A high-yielding traits experiment for modeling potential production of wheat: field experiments and AgMIP-Wheat multi-model simulations
Jose Guarin
(1, 2)
,
Pierre Martre
(3)
,
Frank Ewert
(4, 5)
,
Heidi Webber
(4, 6)
,
Sibylle Dueri
(3)
,
Daniel Calderini
(7)
,
Matthew Reynolds
(8)
,
Gemma Molero
(9)
,
Daniel Miralles
(10)
,
Guillermo Garcia
(10)
,
Gustavo Slafer
(11, 12)
,
Francesco Giunta
(13)
,
Diego Pequeno
(8)
,
Tommaso Stella
(4, 5)
,
Mukhtar Ahmed
(14, 15)
,
Phillip Alderman
(16)
,
Bruno Basso
(17)
,
Andres Berger
(18)
,
Marco Bindi
(19)
,
Gennady Bracho-Mujica
(20)
,
Davide Cammarano
(21)
,
Yi Chen
(22)
,
Benjamin Dumont
(23)
,
Ehsan Eyshi Rezaei
(4)
,
Elias Fereres
(24, 25)
,
Roberto Ferrise
(19)
,
Thomas Gaiser
(5)
,
Yujing Gao
(1)
,
Margarita Garcia-Vila
(24, 25)
,
Sebastian Gayler
(26)
,
Zvi Hochman
(27)
,
Gerrit Hoogenboom
(1)
,
Leslie Hunt
(28)
,
Kurt Kersebaum
(4, 20, 29)
,
Claas Nendel
(4, 29, 30)
,
Jorgen Olesen
(21)
,
Taru Palosuo
(31)
,
Eckart Priesack
(32)
,
Johannes Pullens
(21)
,
Alfredo Rodriguez
(33)
,
Reimund Rotter
(20, 34)
,
Margarita Ruiz Ramos
(35)
,
Mikhail Semenov
(36)
,
Nimai Senapati
(36)
,
Stefan Siebert
(20)
,
Amit Srivastava
(5)
,
Claudio Stockle
(37)
,
Iwan Supit
(38)
,
Fulu Tao
(22, 31)
,
Peter Thorburn
(27)
,
Enli Wang
(27)
,
Tobias Weber
(39, 24)
,
Liujun Xiao
(40, 41)
,
Zhao Zhang
(42)
,
Chuang Zhao
(43)
,
Jin Zhao
(43, 21)
,
Zhigan Zhao
(27)
,
Yan Zhu
(41)
,
Senthold Asseng
(44)
1
UF -
University of Florida [Gainesville]
2 CCSR - Center for Climate Systems Research [New York]
3 LEPSE - Écophysiologie des Plantes sous Stress environnementaux
4 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research
5 INRES - Institut für Nutzpflanzenwissenschaften und Ressourcenschutz
6 BTU - Brandenburgische Technische Universität = Brandenburg Technical University
7 Universidad Austral de Chile
8 CIMMYT - International Maize and Wheat Improvement Center
9 KWS Momont SAS
10 Universitad de Buenos Aires = University of Buenos Aires [Argentina]
11 Universitat de Lleida
12 ICREA - Institució Catalana de Recerca i Estudis Avançats = Catalan Institution for Research and Advanced Studies
13 UNISS - Università degli Studi di Sassari = University of Sassari [Sassari]
14 AAUR - Pir Mehr Ali Shah Arid Agriculture University = PMAS-Arid Agriculture University Rawalpindi
15 SLU - Swedish University of Agricultural Sciences = Sveriges lantbruksuniversitet
16 OSU - Oklahoma State University [Stillwater]
17 Michigan State University [East Lansing]
18 INIA - Instituto Nacional de Investigación Agropecuaria
19 DAGRI - Department of Agriculture, Food, Environment and Forestry
20 Georg-August-University = Georg-August-Universität Göttingen
21 Aarhus University [Aarhus]
22 IGSNRR - Institute of geographical sciences and natural resources research [CAS]
23 [FUSAGx] - Gembloux Agro-Bio Tech [Faculté universitaire des sciences agronomiques de Gembloux]
24 Universidad de Córdoba = University of Córdoba [Córdoba]
25 CSIC - Consejo Superior de Investigaciones Cientificas [España] = Spanish National Research Council [Spain]
26 Universität Hohenheim = University of Hohenheim
27 CSIRO AF - CSIRO Agriculture and Food
28 University of Guelph
29 CAS - Czech Academy of Sciences [Prague]
30 University of Potsdam = Universität Potsdam
31 LUKE - Natural Resources Institute Finland
32 HMGU - Helmholtz Zentrum München = German Research Center for Environmental Health
33 UCLM - Universidad de Castilla-La Mancha = University of Castilla-La Mancha
34 CBL - Centre for Biodiversity and Sustainable Land-use [University of Göttingen]
35 UPM - Universidad Politécnica de Madrid
36 Rothamsted Research
