Exploring DNA quantity and quality from raw materials to botanical extracts

Objectives: The aim of this study was to explore the variability in DNA quality and quantity along a gradient of industrial processing of botanical ingredients from raw materials to extracts. Methods: A data matrix was assembled for 1242 botanical ingredient samples along a gradient of industrial processing commonly used in the Natural Health Product (NHP) industry. Multivariate statistics was used to explore dependant variables for quality and quantity. The success of attaining a positive DNA test result along a gradient of industrial processing was compared among four biotechnologies: DNA barcoding, NGS, Sanger sequencing and qPCR. Results: There was considerable variance in DNA quality and quantity among the samples, which could be interpreted along a gradient from raw materials with greater quantities (50–120 ng/μL) of DNA and longer DNA (400-500bp) sequences to extracts, which were characterized by lower quantities (0.1–10.0 ng/μL) and short fragments (50-150bp). Conclusions: Targeted molecular diagnostic tests for species identity can be used in the NHP industry for raw and processed samples. Non-targeted tests or the use of NGS for any identity test needs considerable research and development and must be validated before it can be used in commercial operations as these methods are subject to considerable risk of false negative and positive results. Proper use of these tools can be used to ensure ingredient authenticity, and to avert adulteration, and contamination with plants that are a health concern. Lastly these tools can be used to prevent the exploitation of rare herbal species and the harvesting of native biodiversity for commercial purposes

Assessing the Impacts of Landscape Change and Habitat Degradation on Mammal Diversity and Distribution in the Northern Eastern Ghats, Andhra Pradesh, Using Ecological, Geographic and Social Information

Landscape structure in forest landscapes strongly determines ecosystems functioning, ecological processes and species persistance. Anthropogenic activities are leading to landscape modification, causing habitat degradation and disruption of ecological processes, resulting in biodiversity loss. Mammals in particular have experienced major declines in their populations and ranges globally and across India, largely owing to human induced landscape changes and habitat degradation. As forest landscapes continue to shrink globally, the impacts of habitat loss and degradation on mammals outside protected areas, and the importance of protected areas in sustaining mammals at a landscape level needs to be examined in finer detail to facilitate their conservation

Assessing the transferability of machine learning algorithms using cloud computing and earth observation datasets for agricultural land use/cover mapping

Mapping of agricultural land use/cover was initiated since the past several decades for land use planning, change detection analysis, crop yield monitoring etc. using earth observation datasets and traditional parametric classifiers. Recently, machine learning, cloud computing, Google Earth Engine (GEE) and open source earth observation datasets widely used for fast, cost-efficient and precise agricultural land use/cover mapping and change detection analysis. Main objective of this study was to assess the transferability of the machine learning algorithms for land use/cover mapping using cloud computing and open source earth observation datasets. In this study, the Landsat TM (L5, L8) of 2018, 2009 and 1998 were selected and median reflectance of spectral bands in Kharif and Rabi season were used for the classification. In addition, three important machine learning algorithms such as Support Vector Machine with Radial Basis Function (SVM-RBF), Random forest (RF) and Classification and Regression Tree (CART) were selected to evaluate the performance in transferability for agricultural land use classification using GEE. Seven land use/cover classes such as built-up, cropland, fallow land, vegetation etc. were selected based on literature review and local land use classification scheme. In this classification, several strategies were employed such as feature extraction, feature selection, parameter tuning, sensitivity analysis on size of training samples, transferability analysis to assess the performance of the selected machine learning algorithms for land use/cover classification. The result shows that SVM-RBF outperforms the RF and CART for both spatial and temporal transferability analysis. This result is very helpful for agriculture and remote sensing scientist to suggest promising guideline to land use planner and policy-makers for efficient land use mapping, change detection analysis, land use planning and natural resource management

Evaluation of the performance of SAR and SAR-optical fused dataset for crop discrimination

