Measurement Of Content Research Articles

The fitness of pelargonium cuttings affects the relationship between the photochemical activity of the photosynthetic apparatus and rooting ability

Pelargoniums cultivated for ornamental purposes rely on efficient vegetative propagation. This study researched applicability of chlorophyll fluorescence for validating the physiological conditions of pelargonium cuttings. Results indicated a correlation between the chlorophyll fluorescence and rooting potential. The ET0/RC values were negatively correlated with the rooting efficiency between the varieties and the duration of cold storage. A negative correlation was observed between OJIP parameters, representing energy flow in thylakoids, and chlorophyll content in cuttings with lower nutritional status. The phenomenological energy fluxes for leaf cross-sections and the number of active PSII reaction centers in the not-excited state (RC/CS0) increase with raised chlorophyll concentration. This imply the influence of rooting ability on the demand for photoassimilates in pelargonium cuttings, which can be detected early on through chlorophyll fluorescence analysis but not chlorophyll content measurements. Chlorophyll fluorescence evaluation, along with specific OJIP test parameters such as the performance indices PIABS and PItotal, prove useful for predicting rooting efficiency in relation to the nutritional status of cuttings, suggesting the effects of cuttings cold storage and discerning varietal differences in rooting. This study establishes the pragmatic application of chlorophyll fluorescence assessment for elucidating the physiological intricacies of pelargonium cuttings and factors influencing rooting efficiency.

Multi-Omics analysis reveals the important role of indole-3-acetic acid homeostasis in male fertility of cotton

Auxin (Indole-3-acetic acid, IAA) is essential for anther development and male fertility, but little is known about its homeostasis in developing anthers due to its complex and diverse synthesis pathways. Here, we employed transcriptomic, targeted metabolomic, and amino acid analyses on a wild type (WT) cotton (Gossypium hirsutum) line SD98–6 and its nearly-isogenic male sterile (MS) line SD98–6A, to delve into the relationship between IAA and anther fertility. In WT anthers, IAA homeostasis was achieved mainly through self-synthesis, conjugate hydrolysis, and polar transport, and accumulation of IAA exhibited an inverted "U" pattern with the highest content observed at the tetrad stage. In MS anthers, no IAA accumulation was observed after the meiosis stage and the IAA content remained constantly low, mainly due to reduction of the substrates (phenylalanine and tryptophan) for IAA synthesis, and significantly decreased expression of the genes involved in IAA synthesis. Meanwhile, carbohydrate metabolism pathways directly contributing to IAA synthesis and synthesis of amino acids were malfunctional in MS anthers based on the expression profile of the metabolic genes and content measurement. These results provide valuable insights into the IAA homeostasis in cotton anthers and imply that genes related to IAA homeostasis are potential targets for development of IAA-sensitive male sterile cotton lines.

A Comprehensive Review of LiDAR Applications in Crop Management for Precision Agriculture.

Precision agriculture has revolutionized crop management and agricultural production, with LiDAR technology attracting significant interest among various technological advancements. This extensive review examines the various applications of LiDAR in precision agriculture, with a particular emphasis on its function in crop cultivation and harvests. The introduction provides an overview of precision agriculture, highlighting the need for effective agricultural management and the growing significance of LiDAR technology. The prospective advantages of LiDAR for increasing productivity, optimizing resource utilization, managing crop diseases and pesticides, and reducing environmental impact are discussed. The introduction comprehensively covers LiDAR technology in precision agriculture, detailing airborne, terrestrial, and mobile systems along with their specialized applications in the field. After that, the paper reviews the several uses of LiDAR in agricultural cultivation, including crop growth and yield estimate, disease detection, weed control, and plant health evaluation. The use of LiDAR for soil analysis and management, including soil mapping and categorization and the measurement of moisture content and nutrient levels, is reviewed. Additionally, the article examines how LiDAR is used for harvesting crops, including its use in autonomous harvesting systems, post-harvest quality evaluation, and the prediction of crop maturity and yield. Future perspectives, emergent trends, and innovative developments in LiDAR technology for precision agriculture are discussed, along with the critical challenges and research gaps that must be filled. The review concludes by emphasizing potential solutions and future directions for maximizing LiDAR's potential in precision agriculture. This in-depth review of the uses of LiDAR gives helpful insights for academics, practitioners, and stakeholders interested in using this technology for effective and environmentally friendly crop management, which will eventually contribute to the development of precision agricultural methods.

