Knowledge Level and Extent of Adoption of Scientific Fish Farming Practices among Members of Fish Farmers Producer Organizations

Fish farming, an ancient occupation, serves as a rapid income booster for small-scale farmers, increasing the socioeconomic status of rural communities (Singh et al., 2024). Fisheries and aquaculture have experienced significant growth in India (Mishra et al., 2017) and are pivotal for food security, providing employment to millions and sustaining livelihoods nationwide (Sahoo et al., 2013; Kumar et al., 2024). Between 2005 and 2020, per capita fish consumption saw a significant increase of 81.43%, indicating growing demand nationwide, including among existing fish consumers (Padiyar et al., 2024). Therefore, it is vital to prioritize this sector to sustainably meet the country’s food requirements. However, there are notable opportunities for innovation, investment and collaboration to overcome these barriers and to promote sustainable aquaculture development. Concerted efforts are required to advocate and integrate fish-farming practices into aquaculture and fisheries (Meena et al., 2024). There is substantial room to increase fish production. Enhancing fish production depends on factors such as farmers adopting recommended scientific practices and interventions, including formal financial institutional linkages, input support from the fishery department and investment in farmer skill development (Ghosh et al., 2022). The future of sustainable aquatic food relies heavily on successful fishery management, which is a significant hurdle for combating diseases. Recently, aquaculture has shifted from traditional, extensive methods to more intensive systems (Budakoti, 2023). Scientific fish culture integrates multiple compatible fish species, such as the Indian major carp (IMC) and exotic carp, into a single water body (Saha, 2011; Goswami, 2016). Initially relying on traditional methods, farmers now acknowledge the necessity of adopting scientific practices for optimal production (Das, 2018). The adoption of these practices among fish farmers is essential for improving productivity, reducing environmental impacts and enhancing their livelihoods of fish farmers. Knowledge is pivotal in shaping individual behaviour in this regard (Sakib et al., 2014). Given these concerns, the multifaceted role of Fish Farmers Producer Organizations (FFPOs) has emerged in nurturing aquaculture and fostering the development of aquapreneurs. By raising awareness and promoting fish farming among impoverished farmers, FFPOs play a crucial role in introducing and popularizing new and improved fish-farming technologies (Singh et al., 2024). FFPOs play a crucial role in facilitating the dissemination and adoption of these practices among members. To enhance the adoption of effective and efficient technologies, it is essential to evaluate the knowledge level of fish farmers (Rathore et al., 2016). Knowledge entails obtaining factual information and comprehending how an innovation functions (Kumar et al., 2018; Mutyaba et al., 2024). Various extension programs have been implemented to raise awareness, educate and inspire farmers, farmwomen and rural youth to embrace and oversee new farming technologies in the field (Singh et al., 2010). Hence, the understanding of and viewpoint regarding new technology can influence a farmer’s stance (Aldosari et al., 2019). Understanding the knowledge level and extent of the adoption of scientific fish farming practices within FFPOs is essential to inform targeted interventions and policy decisions aimed at promoting sustainable aquaculture development. However, only a few studies have been conducted in this regard. Keeping these facts in mind, the main objective of this study was to examine the knowledge level and extent of adoption of scientific fish farming practices among members of FFPOs.  

The research was carried out in the Purba Medinipur District of West Bengal in 2023. Out of fourteen Fish Farmers Producer Organizations (FFPOs) in the district (District Controller, Food and Supply, Purba Medinipur, 2022), four were purposively selected for the study based on specific criteria: operational success of over 3 years, over 400 members and turnover exceeding Rs. 1 crore in the fiscal year 2021-2022, as verified by audit reports. The chosen FFPOs were Tamralipta Fish Producer Company Limited, Global Moyna Farmers Producer Company Limited, Divinius Farmers Producer Company Limited and Patashpur-II Farmers Producer Company Limited. Thirty respondents were selected from each FFPO, totalling 120 respondents, using a simple random sampling technique. Primary data were gathered through pre-tested semi-structured questionnaire schedule. A descriptive research design was employed in the study. Respondents’ knowledge level was measured by a teacher-made knowledge test developed by Nagarajaiah (2002) with few modifications. A score of 1 and 0 was assigned for ‘yes’ and ‘no’ responses, respectively, to each statement. The raw knowledge score of each individual was then converted into a knowledge index and the respondents have been grouped on the basis of mean and standard deviation, viz., low (mean - SD/2), medium (between mean - SD/2 to mean + SD/2) and high (mean + SD/2). 
 

