Leaf area prediction for corn (Zea mays L.) cultivars with multiregression analysis

Title:

Leaf area prediction for corn (Zea mays L.) cultivars with multiregression analysis

Creator:

Oner, F., Odabas, M. S., Sezer, I., and Odabas, F.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:e4392e30-23c7-4b42-84de-75783d72e8a4
uuid:e4392e30-23c7-4b42-84de-75783d72e8a4
issn:0300-3604
doi:10.1007/s11099-011-0069-0

Subject:

botanika, botany, leaf area, multiregression analysis, and Zea mays L.

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

Leaf area is one of the most important parameter for plant growth. Reliable equations were offered to predict leaf area for Zea mays L. cultivars. All equations produced for leaf area were derived as affected by leaf length and leaf width. As a result of ANOVA and multiregression analysis, it was found that there was a close relationship between actual and predicted growth parameters. The produced leaf-area prediction model in the present study is LA = a + b L + c W + d LZ where LA is leaf area, L is leaf length, W is maximum leaf width, LZ is leaf zone and a, b, c, d are coefficients. R2 values were between 0.88-0.97 and standard errors were found to be significant at the p<0.001 significance level. and F. Oner ... [et al.].

Language:

Multiple languages

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

637-640

Source:

Photosynthetica | 2011 Volume:49 | Number:4

Harvested from:

CDK

Metadata only:

false