The population of the world is predicted to reach nine billion by 2050, implying that agricultural output must continue to rise. To deal with population expansion, agricultural chores must be mechanized and automated. Over the last decade, ground robots have been developed for a variety of agricultural applications, with autonomous and safe navigation being one of the most difficult hurdles in this development. When a mobile platform moves autonomously, it must perform a variety of tasks, including localization, route planning, motion control, and mapping, which is a critical stage in autonomous operations. This research examines several agricultural applications as well as the path planning approach used. The purpose of this study is to investigate the current literature on path/trajectory planning aspects of ground robots in agriculture using a systematic literature review technique, to contribute to the goal of contributing new information in the field. Coverage route planning appears to be less advanced in agriculture than point-to-point path routing, according to the finding, which is due to the fact that covering activities are usually required for agricultural applications, but precision agriculture necessitates point-to-point navigation. In the recent era, precision agriculture is getting more attention. The conclusion presented here demonstrates that both field coverage and point-to-point navigation have been applied successfully in path planning for agricultural robots.

This study investigates the socioeconomic and environmental determinants of flood vulnerability in Indian states using a panel data approach. Drawing on state-level flood damage data from 1953 to 2020, sourced from the Ministry of Jal Shakti and affiliated agencies, this study employs a robust econometric framework to identify the key drivers of flood-related damage. The dataset included 16 variables, and rigorous preprocessing steps, such as data cleaning, interpolation, stationarity testing, and multicollinearity checks, to ensure model reliability. Endogeneity was tested using IV regression, and the absence of such issues allowed for the application of Fixed Effects (FE) and Random Effects (RE) models. The Hausman test favored the RE model, which was further validated through diagnostic and robustness tests. The findings reveal that capital expenditure, government spending on natural calamities, and mangrove coverage significantly reduce flood damage, highlighting the importance of both fiscal and ecological interventions. Conversely, population affected, damage to houses, and damage to public utilities were positively associated with flood damage, indicating the need for targeted infrastructure and community resilience strategies. This study offers actionable insights for policymakers, emphasizing the integration of environmental conservation with strategic public investment to enhance flood resilience in India.

Introduction: The inefficient use of inputs in paddy production leads to either over-exploitation or under-exploitation of natural resources, thereby minimizing productivity and sustainability. This study investigates Resource Use Efficiency (RUE) in paddy production across South Indian states.Methods: The study uses secondary data extracted from the Directorate of Economics and Statistics, Department of Agriculture and Farmers’ Welfare, Ministry of Agriculture and Farmers Welfare, Government of India for the period 2022-23 for the South Indian states – Andhra Pradesh, Karnataka, Kerala, Tamil Nadu and Telangana. The research employed Cobb–Douglas production function analysis and RUE estimation to compare the RUE among the study states using the variables like paddy yield, labor (human, animal and machine), fertilizer usage, irrigation and seed application.Results and Discussion: The key findings revealed significant regional disparities in paddy productivity and input efficiency. Telangana has emerged as the most productive state with efficient input–output relationships, whereas Kerala lagged in productivity despite its high input usage. The analysis identifies widespread underutilization of critical inputs, including fertilizers, seeds, and irrigation, across most states, in contrast to the excessive use of labor resources. State-specific interventions for enhancing paddy productivity include optimizing labor and seed rate efficiency in Kerala, fertilizer use efficiency in Tamil Nadu, and capital use (mechanization) efficiency in Andhra Pradesh. The quantitative analysis results reveal the inefficient use of inputs and overuse of labor resources across the states.Policy Suggestions: The implementation of targeted, region-specific, and state-specific strategies, including investments in irrigation infrastructure, promotion of balanced application of fertilizers, adoption of good quality and high-yielding varieties of seeds, and increase in technology adoption, will optimize the input use and enhance the paddy productivity in South India.

This study investigates the gender wage disparities in Indian agriculture utilizing a pseudo-panel dataset and an interaction-based panel regression framework. The study seeks to examine the association of gender on agricultural wages over the years, especially in response to the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), which was enacted in 2005. The study examines whether MGNREGA, which mandates equal wages for male and female workers in public works, is associated with differential gender wage dynamics in the agriculture by shifting wage expectations and enhancing women’s bargaining power. The analysis uses a random effects model with a clustered panel-level standard errors to overcome the problem of serial correlation and heteroscedasticity in the datasets. The findings indicate persistent gender-based wage disparities across various agricultural activities, where male labourers are consistently paid higher wages than their female counterparts. At the same time, the implementation of MGNREGA revealed a significantly positive change observed on rural agricultural wages, with consistent post-policy wage gains reported across most of the farm activities. However, the interaction-based panel regression estimates do not consistently show statistically significant differential gender wage trends during the post-MGNREGA period, suggesting that while overall wages increased, gender disparities remained largely unchanged. Based on these findings, the study discusses policy implications associated with the task-specific nature of gender wage disparities in Indian agriculture. While not directly estimated, the persistence of gender wage gaps highlights the importance of strengthening wage transparency and monitoring mechanisms in informal labour markets, as well as promoting skill development initiatives to enhance women’s participation in higher-paying agricultural activities.