Adoption of Improved Cotton Production Technologies in Katsina State, Nigeria

MATERIALS AND METHODS

The study was carried out in Malumfashi, Daudawa and Funtua villages in Katsina state in the Sudan Savanna specifically, in year 2001. The study areas were purposely selected because of the high concentrations of cotton farmers in these areas, the proximity to IAR, (where cotton packages are being developed) and the efforts of ADP work to push cotton innovations to farmers.

Preliminary field visits were made to identify the villages to be surveyed and to inform the village heads of the date of interview. Pre-tested structured interview schedule was used to elicit information from the respondents on recommended practices.

A simple random sampling technique was used for the choice of respondents within each of the selected zone, One hundred farmers were selected from Funtua and 75 farmers each from Malumfashi and Daudawa The difference in the sample size was due to concentration of cotton farmers in Funtua. In all, a total of 250 farmers made up the sample size for the study.

Types of data collected: The data collected from the farmers include those on their socio-economic characteristics, awareness and adoption of improved technologies for cotton production and constraints to adoption of the technologies.

Cotton requires nitrogen, phosphorous, potassium and boron, Nitrogen should be applied at the rate of 60 kg ha^–1, 30 kg of P₂O₅ ha^–1 and 30 kg ha^–1 of K₂O ha^–1. Boron can be applied where micro nutrient is deficient at the rate of 0.75 kg ha^–1.Weed is a major problem of cotton. Thus, 2 to 3 timely hoe-weeding are recommended. In addition to these, the following herbicides are recommended, Gardoprim at 3-4 L ha^–1, dalapon plus diuron at 2.0+0.8 kg ha^–1, alachlor+diuron at 2.0+0.8 kg ha^–1.

The recommended pesticides are Karate, Cymbush, Decis, Perfecthion. This should be applied 3-4 times depending on incidence of insect infestation.

Methods of analysis: Percentages were used in analyzing objective 1. Frequencies and percentages were used to achieve objective 2. Multiple regression analysis was used to realize objective.

The explicit regression model for the socio-economic variables influencing the farmers’ adoption of improved practices is expressed as follows

Y = f (X_1,X_2,X_3,X_4,X_5,X_6,X_7,X_8,X_9,X_10,X_11,X_12…….e)

In order to determine the factors influencing the adoption of improved technologies, the adoption index was regressed against the selected independent variables. The linear, semi log and double log functional forms were tried based on the size of R and significance of the variables, the linear functional form was chosen.

RESULTS AND DISCUSSION

Level of awareness and adoption: Awareness is the first stage of technology adoption (Akanya, 1990; Adeniji, 1996), A farmer has to know about new innovation before adopting it. From the results of the study, there was high degree of awareness of the improved technological package among the respondents.

Table 1 shows that the level of awareness of use of improved seed, chemical fertilizer, planting date chemical control and plant spacing was high among farmers. However the level of awareness of other technologies like herbicides (15%) and seed dressing (26%) was low. The level of awareness was lower for herbicides and highest (85%) for fertilizer application. The most adopted technology was fertilizer application which was adopted by 77% of the respondents. This was followed by use of improved seed (75%) and chemical spraying (72%). The least adopted technologies were herbicides (10%) seed dressing chemicals (21%) and seed rate (39%).

This is contrary to the study on adoption of improved sorghum production technologies by Banta et al. (1986) which showed that seed dressing chemical was the most adopted technologies among farmers in Maiduguri area. The reason adduced by farmers in the study area for low adoption rate of herbicides and seed dressing chemicals is that farmers consider the two operations as extra expenses; cotton requires a lot of money especially for spraying as such most farmers conserve their resources for this.

The low adoption of seed rate agrees with the findings of Mijindadi and Njoku (1986) on adoption of rice technologies.

There is a gap between awareness and adoption of innovation. Ahmed (1984) observed a similar gap between awareness and adoption of hybrid cattle among settled pastoralist Fulanis in Kachia LGA of Kaduna State. Also, Adeniji (1996) observed that the use of recommended farm innovations by farmers was less than the knowledge of the innovations.

Sources of information on improved cotton technologies: The sources of information through which the respondents first heard about the cotton package included other farmers, extension agents, use of radio, television, pamphlets, posters and hand bills.

