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<title>Journal Articles</title>
<link>http://localhost/xmlui/handle/123456789/5465</link>
<description>Journal Articles Authored by IEET Postgraduate Students</description>
<pubDate>Fri, 22 May 2026 03:03:42 GMT</pubDate>
<dc:date>2026-05-22T03:03:42Z</dc:date>
<item>
<title>Impact of Different Vegetation as Riparian Zones in Controlling Nutrients and Sediment Flow Into Water Bodies Assessment of the</title>
<link>http://localhost/xmlui/handle/123456789/7011</link>
<description>Impact of Different Vegetation as Riparian Zones in Controlling Nutrients and Sediment Flow Into Water Bodies Assessment of the
Kigira, Francis Karanja
In this case study nutrients and sediment were considered to be an important water&#13;
quality concern in Nyangores Catchment in the larger Upper Mara Catchment shown&#13;
in figure 1 due to high eutrophication of the river as is evident at some sections of the&#13;
river. Nitrogen and Phosphorous originates from inorganic and organic fertilizer that&#13;
affect the river water quality due to intensive agricultural farming and livestock&#13;
grazing. Increased fertilizer application has enlarged N and P nutrient burden into the&#13;
river through runoff leading to pollution and consequently eutrophication.Three plots&#13;
of different vegetations were set up to represent different scenarios of riparian&#13;
vegetation. Plots representing natural forest, grassland and bare land a distance of&#13;
twenty meters apart to avoid disparity , were set up to determine their effectiveness in&#13;
controlling the nutrients. The plots each measured 2m by 10m were set up for Natural&#13;
forest, bare ground and grassland field. Runoff samples were collected from the plots&#13;
on rainy days, and taken to the laboratory for Ph, Ec, NO3 and PO4 analysis. From the&#13;
samples analysis the results showed the Ph for the natural forest, bareland and&#13;
grassland were 7.0, 6.8, and 6.5 respectively, for the nitrates were natural forest 0.20&#13;
mg/l, bareland 0.5 mg/l, grassland 0.3 mg/l for phosphates forest it was 0.01gm/l for&#13;
bareland it wasـ&#13;
&#13;
0.57 mg/l and for grassland 0.55 mg/l. For the Electrical conductivity, forest gave 0.4 mhos,&#13;
bareland&#13;
0.5 mhos and 0.2 mhos for grassland. There is a clear indication that Natural forest on&#13;
top of controlling the Ph and Ec better than grassland, it has a natural sink for nitrates&#13;
and phosphate. It is therefore recommended that natural forests be reserved and that&#13;
grass should be used as an alternative for riparian zones.&#13;
Key words: Riparian, Nutrients, Water quality, Water bodies.
PhD Research Publication
</description>
<pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate>
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<dc:date>2026-05-21T00:00:00Z</dc:date>
</item>
<item>
<title>To Assess the Impact of Land Use Change on Nutrients Flow and to Establish the Level of  Key Pollutants of Nyangores River</title>
<link>http://localhost/xmlui/handle/123456789/7010</link>
<description>To Assess the Impact of Land Use Change on Nutrients Flow and to Establish the Level of  Key Pollutants of Nyangores River
Kigira, Francis Karanja
This study was carried out with the aim of assessing the effect of Riparian land use/ land cover change on the &#13;
hydrology and water quality of the upper Mara River catchment specifically Nyangores River. The study &#13;
incorporated remote sensing and GIS tools to prepare and analyze the data. It involved sampling of sediments &#13;
deposits and water flows at various points of the river to quantify water quality parameters such as N, P, Ca and &#13;
Fe etc. These parameters were tested in the laboratory. &#13;
Land cover change was analyzed from dry season Land Sat MSS, TM and ETM images of 1976, 1980, 1985, &#13;
1990, 1995, 2003, 2006, 2010, and 2014 respectively. Digital image analysis for the riparian zone showed that &#13;
between 1976 and 2003, crop land increased by about 100%, other vegetation and forests  reduced by 32% and &#13;
34% respectively with the river line decreasing by 50%. Comparatively high percentages of N, P, Ca and Fe i.e. &#13;
0.07meq/100g soil, 0.66meq/100g soil, 12meq/100g soil and 17mg/kg respectively were detected from soils &#13;
collected along the cattle tracks and in the water directly below the animal tracks. Grass strips along the rivers &#13;
were found to filter sediment and nutrients and soil from the urban set up and tested high for Fe=46 mg/kg, N= &#13;
0.03meq/100g soil K=0.21meq/100g soil caused by channelized flow. Soil composition of 89% sand, 3.4% clay &#13;
and 7.5% silt which is sandy soil forms the downstream banks of river Nyangores and this is the main cause of &#13;
the river banks erosion and subsequent sedimentation. Channelization should be controlled and a lot more of &#13;
grass should be planted along the riparian zone also deep rooted trees should be planted at the downstream of &#13;
river Nyangores to control river bank Erosion.  &#13;
Keywords: Riparian zone, Land use/land cover, water quality, hydrology.
