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We address the estimation of regression parameters for the ill-conditioned predictive linear model in this study. Traditional least squares methods often encounter challenges in yielding reliable results when there is multicollinearity. Therefore, we employ a better shrinkage method, average least squares-centered penalized regression (ALPR), as it offers a more efficient approach for handling multicollinearity than ridge regression. Additionally, we integrate ALPR with the principal component (PC) dimension reduction method for enhanced performance. We compared the proposed PCALPR estimation technique with existing ones for ill-conditioned problems through comprehensive simulations and real-life data analyses using the mean squared error. This integration results in superior model performance compared to other methods, highlighting the potential of combining dimensionality reduction techniques with penalized regression for enhanced model predictions.

Combined drought and low–temperature stress is a crucial factor affecting turfgrass establishment and limiting the sustainability of the turfgrass industry in drought– and cold–prone regions. In this context, we evaluated the effects of regular watering (the soil water content was 80% of the maximum water–holding capacity of the field) at room temperature (25 °C) and combined drought (the soil water content was 30% of the maximum water–holding capacity of the field) and low–temperature (0 °C) stress on the morphology, photosynthesis, and physiology of wild Poa annua seedlings from different provenances (‘PA’, ‘WY’, ‘NX’ and ‘YC’). Results indicated that the combined drought and low–temperature stress changed the morphological and growth indicators of seedlings in four provenances to different extents. Moreover, combined drought and low–temperature stress reduced the net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), water use efficiency (WUE), and chlorophyll content in seedlings from four provenances. However, intertemporal CO2 concentration (Ci), relative electrical conductivity (REC), the contents of malondialdehyde (MDA), proline (Pro), soluble sugars (SS), the superoxide anion (O2•−) production rate, the contents of hydrogen peroxide (H2O2) and hydroxyl radical (·OH), the activities of superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX) were all increased. The increase in ‘PA’ was much greater than that in ‘NX.’ The comprehensive evaluation results showed that the order of combined drought and low–temperature resistance of seedlings from the four provenances was ‘PA’ > ‘YC’ > ‘WY’ > ‘NX’, which corresponded to the order of the morphological damage symptoms. In conclusion, ‘PA’ may maintain stronger combined drought and low–temperature resistance by improving the cellular water absorption and retention capacity, enhancing the function of the antioxidant defense system, and maintaining the integrity of the cell membrane, which is a crucial germplasm resource for breeding combined drought and low–temperature resistance in Poa annua.

The testing of high-dimensional normality is an important issue and has been intensively studied in the literature, it depends on the variance–covariance matrix of the sample and numerous methods have been proposed to reduce its complexity. Principle component analysis (PCA) has been widely used in high dimensions, since it can project high-dimensional data into a lower-dimensional orthogonal space. The normality of the reduced data can then be evaluated by Jarque–Bera (JB) statistics in each principle direction. We propose a combined test statistic—the summation of one-way JB statistics upon the independence of the principle directions—to test the multivariate normality of data in high dimensions. The performance of the proposed method is illustrated by the empirical power of the simulated normal and non-normal data. Two real data examples show the validity of our proposed method.

Tourism has become one of the most important sectors in many countries, significantly contributing to their economic growth and development. However, the expansion of tourism has also brought about various environmental and social challenges. The relationship between tourism, economic growth, trade openness, and the environment is diverse and complex. The objective of this paper is to investigate the relationship between the international tourism development index, GDP per capita, CO2 emissions, trade openness index as well as the energy intensity index in EU 27, over the 1995–2019 period. A composite index for international tourism was developed using the Principal Component Analysis (PCA). Panel Autoregressive distributed lag (ARDL) approach is used to reveal the long- and short-run impact of GDP per capita, CO2 emissions, trade openness index as well as the energy intensity index on the tourism development index. Panel ARDL estimates confirm some of our research hypotheses: at the level of EU countries, there is a short-run relationship between tourism and GDP per capita, but only in a few EU countries, trade openness influences tourism development index. Dumitrescu-Hurlin causality test confirms long-run feedback relationship between tourism development index and trade openness, between tourism development index and CO2 emissions, and between tourism development index and GDP and unilateral causality running from tourism development index towards energy efficiency.