 

 
To assess the extent of adoption regarding scientific fish farming practices, the approach outlined by Nagarajaiah (2002) was employed, with necessary adjustments. Scores of 2, 1 and 0 were assigned for ‘full adoption’, ‘partial adoption’ and ‘non-adoption’ of each recommended practices as proposed by Sinha and Kolte (1974) and the maximum and minimum overall adoption score a respondent could get was 34 and 0. Adoption quotients were calculated from raw adoption scores as suggested by Sengupta (1967) to gauge the overall adoption level followed by Balasubramaniam (1988).
 

After calculating the individual adoption quotient scores, respondents were grouped into three categories, using the mean and standard deviation as measures for verification.
 

Profile of the respondents
 
The study included a diverse group of participants categorized by age, education, family size, farming experience, farming area, annual income, occupation, type of culture, economic motivation, risk and scientific orientation, source of information utilization and the number of training sessions attended, as presented in Table 1. Among the respondents, 19.17% were young (up to 30 years) and 68.33% were middle-aged (30 to 60 years). The predominance of middle-aged farmers suggests a significant level of experience and exposure to fish farming (Rathore et al., 2016; Goswami and Samajdar, 2016; Salam et al., 2020; Anna and Dinesh, 2022). Educational attainment varied, with the 31.66% had the secondary education, followed by 25.83% with middle school education and 24.16% with higher secondary education. Education plays a crucial role to tackle complex problems in farming through improved decision-making and the majority of respondents possessed at least secondary level education (Unnikrishnan and Dinesh, 2020). Regarding family size, 55.83% had small families (fewer than 5 members). A majority (55%) had moderate farming experience (6 to 10 years), followed by 26.67% with long-term experience (above 10 years) and 18.33% with short-term experience (up to 5 years). In terms of farming area, 44.17% had small holdings (2 to 5 acres), 34.16% had marginal holdings (up to 2 acres) and 21.67% had large holdings (more than 5 acres). The majority of respondents (50.83%) had a medium income (Rs. 1 lakh to 3 lakhs) and 31.67% had a high income (more than Rs. 3 lakhs).    

     
 
Aquaculture was the primary occupation for 65.83% of respondents. For the type of culture practiced, 55.83% were involved in polyculture, 32.5% in composite culture and 11.67 % in monoculture. The prevalence of polyculture and composite culture practices indicates a diversified approach to fish farming. Economic motivation varied, with 50.83% having medium motivation and 30.83% high motivation. With medium to high levels of economic motivation noted among the participants, it is evident that the potential for increased profitability from scientific fish farming practices is a compelling incentive for adoption (Swathi Lekshmi et al., 2005; Goswami and Samajdar, 2016). Risk orientation was medium for 55.83% and high for 19.17%. Scientific orientation was medium for 49.17%, low for 30.83% and high for 20%. Respondents with high scientific orientation are likely more proactive in adopting innovative and scientifically proven techniques (Rathore et al., 2016). Regarding the utilization of information sources, 42.5% had medium utilization and 39.16% had high utilization. In terms of training sessions attended, 45.83 % attended 3 to 4 sessions, 31.66% attended up to 2 sessions and 22.5% attended 5 to 6 sessions. The high utilization of information sources (Rathore et al., 2016; Goswami and Samajdar, 2016) and participation in training sessions through FFPO platform suggested an active engagement with learning and knowledge dissemination within the community.

Knowledge level and extent of adoption of recommended scientific fish farming practices among ffpo member fish farmers
 
The distribution of respondents by their knowledge of recommended scientific fish farming practices (Fig 1) showed that 38.33% had a medium level of knowledge followed by 34.17% with a high level and 27.5% with a low level of knowledge. A significant number of respondents exhibited medium to high levels of knowledge, indicating a robust understanding of scientific fish farming within the FFPOs (Sasmal et al., 2006; Saha, 2011; Rajan et al., 2013; Rathore et al., 2016; Goswami and Samajdar, 2016; Yadav et al., 2024). This widespread knowledge is likely facilitated by accessible training programs conducted by FFPO officials for their member, extension services and efficient use of information sources through FFPO platform and peer-to-peer learning within the community. While the prevalence of high and medium knowledge levels suggests effective dissemination of scientific practices, the presence of a smaller segment with low levels of knowledge points to a need for intensified educational support and motivation to reach less informed members. In terms of the adoption of scientific practices (Fig 2), 36.67% of respondents had a medium level of adoption, 32.5% had a high level and 30.83% had a low level of adoption. Regarding adoption of scientific practices of fish farming, a significant number of FFPO members showed medium to high levels of adoption. The finding is line with the result of Talukdar and Sontaki (2005); Pounraj and Rathakrishnan (2011); Goswami et al. (2012); Goswami et al. (2016); Saha et al. (2016); Das et al. (2018). This is influenced by strong support systems from FFPO, successful training programs and visible success stories, which highlight the tangible benefits of adopting scientific methods. However, the existence of a subset of members with low levels of adoption indicates that there are still barriers to embracing these practices fully. So, continuous education, support from FFPO officials and targeted efforts by extension agencies is essential for transitioning these members towards scientific methodologies.




