Assessment of adoption patterns of recommended maize production technology among Nicra village maize growers in Malda district of West Bengal

Introduction

Agriculture continues to play a pivotal role in the Indian economy by ensuring food security, generating rural employment, and contributing substantially to national income. Among cereal crops, maize (Zea mays L.) has emerged as one of the most important and versatile crops due to its wide adaptability, high productivity potential, and diversified utilization in food, feed, fodder, poultry, starch, and industrial sectors. Over the past few decades, maize International Journal of Agriculture and Food Science https://www.agriculturaljournals.com cultivation in India has expanded considerably as a result of increasing demand from livestock feed industries, food processing sectors, and bio-based industries. Consequently, maize has gained strategic importance in the agricultural production system of the country. India presently ranks among the leading maize-producing countries of the world in terms of cultivated area. However, despite substantial expansion in acreage, the average productivity of maize in several regions remains below potential levels. This productivity gap is primarily attributed to the low adoption of recommended production technologies, dependence on traditional cultivation practices, inadequate access to quality agricultural inputs, poor extension support, and limited awareness regarding scientific crop management practices.

In eastern India, particularly in West Bengal, maize cultivation has shown increasing importance in recent years; nevertheless, farmers still face numerous socio-economic, technological, and institutional constraints that hinder productivity enhancement. Malda district of West Bengal possesses considerable potential for maize cultivation due to its favorable agro-climatic conditions and increasing farmer interest in maize-based farming systems. However, the adoption of improved maize production technologies among farmers remains uneven. Recommended practices such as use of improved or hybrid seed varieties, scientific nutrient management, soil testing, integrated pest management, mechanization, and climate-resilient farming approaches are yet to be adopted widely at the grassroots level. The persistence of traditional farming methods, coupled with inadequate technical knowledge and insufficient institutional support, continues to limit farm productivity and profitability in the region. In this context, Krishi Vigyan Kendra (K.V.K.), Malda has been actively engaged in disseminating improved agricultural technologies and promoting climate-resilient farming practices through frontline demonstrations, farmer training programs, advisory services, and extension interventions under the NICRA (National Innovations on Climate Resilient Agriculture) program. The effectiveness of such interventions largely depends on farmers' awareness, perception, and adoption behavior toward recommended technologies. Therefore, understanding the extent of technology adoption and the factors influencing farmers' decision-making processes is essential for designing effective extension strategies and policy interventions. The present study was undertaken to assess the adoption patterns of recommended maize production technologies among maize growers of NICRA villages in Malda district of West Bengal. The study specifically focuses on examining the socio-economic characteristics of farmers, evaluating their level of awareness and adoption of improved maize cultivation practices, identifying the major constraints affecting technology adoption, and analyzing the role of extension services and information dissemination mechanisms in influencing farmers' adoption behavior. The findings of the study are expected to provide valuable insights for researchers, extension personnel, policymakers, and development agencies in formulating suitable strategies for enhancing maize productivity, improving farmers' livelihoods, and promoting sustainable agricultural development in the region.

Materials and Methods

The present investigation was conducted by Malda Krishi Vigyan Kendra (K.V.K.), Malda under the NICRA (National Innovations on Climate Resilient Agriculture) program using a descriptive and analytical research design.

