Search

At a regional scale, decision-making in water resources management is based on the analysis of long-term, continuous observations of hydrometeorological variables including streamflow. Quite often, constraints such as paucity of observed flow data hinder scientific planning in ungauged watersheds of developing countries. In this context, we present an improved framework for predicting streamflow data in an ungauged tropical watershed (Jambhira) in eastern India utilizing coupled data analytics and the Soil and Water Assessment Tool (SWAT) for flow regionalization. In this study, the choice of different dimensionality reduction methods such as principal components analysis (PCA) and Isomap during the clustering stage, as well as the choice of inverse distance weighting (IDW) and physical similarity (PS) approaches for regionalization of SWAT model parameters for the ungauged watershed, are investigated. As a novel aspect, in this case study, we included certain seasonal climate characteristics and changed land-use composition of the study watersheds as pertinent features for clustering of homogeneous watersheds. The proposed framework is then evaluated for its possible limitations, namely, whether the integrated approaches yield the best estimates of hydrological model parameters for ungauged watersheds, and if they guarantee good performance across different flow regimes. The regionalization results for the pseudoungauged watershed (Govindpur, India) indicate that coupled PS-SWAT approach is the most efficient with R2 and Nash–Sutcliffe efficiency (NSE) values ranging from 0.75 to 0.83 and from 0.74 to 0.77, respectively. The hydrological model of the ungauged watershed (Jambhira) is developed using the regionalization framework, and using the simulated flows, flow duration curve (FDC) analysis is also performed. Analysis of regime-based flow characteristics reveals a declining trend in the magnitude of low and high flows by 4% and 22.2%, respectively, in Jambhira. [ABSTRACT FROM AUTHOR]

A comprehensive hydrochemical insight was evaluated to groundwater suitability for drinking and agriculture, and potential nitrate threats in a part of Western India. Total 248 groundwater samples both in pre-monsoon (PrM) and post-monsoon (PoM) seasons were examined for the physicochemical parameters, and major ions by using standard methods, and their spatial distributions using GIS technique. Results show that major cations are influenced as Na+ > Mg2+ > Ca2+ > K+ ions in the PrM, and Ca2+ > Na+ > Mg2+ > K+ ions in the PoM. However, the major anions showed the influences of HCO3− > Cl− > SO42− > NO3− > F− ions both in the seasons. The EC, TDS, TH values are found elevated in some parts. Elevated NO3− concentrations (the maximum: 199 mg/L in the PoM and 357 mg/L in the PrM) indicate the influence of agricultural activities. Groundwater is the dominant of two hydrochemical facies such as mixed Ca-HCO3 type and Mixed Ca–Mg–Cl type waters in both seasons. Hydrochemical compositions are influenced mainly by the dissolution of host rock. The water quality index (WQI) demonstrates that about 29% and 36% of the samples are inappropriate for drinking during the dry and wet periods, respectively. The SAR, RSC, KR, PI, and PS indicate the water suitability for agriculture. The CR values support the necessity of replacing metallic pipes with PVC pipes for groundwater supply. The positive CAIs values indicate a large interchange among Na+ and K+ from water with the Ca2+ and Mg2+ of the parent rocks. Principal component analysis was performed to compare the similarities and dissimilarities of the ions simultaneously for the PrM and PoM samples. In addition, oral exposure to the NO3 is found higher as compared to dermal interaction in the dry season. Total health index (HITotal) values related to the non-carcinogenic health threats of nitrate in groundwater are an average of 1.414, 1.672, and 2.457 for males, females, and children, respectively, in the PrM, whereas 1.055, 1.246, and 1.832 in the PoM. Children are more health threats in the potential nitrate exposure. [ABSTRACT FROM AUTHOR]

AbstractPurposeMaterials and methodsResultsConclusion\nIMPLICATIONS FOR REHABILITATIONThe Tinnitus Functional Index (TFI) is a widely recognized measure for evaluating tinnitus and is frequently used in both therapeutic and research contexts. Unfortunately, TFI is currently not available in any Indian languages. In a multilingual country like India, cross-cultural adaptation, translation, and validation of such scales in regional languages are critical to improving their use for clinical and research purposes. Therefore, this study focused on translating and validating the TFI in Kannada for use among the Indian population.The original version of TFI was translated with the help of audiologists and linguistic experts who were proficient in Kannada. The translated version was content validation by five audiologists and a cognitive debriefing by native speakers to check the familiarity of words. The final version (TFI-K) was then administered to 181 participants with tinnitus. Along with the TFI, other scales like Tinnitus Handicap Inventory (THI) were also obtained to check the convergent validity. The obtained data was then subjected to various statistical analyses like internal consistency, convergent and discriminant validity, and factor analysis.The TFI-K was found to have an excellent internal consistency (Cronbach’s α = 0.974) and good convergent validity (p < 0.001; r = 0.778) with THI-K. A principal component analysis with varimax rotation showed communalities ranging from 0.64 to 0.91. Scree plots with the TFI-K component showed a sharp decline after the first factor and approximately four factors above the eigenvalue of 1. The factor analysis results suggest that the TFI-K has a structurally intact 8-factor loading, with a few exceptions that are discussed in detail.The TFI-K has demonstrated remarkable dependability and satisfactory integrity, making it a valuable tool for assessment and treatment planning in clinical and research settings.Tinnitus is known to impinge multiple domains.Assessing multiple domains provides a comprehensive understanding of the impact of tinnitus.Tinnitus Functional Index (TFI) has been cross-culturally translated into Kannada.Tinnitus Functional Index in Kannada (TFI-K) is reliable and valid and can be used clinically and in research.Tinnitus is known to impinge multiple domains.Assessing multiple domains provides a comprehensive understanding of the impact of tinnitus.Tinnitus Functional Index (TFI) has been cross-culturally translated into Kannada.Tinnitus Functional Index in Kannada (TFI-K) is reliable and valid and can be used clinically and in research. [ABSTRACT FROM AUTHOR]

The Yamuna River in India and the Mississippi River in the United States hold significant commercial, cultural, and ecological importance. This preliminary survey compares the bacterial communities sampled in surface waters at 11 sites (Yamuna headwaters, Mississippi headwaters, Yamuna River Yamunotri Town, Mississippi River at Winona, Tons River, Yamuna River at Paonta Sahib, Yamuna River Delhi-1, Yamuna River Delhi-2, Yamuna River before Sangam, Sangam, Ganga River before Sangam). Bacterial 16S rDNA analyses demonstrate dominance of Proteobacteria and Bacteroidetes phyla. Actinobacteria were also dominant at sites near Sangam in India and sites in Minnesota. A dominance of Epsilonbacteraeota were found in Delhi, India. Principal component analysis (PCA) using unique operational taxonomic units (OTUs) resulted in the identification of 3 groups that included the Yamuna River locations in Delhi (Delhi locations), Yamuna headwaters and Yamuna River at Yamunotri (Yamuna River locations below the Glacier) and Mississippi, Ganga, Tons, and other Yamuna River locations. Diversity indices were significantly higher at the Yamuna River locations below the Glacier (Simpson D = 0.986 and Shannon H = 5.06) as compared (p value <0.001) to the Delhi locations (D = 0.951 and H = 4.23) and as compared (p value < 0.001) to Mississippi, Ganga, Tons, and other Yamuna River locations (D = 0.943 and H = 3.96). To our knowledge, this is the first survey to compare Mississippi and Yamuna River bacterial communities. We demonstrate higher diversity in the bacterial communities below the Yamunotri glacier in India. [ABSTRACT FROM AUTHOR]

This study attempts to develop a composite index by integrating meteorological, hydrological and agricultural droughts over semi-arid Banas River basin, Rajasthan, India. To affect this, the standardized precipitation index (SPI), streamflow drought index (SDI), and vegetation condition index (VCI) have been used at 1-, 3-, 5-, 9- and 12-month time scales using station and remote sensing-based data for the period 2000 to 2020. To identify the occurrence of above-stated droughts and most vulnerable drought period at different time scales (1-, 3-, 5-, 9- and 12-month) regarding SPI, SDI and VCI has been validated with foodgrains produced and occurrence of historical drought years. This validation has been found significant with SPI-3 (r = − 0.81), SDI-3 (r = − 0.78) and VCI-5 (r = − 0.80) time scales. Subsequently, these time scales have been coalesced using weights obtained from principal component analysis (PCA) to develop the composite drought index (CDI). The annual CDI developed this way has been further validated with foodgrains produced and occurrence of historical drought years. The results of CDI demonstrate the maximum area under mild drought (73 percent) followed by moderate (21 percent) and severe (4 percent), whereas minuscule area has been detected under wet conditions (2 percent). Finally, this study suggests that individual drought types (meteorological, hydrological, agricultural) do not appropriately arrest the drought severity, hence, the usage of multiple droughts based composite index can be more realistic for effective drought assessment and monitoring in hydrologic systems. [ABSTRACT FROM AUTHOR]

