Stability Index Research Articles

Wild introgression as an effective tool for aiding the expansion and adaptation of cultivated safflower

AbstractSafflower is a multipurpose crop grown in different regions, mainly for its high oil quality. Crop wild relatives serve as a valuable reservoir of genes that have been depleted due to evolutionary bottlenecks, which are poorly applied in safflower. During the last decade, we developed three populations from hybridization of safflower with its wild relatives and selected the superior lines to develop new varieties. From each of three different interspecific populations (TP: Carthamus tinctorius × Carthamus palaestinus, PO: C. palaestinus × Carthamus oxyacantha, and TO: C. tinctorius × C. oxyacantha), 10 genotypes were selected (a total of 30 lines) in the “F8” generation and were evaluated along with their parents (T, P, and O) and one control cultivar (Golsfid) at the field during 2019–2022 to assess genetic variation, estimate genetic parameters, and evaluate the stability. Considerable genetic variability for oil, seed yield, and other agronomic traits between and within the interspecific populations suggests the high potential of these new recombinant lines for introducing beneficial alleles. Our results indicated that recombinant inbred lines derived from the hybridization of TP were superior in terms of seed yield, oil content, and stability parameters. The use of stability indices of Wricke, Lin and Binns, Eberhart and Russell, and HMRPGVi, along with the biplot analysis, allowed the identification of preferable and stable safflower genotypes. Moderately high values of heritability were found for yield‐related traits. New recombinant lines can be introduced to the safflower gene pool to improve the genetic base of this valuable oil seed crop.

Investigating the performance of PBL parametrizations in WRF model for front enhanced SES simulation in istanbul megacity

Sea-effect snow (SES) is a meteorological phenomenon resulting from cold air moving over warmer waters. Accurate prediction of SES is vital for emergency management, transportation, and water resource planning. A thundersnow event in Istanbul from 17–19 February 2015 caused significant disruptions, with traffic and flights affected, highways temporarily closed, and trees falling due to heavy snowfall. This study investigates the influence of different parameterization schemes in the Weather Research and Forecasting (WRF) model on SES simulations. Six distinct PBL parameterization schemes were used in a series of WRF simulations. In addition, the following factors pivotal to SES event have also been investigated: 1000–500 hPa thickness, total and latent heat fluxes, radar and satellite analyses, temperature gradients, wind shear, inversion levels, and atmospheric stability indices. Additionally, the formation of SES during the cold front transition further contributed to these elements in the Black Sea region. The simulations displayed notably high total heat flux and latent heat flux values, particularly following the passage of the cold front. Furthermore, the northeast-southwest oriented SES cloud, distinguished by its banded structure, was successfully validated using radar and satellite imagery. However, it's worth noting that the model positioned it farther west than its actual location. This study highlights the challenges in precise prediction and analysis of such convective activities. In this thundersnow event, the local closure schemes, particularly MYNN in first place and second MYJ, demonstrated superior performance compared to non-local schemes within the parameterization options.

Fabrication of ultrafine Himalayan walnut oil Pickering emulsions by ultrasonic emulsification: Techno-functional properties of emulsions and microcapsules

In present scenario, much of the attention has been put on the production and utilization of Pickering emulsions deciphering enhanced stability and applicability over wide environmental conditions. In this context the present study was carried out to elaborate effect of different wall materials and pH systems on the physicochemical, structural and morphological properties of Himalayan walnut oil Pickering emulsions by ultrasonic emulsification. In this study, concentrated Pickering emulsion of Himalayan walnut oil (HWO) was prepared utilizing soy protein isolate (SPI), maltodextrin (MD) stabilized by pectin at varying concentrations and pH systems (4.0, 7.0). With increase in pectin and SPI concentration and lowering MD, stable emulsions were obtained as deciphered by an Emulsion stability index (ESI) of 100 for 7 days at ambient storage. HWO Pickering emulsions were analysed for particle size measurements (2.13–13.64 µm) and depicted negative zeta potential values (−3.70 to −18.58). Lyophilized HWO microcapsules depicted moderate encapsulation efficiency (44.69–57.63 %) whereas the hygroscopicity values of the microcapsule ranged from (0.21–12.10 %). Thermogravimetric analysis (TGA) of the samples depicted the temperature of maximum degradation rate up to 550 °C whereas XRD spectra depicted amorphous nature of oil microcapsules. FTIR spectra revealed a close association between the SPI-MD-Pectin matrix. SEM analysis revealed stable oil globules entrapped in protein-polysaccharide matrix with no visible cracks and fissures.

