Scientific Papers

Predictors of inoculant-based technology adoption by smallholder soybean farmers in northern Ghana: implications for soil fertility management | Agriculture & Food Security


Description and summary statistics of the variables

The description and summary statistics of the variables included in the analysis are provided in Table 1.

Most of the respondents were males, in their youthful ages, and possessed very little formal education. Soybean production is therefore an economic activity dominated by young farmers. Olatunde et al. [23] found that most soybean farmers in Nigeria were males as compared to females and in their youthful and prime ages for farming. Promotion of soybean farming can therefore empower the youth to venture into farming to reduce rural unemployment. The respondents had average household and farm size of 13 members and 0.6 hectares, respectively. Farmers perceived their soils to be infertile, while 54.5% applied chemical fertilizer. Also, 50.5% of the respondents had access to agricultural extension, 34.5% were members of a farmer association, while 30% participated in off-farm work as a source of extra income for the household.

Characteristics of the sample according to adoption status

Table 2 presents the results of the farmer-specific factors, input and institutional factors hypothesized to influence farmers’ adoption decisions.

Table 2 Characteristics of the sample according to adoption status

The results showed that there was no significant difference between the mean age of adopters and non-adopters. In the adopter category, males constituted about 66% while in the non-adopter category, males made up 58.9% of the respondents. Mutuma et al. [21] found about 70% of soybean farmers in Kenya to be female farmers. The relatively higher proportion of male soybean farmers agrees with the finding of Olatunde et al. [23] which showed that most soybean farmers in Nigeria were males. Educational status, as well as household size, did not differ statistically between the adopters and non–adopters of rhizobium inoculants in the study area. Also, three farm-level characteristics, namely farm size, degree of specialization and soil fertility status, did not differ statistically between inoculum adopters and non-adopters.

With the input variables considered, the results showed that there was no significant difference in the cost of ploughing for both groups, but there exists a significant mean difference in the usage of fertilizers between adopters and non-adopters. A smaller proportion of adopters applied chemical fertilizer compared to the proportion of non-adopters who applied fertilizer. This means that adoption of inoculants is expected to decrease with chemical fertilizer application. Hence, farmers’ behaviour suggests a possible substitution between rhizobium inoculant and chemical fertilizers in soybean production. Mutuma et al. [21] found a similar result in Kenya where users of rhizobium inoculants applied lower quantities of chemical fertilizers as compared to non-users.

Finally, there was significant difference in access to extension, membership of farmer groups and distance to market between adopters and non-adopters. A greater percentage of adopters had contact with extension agents (i.e. 69.8% as compared to 36.0% for non-adopters), which is expected to enhance adoption of inoculants. Extension agents are important source of information to farmers and, through educational programmes and trainings, help farmers embrace new ideas and technologies that enhance their production activities. A greater percentage of adopters belonged to a farmer group. About 52.3% of respondents belonged to farmer groups relative to 21.1% of non-adopters. This finding also agrees with Olatunde et al. [23] who found that about 96% of soybean farmers using rhizobium inoculants in Kenya belonged to farmer groups. Membership in a farmer group is therefore expected to increase the decision to adopt inoculants. This is expected because farmer associations are fora for exchanging ideas, acquiring and disseminating information relevant to the welfare of members such as modern production methods and access to production factors. Adopters had shorter distance to the local market suggesting greater market access as compared to non-adopters. The market distance variable is therefore expected to influence the decision to adopt inoculant technology.

Expenditure on inoculant technology

Table 3 presents the distribution of farmers’ expenditure per hectare on inoculant technology.

Table 3 Expenditure on rhizobium inoculants

The results indicate that more than half of the respondents (57%) did not use inoculants in production, while 7% applied the equivalent of 1 packet of inoculant. Also, 33% spent between GHȼ 26 and GHȼ 50 per hectare on inoculants (i.e. US$ 6.10 and US$ 9.30, respectively), while 3% of the respondents spent between GHȼ 51 and GHȼ 99 per hectare on inoculants (i.e. US$9.44 and US$18.33, respectively). Santos et al. [25] indicated that rhizobium inoculants are cheaper and environmentally friendlier compared to other agrochemicals like inorganic fertilizers. A pack of 0.1 kg (i.e. 100 g) of inoculant costs between GHȼ 20 and GHȼ 30 (US$ 3.70 and US$ 5.56) in the study area and is recommended for inoculating 20 kg of soybean seeds to an acre of land.

Double-hurdle estimates of factors influencing inoculant technology adoption and intensity of adoption

The determinants of inoculant technology adoption are presented in Table 4. The table presents the results for the probit model (first hurdle) explaining farmers’ discrete adoption decision as well as the truncated regression (second hurdle) showing the intensity of adoption. The results show that both farmer characteristics and farm-level factors, as well as input variables and institutional factors influence farmers’ adoption decision and the intensity of inoculant adoption in northern Ghana.

Table 4 Double-hurdle estimates of factors influencing inoculant technology adoption

The farmer-specific factors showed that sex of the farmer influenced the decision to adopt inoculant-based technology adoption but not the intensity of adoption. The results indicate that female farmers have a higher likelihood to adopt inoculant technology compared to male farmers. The result agrees with Nabintu et al. [22] who found female farmers to have higher adoption of inoculants compared to male farmers in Democratic Republic of Congo.