Non-destructive measurement of rice amylose content using near-infrared spectroscopy for application at grain elevators and milling plants

Non-destructive measurement of rice amylose content using near-infrared spectroscopy for application at grain elevators and milling plants

Identification and Fine Mapping of a Mutant pv‐nts Gene Responsible for Dwarf and Thin Stem of Snap Bean (Phaseolus vulgaris L.)

ABSTRACTPlant height is one of the most important traits in the breeding of snap bean, which determines the planting density and the resistance to failure, which in turn affects its yield and quality. Therefore, studying the molecular mechanism of plant height in snap bean is an important measure to realize the improvement of snap bean. We obtained a dwarf, thin‐stemmed mutant nts (normal to slim) from a dwarf variety of snap bean A18 via 60CO‐γ‐ray treatment. We conducted phenotypic observations, endogenous hormone content measurements and genetic analyses of the dwarfing thin‐stemmed mutant nts and explored gene localization and candidate gene screening for the mutant trait in snap bean. Compared with wild‐type A18, nts mutant exhibited various abnormal phenotypes such as dwarfing, reduced branching, thinner top stem, reduced plant width, reduced number of leaf area and thousand grain weight and increased content of hormones such as indole‐3‐acetic acid (IAA) in the top stem. Genetic analysis indicated that the mutant trait was controlled by a single recessive nuclear gene, and the mutant gene was named pv‐nts. pv‐nts was localized to a 361.1‐kb segment on chromosome 8 as revealed by bovine serum albumin (BSA) hybrid pool sequencing and simple sequence repeat (SSR) molecular markers. Phvul.008G106300 (encoding LAX2 protein) was identified as a candidate gene corresponding to pv‐nts via gene function annotation. Phvul.008G106300 was significantly upregulated in nts mutant compared with wild‐type A18, which was consistent with the results of endogenous IAA levels. Sequence analysis showed that the Phvul.008G106300 gene in nts had a base mutation that altered the protein structure, thus causing the dwarfed, thin‐stemmed phenotype of cauliflower. Taken together, these results contribute to a better understanding of the genetic basis of dwarfing traits in snap bean.

Chitinase 3-Like 1 and C-X-C motif chemokine ligand 5 proteins and the hair cycle.

Dermal papilla cells (DPCs) exhibit self-recovery ability, which may be involved in hair growth. Therefore, we tested whether DPCs subjected to temporary growth-inhibiting stress (testosterone, 17β-estradiol, mitomycin C, or undernutrition) treatments exhibit self-recovery behavior that can activate hair follicle growth, and examined the changes in cell proliferation capacity and gene expression. Related proteins were identified and their relationships with the hair cycle was examined using a mouse model. Recovery-period DPCs (i.e., from day 3 after loading) were subjected to microarray analysis to detect genetic variations common to each stress treatment. Co-culture of recovery-period DPCs and outer root sheath cells (ORSCs) confirmed the promotion of ORSC proliferation, suggesting that the activation of hair follicle growth is promoted via signal transduction. Chitinase 3-like 1 (CHI3L1) and C-X-C motif chemokine 5 (CXCL5) exhibited ORSC proliferation-promoting effects. Measurement of protein content in the skin during each phase of the hair cycle in mice revealed that CHI3L1 and CXCL5 secretion increased immediately after anagen transition. In a hair-loss mouse model treated with testosterone or 17β-estradiol, CHI3L1 and CXCL5 secretion was lower in treated telogen skin than in untreated skin. Our results suggest that CHI3L1 and CXCL5 secreted by recovery-state DPCs promote hair growth.