37 WSU - Washington State University
38 WUR - Wageningen University and Research [Wageningen]
39 University of Kassel
40 Zhejiang University [Hangzhou, China]
41 NAU - Nanjing Agricultural University
42 BNU - Beijing Normal University
43 CAU - China Agricultural University
44 TUM - Technische Universität Munchen - Technical University Munich - Université Technique de Munich
2 CCSR - Center for Climate Systems Research [New York]
3 LEPSE - Écophysiologie des Plantes sous Stress environnementaux
4 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research
5 INRES - Institut für Nutzpflanzenwissenschaften und Ressourcenschutz
6 BTU - Brandenburgische Technische Universität = Brandenburg Technical University
7 Universidad Austral de Chile
8 CIMMYT - International Maize and Wheat Improvement Center
9 KWS Momont SAS
10 Universitad de Buenos Aires = University of Buenos Aires [Argentina]
11 Universitat de Lleida
12 ICREA - Institució Catalana de Recerca i Estudis Avançats = Catalan Institution for Research and Advanced Studies
13 UNISS - Università degli Studi di Sassari = University of Sassari [Sassari]
14 AAUR - Pir Mehr Ali Shah Arid Agriculture University = PMAS-Arid Agriculture University Rawalpindi
15 SLU - Swedish University of Agricultural Sciences = Sveriges lantbruksuniversitet
16 OSU - Oklahoma State University [Stillwater]
17 Michigan State University [East Lansing]
18 INIA - Instituto Nacional de Investigación Agropecuaria
19 DAGRI - Department of Agriculture, Food, Environment and Forestry
20 Georg-August-University = Georg-August-Universität Göttingen
21 Aarhus University [Aarhus]
22 IGSNRR - Institute of geographical sciences and natural resources research [CAS]
23 [FUSAGx] - Gembloux Agro-Bio Tech [Faculté universitaire des sciences agronomiques de Gembloux]
24 Universidad de Córdoba = University of Córdoba [Córdoba]
25 CSIC - Consejo Superior de Investigaciones Cientificas [España] = Spanish National Research Council [Spain]
26 Universität Hohenheim = University of Hohenheim
27 CSIRO AF - CSIRO Agriculture and Food
28 University of Guelph
29 CAS - Czech Academy of Sciences [Prague]
30 University of Potsdam = Universität Potsdam
31 LUKE - Natural Resources Institute Finland
32 HMGU - Helmholtz Zentrum München = German Research Center for Environmental Health
33 UCLM - Universidad de Castilla-La Mancha = University of Castilla-La Mancha
34 CBL - Centre for Biodiversity and Sustainable Land-use [University of Göttingen]
35 UPM - Universidad Politécnica de Madrid
36 Rothamsted Research
37 WSU - Washington State University
38 WUR - Wageningen University and Research [Wageningen]
39 University of Kassel
40 Zhejiang University [Hangzhou, China]
41 NAU - Nanjing Agricultural University
42 BNU - Beijing Normal University
43 CAU - China Agricultural University
44 TUM - Technische Universität Munchen - Technical University Munich - Université Technique de Munich
Jose Guarin
- Fonction : Auteur
- PersonId : 1154515
- ORCID : 0000-0002-3167-4329
Pierre Martre
- Fonction : Auteur
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- IdHAL : pierre-martre
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- IdRef : 163589194
Frank Ewert
- Fonction : Auteur
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- ORCID : 0000-0002-4392-8154
Sibylle Dueri
- Fonction : Auteur
- PersonId : 1179328
- ORCID : 0000-0001-9005-6136
Guillermo Garcia
- Fonction : Auteur
- PersonId : 1277711
- ORCID : 0000-0001-7690-4100
Gustavo Slafer
- Fonction : Auteur
- PersonId : 1247954
- ORCID : 0000-0002-1766-4247
Francesco Giunta
- Fonction : Auteur
- PersonId : 1277712
- ORCID : 0000-0002-7866-8372
Phillip Alderman
- Fonction : Auteur