Horizontal and vertical distributions of heavy metals (Al, Fe, Mg, Cd, Cr, Cu, Ni, Pb and Zn) and magnetic susceptibility of Vaigai river sediment have been assessed to know the heavy metal toxicity and magnetic behavior of the sediment. The present study intentionally shows the magnetic susceptibility as proxy for metal concentrations and their risk levels of sediment. Univariate statistical analysis is carried out to confirm the spatial distribution of the heavy metals. The metal concentrations in present sediment are compared with iportant toxic reference values such as TEL, PEL, ERL, ERM and TRV to predict the toxicity of metals. The result shows that the frequent biological effect can be possible due to Cd, Cr, Cu, Pb and Zn in all feet sediments. Some interesting pollution factors such as PLI, PER and mPEC-Q are calculated to know the pollution status of the river. High magnetic susceptibility values in S16, S18 and S25 indicate the presence of various magnetic minerals. Principal Component Analysis (PCA) is carried out to show magnetic susceptibility as proxy for measuring heavy metals and their risk levels. Since magnetic susceptibility is strongly associated with heavy metals and their risk levels, this may be proxy for determining heavy metals and their risk levels. [ABSTRACT FROM AUTHOR]

Sediments are natural reservoirs of organic carbon assisting in maintenance of natural carbon inventory. The present work was carried out with aims to assess the various labile (employing acid digestion method) and biochemical carbon fractions in sediments of Hirakud reservoir and study the impact of spatial variations on it. The results favor a distinct spatial influence on the distribution and concentration of various carbon fractions in sediments (p < 0.05). The average concentrations of very labile (2.09%) and recalcitrant (1.25%) fractions of total organic carbon dominated the sediments while the labile and less labile fractions shared 0.39 and 0.63% respectively. Similarly, the carbohydrate carbon (0.82 mg/g) and protein carbon (0.78 mg/g) conquered the biopolymeric carbon (BPC) with the lipid carbon being 0.67 mg/g only. While the available K and P ranged between 3.81 and 17.02, and between 6.31 and 27.57 kg/ha respectively, total nitrogen varied from 198.06 to 462.15 kg/ha. Significant spatial variations were observed concerning long-term carbon storage and productivity (eutrophic condition, BPC > 3 mg/g). The reservoir sites were mesotrophic to eutrophic in nature while the downstream displayed oligotrophic condition. Organic sediment index (OSI) value suggests that the reservoir sediment was under practically uncontaminated to moderately contaminated condition (OSI < 0.20). The principal component analysis also suggests that the carbon accumulation is primarily governed by the recalcitrant carbon fraction. Thus, it can be concluded that carbon fractions regulate the sediment quality by influencing its carbon storage, production capacity, and is affected by anthropogenic pressure along a spatial scale. [ABSTRACT FROM AUTHOR]

Forest fire is a major disturbance in mountainous ecosystems across the world. It impacts the composition, functioning, and structure of the forest ecosystem. Demographic pressure and the related climatic factors are thought to exacerbate the danger of forest fires, although there is a lack of statistical data to support this, particularly in South Asian countries with limited historical records. The study looks at how forest fires interact with their causative variables, such as population, topography, vegetation, and climate regimes, in the forests of Northern India. In order to do so, the paper presents a 15-year trend analysis of forest burn scars. This investigation confirmed the utility of principal component analysis using multisource spatial data and correlation matrices. The findings reveal that the occurrence and intensity of forest fires in mountainous locations are influenced by anthropogenic activities, forests near roads and settlements are extremely vulnerable. Based on the analysis, we emphasize the need for restructuring the existing policies like National Action Plan for forest fires and forest fire prevention and management scheme into more practical science-based policies. These findings may be utilized in planning effective fire control processes in time, and the technique provided in this study may be used to discover potential fire-risk zones in other areas. [ABSTRACT FROM AUTHOR]

Purpose: Microfinance emerged as an essential catalyst for socio-economic development and financial inclusion to reduce poverty. Microfinance institutions cannot meet their primary objective of poverty reduction if they are not sustainable financially. With the theoretical support of profit incentive theory, this paper aims to investigate the impact of organizational structure (OS), growth outreach (average loan per borrower [ALPB] and number of active borrowers), women empowerment (percentage of women borrowers [PWB]), liquidity, leverage and cost efficiency (cost per borrower) on the financial sustainability of microfinance providers (MFPs) in India and explore the possible moderating effect of the national governance indicators (NGIs). Design/methodology/approach: A financial sustainability index has been developed by using principal components analysis, including both conventional measures (return of assets and return on equity) and efficiency measures (operational self-sufficiency and financial self-sufficiency). Due to the existence of endogeneity and heteroskedasticity, this study uses two-step system generalized method of moments estimates to examine the relationships for a period of 2006 to 2018. Findings: The finding reveals that there is a strong significant relationship between financial sustainability and its influential factors. Organizatioanl Structure, loan size, women borrowers, Gross Domestic Products and inflation enhance the financial sustainability of India's microfinance sector. However, a number of borrowers, liquidity, leverage and operating costs negatively affect the financial sustainability of MFPs of India. The estimates demonstrate that NGIs significantly moderate the association between financial sustainability and its influential factors. The NGIs negatively affect the positive impact of Organizatioanl Structure on financial sustainability. National governance increases the positive effect of loan size (ALPB) and reduces the negative effect of a number of borrowers and leverage on the financial sustainability of MFPs of India. However, NGIs negatively affect the positive relationship between Percentage of Women Borrowers and Financial sustainability of Microfinance Providers of India. Originality/value: To the best of the authors' knowledge, this study is the first of its kind that incorporates all of the six dimensions of the National Governance Indicators (NGIs) and uses as a moderator. Secondly, a financial sustainability index has been developed for measuring the financial sustainability of Microfinance Providers (MFPs). [ABSTRACT FROM AUTHOR]

AbstractCamellia sinensis, renowned as the second most widely consumed nonalcoholic beverage worldwide, bears substantial economic importance, prompting cultivators to breed various clones for enhanced flavor and quality. This study analyzed the variation in leaf phenotype, phytochemicals (total tannins and proanthocyanidins content) and antioxidant potential of 36 widely cultivated tea clones from India’s sub-Himalayan region using multivariate analysis. Results indicated that TV23 had the largest leaf and SS27 and RR had the smallest. TS520 was the richest in tannin, proanthocyanidins, and antioxidants, while S3A1 and Heeleakah were the least. Principal components analysis (PCA) and cluster analysis unveiled four morphological clusters (representative clones - TV1, TV23, TV30, 124.48.8) and four phytochemical clusters (representative clones - TS520, TV9, TV27, P126). GC-MS analysis revealed that TV1 and TV30 had high caffeine content (82.0%), while TS520 exhibited abundant antioxidant compounds, including sycllo-inositol (23.84%) and epigallocatechin (4.23%). TS520’s exceptional antioxidant properties, confirmed by DPPH, ABTS, and total antioxidant capacity assays, may result from its cultivation through seed propagation. Correlation analysis showed antioxidant potential had moderate negative associations with leaf size, strong negative with inter-secondary vein number, and positive with petiole length. This study is pivotal for assessing tea clone diversity, with broader applications in tea improvement and breeding programs. [ABSTRACT FROM AUTHOR]

The benthic foraminiferal community is an excellent bio-indicator of pollution in coastal and marginal marine settings. Their abundance, diversity and its relationship with environmental parameters, viz. grain size, organic carbon (Corg) and trace metals concentration, from the surface sediment layer of the southwestern shelf of the Bay of Bengal, have been used to understand the marine pollution in this study. A total of 32 surface sediment samples were collected at various water depths.The samples were analysed for grain size distribution, organic matter (OM), foraminiferal and trace metals studies. Statistical analyses such as correlation matrix, PCA (Principal Component Analysis) and cluster analysis show that the foraminiferal species composition is significantly influenced by the organic carbon (Corg), Co, Pb, Zn, Cr, and Ni concentrations. The dominance of stress-tolerant species, viz. Ammonia beccarii, Ammonia tepida, Nonion faba, Bulimina marginata, Bolivina robusta, Elphidium craticulatum and Elphidium advenum, as well as less species diversity, demonstrates the elevated Corg and trace metal pollution in the marine environment. [ABSTRACT FROM AUTHOR]

Agriculture is considered the leading field around the world, which is also the backbone of India. Agriculture is in a flawed state because the temperature changes, along with their uncertainty, cause huge damage to the crops during the manufacturing process. So, the appropriate prediction of crop expansion plays a vital role in the management of crop growth. This prediction can enhance the federated industries to make their sustainability toward the occupation. Recently, the farmers have not selected suitable crops for their cultivation based on soil factors. This makes a negative impact on crop yield, and thus, the Indian farmers can suffer from severe losses besides the monetary front. Hence, the optimal crop recommendation model has to consider different parameters of the soil for forecasting the best crop for cultivation, which increases crop growth and crop production. Thus, this research work explores a new crop recommendation model for precision agriculture intending to promote crop yield and alleviate the loss to farmers. Initially, this research work gathers the standard data regarding the agricultural parameters of some areas. Then, the deep features using an autoencoder, and statistical features are gathered along with the Principal Component Analysis (PCA)-based features. Next, all three sets of features are fused and fed to the developed Adaptive Henry Gas Solubility Optimization (AHGSO) for selecting the optimal features. Finally, the chosen optimal features are fed to the recommendation stage, where a Gated Recurrent Unit with Ridge Classifier (GRU-RC) is suggested for getting the precise outcome regarding the recommended crop suitable to that agricultural parameter. Here, the optimal solutions are attained by tuning the parameters of GRU and ridge classifier with the same I-HGSO. At last, the results obtained from the hybrid method can be considered more efficient. [ABSTRACT FROM AUTHOR]