The Role of Field Measurements of Fine Dead Fuel Moisture Content in the Canadian Fire Weather Index System—A Study Case in the Central Region of Portugal

The Canadian Fire Weather Index System (CFWIS), empirically developed for forests in Canada, estimates the fuel moisture content (mf) at different depths and loads through meteorological parameters. While it is often suggested that adapting an existing fire danger rating system like CFWIS for a new environment requires developing new relationships or modifying existing ones, it is worth considering if such adaptations are always necessary. Based on a dataset of field measurements for surface litter (Pinus pinaster) carried out in the central region of Portugal (2014–2023), we propose a correction of mf based on the Fine Fuel Moisture Code (FFMC) of the CFWIS. This moisture correction was used to determine the Initial Spread Index (ISI) directly and, subsequently, the Fire Weather Index (FWI). Fire records from the study region were used to analyze the performance of the corrected indices. We found that the moisture correction led to higher values and potentially more accurate indices under dry conditions but did not provide a significant improvement in predicting the number of fires and burned areas compared to the original indices. The results suggest that, in relation to fire activity, the CFWIS is sufficiently robust to variations in the fuel moisture content in the study region.

Understanding Variations in Ferrate Detection through the ABTS Method in the Presence of Electron-Rich Organic Compounds.

The chromogenic reaction between 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate) (ABTS) and ferrate [Fe(VI)] has long been utilized for Fe(VI) content measurement. However, the presence of electron-rich organic compounds has been found to significantly impact Fe(VI) detection using the ABTS method, leading to relative errors ranging from ∼88 to 100%. Reducing substances consumed ABTS•+ and resulted in underestimated Fe(VI) levels. Moreover, the oxidation of electron-rich organics containing hydroxyl groups by Fe(VI) could generate a phenoxyl radical (Ph•), promoting the transformation of Fe(VI) → Fe(V) → Fe(IV). The in situ formation of Fe(IV) can then contribute to ABTS oxidation, altering the ABTS•+:Fe(VI) stoichiometry from 1:1 to 2:1. To overcome these challenges, we introduced Mn(II) as an activator and 3,3',5,5'-tetramethylbenzidine (TMB) as a chromogenic agent for Fe(VI) detection. This Mn(II)/TMB method enables rapid completion of the chromogenic reaction within 2 s, with a low detection limit of approximately 4 nM and a wide detection range (0.01-10 μM). Importantly, the Mn(II)/TMB method exhibits superior resistance to reductive interference and effectively eliminates the impact of phenoxyl-radical-mediated intermediate valence iron transfer processes associated with electron-rich organic compounds. Furthermore, this method is resilient to particle interference and demonstrates practical applicability in authentic waters.

Development of a microwave sensor for the non-invasive detection of plant responses to water stress: A practical application on maize (Zea mays L.)

In this study, a novel microwave sensing system, consisting of a microstrip self-resonant spiral coil inductively coupled to an external concentric planar probe loop, is presented and applied to the non-destructive detection of morpho-physiological plant responses to water stress. The optimised set-up of the proposed sensor ensures a highly sensitive spiral coil, which is a fundamental requirement to derive accurate information on plants' behavioural alterations related to water stress conditions. The proposed microwave sensor was tested it on two potted maize cultivars (Zea mays L.), namely “Cinquantino Bianchi” (CB) and “Scagliolo Frassine” (SF). For each cultivar, half of the samples were maintained at 100% (T100) field capacity while the other half was at 25% (T25) from 46 to 74 Days After Sowing (DAS). The frequency (fr) shift and the amplitude peaks variation of the real component of the external planar probe input impedance (ℜ(Zinput)) were obtained daily by positioning the sensor on the stem. These measured data were related to morpho-physiological parameters destructively acquired at four different growth stages. The resulting linear correlation between the stem's freshwater content (FWCstem) with both fr (r > −0.64) and the amplitude peaks (ℜ (Zinput)) (r > -0.70) provided evidence of the sensor's ability to identify stem dielectric properties' variations between the two water treatments. Concurrently, the sensor response demonstrated the capability to identify changes in the morphology and histology of the stem. Based on preliminary findings, the proposed sensor shows potential for employment in the real-time monitoring of plant water status, contributing to more economically and environmentally sustainable crop management practices. While the current correlations between plant water content and sensor measurements require further refinement to meet the rigorous industrial standards, nevertheless a large-scale adoption can be envisioned by leveraging IoT methodologies.

