Indian State Of Karnataka Research Articles

Adoption of Crop Insurance by Smallholder Farmers: Farm-Level Evidence from India

The paper aims to analyse the extent and determinants of smallholder farmers’ adoption of crop insurance. The study conducted a primary survey and collected data from farmers in a drought-prone area of Karnataka state in India using a structured questionnaire. The study has applied a binary logistic regression model to identify the determinants of crop insurance adoption. Empirical results reveal that though most farmers experienced crop loss, only a small percentage subscribed to crop insurance regularly. Lack of money to pay premiums and lack of information are the most common reasons for not subscribing to crop insurance schemes. Further, farmers feel the premium is expensive and do not receive the promised compensation due to the stringent eligibility rules. Most farmers who received compensation think the money is inadequate to cover the cultivation cost. Farmers feel each farm should be treated as a unit against the area-based insurance concept, and more crops should be brought under insurance. They also highlighted the need to further subsidise the premium. Results of the logistic regression confirm that socially marginalised groups and farmers practising agriculture as an ancestral profession are less likely to insure their crops.

Impact of technical service centres as perceived by the sericulture beneficiary farmers in Karnataka state of India

Impact of technical service centres as perceived by the sericulture beneficiary farmers in Karnataka state of India

Effectiveness of a training program in improving knowledge and skills about selected common neurological disorders among primary healthcare doctors: The Karnataka Brain Health Initiative (KaBHI) in India.

Neurological disorders are the leading causes of death and disability globally. In low-middle-income countries such as India, there is a wide treatment gap for neurological disorders. To address this gap, an initiative known as the Karnataka Brain Health Initiative (KaBHI) was developed in collaboration with the public health system of the state of Karnataka in India. A structured hybrid training program was conducted for 120 medical doctors working in the Primary Health Centers (PHCs) in the public health system in three districts of Karnataka. Pre- and post-training evaluation was conducted to assess physicians' knowledge and skills for evaluating patients with common neurological conditions. Of 120 PHC doctors, 111 (92%) scored below the passing score of 50 points out of 100 before the training program. After the training, all trainees scored above this cut-off. The study found a significant improvement in knowledge and skills after the training (before training: 40.48 ± 7.92, after training: 66.28 ± 8.98 (P < 0.001) mean difference = 25.81), and was comparable among the PHC doctors in all three districts. Our study shows the feasibility of training primary care doctors in the public health system to manage selected common neurological disorders. The training program can potentially help to reduce the treatment gap for neurological disorders in India.

Description of a New Species of Anagyrini (Hymenoptera: Encyrtidae), with Some Records from India

One new species of Anagyrini (Encyrtidae: Tetracneminae) Gyranusoidea vasantharaji Zeya, Ashraf and Yadav, sp. nov., is described from the specimens reared from the insect host Planococcus lilacinus (Hemiptera: Sternorrhyncha) infesting Ficus carica plantations in the Indian State of Karnataka. An identification key to Gyranusoidea Compere is also given. Five species viz., are newly recorded from the Indian states noted in parentheses: Anagyrus diversicornis(Howard) (Karnataka), Caenohomalopoda tahai Fatima and Zeya (Uttar Pradesh), Cheiloneurus nankingensis Li and Xu (Uttarakhand, Uttar Pradesh, Karnataka), Sakencyrtus mirus Hayat (Uttarakhand) and S. albiclavus Hayat (Uttarakhand).

A thirty-year time series analyses identifies coherence between oscillations in Anthrax outbreaks and El Niño in Karnataka, India

Anthrax is an economically important zoonotic disease affecting both livestock and humans. The disease is caused by a spore forming bacterium, Bacillus anthracis, and is considered endemic to the state of Karnataka, India. It is critical to quantify the role of climatic factors in determining the temporal pattern of anthrax outbreaks, so that reliable forecasting models can be developed. These models will aid in establishing public health surveillance and guide strategic vaccination programs, which will reduce the economic loss to farmers, and prevent the spill-over of anthrax from livestock to humans. In this study, correlation and coherence between time series of anthrax outbreaks in livestock (1987–2016) and meteorological variables and Sea Surface Temperature anomalies (SST) were identified using a combination of cross-correlation analyses, spectral analyses (wavelets and empirical mode decomposition) and further quantified using a Bayesian time series regression model accounting for temporal autocorrelation. Monthly numbers of anthrax outbreaks were positively associated with a lagged effect of rainfall and wet day frequency. Long-term periodicity in anthrax outbreaks (approximately 6–8 years) was coherent with the periodicity in SST anomalies and outbreak numbers increased with decrease in SST anomalies. These findings will be useful in planning long-term anthrax prevention and control strategies in Karnataka state of India.