The conversion of forest to agricultural land has been a major worldwide concern and a cause of deterioration of soil quality. The study examined the influence of land uses on the soil quality index (SQI) using minimum datasets (MDS) constructed from soil profiles through two methods namely, additive (SQIa) and weighted (SQIw). In this study, 29 geo-referenced soil profiles (116 layers) up to a depth of 150 cm were collected in Northeastern India, representing forest, jhum, jhum fallow, and agricultural land uses. Principal component analysis (PCA) with multiple correlation analysis is found to be a suitable statistical method for selecting the key soil quality indicators. From PCA, organic carbon (OC), sand, clay, available P and available S were selected as soil quality indicators in MDS. Our results showed that these MDS significantly varied within the profiles depending on the land-uses. The estimated values of SQIs showed that SQIa was higher than SQIw across the soil depths and land-uses. For the surface soil, SQIa values were in the order of forest (2.97) > jhum fallow (2.82) > agriculture (2.68) > jhum land (1.97) and for profile soil jhum fallow (2.38) > forest (2.37) > agriculture (2.33) > jhum (1.88). Similarly, SQIw followed the trend of forest > jhum fallow > agriculture > jhum for all the three studied depths. The statistical analysis showed that the surface, subsurface, and profile soil had no significant impact on SQIw for agriculture, fallow jhum, and forest. The overall data indicated that jhum land had a significantly lower SQI than other land-uses for all soil depths. From this study, the information generated can be useful to assess the soil quality in different land-uses for managing soil health in similar areas of the Northeastern region of India. The findings are also useful in the ecosystems in which soils develop in an acid edaphic environment. [ABSTRACT FROM AUTHOR]

Background: Field pea is one of the important cool season grain legume crops cultivated in India. In this investigation, experimental material i.e. eighty germplasm lines of field pea with four checks (IPF 4-9, Adarsh, Ambika and IPFD 10-12) were evaluated to determine the estimates of genetic diversity in the test genotypes. Methods: The data were recorded on thirteen quantitative characters for the study of genetic diversity. The mean data of each characters were subjected to cluster analysis by using D2 Mahalanobis clustering method. The principle component analysis (PCA) for measuring genetic divergence was done by XLSTAT and R 4.0 statistical package. Result: Eighty-four germplasms including checks were categorized into five distinct clusters, indicates the occurrence of high genetic diversity in the evaluated set of germplasm. Between cluster III and IV highest inter-cluster distance was observed, indicates the maximum diversity among genotypes of these clusters. Considerable differences were observed for cluster mean among different distinct clusters for all the thirteen characters. The hybridization programme involving genotypes from cluster III and cluster IV may be used to isolate suitable segregants. Principal component analysis grouped different traits under study into thirteen principal components (PCs) in which only five PCs with eigen value >1 accounted 70.97% of total variation present in genotypes. The traits falling to these five PCs may be given due importance in field pea improvement programmes. [ABSTRACT FROM AUTHOR]

Citrus is considered to have originated in north-eastern India which is recognized for having a wide variety of Citrus plants. Assam (India) is also a rich biodiversity hotspot of different Citrus species. The geographic region of this state is favored by a very suitable climatic condition for the growth of different crop plants including Citrus. But, being a flood prone area, every year Assam faces a destruction of large scale of crop plants. The increasing problem of climate change also affects this region to a greater extent from the past few years. For this reason, some unpredictable environmental conditions are experienced by this area which has become a cause of unfavorable growth of plants. Since Citrus is a very significant fruit crop of Assam, therefore, study on the effect of abiotic stress on this species is necessary. The present investigation includes a study on the morpho-physiological response of five different Citrus species to three different abiotic stresses including submergence, drought and low pH. Growth parameters like leaf fresh weight and dry weight, root fresh weight and dry weight were measured which revealed decreasing value in the stress conditions followed by an increased rate in the recovery. Similarly, the stress conditions were found to affect the physiological parameters including total chlorophyll content, relative water content (RWC), membrane stability index (MSI), relative electrolytic conductance (REC). Maximum quantum efficiency (Fv/Fm) of the Citrus plants under stress was found to be notably reduced which further increased in recovery. The key parameters mostly affected by stress were found in principal component analysis (PCA). Hydrogen peroxide (H2O2) and malondialdehyde (MDA) content of leaves and roots were highly affected by low pH and drought stress, whereas maximum quantum efficiency (Fv/Fm), membrane stability index (MSI) and relative water content (RWC) were come out to be the principal factors affected by submergence stress. Nevertheless, a good recovery rate was observed in the Citrus species. From this study the traditional Citrus species of Assam were discovered to possess significant tolerance ability against abiotic stresses. [ABSTRACT FROM AUTHOR]

Artificial Light at Night (ALAN), particularly the blue lights with short wavelength (450 nm) sourced from LED contributing about 72% of the total ALAN has emerged as a thriving hazard, especially to the nocturnal biotic communities. Fireflies, possessing intrinsic property of bioluminescence are quite vulnerable to the negative impacts of ALAN which threatens the natural courses of their life cycle. The present field-based research highlights the effect of the exposure of differential ALAN intensities on the occurrence of fireflies (Coleoptera: Lampyridae: Luciolinae) for the first time from the Indian subcontinent. Declining effects on the abundance of larvae and adults of three terrestrial firefly species Abscondita chinensis, Abscondita perplexa, and Abscondita terminalis were observed at sites exposed under differential levels of ALAN intensities. Microhabitat occupancy of larvae altered significantly. Availability of larval prey snails increased. The ratio of biomass of the larvae and females represented a deteriorating trend. However, site-specific entomofaunal association did not vary significantly. Cluster analysis reflected the categorization of the study specimens under 3 different assemblages according to the lowest, medium, and highest ranges of ALAN exposure. Principal component analysis indicated that the abundance of adult insects was positively influenced by Sky Quality Meter (SQM) (PC1:0.98) and Naked- eye limiting magnitude (NELM) (PC1:0.97), whereas, the artificial brightness (AB) and total brightness (TB) (PC1: 0.92 for each) had shown negative impacts. The results suggest the scope of utilization of fireflies as a potential bioindicator for light pollution. [ABSTRACT FROM AUTHOR]

India is one of the secondary centers of origin for both wild and domesticated bananas, with the north-eastern region holding the greatest repository. Therefore, the present study used three different molecular marker systems viz., inter simple sequence repeats (ISSR), inter-retrotransposon amplified polymorphism (IRAP), and start codon targeted (SCoT) polymorphism to analyze the genetic diversity among 17 cultivated varieties of the north-eastern region belonging to different genomic groups. The percent polymorphism was found to be 91.79, 86.78, and 82.35 in ISSR, IRAP, and SCoT markers respectively. ISSR had the highest values for all the marker parameters. However, IRAP outperformed SCoT and ISSRs by recording the highest values for effective number of alleles (Ne), Shannon index (I), and Nei's (1973) gene diversity (H). The dendrogram obtained using ISSR, SCoT, and combined data had two major clusters and the clustering pattern was almost similar, but it differed slightly in IRAP markers. To learn more about the population structure and allelic diversity, model-based structural analysis was carried out in addition to phylogenetic analysis and principal component analysis (PCA). The structure analysis identified three subpopulations in ISSR, four in IRAP, and five in SCoT and combined marker data. The Q-value indicates that almost all the subpopulations are composed of varieties with and without admixture, thereby suggesting that more alleles are being shared among the varieties used in this study. [ABSTRACT FROM AUTHOR]

Soil contamination with potentially toxic elements (PTEs) in the Malwa region belt of Punjab, India, can be a serious concern as a result of intensive agricultural practices and overuse of agrochemicals. The main objectives of the present study were to evaluate the spatial distribution, geochemical signature, and contamination level/health risk of PTEs in 76 soil samples (0–10 cm) collected from the three districts viz. Muktar, Faridkot, and Moga of Punjab, India. The result shows that PTEs concentrations vary widely in the region, with Fe and Mn distribution patterns being mostly coherent with each other. When compared to the Indian natural soil background values, the average concentration of Pb and Zn were higher than the limit, only Pb exceeded the average values of the world background and upper continental crust (UCC). Spatial autocorrelation plotted with a local indicator of spatial association (LISA) in GeoDa software version 1.18 was used to identify hotspots. A positive spatial autocorrelation (>0.2) was indicated with Moran's I values for Pb, V, Mn, Cu, and Cr, being highest for Pb. A principal component analysis (PCA) identified the major geo-chemical patterns of Fe-Al-V-Cr and TOC-Mn-Zn-HCO3−, which were positively loaded on PC1. This indicates that Fe/Al-oxyhydroxides and organic matter play a dominant role in controlling metal mobility in soils. This can be further substantiated with the Spearman's rank correlation values. The contamination factor (CF) indicates that only Pb and Zn (15.7% and 3.9% samples, respectively) were under high risk. This could be due to the excessive application of chemical fertilizers. The large range of degree of contamination (Cdeg) values suggests that there are variations in the degree of soil pollution due to PTEs. A little over 3.9% of samples had significant contamination, compared to 72.3% of samples with low contamination and 23.6% of samples with moderate contamination. Human non-carcinogenic and carcinogenic risk levels were investigated. The hazard index (HI) values for adult ranged from 0.00 to 0.2, and values for children ranged from 0.009 to 1.2. These findings suggest that both children and adults are not at potential risk, except in a few locations. Overall, the results of this study provide the current baseline status of toxic elements in agricultural soil. This would be helpful for developing strategies for sustainable management of the soil resources in the region, as well as for future monitoring programs of the soil quality in the Malwa region as a whole, to track any changes in the contamination levels over time. [ABSTRACT FROM AUTHOR]