Micro-scale quantitative analysis of sterol content in liposomes

The high complexity of biological membranes has driven the development and application of a wide range of model membrane systems. Among these models, liposomes are extensively used because of their versatility in mimicking cellular membranes with a wide range of lipid compositions. However, the accurate quantification of lipid components, such as sterols, within these models remains a critical requirement for validation, data interpretation, and comparison. Here, we present a reliable and sensitive colorimetric assay using the Zak color reaction, which we have specifically adapted for the quantification of sterols at the micro-scale level. The assay was evaluated using cholesterol, ergosterol, and sitosterol standards, reflecting the diversity of sterol species across organisms. The reaction mechanism involves the dehydration of sterols to form carbonium ions, which are oxidized to form various enylic carbonium ions with specific absorption peaks. Due to the different chemical structures of cholesterol, ergosterol, and sitosterol, the resulting spectra show that the colored reaction products are formed in different proportions. The stability and interconversion of these species over time were analyzed. Cholesterol and sitosterol showed a clear peak at 555 nm, while ergosterol had prominent peaks at shorter wavelengths. Sterol assays on liposomal preparations showed accurate sterol incorporation with minimal loss during processing steps. These results demonstrate that this assay provides a robust and accurate measurement of sterol content in large unilamellar vesicles, making it a valuable tool for liposomal studies.

Coupling Phase Field Crystal and Field Dislocation Mechanics for a consistent description of dislocation structure and elasticity

This work addresses differences in predicted elastic fields created by dislocations either by the Phase Field Crystal (PFC) model, or by static Field Dislocation Mechanics (FDM). The PFC order parameter describes the topological content of the lattice, but it fails to correctly capture the elastic distortion. In contrast, static FDM correctly captures the latter but requires input about defect cores. The case of a dislocation dipole in two dimensional, isotropic, elastic medium is studied, and a weak coupling is introduced between the two models. The PFC model produces compact and stable dislocation cores, free of any singularity, i.e., diffuse. The PFC predicted dislocation density field (a measure of the topological defect content) is used as the source (input) for the static FDM problem. This coupling allows a critical analysis of the relative role played by configurational (from PFC) and elastic (from static FDM) fields in the theory, and of the consequences of the lack of elastic relaxation in the diffusive evolution of the PFC order parameter.

Total Root Electron Content: A New Metric for the Ionosphere Below Low Earth Orbiting Satellites

AbstractPowerful lightning strikes generate broadband electromagnetic signals. At Extremely Low Frequencies (ELF), the signal partly leaks into the ionosphere and produces whistlers that can be detected by satellites. Indeed, the satellites of the European Space Agency (ESA) Swarm Earth Explorer mission can detect those signals during 250 Hz burst‐mode acquisition campaigns of their Absolute Scalar Magnetometers (ASM). The dispersion of these whistlers depends on their propagation path and the distribution of ionization in the ionosphere crossed along that path. In this paper, we introduce a technique to derive a new measure of ionosphere electron content, the Total square‐Root Electron Content (TREC), using the arrival times of two frequencies of the whistler signal. We validate this approach by using data from ionosondes and from in situ measurements of the electron density at Swarm location. This technique brings new opportunities for sounding the ionosphere in regions poorly observed by other techniques.

Optimized Random Forest Method for 3D Evaluation of Coalbed Methane Content Using Geophysical Logging Data.

