American Journal of Agricultural and Biological Sciences

Prediction Model of Leaf Area in Soybean (Glycine max L.)

Mohammad Nabi Ilkaee, Farzad Paknejad, Mohsen Zavareh, Mohammad Reza Ardakani and Ali Kashani

DOI : 10.3844/ajabssp.2011.110.113

American Journal of Agricultural and Biological Sciences

Volume 6, Issue 1

Pages 110-113

Abstract

Abstract: Problem statement: Measure of leaf area by means of leaf area Meter is very expensive and difficult. Hence obtain of one simple model for calculate of leaf area in soybean (Glycine Max L.) is very necessary. Approach: In order to develop a suitable simple model for calculation of leaf area by means of leaf length and width, a Randomized Complete Block Design base donlit plot experiment with four replications was carried out in 2009 growing season at Karaj, Iran. Four soybean cultivars (Wiliams, Zane, L17 and M7) were used in the experiment. Totally, 1500 leaves for eight different times were measured in the experiment. Leaf width (W), length (W) and Leaf Area (LA) were measured. The actual leaf area of the plant was measured and regression model was fitted. Results: Pierson correlation showed that between actual leaf area relate to leaf width (R2 = 0.89), L × W (R2 = 0.98), W2 (R2 = 0.9), ln L×ln W (R2 = 0.9), ln LW (R2 = 0.87) and (LW)2 (R2 = 0.93) have been positive correlation. Also between L × W and actual leaf area in Zane cultivar have been equation y= 1.173 x + 0.984 (R2 = 0.92), in Williams cultivar y= 1.147×+ 1.052 (R2 = 0.939), in M7 cultivar y= 1.116 x + 1.824 (R2 = 0.962) and in L17 cultivar y= 1.135 x + 0.865 (R2 = 0.976). Conclusion: Developed model was calculated y= 3.46344 – 12.73172 ln LA + 0.827 LW + 9.47628 LL + 12.20208 ln LW + 0.05655 hWW + 0.00074436 h LW. Relation among L×W and actual leaf area in all of the cultivars y = 1.129×+ 1.344 (R2 = 0.965). (h = half).

Copyright

© 2011 Mohammad Nabi Ilkaee, Farzad Paknejad, Mohsen Zavareh, Mohammad Reza Ardakani and Ali Kashani. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.