Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods
ABSTRACT: The length of the hypocotyl has been highlighted as a potential descriptor of the soybean crop. However, there is no information available in the published literature about its behavior over several planting times. The present study aimed to identify soybean cultivars with stability and p...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidade Federal de Santa Maria
2019-03-01
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| Series: | Ciência Rural |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782019000300201&lng=en&tlng=en |
| _version_ | 1818541375291916288 |
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| author | Guilherme Ferreira Alves João Pedro Garcia Nogueira Ronaldo Machado Junior Silvana da Costa Ferreira Moysés Nascimento Eder Matsuo |
| author_facet | Guilherme Ferreira Alves João Pedro Garcia Nogueira Ronaldo Machado Junior Silvana da Costa Ferreira Moysés Nascimento Eder Matsuo |
| author_sort | Guilherme Ferreira Alves |
| collection | DOAJ |
| description | ABSTRACT: The length of the hypocotyl has been highlighted as a potential descriptor of the soybean crop. However, there is no information available in the published literature about its behavior over several planting times. The present study aimed to identify soybean cultivars with stability and predictability of hypocotyl length behavior through neural networks and traditional adaptability and stability methodologies. We analyzed 16 soybean cultivars in 6 planting seasons under greenhouse conditions. In each season, a randomized block design with 4 replications was adopted. The experimental unit was composed of 3 plants. The plot mean was used in the analysis. Hypocotyl length data were analyzed by analysis of variance and Tukey’s test. Then analyses were carried out using the Traditional Method, Plaisted and Peterson, Wricke, Eberhart and Russell, and Artificial Neural Networks. A significant effect (p<0.01 by the F test) was identified for Cultivars versus Planting Season and Planting Seasons and Cultivars. Cultivars BRS810C, BRSMG760SRR, TMG1175RR, and BMX Tornado RR showed lower averages, high stability, and general adaptability regarding soybean hypocotyl length whereas the cultivar BG4272 presented higher mean, high stability, and general adaptability. Identification of soybean cultivars of predictable and stable behavior as to hypocotyl length contributes to Soybean Improvement as it further our knowledge on the potential descriptor and the possibility of increasing the number of descriptors. |
| first_indexed | 2024-12-11T22:08:28Z |
| format | Article |
| id | doaj.art-85b97d718ffc42868baf2b7eefafc801 |
| institution | Directory Open Access Journal |
| issn | 1678-4596 |
| language | English |
| last_indexed | 2024-12-11T22:08:28Z |
| publishDate | 2019-03-01 |
| publisher | Universidade Federal de Santa Maria |
| record_format | Article |
| series | Ciência Rural |
| spelling | doaj.art-85b97d718ffc42868baf2b7eefafc8012022-12-22T00:48:53ZengUniversidade Federal de Santa MariaCiência Rural1678-45962019-03-0149310.1590/0103-8478cr20180300S0103-84782019000300201Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methodsGuilherme Ferreira AlvesJoão Pedro Garcia NogueiraRonaldo Machado JuniorSilvana da Costa FerreiraMoysés NascimentoEder MatsuoABSTRACT: The length of the hypocotyl has been highlighted as a potential descriptor of the soybean crop. However, there is no information available in the published literature about its behavior over several planting times. The present study aimed to identify soybean cultivars with stability and predictability of hypocotyl length behavior through neural networks and traditional adaptability and stability methodologies. We analyzed 16 soybean cultivars in 6 planting seasons under greenhouse conditions. In each season, a randomized block design with 4 replications was adopted. The experimental unit was composed of 3 plants. The plot mean was used in the analysis. Hypocotyl length data were analyzed by analysis of variance and Tukey’s test. Then analyses were carried out using the Traditional Method, Plaisted and Peterson, Wricke, Eberhart and Russell, and Artificial Neural Networks. A significant effect (p<0.01 by the F test) was identified for Cultivars versus Planting Season and Planting Seasons and Cultivars. Cultivars BRS810C, BRSMG760SRR, TMG1175RR, and BMX Tornado RR showed lower averages, high stability, and general adaptability regarding soybean hypocotyl length whereas the cultivar BG4272 presented higher mean, high stability, and general adaptability. Identification of soybean cultivars of predictable and stable behavior as to hypocotyl length contributes to Soybean Improvement as it further our knowledge on the potential descriptor and the possibility of increasing the number of descriptors.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782019000300201&lng=en&tlng=enGlycine max, interação genótipos x ambientes, Eberhart e Russell, inteligência artificialcomprimento de hipocótilo |
| spellingShingle | Guilherme Ferreira Alves João Pedro Garcia Nogueira Ronaldo Machado Junior Silvana da Costa Ferreira Moysés Nascimento Eder Matsuo Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods Ciência Rural Glycine max, interação genótipos x ambientes, Eberhart e Russell, inteligência artificial comprimento de hipocótilo |
| title | Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods |
| title_full | Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods |
| title_fullStr | Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods |
| title_full_unstemmed | Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods |
| title_short | Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods |
| title_sort | stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods |
| topic | Glycine max, interação genótipos x ambientes, Eberhart e Russell, inteligência artificial comprimento de hipocótilo |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782019000300201&lng=en&tlng=en |
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