Winter Wheat Experiments to Optimize Sowing Dates and Densities in a High-Yielding Environment in New Zealand: Field Experiments and AgMIP-Wheat Multi-Model Simulations

This paper describes the data set that was used to test the accuracy of twenty-nine crop models in simulating the effect of changing sowing dates and sowing densities on wheat productivity for a high-yielding environment in New Zealand. The data includes one winter wheat cultivar (Wakanui) grown during six consecutive years, from 2012-2013 to 2017-2018, at two farms located in Leeston and Wakanui in Canterbury, New Zealand. The simulations were carried out in the framework of the Agricultural Model Intercomparison and Improvement Project for wheat (AgMIP-Wheat). Data include local daily weather data, soil profile characteristics and initial conditions, crop measurements at maturity (grain, stem, chaff and leaf dry weight, ear number and grain number, grain unit dry weight), and at stem elongation and anthesis (total above ground dry biomass, leaf number per stem and leaf area index). Several in-season measurements of the normalized difference vegetation index (NDVI) and the fraction of intercepted photosynthetically active radiation (FIPAR) are also available. The crop model simulations include both daily in-season and end-of-season results from twenty-nine wheat models.

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Publication Details

Journal
Open Data Journal for Agricultural Research
Published
2024-09-20
DOI
https://doi.org/10.18174/odjar.v10i0.18442
Primary Topic
Crop Yield and Soil Fertility
Type
article
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article

Winter Wheat Experiments to Optimize Sowing Dates and Densities in a High-Yielding Environment in New Zealand: Field Experiments and AgMIP-Wheat Multi-Model Simulations

Zvi Hochman, Alfredo Rodríguez, Reimund P. Rötter, Taru Palosuo et al.
Open Data Journal for Agricultural Research
Crop Yield and Soil Fertility
article

Winter Wheat Experiments to Optimize Sowing Dates and Densities in a High-Yielding Environment in New Zealand: Field Experiments and AgMIP-Wheat Multi-Model Simulations

Zvi Hochman, Alfredo Rodríguez, Reimund P. Rötter, Taru Palosuo, Jin Zhao, Rob Craigie, Fulu Tao, Sibylle Dueri, Tobias K. D. Weber, Nimai Senapati, Jørgen Eivind Olesen, Claas Nendel, Senthold Asseng, Sebastian Gayler, Yujing Gao, Heidi Webber, Iwan Supit, Stefan Siebert, Enli Wang, Margarita García‐Vila, Pierre Martre, Roberto Ferrise, Gerrit Hoogenboom, Kurt Christian Kersebaum, Chuang Zhao, Andrés Berger, Hamish Brown, Diego Noleto Luz Pequeno, Gennady Bracho‐Mujica, Benjamin Dumont, Margarita Ruiz‐Ramos, Mukhtar Ahmed, Johannes Wilhelmus Maria Pullens, Thomas Gaiser, Frank Ewert, Gloria Padovan, Liujun Xiao, Bruno Basso, Eckart Priesack, Amit K. Srivastava, Jose Rafael Guarin, Davide Cammarano, Phillip D. Alderman, Tommaso Stella, Peter J. Thorburn, Mikhail A. Semenov, Zhigan Zhao, Yi Chen, Yan Zhu, Ehsan Eyshi Rezaei, Mike George, Claudio Stöckle, Elías Fereres
article en

Abstract

This paper describes the data set that was used to test the accuracy of twenty-nine crop models in simulating the effect of changing sowing dates and sowing densities on wheat productivity for a high-yielding environment in New Zealand. The data includes one winter wheat cultivar (Wakanui) grown during six consecutive years, from 2012-2013 to 2017-2018, at two farms located in Leeston and Wakanui in Canterbury, New Zealand. The simulations were carried out in the framework of the Agricultural Model Intercomparison and Improvement Project for wheat (AgMIP-Wheat). Data include local daily weather data, soil profile characteristics and initial conditions, crop measurements at maturity (grain, stem, chaff and leaf dry weight, ear number and grain number, grain unit dry weight), and at stem elongation and anthesis (total above ground dry biomass, leaf number per stem and leaf area index). Several in-season measurements of the normalized difference vegetation index (NDVI) and the fraction of intercepted photosynthetically active radiation (FIPAR) are also available. The crop model simulations include both daily in-season and end-of-season results from twenty-nine wheat models.

Open Data Journal for Agricultural ResearchVol. 10
University of Hohenheim (DE), Nanjing Agricultural University (CN), Commonwealth Scientific and Industrial Research Organisation (AU), Plant & Food Research (NZ), University of Bonn (DE), University of Liège (BE), Lee University (US), National Agricultural Research Institute (PG), Pir Mehr Ali Shah Arid Agriculture University (PK), Aarhus University (DK), Centro Internacional de Mejoramiento de Maíz Y Trigo (MX), Rothamsted Research (GB), Natural Resources Institute Finland (FI), University of Florida (US), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Leibniz Centre for Agricultural Landscape Research (DE), Foundation for Arable Research (NZ), Oklahoma State University Oklahoma City (US), Agriculture and Food (AU), University of Florence (IT), China Agricultural University (CN), Technical University of Munich (DE), Cordoba University (US), Washington State University (US), University of Göttingen (DE), Zhejiang University (CN), Michigan State University (US), Universidad Politécnica de Madrid (ES), Wageningen University & Research (NL)
Openalex Percentile: Top 77%
Crop Yield and Soil Fertility
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