Journal of Food Security
ISSN (Print): 2372-0115 ISSN (Online): 2372-0107 Website: Editor-in-chief: Monideepa Becerra
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Journal of Food Security. 2017, 5(5), 162-168
DOI: 10.12691/jfs-5-5-2
Open AccessArticle

Evaluation and Developing Simple Techniques for Assessing Gari Adulteration

Ernest Teye1, , Robert Sarpong Amoah1, Michael Osei Adu2 and Daniel Darko1

1Department of Agricultural Engineering, School of Agriculture, College of Agriculture and Natural Sciences, University of Cape Coast, Cape Coast, Ghana

2Department of Crop Science, School of Agriculture, College of Agriculture and Natural Sciences, University of Cape Coast, Cape Coast, Ghana

Pub. Date: August 26, 2017

Cite this paper:
Ernest Teye, Robert Sarpong Amoah, Michael Osei Adu and Daniel Darko. Evaluation and Developing Simple Techniques for Assessing Gari Adulteration. Journal of Food Security. 2017; 5(5):162-168. doi: 10.12691/jfs-5-5-2


Gari is a major staple food for many West Africans. This study aimed at evaluating the quality parameters of gari, price per quantity in “Olonka” (a local measuring container) and develop a nondestructive simple technique for assessing adulteration. A completely randomized design (CRD) was used with three replications. The samples of gari were collected from seven regions of Ghana (from: processors and retailers in each region). The results showed that the mean price per weight in “Olonka” was 2.12 kg per Gh 6.4 (0.3313 kg/Gh). The physicochemical properties fall within acceptable range; pH was 4.3 to 5.4, moisture content was 4.5- 7.4 %, and ash content was 1.11-1.61 %. Swelling capacity and bulk density were 3.0- 3.2 and 0.52- 0.61 g/cm3, respectively. Particle size distribution was found to be 0.94-1.69 mm. From this study, bulk density and swelling capacity technique could be used to detect adulteration of gari with sawdust above 10 %. The tests showed that gari produced in Ghana meet the world and local standard, and adulteration of gari with sawdust can easily and simply be detected rapidly using low technology even in rural areas by determining their bulk density and swelling capacity using the developed prediction equations: Y = 0.0035X + 0.239 (R2 = 0.9827) where; Y = bulk density and X= percentage pure gari and Y = 0.0207X + 0.9618 (R2 = 0.9811) where; Y = swelling capacity and X= percentage pure gari, respectively.

quality gari physicochemical properties adulteration prediction equation

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