October 1996 // Volume 34 // Number 5 // Feature Articles // 5FEA4

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Marketing Fruits and Vegetables in South Central Alabama: The Diffusion Approach

The purpose of the study was to evaluate the marketing of fruits and vegetables in South Central Alabama using the diffusion approach. The objectives were: (a) to encourage farmers to attend workshops on grading and packaging of fruits and vegetables, and (b) to determine the impact of these workshops on the operations of the farmers. The diffusion innovation model in agriculture is based on the hypothesis that increasing information flow on innovations to farmers will result in positive results. Data for this study were obtained using a questionnaire. Results indicated that farmers were using the information they obtained at the workshops in their operations, indicating that diffusion has taken place.

Nii O. Tackie
Research Associate
Internet address: ntackie@acd.tusk.edu

Ntam Baharanyi
Associate Professor

Henry J. Findlay

G.W.C. Agricultural Experiment Station
Tuskegee University
Tuskegee, Alabama


Over the last few years, the marketing of agricultural produce has taken on increasing importance for Extension. Marketing Extension is a reinforcing phenomenon to production research and Extension as well as other facets of agricultural development such as credit and farmers' organizations (Narayanan, 1991).

Giving marketing information to farmers can be viewed from the perspective of innovation diffusion and decision-making theories. Rogers and Shoemaker (1971) described the innovation- decision process as a mental process through which an individual goes from first knowledge of an innovation to a decision of whether or not to adopt that innovation. They emphasized that the innovation-decision process is different from the diffusion process. The major difference, they argued, is diffusion occurs among units in a social system, but innovation decision-making takes place within the mind of an individual.

Mahajan and Peterson (1985) stated that of the many forms of innovation and diffusion processes that have been studied, one finding keeps recurring. That is, at the adoption of an innovation only a few people use it. As time goes on, however, more people use. They further noted that diffusion models have been developed to represent the level or spread of an innovation among a set of potential adopters in a social system as a function of time that has elapsed from the introduction of the innovation.

The diffusion model of agriculture is based on the hypothesis that appreciable increases in agricultural production may be achieved by allocating considerable resources to (a) increasing the flow of information to farmers about new agricultural technology and institutional arrangements (e.g., marketing and credit), and (b) teaching tradition-bound farmers how to make more economically rational management decisions on how to use the resources they have access to. Diffusion activities in agriculture have not only been carried out by Extension workers, but also by other communication systems such as radio, TV, and newspaper (Stevens & Jabara, 1988).

Education, in general, increases the speed with which new skills and techniques can be adopted and implemented (Jamison & Lau, 1982). According to Feder, Just, and Zilberman (1985) the probability of adoption increases as the stock of information pertaining to modern production increases through Extension efforts. The likelihood of adoption is a function of producer skills, level of education, ability to consider the information important, and whether the information is already in use. Also, Wozniak (1984) suggested that an increase in contact with sources of information about the use of new products and procedures increases the probability of adoption. Several studies (e.g., Feder, 1980; Just & Zilberman, 1983; Zilberman & Just, 1984; Feder, et al., 1985) have been conducted on innovation diffusion pertaining to Extension production but none was seen in the literature on Extension marketing.

The purpose of this study was to evaluate the marketing of fruits and vegetables in South Central Alabama using the diffusion approach. The objectives included: (a) to encourage farmers to attend workshops on grading and packaging fruits and vegetables, and (b) to determine the impact of these workshops on the operation of the farmers.


Seven workshops were conducted on grading and packaging fruits and vegetables for small and mid-size farmers in selected counties of Alabama over a three-year period. The population for the study included small and mid-size farmers in four counties. These workshops were intended to teach farmers about improved ways of marketing their produce in order to increase their income and knowledge in contemporary ways of marketing.

Representatives from surrounding grocery stores, the Alabama Department of Agriculture and Industries, and officials of the U. S. Department of Agriculture (USDA) were helped in conducting the workshops. Grocery stores provided the necessary fruits and vegetables used for the workshops. Officials of the grocery stores and USDA led the presentation and demonstration on grading and packaging. Issues of size, uniformity, color, weight and packaging were discussed. Samples of fruits and vegetables were used for the demonstration. Fruits and vegetables used included, but were not limited to, tomatoes, onions, sweet potatoes, carrots, watermelon, cantaloupes, corn, peaches, okra, cabbage, strawberries and, blueberries.