Table 2 shows the various sources of information to farmers on the improved cotton production practices. It shows that extension agents were the major channel through which 74%, of the respondents received information on improved practices while about 53% identified radio as the main source of information. Other sources identified were village heads/friends/and neighbours indicated by 9% of the respondent, while 4% of the respondents identified research institute as the major source.

Table 1:	Respondents level of awareness and adoption of recommended cotton production technologies

Table 2:	Sources of information on improved cotton practices
*More than sample size due to multiple responses

Table 3:	Respondents’ reasons for adoption
*More than sample size due to multiple responses

The result suggests that the Training and Visit system of extension is effective in the study area. This could be attributed to the constant visits to the farmers on fixed schedules as being pursued by Katsina State Agricultural development Authority (KTARDA). The result is consistent with earlier report by Voh (1980). Atala (1980) and Chikwendu et al. (1996) where extension agents were identified as the major source of information to farmers on recommended practices.

The response to radio, was popular because most farmers have radio or were able to listen to farming programmes (viz., Noma Kankara, Noma Arski,) through their friends or neighbour’s radio. Radio is equally one of the fastest means of communicating with generality of farmers. this agrees with the findings of Voh (1981) and Adeniji (1996) who found radio as the second source of information after extension agents. The insignificant impact of the printed media such as newspapers, magazines and posters may be due to low educational level of respondents.

Reasons for adoption: The question related to reason for using improved technologies was asked in order to determine the relevance of the technologies. This is presented in Table 3. Ninety six percent of the respondents adopted the innovations to obtain more yield/income, while 25% adopted in order to try out new techniques. Other responses given by the respondents were: conviction and to imitate others who used the technologies.

Table 4:	Respondents reasons for non adoption of technologies for cotton production
*Responses were obtained from farmers who did not adopt the technologies

Table 5:	Linear regression function for the relationship between adoption of cotton technologies and farmers’ socio-economic characteristics
*Coefficient statistically significant at 1% level, R2 = 0.564, Adjusted R2 = O. 542 F = 25.544 at 0.01 level of significance

An important observation of the finding is that for all practices, the highest proportion of adopters did so to obtain high yield and subsequently to have their income raised. This agrees with Clark and Akinbode (1968) that financial gain and high yield are the apparent reasons why farmers adopted recommended practices.

Reasons for non adoption: Table 4 indicates the reasons for non adoption of improved cotton production technologies. Most respondents complained of inadequate knowledge of the technologies on seed dressing chemicals, planting date, seed rate, plant spacing, use of herbicides. The major reason given by some of the respondents for non-adoption of improved seed and fertilizer application was that they were not readily available. Similar findings were obtained by Nweke and Chidebelu (1991).

Table 5 shows the result of multiple regression analysis of factors affecting adoption of recommended improved practices (Table 5) shows that the R² (coefficient of multiple determination) was. 564 which means that about 56% of the variation in the adoption of recommended practices was explained by the variables included in the model. It suggests that the variables have a moderate effect on adoption of recommended practices for cotton production. The remaining 44% could be attributed to the variables not included in the model.

Extension contacts, hired labour, awareness of innovations were the most important variables in the adoption of improved technologies for cotton production. They have positive coefficient, implying that the level. This indicates that the level of adoption increases correspondingly with increase in household size and intensity of extension contact.

Farming experience was negatively related to adoption. This may be because of those farmers who have over the years gained experience in using particular innovation may find it difficult to switch to a new one no matter the perceived benefits. Similarly educational levels, income, membership of cooperatives were found to be statistically not significant. The non significance of education may not be unconnected with the low level of education in the study area. This agrees with that of Patel and Anthonio (1971) and Chikwendu et al. (1996) who did not establish any significant relationship between education and adoption behaviour.

CONCLUSIONS

\The study shows that there is an appreciable level of awareness of improved technologies for cotton production. However, the level of adoption was low. While it may be somewhat misleading to make generalized conclusions based on this study the findings suggest that some socio-economic variables are important predictors of improved cotton production technologies. Therefore there is the need for promotion of the packages by extension services and other media to enhance the adoption of these technologies.