دورية أكاديمية
Novel Tools for Adjusting Spatial Variability in the Early Sugarcane Breeding Stage.
| العنوان: | Novel Tools for Adjusting Spatial Variability in the Early Sugarcane Breeding Stage. |
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| المؤلفون: | Cursi DE; Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, Brazil.; Sugarcane Breeding Program of RIDESA/UFSCar, Araras, Brazil., Gazaffi R; Sugarcane Breeding Program of RIDESA/UFSCar, Araras, Brazil.; Department of Biotechnology, Vegetal and Animal Production, Federal University of São Carlos, Araras, Brazil., Hoffmann HP; Sugarcane Breeding Program of RIDESA/UFSCar, Araras, Brazil.; Department of Biotechnology, Vegetal and Animal Production, Federal University of São Carlos, Araras, Brazil., Brasco TL; School of Agricultural Engineering, University of Campinas (FEAGRI/UNICAMP), Campinas, Brazil., do Amaral LR; School of Agricultural Engineering, University of Campinas (FEAGRI/UNICAMP), Campinas, Brazil., Dourado Neto D; Luiz de Queiroz College of Agriculture, University of São Paulo (ESALQ/USP), Piracicaba, Brazil. |
| المصدر: | Frontiers in plant science [Front Plant Sci] 2021 Nov 18; Vol. 12, pp. 749533. Date of Electronic Publication: 2021 Nov 18 (Print Publication: 2021). |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101568200 Publication Model: eCollection Cited Medium: Print ISSN: 1664-462X (Print) Linking ISSN: 1664462X NLM ISO Abbreviation: Front Plant Sci Subsets: PubMed not MEDLINE |
| أسماء مطبوعة: | Original Publication: Lausanne : Frontiers Research Foundation, 2010- |
| مستخلص: | The detection of spatial variability in field trials has great potential for accelerating plant breeding progress due to the possibility of better controlling non-genetic variation. Therefore, we aimed to evaluate a digital soil mapping approach and a high-density soil sampling procedure for identifying and adjusting spatial dependence in the early sugarcane breeding stage. Two experiments were conducted in regions with different soil classifications. High-density sampling of soil physical and chemical properties was performed in a regular grid to investigate the structure of spatial variability. Soil apparent electrical conductivity (ECa) was measured in both experimental areas with an EM38-MK2 ® sensor. In addition, principal component analysis (PCA) was employed to reduce the dimensionality of the physical and chemical soil data sets. After conducting the PCA and obtaining different thematic maps, we determined each experimental plot's exact position within the field. Tons of cane per hectare (TCH) data for each experiment were obtained and analyzed using mixed linear models. When environmental covariates were considered, a previous forward model selection step was applied to incorporate the variables. The PCA based on high-density soil sampling data captured part of the total variability in the data for Experimental Area 1 and was suggested to be an efficient index to be incorporated as a covariate in the statistical model, reducing the experimental error (residual variation coefficient, CVe). When incorporated into the different statistical models, the ECa information increased the selection accuracy of the experimental genotypes. Therefore, we demonstrate that the genetic parameter increased when both approaches (spatial analysis and environmental covariates) were employed. Competing Interests: The 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. (Copyright © 2021 Cursi, Gazaffi, Hoffmann, Brasco, do Amaral and Dourado Neto.) |
| References: | Front Plant Sci. 2021 Apr 16;12:651480. (PMID: 33936136) BMC Genomics. 2017 Jan 11;18(1):72. (PMID: 28077090) Theor Appl Genet. 2016 Apr;129(4):653-673. (PMID: 26932121) Trends Plant Sci. 2017 Nov;22(11):961-975. (PMID: 28965742) Funct Plant Biol. 2012 Aug;39(7):609-618. (PMID: 32480813) Theor Appl Genet. 2021 Jan;134(1):95-112. (PMID: 32964262) PLoS One. 2019 Jul 18;14(7):e0219843. (PMID: 31318931) |
| فهرسة مساهمة: | Keywords: Saccharum officinarum L. (Poaceae); envirotyping; geostatistics; proximal sensing; quantitative genetics; spatial variability |
| تواريخ الأحداث: | Date Created: 20211206 Latest Revision: 20211207 |
| رمز التحديث: | 20231215 |
| مُعرف محوري في PubMed: | PMC8638809 |
| DOI: | 10.3389/fpls.2021.749533 |
| PMID: | 34868135 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1664-462X |
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| DOI: | 10.3389/fpls.2021.749533 |