Lung cancer in females from nonsmoker families in India: Observations and inferences in 5 years.

e20610 Background: Incidence in lung cancer in last two decades has been changing drastically in terms of gender, age, smoking behaviour of patients, stage at presentation, histopathology, genetic abnormalities, operability at presentation and survival. More perplexing is the increase in its occurrence in females from non smoker families, mitigating the sole importance of the traditional risk factors of tobacco and smoking in the recent times. This highlights the need to investigate other risk factors like radon exposure from indoor pollution where females stay most of the time, exposure to arsenic and other chemicals in daily life, particle pollution, physical inactivity and inflammatory diseases of airways. Methods: It was an observational study of patients who were diagnosed and treated at a high volume cancer centre in Karnataka state of India. 89 never smoker female patients under 50 years of age from non smoker families with no obvious exposure to second hand or third hand smoke were enrolled from October, 2018 to June, 2023. It was a longitudinal prospective cohort study where the demographic data, symptoms with duration, histopathology including genetic abnormalities, treatment details and survival were noted. Results: 89 never smoker females from non smoker families with ages ranging from 36 to 50 years had a median age of 46 years. About 70% of the ladies were from houses closely associated with farm in past or present. 55% of them had overweight and obese body habitus. Most common presenting symptom was dry cough with median duration of about 3 months in about 89%. Other symptoms were pleuritic chest pain(39%), breathlessness (19%), generalized body ache(9%) and jaundice(2%). Stage of disease was IV(69%), IIIC(12.3%), IIIB(11.2%), IIIA(5.6%) and II in just one patient. Most common sites of metastasis were contralateral lung(45%), bone(20%), liver(20%), adrenal glands(10%) and brain (15%). Most common histopathology was adenocarcinoma(87.6%), adenosquamous carcinoma(7.8%), squamous cell carcinoma(3.3%), large cell neuroendocrine carcinoma in just one patient. EGFR was mutated in 56(62.9%) with deletion 19( 33%) and L858R(21%) being the most common abnormalities. ALK rearrangements and ROS1 fusion were seen in about 9(3.3%) and 3(3.3%) patients respectively. Surgery was done in only 3 patients and chemoradiation after neoadjuvant chemotherapy was given in 8(8.9%) patients. Median overall survival was about 42 months in stage IV patients. Conclusions: Changing demographic profile of lung cancer warrants more research into the other causes of lung cancer. More stage IV disease highlights the emphasis on prevention and screening for the disease.

Effect of Input Subsidy Reduction on Greenhouse Emission Reduction Potential in Paddy Production Systems in Karnataka State of India

Increasing concerns and call for reduction in Greenhouse gas (GHG) emission have necessitated the search for broader and all-inclusive policy initiatives, extending into agricultural production, where high carbon energy inputs are used. One classical policy strategy for GHG emission reduction, has been taxation. However, given the critical role of agriculture, especially in developing economies, policies that directly or indirectly increase agricultural inputs costs and reduce their demand require stronger theoretical, conceptual and empirical support to ensure that while agri-environmental quality is promoted, welfare of farming households, food security and overall economic growth are not compromised. Using paddy production in Karnataka state in India, the study assessed effects of agricultural input taxation (reduction in rice input subsidy) on future demand for such inputs and their effect on GHG emission reduction, vis-a-viz production and welfare losses. In microeconomic modelling framework, we applied quadratic almost ideal demand system and stochastic efficiency functions in the analysis of the data. Data for the study, a micro-level farm data, was obtained from Cost of Cultivation Scheme (CSS) for irrigated and non-irrigated production systems, covering the period 2009 -2018 production seasons. Specifically, the study used three future tax regime scenarios- 10%, 20% and 30% input subsidy reduction rates, to model an optimum greenhouse emission reduction potential. The results revealed that inputs evaluated were normal with inelastic demand functions; many input coefficients implied significant complementary relationships; irrigated paddy production system had higher estimates of GHG emissions. Input taxation (reduction in subsidy) under all the three scenarios effectively, resulted in declined inputs consumption patterns, and subsequently led to significant decrease in greenhouse emissions. The highest GHG emission reduction potential was observed in irrigated farming system. Greenhouse emission reduction potential was optimal at moderate subsidy reduction policy rate of 10%. It is recommended that, given the inelastic estimates derived, moderate tax (reduction in subsidy) policy option on inputs would yield effective greenhouse mitigation with appropriate compensation through effective integrative schemes.

