Bayesian network: a simplified approach for environmental similarity studies on maize
| Autor: | Rodolfo Buzinaro, Camila Baptista do Amaral, Gustavo Hugo Ferreira de Oliveira, Kian Eghrari, Gustavo Vitti Môro |
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| Přispěvatelé: | Universidade Estadual Paulista (Unesp) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Bayesian network
Biology Zea mays genotype x environment interaction Similarity (network science) Categorization Statistics Trait General Earth and Planetary Sciences Grain yield Cluster analysis Agronomy and Crop Science Simple correlation prediction method Biotechnology General Environmental Science environmental correlation |
| Zdroj: | Crop Breeding and Applied Biotechnology, Volume: 19, Issue: 1, Pages: 70-76, Published: 11 APR 2019 Crop Breeding and Applied Biotechnology v.19 n.1 2019 Crop Breeding and Applied Biotechnology Sociedade Brasileira de Melhoramento de Plantas instacron:CBAB Web of Science Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP |
| ISSN: | 1984-7033 |
| Popis: | Made available in DSpace on 2019-10-04T12:36:54Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-01. Added 1 bitstream(s) on 2019-10-09T18:34:02Z : No. of bitstreams: 1 S1984-70332019000100070.pdf: 373302 bytes, checksum: 81667f24712ea3cea6d2a986e79afbdb (MD5) The current methodologies used to evaluate environmental similarities do not allow the simultaneous analysis and categorization of the environments. The objective of this study was to verify the possibility of using the Bayesian network (BN) to detect similarities between environments for plant height, lodging, and grain yield in maize. Thirteen experimental varieties were grown in six environments to measure the traits plant height, lodging, and grain yield. The BN was constructed for each trait, using the Hill-Climbing algorithm. Results were compared with the simple part of the genotypes x environments interaction, clustering by the Lin's method and by simple correlation between environments. The Lin's method clustered environments with predominance of complex interaction for all traits. The BN is efficient to analyze environmental similarity for plant height and grain yield since it detected the highest correlations. The BN revealed no connections among the environments that presented predominance of complex interaction. Univ Estadual Paulista, Dept Fitotecnia, BR-14884900 Jaboticabal, SP, Brazil Univ Estadual Paulista, Dept Fitotecnia, BR-14884900 Jaboticabal, SP, Brazil |
| Databáze: | OpenAIRE |
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