CSIRO Publishing Books Journals About Us Shopping Cart You are here: Journals > Animal Production Science   
Animal Production Science
  Food, Fibre and Pharmaceuticals from Animals
 
Search
 
 
  Advanced Search
   

Journal Home
About the Journal
Editorial Board
Contacts
Content
Online Early
Current Issue
Just Accepted
All Issues
Special Issues
Research Fronts
Reviews
Sample Issue
For Authors
General Information
Notes for Authors
Submit Article
Open Access
For Referees
General Information
Review Article
Annual Referee Index
For Subscribers
Subscription Prices
Customer Service
Print Publication Dates

 Early Alert
Subscribe to our Email Alert or RSS feeds for the latest journal papers.

 Connect with us
facebook   youtube

Training

Publication Workshops


 

Article << Previous     |     Next >>   Contents Vol 48(3)

Analysis of high yielding maize production – a study based on a commercial crop

C. J. Birch A, G. McLean B, A. Sawers C

A School of Land, Crop and Food Science, The University of Queensland, Gatton Campus, Gatton, Qld 4343, Australia.
B Queensland Department of Primary Industries and Fisheries, Agricultural Production Systems Research Unit, Tor Street, Toowoomba, Qld 4350, Australia.
C Sawers Farms, Boort, Vic. 3537, Australia.
D Corresponding author. Email: c.birch@uq.edu.au
 
PDF (186 KB) $25
 Export Citation
 Print
  


Abstract

This paper reports on the use of APSIM – Maize for retrospective analysis of performance of a high input, high yielding maize crop and analysis of predicted performance of maize grown with high inputs over the long-term (>100 years) for specified scenarios of environmental conditions (temperature and radiation) and agronomic inputs (sowing date, plant population, nitrogen fertiliser and irrigation) at Boort, Victoria, Australia. It uses a high yielding (17 400 kg/ha dry grain, 20 500 kg/ha at 15% water) commercial crop grown in 2004–05 as the basis of the study. Yield for the agronomic and environmental conditions of 2004–05 was predicted accurately, giving confidence that the model could be used for the detailed analyses undertaken. The analysis showed that the yield achieved was close to that possible with the conditions and agronomic inputs of 2004–05. Sowing dates during 21 September to 26 October had little effect on predicted yield, except when combined with reduced temperature. Single year and long-term analyses concluded that a higher plant population (11 plants/m2) is needed to optimise yield, but that slightly lower N and irrigation inputs are appropriate for the plant population used commercially (8.4 plants/m2). Also, compared with changes in agronomic inputs increases in temperature and/or radiation had relatively minor effects, except that reduced temperature reduces predicted yield substantially. This study provides an approach for the use of models for both retrospective analysis of crop performance and assessment of long-term variability of crop yield under a wide range of agronomic and environmental conditions.

Keywords: irrigation modelling, nitrogen optimisation, plant population, radiation, sowing date, temperature, yield, yield reliability, Zea mays.


   
Subscriber Login
Username:
Password:  

    


 
Top  Email this page
 
Legal & Privacy | Contact Us | Help

CSIRO

© CSIRO 1996-2012