Direct and indirect effect between characteristics of the farmers and their utility perception towards integrated farming system

Introduction

In India, marginal and small farmers face several issues such as low yield, poor income, limited technology use and resource inefficiency. Integrated Farming System (IFS) provides a holistic solution by integrating crops with poultry, fisheries, livestock, fruits, vegetables, floriculture and beekeeping. This diversification improves land use, boosts income and reduces the risk of crop failure. IFS promotes the recycling of farm resources such as manure, reduces input costs and enhances soil fertility and water conservation. Endorsed by the Ministry of Agriculture and Farmers' Welfare, IFS contributes to environmental sustainability and offers a practical model for addressing the gaps left by the Doubling Farmers' Income initiative (Anonymous, 2017) [1] .

Objective

To study the direct and indirect effect between characteristics of the farmers and their utility perception towards Integrated Farming System

Methodology

The study followed a Positivist research philosophy, emphasizing objectivity and quantifiable measurement of direct and indirect effect between characteristics of the farmers and their utility perception towards Integrated Farming System (IFS). A deductive research approach was adopted to test them through empirical data. The Quantitative methodological choice was employed using a Survey research strategy to collect data from farmers across selected talukas. The study was cross-sectional, conducted in Anand district of Gujarat during 2025. Anand district (22.3299 ° N, 72.6151 ° E) was purposively selected as it represents a progressive agricultural region where Integrated Farming System models are actively promoted by Anand Agricultural University. From four talukas viz., Anand, Anklav, Borsad and Khambhat with 120 farmers practicing IFS were chosen using simple random sampling. An Ex-post-facto (Kerlinger, 1976) [2] research design was used since the variables had already occurred. Primary data were collected through a structured interview schedule and analysed using Microsoft Excel (MS 365) and SPSS (version 16.0). Path coefficient technique is the rate of the standard deviation of the effect due to a given cause of the total standard deviation of the effect. Path effects were obtained by solving simultaneous equations set up for the purpose using the correlation matrix. Considering XI as independent variable to be influencing the dependent variable Y the entrepreneurial competence.

Path analysis

Path co-efficient technique is an extension of the technique of standard partial regression co-efficient. Path effects were obtained by solving the simultaneous equations set up for the purpose using the correlation matrix considering one variable 1 to be influencing other variable '1' the simultaneous equation would be: www.extensionjournal.com Where, r yxi = Correlation coefficient between X i with Y P yxi = Direct effect of X i variableon to Y variable r xixj 𝑥 p yxi = Indirect effect of independent variable on dependent variable via. another independent variable.

Results and Discussion

Path analysis was performed on each of the fifteen variables. According to the statistics, there was only a partial absolute and partial relative link between the variables. A partial relationship was the result of multiple variables working together to exert their influence. Table 1 displays the outcome of the path analysis and therefore, it is essential to investigate how one variable affects another, both directly and indirectly other factors that are present in the scenario. [3] , Madhuprasad et al. (2024) [4] and Singh et al. (2025) [5] .

Total indirect effect

So far, total indirect effect is concerned; 14 variables had positive total indirect effect except Size of family. Further, it can be observed that annual income (0.448) had maximum total indirect effect through extension participation (0.043) and education (0.041), land holding (0.296) through attitude towards IFS (0.062) and economic motivation (0.047) followed by agri mass media exposure (0.284) through credit orientation (0.052) and extension participation (0.045), credit orientation (0.257) through management orientation (0.054) and agri mass media exposure (0.047), management orientation (0.

Conclusion

The correlation matrix for fifteen variables was used to solve simultaneous equations created specifically for the purpose of obtaining path effects. The extension participation had exerted a maximum direct positive effect on utility perception of the farmers towards integrated Farming System (0.365), while negative direct effect on age (-0.074) in the study. It can be said that extension participation exerted the highest direct effect and extension participation itself also had exerted the highest substantial effect and annual income exerted the maximum total indirect effect on utility perception of the farmers towards Integrated Farming System.

Acknowledgement

AcknowledgementI extend my heartfelt appreciation to those individuals and institutions whose assistance and direction have been important in the accomplishment of this research work.

References

1. Anonymous. National Institution for Transforming India. Ministry of Agriculture and Farmers' Welfare, Government of India. New Delhi; 2017.
2. Kerlinger FN. Foundation of behavioural research. New Delhi: Sur Pub; 1976. p. 129.
3. Patel PC, Patel JK, Macwan JD. Direct and indirect effect between antecedent characteristics of inland fish farmers and their entrepreneurial competence. Guj J Ext Edu. 2023;36(1):65-67.
4. Madhuprasad VL, Ravindra U, Harshitha D. Livelihood security of scheduled caste farmers through integrated farming system. Guj J Ext Edu. 2024;31(1):170-177.
5. Singh S, Riar ST, Walia SS. Present status of integrated farming system in Patiala. Guj J Ext Edu. 2025;39(1):115-122.