Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.
Skip to main content

Table 1 Combined analysis of AMMI and ANOVA of maize hybrids evaluated for grain yield across locations in 2020–2022

From: Multi-model approach for optimizing cold-wave resilient maize selection: unveiling genotype-by-environment interaction and predicting yield stability

Source

df

Sum Sq

Mean Sq

F value

Pr(> F)

Proportion

Accumulated

Significance

ENV

3

28.418

9.472617

75,400

0.0001

NaN

NaN

***

REP(ENV)

8

0.001

0.000126

0.0002

1.00

NaN

NaN

ns

GEN

42

392.27

9.33975

11.4

0.000174

NaN

NaN

***:

GEN:ENV

126

368.599

2.925387

3.56

0.000384

NaN

NaN

***

PC1

44

90.28

2.05181

2.5

0.0012

49

49

**

PC2

42

52.324

1.2458

1.52

0.00196

28.4

77.4

**

PC3

40

41.696

1.0424

1.27

0.125

22.6

100

ns

Residuals

852

700.023

0.821624

NA

NA

NA

NA

 
  1. All variables with significant (p < 0.05) genotype-vs-environment interaction were analyzed. To minimize the blocking effect, the mean of each year was applied during the analysis. Df: degree of freedom, ENV: Environment, REP: Replication, GEN: Genotype, PC: Principal components.NA: Not available, ns: none significant
Back to article page

CABI Agriculture and Bioscience

ISSN: 2662-4044