Agronomy Journal Journal of Natural Resources and Life Sciences Education
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


Published online 7 May 2008
Published in Agron J 100:760-764 (2008)
DOI: 10.2134/agronj2006.0282
© 2008 American Society of Agronomy
677 S. Segoe Rd., Madison, WI 53711 USA
This Article
Right arrow Figures Only
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Google Scholar
Right arrow Articles by Sabaghnia, N.
Right arrow Articles by Sabaghpour, S. H.
PubMed
Right arrow Articles by Sabaghnia, N.
Right arrow Articles by Sabaghpour, S. H.
Agricola
Right arrow Articles by Sabaghnia, N.
Right arrow Articles by Sabaghpour, S. H.
Related Collections
Right arrow Statistics
Right arrow Plant and Environment Interactions

LEGUMES

Graphic Analysis of Genotype by Environment Interaction for Lentil Yield in Iran

Naser Sabaghniaa, Hamid Dehghania,* and Sayyed Hossain Sabaghpourb

a Dep. of Plant Breeding, Tarbiat Modares Univ. P.O. Box 14115-336 Tehran, Iran
b Dryland Agricultural Research Institute, Kermanshah, Iran

* Corresponding author (dehghanr{at}modares.ac.ir).

Selection of lentil (Lens culinaris Medik) cultivars with wide adaptability across diverse farming environments is important, before recommending them to achieve a high rate of cultivar adoption. Seed yield of 11 lentil genotypes, tested in a randomized complete-block design with four replicates across 20 environments in Iran, was analyzed using site regression (SREG) stability model. The biplot technique facilitates a visual evaluation of superior genotypes, which is useful for cultivar recommendation and megaenvironment identification. A substantial amount of genotype x environment (GE) interaction for lentil grain yield was detected. Location (L) and genotype x location (GL) variabilities were the predominant components of total yield variation. The first two principal components (PC1 and PC2) of the SREG model accounted for 76% of the total GE interaction. There were four winning genotypes and three megaenvironments according to the SREG model. The best genotype in one location was not always so in other test locations. According to the ideal-genotype biplot, genotype G5 was better than all other genotypes; G5 exhibited both high mean yield and high stability of performance across environments. According to G + GE sources of variations, the genotypes (G4, G7, G9, and G10) were the most suitable varieties for the lentil-producing regions in Iran.

Abbreviations: ICARDA, International Center for Agricultural Research in Dry Areas • E, environment main effect • G, genotypic main effect • GE, genotype x environment interaction • GGE, G plus GE • MET, multiple-environment trials • SREG, site regression • SVD, singular value decomposition

All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher.

Received for publication October 11, 2006.





HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
The SCI Journals Crop Science Vadose Zone Journal
Journal of Plant Registrations Soil Science Society of America Journal
Journal of Natural Resources
and Life Sciences Education
Journal of
Environmental Quality
Copyright © 2008 by the American Society of Agronomy.