 
Knowledge level predictors
 
 The stepwise linear regression analysis identified several significant independent variables associated with the knowledge level of respondents (Table 2; N = 120). Education (β = 0.217, t = 2.588, p = 0.011), annual income (β = 0.193, t = 2.162, p = 0.033), risk orientation (β = 0.256, t = 3.165, p = 0.002), training attended (β = 0.210, t = 2.606, p = 0.010) and utilization of information sources (β = 0.354, t = 4.595, p = 0.000) showed significant positive standardized coefficients (1% significant level). Higher levels of education and income were positively associated with knowledge levels (Saha, 2011; Rajan et al., 2013; Sakib et al., 2014; Sarma et al., 2016; Rathore et al., 2016), as this might the driver of greater access to materials, training programs and scientific information regarding scientific fish farming. Participation in training sessions was positively correlated with knowledge (Rajan et al., 2013; Rathore et al., 2016), highlighting the importance of continuous learning and skills development in enhancing knowledge levels. The strong positive correlation between source of information utilization (Sasmal et al., 2006; Saha, 2011; Rajan et al., 2013; Sakib et al., 2014; Rathore et al., 2016) and knowledge level underscores the significance of accessing and utilizing various sources of information, such as extension services, research publications and peer networks, in expanding one’s knowledge base. Conversely, age had a negative standardized coefficient (β = -0.251, t = -4.242, p = 0.000). Younger individuals being more receptive to new information (Sasmal et al., 2006; Rajan et al., 2013). These results indicate that higher levels of education, income, risk orientation, participation in training sessions and effective utilization of information sources are associated with increased knowledge levels. The model explained approximately 90.3% of the variation in knowledge level (adjusted R-square = 0.903).


 
Extent of adoption predictors
 
Regarding the extent of adoption of fish farming practices (Table 3). Positive predictors included education (β = 0.187, t = 3.085, p = 0.003), training attended (β = 0.172, t = 1.902, p = 0.060), scientific orientation (β = 0.489, t = 4.861, p = 0.000) and source of information utilization (β = 0.601, t = 9.203, p = 0.000). However, age negatively influenced adoption (β = -0.116, t = -2.551, p = 0.012). Farming experience (β = -0.270, t = -4.321, p = 0.000), risk orientation (β = -0.136, t = -2.023, p = 0.045) and occupation (β = -0.206, t = -4.768, p = 0.000) were also negative predictors. This model explained approximately 95.1% of the variation in the extent of adoption (adjusted R-square = 0.951) (1% significant level). The negative association between farming experience and adoption extent (contrary with the findings of Swathi Lekshmi et al., 2005; Pounraj and Rathakrishnan, 2011; Das et al., 2018; Aswathy and Imelda, 2020) suggests that respondents with less experience in fish farming were more inclined to adopt newer, more scientifically advanced practices. Utilization of information sources, educational status, exposure to training and risk orientation were also strong predictors of extent of adoption highlights the crucial role of access to information regarding scientific fish farming and willingness to take calculated risks in driving the adoption of these practices (Sasmal et al., 2006, Pounraj and Rathakrishnan, 2011; Goswami, 2012; Goswami et al., 2012; Sakib et al., 2014; Aswathy and Imelda, 2020).

The author is thankful to all resource persons as well as all respondents and also expresses gratitude to the West Bengal University of Animal and Fishery Sciences, which provided the necessary resources and support for conducting this research.

Author’s contribution
 
Conceptualization and designing of the research work (A.H.M., S.S.D.); Execution of field/lab experiments and data collection (A.H.M.); Analysis of data and interpretation (A.H.M., S.K.); Preparation of manuscript (A.H.M., M.R.S.).

The authors declare that there are no conflicts of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.