Throughout the globe morphological, biochemical and genetic variability exists in chilli and is harnessed to achieve specific breeding objectives. In this study, chilli germplasm was characterized based on horticultural traits, biochemical quantification and simple sequence repeat (SSR) polymorphism for diversity estimation. A total of 36 SSR primers were utilised to study the genetic divergence among 48 genotypes of chilli collected from nine states of India. Among the 36 primers, sixteen amplified null alleles. A total of 41 alleles were detected with average 2.05 alleles per locus. The largest number of alleles (5) were obtained with marker CAMS-234. The polymorphic information content ranged from 0.06 to 0.72 with an average of 0.50. On the basis of SSR analysis, the UPGMA cluster classified 48 genotypes into three groups. There was significant variability in germplasm for all morpho-biochemical traits. Kashi Anmol (100.50 q/ha) expressed the highest yield. Highest vitamin C content at green stage was recorded in IC-561635 (187 mg/100 g) and the greatest capsaicin content (9547.90 µg/g) equivalent to pungency of 171,862.2 Scoville heat units (SHU) was recorded in Bhut Jolokia. Principal component analysis indicates that the first five principal components explain 74.63% per cent of the total variation. Additionally, analysis of molecular variance (AMOVA) showed that 1% of the total genetic variation occurred among the population and 99% genetic variation within the populations, whereas the pairwise Fst specified the moderate genetic variation ranging from 0.002 to 0.020. The present investigation has strengthened the knowledge of genetic worth of this germplasm for application in various genetic improvement programmes. [ABSTRACT FROM AUTHOR]

A survey was conducted in the agricultural fields of mustard of Haridwar district, Uttarakhand, India, where a heavy population of Zeldia was recovered. The morphological, molecular, and phylogenetic characterization confirmed the nematode as Zeldia punctata. The phylogenetic analysis based on 18 and 28S rDNA placed the studied population of Z. punctata close to other populations of the same species. The principal component analysis (PCA) data revealed the high intraspecific and interspecific variations between the populations of Zeldia punctata from different geographical regions. The result indicated a variation between the Indian populations of Z. punctata. Additionally, the selected ecological factors indicated an impact of EC, temperature, and phosphorus on Z. punctata during the flowering and podding time of mustard crops in India. However, the PCA revealed no effect of ecological factors on the nematode diversity indices. In conclusion, Z. punctata, with its high individual numbers on mustard, may affect crop production due to activating the bacterial community of the soil and less space for plant-parasitic nematodes. [ABSTRACT FROM AUTHOR]

A hydro-geochemical study for water-quality assessment was conducted in the Tuticorin region of Tamil Nadu in southern India during the pre- and post-monsoon seasons of 2022 and the water samples are examined to comply with BIS and WHO guidelines. In the present study, the values of TDS (75%), Mg (37.5%), and TH (25%) have exceeded the permissible limits namely 500, 100, and 600 mg/L, respectively. The WQI proposed by CCME is used to analyze water suitability. The Pearson correlation and principal component analysis are used to study the relationship between various physicochemical parameters and principal components of water quality, respectively. Piper & Gibbs diagrams are plotted to identify the water types and the main water type predicted by the piper plot is Ca-Mg-Cl-SO4 which makes up 74.3% of the the samples studied. WQI suggests that 22.5% and 50.0% specimens have excellent water quality during pre and post-monsoon seasons, respectively. [ABSTRACT FROM AUTHOR]

Mercury cycling in coastal metropolitan areas on the west coast of India becomes complex due to the combined effects of both intensive domestic anthropogenic emissions and marine air masses. The present study is based on yearlong data of continuous measurements of gaseous elemental mercury (GEM) concentration concurrent with meteorological parameters and some air pollutants at a coastal urban site in Mumbai, on the west coast of India, for the first time. The concentration of GEM was found in a range between 2.2 and 12.3 ng/m3, with a mean of 3.1 ± 1.1 ng/m3, which was significantly higher than the continental background values in the Northern Hemisphere (~ 1.5 ng/m3). Unlike particulates, GEM starts increasing post-winter to peak during the monsoon and decrease towards winter. July had the highest concentration of GEM followed by October, and a minimum in January. GEM exhibited a distinct diurnal cycle, mainly with a broad peak in the early morning, a narrow one by nightfall, and a minimum in the afternoon. The peaks and their timing suggest the origin of urban mobility and the start of local activities. A positive correlation between SO2, PM2.5, temperature, relative humidity, and GEM indicates that emissions from local industrial plants in the Mumbai coastal area. Principal component analysis (PCA) and cluster analysis (CA) confirm this fact. Monthly back trajectory analysis showed that air mass flows are predominantly from the Arabian Sea and local human activities. Assessment of human health risks by USEPA model reveals that the hazardous quotient, HQ < 1, implies negligible carcinogenic risk. GEM observations in Mumbai during the study period are below the World Health Organization's (WHO) safe limit (200 ng/m3) for long-term inhalation. [ABSTRACT FROM AUTHOR]

Background: A thorough understanding of lameness prevalence is essential for evaluating the impact of this condition on the dairy industry and assessing the effectiveness of preventive strategies designed to minimize its occurrence. Therefore, this cross-sectional study aimed to ascertain the prevalence of lameness and identify potential risk factors associated with lameness in Holstein Friesian crossbred cows across both commercial and smallholder dairy production systems in Bengaluru Rural District of Karnataka, India. Methods: The research encompassed six commercial dairy farms and 139 smallholder dairy farms, involving a total of 617 Holstein Friesian crossbred cattle. On-site surveys were conducted at the farms, employing a meticulously designed questionnaire. Lameness in dairy cattle was assessed subjectively using a locomotion scoring system. Both bivariate and binary logistic regression models were employed for risk assessment, while principal components analysis (PCA) was conducted to address the high dimensionality of the data and capture the underlying structure of the explanatory variables. Results: The overall lameness prevalence of 21.9% in commercial dairy farms and 4.6% in smallholder dairy farms. Various factors such as age, body weight, parity, body condition score (BCS), floor type, hock and knee injuries, animal hygiene, provision of hoof trimming, and the presence of hoof lesions were found to be significantly associated with lameness. Binary logistic regression analysis indicated that the odds of lameness in crossbred cows increased with higher parity, decreased BCS, presence of hard flooring, poor animal hygiene, and the existence of hoof lesions. These factors were identified as potential risk factors for lameness in dairy cows. Principal component analysis unveiled five components explaining 71.32% of the total variance in commercial farms and 61.21% in smallholder dairy farms. The extracted components demonstrated higher loadings of housing and management factors (such as hoof trimming and provision of footbath) and animal-level factors (including parity, age, and BCS) in relation to lameness in dairy cows. Conclusions: The findings suggest that principal component analysis effectively reduces the dimensionality of risk factors. Addressing these identified risk factors for lameness is crucial for the strategic management of lameness in dairy cows. Future research in India should investigate the effectiveness of management interventions targeted at the identified risk factors in preventing lameness in dairy cattle across diverse environments. [ABSTRACT FROM AUTHOR]

Rice metabolomics is widely used for biomarker research in the fields of pharmacology. As a consequence, characterization of the variations of the pigmented and non-pigmented traditional rice varieties of Tamil Nadu is crucial. These varieties possess fatty acids, sugars, terpenoids, plant sterols, phenols, carotenoids and other compounds that plays a major role in achieving sustainable development goal 2 (SDG 2). Gas-chromatography coupled with mass spectrometry was used to profile complete untargeted metabolomics of Kullkar (red colour) and Milagu Samba (white colour) for the first time and a total of 168 metabolites were identified. The metabolite profiles were subjected to data mining processes, including principal component analysis (PCA), Orthogonal Partial Least Square Discrimination Analysis (OPLS-DA) and Heat map analysis. OPLS-DA identified 144 differential metabolites between the 2 rice groups, variable importance in projection (VIP) ≥ 1 and fold change (FC) ≥ 2 or FC ≤ 0.5. Volcano plot (64 down regulated, 80 up regulated) was used to illustrate the differential metabolites. OPLS-DA predictive model showed good fit (R2X = 0.687) and predictability (Q2 = 0.977). The pathway enrichment analysis revealed the presence of three distinct pathways that were enriched. These findings serve as a foundation for further investigation into the function and nutritional significance of both pigmented and non-pigmented rice grains thereby can achieve the SDG 2. [ABSTRACT FROM AUTHOR]

Background Antimalarial drug resistance surveillance and containment are crucial for countries aiming to eliminate malaria. Monitoring resistance evolution through studies before and after treatment policy changes is essential. Methods A total of 939 Plasmodium falciparum-positive blood samples were collected between 2014 and 2015 across 10 sites in India, categorized into 4 geographic clusters. Polymerase chain reaction-amplified products were sequenced to identify point mutations at drug resistance-conferring genes (Pfdhfr , Pfdhps , Pfmdr1, and Pfk13). Results Triple Pfdhfr mutants were found only in northeast India bordering Myanmar, while the wild type (WT) was dominant in central India. Pfdhps WTs were prevalent in all areas, and no double mutants were found. Except in northwest India, Pfmdr1 WT was dominant in all clusters. Nonsynonymous double mutations were only found in northwest India. Only synonymous mutations occurred in Pfk13. These were found in central India at a low frequency. The pattern of linkage disequilibrium and principal component analysis reflects low pressure for drug resistance and heterogeneity between the geographic clusters. Conclusions Resistance levels were highest in northeast India, close to the Myanmar border, where resistance is common. Primaquine has been widely used as a gametocidal and schizonticidal drug, likely contributing to maintaining low drug resistance levels and preventing strong selection for resistance. [ABSTRACT FROM AUTHOR]