The results also show that the age of the farmer influenced the decision to adopt inoculant-based technology adoption but not the intensity of adoption. The results show that adoption initially decreases with age of the farmer. However, as the farmer increases in age, the probability of adoption increases. Hence, adoption of inoculant technology follows a non-linear pattern among the smallholder farmers in the study area.

Also, educational status of the farmer was significant in explaining the decision to adopt inoculant-based technology. The results showed that farmers with formal education were less likely to adopt the inoculant-based technology. This contradicts the a priori expectation because one would expect that formally educated farmers would have had more knowledge about the benefits of the technology, but the results showed otherwise. Mahama et al. [18] found that the education of a farmer had a positive influence on the intensity of adopting soybean technologies in Ghana. Their measure of education was, however, continuous as opposed to the discrete scale employed in this study. Even though Donkoh et al. [10] and Olatunde et al. [23] highlighted that educated farmers are more risk averse and have a higher probability to adopt agricultural technology, the justification for the finding in this study could be explained by two reasons. First, most of the farmers in the study did not have access to formal education. About 85% of them did not have formal education but adopted the technology probably because they were exposed to it. Secondly, it could be that, the farmers who were formally educated were involved in other off-farm activities with less commitment to soybean farming activities, hence their lower probability of adoption.

Additionally, household size explained both the decision to adopt and the intensity of adoption. While adoption of inoculants decreased with household size, intensity of adoption on the other hand increased. Kimaro et al. [15] alluded that households with many members are more disposed to adopt technologies that enhance farm profitability such as inoculants and improved varieties.

The results also indicate that cattle ownership was associated with higher adoption intensity but did not significantly influence the decision to adopt inoculant technology. Herd owners could benefit from availability of manure from the cattle they rear, which could be used to improve soil fertility, thus reducing their dependence on fertility-enhancing inputs. On the other hand, cattle owners may be classified as “better-off” compared to non-cattle owners, hence may be able to intensify input use such as inoculants. Anang and Zakariah [4] reported that herd ownership had a significant effect on joint adoption of inoculants and inorganic fertilizer in Ghana.

Results from the farm-level factors showed that the degree of specialization measured as the proportion of the total land area allocated to soybean production was found to positively influence the intensity of adoption. This implies that farmers who allocated a larger proportion of their total land to soybean cultivation were more likely to spend more on inoculants.

This study further revealed that adoption of inoculants decreased with fertility of farmers’ field. In other words, the more fertile the soil, the lower the likelihood to adopt inoculants, which is consistent with a priori expectation. Farmers are rational, hence will allocate resources in the way that meets their needs. As a result of resource constraints, smallholder farmers with relatively fertile soils are expected to channel their limited resources into other limiting factors of production, thus reducing the adoption of fertility-improving inputs such as inoculants. Perception of soil fertility status, however, had no influence on the intensity of adoption.

With the input factors, the cost of ploughing had a negative influence on the intensity of adoption of inoculants. This meets the study’s a priori expectation because as the cost of ploughing increases, smallholder farmers who typically have low level of incomes are less likely to intensify adoption. The cost of ploughing is an important part of the cost structure of most smallholder farmers and therefore plays a critical role in farm investment decisions.

Also, chemical fertilizer adoption was found to reduce the probability and intensity of inoculant adoption implying that farmers generally consider rhizobium inoculant and chemical fertilizer as substitutes. Sammauria et al. [24] indicated that, the use of inoculants as a substitute for chemical fertilizers is not only efficient but also sustainable and that continuous use of chemical fertilizers has a deterioration effect on soil health and pollutes water bodies. It may also be argued that since farmers are generally resource poor, they are not able to afford both soil amendment factors at the same time. However, unlike chemical fertilizer, application of pesticides and herbicides increased the probability and intensity of inoculant adoption, implying that farmers generally perceive pesticides and herbicides to be complementary to rhizobium inoculant in soybean cultivation.

Institutional factors were very influential in farmers’ decisions to adopt inoculant technology. For example, access to agricultural extension agents significantly influenced the decision to adopt inoculant-based technology. This was expected and makes economic sense because the technology was disseminated to farmers through agricultural extension agents. Hence, farmers who received extension visits are more likely to learn about the technology and subsequently adopt it. The results align with that of Danso-Abbeam and Baiyegunhi [8] who found extension visits to have a positive influence on adoption of agrochemical management practices in Ghana.

Participation in off-farm work had a negative influence on the probability and intensity of adoption of inoculant technology. The result implies that smallholder farmers who work outside the farm use less inoculants in production. This may indicate that majority of the farmers who engage in off-farm work may not be full-time farmers and do not give full attention to soybean cultivation. It may further suggest that these farmers may be worse-off economically, hence their participation in off-farm jobs in a rural setting to generate additional income. As indicated by Anang and Zakariah [4], for very low-income households, participation in off-farm work may not lead to higher farm investment, and may even result in a reduction in on-farm investment because such households may be driven by the need to survive. In other words, income from off-farm employment may be insufficient to finance farm operations and may be diverted to meet other pressing household needs, because for such households, survival is prioritized above other household decisions.

Membership of farmer groups was another significant institutional factor that explains producers’ choice to adopt rhizobium inoculant technology. Farmer group membership enhanced inoculant technology adoption which aligns with the study’s a priori expectation because membership of farmer groups helps in promoting smallholders’ access to information, services and farm inputs. The result is consistent with Wafullah [27] who found that membership of farmer groups significantly influences the probability of adopting inoculant technology in Kenya.



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