Exploring the lives of women in agriculture: Socio-economic and income dynamics in Ahilyanagar, Maharashtra

Introduction

As noted by M.S. Swaminathan, women were the first to domesticate plants, laying the foundation of farming as we know it today. Globally, women account for about 38% of all agricultural production workers as of 2019 (FAO 2023) [3] , with participation reaching 66% in Sub-Saharan Africa and 71% in Southern Asia (FAO 2023) [3] . In India, nearly 42% of the total agricultural workforce are women (PLFS 2022-23) and the share of rural female labor force participation has impressively increased from 24.6% in 2017-18 to 47.6% in 2023-24 (Economic Survey 2023-24). Maharashtra, a leading agrarian state, contributes around 15% of India's female main workers. Despite their substantial contributions, women's work remains largely informal, low-paid, and subject to various socio-economic constraints. Women in rural India shoulder a triad of responsibilities: agricultural, allied, and domestic work. They perform critical functions from sowing to harvesting, manage livestock, and undertake significant household tasks. However, their labor often remains unrecognized and undervalued, especially concerning wage differentials, job security, and access to resources (Kavitha 2020) [6] . The participation of rural women in agricultural activities forms the backbone of agrarian economies, particularly in developing countries like India. Rural women are indispensable contributors to agriculture, not only as laborers but also as caretakers of biodiversity and custodians of traditional farming knowledge (Patel and Dwaraka, 2025) [10] .

Objectives

1. To study the socio-economic background of women workers in agriculture 2. To examine the sources of income and wage structure of farm women workers

Research Methodology

The present study adopts an exploratory research approach to examine the evolving roles, contributions, constraints, and opportunities of women agricultural workers within a changing socio-economic landscape, with a focus on factors influencing their economic status. A total of 120 women agricultural workers were selected as the sample size. Systematic random sampling was employed, wherein four villages Khanapur, Gardani, Rede, and Kumbhefal were randomly chosen from among 191 villages in Akole Tehsil, Ahilyanagar District, Maharashtra. From each village, 30 women workers were systematically selected to ensure unbiased and representative data. Primary data were collected through a structured questionnaire comprising both open-and close-ended questions covering aspects such as socio-economic background, wage structure, occupation, and income sources. Data were collected through face-toface interviews, ensuring accuracy and comprehensiveness of responses, particularly among women with lower literacy levels. www.extensionjournal.com

Data analysis

To examine the relationship between socio-economic factors and the income level of women agricultural workers, multiple linear regression analysis was employed. In this model, total income was taken as the dependent variable, while age, caste, family type, education, marital status, number of family members, nature of farm employment, decision-making and control over income, and income from agriculture were treated as independent variables.

Multiple linear regression model

Results and Discussion

Results aim to offer a clear understanding of the real-life conditions, experiences, and economic roles of women agricultural workers. The data has been systematically

organized and discussed to reflect the various aspects of their socio-economic background, income patterns, work participation.

Socio-Economic Background of Women Agricultural Workers

This section presents the socio-economic profile of women agricultural workers from the selected villages of Akole Tehsil in Ahilyanagar district, where agriculture is the primary occupation. The analysis includes key variables such as age, caste, education, family type, marital status, family size, nature of farm employment, decision-making role, income from agricultural wages, and total family income. The R² value of 0.74 indicates that 74% of the variation in total income is explained by the selected independent variables, demonstrating a strong fit of the regression model. Among the independent variables, four factors are found statistically significant at the 1% level Family Type, Marital Status, Number of Family Members, Income from Agricultural Wages. Additionally, Nature of Employment is significant at the 5% level. Family Type shows a highly significant and positive influence on income. This suggests that being in nuclear allows women to contribute to income, possibly due to fewer earners. Income from Agricultural Wages positively affects total income and is significant at the 1% level. This is expected, as wage earnings are a direct component of family income and reflect the active economic contribution of women workers. Nature of Employment, significant at the 5% level, suggests that women with more stable, possibly permanent or regular seasonal work, tend to earn more than those in irregular. www.extensionjournal.com Highest involvement of farm woman workers was observed in Tomato and Onion crop as in these crops operations like staking, transplanting, weeding, harvesting needs to be carried out. These operations demands laborious work. Transplanting, harvesting, weeding, and carrying harvested products are the principal operations performed by women.

Sources of Income and Wage Structure

No participation was reported in pesticide application, likely due to health and social barriers. Highest participation of woman workers noticed in harvesting operation (19.25%) as cropping pattern of studied area includes tomato and onion as major crops. Farm women workers showed high participation in labor intensive operations according to collected data.

Conclusion

The participation of women in agricultural activities is closely linked to their socio-economic background. Factors such as family type, number of family members, marital status, nature of farm employment, and women's income from wages were found to have a significant influence on the total family income, as shown through multiple regression analysis. Farm women are primarily involved in physically demanding tasks such as harvesting, transplanting, weeding, staking, and loading/unloading of produce. Among these, harvesting emerged as the most commonly performed activity. During non-cropping or fallow seasons, livestock management becomes the predominant occupation for women, offering relatively higher returns compared to other off-season work. Wage payments are generally made on a weekly basis, but inconsistencies and disparities persist across different types of agricultural operations. These findings underscore the need for more equitable wage structures and support mechanisms to enhance the livelihoods of women agricultural workers.

Suggestions

To improve the socio-economic status and working conditions of farm women, key interventions include enforcing minimum wage laws with regular audits to ensure fair pay, and forming SHGs or unions for collective bargaining. Promoting fair trade practices among cooperatives and buyers can create a transparent market. Appointing women as supervisors enhances leadership and representation. Basic facilities like toilets, resting sheds, and drinking water at farms are essential for their well-being.

Training in integrated farming systems (crop, dairy, poultry, horticulture) offers diversified income. Childcare centers near farms can support working mothers, improving their participation and livelihoods.

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