Simulation models and statistical methods to assist in targeting and breeding for drought tolerance (Record no. 3766)

000 -LEADER
fixed length control field 03250nam a22004217a 4500
001 - CONTROL NUMBER
control field 65928
003 - CONTROL NUMBER IDENTIFIER
control field MX-TxCIM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20190319180001.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 121211s ||||f| 0 p|p||0|| |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 968-6923-93-4
040 ## - CATALOGING SOURCE
Original cataloging agency MX-TxCIM
072 #0 - SUBJECT CATEGORY CODE
Subject category code F30
072 #0 - SUBJECT CATEGORY CODE
Subject category code H50
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 633.153
Item number EDM
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Chapman, S.C.
Affiliation Developing Drought- and Low N-Tolerant Maize. Proceedings of a Symposium; El Batan, Mex. (Mexico); 25- 29 Mar 1996
110 2# - MAIN ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Centro Internacional de Mejoramiento de Maiz y Trigo (CIMMYT), Mexico DF (Mexico)
245 00 - TITLE STATEMENT
Title Simulation models and statistical methods to assist in targeting and breeding for drought tolerance
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. Mexico, DF (Mexico)
Name of publisher, distributor, etc. CIMMYT :
Date of publication, distribution, etc. 1997
340 ## - PHYSICAL MEDIUM
Material base and configuration Printed
520 ## - SUMMARY, ETC.
Summary, etc. Simulation models can be used in combination with spatial (geographic information systems) and historical data to determine how different sites and seasons (the target population of environments - TPE) provide different challenges to plant cultivars. Examples for maize in Central America and southern Africa and for sorghum in northern Australia are used to demonstrate aspects of the nature of these three TPEs. Models can be used to simulate the value of different traits over a range of environments from the TPE. For such 'specific-adaptation' cultivars, models might also be used to determine where the cultivars would be best deployed. Further, if models are used to determine the 'types' of abiotic challenges that exist in the TPE, we can ensure that the combination of test environments sampled in the multi environment trials matches the frequency of challenges in the TPE. It is argued that, in smaller, more-targeted multi environment trials, it should be feasible to identify the same superior genotypes that would have been selected in more extensive and costly random testing in the production environment. The paper also illustrates how pattern analysis of multi-environment trials can elucidate different aspects of the interaction of genotypes with dryland environments. For maize, this analysis demonstrates the necessity of testing in both dry and irrigated environments to facilitate drought tolerance gains in a diverse TPE. In the case of sorghum, the same statistical techniques demonstrate differences among locations within a geographically large TPE. These results correlate with independent measures of the environment (simulation model output). The linkage between real data and simulation output allows breeders to weight selection decisions by location and season, depending on how representative the sampled environments are of the real TPE.
546 ## - LANGUAGE NOTE
Language note English
591 ## - CATALOGING NOTES
Affiliation 9802|AGRIS 9702
595 ## - COLLECTION
Collection CIMMYT Publications Collection
650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Breeding methods
9 (RLIN) 1030
650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Drought resistance
650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 1133
Topical term or geographic name as entry element Genotype environment interaction
Miscellaneous information AGROVOC
650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Selection
650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Simulation models
9 (RLIN) 2569
653 0# - INDEX TERM--UNCONTROLLED
Uncontrolled term CIMMYT
650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 1314
Topical term or geographic name as entry element Zea mays
Miscellaneous information AGROVOC
650 10 - SUBJECT ADDED ENTRY--TOPICAL TERM
9 (RLIN) 1203
Topical term or geographic name as entry element Plant breeding
Miscellaneous information AGROVOC
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Barreto, H.J.,
Relator term coaut.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Cooper, M.,
Relator term coaut.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Edmeades, G.O.|Banziger, M.|Mickelson, H.R.|Pena-Valdivia, C.B.
Relator term eds.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Hammer, G.L.,
Relator term coaut.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Conference proceedings
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Permanent Location Current Location Date acquired Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not Lost     CIMMYT Publications Collection CIMMYT Knowledge Center: John Woolston Library CIMMYT Knowledge Center: John Woolston Library 2015-02-10 633.153 EDM 3P624179 2015-02-10 1 2015-02-10 Conference proceedings
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Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT) © Copyright 2015. Carretera México-Veracruz. Km. 45, El Batán, Texcoco, México, C.P. 56237.
Si tiene cualquier pregunta, contáctenos a CIMMYT-Knowledge-Center@cgiar.org