Designing crop technology for a future climate

An example using response surface methodology and the CERES-Wheat model

P. Dhungana, Kent M Eskridge, A. Weiss, P. S. Baenziger

Research output: Contribution to journalArticle

41 Citations (Scopus)

Abstract

Future crop production will be adapted to climate change by implementing alternative management practices and developing new genotypes that are adapted to future climatic conditions. It is difficult to predict what new agronomic technologies will be necessary for crop production under future climatic conditions. The purpose of this work was to develop an approach useful in identifying crop technologies for future climatic conditions. As an example of the approach, we used response surface methodology (RSM) in connection with the CERES-Wheat model and the HADCM2 climate simulation model to identify optimal configurations of plant traits and management practices that maximize yield of winter wheat in high CO2 environments. The simulations were conducted for three Nebraska locations differing in altitude and rainfall (Lincoln, Dickens and Alliance), which were considered representative of winter wheat growing areas in the central Great Plains. At all locations, the identified optimal winter wheat cultivar under high CO2 conditions had a larger number of tillers, larger kernel size, fewer days to flower, grew faster and had more kernels m-2 than the check cultivar under normal CO2 conditions. In addition, optimal sowing dates were later and optimal plant densities were smaller than under normal conditions. We concluded that RSM used in conjunction with crop and climate simulation models was useful in understanding the complex relationship between wheat genotypes, climate and management practices.

Original languageEnglish (US)
Pages (from-to)63-79
Number of pages17
JournalAgricultural Systems
Volume87
Issue number1
DOIs
StatePublished - Jan 1 2006

Fingerprint

response surface methodology
winter wheat
climate models
climate
wheat
crop production
simulation models
crops
genotype
cultivars
sowing date
seeds
tillers
plant density
climate change
rain
flowers

Keywords

  • CERES-Wheat model
  • Climate change
  • High CO conditions
  • Method of steepest ascent
  • Optimization

ASJC Scopus subject areas

  • Animal Science and Zoology
  • Agronomy and Crop Science

Cite this

Designing crop technology for a future climate : An example using response surface methodology and the CERES-Wheat model. / Dhungana, P.; Eskridge, Kent M; Weiss, A.; Baenziger, P. S.

In: Agricultural Systems, Vol. 87, No. 1, 01.01.2006, p. 63-79.

Research output: Contribution to journalArticle

@article{9c5d8cdb65404d5cafca5380d89669c2,
title = "Designing crop technology for a future climate: An example using response surface methodology and the CERES-Wheat model",
abstract = "Future crop production will be adapted to climate change by implementing alternative management practices and developing new genotypes that are adapted to future climatic conditions. It is difficult to predict what new agronomic technologies will be necessary for crop production under future climatic conditions. The purpose of this work was to develop an approach useful in identifying crop technologies for future climatic conditions. As an example of the approach, we used response surface methodology (RSM) in connection with the CERES-Wheat model and the HADCM2 climate simulation model to identify optimal configurations of plant traits and management practices that maximize yield of winter wheat in high CO2 environments. The simulations were conducted for three Nebraska locations differing in altitude and rainfall (Lincoln, Dickens and Alliance), which were considered representative of winter wheat growing areas in the central Great Plains. At all locations, the identified optimal winter wheat cultivar under high CO2 conditions had a larger number of tillers, larger kernel size, fewer days to flower, grew faster and had more kernels m-2 than the check cultivar under normal CO2 conditions. In addition, optimal sowing dates were later and optimal plant densities were smaller than under normal conditions. We concluded that RSM used in conjunction with crop and climate simulation models was useful in understanding the complex relationship between wheat genotypes, climate and management practices.",
keywords = "CERES-Wheat model, Climate change, High CO conditions, Method of steepest ascent, Optimization",
author = "P. Dhungana and Eskridge, {Kent M} and A. Weiss and Baenziger, {P. S.}",
year = "2006",
month = "1",
day = "1",
doi = "10.1016/j.agsy.2004.11.004",
language = "English (US)",
volume = "87",
pages = "63--79",
journal = "Agricultural Systems",
issn = "0308-521X",
publisher = "Elsevier BV",
number = "1",

}

TY - JOUR

T1 - Designing crop technology for a future climate

T2 - An example using response surface methodology and the CERES-Wheat model

AU - Dhungana, P.

AU - Eskridge, Kent M

AU - Weiss, A.

AU - Baenziger, P. S.

PY - 2006/1/1

Y1 - 2006/1/1

N2 - Future crop production will be adapted to climate change by implementing alternative management practices and developing new genotypes that are adapted to future climatic conditions. It is difficult to predict what new agronomic technologies will be necessary for crop production under future climatic conditions. The purpose of this work was to develop an approach useful in identifying crop technologies for future climatic conditions. As an example of the approach, we used response surface methodology (RSM) in connection with the CERES-Wheat model and the HADCM2 climate simulation model to identify optimal configurations of plant traits and management practices that maximize yield of winter wheat in high CO2 environments. The simulations were conducted for three Nebraska locations differing in altitude and rainfall (Lincoln, Dickens and Alliance), which were considered representative of winter wheat growing areas in the central Great Plains. At all locations, the identified optimal winter wheat cultivar under high CO2 conditions had a larger number of tillers, larger kernel size, fewer days to flower, grew faster and had more kernels m-2 than the check cultivar under normal CO2 conditions. In addition, optimal sowing dates were later and optimal plant densities were smaller than under normal conditions. We concluded that RSM used in conjunction with crop and climate simulation models was useful in understanding the complex relationship between wheat genotypes, climate and management practices.

AB - Future crop production will be adapted to climate change by implementing alternative management practices and developing new genotypes that are adapted to future climatic conditions. It is difficult to predict what new agronomic technologies will be necessary for crop production under future climatic conditions. The purpose of this work was to develop an approach useful in identifying crop technologies for future climatic conditions. As an example of the approach, we used response surface methodology (RSM) in connection with the CERES-Wheat model and the HADCM2 climate simulation model to identify optimal configurations of plant traits and management practices that maximize yield of winter wheat in high CO2 environments. The simulations were conducted for three Nebraska locations differing in altitude and rainfall (Lincoln, Dickens and Alliance), which were considered representative of winter wheat growing areas in the central Great Plains. At all locations, the identified optimal winter wheat cultivar under high CO2 conditions had a larger number of tillers, larger kernel size, fewer days to flower, grew faster and had more kernels m-2 than the check cultivar under normal CO2 conditions. In addition, optimal sowing dates were later and optimal plant densities were smaller than under normal conditions. We concluded that RSM used in conjunction with crop and climate simulation models was useful in understanding the complex relationship between wheat genotypes, climate and management practices.

KW - CERES-Wheat model

KW - Climate change

KW - High CO conditions

KW - Method of steepest ascent

KW - Optimization

UR - http://www.scopus.com/inward/record.url?scp=27644570973&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=27644570973&partnerID=8YFLogxK

U2 - 10.1016/j.agsy.2004.11.004

DO - 10.1016/j.agsy.2004.11.004

M3 - Article

VL - 87

SP - 63

EP - 79

JO - Agricultural Systems

JF - Agricultural Systems

SN - 0308-521X

IS - 1

ER -