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Water is the most essential substance that supports life on earth. Animals and plants require water for their survival. Since water is being lost or used by our body, it is essential to replace it constantly. Humans need clean, potable water for consumption and to meet their daily hygiene needs. However, increased anthropogenic activities have caused a drastic increase in heavy metals in fresh waters. Heavy metals interfere with the normal physiology of the human body. It binds to cellular components, leading to dysfunction of the metabolic processes in our body. This study was undertaken to study the geospatial distribution of selected heavy metals in open-well waters within Mangalore City Corporation limits. Mangalore is perched strategically on the path of rapid development, heading toward becoming a smart city in India. Water samples were collected from all 60 wards in the jurisdiction of Mangalore City Corporation. The fluoride concentration was estimated using the spectrophotometric method using the Sodium 2-(parasulfophenylazo)-1,8-dihydroxy3,6-naphthalene disulfonate (SPADNS) reagent. Similarly, iron was estimated using the phenanthroline reagent. The findings report that the pH of the samples was acidic in 20 wards. Panambur, Kunjathbail North, Mannagudda, Court and Cantonment water was colored. Kunjathbail (North), Kunjathbail (South), Kambala, Kadri North, Bendoor, Bolar, Mannagudda, and Markada, showed high turbidity levels. The fluoride concentration in the samples collected from 60 wards of Mangalore city was less than 1.5 ppm, which is the permissible limit by the World Health Organization. Iron is within the permissible limit except for the wards Court and Boloor, which showed an iron concentration of 0.4 ppm and 3.08 ppm, respectively. However, arsenic was not detected in any of the 180 samples collected from the 60 wards of Mangalore City Corporation.

Salt stress is a major abiotic stress affecting the productivity of rice crop worldwide. This study screened a set of 71 rice genotypes collected from coastal parts of Goa and Karnataka states in India for seedling stage salinity tolerance to identify genotypes alternative to standard salt-tolerant donors Pokkali, FL478, etc. Phenotyping for seedling stage tolerance was carried out under micro plots at an induced salinity of 12 dS/m. For haplotyping, 14SaltolQTL linked simple sequence repeat (SSR) markers on chromosome 1 were utilized. On the basis of the response to salt stress, 10 genotypes were found tolerant, 16 moderately tolerant, 29 sensitive and 15 as highly sensitive. Among the SSR markers, marker RM10871 was the most polymorphic with a polymorphic information content of 0.90, exhibiting 14 different alleles followed by RM10793 (0.84) and RM3412 (0.80) with 8 and 7 alleles, respectively. These markers also exhibited high values for the effective number of alleles (Ne) and gene diversity (I). The haplotype analysis revealed that the allelic constitution of theSaltolregion of 10 tolerant genotypes from our study varied in comparison to the reference tolerant check FL478. Further, the haplotype of three tolerant genotypes, namely, Goa Dhan 2, Panvel 1 and Goa wild rice (GWR) 005 appears to be completely different from the FL478 haplotype indicating tolerance in these genotypes is controlled by genomic region other thanSaltol.These three genotypes with probable novel regions for seedling stage salt tolerance can be considered for enhancing salinity tolerance of rice cultivars.

Land degradation is becoming a serious problem in the west coast region of India where one of the world's eight biodiversity hotspots, the ‘Western Ghats’, is present. Poor land management practices and high rainfall have led to increasing problems associated with land degradation. A long-term (13-year) experiment was done to evaluate the impact of soil and water conservation measures on soil carbon sequestration and soil quality at three different depths under cashew nut cultivation on a 19% slope. Five soil and water conservation measures - continuous contour trenches, staggered contour trenches, half-moon terraces, semi-elliptical trenches, and graded trenches all with vegetative barriers of Stylosanthes scabra and Vetiveria zizanoides and control were evaluated for their influence on soil properties, carbon sequestration, and soil quality under cashews. The soil and water conservation measures improved significantly the soil organic carbon, soil organic carbon stock, carbon sequestration rate and microbial activity compared to the control condition (without any measures). Among the measures tested, continuous contour trenches with vegetative barriers outperformed the others with respect to soil organic carbon stock, sequestration rate, and microbial activity. The lower metabolic quotient with the measures compared to the control indicated alleviation of environmental stress on microbes. Using principal component analysis and a correlation matrix, a minimum dataset was identified as the soil available nitrogen, bulk density, basal soil respiration, soil pH, acid phosphatase activity, and soil available boron and these were the most important soil properties controlling the soil quality. Four soil quality indices using two summation methods (additive and weighted) and two scoring methods (linear and non-linear) were developed using the minimum dataset. A linear weighted soil quality index was able to statistically differentiate the effect of soil and water conservation measures from that of the control. The highest value of the soil quality index of 0.98 was achieved with continuous contour trenches with a vegetative barrier. The results of the study indicate that soil and water conservation measures for cashews are a potential strategy to improve the soil carbon sequestration and soil quality along with improving crop productivity and reducing the erosion losses.

