Agriculture is central to the Indian economy and suffers from widespread operational inefficiencies that could be corrected by the use of digital agriculture technologies (DA). We review and synthesise available literature concerning digital agriculture in India and anticipate its transformative potential in the coming decade. Although the initial growth of DA was more conspicuous in the downstream sectors and high-value crops, reaching smallholder farmers upstream is slowly emerging despite significant obstacles such as small fragmented holdings, inadequate data infrastructure and public policy, and unequal access to digital infrastructure. Agri-tech enables innovation at many locations within value chains, and a steady shift is occurring in change from individual farms to the whole value chain. Technology in the sector is progressing from information and communication technology-based solutions to Internet of Things and artificial intelligence–machine learning-enabled services. India’s public policy shows signs of a longstanding investment and collaboration in the sector, with an explicit focus on data infrastructure development. We find smallholder predominance, diversity in production systems, the predominance of commodity crops, proximity to urban markets, and public policy as the major factors of DA’s success in India. A stocktake of the available technologies and their applications by the public sector, tech giants, information technology leaders and agri-food tech startups in India strongly indicates a digital transformation of Indian agriculture. However, given the federal structure of governance and agriculture being a state (province) subject, we need to wait to see how DA policies are rolled out and taken up across the country.

The highly heterogeneous and complex farm holdings operated by the smallholders in developing countries are often deprived of optimum production and profitability. The farming systems in the state of Jharkhand, India, are heterogeneous due to biophysical (e.g., climatic conditions, fertilizer status, elevation, etc.) and socio-economic (investment potential, production goals, income preferences) factors. The extension interventions to reach the smallholders often face the one-size-fits-all approach making farming less attractive with diminished potential. There is a need to understand the diversity of the farms to classify them into different homogenous groups after studying the nature and characteristics of the farm and operators on the farms. In the current study, twenty-one different variables related to socio-economic,biophysical and geospatial features of the farms from 394 farm households were used for the analysis using Principal Component Analysis to identify six principal components explaining 73.07% of the total variability in the dataset. The first six factors were further analyzed using Euclidean Distance as distance measure and Ward’s technique as agglomerative clustering to form four clusters that were found to represent the farm households in the three villages. The four farm types identified were, Type 1. Large farm household with a diversification of crops and intensification of labour (22%), Type 2. Small farm households with major income from livestock (9%), Type 3. Small farm households with diversified cropping system and income from other sources (17%), and Type 4. Small farm households with monocropping dominated by senior farmers with an additional source of income (51%). The validation of the clusters was undertaken through qualitative methods such as focused group discussions and participatory workshops. The findings back up previous research that showed a positive association between farmer categorization and mathematical classification. The study offers a verifiable scientific methodology that could help scale agricultural technologies by forming a specific cluster of farmers based on their characteristics. The technologies applied to various farm types would be helpful to the extension system to target the interventions among the precise members of the identified farm types. Thus, the study suggests the farming system typology based on socio-economic, biophysical and geospatial factors for targeted farming systems interventions among smallholders.

This article is based on reviews of studies in the field of journalism education in India after the proliferation of the Internet, particularly after the year 2010. The journalism practices have undergone a significant change in the past two decades, with the enabling of new information technologies, resulting in increased feedback from the audiences as well as globalized education opportunities for the content creators. The article is based on the content analysis, using grounded theory as the qualitative research method, to identify various themes in journalism researches, from Indian universities during the same period. The implications of the results suggest that there is a wide gap between the research conducted in the educational institutions and the prevailing pattern in the journalism industry in the country.

The spread of misinformation and fake news with the advent of social media is widespread to influence public opinion. A lack of common consensus between the journalists, media houses and social media companies on combating disinformation is causing distrust and scope for pessimism. The current research was conducted in the Indian context adopting mixed methods research to find out the roles and responsibilities of journalists and media houses in combating disinformation along with the effect of social media and advanced technologies in the changing scenario. The results revealed that journalists demanded more access to audience and providing a platform for practicing ethical journalism. Secondly, the effect of social media on journalism was considered as a net positive with no escape from the same in this digital era. Thirdly, an upgrade of skills related to tackling misinformation with technology was felt by the journalists. The paper provides the intricacies of journalism practice in the changing world for a better future..

Agricultural Extension is vital for sustainable farming development and food systems. During the past decades, several agricultural extension modelshave been implemented in India. The present study emphasises on the scientific contribution of agricultural extension researchduring the last decade (2011-2020). Bibliometric techniques have been employed to the secondary data for analysing 145 articles to identify relevant themes, collaboration patterns, topics under study and major journals for publication. It was observed that the research on agricultural extension has been increasing in recent years. The journals that have published the articles have highlighted multi-disciplinary research to address the challenges of the discipline. The central thematic area of research in the domain was new extension methodologies for technology transfer,applying information and communication technologies (ICTs) in farming and climate-change based research in extension. Probably, this might be the first bibliometric study to offer exhaustive information on extension research in India. The findings of the study will aid academics and decision-makers in formulating plans and strategies for better extension approaches for agricultural development. Agricultural extension practitioners may also use those findings for reorienting advisory services at the grassroots level.