Observations from a hyperspectral infrared (IR) sounding interferometer such as the Infrared Atmospheric Sounding Interferometer (IASI) and the Cross-Track Infrared Sounder (CrIS) are crucial to numerical weather prediction (NWP). By measuring radiance at the top of the atmosphere using thousands of channels, these observations convey accurate atmospheric information to the initial condition through data assimilation (DA) schemes. The massive data volume has pushed the community to develop novel approaches to reduce the number of assimilated channels while retaining as much information content as possible. Thus, channel-selection schemes have become widely accepted in every NWP center. Two significant limitations of channel-selection schemes are (1) the deficiency in retaining the observational information content and (2) the higher cross-channel correlation in the observational error (R) matrix. This paper introduces a hyperspectral IR observation DA scheme in the principal component (PC) space. Four-month performance comparison case studies using the Weather Research and Forecasting model (WRF) as a forecast module between PC-score assimilation and the selected-channel assimilation experiment show that the PC-score assimilation scheme can reduce the initial condition’s root-mean-squared error for temperature and water vapor compared to the channel-selection scheme and thus improve the forecasting of precipitation and high-impact weather. Case studies using the Unified Forecast System Short-Range Weather (UFS-SRW) application as forecast module also indicate that the positive impact can be retained among different NWP models.

Genetic variation in wild relatives, GenBank accessions, landraces, and cultivars can unlock key alleles for the traits of interest for breeding programs. Breeding programs often utilize different strategies to quantify the source of heritable variation for target traits. One neglected area of study is the root traits of diverse genotypes, and this is especially the case for aluminum toxicity effects on legumes such as the common bean, which is the most used pulse for direct human consumption. This study evaluated 267 genotypes of common bean that were part of the global Andean Diversity Panel (ADP), consisting mainly of genotypes assembled from public and private breeding programs in Africa and North America, as well as elite lines and land races from the USDA. The ADP was evaluated for root traits at the seedling stage in the Tennessee State University (TSU) greenhouse using a hydroponic system with a standard nutrient solution with and without aluminum (Al). The recorded data on the roots per trial were fit to a linear mixed model for the analysis of variance in order to test for the genotype differences. Adjusted means considered replication and blocks within replication as random effects and genotypes as fixed effects. These were then used for Pearson correlation tests and for principal component analysis (PCA), where the first two vectors accounted for 94.5% and 93% of the explained variation under the control and Al-treatment conditions, respectively. Genotypes were clustered based on the morphology of roots in response to Al-toxicity treatment using the Euclidean distance and Ward’s hierarchical agglomerative clustering method, identifying four distinctive groups significant at p < 0.01. The intra-cluster distance was lower than the inter-cluster distances, which indicated a heterogeneous and homogeneous nature between and within clusters, respectively. The results suggest that crossing between accessions from two of the clusters would result in the maximum genetic segregation. One cluster was found to have a higher Al-toxicity tolerance than the others.

Hyperspectral-image (HSI) restoration plays an essential role in remote sensing image processing. Recently, superpixel segmentation-based the low-rank regularized methods for HSI restoration have shown outstanding performance. However, most of them simply segment the HSI according to its first principal component, which is suboptimal. In this paper, integrating the superpixel segmentation with principal component analysis, we propose a robust superpixel segmentation strategy to better divide the HSI, which can further enhance the low-rank attribute of the HSI. To better employ the low-rank attribute, the weighted nuclear norm by three types of weighting is proposed to efficiently remove the mixed noise in degraded HSI. Experiments conducted on simulated and real HSI data verify the performance of the proposed method for HSI restoration.

The study of functional connectivity (FC) of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) has gained traction for uncovering FC patterns related to autism spectrum disorder (ASD). It is believed that the neurodynamic components of neuroimaging data enhance the measurement of the FC of brain nodes. Hence, methods based on linear correlations of rs-fMRI may not accurately represent the FC patterns of brain nodes in ASD patients. In this study, we proposed a new biomarker for ASD detection based on wavelet coherence and singular value decomposition. In essence, the proposed method provides a novel feature-vector based on extraction of the principal component of the neuronal dynamic FC patterns of rs-fMRI BOLD signals. The method, known as principal wavelet coherence (PWC), is implemented by applying singular value decomposition (SVD) on wavelet coherence (WC) and extracting the first principal component. ASD biomarkers are selected by analyzing the relationship between ASD severity scores and the amplitude of wavelet coherence fluctuation (WCF). The experimental rs-fMRI dataset is obtained from the publicly available Autism Brain Image Data Exchange (ABIDE), and includes 505 ASD patients and 530 normal control subjects. The data are randomly divided into 90% for training and cross-validation and the remaining 10% unseen data used for testing the performance of the trained network. With 95.2% accuracy on the ABIDE database, our ASD classification technique has better performance than previous methods. The results of this study illustrate the potential of PWC in representing FC dynamics between brain nodes and opens up possibilities for its clinical application in diagnosis of other neuropsychiatric disorders.

