Quantitative analysis of maize leaf collar appearance rates.

Area of Science:

• Agronomy
• Plant Physiology
• Crop Modeling

Background:

• Phyllochron is crucial for crop growth and yield prediction.
• Current models lack accuracy across diverse maize cultivars and environments.

Purpose of the Study:

• Quantify and separate the impacts of sowing date and cultivar on maize leaf collar appearance (LCA).
• Develop a more accurate model for predicting maize LCA.

Main Methods:

• Field experiments were conducted to collect maize LCA data.
• A bilinear model was employed to analyze LCA patterns.
• Statistical analysis was used to assess the effects of sowing date and cultivar.

Main Results:

• A bilinear model accurately described maize LCA (R²adj > 0.99).
• Leaf collar appearance rate was slower for early leaves than later leaves.
• Phyllochron before the turning point (PHYLL I) was significantly higher than after (PHYLL II), averaging twice the duration.
• Both PHYLL I and PHYLL II were influenced by sowing date and cultivar, showing plasticity.

Conclusions:

• The study reveals significant plasticity in maize phyllochron, influenced by leaf rank, sowing date, and cultivar.
• Findings enhance the applicability of phyllochron-collar measurements in crop models.
• Results can inform improved maize management strategies and yield prediction.