Study on Characteristics of Soil Profile Stability Indexes in Sakita

This research examines the suitability of soil as infrastructure which can help in the classification and identification of its properties for ideal engineering structures. Sakita, an area in Gesse III as a case study, is a virgin land, allocated for residential buildings. The need to investigate the soil profile in the report area prompted these studies as its physical properties are used for classifying its various engineering applications. These properties indicate qualitative behaviors of soil when subjected to various types of loads. Apart from physical/visual observation made of the soil, trial pits were dug to depths of 0.5m, 1.0m, 1.5m, 2.0m, and 2.5m respectively and disturbed soil samples were taken for tests. The disturbed soil samples obtained were analyzed for grading including mechanical sieve analysis, specific gravity, plastic limit, liquid limit, and bulk density tests. The resistances of the cone against penetration, compaction, consolidation, and permeability properties were also assessed. The detected geotechnical properties varied significantly with depth, except for specific gravity, which did not vary significantly at 0.5 m with depth. Soil samples from all pits consist mainly of poorly sorted gravel and sand with little fineness. They contain a medium- to coarse-grained fraction of sand on average above 85%. The puncture resistance obtained from the cone puncture test ranges from 100 knm2 to 950 knm2. The average safe bearing capacity estimated for the footing using a factor of safety of 3 at a depth of 1 m was not less than 473 km2 anywhere in the study area. The samples from the three locations generally have good compaction parameters, medium to high permeability, and low compressibility. The highest load-bearing capacity is associated with the lateralized basement ceiling. This means that the safety depth for placing infrastructure foundations in the prescribed research area (Sakita) is the depth where it meets the lateralized basement.

Stabilizing and Accelerating Federated Learning on Heterogeneous Data With Partial Client Participation.

Federated learning (FL) commonly encourages the clients to perform multiple local updates before the global aggregation, thus avoiding frequent model exchanges and relieving the communication bottleneck between the server and clients. Though empirically effective, the negative impact of multiple local updates on the stability of FL is not thoroughly studied, which may result in a globally unstable and slow convergence. Based on sensitivity analysis, we define in this paper a local-update stability index for the general FL, as measured by the maximum inter-client model discrepancy after the multiple local updates that mainly stems from the data heterogeneity. It enables to determine how much the variation of client's models with multiple local updates may influence the global model, and can also be linked with the convergence and generalization. We theoretically derive the proposed local-update stability for current state-of-the-art FL methods, providing possible insight to understanding their motivation and limitation from a new perspective of stability. For example, naively executing the parallel acceleration locally at clients would harm the local-update stability. Motivated by this, we then propose a novel accelerated yet stabilized FL algorithm (named FedANAG) based on the server- and client-level Nesterov accelerated gradient (NAG). In FedANAG, the global and local momenta are elaborately designed and alternatively updated, while the stability of local update is enhanced with help of the global momentum. We prove the convergence of FedANAG for strongly convex, general convex and non-convex settings. We then conduct evaluations on both the synthetic and real-world datasets to first validate our proposed local-update stability. The results further show that across various data heterogeneity and client participation ratios, FedANAG not only accelerates the global convergence by reducing the required number of communication rounds to a target accuracy, but converges to an eventually higher accuracy.