The currents study evaluated the morphology (apperture, size, perine structures and surface ornamentation) of treated spores of 45 selected fern species from the Western Ghats of India, using Scanning Electron Microspcopy (SEM). Twenty-six species of fern spores were trilete type, while 19 of them had monolete aperture types. The size of the spore were found to be highly variable (20X20µm to 60X60µm) with an average mean spore size of 44 µmX38µm. Further more the spores were found to have a highly diverse perine ornementaion with 11 different types of perine structures. Gammate and psilatetype of perine ornamentation,and Globose and ellipsoidal spore shape were found to be the most common within the studies fern spore samples.The variability found in the spore ultra structure and perispore ornamentation of the selected pteridophytes species reflects the morphological differences observed in the sporophyte. The spores could be an important source of characteristics with systematic value in fern taxonomy.The spore morphology of the examined pteridophytes studied common, endemicor otherwise will find a significant role in future taxonomic surveys, and other morphology, Palynology, discrimination, and identification studies of pteridophytesin the Western Ghats.

Soil quality (SQ) under any agriculture system is greatly influenced by source of nutrients, type of soil, crop, and their management practices. In this regard, a field experiment was conducted und...

The current investigation is an attempt to verify the claim of a new variant of P. vittata L. as P. vittata L. nano, with evidence of molecular data and phylogenetic analysis, in addition to morphological considerations. Classical taxonomic key and SEM imagery are used to elucidate morphological variations in the reported variant. DNA barcoding marker loci ribulose-1,5-bisphosphate carboxylase/oxygenase large sub-unit (rbcL) is utilised to detect the molecular incongruences in the same. Morphological examination revealed subtle changes in size of the mature sporophyte and the perine structure of the spores. Molecular analysis of the reported variant of P. vittata L. nano, presented three transitions and transversions in the otherwise highly conservative rbcL sequence. The translated amino acid sequences between the two samples also exhibited four notable changes in amino acid composition. The phylogenetic analysis based on rbcL sequences, resulted in partially resolved clades within Pteridaceae which include other ecotypes of P. vittata and the P. vittata L. nano sequence. Molecular evidence in addition to the sporophyte morphology indicates that the reports of a new variant of P. vittata L. are a potential new ecotype of P. vittata L. as P. vittata L. ecotype nano.

Soil salinity and acidity are some of the major causes of land degradation and have a negative impact on agricultural productivity. Assessing soil quality (SQ) of soils affected by soil salinity and acidity is required for their sustainable utilization for agricultural production. The aim of the present study was to evaluate the SQ of the salt-affected acid soils of the Indian West Coastal region using the additive and weighted soil quality indices (SQIs). The SQIs were developed using a total dataset (TDS) and a minimum dataset (MDS). The TDS comprised of 15 different soil properties as electrical conductivity (EC), pH, bulk density, soil available nitrogen (N), phosphorus (P), potassium (K), sulfur (S), boron (B), iron (Fe), manganese (Mn), copper (Cu), zinc (Zn) and exchangeable calcium (Ca), magnesium (Mg), and sodium (Na) measured on 300 soil samples (depth 0–0.15 m). Based on principal component analysis and correlation analysis, an MDS with soil properties like soil pH, EC, Na, Cu, Mn, and BD was formed. Using two approaches (additive and weighted), two datasets (TDS and MDS), and two scoring methods (linear and non-linear), eight SQIs were developed. The MDS-based linear weighted and non-linear weighted SQI found suitable to evaluate SQ of salt-affected acid soils and SQI had a significant and negative correlation of − 0.83 and − 0.70 (p

The coastal ecosystem is one of the most fragile ecosystems to climate change. Soil salinization in these ecosystems due to climate change-induced sea-level rise could be a major threat and constraint to agricultural production. Thus, assessing the soil quality of these soils using a suitable indexing method can help to decide the countermeasures for their sustainable utilization. The present study aimed to evaluate the soil quality of the salt-affected soils in the coastal region of India using different soil quality indexing methods. The soil quality indices (SQIs) were developed using two scoring methods: linear and non-linear of the minimum dataset and weighted approach. Based on electrical conductivity (EC1:2.5, EC in 1:2.5 soil to water ratio), the soils were categorized into five classes as non-saline, slightly-saline, moderately-saline, strongly-saline, and very strongly-saline. The soil salinity impacted the soil's physical, chemical, and biological properties significantly. Using principal component analysis and correlation, a minimum dataset comprising of eight soil properties namely basal soil respiration, urease enzyme activity, EC, soil available copper, zinc, boron, iron and soil pH was identified. The overall performance of the weighted SQIs developed using non-linear scoring was better than linear scoring. The weighted SQI developed using non-linear scoring (SQINLW) revealed that the class non-saline had the highest soil quality values and the very strongly saline the lowest. The SQINLW correlated strongly with the EC1:2.5 (r = 0.96; p moderately saline = slightly saline > strongly saline > very strongly saline and thus, the SQINLW could be used as an effective tool to assess the soil quality of salt-affected soils of the coastal region. The correlation analysis between the SQIs and grain yield for different salinity classes revealed significant (p

