International Journal of Horticulture, 2025, Vol.15, No.6, 299-311 http://hortherbpublisher.com/index.php/ijh 302 The average number of family members was 7, with small producers having 7 members and large producers averaging 8. The overall standard deviation was 2.79, reflecting moderate variability in family size. The mean difference of 0.24 was not significant (p = 0.682), indicating that family size did not differ significantly between the two groups. The overall average dependency ratio was 0.45, with small producers slightly higher at 0.46 and large producers at 0.43. The standard deviation of 0.19 suggested low variability in the dependency ratios among participants. The mean difference of -0.03 was not statistically significant (p=0.450), indicating comparable dependency levels across small and large producers. A notable difference was observed in the amount of irrigated land, with small producers averaging 3.21 ropani and large producers averaging 11.72 ropani, leading to a significant mean difference of 8.51 (p<0.001). The overall standard deviation was 6.63, highlighting substantial variability in land ownership, particularly among large producers, who had a standard deviation of 6.86. The average rainfed land for small producers was 4.26 ropani, while large producers had an average of 8.72 ropani, resulting in a significant mean difference of 4.46 (p<0.001). The overall standard deviation of 6.32 indicated considerable variability in rainfed land holdings, with small producers exhibiting lower variability (3.827) compared to large producers (7.84). Total land area further illustrated significant disparities, with small producers averaging 7.60 ropani and large producers at 20.33 ropani, resulting in a significant mean difference of 12.72 (p < 0.001). The standard deviation of 7.57 indicated considerable diversity in land ownership, with small producers showing lower variability (3.458) than large producers (4.84). The average male employment rate was 3.02, with small producers at 2.94 and large producers at 3.12. The overall standard deviation of 1.64 indicated moderate variability, while the mean difference of 0.18 was not significant (p = 0.600), suggesting comparable employment levels for males in both groups. The average male unemployment rate was 1.28, with small producers experiencing 1.38 and large producers 1.15. The standard deviation of 0.90 suggested low variability in unemployment rates, and the mean difference of -0.23 was not statistically significant (p = 0.230), indicating similar unemployment levels across the two groups. The average female employment rate was 2.17, with small producers at 2.22 and large producers at 2.10. The overall standard deviation of 1.08 reflected moderate variability, and the mean difference of -0.12 was not significant (p = 0.604), showing comparable female employment rates between small and large producers. 3.2 Socio-demographic characteristics of study area (b) The analysis of the socio-demographic variables revealed key insights into gender, ethnicity, religion, education, types of agriculture, annual family income, and major economic activities among participants (Table 2). The overall male representation was 61.11% and female 38.89%, with no significant differences found (chi-square = 0.058, p = 0.809). Ethnic groups showed no significant differences either, with Brahmin/Chettri at 58.89% and Janjati at 41.11% (chi-square = 0.036, p = 0.848). In terms of religion, Hindu participants comprised 58.89% and Buddhists 41.11%, with no significant difference (chi-square = 0.387, p=0.533). The level of education was notably diverse, but primary education showed no significant difference (chi-square = 2.596, p = 0.627). A significant finding emerged in the types of agriculture, where subsistence farming was predominant among small producers (52.00%) compared to only 10.00% among large producers, resulting in a highly significant chi-square value of 23.621 (p <0.001). Regarding annual family income, a significant difference was noted, with the majority of small producers (70.00%) earning less than 2.5 lakh, contrasting with only 15.00% of large producers; this yielded a significant chi-square of 32.304 (p < 0.001). Major economic activities primarily revolved around agriculture (74.44%), but no significant differences were found in mixed activities (chi-square = 5.818, p =0.213).
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