This report summarizes recent findings of environmental arsenic (As) contamination and the consequent health effects in a community located near historic gold mining activities in the Mangalur greenstone belt of Karnataka, India. Arsenic contents in water, hair, nail, soil and food were measured by FI-HG-AAS. Elemental analyses of soils were determined by ICP-MS (inductively coupled plasma-mass spectrometry). Of 59 tube-well water samples, 79% had As above 10 μg L−1 (maximum 303 μg L−1). Of 12 topsoil samples, six were found to contain As greater than 2000 mg kg−1 possibly indicating the impact of mine tailings on the area. All hair and nail samples collected from 171 residents contained elevated As. Arsenical skin lesions were observed among 58.6% of a total 181 screened individuals. Histopathological analysis of puncture biopsies of suspected arsenical dermatological symptoms confirmed the diagnosis in 3 out of 4 patients. Based on the time-course of arsenic-like symptoms reported by the community as well as the presence of overt arsenicosis, it is hypothesized that the primary route of exposure in the study area was via contaminated groundwater; however, the identified high As content in residential soil could also be a significant source of As exposure via ingestion. Additional studies are required to determine the extent as well as the relative contribution of geologic and anthropogenic factors in environmental As contamination in the region. This study report is to our knowledge one of the first to describe overt arsenicosis in this region of Karnataka, India as well as more broadly an area with underlying greenstone geology and historic mining activity.

India is the highest producing country in the world and contributes one fourth in total pulse production. The Karnataka state is one of the leading pigeonpea growing states, with Gulbarga district contributing about 56 per cent of the total pigeonpea area of the state. The present study investigates the adoption pattern of improved varieties of pigeonpea. A sample size of farmers each of adopters and non-adopters of improved varieties of pigeonpea were selected randomly from four villages in two blocks of Gulbarga district. The result indicates that more than 45 years age group with higher education background was the adopters of improved varieties. WRP-1variety released by University of agricultural Sciences, Dharwad was the leading improved cultivar's among the sample farmers which has higher net return over ICP-8863 and local varieties. The short duration of the crop, more grain yield and high market price were found to be the main reasons for adoption of the improved varieties. The logit analysis interpret that size of operational holding, education and age of farmers were found significant and positive factors influencing adoption decisions of farmers. It was suggested that greater agricultural research efforts are needed towards varietal improvement in pigeonpea crop in order to improve their yield. Emphasis may be given for improvement in the development of infrastructural facilities for quality and timely availability of inputs including credit facilities.

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Background: Online purchase has a very important role to play in creating consistent demand for farmers’ products and linking them directly to final consumers. Preferences of consumers are the most important driver of online purchases that prosper the linkage between farmers and the final consumers and these preferences are vastly influenced by consumers’ socio-economic characteristics. The current study was conducted to analyse the influence of socio-economic factors on the online purchase of food products in Bangalore city. Methods: Individual cross-sectional data were collected using a pre-tested questionnaire from 105 consumers of randomly selected areas of Bangalore city namely, Sahakarnagar, Judicial Layout, Yelahanka, Canara bank layout, Mahadevapura, Sanjaynagar and Jayanagar. Binary logistic regression was applied as the research method to examine the influence of socio-economic characteristics like gender, age, occupation, education, number of family members with income and income (as predictor variables) towards the online purchase of food products (as dependent variable). Result: Results indicated that age (negatively), number of family members earning income and monthly income (positively) significantly influenced the online purchase of food products. Other variables like education, gender (in favour of men) and occupation also influenced (positively) the outcome variable but, statistically were not significant.

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