Application of yellow mustard gum in preparation of egg‐free mayonnaise

SummaryYellow mustard gum (YMG) is a natural hydrocolloid extracted from the viscous fraction of the seed coat, a by‐product of mustard seeds, and possesses superior emulsifying capacity in emulsions. However, there is no application of YMG for commercial products. The demand for vegan mayonnaise (VM) has increased in recent years and the challenge is to maintain the original consistency and taste while replacing eggs from conventional mayonnaise. To obtain high‐quality VM and to investigate the potential of YMG as a food additive, YMG was applied to VM at 0%, 0.2%, 0.4%, 0.6%, 0.8%, and 1.0% (w/w) in this study. The physical properties (index of stability, rheological properties and particle size characterisation), storage stability (visual stability, microstructure observation and cold tolerance) and texture of YMG‐formulated VM were measured and compared with commercial products to assess the quality and market prospects. The results showed that the VM obtained higher stability, more non‐Newtonian flow behaviour, and a smaller droplet size with higher YMG content. After 90 days of storage, no separation occurred in the YMG‐added VM. YMG improves the shelf‐life of VM, and mayonnaise formulated with YMG has comparative or better texture properties compared with commercial counterparts. Overall, YMG‐added VM could be more appealing to consumers favouring plant‐based foods and have the potential to substitute for traditional products. YMG is beneficial to vegan product development with clean‐label requirements.

Optimization screening, performance and mechanism analysis of green and low-carbon surfactants for oil-based drilling cuttings treatment

Oil-Based Drilling Cuttings (OBDC) have attracted extensive attention from scholars due to their high annual generation and high toxicity. At present, the thermal cleaning technology of surfactant is one of the research hotspots for treating OBDC, but it still faces the problems of high toxicity of surfactant, high carbon emission and unknown treatment mechanism. Therefore, we sequentially optimized screening the surfactants through the perspectives of greenness, treatment performance and costs, and low-carbon. A single-variable experiment was used to optimize the process parameters for treating OBDC, and the oil removal mechanism was explored by oil droplet size, TSI, Zeta potential and SARA fractions. The SLM was the most green and low carbon surfactant in this study, and had a better treatment performance for OBDC (51.56% oil removal rate). The optimal treatment parameters for SLM treatment of OBDC were 70 °C, 45 min, 300 r/min, 1:4 (solid/liquid) and pH 8.2. The lipophilic groups of SLM "striped" the asphaltenes and saturates in oil phase from the solid phase surface and "integrated" them into the water phase by its hydrophilic group. The mean value of the oil droplet sizes (Dmean) and Turbiscan stability index (TSI) value of the OBDC-water mixtures increased and the |Zeta potential| decreased after treatment, and the mixture system became more unstable, which promotes the subsequent separation of the oil phase from the solid phase.

Oil-in-water emulsion stabilized by hydrolysed black soldier fly larvae proteins: Reproduction of experimental data via phase-field modelling

A phase field model based on the Cahn-Hilliard equation was validated experimentally by comparison of the numerical data with experimental data of emulsions of oil in water stabilized with Black Soldier Fly Larvae Proteins (BSFLP) and protein hydrolysates. Among the model parameters, the surface tension was determined by the pendant drop method, and the mobility by two different experiments, one based on the Turbiscan Stability Index, and another one based on the history of the average d3,2, both of them throughout a 48 h period. The initial condition was built from an experimental droplet size distribution measured prior to phase separation. Results show that the model is able to quantitatively reproduce the phase separation kinetics, and provide an intuitive graphical representation of the droplet growth. Application of this procedure to other systems will allow the generalization of phase field modelling as a predictive tool for food applications.