This study aims to investigate the factors influencing seasonal and long-term (2003–2021) changes in the near surface ozone (850 hpa) concentrations over different climatic sub-regions of India. Detailed comparison of daily (2019–2021) near surface ozone values of ERA-5 and CAAQMS (Continuous Ambient Air Quality Monitoring Stations) ground-based measurements revealed that ERA-5 is temporally in phase with CAAQMS measurements falling indifferent climatic sub-regions of India. ERA-5 near surface ozone shows statistically significant long-term (2003–2021) positive trends [2–4 percent per decade (ppd)] over most of the climatic sub-regions, over Indo-Gangetic Planes (IGPs), Southern and Central India trends are particularly strong. Trends were also estimated for each season separately, which were largely positive (2–6 ppd) over Central and Southern India in the Autumn and Winter seasons. Extensive climatological analysis reveals that the reversal of winds in the Indian monsoonal system plays a vital role in such trend patterns across the Indian subcontinent. South-westerly winds from June through September presumably bring ozone deficit air of marine origin, thus causing a dilution effect while the North-easterly winds during late Autumn and early Winters plausibly bring ozone-rich air from the stratospheric-tropospheric efflux dominated Himalayan region. It allows near surface ozone enhancement over Central and Southern India. Seasonal Principal component analysis (PCA) revealed that precursor gases (CH4 and NO2) and climatic variables especially specific humidity (SH) are the primary drivers of near surface ozone variability in the Winter season, while in Spring, climatic variables like boundary layer height (BLH), temperature (T) and SH have a significant role. Principal component regression (PCR) reveals a long-term increase in near surface ozone levels mostly dominated by precursor concentration over IGPs and Southern sub-regions. Whereas, BLH, T and SH significantly explain near surface ozone trends over North-eastern and Coastal India. [ABSTRACT FROM AUTHOR]

The disparity in child health outcomes across Indian districts, particularly in Eastern India, is alarming. Approximately half of the districts in this region exhibit very poor child health outcomes, evidenced by alarmingly high neonatal, infant, and under‐five mortality rates. This study analyses the existing levels and patterns of child health outcomes across 112 districts of Eastern India, a region known for its low levels of child health status. To do this, we have constructed a composite child health index (CHI) using nationally representative data from the National Family Health Survey (NFHS‐5). Using Principal Component Analysis, the study uses the CHI values to categorize the districts into high, moderate, and low‐performing districts. The results show a significant variation in CHI outcomes across the districts, with striking regional disparities. Notably, all high‐performing districts were located only in the state of Odisha. In contrast, a substantial proportion of the low‐performing districts were in the state of Bihar, suggesting systemic healthcare deficiencies. Using discriminant function analysis, we obtain the critical determinants of CHI to be sanitation facilities, mother's education, marriage before 18 years, and low body mass index of the mother. Our findings confirm that improvements in these areas are crucial for enhancing child health outcomes and ending intergenerational transmission of poor health outcomes. The implications of this study extend beyond eastern India, offering valuable insights into similar challenges in global low‐ and middle‐income regions. [ABSTRACT FROM AUTHOR]

Cranial measurements have been widely used in various studies in wildlife sciences, ranging from understanding predator ecology to wildlife forensics. However, detailed description of morphometry and sexual dimorphism of the skull of gaur Bos gaurus gaurus is lacking. The present study was undertaken to determine the sexual dimorphism based on the cranial measurements of gaur. A total of 12 individual gaur skulls of male (n = 6) and female (n = 6) were studied in the field from the naturally deceased animals between January 2018 and December 2021 in different ranges of Bandhavgarh tiger reserve (BTR), Madhya Pradesh, India. The skull measurements were analysed using univariate and multivariate statistics to determine whether cranial dimensions could be used to differentiate male and female skulls reliably. A total of 43 morphometrical parameters grouped into nine indices were calculated. Select morphometrical parameters viz PL, GFL, AKI, LBB, LFB, GBEE, GBAN, BPOP and GTCH were significantly different (p < 0.05) between sexes, whereas GBAN were significantly higher in female skulls. The measurements demonstrated that the skull of the gaur was dolichocephalic as the profile length and the otion to otion breath in both male and female were <75% of the length. Overall, 28 linear measurements of both the sexes were statistically significant (p < 0.05; <0.01). The calculated indices revealed that the foramen magnum index in the female gaur were significantly higher. In calculated cranial indices the facial index (a) was higher in female and facial index (b) were higher in males. The two important parameters, facial breadth in facial index (a) and the greatest breadth in facial index (b) were positively correlated, though facial index (a) was statistically not significant between the sexes. The greater inner length of the foramen magnum in female skull resulted in foramen being oval whereas it was circular in males. These parameters were decisive for sexual dimorphism, skull comparison and craniological studies. This study ascertained that the frontal index and skull index had no significant influence and were not good indices for discriminating skulls between male and female. Based on the Principal Component Analysis, it was found that skull of male and female gaurs exhibits differences in cranial morphology viz. cranial profile length or total length (PL) and the least inner height of the temporal groove (LIHT). The findings of the present study provide baseline information on various craniometrical measurements of skull of gaur, indices and parameters for sex identification that can be effectively used in understanding sex biased predation ecology, provide base line information to describe variation across its geographic range, and in identifying skulls recovered in wildlife offence cases. [ABSTRACT FROM AUTHOR]

Morphometric analysis of a drainage basin along with its stream network is indispensable for analysing a river basin's prevailing geomorphology, geo-hydrology, and erosional susceptibility. In this study, an enhanced morphometric evaluation method using Google Earth Engine (GEE) and Principal Component Analysis (PCA) was used to assess and prioritize 12 sub-basins of the Godavari River basin (GRB), India, based on their erosional susceptibility. The findings of erosional susceptibility were validated using the Sediment Yield (SY) model. Our findings highlight that the sub-basins of Indravati, Pranhita, and Manjira, i.e. 42.42% (132707.4 km2) of the entire GRB are at high risk of erosional susceptibility, requiring immediate implementation of soil conservation measures. Our findings also highlight that 52.71% of the GRB is in the mature stage of geological evolution, wherein erosional landform-building processes are still ongoing. Overall, GRB has a relatively low drainage density with dendritic drainage patterns, permeable soils, and elongated sub-basins of enhanced erosional susceptibility. Moreover, the results of the SY model exhibited 90% agreement with the results of the enhanced morphometric analysis. This study presents an efficient framework for enhanced morphometric analysis that can assist policymakers in the demarcation of priority zones for erosional susceptibility. [ABSTRACT FROM AUTHOR]

The rapid deterioration of freshwater ecosystems, particularly rivers, has threatened many living organisms, including human beings. In order to comprehend and maintain the well-being of a river ecosystem, it is important to assess the spatial and temporal variations in its physico-chemical parameters. The aim of the present study was to examine spatial and temporal physico-chemical parameters of snow-fed River Poonch in the Northwest Himalayas from July 2021 to June 2023. In order to generate precise and reliable data, one-way ANOVA, Duncan's multiple range test, Pearson correlation, linear regression, principal component analysis (PCA) and cluster analysis (CA) were used to analyse a total of fifteen physico-chemical parameters of the river. Significant (p < 0.05) differences spatio-temporally in physico-chemical parameters were found through one-way ANOVA followed by Duncan's multiple range test. Pearson correlation revealed that majority of the examined physico-chemical parameters exhibited a robust positive association (r > 0.70) in most cases, apart from DO (r ≥ − 0.80). Linear regression indicated significant (p < 0.05) associations among various physico-chemical parameters, which were substantial both in nature and size, with a coefficient of determination (r2 > 0.70) in most of the cases. PCA showed that physico-chemical parameters such as AT, WT, EC, TDS, FCO2, TA, TH, NO2-N, NO3-N, TP, SO42− and F− were significant for the determination of qualitative characteristics of River Poonch. In CA, two distinct clusters, viz. Cluster-I consisting of Site-III, downstream site prone to pollution and Cluster-II consisting of Site-II and Site-I, mid and upstream sites, respectively, less prone to pollution were obtained. The results of the study revealed that the water quality parameters were found well within the recommended ranges, suggesting that they are conducive for the existence of inhabitant fish species, which influence the local economy of the region. [ABSTRACT FROM AUTHOR]

Drought is a major abiotic stress worldwide limiting chickpea yield drastically. Low heritability and high genotype × environment interactions make the trait-based breeding strategy an unreliable approach. This study was planned to identify the drought-tolerant lines by evaluating yield-based selection indices in a recombinant inbred line (RIL) population derived from an inter-specific cross between drought-tolerant genotype GPF 2 (Cicer arietinum L.) and drought-sensitive accession ILWC 292 (C. reticulatum) at two locations in India (Ludhiana and Faridkot). A total of six yield-based selection indices were calculated and significant variation was observed in the RILs and their parents for yield-based selection indices at both locations. A holistic approach across association analysis and principal component analysis identified drought tolerance index, mean productivity, geometric mean productivity and harmonic mean productivity as key selection indices, which could be used for indirect selection of drought-tolerant lines. Overall, on the basis of these approaches, a total of 15 promising RILs were identified for their use in chickpea breeding programme for developing drought-tolerant cultivars. [ABSTRACT FROM AUTHOR]

