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Consumer acceptance of quality protein maize (QPM) in East Africa

Consumer acceptance of quality protein maize (QPM) in East Africa

De Groote, Hugo, Gunaratna, Nilupa S., Okuro, James O., Wondimu, Asrat, Chege, Christine K. and Tomlins, Keith (2014) Consumer acceptance of quality protein maize (QPM) in East Africa. Journal of the Science of Food and Agriculture, 94 (15). pp. 3201-3212. ISSN 0022-5142 (Print), 1097-0010 (Online) (doi:https://doi.org/10.1002/jsfa.6672)

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Abstract

BACKGROUND: Undernutrition in sub-Saharan Africa remains problematic, and quality protein maize (QPM) can benefit populations whose diets are heavily based on maize and who are consequently at risk for inadequate intakes of quality protein. However, changes in the chemical composition of QPM may affect its sensory characteristics and, hence, acceptance. Acceptance tests were therefore conducted to evaluate QPM varieties in three East African countries using central location tests with one or two varieties in each country, using the most popular preparations: ugali (Tanzania), githeri (Kenya) and injera (Ethiopia). In total, 281 urban and rural consumers of both sexes and varying levels of education evaluated the products on standard sensory criteria: appearance, aroma, texture, taste and overall, using a Likert scale.

RESULTS: The results show that African consumers can differentiate QPM products from their conventional counterparts, indicating that the QPM trait results in distinguishable sensory changes. Analysis by ordinal mixed regression models showed that consumers found QPM acceptable and even preferable to conventional maize.

CONCLUSION: The sensory characteristics of QPM are therefore no impediment to its adoption; on the contrary, when coupled with good agronomic performance, they may help its utilization, leading to a positive impact in nutritionally vulnerable populations.

Item Type: Article
Additional Information: © 2014 Society of Chemical Industry
Uncontrolled Keywords: quality protein maize, East Africa, consumer acceptance, affective test, ordinal regression, mixed models
Subjects: S Agriculture > S Agriculture (General)
S Agriculture > SB Plant culture
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Natural Resources Institute
Last Modified: 10 Oct 2016 10:53
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/12703

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