The present investigation was undertaken to assess the hybridity of experimental F1 plants derived from the crossing of salinity and/or submergence tolerant landraces with the high-yielding popular varieties of the west coast region of India. Seven microsatellite markers were utilized for confirming the hybridity of the 16 F1 plants developed from four cross combinations, viz. Karjat-3 X KS-19-2 (Cross 1), Goa dhan-3 X Jaddubatta (Cross 2), Jaya X KS-19-2 (Cross 3) and Karjat-3 X Jaddubatta (Cross 4). Polymorphism survey using above seven markers between the parents of all the four crosses revealed that six of them were polymorphic, whereas one marker was monomorphic. The marker RM21539 was found to be polymorphic in all the four cross combinations, followed by RM493, RM3412, RM206 and RM10843 exhibiting polymorphism in three crosses, while marker RM25181 was polymorphic in two crosses. The screening of F1s with polymorphic markers revealed that the F1s from Cross 3 exhibited heterozygosity (showing alleles from both the parents) at six marker loci, whereas the F1s from Cross 1 and Cross 4 at five loci and Cross 2 at two marker loci, thereby confirming hybridity in all the 16 tested F1 plants.

Pteridophyte richness and diversity in Kudremukh National Park (KNP) was assessed using qualitative and quantitative diversity indexing methods, along with the geographic spatial distribution of the extant pteridophyte flora. The field research design employed a stratified random sampling method and was conducted in two phases. Phase 1 included the survey, identification and distribution of the pteridophyte flora and Phase 2 was to study the diversity of the extant pteridophytes throughout the KNP using seven transects. The region exhibited rich and highly diverse (Shannon-Wiener Diversity Index of 3.38), non-homogenous (compared to normal Raunkiaer’s frequency curve) stand of 46 different unevenly (evenness index 0.64) distributed pteridophyte flora. The study region was dominated by two unambiguous pteridophyte species of weedy nature (Pteridium aquilinum and Dicranopteris linearis), with a high Simpson's dominance index of 0.96. The study reports eight endemic, two rare, five at risk and seven vulnerable and near-threatened IUCN listed pteridophyte species in the study region. The quantitative diversity indices i.e. frequency, density, abundance, relative abundance and important value index of each extant pteridophyte is calculated. The study also noted that some endemic species such as Osmunda huegeliana and Cyathea nilgirensis present in KNP needed immediate conservation efforts. This study gives an extensive report on the extant pteridophyte flora of KNP and will help future taxonomic surveys and research, as well as conservation and sustenance measures.

Conventional methods of plant nutrient estimation for nutrient management need a huge number of leaf or tissue samples and extensive chemical analysis, which is time-consuming and expensive. Remote sensing is a viable tool to estimate the plant’s nutritional status to determine the appropriate amounts of fertilizer inputs. The aim of the study was to use remote sensing to characterize the foliar nutrient status of mango through the development of spectral indices, multivariate analysis, chemometrics, and machine learning modeling of the spectral data. A spectral database within the 350–1050 nm wavelength range of the leaf samples and leaf nutrients were analyzed for the development of spectral indices and multivariate model development. The normalized difference and ratio spectral indices and multivariate models–partial least square regression (PLSR), principal component regression, and support vector regression (SVR) were ineffective in predicting any of the leaf nutrients. An approach of using PLSR-combined machine learning models was found to be the best to predict most of the nutrients. Based on the independent validation performance and summed ranks, the best performing models were cubist (R2 ≥ 0.91, the ratio of performance to deviation (RPD) ≥ 3.3, and the ratio of performance to interquartile distance (RPIQ) ≥ 3.71) for nitrogen, phosphorus, potassium, and zinc, SVR (R2 ≥ 0.88, RPD ≥ 2.73, RPIQ ≥ 3.31) for calcium, iron, copper, boron, and elastic net (R2 ≥ 0.95, RPD ≥ 4.47, RPIQ ≥ 6.11) for magnesium and sulfur. The results of the study revealed the potential of using hyperspectral remote sensing data for non-destructive estimation of mango leaf macro- and micro-nutrients. The developed approach is suggested to be employed within operational retrieval workflows for precision management of mango orchard nutrients.

A field experiment was conducted during rabi season 2018-19 to study the response of 23 cowpea genotypes grown under residual moisture condition in rice-fallow situation of Goa state. Analysis of variance revealed significant differences among the genotypes for all the eleven characters, justifying the selection of genotypes for the study. The estimate of Phenotypic Coefficient of Variation (PCV) and Genotypic Coefficient of Variation (GCV) were high (>20%) for seed yield, straw yield, pods per plant and 100 seed weight. Heritability and genetic advance as per cent mean estimates were high for most of the characters except for days to 50 per cent flowering, days to maturity and plant height. Characters plant height, pods per plant, straw yield and harvest index showed positive and significant association with seed yield. Path analysis based on seed yield, as a dependent variable, revealed that straw yield and harvest index had the highest positive direct effect on seed yield. Therefore, maximum importance should be given to these traits during the selection for achieving the higher seed yield under rice-fallow situation. Three promising genotypes identified from this study viz., PCP-1131, SKAU-C- 407 and RC 101 would serve as dual-purpose cowpea under rice-fallow areas due to their high seed yield and straw yield