Prediction of Rate of Leaf Appearance, Leaf Area Index and Growth Stages in Corn and Sunflower plants

Document Type : Research Paper

Authors

1 Assistant Professor of Agriculture Department, Payame Noor University, Tehran, Iran

2 Agriculture Faculty, Payame Noor University, Tehran, Iran

Abstract

Abstract
Background and objectives
Prediction of development periods of crops by mathematical models, especially, time to growth ending is so important in every area. So, as impotence of prediction of phenology, leaf area and time to leaf growth ending, this research performed to introduce and test of Phenology MMS model in environmental conditions of Boukan, prediction of leaf appearance rate, phyllochron in stress condition of drought and to correct coefficient of allometric equations of predicting of leaf area of Corn (cv. Single cross 704) and Sunflower (cv. Shamshiri).

Method and Materials
In this research, Phenology MMS evaluated using field data for corn and sunflower . Then time and thermal time needed to leaf growth ending and phyllochron (degree day per leaf) obtained using segmented model in every stress level. So, the best algometric model selected for describing of relation between leaf area and leaf number.

Results
Results showed that the model predicted development periods of corn and sunfloer well and was capable to estimate day and thermal time needed to every special development period in two state: day after sowing and day after emergence. Also, in corn, results released that time to leaf growth ending will occur after reception of 782.9 degree day which equal to 72.3 day after emergence whereas for sunflower time to leaf growth ending will occur after reception of 798.1 degree day which equal to 59.14 day after emergence. On other hands, a leaf will include to plant 3 and 2.06 day after emergence in corn and sunflower respectively. In medium tension, the slope of regression line of leaf number versus thermal time, increased and reached to 0.0285 and 0.033 leaf per degree day in corn and sunflower respectively. Results of predicting of leaf area using exponential segmented models showed that all of models were good in predicting of leaf area index.

Conclusion
As for being acceptable of results of phonological model for prediction of thermal time, leaf number and phyllochron, we advise using of this model in modeling and agronomical studies. So, drought stress can effect on leaf appearance rate and phyllochron value. All of models were good in predicting of leaf area index.
Conclusion
As for being acceptable of results of phonological model for prediction of thermal time, leaf number and phyllochron, we advise using of this model in modeling and agronomical studies. So, drought stress can effect on leaf appearance rate and phyllochron value. All of models were good in predicting of leaf area index.

Keywords


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