PhD Research Publication
</description>
<pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate>
<guid isPermaLink="false">http://localhost/xmlui/handle/123456789/7010</guid>
<dc:date>2026-05-21T00:00:00Z</dc:date>
</item>
<item>
<title>OPERATIONS MANAGEMENT AND PERFORMANCE OF FOOD AND  BEVERAGE MANUFACTURING FIRMS IN KENYA</title>
<link>http://localhost/xmlui/handle/123456789/6994</link>
<description>OPERATIONS MANAGEMENT AND PERFORMANCE OF FOOD AND  BEVERAGE MANUFACTURING FIRMS IN KENYA
Mbugua, Annevelyn Njoki
Despite the importance of the food manufacturing industry in Kenya, it has been &#13;
experiencing a lot of turbulence in the recent past including a drop in the GDP, an &#13;
increasing imbalance of trade, and the exiting of large multinationals. The main focus of &#13;
this study was to assess the effect of operations management on the performance of food &#13;
and beverage manufacturing firms in Kenya. The research design that was appropriate for &#13;
this study was a descriptive cross-sectional design. 246 food and beverage manufacturing &#13;
firms formed the source from which the respondents will be sourced. The population frame &#13;
was thus the procurement managers of the 246 food and beverages firms. These firms are &#13;
registered under the Kenya Association of Manufacturers. The study used a Stratified &#13;
random sampling technique. The study further used simple random sampling within the &#13;
different strata of 152 food and beverage manufacturing firms. The heads of departments &#13;
concerned with procurement formed the unit of observation. The questionnaire was used to &#13;
collect primary data. Quantitative and qualitative data were generated from the closed&#13;
ended and open-ended questions, respectively. Descriptive statistics such as frequency &#13;
distribution, mean (measure of dispersion), standard deviation, and percentages were used. &#13;
Inferential data analysis was conducted by use of univariate regression analysis, Pearson &#13;
correlation coefficient, and multiple regression analysis. The inferential statistic is used to &#13;
make judgments about the probability that an observation is dependable or one that &#13;
happened by chance in the study. The study results were presented through the use of tables &#13;
and figures. The study found that operations management is statistically significant in &#13;
explaining performance of food manufacturing firms in Kenya. The influence was found to &#13;
be positive, indicating that an increase in operations management would lead to an increase &#13;
in performance of food manufacturing firms. Therefore, the study concluded that operations &#13;
management has a positive and significant relationship with performance of food &#13;
manufacturing firms in Kenya. The study therefore recommends that manufacturing firms &#13;
should reduce excess inventory by implementing just-in-time (JIT) inventory systems. This &#13;
minimizes carrying costs, reduces the risk of waste due to product expiration, and optimizes &#13;
working capital. In addition, the firms should develop standardized work procedures and &#13;
ensure that all employees follow these procedures rigorously. This will lead to consistent &#13;
product quality and efficient production processes
PhD Research Publication
</description>
<pubDate>Wed, 20 May 2026 00:00:00 GMT</pubDate>
<guid isPermaLink="false">http://localhost/xmlui/handle/123456789/6994</guid>
<dc:date>2026-05-20T00:00:00Z</dc:date>
</item>
<item>
<title>OUTBOUND LOGISTICS AND PERFORMANCE OF FOOD AND BEVERAGE  MANUFACTURING FIRMS IN KENYA</title>
<link>http://localhost/xmlui/handle/123456789/6993</link>
<description>OUTBOUND LOGISTICS AND PERFORMANCE OF FOOD AND BEVERAGE  MANUFACTURING FIRMS IN KENYA
Mbugua, Annevelyn Njoki
Despite the importance of the food manufacturing industry in Kenya, it has been &#13;
experiencing a lot of turbulence in the recent past including a drop in the GDP, an &#13;
increasing imbalance of trade, and the exiting of large multinationals. The main focus of &#13;
this study was to assess the effect of outbound logistics on the performance of food and &#13;
beverage manufacturing firms in Kenya. The research design that was appropriate for this &#13;
study was a descriptive cross-sectional design.246 food and beverage manufacturing firms &#13;
formed the source from which the respondents will be sourced. The population frame was &#13;
thus the procurement managers of the246food and beverages firms. These firms are &#13;
registered under the Kenya Association of Manufacturers. The study used a Stratified &#13;
random sampling technique. The study further used simple random sampling within the &#13;
different strata of 152 food and beverage manufacturing firms. The heads of departments &#13;
concerned with procurement formed the unit of observation. The questionnaire was used to &#13;
collect primary data. Quantitative and qualitative data were generated from the closed&#13;
ended and open-ended questions, respectively. Descriptive statistics such as frequency &#13;
distribution, mean (measure of dispersion), standard deviation, and percentages were used. &#13;
Inferential data analysis was conducted by use of univariate regression analysis, Pearson &#13;
correlation coefficient, and multiple regression analysis. The inferential statistic is used to &#13;
make judgments about the probability that an observation is dependable or one that &#13;
happened by chance in the study. The study results were presented through the use of tables &#13;
and figures. the study found that Outbound Logistics is statistically significant in explaining &#13;
the performance of food manufacturing firms in Kenya. The influence was found to be &#13;
positive, indicating that an increase in Outbound Logistics would lead to an increase in the &#13;
performance of food manufacturing firms in Kenya. Therefore, the study concluded that &#13;
Outbound Logistics has a positive and significant relationship with the performance of food &#13;
manufacturing firms in Kenya. From the findings, the study recommends that &#13;
manufacturing firms should develop a more efficient distribution network to ensure timely &#13;
and cost-effective delivery of products to customers. The firms should utilize route &#13;
planning software to determine the most efficient delivery routes, minimizing travel tim
PhD Research Publication
</description>
<pubDate>Wed, 20 May 2026 00:00:00 GMT</pubDate>
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<dc:date>2026-05-20T00:00:00Z</dc:date>
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