Assessing the utility of Munsell soil color in building and evaluating spectral models for soil clay content prediction

AbstractThe present study examined how the use of soil color can help build and evaluate clay content prediction models from laboratory visible and near infrared spectroscopic data. This study was based on a regional database containing 449 soil samples collected over Karnataka state in India, which has been divided into red soils (240 samples) and black soils (209 samples) based on their Munsell soil color. Partial least squares regression models were calibrated and validated from both the regional datasets and subsets stratified as red and black soils. In addition, a random forest model was used to classify the validation soil samples into black and red classes to evaluate models’ performance. First, while the clay content predicted by the regression model built from regional data was evaluated as correct at regional scale (R2val of 0.75), this model was evaluated as more accurate over black (R2val of 0.8) than red (R2val of 0.63) soil samples. Second, the regression models built from subsets stratified per soil color provided different performances than the regression model built from the regional data, both at the regional scale and soil color scale. In conclusion, this study demonstrated that (1) predictions are highly dependent on calibration data, (2) the interpretation of prediction performances relies heavily on validation data, and (3) pedological knowledge, such as soil color, can be effectively employed as an encouraging covariate in both the construction and evaluation of regression models.

CHALLENGES OF RURAL SMALL AND MARGINAL FARMERS IN DEVELOPING COUNTRIES: A CASE STUDY OF RURAL SMALL AND MARGINAL FARMERS IN KARNATAKA.

This paper explores the multifaceted challenges faced by rural small and marginal farmers in developing countries, specifically focusing on the state of Karnataka in India. Using a Mixed method study approach, a Questionnaire and focused group discussion were used to collect data from 120, small and medium farmers, the study delves into the access market, awareness of Agriculture schemes and Agricultural credit, and challenges faced by S&amp; M.F. in I.C.T. adoption in Karnataka. Through a combination of qualitative interviews, surveys, and secondary data analysis, the paper identifies key challenges, including Quality Seeds Availability, Proper Irrigation system, Agriculture Labor Problems, Power problems, Lack of Mechanization, Lack of Information on Pesticides and Crop Diseases, Lack of Support from Local Government, Credit facilities. Climate changes (Natural Hazards), Transportation, Market Linkage, and Storage Facilities The findings underscore the urgent need for tailored policies and interventions to address the unique circumstances of rural small and marginal farmers, enhance their resilience, and promote sustainable agricultural development in the region.

Leveraging Digital Technology to Improve Monitoring and Planning in Public Sector Supply Chains: Evidence From India’s Food Security Program

Governments across the developing world are adopting digital technologies to improve the performance of public sector supply chains. However, empirical evidence regarding the impact of these technologies on performance is mixed. In this paper, we evaluate the impact of using biometric authentication (BA) devices on the performance of India’s food security program. The program aims to deliver subsidized food grains to nearly 160 million low-income households through approximately 500,000 fair price shops (FPSs). Nearly half of those grains do not reach the beneficiaries and are diverted to the open market for private benefit. We estimate the impact of installing BA devices on reducing diversion in more than 3,300 FPSs in the Indian state of Karnataka between 2013 and 2015 using a difference-in-differences approach. We find that BA devices reduce up to 4% of the current diversion at the last mile. We argue that this relatively low impact is due to the presence of a workaround mechanism which results in imperfect monitoring and validate the decrease in diversion mechanism by estimating the differential impact of BA devices. We complement the empirical analysis with a simulation exercise to estimate the additional value that can be unlocked by using the BA devices. We find that the value of better replenishment planning using sales and inventory information captured by BA devices can be significant. The value of better planning can be as high as six times the value of reduction in diversion, depending on the preintervention levels of demand from genuine beneficiaries and diversion at the FPSs.