Accurate evaluation of coalbed methane (CBM) content is crucial for effective exploration and development. Traditional gas content measurement methods based on laboratory analysis of drill core samples are costly, whereas geophysical logging methods offer a cost-effective alternative by providing continuous high-resolution profiles of rock layer physical properties. However, the relationship between CBM content and geophysical logging data is complex and nonlinear, necessitating an advanced prediction method. This study focuses on the No. 3 coal seam in the Shizhuang South Block of the Qinshui Basin, utilizing geophysical logging data and 148 sets of laboratory core samples. We employed the Random Forest (RF) method optimized with a simulated annealing-genetic algorithm (SA-GA) to develop the SA-GA-RF model for evaluating CBM content. The model's performance was validated using test data and new CBM well data, and it was applied to calculate the vertical gas content profiles of No. 3 coal seam across 128 wells. The SA-GA-RF model demonstrated an average relative error of 13.13% in the test data set, outperforming Backpropagation Neural Network (BPNN), Least Squares Support Vector Machine (LSSVM), Extreme Learning Machine (ELM), and multivariate regression (MR) methods. The model also exhibited strong generalizability in new wells and improved model-building efficiency compared to traditional cross-validation grid search methods. The construction of a three-dimensional CBM content model, incorporating well coordinates and elevation data, allowed for detailed identification of high gas content areas and layers. This three-dimensional model offers a more precise characterization than traditional two-dimensional isopleth maps, providing valuable insights for CBM exploration, reserve evaluation, and production optimization.

Melatonin-Nitric Oxide Crosstalk in Plants and the Prospects of NOMela as a Nitric Oxide Donor.

Melatonin regulates vital physiological processes in animals, such as the circadian cycle, sleep, locomotion, body temperature, food intake, and sexual and immune responses. In plants, melatonin modulates seed germination, longevity, circadian cycle, photoperiodicity, flowering, leaf senescence, postharvest fruit storage, and resistance against biotic and abiotic stresses. In plants, the effect of melatonin is mediated by various regulatory elements of the redox network, including RNS and ROS. Similarly, the radical gas NO mediates various physiological processes, like seed germination, flowering, leaf senescence, and stress responses. The biosynthesis of both melatonin and NO takes place in mitochondria and chloroplasts. Hence, both melatonin and nitric oxide are key signaling molecules governing their biological pathways independently. However, there are instances when these pathways cross each other and the two molecules interact with each other, resulting in the formation of N-nitrosomelatonin or NOMela, which is a nitrosated form of melatonin, discovered recently and with promising roles in plant development. The interaction between NO and melatonin is highly complex, and, although a handful of studies reporting these interactions have been published, the exact molecular mechanisms governing them and the prospects of NOMela as a NO donor have just started to be unraveled. Here, we review NO and melatonin production as well as RNS-melatonin interaction under normal and stressful conditions. Furthermore, for the first time, we provide highly sensitive, ozone-chemiluminescence-based comparative measurements of the nitric oxide content, as well as NO-release kinetics between NOMela and the commonly used NO donors CySNO and GSNO.

Emergence of Internet of Things technology in food and agricultural sector: A review

AbstractFood processing is an indispensable sector crucial for controlling the food losses. Discrete measures were introduced and implemented to enhance the food shelf life and preservation techniques. However, poor handling and preservation methods usher to the food deprivation. In such milieu, amalgamation of futuristic technologies like sophisticated sensors tether with Internet of Things (IoT) could shoot up the food safety and minimize the deprivation. Research across the globe have proved that integration of IoT‐smart sensors in scrutinizing ecological factors such as temperature, radiation, gaseous composition, relative humidity, and moisture content that are critical for food processing and preservation. IoT has the prospects to ameliorate nationwide explicable execution, slash energy depletion, slash manufacturing expenses, inflate worker health and safety during food processing unit. Smart agricultural techniques also enable measurement of temperature, relative humidity, soil moisture, and nitrogen contents in smart farming and helps the user to determine the status of crops and commodity. This article aims to focus a few aspects and budding areas of IoT in the food and agricultural sectors. With this outlook, advancement and smartness in agriculture and food processing can be created by collaborating with IoT technology.

