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Analysis of Factors Affecting Canola Plantation Development in Tabriz

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Analysis of Factors Affecting Canola Plantation Development in Tabriz International Journal of Agricultural Management and Development (IJAMAD) Available online on: www.ijamad.iaurasht.ac.ir ISSN: 2159-5852 (Print) ISSN:2159-5860 (Online) Analysis of Factors Affecting Canola Plantation Development in Tabriz and Marand Counties, Iran Ghader Dashti, Babollah Hayati, Noushin Bakhshy * and Mohammad Ghahremanzadeh Received: 29 August 2015, his study identifies and analyzes factors influencing canola Accepted: 02 January 2016 plantation development in Tabriz and Marand Counties. TThe Censored Model was used to analyze cross-sectional data collected from 372 farmers using a questionnaire. Due to the weakness of the Tobit model in separating factors affecting the adoption decision of farmers and factors affecting the rate of adoption, the Heckman Model was employed to separate the contributions made by these factors. The results of estimated Probit model in the first stage of the Heckman Approach showed that machinery ownership had an important effect on canola adoption, as a 1% increase in machinery ownership had led to 0.158% increase in canola adoption probability. Contact with extension agents, farm income proportion, education, and farmers’ Abstract experience influenced canola plantation probability positively, and the age and number of fragmentations had a negative impact on it. The significance of inverse Mill’s ratio indicates that the factors affecting the decision to start planting and the amount of canola plantation are not the same. The Heckman’s second step estimation results indicated that the loan amount, canola relative benefit, and family labor had a positive effect, and that machinery cost and farm distance from the road had a negative effect on Keywords: canola acreage. Relative benefit was the most effective element, Canola Adoption, Censored as 1% increase in relative benefit results in a 0.342% increase in Model, Heckman two step procedure canola plantation. International Journal of Agricultural Management and Development, 7(1):25-35, March 2017. International Journal of University of Tabriz, Faculty of Agriculture, Department of Agricultural Economics * Corresponding author’s email: [email protected] 25 Analysis of Factors Affecting Canola Plantation Development / Dashti et al INTRODUCTION for this study. Studies of adoption of new crops Canola is the third most important source of by farmers have been often framed within the vegetable oil in the world after soybean and traditional adoption-diffusion model of innovation. palm. Rapeseed contains about 48% oil and has Rogers (1962) developed a model of diffusion, an appropriate fatty acid composition (Taheri et which has become widely established in the al., 2010) . Per capita consumption of oil and fat marketing literature. The diffusion process con - is 17.4 kg in Iran and 90% of Iran’s population sists of four key elements: an innovation, the oil need (2610 thousand tones) is imported from social system on which the innovation impacts, Brazil, Canada and Swiss (Mostofi, 2008; Yousse - the communication channels of that social fi et al., 2010) . Given that domestic production system, and time (Wright & Charlet, 1995) . of edible oils is insufficient to meet increasing Notwithstanding, this model has some weak - demands due to population growth, the policy nesses, because it ignores individual farmer approach to Iran’s agriculture has been increasing characteristics, social relations in decision- strategic agricultural products (especially oilseeds) making and noneconomic goals. The other model to meet domestic consumption and to reduce is a farm structure model. This model looks at the dependence on food imports. In this regard, economic constraints imposed by farm size and area expansion and yield improvement have generally argues that larger and more economically been envisaged as the most significant solutions viable farms are more capable of assuming the (Abyar, 2002) . risks of new behaviors. Finally, researchers com - Canola contains a high percent of oil. Charac - bined two theoretical explanations of farmer adop - teristics and compatibility of canola with different tion behavior, the diffusion-in novation model climate conditions have increased its importance and farm structure model (Lubell, 2004) . as hopes for the supply of edible oil in Iran. The decision to adopt a new crop or technology . 