Heavy metals in the agrarian wetlands have substantial implications for the environment, agriculture, and human well-being. This study is a comprehensive examination of heavy metal concentrations and hydrochemical characteristics in the Kol wetland system, a Ramsar site located on the southwest coast of India. It represents the first comprehensive assessment of the distribution of nine heavy metals (Cu, Cd, Zn, Pb, Fe, Ni, Mn, Co, and Cr) to evaluate Kol wetland water suitability for aquatic life and irrigation purposes. To achieve this, surface water samples were collected during two consecutive monsoon periods in September 2018 and 2019. The average concentrations of the heavy metals in the Kol area were: Zn (0.31–618 µg/L), Cu (BDL-212 µg/L), Fe (30.17–4418.5 µg/L), Mn (1.2–506 µg/L), Ni (BDL-61.96 µg/L), Cr (BDL-61.96 µg/L), Cd (BDL-46.19 µg/L), Co (BDL-4.03 µg/L), and Pb (BDL-103 µg/L). While Cd and Zn exceeded recommended limits by the US Environment Protection Agency, all metal concentrations fell within acceptable levels for irrigation set by the Food and Agriculture Organization. The spatial distribution pattern revealed significant disparities among the three zones of the study area, with the central and southern regions exhibiting higher metal concentrations than the northern zone. Pollution indices indicated that Kol water is suitable for irrigation, with medium contamination and threat to aquatic life noted at the S3 station. Principal components analysis highlighted siltation processes and anthropogenic activities as likely sources of heavy metal contamination. This scenario provides valuable data for strengthening the supervision of the Kol wetlands. [ABSTRACT FROM AUTHOR]

Marigold oleoresin is an oil-soluble natural colorant mainly extracted from marigold flowers. Xinjiang of China, India, and Zambia of Africa are the three main production areas of marigold flowers. Therefore, this study utilized ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS/MS) technology, combined with Global Natural Products Social Molecular Networking (GNPS) and multivariate statistical analysis, for the qualitative and discriminant analysis of marigold oleoresin obtained from three different regions. Firstly, 83 compounds were identified in these marigold oleoresin samples. Furthermore, the results of a principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) indicated significant differences in the chemical compositions of the marigold oleoresin samples from different regions. Finally, 12, 23, and 38 differential metabolites were, respectively, identified by comparing the marigold oleoresin from Africa with Xinjiang, Africa with India, and Xinjiang with India. In summary, these results can be used to distinguish marigold oleoresin samples from different regions, laying a solid foundation for further quality control and providing a theoretical basis for assessing its safety and nutritional aspects. [ABSTRACT FROM AUTHOR]

The abundance of country-level socio-economic development indices is of limited help unless sub-country-level indices on the quality of policies are also available. Tracing the regional indices landscape of India, this study proposes the state-level Environment Policy Stringency Index for Indian states. Capturing Indian states' policies across six areas with weight determination done deploying principal component analysis and Data Envelopment Analysis-Benefit of Doubt approach, the composite index calculated in the study also examines the scores grouping the sub-national units based upon the income levels. Besides ranking for inter-state comparison, the proposed index is significantly associated with particulate matter pollution levels in states. This study has three key contributions: conceptualising the principal-based sub-national index while making a case for developing sub-country level policy indices, identifying state-level environment policy variables and constructing an Environment Policy Stringency Index for Indian states. [ABSTRACT FROM AUTHOR]

The Betwa River Basin (BRB), a sub-basin of the River Yamuna, is the oldest flowing water system in Central India. The water quality of the rivers are under stress, hence regular monitoring and appraisal is required to know the health of the rivers. Factor analysis and principal component analysis (FA/PCA) multivariate statistical techniques were used to extract three and four varimax factors that explained 96.408 and 100.00 percent of the total variance in water quality, respectively. Cluster analysis (CA) categorizes observed items into distinct quality categories based on correlations between stations and years. Point industrial/sewage effluents, diffuse pollution as runoff from arable land, erosion, and natural source pollution contribute to the pollution of the BRB. As a result, water quality is threatened or impaired, and conditions often departed from natural or desirable levels at Rajghat, Garrauli, Mohana, and Shahijina stations. According to the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI), the surface water quality at the Rajghat and Mohana stations corresponds to fair ecological status. However, the surface water quality of the Garrauli and Shahijina stations has a marginal water quality as per CCME-WQI. From 1985 to 2018, the Shahijina had the most considerable load of nutrients and organic matter, as determined by the CCME-WQI and by comparing the water quality data. A thorough examination had revealed a fluctuating trend in the BRB pollution, particularly at all stations. Results indicate that between 1985 and 2018, the only defense mechanism of the river was the auto purification mechanism, which is strongly influenced by the drought, point pollution source, and extreme meteorological events that probably cause these fluctuations. [ABSTRACT FROM AUTHOR]

High concentration of trace elements in groundwater poses more health risks to humans by drinking groundwater and dermal contact. This work aimed to assess the trace element concentration in groundwater, water quality for drinking purposes, and its effect on human health upon prolonged consumption. The study was carried out in the gneissic terrain of Perambalur District, Tamil Nadu, India, where groundwater is used mainly for drinking, agricultural, and domestic purposes. Hydrochemistry, water quality, and health risk assessments of trace elements from 44 groundwater samples for pre- and post-monsoon were determined by drinking water quality, hazard quotient, hazard index, and carcinogenic risk. The dominance of trace elements in groundwater was in the order of Zn > Fe > Cu > Ni > Te > Pb > Co. Ni and Co are released more during the post-monsoon, and Zn, Fe, Cu, and Pb concentration during the pre-monsoon. The dominant type of groundwater was Ca-HCO3 and mixed Ca–Mg–Cl type. The dissolution of fissile hornblende biotite gneissic rock dissolves more trace elements to groundwater than charnockite rock. The correlation matrix indicates that major ion and trace elements were positively good in groundwater during the pre-monsoon and post-monsoon 2018. The principal component analysis suggests that the weathering of rocks, rainwater recharge, and evaporation processes controlled the hydrochemistry of trace and major ions. The concentration of Pb, Ni, and Cd elements exceeded the permissible limit of BIS and WHO; these elements are unsuitable for drinking. The trace element concentration in groundwater was good for drinking and irrigation in the study area, except in a few wells. The hazard quotient and hazard index were computed, which revealed that non-carcinogenic risk to human health by drinking groundwater was more of a problem for children than adults. This study will help prevent children from health risks of trace elements. [ABSTRACT FROM AUTHOR]

This study is carried out to understand the degree of soil pollution, transport mechanism, and distribution pattern of potentially toxic elements (PTEs), including the exposure effects on human health. Towards this, topsoil samples were collected from the Saman wetland and surrounding agricultural fields in the Gangetic plain, India. The results show that the mean concentration of Cu, Hg, Zn, Pb, Th, As, U, and Cd of both soil types exceed the natural background values. The multivariate analysis suggests the soils are moderately contaminated with As, Cd, Zn, Pb, and Hg (possibly from anthropogenic sources) and heavily contaminated with Th and U, likely ascended from geogenic sources. The GIS-based geostatistical plots coupled with principal component analysis (PCA) and hierarchical cluster analysis (HCA) apportion the sources of these toxic elements, which vary greatly and are closely correlated to the geogenic processes and local anthropogenic sources like pesticides and agrochemicals. The health risk assessment revealed that the cumulative hazard index (HI) values of PTEs are lower than the safe level, suggesting no significant noncarcinogenic effect for adults and children. However, excess cancer risk (ECR) values exceed the permissible limit (1 × 10−6), signifying that exposure to the toxic element concentration may cause cancer in the exposed population, most probably in the children subpopulation. Thus, this study highlights the importance of local compliance, ensuring the quality checks and management policies in using pesticides and other agrochemicals containing PTEs to control the imposed cancer risks. [ABSTRACT FROM AUTHOR]

Native potatoes are an important source of biotic/abiotic resistance and quality traits improvement. The aim of this study was to analyse genetic diversity and population structure using 14 simple sequence repeat (SSR) markers and 51 distinctness, uniformity and novelty (DUS) phenotypic traits in native potato collection (94 accessions) in India representing sub-tropical plains (45), north-west (NW) hills (25), north-east (NE) hills (22) and two unknown sources. Polymorphic 14 SSR loci revealed 97 alleles, where allele sizes per marker ranged between 75 bp (STM0037) and 296 bp (STM5114), and the number of alleles per marker varied between 2 (STI0030) and 13 (STPoAc58/STM0031). The polymorphic information content (PIC) of SSR was found between 0.29 (STI0030) and 0.90 (STPoAc58/STM0031). The accessions were grouped into four major clusters using both SSR and phenotypic traits separately based on the Jaccard similarity coefficient using the neighbour-joining clustering approach by the DARWin software. However, both clusters contained different accessions and intermixing was observed amongst collection sources. Clusters were supported by principal component analysis (PCA) plots based on both SSR and phenotypic data. Population structure analysis revealed four populations using the SRUCTURE software based on the SSR data. Taken together, our study suggests that SSR and DUS trait profiling are the key components of genetic diversity and population structure analysis in the potato. This would be useful for genetic fidelity testing of true-to-type accessions in future. [ABSTRACT FROM AUTHOR]

