The migration patterns of farmers, rural women, and youth within agricultural households have a significant impact on rural communities and the agricultural sector. To gain a deeper understanding of research trends in migration behavior, a study was conducted using comprehensive bibliometric analysis and text mining. René Descartes’ Discourse framework was employed to analyze 504 research articles retrieved from the Dimension.ai database followed by further analysis with Microsoft Excel, R software and VOS viewer. The study revealed a growing interest of various stakeholders in this field, with an increasing number of publications focusing on various aspects from 1934 to 2023. In terms of the publication’s performance analysis, the study identified human society and the second Sustainable Development Goal (SDG) as the most significant research areas. These areas aim to address hunger and improve food security for migrants. Regarding migration studies, three influential journals—Sustainability, World Development, and Journal of Rural Studies—were identified, with the most influential author being J. Vernon Henderson from the United Kingdom. Citation analysis was conducted to determine the highest number of citations for the influential author (J. V. Hernderon), journal (World Development), organization (World Bank), and country (United States) based on scientific attribution. Additionally, a co-word analysis was performed to research article’s abstracts to map into key thematic clusters that include climate change, food insecurity, and the COVID-19 crisis. The study visualized the social network of authors, organizations, and countries involved in co-authorship analysis within the research field. Furthermore, a journal co-citation analysis was undertaken to reveal the intellectual structure of migration studies in the agricultural context. Text mining of the research documents uncovered both anticipated and unanticipated effects of migration on households. Consequently, these findings provide valuable insights into future research directions and evidence-based policy framing which will contribute to shielding agricultural households from unforeseen consequences of migration, benefiting researchers, policymakers, and practitioners in this arena.

In spite of the detrimental effects of climate change and decreasing resource efficiency, maize farming is essential to the world’s food and nutritional security. With regard to sustainable maize farming in this environment, conservation agriculture (CA) offers a framework that holds promise in terms of low soil disturbance, perennial soil cover, and sustainable crop rotation. In order to acquire more profound information on the research advancements and publication patterns related to maize under CA scenarios, a bibliometric analysis was conducted. This involved utilizing René Descartes’s Discourse Framework to extract and screen 2587 documents spanning the years 2001 to 2023 from the Dimensions.ai database. The mapping showed that different stakeholders were becoming more interested in maize research under various CA pathways, with a greater emphasis on reaching the second sustainable development target, or “zero hunger”. The most influential journals were “Soil and Tillage Research” and “Field Crops Research”, with 131 and 85 papers with 6861 and 6186 citations, respectively. The performance analysis found “Christian L. Thierfelder” and “Mangi Lal Jat” as the eminent researchers in the areas of maize research under CA. Thus, the International Maize and Wheat Improvement Center (CIMMYT) and the Indian Agricultural Research Institute (IARI) were identified as the important institutions in conducting research pertaining to maize under CA systems, while the United States, India, and Mexico emerged as prominent countries with notable collaboration efforts for imparting research under the given scenarios. Three thematic clusters delineating keywords from three distinct sections—key drivers, objectives, and methodology—were identified through co-word analysis using word clouds, tree maps, and thematic networking of the keywords from the abstract and titles of screened publications. These thematic clusters highlighted the growing emphasis on region-specific studies under CA, particularly in sub-Saharan Africa and the Indo-Gangetic plain, to enhance the resilience of the agri-food system. Therefore, mapping maize’s potentialities within the CA framework has revealed the field’s dynamic nature and offers insightful information to researchers and policymakers that could help them plan future studies and cooperative initiatives aimed at boosting the productivity and sustainability of maize-based systems under the CA framework.

Migration in agriculture is influenced by an intricate interplay of socio-economic as well as ecological factors and has emerged as a predominant marvel. India has a diverse array of agro-ecological regions, each presenting numerous opportunities for farmers to significantly improve their livelihoods. The Indo-Gangetic Plains (IGP) and the Western Dry Region were the focal points of this study, as Uttar Pradesh and Rajasthan were intentionally chosen for an in-depth investigation into both the constraints and innovative agricultural initiatives. In structuring the sampling approach, a stratified multistage sampling methodology was employed, encompassing 480 migrant and 480 non-migrant farmers. Constraints were analyzed using the Garrett ranking method, while text mining was employed to explore innovative agricultural practices among migrants. The findings unveiled a range of challenges faced by migrants at their usual places of residence (UPR), including limited employment opportunities, untimely availability of farm inputs, inadequate support from service providers, and soil salinization. Upon migration, destination-related challenges included irregular wages/salaries, lack of affordable housing options, absence of insurance schemes, and instances of discrimination against local communities. The study further illuminated the income-generating activities in Rajasthan, primarily revolving around livestock management, leafy vegetable production, and oilseed cultivation. In Uttar Pradesh, the focus was on vegetable production, livestock management, and seed cultivation. These lucrative and innovative ventures were custom-tailored to the agro-ecological contexts of the migrants, providing a glimpse into the transformative potential of amalgamating tradition with innovation. Such insights offer valuable guidance to policymakers in empowering migrant populations in agriculture.

Digital Agro-Advisory Platforms (DAAPs) are emerging as vital tools to address gaps in agricultural extension services, particularly in developing economies like India. Kisan Sarathi, implemented by the Indian Council of Agricultural Research (ICAR), represents a pioneering initiative to deliver real-time, multilingual, and location-specific advisories to farmers. Despite its rapid expansion, limited empirical research has examined the behavioural factors driving farmers’ sustained use of such platforms. This study extends the Technology Acceptance Model (TAM) by integrating self-efficacy and system quality to investigate determinants of farmers’ usage behaviour of Kisan Sarathi across the Indo-Gangetic Plains. Using stratified two-stage sampling, data were collected from 350 registered farmers in Haryana, Uttar Pradesh, and West Bengal. Structural Equation Modelling (SEM) and Random Forest techniques were employed. SEM revealed that perceived usefulness, perceived ease of use, self-efficacy, and system quality significantly influenced farmers’ attitudes, which strongly predicted behavioural intention and subsequent usage behaviour. Random Forest analysis further identified perceived usefulness, attitude, and behavioural intention as the strongest predictors across states, highlighting regional variations in system quality. The findings underscore the importance of user confidence, system performance, and farmer-centric design. The study contributes to the ICT4Ag literature by advancing TAM with psychological and technical dimensions, while offering insights for policymakers, developers, and extension agencies seeking to design inclusive digital advisory systems and reduce the digital divide in agriculture.