Effects of selected drivers of information and communication on awareness and perception of tomato post-harvest loss-reduction technologies in Kaduna, Nigeria

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Nnaemeka Korie
Lucy Njeru
John Mburu
George Gitau


Adoption; Awareness; Multivariate; Post-harvest losses; Probit Model; perception; Technologies


The Nigerian government's policy on agriculture has supported productivity enhancements among smallholder farmers, yet tomato production is constrained by post-harvest losses leading to over 45 % (750,000 metric tons) loss. Various initiatives are constantly being introduced to make technologies and practices available to reduce these losses. This study was carried out to determine the level of awareness and perception of four technologies. A total of 420 tomato farmers were selected in Kaduna State, Nigeria. Awareness and perception were modelled using the Multivariate Probit Model. The results showed that one or more of the independent variables including cooperative affiliation (p<0.001, for awareness of Reusable Plastic Crate {RP} technique), frequency of extension visit (p<0.001, for awareness of RP), and farm area cultivated (p<0.05, for awareness of Refrigerated Truck {RT}/ Machine Drying {MD}) were significant. For perception, some of the independent variables explored and found significant included multiple sources of information for CS/RT, losses through transit/storage (P<0.01) and the number of technologies adopted (P<0.001) for cheapness; credit access (P<0.001) and farm area (P<0.001) for availability; marital status (P<0.01) and losses through storage (P<0.021) for labour saving perceptions. The awareness and perception of the tomato PHL reduction technologies do not provide common determinants. The study concluded that the communication channels such as Farmer to Farmer, Radio and extension agents (57.9%, 9.3%, 33% for RP, respectively), among others, influenced awareness of the new technologies among farmers. The study recommends the need to drive farmers’ awareness using suitable advocacy channels. A better understanding of constraints that influence farmers' perceptions is important while designing and rolling out technologies.

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