Application of Crop Growth Models to Assist Breeding for Intercropping: Opportunities and Challenges.

APSIM STICS biodiversity complementary resource use mixed cropping plant breeding process-based models

Journal

Frontiers in plant science
ISSN: 1664-462X
Titre abrégé: Front Plant Sci
Pays: Switzerland
ID NLM: 101568200

Informations de publication

Date de publication:
2022
Historique:
received: 04 06 2021
accepted: 17 01 2022
entrez: 21 2 2022
pubmed: 22 2 2022
medline: 22 2 2022
Statut: epublish

Résumé

Intercropping of two or more species on the same piece of land can enhance biodiversity and resource use efficiency in agriculture. Traditionally, intercropping systems have been developed and improved by empirical methods within a specific local context. To support the development of promising intercropping systems, the individual species that are part of an intercrop can be subjected to breeding. Breeding for intercropping aims at resource foraging traits of the admixed species to maximize niche complementarity, niche facilitation, and intercrop performance. The breeding process can be facilitated by modeling tools that simulate the outcome of the combination of different species' (or genotypes') traits for growth and yield development, reducing the need of extensive field testing. Here, we revisit the challenges associated with breeding for intercropping, and give an outlook on applying crop growth models to assist breeding for intercropping. We conclude that crop growth models can assist breeding for intercropping, provided that (i) they incorporate the relevant plant features and mechanisms driving interspecific plant-plant interactions; (ii) they are based on model parameters that are closely linked to the traits that breeders would select for; and (iii) model calibration and validation is done with field data measured in intercrops. Minimalist crop growth models are more likely to incorporate the above elements than comprehensive but parameter-intensive crop growth models. Their lower complexity and reduced parameter requirement facilitate the exploration of mechanisms at play and fulfil the model requirements for calibration of the appropriate crop growth models.

Identifiants

pubmed: 35185972
doi: 10.3389/fpls.2022.720486
pmc: PMC8854142
doi:

Types de publication

Journal Article

Langues

eng

Pagination

720486

Informations de copyright

Copyright © 2022 Weih, Adam, Vico and Rubiales.

Déclaration de conflit d'intérêts

EA is employed by Saatzucht Gleisdorf GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Martin Weih (M)

Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden.

Eveline Adam (E)

Saatzucht Gleisdorf GmbH, Gleisdorf, Austria.

Giulia Vico (G)

Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden.

Diego Rubiales (D)

Institute for Sustainable Agriculture, Consejo Superior de Investigaciones Científicas (CSIC), Córdoba, Spain.

Classifications MeSH