IJCM_235A: Extent and pattern of telemedicine usage and perceptions about telemedicine among health care practitioners across the state of Karnataka, A cross sectional study

Background: Telemedicine is a developing technology in the Indian healthcare sector. The success of any new technology depends on factors such as knowledge, perception, and willingness of users and professionals to engage it. Hence this study will be conducted to assess the perceptions and usage of telemedicine by healthcare professionals in Karnataka state of India. Objectives: a. To ascertain the extent of telemedicine usage by healthcare professionals in different parts of the state of Karnataka. b. To determine the different models of telemedicine used by healthcare professionals. c. To compare the utilization pattern of telemedicine across various demographic, academic, career and healthcare setting-related parameters of healthcare providers. Methodology: Methods: This study will be conducted using a cross-sectional survey design. The survey will be conducted among healthcare professionals in Karnataka, including doctors, nurses, and other healthcare professionals. Results: In the present study overall usage f telemedicine was 30%. The utilization pattern of telemedicine various widely across various demographic, academic, career and healthcare setting-related parameters of healthcare providers. Different models of telemedicine were used by healthcare professionals in different parts of Karnataka. The utilization pattern of telemedicine is more in urban areas of state. Covid 19 pandemic has a great effect on usage of telemedicine by healthcare professionals. Conclusion: In the present study overall usage f telemedicine was 30%. The utilization pattern of telemedicine various widely across various demographic, academic, career and healthcare setting-related parameters of healthcare providers. Different models of telemedicine were used by healthcare professionals in different parts of Karnataka.

IDENTIFYING BARRIERS TO WALKABILITY WITHIN THE HERITAGE CITY OF MYSORE, KARNATAKA, INDIA

Historically, streets have served a range of functions, primarily those associated with shopping and social interactions. However, in the 20th century, the street design became centred on traffic movement. It enhanced the space for automobiles, while public lives were marginalized to sidewalks, not to forget the problems faced by the street hawkers, quintessential to the Street scene in India. The historic core of Mysore, a metropolitan city in the Southern state of Karnataka in India, has had various attempts to enhance its mobility but has not had much success. The paper summarises a pilot study carried out on Asoka Road in the city of Mysore to investigate its walkability. A descriptive quantitative technique was adopted, in which a random sample of respondents who happened to walk down Asoka Street were given questionnaires and surveys to complete to collect data. The results revealed that the level of comfort of the street amounted to 51.8% and that the pedestrian path was quite uncomfortable.

Brand loyalty in FinTech services: The role of self-concept, customer engagement behavior and self-brand connection

The concurrent effects of customer predispositions, customer engagement behaviour (CEB) and self-brand connections (SBC) on loyalty are less understood. This article will examine how relationship quality and consumer predispositions (self-concept, brand communal focus) affect loyalty, with customer engagement behaviour and self-brand connection acting as mediating factors. A cross-sectional survey with a quantitative study design was used to gather information from 380 users of FinTech apps in the Indian state of Karnataka. The main findings indicate that self-concept does not generate loyalty by itself but rather fosters loyalty through the mediation of SBC and CEBs. Similarly, a trusted and satisfied customer remains brand loyal. A sense of communal focus among consumers results in self-brand connections only if they are positively engaged with the brand. Customer interactions and engagement in social media can have a significant impact on the development of digital self-brand relationships. Contrary to the literature, we found that positive engagement fosters loyalty only if it leads to brand connection. Repeat patronage and willingness to buy new products or price insensitivity depend on strong emotional brand connections and CEBs. Hence, FinTech companies should match their experiences, offerings, and brand messages to the way that consumers view themselves. To engage customers in new ways and establish a connection with them, they should also offer stimulating and compelling virtual experiences on their platforms. Therefore, FinTech consumers can maintain brand loyalty through self-brand connections and brand engagement through self-concepts.

