Background Mangroves are important tropical carbon sinks, and their role in mitigating climate change is well documented across the globe. However, the ecosystem carbon stocks in the mangroves of India have not been studied comprehensively. Data from this region is very limited for providing sufficient insights and authentic evaluation of carbon stocks on a regional scale. In this study, we evaluated the ecosystem carbon stock and its spatial variation in mangroves of Kerala, southwest coast of India. Results The mean biomass stored in mangrove vegetation of Kerala is 117.11 ± 1.02 t/ha (ABG= 80.22 ± 0.80, BGB =36.89 ± 0.23 t/ha). Six mangrove species were found distributed in the study area. Among the different species, Avicennia marina had the highest biomass (162.18 t/ha) and least biomass was observed in Sonneratia alba (0.61 t/ha). The mean ecosystem carbon stock of mangrove systems in Kerala was estimated to be 139.82 t/ha, equivalent to 513.13 t CO2 e/ha with the vegetation and soil storing 58.56 t C/ha and 81.26 t C/ha respectively. Conclusion The present study reveals that Kerala mangroves store sizable volume of carbon and therefore need to be preserved and managed sustainably, to retain along with the increase in carbon storage. This features the need of broadening mangrove cover as well as restoring deteriorated land in the past 50 years. Although mangrove forests in this region are protected by the Kerala Forest Department, they have been frequently facing illegal encroachment, prawn cultivation, and coastal erosion.

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The evaluation and selection of strategies for sustainable development in manufacturing supply chains are critical tasks for the decision-maker because of the complexity involving various criteria. This paper deals with the prioritization of critical sustainability criteria and the sustainability strategy selection (SSS) using an integrated weighting approach. This approach consists of the analytic hierarchy process (AHP), the subjective and objective weight integrated approach (SOWIA) and the technique for order preference by similarity to an ideal solution (TOPSIS) and is found to be effective for solving this multi-criteria decision-making problem. The proposed methodology is applied to solve a real-time supply chain decision-making issue of an Indian manufacturing industry. From a sustainability perspective, the results indicate the second strategy set as the best among the given alternatives, with an objective factor of 0.5. The robustness of the results has been analysed to identify the uncertainty in the final ranking. The consistency of the final ranking has been evaluated based on different objective factor values. The novelty of this paper pertains to addressing the most relevant SSS problem involved in a manufacturing supply chain and in establishing a hybrid approach for solving it. This approach offers a flexible provision for decision-makers to incorporate the appropriate level of subjectivity and objectivity into their decisions based on their degree of expertise. This study is unique and carries a high originality value, as it offers a new structured and flexible approach to solving the SSS problem.

Artocarpus altilis (Park.) Fosberg is an important fruit vegetable tree grown in the homesteads of southern part of India. To provide reasoned scientific management practices and conservation measures, the pattern of morphological and genetic variation were investigated for six populations using Amplified Fragment Length Polymorphism (AFLP) markers and 15 morphological traits. The use of five selective primer combinations on 60 samples resulted a total of 414 bands in which 85% were polymorphic. The values of Nei's genetic distance varied from 0.0044 (PalaiPalghat) to 0.3376 (Palghat-Mangalore). Analysis of molecular variance revealed most of the variation within populations (57.45%) than (42.55%) among populations. The genetic variation by AFLP data is not reflected in quantitative morphological variables. However, the genetic and geographical distances were positively correlated which were further well supported by the PCO analysis and Dollo-parsimony tree, both show the tendency of the individuals to group according to the geographical localities.

Objective:Arterolane maleate is an antimalarial drug currently under Phase III clinical evaluation, and presents a simple, economical and scalable synthesis, and does not suffer from safety problems. Arterolane maleate is more active than artemisinin; and is cheap to produce. It has a longer lifetime in the plasma, so it stays active longer in the body. To provide quality control over the manufacture of any API, it is essential to develop highly selective analytical methods. In the current article we are reporting the development and validation of a rapid and specific Head space gas chromatographic (HSGC) method for the determination of organic volatile impurities (residual solvents) in Arterolane Maleate bulk drug.Materials and Methods:The method development and its validation were performed on Perkin Elmer's gas chromatographic system equipped with Flame Ionization detector and head space analyzer. The method involved a thermal gradient elution of ten residual solvents present in arterolane maleate salt in RTx-624, 30 m × 0.32 mm, 1.8 μ column using nitrogen gas as a carrier. The flow rate was 0.5 ml/min and flame ionization detector (FID) was used.Results:During method validation, parameters such as precision, linearity, accuracy, limit of quantification and detection and specificity were evaluated, which remained within acceptable limits.Conclusions:The method has been successfully applied for the quantification of the amount of residual solvents present in arterolane maleate bulk drug.The method presents a simple and reliable solution for the routine quantitative analysis of residual solvents in Arterolane maleate bulk drug.

Random amplified polymorphic DNA fingerprinting was performed to assess the genetic diversity among rarely cultivated traditional indica rice (Oryza sativa L.) varieties collected from a tribal hamlet of Kerala State, India. A total of 664 DNA bands amplified by 15 primers exhibited 72.9% polymorphism (an average of 32.3 polymorphic bands per primer). The varieties Jeerakasala and Kalladiyaran exhibited the highest percent (50.19%) polymorphism, while Thondi and Adukkan showed the lowest (9.85%). Adukkan (78 bands) and Jeerakasala (56 bands) yielded the highest and the lowest number of amplicons, respectively. Unweighted Pair Group Method with Arithmetic mean analysis using the Dice similarity coefficient showed the highest value of similarity coefficient between the varieties Adukkan and Thondi, both shared higher level of similarity (0.81), followed by Kanali and Thondi (0.88). Of the three subclusters, the varieties of Adukkan, Thondi, Kanali, Mannuveliyan, Thonnuranthondi, and Chennellu grouped together with a similarity of 0.77. The second group represented by Navara, Gandhakasala, and Jeerakasala with a similarity coefficient of 0.76 formed a cohesive group. The variety Kalladiyaran formed an isolated position that joined the second cluster. The Principal Coordinate Analysis also showed separation of Kalladiyaran from the other varieties.

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