Anisotropic Durgapal-Fuloria compact stars in f(R) gravity

This study presented a new exact solution for anisotropic compact stellar objects within the framework of f(R)=R+αR2 gravity. In this context, the Durgapal-Fuloria metric potential has been employed to solve the field equation derived for f(R) theory. Furthermore, we have derived the generalized Darmois-Israel junction condition necessary for seamlessly connecting the interior region to the Schwarzschild exterior metric across the boundary hypersurface of the star in the context of f(R) gravity, and the interior solution is matched with the Schwarzschild exterior metric over the bounding surface of a compact star. These junction conditions stipulate that the pressure must not be zero at the boundary and should be proportional to the non-linear terms of f(R) gravity, a crucial aspect often overlooked by many researchers when investigating compact stellar models. Additionally, we derived the values of these parameters by using observational data of various compact stars (CSs), namely Her X-1, SAX J1808.4-3658, SMC X-1, LMC X-4, Cen X-3, 4U 1820-30, PSR J1903+327, 4U 1608-52, Vela X-1, and PSR J1416-2230. This approach enables us to investigate the comprehensive analysis of solutions numerically and graphically. We conducted various physical tests, including gradient of energy density and pressures, anisotropy, stability, equilibrium conditions, energy-density constraints, mass function, compactness, redshift, and adiabatic index, to assess the feasibility of our models. Our findings demonstrate the consistent behavior of our models provides a satisfactory physical situation as far as the observational results are confirmed.

A framework for appraising the status of disaster resilience within the multi-hazard environment of coastal Bangladesh

Fostering resilience is widely acknowledged as a crucial strategy for mitigating the escalating risks posed by climate-related disasters around the world. Resilience assessment plays a vital role in this endeavour by assessing the baseline level of resilience, identifying the key resilience factors, and monitoring progress towards building resilience with time. Given this context, and considering the evolving conceptualization of resilience, we devised a framework for appraising the status of resilience across the coastal region of Bangladesh. Our framework represents a significant scholarly contribution, as it encompasses a broad spectrum of resilience dimensions, including stability, recoverability, and transformability. To operationalize this framework, we selected thirty context-specific variables and organized them systematically around these three overarching components. Employing a simple weighted average methodology, we constructed sub-indices for each component, which were subsequently aggregated into a composite resilience index. For spatial visualization, our findings were mapped in a Geographic Information System (GIS) environment. Our analysis revealed Chattogram, Barguna, and Khulna as the most resilient districts. This manifests the potential for resilience enhancement even within areas exposed and inherently sensitive to multiple hazards through the optimal use of available resources. Notably, in the trio of districts, Barguna exhibited the highest stability index score, Chattogram showcased the highest recoverability score, and Khulna emerged with the top transformability index score. This finding underscores the significance of incorporating diverse capacities in resilience frameworks. These insights offer valuable guidance for refining resilience assessment frameworks in other developing countries of the world. Furthermore, the outcomes of our assessment can serve as a baseline for the coastal administrators of Bangladesh while developing disaster management policies and actions centering around fostering resilient communities. Thus, our study not only contributes to disaster theory, but holds practical implications for evidence-based decision-making to secure a more resilient future of the coastal communities of Bangladesh.

Weld quality monitoring in friction stir lap joining of dissimilar Al6061 to polycarbonate using thrust–torque-based process stability signatures

The joining of dissimilar aluminium-based alloys to thermoplastic polymers is highly challenging which indicates the necessity of friction welding procedures. The present work addresses the degrees of steadiness in welding thrust-torque to monitor the lap weld contour of aluminium alloy (Al6061) overlapped on polycarbonate sheet or vice versa using friction stir welding. The primary objective was to compare the monitoring capability of the weld non-uniformity by using raw signals and stability signature of welding thrust and stirring torque. Further, these stability indices were used for the prediction of weld mechanical behaviour using response surface methodology. The stability signatures were found to be a better indicator of weld profile unevenness than raw signals as it was an amplified version of the local deviations in welding thrust-torque. Improved strength efficiency up to 49% was noticed in PC-Al welds due to improved process stability at intermediate tool traverse (55 mm/min) and revolving speeds (1100 rpm). The stability in stirring torque was better indicator of weld quality features than tool thrust steadiness in Al-PC lap while it was reversed in PC-Al lap. Thus, the thrust force instability was mostly indicated the joint ductility while combined steadiness in thrust-torque were essential for the prediction of weld strength. The higher stability index in tool thrust (≥7.5) with ample torque steadiness (5–8) can upgrade the Al-PC weld strength (≥20 MPa), whereas intermediate thrust stability (6–6.5) with high stable torque (≥7) can uplift the joint strength (≥25 MPa) in PC-Al welds.