Physics‐Informed Neural Networks Trained With Time‐Lapse Geo‐Electrical Tomograms to Estimate Water Saturation, Permeability and Petrophysical Relations at Heterogeneous Soils

AbstractDetermining soil hydraulic properties is complex, posing ongoing challenges in managing subsurface and agricultural practices. Electrical resistivity tomography (ERT) is an appealing geophysical method to monitor the subsurface due to its non‐invasive, easy‐to‐apply and cost‐effective nature. However, obtaining geoelectrical tomograms from raw measurements requires the inversion of an ill‐posed problem, which causes smoothing of the actual structure. Furthermore, the spatial resolution is determined from the distances in the electrode placement, thus inherently upscaling the obtained structure. This study explores the applicability of physics‐informed neural networks (PINNs) for upscaling permeability and petrophysical relations and monitoring water dynamics at heterogeneous soils using time‐lapse geoelectrical data. High‐resolution numerical simulations mimicking water infiltration were used as benchmarks. Synthetic ERT surveys with electrode spacing 10 times larger than the numerical model resolution were conducted to provide 2D electrical tomograms. The tomograms were fed to a PINNs system to obtain the permeability, petrophysical relations, and water content maps. An additional PINNs system incorporating water content measurements was trained to examine measurement sensitivity. Results have shown that the PINNs system could produce reliable results regarding the upscaled permeability and petrophysical relations fields. Water dynamics at the subsurface was accurately predicted with an average error of ∼3%. Adding water content measurements to PINNs training improved the system outcomes, mainly at the ERT low sensitivity zones. The PINNs system reduced water saturation errors by more than 30% compared to the common practice of directly translating the geoelectrical tomograms to water saturations using known, homogeneous petrophysical relations.

Optimization of Hydrolytic Enzyme Production from Tempeh Starter to Increase In Vitro Pepsin Digestibility of Black Soldier Fly Maggot

This research aims to evaluate the optimal level and incubation time for the production of hydrolytic enzymes from tempeh starter (TS), in order to increase the in vitro pepsin digestibility of Black Soldier Fly (BSF), Hermetia illucens, maggot flour. The materials used were commercial tempeh starter, pepsin, and 15 days of age dried BSF maggot. In this study, two experiments were conducted. In a factorial completely randomized design, the analysis of variance (ANOVA) was performed to assess the significance of treatment effects, and orthogonal polynomial contrasts were employed to identify specific linear and quadratic trends among the group means. In experiment 1, research was carried out to determine the optimal starter level and incubation time to produce hydrolytic enzymes from tempeh starter. In experiment 2, crude enzyme from the best treatment in the first stage was used to increase the pepsin digestibility of BSF maggot flour. The optimal protein content and enzyme activities of tempeh starter was 0.10-0.13% starter with an incubation time of 2.00-3.47 days. Meanwhile, the optimal pepsin digestibility of BSF maggot flour was 1.51% enzymes with a hydrolysis time of 23.87 hours. This analysis measurement of protein content and enzymatic activity of tempeh starter and in vitro digestibility of BSF flour represent the preliminary methodology used to initially select hydrolyzed BSF flour to be a source of protein in animal feed.

High-resolution 3-D imaging of electron density perturbations using ultra-dense GNSS observation networks in Japan: an example of medium-scale traveling ionospheric disturbances

For the first time using computerized ionospheric tomography (CIT) and leveraging ultra-dense slant total electron content (STEC) measurements derived from two ground-based Global Navigation Satellite System (GNSS) receiver networks in Japan, we have reconstructed the 3-D field-aligned structure of nighttime medium-scale traveling ionospheric disturbances (MSTIDs) with high spatiotemporal resolution. The CIT algorithm focuses on electron density perturbation components, allowing for the imaging of disturbances with small amplitudes and scales. Slant TECs used for CIT are setup to consist of two components: the background derived from IRI-2016 model and TEC perturbations obtained by subtracting a 30-min running average from observations. The resolution is set to 0.25º in latitude and longitude, 10 km in altitude, 30 s in time. Simulations were conducted to assess the performance of the CIT algorithm, revealing that this technique has good fidelity by accurately reconstructing more than 80% of the electron density perturbations. The focus is on the nighttime event of July 4, 2022, when data were accessible. The reconstruction results show that the MSTIDs initially form at lower altitudes and subsequently develop to exhibit large amplitudes and scales that extend to higher altitudes, characterized by a well-defined frontal structure with electrodynamic signatures. These results are consistent with theories and snippets of observational evidence regarding electromagnetic-influenced MSTIDs, hence affirming the effectiveness of the developed CIT technique in probing of the variations in the 3-D structure of ionospheric electron density. This is expected to contribute to a compressive understanding of the underlying mechanisms of ionospheric inhomogeneities.Graphical