The special causes of variations, which is also known as a shift, can occur in a single or more than one related process characteristics. Statistical process control tools such as control charts are useful to monitor shifts in the process parameters (location and/or dispersion). In real-life situation, the shift is emerging in different sizes, and it is hard to identify it with classical control charts. Moreover, more than one process of characteristics required special attention because they must monitor jointly due to the association among them. This study offers two adaptive control charts to monitor the different sizes of a shift in the process mean vector. The novelty behind this study is to use dimensionally reduction techniques such as principal component analysis (PCA) and an adaptive method such as Huber and Bi-square functions. In brief, the multivariate cumulative sum control chart based on PCA is designed, and its plotting statistic is utilized as an input in the classical exponentially weighted moving average (EWMA) control chart. The run length (RL) properties of the proposed and other control charts are obtained by designing algorithms in MATLAB through a Monte Carlo simulation. For a single shift, the performance of the control charts is assessed through an average of RL, standard deviation of RL, and standard error of RL. Likewise, overall performance measures such as extra quadratic loss, relative ARL, and the performance comparison index are also used. The comparison reveals the superiority over other control charts. Furthermore, to emphasize the application process and benefits of the proposed control charts, a real-life example of the wind turbine process is included.

The water (W; W50, W75, and W100)–zeolite (Z; Z0, Z3, Z6 and Z9) coupling (W-Z) regulation strategy of high-quality and high-yield tomato was explored with alternate drip irrigation under mulch. Greenhouse planting experiments were used in monitoring and analyzing tomato growth, physiology, yield, quality, and water use efficiency (WUE). Suitable amounts of W and Z for tomato growth were determined through the principal component analysis (PCA) method. Results showed that tomato plant height (Ph), stem thickness (St), root indexes, leaf area index (LAI), photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), organic acid (OA), and yield showed a positive response to W, whereas nitrate (NC), vitamin C (VC), soluble solid (SS), intercellular CO2 concentration (Ci), fruit firmness (Ff), and WUE showed the opposite trend. The responses of Ci and Ff to Z were first negative and then positive, whereas the responses of other indexes to Z showed an opposite trend (except yield under W50). The effects of W, Z, and W-Z on tomato growth, physiological, and quality indexes and yield were as follows: W > Z > W-Z; the effects on WUE were as follows: Z > W > W-Z. The two principal components of growth factor and water usage factor were extracted, and the cumulative variance contribution rate reached 93.831%. Under different treatments for tomato growth, the comprehensive evaluation score F was between −1.529 and 1.295, the highest treated with Z6W100, the lowest treated with Z0W50. The PCA method showed that under the condition of alternate drip irrigation under mulch, the most suitable W for tomato planting was 100% E (E is the water surface evaporation), and the amount of Z was 6 t·ha−1.

Maize is one of the most widely used plants in the agricultural industry, and the fields of application of this plant are broad. The experiment was conducted at the Látókép Crop Production Experimental Station of the University of Debrecen, Hungary. Three mid-ripening maize hybrids with different FAO numbers were used in the present study. The effects of different nitrogen supplies were examined as a variable rate of abiotic stress and the interrelationship among the essential nutrients through the nutrient acquisition and partitioning of the different vegetative and generative plant parts. The results showed that NPK application compared to the control treatment (no fertilizer application) increased DM in all tissues of maize, while increasing nitrogen application from 120 to 300 kg ha−1 had no significant effect on this trait. The highest protein content was obtained with the nitrogen application of 120 kg ha−1, and the higher nitrogen fertilizer application had no significant effect on this trait. Seeds and leaves had a maximum zinc and manganese value in terms of nitrogen content (protein). Dry matter was positively correlated with nitrogen, potassium, and manganese content, while the dry matter had a negative correlation with nickel content. In general, to achieve a maximum quantitative and qualitative yield, it is recommended to use NPK fertilizer with a rate of 120 kg ha−1 N for maize cultivation.