The final workshop was held at the Montgomery State Farmers' Market wholesale shed, enabling farmers to see first hand workers grading and packaging fruits and vegetables.

In addition, information was given to the farmers on food chain store requirements for farm produce, selected marketing strategies, and using cooperatives as a marketing strategy. The innovation in this case was the grading and packaging of produce.

In an effort to determine if the information given to these farmers was being used and to what extent, interviews were conducted (several months later) using a questionnaire. The questionnaire was designed to seek information on such things as the county and city of residence of farmer, the rating of workshop by farmer, and impact of workshop on operation. Ninety- eight questionnaires were mailed and 54 were returned.


Table 1 shows the results of assessment of the impact of grading and packaging workshops on operation of farmers. The farmers interviewed resided in Dallas, Sumter, Elmore, and Lowndes counties.

Table 1
Frequency and Percentages Reflecting Assessment of Workshops on Grading and Packaging
Category Number Percent
Sumter 21 38.9
Dallas 12 22.2
Elmore 18 33.3
Lowndes 3 5.6
City Where Attended
Epes 21 38.9
Selma 12 22.2
Montgomery 21 38.9
Workshop Year
1992 21 38.9
1993 27 50.0
1994 24 44.4
Value of Workshop
Poor 0 0.0
Good 3 5.6
Very Good 39 72.2
Excellent 12 22.2
Better Product 43 79.3
Higher Price 48 88.9
Future Preference
The Same 0 0.0
More Hands-on 36 66.7
Involve More Wholesalers 42 77.8

About 22.0% said the workshops were very good. Most farmers (94.4%) thought the general value of the workshop was high (very good and excellent). They said the information was very useful to them. When asked what impact the workshop is having on their marketing activities, 79.3% indicated that the grading and packaging information they received helps them select a uniform and better product, and hence get better produce to sale; 88.9% stated they got higher prices than usual due to using grading and packaging information.

This indicated that most of the farmers had adopted and were using the information they received from the workshops in their marketing practices. In response to their future preferences for workshops, 66.7% said they prefer hands-on workshops and 77.8% said they would like to see more involvement of wholesale buyers.


The study was conducted to see if farmers would adopt an innovation regarding grading and packaging fruits and vegetables. In this regard, a series of workshops were held for farmers in selected South Central Alabama Counties. The results of this study indicated that the farmers were using the information they obtained at the workshops in their operations, implying they considered the information important and useful. Because the study was preliminary and limited to farmers in only four of 67 counties in Alabama, it is suggested that more counties be included in future studies. It is also possible to replicate this study in other states. The findings of this study should be beneficial to practitioners and pre-service Extension educators in designing and implementing training programs for marketing farm produce.


Feder, G. (1980). Farm size, risk aversion and adoption of new technology under uncertainty. Oxford Economic Papers, 32, 263 -283.

Feder, G., Just, R. E., & Zilberman, D. (1985). Adoption of agricultural innovations in developing countries: A survey. Economic Development and Cultural Change, 33, 255-298.

Jamison, D. T., & Lau, L. J. (1982). Farmer education and farm efficiency. Baltimore: Johns Hopkins University.

Just, R. E., & Zilberman, D. (1983). Stochastic structure, farm size and technology adoption in developing agriculture. Oxford Economic Papers, 35, 307-328.

Mahajan, V., & Peterson, R. A. (1985). Models for innovation diffusion. Beverly Hills, CA: Sage.

Narayanan, A. (1991). Enhancing farmers' income through Extension services for agricultural marketing. In W. M. Rivera & D. J. Gustafson (Eds.), Agricultural Extension: Worldwide institutional evolution and forces change (pp. 151-161). Amsterdam: Elsevier Science.

Rogers, E. M., & Shoemaker, F. F. (1971). Communication of innovations: A cross-cultural approach (2nd ed.). New York: Free Press.

Stevens, R. D., & Jabara, C. L. (1988). Agricultural development principles: Economic theory and empirical evidence. Baltimore: Johns Hopkins University.

Wozniak, G. D. (1984). The adoption of interrelated innovations: A human capital approach. Review of Economics and Statistics, 66, 70-79.

Zilberman, D., & Just, R. E. (1984). Labor supply uncertainty and technology adoption. In R. D. Emerson, (Ed.), Seasonal labor markets in the United States (pp. 200-224). Ames: Iowa State University.