Spaces of Yoga – Towards a Non-Essentialist Understanding of Yoga

This chapter will examine some of the spaces that yoga occupies in the contemporary world, both physical and social. By looking at yoga through the focus of particular, contested spaces and locations, it will be argued that overarching essentialist definitions of yoga are impossible, although individuals and social groups can and do create essentialist definitions that are more or less useful for particular purposes. By exploring these narratives and boundaries in the context of specific locations, we can better understand what people are doing with the collection of beliefs and practices known as yoga

Assessing the feasibility of integrating ecosystem-based with engineered water resource governance and management for water security in semi-arid landscapes: A case study in the Banas catchment, Rajasthan, India

Much of the developing world and areas of the developed world suffer water vulnerability. Engineering solutions enable technically efficient extraction and diversion of water towards areas of demand but, without rebalancing resource regeneration, can generate multiple adverse ecological and human consequences. The Banas River, Rajasthan (India), has been extensively developed for water diversion, particularly from the Bisalpur Dam from which water is appropriated by powerful urban constituencies dispossessing local people. Coincidentally, abandonment of traditional management, including groundwater recharge practices, is leading to increasingly receding and contaminated groundwater. This creates linked vulnerabilities for rural communities, irrigation schemes, urban users, dependent ecosystems and the multiple ecosystem services that they provide, compounded by climate change and population growth. This paper addresses vulnerabilities created by fragmented policy measures between rural development, urban and irrigation water supply and downstream consequences for people and wildlife. Perpetuating narrowly technocentric approaches to resource exploitation is likely only to compound emerging problems. Alternatively, restoration or innovation of groundwater recharge practices, particularly in the upper catchment, can represent a proven, ecosystem-based approach to resource regeneration with linked beneficial socio-ecological benefits. Hybridising an ecosystem-based approach with engineered methods can simultaneously increase the security of rural livelihoods, piped urban and irrigation supplies, and the vitality of river ecosystems and their services to beneficiaries. A renewed policy focus on local-scale water recharge practices balancing water extraction technologies is consistent with emerging Rajasthani policies, particularly Jal Swavlamban Abhiyan (‘water self-reliance mission’). Policy reform emphasising recharge can contribute to water security and yield socio-economic outcomes through a systemic understanding of how the water system functions, and by connecting goals and budgets across multiple, currently fragmented policy areas. The underpinning principles of this necessary paradigm shift are proven and have wider geographic relevance, though context-specific research is required to underpin robust policy and practical implementation

Genomic-based-breeding tools for tropical maize improvement

Maize has traditionally been the main staple diet in the Southern Asia and Sub-Saharan Africa and widely grown by millions of resource poor small scale farmers. Approximately, 35.4 million hectares are sown to tropical maize, constituting around 59% of the developing worlds. Tropical maize encounters tremendous challenges besides poor agro-climatic situations with average yields recorded <3 tones/hectare that is far less than the average of developed countries. On the contrary to poor yields, the demand for maize as food, feed, and fuel is continuously increasing in these regions. Heterosis breeding introduced in early 90 s improved maize yields significantly, but genetic gains is still a mirage, particularly for crop growing under marginal environments. Application of molecular markers has accelerated the pace of maize breeding to some extent. The availability of array of sequencing and genotyping technologies offers unrivalled service to improve precision in maize-breeding programs through modern approaches such as genomic selection, genome-wide association studies, bulk segregant analysis-based sequencing approaches, etc. Superior alleles underlying complex traits can easily be identified and introgressed efficiently using these sequence-based approaches. Integration of genomic tools and techniques with advanced genetic resources such as nested association mapping and backcross nested association mapping could certainly address the genetic issues in maize improvement programs in developing countries. Huge diversity in tropical maize and its inherent capacity for doubled haploid technology offers advantage to apply the next generation genomic tools for accelerating production in marginal environments of tropical and subtropical world. Precision in phenotyping is the key for success of any molecular-breeding approach. This article reviews genomic technologies and their application to improve agronomic traits in tropical maize breeding has been reviewed in detail

Genomic Prediction with Genotype by Environment Interaction Analysis for Kernel Zinc Concentration in Tropical Maize Germplasm

Zinc (Zn) deficiency is a major risk factor for human health, affecting about 30% of the world’s population. To study the potential of genomic selection (GS) for maize with increased Zn concentration, an association panel and two doubled haploid (DH) populations were evaluated in three environments. Three genomic prediction models, M (M1: Environment + Line, M2: Environment + Line + Genomic, and M3: Environment + Line + Genomic + Genomic x Environment) incorporating main effects (lines and genomic) and the interaction between genomic and environment (G x E) were assessed to estimate the prediction ability (rMP) for each model. Two distinct cross-validation (CV) schemes simulating two genomic prediction breeding scenarios were used. CV1 predicts the performance of newly developed lines, whereas CV2 predicts the performance of lines tested in sparse multi-location trials. Predictions for Zn in CV1 ranged from -0.01 to 0.56 for DH1, 0.04 to 0.50 for DH2 and -0.001 to 0.47 for the association panel. For CV2, rMP values ranged from 0.67 to 0.71 for DH1, 0.40 to 0.56 for DH2 and 0.64 to 0.72 for the association panel. The genomic prediction model which included G x E had the highest average rMP for both CV1 (0.39 and 0.44) and CV2 (0.71 and 0.51) for the association panel and DH2 population, respectively. These results suggest that GS has potential to accelerate breeding for enhanced kernel Zn concentration by facilitating selection of superior genotypes