This study introduces Pakistan’s multidimensional energy security index (PMESI) and indices across dimensions from 1991 to 2020 through indicator optimization. Based on criteria, expert participation, and reliability testing, 27 indicators were identified and weighted based on dimension reduction utilizing the Varimax Rotation technique. As a result of robust evaluation framework, there has been a considerable change in Pakistan’s energy security when compared to other studies such as the energy security indicator of Pakistan (ESIP) and the energy security index of Pakistan (ESIOP). According to the findings, energy security decreased by 25% between 1991 and 2012, followed by a modest increase through 2020. During the study period, the “Affordability” dimension improved; however, the other four dimensions, namely “Availability,” “Technology,” “Governance,” and “Environment,” regressed. Few goals under the petroleum policy (1991), petroleum policy (2012), and power policy (2013) were partially met, while conservation programs, such as the renewable policy (2006) and national climate change policy (2012), fell short. Indicators such as price, reserves, governance, corruption, and consumption contributed to PMESI across five dimensions. Thus, PMESI and indices guiding policymakers to focus on improving governance and exploiting local energy resources in order to provide affordable and sufficient energy in the long run.

This study presents a spatial assessment of eight potentially toxic elements (PTE: Cd, Cr, Cu, Fe, Pb, Ni, Mn, and Zn) in white button (Agaricus bisporus J.E. Lange) mushroom samples collected from the local vegetable markets of Uttarakhand State, India. Fresh A. bisporus samples were collected from thirteen districts and fifteen sampling locations (M1-M15) and analyzed for the concentration of these PTE using atomic absorption spectroscopy (AAS). The results revealed that A. bisporus contained all eight selected PTE in all sampling locations. Based on the inverse distance weighted (IDW) interpolation, principal component (PC), and hierarchical cluster (HC) analyses, the areas with a plane geographical distribution showed the highest PTE concentrations in the A. bisporus samples as compared to those in hilly areas. Overall, the decreasing order of PTE concentration in A. bisporus was recognized as Fe > Zn > Mn > Cr > Cu > Ni > Cd > Pb. The Kruskal–Wallis ANOVA tests displayed a highly significant (p < 0.05) difference among the sampling locations. However, the concentration of PTE was below permissible limits, indicating no potential hazard in consuming the A. bisporus. Similarly, the health risk assessment studies using the target hazard quotient (THQ) also showed no significant health risk associated with the consumption of A. bisporus being sold in the local mushroom markets of Uttarakhand, India. This study is the first report on state-level monitoring of PTE in A. bisporus mushrooms, which provides crucial information regarding the monitoring and occurrence of potentially toxic metallic elements.

The soy beverage is a healthy product rich in plant protein; however, its unpleasant flavor affects consumer acceptance. The aim of this study was to determine the feasibility of using Naematelia aurantialba as a strain for the preparation of fermented soybean beverages (FSB). Increases in Zeta potential, particle size, and viscosity make soy beverages more stable. We found that nutrient composition was increased by fermenting N. aurantialba, and the antioxidant activity of soybean beverages significantly increased after 5 days of fermentation. By reducing the content of beany substances such as hexanal and increasing the content of 1-octen-3-ol, the aroma of soybean beverages fermented by N. aurantialba changed from “beany, green, and fatty” to “mushroom and aromatic”. The resulting FSB had reduced bitterness but considerably increased sourness while maintaining the fresh and sweet taste of unfermented soybean beverages (UFSB). This study not only provides a theoretical basis for the market promotion of FSB but also provides a reference for basidiomycetes-fermented beverages.

Macroautophagy/autophagy is a fundamental catabolic pathway that maintains cellular homeostasis in eukaryotic cells by forming double-membrane-bound vesicles named autophagosomes. The autophagy family genes remain largely unexplored except in some model organisms. Legumes are a large family of economically important crops, and knowledge of their important cellular processes is essential. Here, to first address the knowledge gaps, we identified 17 ATG families in Phaseolus vulgaris, Medicago truncatula and Glycine max based on Arabidopsis sequences and elucidated their phylogenetic relationships. Second, we dissected ATG18 in subfamilies from early plant lineages, chlorophytes to higher plants, legumes, which included a total of 27 photosynthetic organisms. Third, we focused on the ATG18 family in P. vulgaris to understand the protein structure and developed a 3D model for PvATG18b. Our results identified ATG homologs in the chosen legumes and differential expression data revealed the nitrate-responsive nature of ATG genes. A multidimensional scaling analysis of 280 protein sequences from 27 photosynthetic organisms classified ATG18 homologs into three subfamilies that were not based on the BCAS3 domain alone. The domain structure, protein motifs (FRRG) and the stable folding conformation structure of PvATG18b revealing the possible lipid-binding sites and transmembrane helices led us to propose PvATG18b as the functional homolog of AtATG18b. The findings of this study contribute to an in-depth understanding of the autophagy process in legumes and improve our knowledge of ATG18 subfamilies.