7 Meanwhile, despite the attempt made to increase has been widely documented throughout the 1 0 2 canola production, East Azerbaijan Province literature. Shapiro et al. (1992) used the Tobit h c r a has experienced considerable variation in canola Model to study the adoption of double cropping M , cultivation to the extent that the number of soybeans and wheat in the Midwest. The results 5 3 - 5 canola cultivars has dropped from 1957 in 2007 showed that farmers start double cropping in an 2 : ) 1 to approximately 867 in 2010; it means 55% of attempt to boost revenue and lower the risks. As ( 7 , t canola cultivators during these years were de - Shapiro shows higher income encourages farmers n e creased. Tabriz and Marand counties have an to adopt new thing, so we can consider income m p o l important role in whole province canola acreage and benefit as factors affecting canola cultivation e v e determination. About one-third of province’s adoption. Fo ster and Rosenzweig (1995) studied D d n canola cultivated area was assigned to these adoption and profitability of high-yielding seed a t n two counties. varieties (HYV) associated with the Green Rev - e m e Study of trend of canola plantation shows olution of rural Indian households. They used a g a n farmers’ primary interest in canola plantation model incorporating learning by doing and a M l and in their turning away from this product. learning spillovers. The estimates indicated that a r u t Farmers' attitudes toward canola are not stable; imperfect knowledge about the management of l u c i they may plant canola one year and give it up the new seeds was a significant barrier to adop - r g A next year. Therefore, it must be investigated tion; this barrier diminished as farmers’ experience f o l why farmers adopt different behaviors toward with the new technologies increased. As they a n r u canola (cultivation continuity, or stop or deciding stated own experience and neighbors’ experience o J l to start plantation for the first time). with HYVs significantly increased HYV prof - a n o i Canola adoption and its plantation development itability, therefore experience and participation t a n r can be a solution for oil import dependence in extension classes could be an important factor e t n I problems. Whereas canola is an almost new influencing canola cultivation. Munshi (2004) crop in Iran, adoption models can be employed studied technology diffusion in the Indian Green 26 Analysis of Factors Affecting Canola Plantation Development / Dashti et al revolution. As they stated, information flows on internal and external factors, such as infor - are weaker in a heterogeneous population when mation and prices. The results emphasize the the performance of a new technology is sensitive role of profitability in expanding new crops. It to unobserved individual characteristics, pre - is an important factor that encourages farmers venting individuals from learning from neighbors’ to plant new crops. A number of studies have experiences. This characterization of social been conducted in Iran. Salami and Einallahi learning is tested with wheat and rice. The rice- Ahmad Abadi (2001) applied Tobit and two- growing regions display greater heterogeneity stage Heckman Models to specify factors affecting in growing conditions and the new rice varieties sugar beet production in Khorasan, Iran. The were also sensitive to unobserved farm charac - results showed that the factors influencing the teristics. Wheat growers respond strongly to farmers' decision to cultivate sugar beet are not neighbors’ experiences, while rice growers do the same as those affecting the area under culti - not. Oladele (2005) applied the Tobit Model to vation. Abyar (2002) conducted a survey of study the discontinued adoption of agricultural factors influencing soybean area expansion in technology among farmers in southwestern Golestan province of Iran. Using the Tobit Nigeria. The results indicated that the lack of method, the study found out that farm size, extension visits and lack of input required were farmers experience, access to farm machinery, the most important factors on discontinuing and the type of irrigation water source were the adoption of improved maize. Accordingly, it most effective factors in the soybean area ex - could be deducted that inputs like machinery pansion. Shafiei (2007) identified factors affecting ownership, credits and so on, can influence olive plantation development in Kerman province, canola cultivation. Amao and Awoyemi (2008) using Logit Model. The results showed that studied adoption of improved cassava varieties variables including education, children above . and its welfare effect on households in Osogbo. 14 years old, contact with extension agents, 7 1 0 2 The results indicated that age, access to extension and acreage of garden can affect olive adoption. h c r agents, crop yield, marital status, labor, production As these studies indicate, some factors can in - a M input, and education influenced the adoption fluence adoption and other can influence culti - , 5 3 - positively, and family, size, had a negative vated area acreage. Those which can affect the 5 2 : ) effect, and that poverty was higher among the adoption (first stage) are machinery ownership, 1 ( 7 , non-adopters. Their results show the importance income proportion, age, education, experience, t n of farmer characteristics on adoption. Oyekale fragments, and contact with extension agents. e m p o and Idjesa (2009) studied adoption of improved These variables are mostly characteristic variables. l e v maize seeds and production efficiency in Rivers On the other hand, some variables can affect e D d state, Nigeria. The findings showed that education, canola acreage like family labor, machinery n a t farming experience, mono-cropping, minimum cost, relative benefit, credit, and distance.
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