The role of corporate environmental ethics in shaping environmental management accounting adoption under the institutional theory

This study aims to investigate the complex association between institutional pressure, adoption of environmental management accounting (EMA), and financial performance, with corporate environmental ethics as a moderating component. It explains why and how firms adopt EMA in response to institutional demand to factor environmental factors into their strategic decision-making processes. Quantitative information is gathered using a structured questionnaire from 256 manufacturing companies’ environmental managers and executives who monitor environmental practices and policies and decision-makers who shape business environmental ethics and strategy in the Indian state of Karnataka. Data are analyzed using SmartPLS 4, and PLS-SEM tests the hypotheses. The results show that coercive pressure (β = 0.244, p = 0.000), mimetic pressure (β = 0.221, p = 0.000), and normative pressure (β = 0.209, p = 0.000) have a major role in determining the rate of EMA adoption. It is further identified that EMA adoption (β = 0.217, p = 0.000) positively influences the organization's financial performance. Furthermore, EMA adoption mediates the relationship between coercive pressure (β = 0.053, p = 0.000), normative pressure (β = 0.045, p = 0.000), mimetic pressure (β = 0.048, p = 0.000), and firm’s financial performance. Coercive pressure is associated with higher EMA adoption, although the impact of this link is moderated by corporate environmental ethics (β = 0.069, p = 0.000).

Change Point Detection of Temperature in Karnataka State in India During the Period 1979-2019

This paper deals with study of exposure of Karnataka state to climate change for a period 1979-2019. The Mann Whitney Pettit’s homogeneity test (MWP) was analysed for 240 data sets for monthly data of minimum (MTmin) and maximum temperature (MT max) across ten agro climatic zones) to estimate the year of structural break or year of shift in mean monthly temperature from one level to next higher level during the forty years of study period i.e., 1979-2019. About 77 data sets were identified to show year of structural break The annual mean temperature recorded anupward shift in all the agro climatic zones of Karnataka except in hilly zone. The break year was chosen based on its frequent occurrence in data sets of minimum and maximum temperature. It is observed to be 1998 for North Eastern Transition Zone and is 1997, 1994, 1996, 1995, 1996, 1999, 1999, 1999 and 1997 for North Eastern Dry Zone, Northern Dry Zone, Central Dry Zone, Eastern Dry Zone, Southern Dry Zone, Southern Transition Zone, Northern Transition Zone, Hilly Zone and Coastal Zone respectively. Therefore, it is a evidential picture reflecting the increase in temperatures across the zones. Researchers should develop crop varieties that are insensitive to temperature changes and should develop packages of practices which will mitigate adverse effect of fluctuations in climate parameters on crop productivity.

First report of quinone outside inhibitor (QoI) resistance in Plasmopara viticola (grape downy mildew) in Karnataka state in India

First report of quinone outside inhibitor (QoI) resistance in Plasmopara viticola (grape downy mildew) in Karnataka state in India

Improved Biomass Stoves in Rural Areas in Karnataka, India

Aims: the study aimed to quantify fuel wood consumption in traditional and biomass stoves as well asto estimate the Carbon dioxide (Co2) and carbon monoxide (Co) while cooking with different fuel wood.&#x0D; Study Design: exploratory and experimental.&#x0D; Place and Duration of Study: The duration of the Study was 2 years and the place of the study was Dharwad and Vijayapur districts of Karnataka state India.&#x0D; Methodology: Keeping this in view a study was conducted in two villages namely Timmapur Village of Dharwad district and Bhaganager Village of Vijayapur district Karanarak State India. From each village 60 households were selected randomly thus total sample size comprises 120 rural women.&#x0D; Results: About 80 per cent of the women were illiterate in Timmapur and 76.70 per cent of the women were illiterate in Bhaganagar. The quantity of ash, charcoal and smoke after food preparation was significantly varied in both villages. A reduction in the percentage of both carbon dioxide and carbon monoxide was found in biomass stoves compared to traditional stoves. The experimental research revealed that 58 per cent of the fuel wood was saved per year per 100 families when compared to traditional stoves. Whereas the traditional stove consumes 1200 kg /month/100 families.&#x0D; Conclusion: Improved biomass stoves should be promoted to encourage rural women to better use the stove.