Solar-induced chlorophyll fluorescence (SIF), one of the three main releasing pathways of vegetation-absorbed photosynthetic active radiation, has been proven as an effective monitoring implementation of leaf photosynthesis, canopy growth, and ecological diversity. There exist three categories of SIF retrieval methods, and the principal component analysis (PCA) retrieval method is obtrusively eye-catching due to its brief, data-driven characteristics. However, we still lack a lucid understanding of PCA’s parameter settings. In this study, we examined if principal component numbers and retrieval band regions could have effects on the accuracy of SIF inversion under two controlled experiments. The results revealed that the near-infrared region could remarkably boost SIF’s retrieval accuracy, whereas red and near-infrared bands caused anomalous values, which subverted a traditional view that more retrieval regions might provide more photosynthetic information. Furthermore, the results demonstrated that three principal components would benefit more in PCA-based SIF retrieval. These arguments further help elucidate the more in-depth influence of the parameters on the PCA retrieval method, which unveil the potential effects of different parameters and give a parameter-setting foundation for the PCA retrieval method, in addition to assisting retrieval achievements.

Water quality evaluation is fundamental for water resources management. Water quality index (WQI) is an accurate and easily understandable method for assessing water quality for different purposes. In this study, the Iraqi water quality index (Iraq WQI) was constructed to be used to evaluate the Iraqi rivers for drinking. For this purpose, some statistical techniques, experts’ advice, literature reviews, and authors’ experience were used. First, the principal component analysis (PCA) method and the modified Delphi method were used to select the most influential water quality parameters and their relative weights. Second, the quality curves of selected parameters were drawn to calculate the WQI scores basing on the water quality standards. Of twenty-seven parameters, six parameters were chosen to be within the index depending on their effect on water quality in order to reflect the specific characteristics of the Iraqi waters. The Iraq WQI was applied to the Tigris River within Baghdad as a case study and for some sites on other Iraqi rivers, and gave acceptable results. Results revealed that the statistical techniques used in this paper can be applied in all Iraqi rivers considering their specific characteristics. Based on the reliability of the Iraq WQI, there is no longer a need to use Indices designed for water for other countries.

The Chaobai River (CBR) basin in northern China is experiencing an unprecedented continuous inflow of external water via the South–North Water Diversion Project, which has channeled water from the southern part of the country to the north. Consequently, the steady rise of groundwater table in recent years is threatening soil salinity regulation. The purpose of this study was to describe the status of salinity of the surface soil in the CBR basin and to evaluate the impact of environmental factors including groundwater table on the spatial distribution of soil salinity using multivariate analysis (MVA) technique. In this study, 10 chemical variables of soil samples collected in 204 sites along CBR were analyzed, considering their interaction with three environmental factors: the density of irrigation canals, groundwater depth and topography. Statistical analysis mainly consisted of principal component analysis (PCA), redundancy analysis (RDA) and clustering analysis (CA). The results allow defining the surface soil in the CBR basin as a slightly saline and moderately alkaline media. The first two axes of multivariate model approximately explains 51% of the observed variability and allows distinguishing two main domains: the saline and the alkaline. The variability of the saline domain, defined by major cations and anions, is obviously controlled by macro environmental factors, of which the density of irrigation canals and groundwater depth contributes 71% and 28%, respectively, while that of the alkaline domain, related to pH and bicarbonate, mainly manifests as singular behaviors of soil groups like rice cultivation or sewage irrigation. The results suggests that more attention should be paid to the ongoing water table rise to help inform future land management decisions and to prevent a double threat of both groundwater and surface water on soil salinization. Meanwhile, this study shows the enormous potential of MVA technique, specifically the complementary duo of RDA and CA, for integrating both global and local information of soil salinity and environmental factors.