The effect of biofertilizers on nickel accumulation, nitrogen metabolism and amino acid profile of corn (Zea mays L.) exposed to nickel stress.

The issue of heavy metal pollution such as nickel poses a significant environmental concern, exerting detrimental effects on the growth and viability of plant life. Plants have various mechanisms to effectively manage heavy metal stress, including the ability to modify their amino acid type and content. This adaptive response allows plants to mitigate the detrimental effects caused by excessive heavy metal accumulation. The aim of this study was to investigate the effect of biofertilizers on nickel accumulation, nitrogen metabolism and amino acid profile of corn (Zea maysL.) cv. 'PL438' exposed to Ni stress. After disinfecting and soaking in water for 24 h, corn seeds were primed with bacterial biofertilizers (T2: NPK + FZ), fungal biofertilizers (T3: Arbuscular mycorrhizal fungi (AMF) + Trichoderma (T)), or a combination of them (T4: NPK + FZ + AMF + T) and were cultured by the hydroponic method in completely controlled conditions. Then, they were simultaneously exposed to nickel chloride at various rates (0, 75, or 150 µM) at the three-leaf stage. They were harvested two weeks later and were subjected to the measurement of Ni content, nitrate and nitrite content, nitrate reductase activity, and amino acid profile by high-performance liquid chromatography. The results showed that the application of Ni at higher rates increased Ni, nitrate, and nitrite contents and nitrate reductase activity. The study of Ni accumulation and TF revealed that Ni accumulated in the roots to a greater extent than in the shoots and TF was < 1 in all treatments. The shoot amino acid profile showed that the treatment of Ni+2 increased som amino acids such as aspartic acid, asparagine, serine, histidine, and glycine versus the control, whereas T4Ni+2 increased aspartic acid, glutamic acid, threonine and arginine. The change in amino acids in Ni-treated plants may play a key role in their adaptation to Ni stress. The findings indicate that biofertilizers played a crucial role in mitigating the negative impacts of Ni on corn plants through alterations in amino acid composition and decreased absorption and translocation of Ni.

Effect of Polar Cap Patches on the High‐Latitude Upper Thermospheric Winds

AbstractThis study focuses on the poorly known effect of polar cap patches (PCPs) on the ion‐neutral coupling in the F‐region. The PCPs were identified by total electron content measurements from the Global Navigation Satellite System (GNSS) and the ionospheric parameters from the Defense Meteorological Satellite Program spacecraft. The EISCAT incoherent scatter radars on Svalbard and at Tromsø, Norway observed that PCPs entered the nightside auroral oval from the polar cap and became plasma blobs. The ionospheric convection further transported the plasma blobs to the duskside. Simultaneously, long‐lasting strong upper thermospheric winds were detected in the duskside auroral oval by a Fabry‐Perot Interferometer (FPI) at Tromsø and in the polar cap by the Gravity Recovery and Climate Experiment satellite. Using EISCAT ion velocities and plasma parameters as well as FPI winds, the ion drag acting on neutrals and the time constant for the ion drag could be estimated. Due to the arrival of PCPs/blobs and the accompanied increase in the F‐region electron densities, the ion drag is enhanced between about 220 and 500 km altitudes. At the F peak altitudes near 300 km, the median ion drag acceleration affecting neutrals more than doubled and the associated median e‐folding time decreased from 4.4 to 2 hr. The strong neutral wind was found to be driven primarily by the ion drag force due to large‐scale ionospheric convection. Our results provide a new insight into ionosphere‐thermosphere coupling in the presence of PCPs/blobs.