The effect of planting date on yield was studied in Parana State, Brazil where five tropical hybrids of maize were planted at 14 planting dates over three growing seasons at five locations. Soil water holding characteristics and meteorological variables were measured at each location. The water release curve for each soil was determined, using a power function. Corn heat units were calculated and used to measure the phenological development of each hybrid. This information, along with meteorological data, was used in a mathematical model to simulate plant growth over each growing period. Meteorological data from 1976 to 1986 were employed to simulate yield data for 14 planting dates during each growing season at four locations for each hybrid. The average production curve for the 10 growing seasons was compared to the curve observed for the 1986/87 growing season for three of the five hybrids. Thermal requirements appeared as an efficient tool to predict corn developmental stages, and the power function fit satisfactorily the observed soil data. The predicted curve, representing a 10-year average, showed that the designed model accounted for the major cultural and environmental factors that affect yield at each location, being sensitive enough to detect differences among genotypes. Comparisons between predicted and observed curves showed that they had the same shape.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.75868 |
| Date | January 1988 |
| Creators | Gomes, Jose |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Doctor of Philosophy (Department of Plant Science.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 000730715, proquestno: AAINL48623, Theses scanned by UMI/ProQuest. |
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