Predicting leaf area development of sunflower

Chapman, S.C., Hammer, G.L. and Palta, J.A. (1993) Predicting leaf area development of sunflower. Field Crops Research, 34 1: 101-112. doi:10.1016/0378-4290(93)90114-3

Author Chapman, S.C.
Hammer, G.L.
Palta, J.A.
Title Predicting leaf area development of sunflower
Journal name Field Crops Research   Check publisher's open access policy
ISSN 0378-4290
Publication date 1993-07
Sub-type Article (original research)
DOI 10.1016/0378-4290(93)90114-3
Volume 34
Issue 1
Start page 101
End page 112
Total pages 12
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Language eng
Abstract The effects of genotype and environment on canopy development of sunflower (Helianthus annuus L.) have been the subject of much research. A framework was developed to analyse data from this research and predict leaf area of irrigated sunflower as affected by daily temperature, and the phenology of different cultivars and hybrids. Between emergence and anthesis, total leaf area per plant (TPLA) was determined as a logistic function of TPLA at anthesis and thermal time from emergence (TT). Total leaf area per plant at anthesis was linearly related to total leaf number for a range of cultivars and hybrids. Total leaf number was estimated as the product of the duration of the period emergence to head visible (in days) and the average leaf initiation rate in that period. Leaf initiation rate was related to the average temperature during this period. Senescent leaf area per plant (SPLA) was calculated as an exponential function of TT from head visible. Leaf area index (LAI) was determined as the difference at any time between TPLA and SPLA, multiplied by plant density and a density modifier, which allowed for the effect of density on leaf area per plant. Almost all variation in the TPLA and SPLA data was accounted for using inputs of TT and dates of phenological stages. When the model was tested on independent data it accounted for 93% of the observed variation in LAI.
Keyword Water stress
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Queensland Alliance for Agriculture and Food Innovation
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Citation counts: TR Web of Science Citation Count  Cited 12 times in Thomson Reuters Web of Science Article | Citations
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Created: Mon, 07 Mar 2011, 15:30:23 EST