The linkage between atmospheric blocking (blocking frequency, BF) and total monthly July precipitation in the Selenga River Basin, the main tributary of Lake Baikal, for the period 1979−2016 was investigated. Based on empirical orthogonal functions (EOF) analysis, two dominant modes of precipitation over the Selenga River Basin were extracted. The first EOF mode (EOF 1) is related to precipitation fluctuations mainly in the Mongolian part of Selenga; the second EOF mode (EOF 2)—in the Russian part of Selenga. Based on two different modes obtained, the total amount of precipitation individually for the Russian and Mongolian part of Selenga was calculated. Correlation analysis has demonstrated that precipitation over the Mongolian part of the Selenga Basin is positively correlated to blocking over Eastern Siberia/Mongolia (80−120° E, ESM-BF). Precipitation over the Russian part of the Selenga Basin is positively correlated to blocking over the Urals-Western Siberia (50−80° E, UWS-BF) and European blocking (0−50° E, E-BF). However, the linkage is not stable, and after the mid-1990s, the obtained positive correlation became insignificant. The analysis has shown that the dominance of E or ESM-blocking in July was the primary driver of the existence of two precipitation modes over the Selenga River Basin. During 1996−2016, the negative trend of time coefficients of EOF 1 and 2 for precipitation in Selenga had been observed, which was characterized by displacement of positive precipitation anomalies outside the basin. At the same time, there was a weakening of the linkage between precipitation in the Selenga Basin and blocking frequency. We have revealed two wave-like modes over Northern Eurasia and the subtropical part of Eurasia corresponding to E, ESM-blocks in 1979−1995 and 1996−2016. The change of the Northern and subtropical wave modes is one of the causes for the weakening of the linkage between atmospheric blocking and precipitation in the Selenga Basin and as a consequence decreased precipitation in the Russian and Mongolian part of Selenga during 1979−2016.

Remote sensing techniques have been shown effective for large-scale damagesurveys after a hazardous event in both near real-time or post-event analyses. The paperaims to compare accuracy of common imaging processing techniques to detect tornadodamage tracks from Landsat TM data. We employed the direct change detection approachusing two sets of images acquired before and after the tornado event to produce a principalcomponent composite images and a set of image difference bands. Techniques in thecomparison include supervised classification, unsupervised classification, and object-oriented classification approach with a nearest neighbor classifier. Accuracy assessment isbased on Kappa coefficient calculated from error matrices which cross tabulate correctlyidentified cells on the TM image and commission and omission errors in the result. Overall,the Object-oriented Approach exhibits the highest degree of accuracy in tornado damagedetection. PCA and Image Differencing methods show comparable outcomes. Whileselected PCs can improve detection accuracy 5 to 10%, the Object-oriented Approachperforms significantly better with 15-20% higher accuracy than the other two techniques.

Maize is one of the most widely used plants in the agricultural industry, and the fields of application of this plant are broad. The experiment was conducted at the Látókép Crop Production Experimental Station of the University of Debrecen, Hungary. Three mid-ripening maize hybrids with different FAO numbers were used in the present study. The effects of different nitrogen supplies were examined as a variable rate of abiotic stress and the interrelationship among the essential nutrients through the nutrient acquisition and partitioning of the different vegetative and generative plant parts. The results showed that NPK application compared to the control treatment (no fertilizer application) increased DM in all tissues of maize, while increasing nitrogen application from 120 to 300 kg ha -1 had no significant effect on this trait. The highest protein content was obtained with the nitrogen application of 120 kg ha -1 , and the higher nitrogen fertilizer application had no significant effect on this trait. Seeds and leaves had a maximum zinc and manganese value in terms of nitrogen content (protein). Dry matter was positively correlated with nitrogen, potassium, and manganese content, while the dry matter had a negative correlation with nickel content. In general, to achieve a maximum quantitative and qualitative yield, it is recommended to use NPK fertilizer with a rate of 120 kg ha -1 N for maize cultivation.

