Analysis and Modelling of the Effects of Water Stress on Maize Growth and Yield in Dryland Conditions
It is essential to provide experimental evidence and reliable predictions of the effects of water stress on crop production in the drier, less predictable environments. A field experiment undertaken in southeast Queensland, Australia with three water regimes (fully irrigated, rainfed and irrigated u...
Saved in:
Published in: | Plant production science Vol. 13; no. 2; pp. 199 - 208 |
---|---|
Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Tokyo
Taylor & Francis
2010
Crop Science Society of Japan Taylor & Francis Ltd Taylor & Francis Group |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | It is essential to provide experimental evidence and reliable predictions of the effects of water stress on crop production in the drier, less predictable environments. A field experiment undertaken in southeast Queensland, Australia with three water regimes (fully irrigated, rainfed and irrigated until late canopy expansion followed by rainfed) was used to compare effects of water stress on crop production in two maize (Zea mays L.) cultivars (Pioneer 34N43 and Pioneer 31H50). Water stress affected growth and yield more in Pioneer 34N43 than in Pioneer 31H50. A crop model APSIM-Maize, after having been calibrated for the two cultivars, was used to simulate maize growth and development under water stress. The predictions on leaf area index (LAI) dynamics, biomass growth and grain yield under rainfed and irrigated followed by rainfed treatments was reasonable, indicating that stress indices used by APSIM-Maize produced appropriate adjustments to crop growth and development in response to water stress. This study shows that Pioneer 31H50 is less sensitive to water stress and thus a preferred cultivar in dryland conditions, and that it is feasible to provide sound predictions and risk assessment for crop production in drier, more variable conditions using the APSIM-Maize model. |
---|---|
ISSN: | 1343-943X 1349-1008 |
DOI: | 10.1626/pps.13.199 |