Representational Content and Agent-Environment Interaction

Proceedings of EuroCogSci 03 ◽

10.4324/9781315782362-78 ◽

2019 ◽

pp. 375-375

Author(s):

Tibor Bosse ◽

Catholijn M. Jonker ◽

Jan Treur

Keyword(s):

Representational Content ◽

Environment Interaction

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Supplemental Material for Effects of the Family Environment: Gene–Environment Interaction and Passive Gene–Environment Correlation

Developmental Psychology ◽

10.1037/0012-1649.44.2.305.supp ◽

2008 ◽

Keyword(s):

Family Environment ◽

Environment Interaction ◽

Gene Environment Interaction ◽

Gene Environment ◽

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Supplemental Material for Rethinking Expertise: A Multifactorial Gene–Environment Interaction Model of Expert Performance

Psychological Bulletin ◽

10.1037/bul0000033.supp ◽

2015 ◽

Keyword(s):

Interaction Model ◽

Environment Interaction ◽

Expert Performance ◽

Gene Environment Interaction ◽

Gene Environment

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A physiological model of cybersickness during virtual environment interaction

PsycEXTRA Dataset ◽

10.1037/e577422012-003 ◽

2005 ◽

Author(s):

W. Kendal Roberts ◽

Jennie J. Gallimore

Keyword(s):

Virtual Environment ◽

Physiological Model ◽

Environment Interaction

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Developmental perspectives on gene x environment interaction in psychopathology

PsycEXTRA Dataset ◽

10.1037/e740232011-115 ◽

2011 ◽

Author(s):

Steve S. Lee

Keyword(s):

Environment Interaction ◽

Gene X Environment Interaction

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Gene-Environment Interaction in the Determination of Levels of Haemostatic Variables Involved in Thrombosis and Fibrinolysis

Thrombosis and Haemostasis ◽

10.1055/s-0038-1657569 ◽

1997 ◽

Vol 78 (01) ◽

pp. 457-461 ◽

Author(s):

S E Humphries ◽

A Panahloo ◽

H E Montgomery ◽

F Green ◽

J Yudkin

Keyword(s):

Environment Interaction ◽

Gene Environment Interaction ◽

Gene Environment

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TO THE EXPERIMENTAL CONFIRMATION OF THE HYPOTHESIS ABOUT AN ECO-GENETIC NATURE OF THE PHENOMENON GENOTYPE * ENVIRONMENT INTERACTION FOR WOODY PLANTS

Sel skokhozyaistvennaya Biologiya ◽

10.15389/agrobiology.2018.1.151eng ◽

2018 ◽

Vol 53 (1) ◽

pp. 151-156 ◽

Author(s):

V.A. Dragavtsev ◽

◽

I.A. Dragavtseva ◽

I.L. Efimova ◽

A.P. Kuznetsova ◽

...

Keyword(s):

Woody Plants ◽

Experimental Confirmation ◽

Environment Interaction ◽

Genotype Environment Interaction ◽

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Genotype-Environment Interaction in Calf Production. II. Live Measurements and Carcass Traits

Journal of Animal Science ◽

10.2527/jas1973.363471x ◽

1973 ◽

Vol 36 (3) ◽

pp. 471-475 ◽

Author(s):

T. R. Batra ◽

W. R. Usborne ◽

D. G. Grieve ◽

E. B. Burnside

Keyword(s):

Carcass Traits ◽

Environment Interaction ◽

Genotype Environment Interaction

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Settlement Change, Urbanism, and Human and Environment Interaction at Lamanai and Ka’kabish: Two Precolumbian Maya sites in Northern Belize

10.30861/9781407357560 ◽

2020 ◽

Author(s):

Alec McLellan

Keyword(s):

Environment Interaction

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Genotype x environment interaction in European black alder (Alnus glutinosa (L.) Gaertn)

10.31274/rtd-180814-5237 ◽

1984 ◽

Author(s):

Oghenekome Ukrakpo Onokpise

Keyword(s):

Alnus Glutinosa ◽

Genotype X Environment Interaction ◽

Environment Interaction ◽

Genotype X Environment ◽

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Using AMMI approach to delineate genotype by environment interaction and stability of barley (Hordeum vulgare L.) genotypes under northern Indian shivalik hill conditions

Indian Journal of Genetics and Plant Breeding (The) ◽

10.31742/ijgpb.80.3.15 ◽

2020 ◽

Vol 80 (03) ◽

Author(s):

Om Prakash Yadav ◽

A. K. Razdan ◽

Bupesh Kumar ◽

Praveen Singh ◽

Anjani K. Singh

Keyword(s):

Hordeum Vulgare ◽

Grain Yield ◽

Principal Component ◽

Genotype By Environment Interaction ◽

Environment Interaction ◽

Hordeum Vulgare L ◽

Genotype By Environment ◽

Biplot Analysis ◽

Principal Component Axis ◽

Genotype by environment interaction (GEI) of 18 barley varieties was assessed during two successive rabi crop seasons so as to identify high yielding and stable barley varieties. AMMI analysis showed that genotypes (G), environment (E) and GEI accounted for 1672.35, 78.25 and 20.51 of total variance, respectively. Partitioning of sum of squares due to GEI revealed significance of interaction principal component axis IPCA1 only On the basis of AMMI biplot analysis DWRB 137 (41.03qha–1), RD 2715 (32.54qha–1), BH 902 (37.53qha–1) and RD 2907 (33.29qha–1) exhibited grain yield superiority of 64.45, 30.42, 50.42 and 33.42 per cent, respectively over farmers’ recycled variety (24.43qha–1).

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