This study presents a spatial assessment of eight potentially toxic elements (PTE: Cd, Cr, Cu, Fe, Pb, Ni, Mn, and Zn) in white button (Agaricus bisporus J.E. Lange) mushroom samples collected from the local vegetable markets of Uttarakhand State, India. Fresh A. bisporus samples were collected from thirteen districts and fifteen sampling locations (M1-M15) and analyzed for the concentration of these PTE using atomic absorption spectroscopy (AAS). The results revealed that A. bisporus contained all eight selected PTE in all sampling locations. Based on the inverse distance weighted (IDW) interpolation, principal component (PC), and hierarchical cluster (HC) analyses, the areas with a plane geographical distribution showed the highest PTE concentrations in the A. bisporus samples as compared to those in hilly areas. Overall, the decreasing order of PTE concentration in A. bisporus was recognized as Fe > Zn > Mn > Cr > Cu > Ni > Cd > Pb. The Kruskal−Wallis ANOVA tests displayed a highly significant (p < 0.05) difference among the sampling locations. However, the concentration of PTE was below permissible limits, indicating no potential hazard in consuming the A. bisporus. Similarly, the health risk assessment studies using the target hazard quotient (THQ) also showed no significant health risk associated with the consumption of A. bisporus being sold in the local mushroom markets of Uttarakhand, India. This study is the first report on state-level monitoring of PTE in A. bisporus mushrooms, which provides crucial information regarding the monitoring and occurrence of potentially toxic metallic elements.

Hostile aortic neck characteristics, such as short length and large diameter, have been associated with type Ia endoleaks and reintervention after endovascular aneurysm repair (EVAR). However, such characteristics partially describe the complex aortic neck morphology. A more comprehensive quantitative description of 3D neck shape might lead to new insights into the relationship between aortic neck morphology and EVAR outcomes in individual patients. This study identifies the 3D morphological shape components that describe the infrarenal aortic neck through a statistical shape model (SSM). Pre-EVAR CT scans of 97 patients were used to develop the SSM. Parameterization of the morphology was based on the center lumen line reconstruction, a triangular surface mesh of the aortic lumen, 3D coordinates of the renal arteries, and the distal end of the aortic neck. A principal component analysis of the parametrization of the aortic neck coordinates was used as input for the SSM. The SSM consisted of 96 principal components (PCs) that each described a unique shape feature. The first five PCs represented 95% of the total morphological variation in the dataset. The SSM is an objective model that provides a quantitative description of the neck morphology of an individual patient.

The soy beverage is a healthy product rich in plant protein; however, its unpleasant flavor affects consumer acceptance. The aim of this study was to determine the feasibility of using Naematelia aurantialba as a strain for the preparation of fermented soybean beverages (FSB). Increases in Zeta potential, particle size, and viscosity make soy beverages more stable. We found that nutrient composition was increased by fermenting N. aurantialba , and the antioxidant activity of soybean beverages significantly increased after 5 days of fermentation. By reducing the content of beany substances such as hexanal and increasing the content of 1-octen-3-ol, the aroma of soybean beverages fermented by N. aurantialba changed from "beany, green, and fatty" to "mushroom and aromatic". The resulting FSB had reduced bitterness but considerably increased sourness while maintaining the fresh and sweet taste of unfermented soybean beverages (UFSB). This study not only provides a theoretical basis for the market promotion of FSB but also provides a reference for basidiomycetes-fermented beverages.

Macroautophagy/autophagy is a fundamental catabolic pathway that maintains cellular homeostasis in eukaryotic cells by forming double-membrane-bound vesicles named autophagosomes. The autophagy family genes remain largely unexplored except in some model organisms. Legumes are a large family of economically important crops, and knowledge of their important cellular processes is essential. Here, to first address the knowledge gaps, we identified 17 ATG families in Phaseolus vulgaris , Medicago truncatula and Glycine max based on Arabidopsis sequences and elucidated their phylogenetic relationships. Second, we dissected ATG18 in subfamilies from early plant lineages, chlorophytes to higher plants, legumes, which included a total of 27 photosynthetic organisms. Third, we focused on the ATG18 family in P. vulgaris to understand the protein structure and developed a 3D model for PvATG18b. Our results identified ATG homologs in the chosen legumes and differential expression data revealed the nitrate-responsive nature of ATG genes. A multidimensional scaling analysis of 280 protein sequences from 27 photosynthetic organisms classified ATG18 homologs into three subfamilies that were not based on the BCAS3 domain alone. The domain structure, protein motifs (FRRG) and the stable folding conformation structure of PvATG18b revealing the possible lipid-binding sites and transmembrane helices led us to propose PvATG18b as the functional homolog of AtATG18b. The findings of this study contribute to an in-depth understanding of the autophagy process in legumes and improve our knowledge of ATG18 subfamilies.