Improving Wheat Production and Breeding Strategies Using Crop Models

Jose Rafael Guarin; Senthold Asseng

doi:10.1007/978-3-030-90673-3_31

Improving Wheat Production and Breeding Strategies Using Crop Models

Jose Rafael Guarin
, Senthold Asseng

Chair of Digital Agriculture

University of Florida
Center for Climate Systems Research

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

5 Scopus citations

Abstract

Crop simulation models are robust tools that enable users to better understand crop growth and development in various agronomic systems for improved decision making regarding agricultural productivity, environmental sustainability, and breeding. Crop models can simulate many agronomic treatments across a wide range of spatial and temporal scales, allowing for improved agricultural management practices, climate change impact assessment, and development of breeding strategies. This chapter examines current applications of wheat crop models and explores the benefits from model improvement and future trends, such as integration of G × E × M and genotype-to-phenotype interactions into modeling processes, to improve wheat (Triticum spp.) production and adaptation strategies for agronomists, breeders, farmers, and policymakers.

Original language	English
Title of host publication	Wheat Improvement
Subtitle of host publication	Food Security in a Changing Climate
Publisher	Springer International Publishing
Pages	573-591
Number of pages	19
ISBN (Electronic)	9783030906733
ISBN (Print)	9783030906726
DOIs	https://doi.org/10.1007/978-3-030-90673-3_31
State	Published - 1 Jan 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 2 Zero Hunger
SDG 8 Decent Work and Economic Growth
SDG 13 Climate Action
SDG 15 Life on Land
SDG 17 Partnerships for the Goals

Keywords

Adaptation strategies
Crop simulation model
Food security
Genetic improvement
Wheat yield

Access to Document

10.1007/978-3-030-90673-3_31

Cite this

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AB - Crop simulation models are robust tools that enable users to better understand crop growth and development in various agronomic systems for improved decision making regarding agricultural productivity, environmental sustainability, and breeding. Crop models can simulate many agronomic treatments across a wide range of spatial and temporal scales, allowing for improved agricultural management practices, climate change impact assessment, and development of breeding strategies. This chapter examines current applications of wheat crop models and explores the benefits from model improvement and future trends, such as integration of G × E × M and genotype-to-phenotype interactions into modeling processes, to improve wheat (Triticum spp.) production and adaptation strategies for agronomists, breeders, farmers, and policymakers.

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KW - Crop simulation model

KW - Food security

KW - Genetic improvement

KW - Wheat yield

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M3 - Chapter

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BT - Wheat Improvement

PB - Springer International Publishing

ER -

Improving Wheat Production and Breeding Strategies Using Crop Models

Abstract

UN SDGs

Keywords

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