The discharge of industrial effluents has a significant impact on the Water Quality Index (WQI) of the water bodies and is a major source of contamination of groundwater. The present study investigated the physicochemical characteristics and scrutinized the pollution potential of the tannery, textile, and electroplating effluents uploading into the Kala Sanghian drain, located in Jalandhar, Punjab, India. In this study, 12 samples were collected from the four sites (leather complex drain (LD), leather complex outlet (LO), focal point drain (FD), and Bulandpur drain (BD)) of Kala Sanghian drain in the dry season. The result showed that the drain under consideration is very much contaminated and the water is not suitable for irrigation and agricultural purposes. Rather it has a bad impact on the health of local people, the physiology of aquatic organisms, and the soil quality of agricultural land nearby. The present study confirmed the water quality index was more than 100, indicating a highly contaminated drain and water is unfit for any use. The correlation analysis shows that there exists a positive correlation between TDS and temperature (r = 0.994), DO and pH (r = 0.808), BOD and temperature (r = 0.987), BOD and TDS (r = 0.978), EC and temperature (r = 0.963), EC and TDS (r = 0.954), and EC and BOD (r = 0.956). The principal component analysis (PCA) confirms that PC1 alone has more than 89% of the variance with high positive loading for TDS, temperature, EC, and BOD. The hierarchical cluster analysis (HCA) reflected two clusters where cluster 1 consists of pH, DO, temperature, and BOD of water while cluster 2 consists of TDS and EC of water. The PCA and HCA study of the data set confirms the high degree contribution of anthropogenic activities through the application of chemicals in agriculture, disposal of municipal waste, and industrial effluents in the deterioration of water quality. The results of the study will help to enhance the sustainable action plan for the management of industrial effluents in the studied area. [ABSTRACT FROM AUTHOR]

Owing to globalization, the popular indigenous products from various ethnical backgrounds are increasingly making their presence felt all over the world. This opens up a new arena for food technologists to conduct intensive research and developmental activities on the indigenous products. In this study, six popular Indian rice products viz. plain rice, pulao, kheer, idli, khichdi and pakoda were formulated and evaluated for their proximate composition, sensory attributes and textural parameters. Out of these, kheer with semi-fluid consistency had the highest moisture content and the lowest protein and fiber contents. Kheer is similar to rice pudding consumed in the U.S.A. and Europe. Fat content was the highest in pakoda being a crispy fried product. Khichdi being a cereal pulse combination product had the highest protein content. Khichdi is also the national dish of India. The overall acceptability scores were high for pakoda, pulao and kheer which were 8.60, 7.90 and 7.30, respectively. Electromyographic analysis was conducted for in vivo textural evaluation of formulated rice products. The analysis showed reproducible masticatory behavior of human subjects within an EMG session. Twenty-five masticatory parameters, which could establish significant (p < 0.05) differences between textural perceptions among the formulated rice products, were used for cluster analysis followed by principal component analysis (PCA). The PCA resulted in one principal component which could explain data variance of up to 93%. Further, significant positive correlations were found between EMG parameters and sensory textural attributes indicating applicability of electromyography for comprehensive textural evaluation of formulated rice products. [ABSTRACT FROM AUTHOR]

Stingless bees also referred to as meliponine bees and morphological characteristics of these differ depending on are the species and environmental kinds. The current study explores morphology and morphometrics of Tetragonula iridipennis Smith in Tamil Nadu, India. The morphometrics of worker bees were compared over locations. The bees captured in the Kolli hills were significantly larger than those collected elsewhere. The mean value of head length (HL) (1.43 mm), head width (HW) (1.68 mm), antennal length (AL) (1.98 mm), hind leg length (HLL) (3.54 mm) and forewing length (FL) (3.84 mm) were recorded. The results revealed variance of four principal components (PC) reaching 82.4%, as (PC1) 38.58%, (PC2) 20.95%, (PC 3) 19.75% and (PC4) 8.10%. The characters of FL, HW, FW (forewing width), HLL, AL, OOD (ocello ocular distance), HTW (hind tibial width) and HL were the most discriminative in the principal component analysis. [ABSTRACT FROM AUTHOR]

In this study, an extensive exploration survey of wild progeny was conducted which yielded 18 candidate plus trees (CPTs) of Terminalia bellerica. Seeds of these CPTs were collected from diverse locations between 10°54′ and 28°07′ E longitude, and 76°27′ and 95°32′ N latitude, covering 18 different locations across 5 states of the Indian subcontinent. The objective of the progeny trial was to assess genetic associations and variability in growth and physio-chemical characteristics. Significant variations (p < 0.05) were observed among the growth traits, encompassing plant height, basal diameter, girth at breast height and volume, as well as physio-chemical characteristics such as leaf length, width, area and chlorophyll content, carotenoids, and protein in the progeny trial. Broad-sense heritability (h2b) estimates were consistently high, exceeding 80% for all growth and physiological related traits under investigation except for plant height, leaf length, and girth at breast height. A correlation study revealed that selecting based on plant height, leaf area, and girth at breast height effectively enhances T. bellerica volume. A moderate genetic advance in percent of the mean (GAM) was observed for most traits, except leaf length, leaf width, girth at breast height, and plant height. Across all 13 traits, phenotypic coefficient of variation (PCV) surpassed genotypic coefficient of variation (GCV). Utilizing principal component analysis (PCA) and dendrogram construction categorized the genotypes into seven distinct groups. In conclusion, the study has demonstrated that targeting girth at breast height and plant height would be a highly effective strategy for the establishment of elite seedling nurseries and clonal seed nurseries for varietal and hybridization programs in the future. [ABSTRACT FROM AUTHOR]

• Every part of Moringa oleifera is valuable for food and enriched with nutrients, minerals, antioxidants, proteins, and phenols. • Thirty four germplasm are profiled for protein, antioxidants and nutrient content in leaves. • PCA using the fifteen nutritional traits of thirty-four accessions of M. oleifera indicated that 74.70 % variability was accounted for the first six principal components (PCs) with eigenvalues ≥1. • Protein content was significantly and highly correlated with nitrogen content in leaves (r = +1.0). • High magnitude and significant correlation were found between FRAP and DPPH (r = +0.9). • The thirty-four germplasm were grouped in five main clusters and cluster V had maximum mean values for iron, zinc, manganese, calcium, magnesium, sulphur, nitrogen, potassium, protein, total phenols, DPPH and FRAP. This study aimed to select elite germplasm based on nutritional, antioxidants and protein profiling of leaves of Moringa oleifera germplasm. Principal components analysis (PCA) using the fifteen nutritional traits of thirty-four accessions of M. oleifera indicated that 74.70 % variability was accounted for the first six principal components (PCs) with eigenvalues ≥1. The first principal component (PC1) had an eigenvalue of 3.6 and explained 23.90 % of the total variation. Nitrogen, protein, magnesium, iron, zinc, calcium and potassium had high positive eigenvectors in PC1. The second component (PC2) explained 15.27 % of the total variance with an eigen value of 2.29 and positively correlated to copper, calcium, phosphorus and total phenols. Protein content was significantly and highly correlated with nitrogen content in leaves (r = +1.0). High magnitude and significant correlation were found between FRAP and DPPH (r = +0.9). The thirty-four germplasm were investigated in this study on quality parameters at ICAR-Central Horticultural Experiment Station, Godhra, Gujarat, India and grouped in five main clusters. Distance estimates based on the fifteen qualitative traits ranged from 2734.15 to 3868.43. The cluster V had maximum mean values for nutrients (mg/100 g dw) iron (81.76),zinc (7.66), manganese (27.13), calcium (4470.58), magnesium (1068.28), sulfur (3758.68), nitrogen (4615.84), potassium (1558.51), protein (29.40 g/100 g), total phenols (900.21 mg GAE/100 g fw), DPPH (31.17 µmol (TE)/g fw) and FRAP (50.42 µmol (TE)/g fw). The germplasm CHES D_40 and CHES D_45 (cluster V) could be utilized for further exploration based on their nutritional, antioxidants and protein content and for conservation of nutritionally superior germplasm. [ABSTRACT FROM AUTHOR]

Despite the widespread attention given to discrimination of fuel, differentiating Indian kerosene by the scheme origin has yet to be reported. The scheme origin predominantly governs the selling price of Indian kerosene. Subsidized kerosene, which is from the Public Distribution Service (PDS), is often illegally sold as a nonPDS scheme at a higher price. The current study explores the differences between PDS and nonPDS Indian kerosene based on their infrared fingerprints acquired by attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy. A total of 19 kerosene samples, composing PDS and nonPDS schemes, were purchased from various geographical locations in India. The global IR region was first truncated into three sub-IR regions containing various clustered peaks. Then, the baseline of the sub-IR regions and the global counterpart were corrected via the asymmetric least squares algorithm, followed by normalization to sum. By this, 12 sub-datasets were prepared for discriminating the kerosene samples by the scheme. The spatial distribution of the samples was first examined using the scores plot of principal component analysis. Then, predictive modeling coupled with random resampling was performed to determine the discriminatory capability of the IR dataset. Results showed that the inter-geographical location variation was much more pronounced than the inter-scheme one. Predictive modeling performed on kerosene samples from Delhi alone achieved an accuracy of approximately 86% for testing samples via the K-nearest neighbor algorithm in discriminating the samples by scheme. In conclusion, ATR-FTIR spectroscopy coupled with predictive modeling could be applied to determine the scheme of unknown kerosene. [ABSTRACT FROM AUTHOR]