Crop discrimination and acreage play a vital role in interpreting the cropping pattern, statistics of the produce and market value of each product. Sultan Battery is an area where a large amount of irrigated and rainfed paddy crops are grown along with Rubber, Arecanut and Coconut. In addition, the northern region of Sultan Battery is covered with evergreen and deciduous forest. In this study, the main objective is to evaluate the performance of optical and Synthetic Aperture Radar (SAR)-optical hybrid fusion imageries for crop discrimination in Sultan Bathery Taluk of Wayanad district in Kerala. Seven land use classes such as paddy, rubber, coconut, deciduous forest, evergreen forest, water bodies and others land use (e.g., built-up, barren etc.) were selected based on literature review and local land use classification policy. Both Sentinel-2A (optical) and sentinel-1A (SAR) satellite imageries of 2017 for Kharif season were used for classification using three machine learning classifiers such as Support Vector Machine (SVM), Random Forest (RF) and Classification and Regression Trees (CART). Further, the performance of these techniques was also compared in order to select the best classifier. In addition, spectral indices and textural matrices (NDVI, GLCM) were extracted from the image and best features were selected using the sequential feature selection approach. Thus, 10-fold cross-validation was employed for parameter tuning of such classifiers to select best hyperparameters to improve the classification accuracy. Finally, best features, best hyperparameters were used for final classification and accuracy assessment. The results show that SVM outperforms the RF and CART and similarly, Optical+SAR datasets outperforms the optical and SAR satellite imageries. This study is very supportive for the earth observation scientists to support promising guideline to the agricultural scientist, policy-makers and local government for sustainable agriculture practice

Mainstreaming human and large carnivore coexistence through institutional collaboration

Achieving coexistence between large carnivores and humans in human-dominated landscapes (HDLs) is a key challenge for societies globally. This challenge cannot be adequately met with the current sectoral approaches to HDL governance and an academic community largely dominated by disciplinary sectors. Academia (universities and other research institutions and organizations) should take a more active role in embracing societal challenges around conservation of large carnivores in HDLs by facilitating crosssectoral cooperation to mainstream coexistence of humans and large carnivores. Drawing on lessons from populated regions of Europe, Asia, and South America with substantial densities of large carnivores, we suggest academia should better embrace the principles and methods of sustainability sciences and create institutional spaces for the implementation of transdisciplinary curricula and projects; reflect on research approaches (i.e., disciplinary, interdisciplinary, or transdisciplinary) they apply and how their outcomes could aid leveraging institutional transformations for mainstreaming; and engage with various institutions and stakeholder groups to create novel institutional structures that can respond to multiple challenges of HDL management and human–large carnivore coexistence. Success in mainstreaming this coexistence in HDL will rest on the ability to think and act cooperatively. Such a conservation achievement, if realized, stands to have far-reaching benefits for people and biodiversity

Role of endophytes in early seedling growth of plants: a test using systemic fungicide seed treatment

Systemic fungicide seed treatments are routinely used in conventional agriculture to control soil and seedborne diseases, but little is known about their unintended adverse effects on non-target beneficial fungal endophytes that are known to be involved in plant growth and development. This study evaluated the seed treatment effect of a broad spectrum systemic fungicide, carbendazim (bavistin) on symbiotic association of fungal endophytes in rice and on early seedling growth of rice, green gram, soybean, and cowpea. Seeds were surface sterilized with sodium hypochlorite followed by 0.2% bavistin treatment. Growth of fungal endophytes was significantly affected by the seed treatment with fungicide in rice seedlings, while shoot and root growth was suppressed in all the crops. Quantitative real time PCR showed that the level of expression of two basal transcriptional regulator genes, OsBTF3 and OsNFYC1 that are required for seed germination and seedling growth significantly decreased in bavistin treated rice seedlings. Re-inoculation of consortia of fungal endophytes onto bavistin treated rice seedlings significantly recovered seedling growth and development. These results suggest that fungicide treatment of seeds affects early seedling growth and has negative impact on beneficial fungal endophytes that are involved in plant growth and development. This study provides information on possible ill effects of fungicide on beneficial fungal endophytes that play key roles in early seedling growth of plants and also open up the prospect to additional research on different crops in vitro and field conditions to determine the consequences of fungicide effects and optimise fungicide application strategies to develop sustainable disease control methods

Adapting or Chasing Water? Crop Choice and Farmers' Responses to Water Stress in Peri‐Urban Bangalore, India

Unregulated groundwater extraction has led to declining groundwater tables and increasing water scarcity in the Indian subcontinent. Understanding how farmers respond to this scarcity is important from multiple perspectives—equity in access, livelihood security and resource sustainability. We present a case from the rapidly urbanizing Arkavathy sub-basin near Bangalore city in southern India where irrigation is fully groundwater dependent. Using cross-sectional data from a stratified random sample of 333 farmers from 15 villages, we investigated the factors that determine their choice of crops under conditions of water scarcity and urbanization. Binary logit analysis showed that farmers with a large landholding respond by tapping deep groundwater using borewells. Multinomial logit analysis revealed that access to groundwater, variation in the proximity to the product market (city) and labour availability influence crop choice decisions. We observe that current responses indicate what has been characterized in the literature as chasing strategies. These largely favour well-off farmers and hence are inequitable. While the choice of water-intensive crops and unregulated pumping have aggravated water stress, the uptake of watersaving technologies among irrigated farmers has been low, showing that resource sustainability may not be a concern where non-farm diversification opportunities exist

