Modelling of grain yield in maize
| dc.contributor.author | Dwamena, Harriet Achiaa | |
| dc.date.accessioned | 2016-10-14T11:25:49Z | |
| dc.date.accessioned | 2023-04-19T13:53:47Z | |
| dc.date.available | 2016-10-14T11:25:49Z | |
| dc.date.available | 2023-04-19T13:53:47Z | |
| dc.date.issued | May 12, 2016 | |
| dc.description | A thesis submitted to The Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirement for the degree of M.Phil Applied Mathematics | en_US |
| dc.description.abstract | Grain yield is very important in maize production for breeders at the Crops Research Institute (CRI) of Ghana. However the yields of most varieties that are high yielding released by breeders does not perform so well after some of their release. This study was carried out to nd what causes the reduction in yield of these maize varieties of CRI over the years. An autoregressive moving average model (ARMA) was tted using a 20 year data (1995-2014) from CRI Fumesua. A multiple linear regression model was also tted to study factors a ecting grain yield in maize. Flowering data recorded on a trial eld at Fumesua research station in 2014 was used for the regression model. The study revealed that ARMA (2, 2) was found to be most suitable model for the di erenced series of maize yield. The multiple regression model showed that the factors plants height, days to owering and eld weight were statistically signi cant at 0.05 level. These factors (plants height, the days to ower and eld weight) are signi cant factors a ecting maize grain yield in Ghana. | en_US |
| dc.description.sponsorship | KNUST | en_US |
| dc.identifier.uri | https://ir.knust.edu.gh/handle/123456789/9255 | |
| dc.language.iso | en | en_US |
| dc.title | Modelling of grain yield in maize | en_US |
| dc.type | Thesis | en_US |
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