High temperature affects wheat yield severely. This study aimed to explore the variation and recognition of heat responsive traits, to enhance wheat productivity in high temperature stress condition. The recombinant inbred lines were developed by crossing of released wheat variety MACS2496 (heat sensitive) and WH730 (heat tolerant). The experiments were conducted into 2 years at three locations of two planting conditions (heat and terminal heat stress). Combined analysis of variance shows significant variations among all the studied traits at individual location, year and planting conditions. The phenological and yield component traits were highly influenced by environment under terminal heat stress condition. Days to heading and thousand kernel weight coupled with high heritability and high genetic advance per cent of mean in heat and terminal heat stress environments. In heat and terminal heat stress planting conditions, tiller number per plant, kernels per spike, kernel weight per spike and thousand kernel weight confirm positive relationship with grain yield per plant by correlation and principal component analysis. Path and multiple regression analysis accomplish that tiller number per plant, kernel weight per spike, kernel per spike and thousand kernel weight were identified as the key contributor towards grain yield per plant in heat and terminal heat stress environment. Thus, all‐inclusive approaches demonstrated that the promising traits deliver a framework to develop heat tolerant cultivars in future. [ABSTRACT FROM AUTHOR]

Tamarindus indica L. is a multipurpose monotypic agroforestry species, possessing numerous domestic and industrial applications. It grows naturally in subtropical and semi-arid tropical regions of the world. Sixteen quantitative traits of T. indica were used in this study to unravel the phenotypic diversity on a large scale (422 accessions sourced from 12 districts of 8 Indian states) using multivariate analysis. Significant difference between the provenances were recorded for all the traits (P < 0.001). In terms of total pod weight, shell weight, fiber weight, pulp weight, real pulp value, and seed weight, Karnataka outperformed the other states. There were strong positive associations between real value of pulp (RVP) and all pod size traits ranging from 0.37 to 0.93. Titratable acidity was found to have a significant positive relationship with pod size and pulp recovery (r = 0.513–0.742); sugar/acid ratio with seed percent (r = 0.718) and shell percent (r = 0.537). According to the principal component analysis (PCA), the first five principal components accumulated 98.61% of the variation. Morphological cluster analysis revealed four distinct clusters with high diversity. A unique accession from Karnataka was selected by participatory breeding, enabling the farmer to establish a successful nursery and conserve the valuable genotype. Our study provides valuable information about phenotypic diversity, in situ evaluation, selection indices for plus trees and conservation of tamarind genetic resources in India. [ABSTRACT FROM AUTHOR]

Brain tumors are a leading cause of mortality in India, with over 28,000 cases reported annually, resulting in more than 24,000 deaths per year as per the International Association of Cancer Registries. Early detection, segmentation, and accurate classification are crucial in effective tumor analysis, and various algorithms have been developed to achieve this. This study proposes a new approach for the detection and classification of Meningioma and Sarcoma brain tumors using both single slices of MRI and CT, as well as input-level fused images of MRI & CT. Our approach involves the implementation of the PrinciResNet16 model for classification of brain tumors. This model is based on Principal Component Analysis (PCA) and ResNet techniques. We report that our approach significantly improves the accuracy, sensitivity, and specificity parameters to 99%, 95%, and 95%, respectively, based on a dataset of 600 fused slices and 1000 single slices obtained from reputable sources. Our findings hold promise for better brain tumour detection and therapy, which are a significant cause of mortality globally. [ABSTRACT FROM AUTHOR]

Litchi (Litchi chinensis Sonn.) is considered one of the most important sub-tropical fruits of the world. In the western part of Odisha, India, litchi growers are facing problems of unstable and lower marketable yield and inferior quality due to a higher incidence of fruit cracking, fruit drop, low sugar content, and higher fruit acidity. Keeping in mind the positive effects of nutrients and bioregulators, the current study was conducted to elucidate their impact on fruit yield and quality in the farmers' field of Jamankira block in Sambalpur district of Odisha, which is under the care of Odisha University of Agriculture and Technology, India. For this study, eight-year-old litchi trees were selected. With 12 treatments, the experiment was set up in a Randomized Block Design replicated thrice, as follows: T1: spray treatment with Borax—0.5%; T2: spray treatment with Borax—0.3%; T3: spray treatment with ZnSO4—0.75%; T4: spray treatment with ZnSO4—0.5%; T5: spray treatment with CaCl2—0.5%; T6: spray treatment with CaCl2—0.1%; T7: spray treatment with humic acid—1.5%; T8: spray treatment with humic acid—1%; T9: spray treatment with seaweed extract—0.5%; T10: spray treatment with seaweed extract—0.1%; T11: foliar spray with NAA—20 ppm; and T12: control (Water Spray). The current study compared foliar feeding treatments comprising different nutrient and bioregulators, which were applied during the first week of December, just after the completed formation of new leaves and the untreated control. The highest total number of fruits per plant was recorded in plants sprayed with 0.5% ZnSO4 (T4) followed by those treated with 1% humic acid (T8). The highest total fruit yield was recorded in plants subjected to foliar feeding with 0.3% Borax (T2) which was found to be statistically similar to plants treated with 0.1% seaweed extract (T10) and 0.5% seaweed extract (T9). Among the treatments, a better response, i.e., a higher number of marketable fruits and marketable yield, was recorded in litchi plants treated with 0.3% Borax (T2) followed by 0.5% zinc sulphate (T4), 1% humic acid (T8), and 0.1% CaCl2 (T6). The application of 1% humic acid (T8) followed by 1.5% humic acid (T9) enhanced fruit setting (%) and fruit retention rates (%) and reduced the fruit drop rate (%). The enhanced fruit size (fruit length and fruit width) and higher fruit weight was obtained in litchi plants treated with 0.3% Borax. The foliar application of 0.3% Borax (T2) also resulted in a higher TSS, total sugars, reducing sugar content, lower acidity, the highest aril weight, and lower seed weight in litchi cv. Bombai. In this research, among the five principal components, only PC1 demonstrated approximately 45.14% variability within the influential axes. PC1 contributed the highest proportion (48.9%) to the overall variability, followed by PC2 with 29.1%, PC3 with 11.9%, PC4 with 0.59%, and PC5 with 0.20%. Consequently, the outcomes of the principal component analysis indicate the presence of extensive variability among treatments. [ABSTRACT FROM AUTHOR]

Cashew is cultivated in varied agro-ecological regions of India and yield levels vary with regions. Therefore, to identify stable genotype for yield, 18 genotypes were tested in four environments for nut yield and ancillary traits during 2008 to 2018 in randomized block design with two replications. The data of 6th annual harvest and cumulative nut yield of six years was analyzed employing additive main effect and multiplicative interaction (AMMI) and genotype and genotype by environment (GGE) methods. Analysis of variance for 6th annual harvest indicated significant differences (p < 0.01) for eight traits. Environments varied significantly (p < 0.01) for seven traits. Genotype by environment (G × E) interactions were significant (p < 0.01) for all traits. Analysis of variance for cumulative yield revealed significant variations between genotypes, environments, G x E interactions. Interaction principal component analysis (IPCA) 1 (84.39%) and IPCA 2 (10.27%) together captured 95% of variability. Genotypes, environments and G × E interaction were accounted for 16.18%, 4.50% and 77.22% respectively of total variation. The environment Pilicode discriminated better while Vridhachalam was representative. BPP-8 and Vengulra-7 were the winning genotypes in Bhubaneswar while Kanaka and Priyanka in Pilicode, Vengurla-4 in Jhargram and UN-50 in Vridhachalam. Therefore, promoting cultivation of these winning genotypes in the corresponding environments is highly recommended to enhance cashew nut production. As per ASV (AMMI stability value,) K-22-1 was stable genotype followed by Bhubaneswar-1. As per YSI (yield stability index), Bhubaneswar-1 was stable and high yielding followed by K-22-1 and BPP-8. Thus stable genotypes identified in this study viz., K-22-1 and Bhuvaneswar-1 are recommended for cultivation in west and east regions of India which have most cashew growing areas for increasing the cashew nut production. [ABSTRACT FROM AUTHOR]

The effects of urbanisation in developing countries like India call for measuring regional disparities in Quality of Life (QOL). Though there exists, several internationally recognized indexes to assess QOL, a regional QOL assessment is yet not studied in India. The study attempts to develop such an assessment framework for measuring objective QOL at the regional level using a composite index, taking the case of Kozhikode, Kerala, India, as a case example. Firstly, a set of 19 variables under five domains of QOL was arrived at through several steps of screening processes, refinement from a master list, and a final expert opinion survey. Secondly, a Composite Quality of Life Index (CQOLI) was formulated by conducting a series of statistical analyses on the data set, including Principal Component Analysis (PCA). Thirdly, a spatial analysis of QOL of the study area was conducted by mapping the CQOLI scores to understand the pattern and analyse inequities. Accordingly, the spatial study units were grouped into High, Medium, and Low QOL. Out of the total settlements, it was found that 20% fell in high QOL, 46.25% in medium QOL, and 33.75% in low QOL. The pattern was spatially analysed based on the topographical divisions, namely lowlands, midlands, and highlands, and it was found that the QOL decreased from lowlands towards highlands. Finally, solutions and strategies which may be used as policy directives were proposed for each QOL group. The insights from the study are helpful for planners and decision-makers while implementing interventions in the study region. The methodology adopted here can be replicated in other regions of similar scale by altering the variables suited to the context. [ABSTRACT FROM AUTHOR]