The study was undertaken to assess the adoption patterns of recommended maize production technologies among maize growers in selected NICRA villages of Malda district, West Bengal. Both survey and fact-finding approaches were employed to collect comprehensive information from the respondents regarding their socio-economic characteristics, technological adoption behavior, and constraints associated with maize cultivation. The study was carried out in Malda district of West Bengal, which is recognized as one of the important maize-growing regions of the state. A multi-stage stratified sampling technique was followed for the selection of respondents. In the first stage, Malda district was purposively selected considering the increasing importance of maize cultivation and the active implementation of NICRA interventions by K.V.K., Malda. In the second stage, two NICRA villages, namely Ramayanpur village under Ratua block and Paschim Narayanpur village under Manikchak block, were selected for the study. These villages were chosen due to their significant involvement in maize cultivation and participation in climate-resilient agricultural activities promoted by K.V.K., Malda. In the final stage, a total of 70 maize-growing farmers were selected purposively from the two selected villages, comprising 35 respondents from Ramayanpur village and 35 respondents from Paschim Narayanpur village. The respondents were selected based on their active involvement in maize cultivation and exposure to recommended maize production technologies. Both primary and secondary data were utilized for the study. Primary data were collected through personal interviews with the help of a structured and pre-tested interview schedule. Secondary information was obtained from reports, journals, official records, and publications related to maize production and agricultural technology adoption. Appropriate statistical tools and techniques such as frequency, percentage, mean, and standard deviation were employed for analysis and interpretation of the collected data. The study primarily focused on analyzing the socio-economic profile of maize growers, their awareness and adoption level of recommended maize production technologies, attitudes toward improved cultivation practices, and the major constraints affecting technology adoption. The investigation also attempted to assess the role of extension services, training programs, and technology dissemination activities conducted by K.V.K., Malda in promoting climate-resilient maize production practices among farmers in the selected NICRA villages. The educational profile revealed that most farmers were graduates or above (32.85%), followed by middle (30%) and secondary education (28.57%), while only 8.57% had primary education. The mean education score was 3.01±1.20, indicating moderate variation and reflecting increasing participation of educated farmers in modern, knowledge-based agriculture. The farming experience distribution showed that 61.43% of farmers had less than 15 years of experience, while 25.71% and 12.86% possessed 15-25 years and above 25 years of experience, respectively. The mean farming experience was 14.17±6.75 years, indicating dominance of relatively new farmers and limited availability of highly experienced farmers. The landholding distribution revealed that 50% of farmers were marginal farmers owning 5-8 bigha, followed by big farmers (34.29%) and small farmers (15.71%). The average landholding was 7.62±3.82 bigha, indicating moderate variation. The findings suggest dominance of medium-sized holdings with comparatively fewer small landholders in the study area. The occupational distribution showed that farming was the primary livelihood for 75.71% of respondents, followed by labour work (14.29%), business (7.14%), and service occupations (2.86%). The mean score was 3.62±0.74, indicating low variation. The findings highlight strong dependence on agriculture with limited occupational diversification among farmers. The table presents farmers' attitudes towards adopting recommended maize production technologies based on their level of agreement with various statements. The responses are categorized as Agree, Undecided, and Disagree. Below is a detailed analysis based on key themes.

Results and Discussion

Awareness and Information Sources

• 50 farmers believe they are well-informed about maize production technologies. • 56 farmers agree that agricultural extension services provide adequate information. • However, 41 farmers are undecided about the influence of fellow farmers, and 36 are unsure about the effectiveness of government initiatives. • 46 farmers agree that mobile apps and digital services are helpful. • While many farmers receive adequate information from agricultural extension services, uncertainty about the role of peer influence and government initiatives suggests a gap in awareness-building efforts.

Adoption of Specific Technologies

• Crop rotation (60 farmers) and mechanized farming (59 farmers) receive the highest agreement. • IPM (49 farmers) and organic farming (50 farmers)** are widely adopted. • Fertilizer application decisions (soil testing) have 43 undecided responses, indicating a lack of awareness or access. • Farmers are more confident about adopting mechanization and crop management practices but show uncertainty in practices like soil testing.

Economic and Access Challenges

• 64 farmers disagree that the cost of improved seeds and fertilizers is a barrier, suggesting affordability may not be the biggest issue. • However, 21 farmers agree that lack of access to quality inputs is a challenge.

• 49 farmers agree that financial support is necessary for adoption. • Market demand (57 farmers) influences adoption decisions. • While cost alone may not be the primary issue, access to quality inputs and financial support remain crucial factors for adoption.

Impact of Technology Adoption

• 56 farmers report an increase in yield.

• 51 farmers agree that improved practices have reduced production costs. • However, 26 farmers disagree that technology adoption has improved their income. • Yield improvements are recognized, but the financial benefits are not equally felt by all, possibly due to market fluctuations or high input costs. • 45 farmers are satisfied with government support.