Knowledge Assessment of Beneficiary Farmers of Technical Service Centres (TSCs) about Recommended Technologies of Sericulture in Karnataka State of India

Sericulture in Karnataka is in the process of modernization in many phases through new demand driven extension approach called Technical Service Centres (TSCs) located at the grass-root level (Hobli and Taluka level). These centres are mainly involved in the dissemination of the technologies developed by the Research Institutes and also in supply of mulberry cuttings/saplings, monitoring mulberry cultivation, silkworm rearing and providing information about loan facilities and subsidy schemes. There is a need to study the attitude of sericulture beneficiary farmers towards activities of TSCs. The study was conducted during 2018-20 in the Karnataka state which contribute 35 per cent of silk production in India. An ex-post facto research design was used or the study. Knowledge test was constructed to measure the knowledge of sericulture farmers on recommended sericulture technologies. The Ramanagara and Mandya districts were selected because these district have highest number of TSCs in Bangalore and Mysore division respectively. Mandya, Malavalli and K.R Pet taluks from Mandya district as well as Ramanagara, Channapatna and Kanakapura taluks from Ramanagara district were selected for the study with four TSCs from each taluk. Totally, 24 TSCs were selected for the study. Ten sericulture farmers under each TSC, collectively 240, were selected by using random sampling method. The study highlighted that more than half (52.50%) and more than one third (36.25%) of the sericulture farmers had medium and high knowledge on recommended technologies of sericulture respectively. Only just more than one tenth (11.25%) of the sericulture farmers had low knowledge on recommended technologies of sericulture. The probable reason might be due to fact that sericulture farmers were regularly consulting from officials of grainage centres, TSC extension functionaries, input dealers and peer group about the information on latest sericulture technologies.

Unmet Needs and Barriers to Assistive Technology in the Coastal Districts of Karnataka, India.

Assistive Technologies (AT), such as hearing aids, walking aids, prostheses, spectacles, can improve the quality of life and enable many to lead dignified lives. The rapid Assistive Technology Assessment (rATA) tool developed by World Health Organization (WHO) can measure the needs of AT and the barriers to accessing them. This study aimed to measure the unmet needs and the usage of AT via the rATA tool in the coastal state of Karnataka in India. A population-based survey was conducted among a total of 500 households - 250 from Mangalore and 250 from Udupi of Coastal Karnataka. The need for AT was assessed under six domains of activities, including mobility, seeing, hearing, communication, remembering, and self-care. The mean age of study participants was 34.3 years with standard deviation of 21.2 years. 30.6% of the study participants reported the use of assistive products out of which 27.3% used one product and 2% used two products. 89.5% of assistive products were procured from private sector and only 4.1% was obtained from public sector. The level of difficulty in doing any activity increased with age. 301 participants reported out of pocket expenditure for assistive products with mean expenditure of Rs 2226.05 (S. D. 2204) per year. Spectacles, orthoses (spinal) and therapeutic footwear were most common assistive products with unmet need. Our findings highlight the urgent need to mainstream geriatric care policies which address functional difficulties among older people, resolve out-of-pocket spending through public private partnership for assistive technologies.

Drought Prediction with Feature Enhanced LSTM Model using Metaheuristic Optimization Algorithms

The impact of drought builds on all three fronts of economy, environment, and society is devastating. Predicting its arrival and duration is highly important to arrange any sort of mitigation plans. The association of detailed relationship between multiple variables makes drought prediction a highly complex task. Especially influence of global warming, polar sea extent variations and their influence on overall ocean temperature have altered the seasonal rainfall behaviors all over the world. In the midst of it, predictions centered on the history of rainfall levels become inaccurate. The proposed system is an optimized deep learning prediction model integrating indigenous knowledge (IK) is proposed to predict the drought. IK expressed in human language is translated using fuzzy function and fed to an improved Long Short Term Memory (LSTM) model. The LSTM model hyperparameters are optimized using a hybrid of Particle Swarm Optimization (PSO) with firefly to produce the meta-heuristics algorithm which will provide the best performance in presence of integration of IK features into modern meteorological features which solves the problem of local minima in LSTM hyperparameter optimization. The performance of the proposed results were tested compared with the meteorological information gathered by the Karnataka Natural Disaster Monitoring Centre (KNDMC) for the district named Chitradurga of the Karnataka state in India. The proposed system which is Indigenous Knowledge merged along the cross model attention network can produce at least 1.4% higher Nash–Sutcliffe model efficiency coefficient (NSE) and 30% lower Mean Absolute Error (MAE) in the prediction of Standard Precipitation Index (SPI) compared to Convolution Neural Networks (CNN) and LSTM based time series prediction models.