Invasion compounds an ecosystem-wide loss to afforestation in the tropical grasslands of the Shola Sky Islands

Tropical montane habitats, including the Shola Sky Islands in the Western Ghats, host several threatened taxa of which, the global distributions are restricted to these mountain-tops. The rapidly increasing human footprint and the spread of invasive alien plants have already resulted in the local extinction of several taxa. Here we examine the entire Shola Sky Islands ecosystem to estimate the extent of habitat loss and to create a baseline of land use in this rapidly changing landscape. We used LANDSAT imageries from 1973, 1995 and 2017, with 840 ground truth points across the ecosystem. We find substantial landscape modification in the large high elevation plateaus (7–60%) over the last four decades while changes are muted in the other parts. The loss of grasslands to exotic trees predominates (340 km2, 23%) the modification of this landscape, and, continues today at a rapid pace. Contrary to popular belief, Shola Forests have been relatively stable, implying that most plantations were established on grasslands—traditionally classified as “unproductive wastelands”. Across the Protected Area (PA) network, Reserve Forests (RF), the least protected areas have faced the greatest loss of grasslands. Older PAs have lost relatively fewer grasslands, but the invasion from adjoining RFs is now increasing. We highlight the complexity of conservation in this landscape with three case studies of PAs with different management histories. Our study highlights the rapid loss of native Shola Grasslands, the continuing loss to invasive exotic trees, and the challenges of conserving this critical habitat with traditional modes of conservation

Knowledge, attitudes and practices (KAP) towards rabies and free-roaming dogs (FRD) in Shirsuphal village in western India: A community based cross-sectional study

The lack of awareness about dog-bite related rabies in the rural population of developing countries, including India, is a major impediment to controlling the incidence of disease in humans. A survey of 127 rural residents was undertaken in Shirsuphal village in western India using a structured questionnaire to assess the influence of demographic and pet/livestock owning characteristics on the knowledge, attitudes and practices of the respondents towards rabies and free roaming dogs (FRD). Multivariable logistic regression models were constructed and the knowledge of the rural residents of Shirsuphal village was found to be significantly influenced by family size (OR 2.1, 95%CI 1.0–4.6, p = 0.04) and poultry ownership (OR 2.3, 95%CI 1.1–4.9, p = 0.03), while their attitudes towards FRD was significantly influenced by age of the respondents (OR 2.6, 95% CI 1.2–5.8) and ownership of cattle/ buffalo (OR 2.2, 95% CI 1.1–5.5). Although the knowledge score about rabies was high, a comprehensive understanding of the disease was lacking. Concerted efforts to widen the knowledge about rabies and promote healthier practices towards FRD are recommended

Contesting renewable energy in the global south: A case-study of local opposition to a wind power project in the Western Ghats of India

Influenced by global concerns around climate change mitigation, reduction in carbon emissions and energy security, countries are increasingly focussing on increasing the share of renewable energy. Various national and provincial level authorities are aggressively promoting renewable energy expansion, resulting in new geographies of renewable energy. The expansion of renewable energy, particularly large-scale projects, is contingent upon access to natural resources. However, areas that have high natural resource endowment for renewable energy, often have other overlapping uses of natural resources, including livelihoods and biodiversity. And renewable energy projects located in these areas compete with these other multiple uses of natural resources, often leading to unintended consequences. This study employs ethnographic methods to analyse the case of local opposition to a 113 MW wind power project, located in the Western Ghats of India. India, an emerging economy, is the fourth largest producer of wind energy worldwide and is expanding the share of renewable energy through national as well as provincial level policies. The Western Ghats are a designated UNESCO world heritage site for their exceptional biodiversity and the wind power project conflicted with natural resource-based livelihoods of indigenous populations and threatened their subsistence agricultural practices along with posing a threat to the ecology of the landscape. As a result, local activists protested against the wind power project and this contestation was animated and influenced by a variety of public, civic and private actors and institutions across scale. This paper uses insights from political ecology and energy geography to shed light on the interaction between these multiple actors and how this interaction mediated the contestations around renewable energy. It focuses on the micropolitics of this contestation to highlight the social and political processes that underpin the transition to sustainable energy. It sheds light on local struggles and contestations around renewable energy projects in conjunction with national and global commitments and shows how contestations around renewable energy in the Global South are distinct from the largely prevalent NIMBY approaches in the developed countries. This study contributes to global debates around governing renewable energy, particularly in developing countries