Almond protein as Pickering emulsion stabilizer: Impact of microgel fabrication method and pH on emulsion stability

We evaluated the ability of almond proteins to produce Pickering emulsions (EM) stabilized by microgels (MG) fabricated by three different methods (heat treatment–HT, crosslinking with transglutaminase–TG or calcium–CA), at two pH levels (pH 3 or 7). Compared to pH 7, acidic pH significantly denatured almond proteins (ellipticity ∼0 mdeg), decreased absolute zeta potential values (10.5 to 18.6 mV at pH 3 and − 24.6 to −32.6 mV at pH 7), and free thiol content (114.64–131.60 μmol SH/g protein at pH 3 and 129.46–148.17 μmol SH/g protein at pH 7 – except in CA-crosslinked microgels, p > 0.05). These changes led to larger microgel sizes (D3,2pH3: 26.3–39.5 μm vs. D3,2pH7: 5.9–9.0 μm) with lower polydispersity (SpanpH3: ∼ 1.94 vs. SpanpH7: 2.32, excluding CA-based samples). Consequently, the Turbiscan Stability Index (TSI) was higher in acidic conditions for all emulsions, except for the calcium-containing formulation (EM_CApH3), emphasizing the critical role of calcium binding in maintaining emulsion stability in acidic environments. Microgels prepared via the traditional heat treatment method produced emulsions with intermediate stability (TSI ranging from 3.4 % to 5.1 % at 28 days of storage). Conversely, TG-crosslinked microgels led to unstable emulsions at pH 3, likely due to the lowest zeta potential (+4.2 mV), whereas at pH 7, the greatest stability was attributed to bridging flocculation that created a stable gel-like structure. Indeed, emulsions with lower TSI (EM_CApH3 = 1.8 %, EM_CApH7 = 2.3 % and EM_TGpH7 = 1.0 %, at 28 days of storage) also exhibited higher elastic modulus (G') over frequency sweep, indicating that the strong elastic network was relevant for emulsion stability (up to 28 days). This study, for the first time, demonstrated the production of stable almond-based Pickering emulsions, with properties modulated by the pH and method used to fabricate the microgels.

Multi‐Environment Analysis of Nutritional and Grain Quality Traits in Relation to Grain Yield Under Drought and Terminal Heat Stress in Bread Wheat and Durum Wheat

ABSTRACTHeat and drought are two important constraints to global wheat productivity; understanding the genotypic responses for quality parameters under harsh production conditions (drought and heat) is very important for developing nutrient‐dense wheat varieties. A set of 15 modern bread wheat (Triticum aestivum L. subsp. aestivum) and durum wheat (Triticum turgidum subsp. durum) cultivars were tested in nine environments, including three different production conditions (normal, heat and drought) during 2020–21. Genotype stability performance for yield, nutrition and quality parameters is assessed using multienvironment trials through AMMI and GGE Biplot analysis. We discovered intriguing stress dynamics in grain zinc content (Zn) and grain iron content (Fe). Under heat stress, zinc concentration increases but decreases under drought stress, while iron does the opposite. Selecting zinc, starch and kernel weight under terminal heat stress can boost yield. Protein content and yield are inversely related, making it difficult for breeders to optimise both traits. G × E interactions and stability indices across all environments have found genotypes with high‐yielding stable genotypes, G12 (MP1358) (42.09 ppm) and G5 (HI1544) (42.41 ppm) have high Fe content. G12 (MP1358) (14.98%) ranked highest in protein concentration. Meanwhile, for Zn content, G11 (MACS 4058) (45.23 ppm) and G15 (WH730) (42.44 ppm) were top performers across environments. G7 (HI 1636) and G12 (MP1358) stand out as a win‐win genotype for their high potential and stability in yield, protein, Zn and Fe content. Our study shows the complex relationships and possible suggestions for targeted breeding programmes under heat and drought stress conditions to improve wheat grain quality and micronutrient profiles without yield loss.