- PersonId : 1277713
- ORCID : 0000-0003-1467-2337
Gennady Bracho-Mujica
- Fonction : Auteur
- PersonId : 1154517
- ORCID : 0000-0002-6988-6781
Benjamin Dumont
- Fonction : Auteur
- PersonId : 1163463
- ORCID : 0000-0001-8411-3990
Roberto Ferrise
- Fonction : Auteur
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- ORCID : 0000-0001-8236-7823
Thomas Gaiser
- Fonction : Auteur
- PersonId : 1215367
- ORCID : 0000-0002-5820-2364
Yujing Gao
- Fonction : Auteur
- PersonId : 1277714
- ORCID : 0000-0001-5334-8500
Sebastian Gayler
- Fonction : Auteur
- PersonId : 1217290
- ORCID : 0000-0002-8577-6486
Gerrit Hoogenboom
- Fonction : Auteur
- PersonId : 784208
- ORCID : 0000-0002-1555-0537
Johannes Pullens
- Fonction : Auteur
- PersonId : 1154525
- ORCID : 0000-0003-4581-6444
Alfredo Rodriguez
- Fonction : Auteur
- PersonId : 1277715
- ORCID : 0000-0001-7987-1623
Reimund Rotter
- Fonction : Auteur
- PersonId : 1154526
- ORCID : 0000-0002-3804-9964
Margarita Ruiz Ramos
- Fonction : Auteur
- PersonId : 1277716
- ORCID : 0000-0003-0212-3381
Stefan Siebert
- Fonction : Auteur
- PersonId : 1159367
- ORCID : 0000-0002-9998-0672
Amit Srivastava
- Fonction : Auteur
- PersonId : 1277717
- ORCID : 0000-0001-8219-4854
Iwan Supit
- Fonction : Auteur
- PersonId : 1277718
- ORCID : 0000-0002-8031-5162
Fulu Tao
- Fonction : Auteur
- PersonId : 1277719
- ORCID : 0000-0001-8574-0080
Peter Thorburn
- Fonction : Auteur
- PersonId : 1215366
- ORCID : 0000-0002-6506-0456
Tobias Weber
- Fonction : Auteur
- PersonId : 1154528
- ORCID : 0000-0002-3448-5208
Zhigan Zhao
- Fonction : Auteur
- PersonId : 1154529
- ORCID : 0000-0003-1533-7215
Senthold Asseng
- Fonction : Auteur
- PersonId : 1154513
- ORCID : 0000-0002-7583-3811
Résumé
Grain production must increase by 60% in the next four decades to keep up with the expected population growth and food demand. A significant part of this increase must come from the improvement of staple crop grain yield potential. Crop growth simulation models combined with field experiments and crop physiology are powerful tools to quantify the impact of traits and trait combinations on grain yield potential which helps to guide breeding towards the most effective traits and trait combinations for future wheat crosses. The dataset reported here was created to analyze the value of physiological traits identified by the International Wheat Yield Partnership (IWYP) to improve wheat potential in high-yielding environments. This dataset consists of 11 growing seasons at three high-yielding locations in Buenos Aires (Argentina), Ciudad Obregon (Mexico), and Valdivia (Chile) with the spring wheat cultivar Bacanora and a high-yielding genotype selected from a doubled haploid (DH) population developed from the cross between the Bacanora and Weebil cultivars from the International Maize and Wheat Improvement Center (CIMMYT). This dataset was used in the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Phase 4 to evaluate crop model performance when simulating high-yielding physiological traits and to determine the potential production of wheat using an ensemble of 29 wheat crop models. The field trials were managed for non-stress conditions with full irrigation, fertilizer application, and without biotic stress. Data include local daily weather, soil characteristics and initial soil conditions, cultivar information, and crop measurements (anthesis and maturity dates, total above-ground biomass, final grain yield, yield components, and photosynthetically active radiation interception). Simulations include both daily in-season and end-of-season results for 25 crop variables simulated by 29 wheat crop models.
