مورد إلكتروني
Combining Crop Growth Modeling and Statistical Genetic Modeling to Evaluate Phenotyping Strategies
العنوان: | Combining Crop Growth Modeling and Statistical Genetic Modeling to Evaluate Phenotyping Strategies |
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المصدر: | ISSN: 1664-462X |
بيانات النشر: | 2019 |
تفاصيل مُضافة: | Bustos-Korts, Daniela Boer, Martin P. Malosetti, Marcos Chapman, Scott Chenu, Karine Zheng, Bangyou Eeuwijk, Fred A., van |
نوع الوثيقة: | Electronic Resource |
مستخلص: | Genomic prediction of complex traits, say yield, benefits from including information on correlated component traits. Statistical criteria to decide which yield components to consider in the prediction model include the heritability of the component traits and their genetic correlation with yield. Not all component traits are easy to measure. Therefore, it may be attractive to include proxies to yield components, where these proxies are measured in (high-throughput) phenotyping platforms during the growing season. Using the Agricultural Production Systems Simulator (APSIM)-wheat cropping systems model, we simulated phenotypes for a wheat diversity panel segregating for a set of physiological parameters regulating phenology, biomass partitioning, and the ability to capture environmental resources. The distribution of the additive quantitative trait locus effects regulating the APSIM physiological parameters approximated the same distribution of quantitative trait locus effects on real phenotypic data for yield and heading date. We use the crop growth model APSIM-wheat to simulate phenotypes in three Australian environments with contrasting water deficit patterns. The APSIM output contained the dynamics of biomass and canopy cover, plus yield at the end of the growing season. Each water deficit pattern triggered different adaptive mechanisms and the impact of component traits differed between drought scenarios. We evaluated multiple phenotyping schedules by adding plot and measurement error to the dynamics of biomass and canopy cover. We used these trait dynamics to fit parametric models and P-splines to extract parameters with a larger heritability than the phenotypes at individual time points. We used those parameters in multi-trait prediction models for final yield. The combined use of crop growth models and multi-trait genomic prediction models provides a procedure to assess the efficiency of phenotyping strategies and compare methods to model trait dynamics. It |
مصطلحات الفهرس: | APSIM model, crop growth model, dynamic traits, genomic prediction, genotype to phenotype, P-spline, trait hierarchy, wheat, Article/Letter to editor |
URL: | |
الإتاحة: | Open access content. Open access content Wageningen University & Research |
ملاحظة: | application/pdf Frontiers in Plant Science 10 (2019) ISSN: 1664-462X ISSN: 1664-462X English |
أرقام أخرى: | NLWUP oai:library.wur.nl:wurpubs/558620 https://library.wur.nl/WebQuery/wurpubs/558620Test 10.3389/fpls.2019.01491 1200318742 |
المصدر المساهم: | WUR STAFF PUBNS From OAIster®, provided by the OCLC Cooperative. |
رقم الانضمام: | edsoai.on1200318742 |
قاعدة البيانات: | OAIster |
الوصف غير متاح. |