Comparison Between Cubic and Quadratic Models of Hydrodynamic Derivatives to the Ship Course Stability Index

Comparison Between Cubic and Quadratic Models of Hydrodynamic Derivatives to the Ship Course Stability Index

A general formula for the index of depth stability of edge ideals

By a classical result of Brodmann, the function d e p t h R / I t depthR/I^t is asymptotically a constant, i.e. there is a number s s such that d e p t h R / I t = d e p t h R / I s depthR/I^t = depthR/I^s for t > s t > s . One calls the smallest number s s with this property the index of depth stability of I I and denotes it by d s t a b ( I ) dstab(I) . This invariant remains mysterious till now. The main result of this paper gives an explicit formula for d s t a b ( I ) dstab(I) when I I is an arbitrary ideal generated by squarefree monomials of degree 2. That is the first general case where one can characterize d s t a b ( I ) dstab(I) explicitly. The formula expresses d s t a b ( I ) dstab(I) in terms of the associated graph. The proof involves new techniques which relate different topics such as simplicial complexes, systems of linear inequalities, graph parallelizations, and ear decompositions. It provides an effective method for the study of powers of edge ideals.

Does multifactorial inspiratory muscle training improve postural stability and quality of life of patients with diabetes in Pakistan? A randomised controlled trial

ObjectiveTo determine the effects of multifactorial inspiratory muscle training (IMT) combined with Otago Exercise Programme (OEP) on balance and quality of life (QoL) in patients with diabetes.MethodsPretest–post-test randomised controlled trial.SettingRehabilitation...

Graph theory-enhanced integrated distribution network reconfiguration and distributed generation planning: A comparative techno-economic and environmental impacts analysis

In today's world, eco-friendly solutions are crucial for efficient power delivery and assessing their corresponding economic and environmental benefits is essential. As innovators, it is also imperative to continually improve on existing techniques to solve a problem. Evaluating the existing literature in this area of study, gaps of improving the optimization techniques by reducing the amount of infeasible configurations the reconfiguration procedure encounters was established, additionally, the need to utilize distributed generations that significantly reduce carbon footprint in the environment was also ascertained. Hence, this paper presents an effective integration method for the simultaneous reconfiguration of Radial Distribution Networks (RDNs) and Photovoltaic (PV) DGs allocation, considering the tripodal issues of cost, operational efficiency, and environmental sustainability. A modification of the adaptive mountain gazelle optimizer (AMGO) enhanced with graph theory is deployed for the optimization procedures. The crucial feature of the proposed approach is the reduction of unfeasible configurations throughout the optimization procedure toward satisfying the network's radiality constraints, achieving consistent convergence and reduced computation time. The technical benefits are active power loss minimization, voltage stability, and voltage profile improvement. The economic benefits are analyzed by estimating the purchased power, the associated cost of power losses, and the cost of DGs and switches over a planning period of 20 years. The consequent environmental benefits are analyzed in detail, highlighting the significant reduction in pollutant emissions. The proposed model was tested on the IEEE 33- and 69-bus RDN, considering several scenarios, including synchronous network reconfiguration and DG installations. From the results procured, the simultaneous network reconfiguration and DG allocation provided better outcomes, yielding minimum active power loss of 35.36 kW, minimum voltage of 0.9541 p.u., voltage stability index of 1.9936 p.u., total planning cost of $3.456 million, and emission of 1.744 million lb/hr, respectively, for the 33-bus systems. The corresponding value for the 69-bus system is 32.57 kW, 0.9832 p.u., 2.3847 p.u., $ 2.524 million, and 2.53 million lb/hr, respectively. The proposed model was compared with other reported techniques for performance validation, and its efficacy and superior performance was established.