• 58 farmers would recommend improved technologies to others. • Overall satisfaction with maize production technologies is high, and most farmers are willing to promote them within their community. • Farmers show a positive attitude toward adopting maize production technologies, especially in areas like mechanization, crop management, and Integrated Pest Management. However, challenges such as access to quality inputs, financial support, and uncertainty about some practices (soil testing, government initiatives) remain. Addressing these gaps through better extension services, targeted subsidies, and improved market linkages could further enhance adoption rates.

The "Knowledge-Action" Gap

High-Adoption "Frontrunners"

The most successful areas of adoption involve physical inputs and basic field management:

• Improved Seeds (62.86%): This is the most adopted technology. It suggests that farmers recognize the yield benefits of hybrid varieties over traditional cultivars. • Sowing and Soil Health (51%-53%): Over half of the farmers follow recommended sowing times and spacing and practice soil testing. This indicates a growing awareness of scientific field preparation.

The "Knowledge Paradox"

There is a striking disconnect between what farmers do and what they know technically:

• The Awareness Gap: While 62.86% use improved seeds, only 12.86% claim to be "aware" of the full suite of recommended technologies.

• Training Deficit: Only 32.86% of farmers have attended formal training or demonstrations. This suggests that many farmers may be adopting seeds based on market availability or peer observation rather than formal technical education.

Critical Barriers and Low-Adoption Areas

The lowest adoption rates point toward specialized knowledge and high-resource requirements:

• Integrated Pest Management (IPM) (12.86%): This is the most neglected area. The reliance on traditional pest control methods likely leads to lower yields and higher chemical dependency. • Digital and Mechanized Farming (30%-38%):

Adoption of mobile advisory services (30%) and heavy machinery like planters or harvesters (38.57%) remains low. This is likely tied to the fact that 50% of these farmers are marginal landholders (5-8 bigha) , making large-scale mechanization or expensive digital subscriptions less accessible.

Economic Disconnect

• Yield vs. Income: While 56% of farmers reported a yield increase from these technologies, 26% of farmers disagreed that their income had improved. • Profitability Pressure: This indicates that even when technology works, market imperfections-such as high input costs or lack of credit access-prevent increased productivity from translating into higher household wealth.

References

1. Berkeley Oostendorp RH, Zaal F. Understanding adoption of soil and water conservation techniques: the role of new owners. CSAE Working Paper WPS/201105. Oxford: Department of Economics, Oxford University; 2011.
2. Rausser G, editor. Handbook of Agricultural and Resource Economics. Amsterdam: Elsevier, North Holland; 2001. p. 2001.
3. McGuirk DF, Mundlak Y. Incentives and constraints in the transformation of Punjab agriculture. IFPRI Research Paper No. 87. Washington, DC: International Food Policy Research Institute (IFPRI); 1991.
4. Mellor JW. The New Economics of Growth: A Strategy for India and the Developing World. Ithaca: Cornell University Press; 1976.
5. International Grain Council. International Grain Council report. 2015 Sep.
6. Koundouri P, Nauges C, Tzouvelekas V. Technology adoption under production uncertainty: theory and application to irrigation technology. American Journal of Agricultural Economics. 2006;88(3):657-670.
7. Maddala GS. Limited-Dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press; 1983.
8. Makokha S, Kimani S, Mwangi W, Verkuijl H, Musembi F. Determinants of fertilizer and manure use for maize production in Kiambu District, Kenya. Mexico: CIMMYT (International Maize and Wheat Improvement Center); 2001.
9. Ogada MJ, Nyangena W, Yesuf M. Production risk and farm technology adoption in rain-fed semi-arid lands of Kenya. AfJARE. 2010;4(2).
10. Olwande J, Sikei G, Mathenge M. Agricultural technology adoption: a panel analysis of smallholder farmers' fertilizer use in Kenya. CEGA Working Paper Series No. AfD-0908. California: Centre of Evaluation for Global Action, University of California; 2009.
11. Ouma J, Murithi F, Mwangi W, Verkuijl H, Gethi M, De Groote H. Adoption of maize seed and fertilizer technologies in Embu District, Kenya. Mexico: CIMMYT (International Maize and Wheat Improvement Center); 2002.