Masters Thesis
Most of the complementary foods in Tanzania have been reported to be poorly prepared,
low energy and nutrient density and low nutrients’ bioavailability. This study was carried
out in Rombo district with the aim to assess feeding practices, nutrient content of the
frequently used complementary foods, identify nutrient gaps and then develop more
nutritious recipes that may either fill or narrow the gaps. A cross-sectional study was
conducted in three ra ndomly selected villages. Information on feeding practices and
types of complementary foods was collected using questionnaires. Seven samples of
complementary foods with high frequency were collected and analysed for proximate
composition, vitamin A and C, iron, zinc, iodine and calcium and results were expressed
per 100 g dry weight. They were then converted to the amount consumed per day and
then subtracted from the recommended amount needed from complementary foods per
day based on child’s age in order to identify the gaps. Linear programming method was
used to formulate the recipes, which were then taken to laboratory for analysis of the
same parameters. Sensory evaluation was conducted to test the acceptability of the
formulated recipes. The results showed poor feeding practices, gaps in energy, vitamin C,
iron, zinc, calcium and iodine of the frequently used complementary foods. There was a
significant (p<0.05) improvement in the nutrient content of the formulated recipes with
the exception of zinc. Energy, vitamin A, vitamin C, iron, zinc, calcium and iodine
content of the formulations ranged from 376.31-486.42 kcal, 1122-3622 µg, 65.05-124.07
mg, 8.08-53.05 mg, 2.29-8.68 mg, 333.98-1228.16 mg and 126.81-792.78 µg/100 g dry
weight, respectively. There were significant differences (p<0.05) among formulations for
all the sensory attributes. Linear programming was found to be a good method to
improve nutrient content of complementary foods using low cost, locally available and
cultural acceptable ingredients.
Innovative Agriculture Research Initiative (iAGRI)