A recyclable dispersant based on carbomer utilizing controllable viscosity for high-efficiency dispersion of carbon fibers

Good dispersion of carbon fibers is important for the carbon paper production, which is usually achieved using low carbon fiber concentrations and disposable dispersants. In this study, we developed carbomer as a recyclable and high-efficiency dispersant for carbon fibers. When the carbon fiber concentration was 0.1 wt%, carbon fiber suspension showed improved dispersion performance as increasing the carbomer dosage. It exhibited low Turbiscan Stability Index (TSI) of 0.41 and small change of delta backscattering between −0.5 to 0.8 % when using 0.5 wt% carbomer. However, the good dispersibility fade away when increasing the concentration of carbon fibers. Subsequently, the pH of the carbon fiber suspension was adjusted to 7.0 to improve the dispersibility by increasing the viscosity, but causing a worse flowability. Then the pH was further adjusted to 13.0 to ensure good flowability in the wet-forming process and good dispersibility at carbon fiber concentration of 0.5 wt%. More importantly, the dispersant was successfully recycled and still exhibited excellent dispersion effects for carbon fibers after 5 cycles. Notably, the high-efficiency dispersion of carbon fibers and the recyclability of dispersant were achieved simultaneously for the first time, which is suitable for the eco-friendly and sustainable production of carbon paper.

The Efficiency of Seed Priming with Dead Sea Water for Improving Germination and Early Seedling Growth of Wheat (Triticum aestivum L.) under Salinity

<p>Salinity is considered the most critical environmental factor which negatively affects the germination and growth of plants. In this study, the potential of using Dead Sea water (DS) as a seed priming agent for the mitigation of the adverse effects of salinity on seed germination and growth performance of wheat (<em>Triticum aestivum</em> L.) was investigated. Germination of wheat seeds primed with different doses of DS; 0%, 5%, 10%, 15%, and 20% were evaluated under different saline conditions (0, 100, 200, and 300 mM NaCl). High salinity (300 mM NaCl) remarkably inhibited germination attributes and reduced seedling length. However, seeds primed with DS exhibited improved germination parameters and seedling growth. Among the different DS concentrations used, the 10% DS priming achieved the highest increase in final germination percentage tolerance, germination index, relative germination salt tolerance, and seedling length. The increased tolerance to salinity was associated with improved water imbibition, α-amylase activity, antioxidant capacity and osmotic homeostasis correlated with high proline and soluble sugar levels. In addition, DS priming increased the membrane stability index, and reduced malondialdehyde content and K<sup>+</sup> leakage besides lowering Na<sup>+</sup>/K<sup>+</sup> ratio. Overall, priming with DS could be a promising strategy for minimizing the damaging effects of salinity in wheat.</p>

Deciphering the stability indices using additive main effect and multiplicative interaction model for high yielding registered variety of Lemongrass (Jor Lab L-8)

Cymbopogon flexuosus, commonly known as Lemongrass (Poaceae) is an industrially significant plant due to its fragrant compounds and ability to produce a large amount of essential oil. However, variations in chemical components, agronomical characters and essential oil output can be observed due to grown in different climatic conditions. Pertaining to the economic importance of the crop, the present study was designed to evaluate the stability indices of the developed and registered variety of lemongrass ‘Jor Lab L-8’. In this experiment, cv. Jor Lab L-8 was assessed along with two check varieties at eight different locations of NE India for two years (2021-2022, 2022-2023). The analysis of variance (ANOVA) by regression method revealed that Jor Lab L-8 had a significantly higher herbage yield, essential oil yield, citral content and total essential oil yield than the other two check varieties. Furthermore, AMMI ANOVA was used to confirm the consistent performance of the recorded agro-morphological and quality characters and Jor Lab L-8 was shown to be stable in plant height, herbage yield, essential oil yield, citral content and total essential oil yield. The GC-MS study of the essential oil identified 18 constituents, with citral emerging as the predominant constituent. Additionally, majority of the locations were pinpointed as ideal environments for cultivating Jor Lab L-8, underscoring its resilience across multiple locations and highlighting its long-term industrial promise.