum conversion efficiency achieved by this converter is 95.63%. This converter finds application in multi-source fed hybrid electric vehicle applications. The simulation analysis is carried out using MATLAB/R2022a Simulink tool and the real time experimental prototype is implemented in the laboratory to validate the simulation and theoretical analysis.

Power losses and voltage deviations in distribution power networks (DPNs) are high since they carry more power demand than transmission power networks. Also, voltage deviation beyond the allowable range causes voltage stability problems in the DPN. The power loss (PL) in the DPN should be kept at the minimum level for the economic operation of the electric grid. Integrating distributed generation (DG) in appropriate sites of the power networks can minimize the power losses and voltage drops. An integrated optimization approach is proposed in this paper, by combining an analytical and metaheuristic algorithm to optimize the placement and sizing of multiple DGs. The active power loss sensitivity (APLS) index is an analytical mathematical computation approach used to identify the optimal bus locations for DG placement. The modified ant lion optimization (MALO) algorithm is applied to optimize the ratings of the DG systems. The MALO algorithm is proposed by adopting the Lévy flights (LF) pattern in the random walk process (RWP). LF representation of RWPs enhances the exploration phase of the ALO algorithm and helps to obtain the near-optimal solution. The proposed integrated approach optimizes multiple units of photovoltaic (PV) and wind turbine (WT) units to minimize the multi-objective function, including AP loss and voltage deviation (VD) minimizations. The effectiveness of the proposed integrated approach is validated on the IEEE 69-bus, 85-bus, and 118-bus radial DPNs. Besides, the simulation study is extended for ant lion optimization (ALO), BAT, and artificial bee colony (ABC) algorithms-based techniques. The integrated approach has reduced the total AP loss of the IEEE 69-bus and 85-bus radial DPN from 225 kW to 70.51 kW and 316.12 kW to 162.80 kW, respectively, for the optimized three PV DG units allocation. Likewise, the total AP loss of the 118-bus radial DPN is cut down from 1296.3 kW to 432.3 kW after the optimized five PV DG units allocation. Meanwhile, the total AP LOSS of the 69-bus, 85-bus, and 118-bus radial DPNs is reduced to 4.78 kW, 53.87 kW, and 112.2 kW, respectively, after the optimized WT DG allocation. Additionally, the optimized inclusion of multiple DG units significantly minimized the VD of the DPNs. The minimum VD of the 69-bus, 85-bus, and 118-bus test systems is reduced from 0.0908 p.u., 0.1297 p.u., and 0.1312 p.u. to 0.0174 p.u., 0.0384 p.u., and 0.0201 p.u., respectively, for the multiple PV unit allocations. Similarly, the minimum VDs of the 69-bus, 85-bus, and 118-bus radial DPNs are minimized to 0.0048 p.u., 0.0190 p.u., and 0.0093 p.u., respectively, following the multiple WT DG unit allocations. The simulation findings of the APLS-MALO integrated approach are related to the various optimization techniques. The comparative study reveals that the proposed integrated approach gives a more effective and efficient solution than ALO, BAT, ABC, and other optimization techniques. Finally, the simulation findings of the APLS-MALO integrated technique are verified via the calculation of conventional statistical metrics and the conduction of a non-parametric Wilcoxon test.

Present research deals with the thermo-mechanical analysis of the butt joint plate and weld pool characteristics of the bead on plates fabricated using A-TIG and conventional TIG process. A square butt joint was welded using P91 steel of 4 mm thickness plates, employing in-house developed oxide flux. Thermal cycles induced during the welding was recorded with thermocouple, and residual stress produced in both plates was measured using the XRD method. It is observed that A-TIG produces less detrimental effects than the conventional TIG. Concentrated heat intensity is observed during the A-TIG with the narrow and deep penetration depth dispersed with lesser heat to base metal than the TIG welded joint. Comparison of bead on plate showed that FZ and HAZ increase to 10% and 34% more widely in the TIG welding process. The maximum stress value in the A-TIG welding process reached up to 471 MPa near the weld bead, whereas in the TIG welding, it was 509 MPa with 8% reduction in stress value. Reduction in distortion is also observed in the case of A-TIG, with a 36% reduction in values. Distortion in the weld plate is also compared with predicted results. FEM-based simulation is performed for both processes using the SYSWELD. Combined double ellipsoidal with conical heat source model was used for A-TIG and double ellipsoidal model was used for conventional TIG welding. Based on the comparison of the results, it can be concluded that the predicted results are approximately near to experimental measured values for thermal and mechanical results. It is observed that A-TIG plate induced less distortion and stress than the conventional TIG process.

Refrigeration methods in secluded regions are a major issue for sustaining the quality of perishables like vaccines and food. Traditional refrigeration systems, including kerosene and gas-powered units, often suffer from interruptions in the supply of fuel. Additionally, they do not satisfy the stringent criteria set by the World Health Organization (WHO) Performance, Quality and Safety (PQS) system requirements. While solar-powered refrigeration is an alternative, existing systems heavily rely on battery storage, which increases maintenance, costs, and limits system lifespan. This study analyses the operational efficiency of a solar-powered VISI cooler with a DC compressor-based refrigeration system, adding and omitting phase change materials (PCM). The experimental findings demonstrate that incorporating PCM significantly enhances energy efficiency by reducing average power consumption from 48 to 40 W. This decreased power consumption increases suction pressure by 0.13 bar and decreases compressor output pressure by 0.76 bar. These improvements aid in optimised thermal regulation which lowers dependency on conventional energy storage methods. The research indicates the role of collaborative partnerships between governments, research bodies, and technology developers aimed at fostering sustainable and innovative peak-shaving refrigeration solutions geared towards off-grid systems.