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        <rdf:li rdf:resource="https://cris.library.msu.ac.zw//handle/11408/6924" />
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    <dc:date>2026-04-14T23:14:22Z</dc:date>
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  <item rdf:about="https://cris.library.msu.ac.zw//handle/11408/6924">
    <title>Use of Indigenous Knowledge Systems and Scientific Methods for Climate Forecasting in Southern Zambia and North-Western Zimbabwe</title>
    <link>https://cris.library.msu.ac.zw//handle/11408/6924</link>
    <description>Title: Use of Indigenous Knowledge Systems and Scientific Methods for Climate Forecasting in Southern Zambia and North-Western Zimbabwe
Authors: Mugabe, F. T.; Mubaya, C. P.; Nanja, D.; Gondwe, P.; Munodawafa, Adelaide; Mutswangwa, E.; Chagonda, I.; Masere, Tirivashe P.; Dimes, J.; Murewi, C
Abstract: The semi-arid areas of Southern Africa receive low and erratic rainfall which varies in both seasons and from year to year resulting in food insecurity. Few of the smallholder farmers have access to seasonal climate forecasts from the meteorological department hence they depend mostly on their indigenous knowledge systems for forecasting seasons which they make use of to develop crop management adaptive strategies. The study shows that farmers have several indicators for weather forecasting and some of these are similar in both Zambia and Zimbabwe. Some of these indicators include; floods or excessive rains in the preceding season, strong winds around October, an extended cold season that goes up to August and sometimes September and abundance or scarcity of certain fruits. The indicators conflict in some seasons and in such cases the farmers resort to using those that they know to have stronger signals from their reliability factors. Positive relationship between indigenous knowledge systems and modern science were observed between the 2008/9 season and 2009/10 which confirms that indigenous knowledge systems, when fully developed could be very helpful in seasonal forecasting. The study recommends the importance of the restoration of the confidence of the indigenous people in their traditional knowledge and skills of weather forecasting.</description>
    <dc:date>2010-01-01T00:00:00Z</dc:date>
    <dc:creator>Mugabe, F. T.</dc:creator>
    <dc:creator>Mubaya, C. P.</dc:creator>
    <dc:creator>Nanja, D.</dc:creator>
    <dc:creator>Gondwe, P.</dc:creator>
    <dc:creator>Munodawafa, Adelaide</dc:creator>
    <dc:creator>Mutswangwa, E.</dc:creator>
    <dc:creator>Chagonda, I.</dc:creator>
    <dc:creator>Masere, Tirivashe P.</dc:creator>
    <dc:creator>Dimes, J.</dc:creator>
    <dc:creator>Murewi, C</dc:creator>
  </item>
  <item rdf:about="https://cris.library.msu.ac.zw//handle/11408/6923">
    <title>Effect of within-season daily rainfall distribution on maize crop yields</title>
    <link>https://cris.library.msu.ac.zw//handle/11408/6923</link>
    <description>Title: Effect of within-season daily rainfall distribution on maize crop yields
Authors: Kevin Jan Duffy; Masere, Tirivashe P.
Abstract: It is well known that major changes in global food systems are needed when agriculture must meet the challenge of feeding a growing population and at the same time minimize global environmental impacts. Both these aims require optimal crop yields. This need applies crucially to staple foods, such as maize, and in&#xD;
developing parts of the world, such as much of Africa. Within-season rainfall will affect crop yields, and this paper, using simulations, investigates the effects of varying within-season daily rainfall distributions on potential maize yields. The results show that within-season distributions can affect maize yields in low-rainfall&#xD;
seasons, but yields are also dependent on the use of fertilizer. In average and above average rainfall seasons, within-season variance has little effect on maize yields. If within-season distributions affect crop yields in low-rainfall seasons, as shown here, then this finding could be important for understanding the impacts of possible&#xD;
changes in climate.</description>
    <dc:date>2015-01-01T00:00:00Z</dc:date>
    <dc:creator>Kevin Jan Duffy</dc:creator>
    <dc:creator>Masere, Tirivashe P.</dc:creator>
  </item>
  <item rdf:about="https://cris.library.msu.ac.zw//handle/11408/6922">
    <title>Factors cost effectively improved using computer simulations of maize yields in semi-arid Sub-Saharan Africa</title>
    <link>https://cris.library.msu.ac.zw//handle/11408/6922</link>
    <description>Title: Factors cost effectively improved using computer simulations of maize yields in semi-arid Sub-Saharan Africa
Authors: Masere, Tirivashe P.; Duffy, Kevin
Abstract: Achieving food security is a challenge for the developed and developing world. These challenges are greater for developing nations such as in Africa because of the severity of the problems. An important aspect of this is poor agricultural productivity. Worldwide, technology is being developed to increase agricultural production. One aspect of this is the development of predictive computer models that enable farmers to optimise crops using management decision based on simulation scenarios. Most African farmers do not have the computer resources or expertise to implement these types of technology. Even extension offices in Africa, who provide much needed advice, can be under resourced in this way. We suggest here that simpler computer models that are cheaper and easier to use need to be developed. As a first step in this process we investigate here which factors are most cost effectively managed using computer simulations in semi-arid conditions pertinent to much of sub-Saharan Africa. Factors known to be important in crop farming are planting date, sowing density, variety, weeding, soils and fertiliser. We use qualitative arguments with simulations and conclude that interactions between rainfall, soil condition and fertiliser can benefitfrom simulations and thus should help in their management.</description>
    <dc:date>2014-01-01T00:00:00Z</dc:date>
    <dc:creator>Masere, Tirivashe P.</dc:creator>
    <dc:creator>Duffy, Kevin</dc:creator>
  </item>
  <item rdf:about="https://cris.library.msu.ac.zw//handle/11408/6921">
    <title>Crop management decision making  processes by small-scale farmers of  Lower Gweru Communal area, Zimbabwe</title>
    <link>https://cris.library.msu.ac.zw//handle/11408/6921</link>
    <description>Title: Crop management decision making  processes by small-scale farmers of  Lower Gweru Communal area, Zimbabwe
Authors: Masere, Tirivashe P.
Abstract: Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less &#xD;
between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. Abstract comes here. It must be not less between 150 and 200 words. A study was conducted with 30 representative farmers in Lower Gweru Communal area to determine how small-scale farmers were making their crop management and climatic decisions. Data was gathered through focus group discussions, resource allocation mapping and semi structured interviews. The farmers perceived the climate of their area to be changing to an extent that their usually trusted local indicators to forecast the nature of the next season were no longer reliable to guide farm decisions. &#xD;
They noted that they were stuck with these local indicators due to lack of tested and proven alternatives to aid the &#xD;
decision making process.</description>
    <dc:date>2014-01-01T00:00:00Z</dc:date>
    <dc:creator>Masere, Tirivashe P.</dc:creator>
  </item>
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