Stability of the hypocotyl length of soybean cultivars using neural networks and traditional methods

Guilherme Ferreira Alves,Moysés Nascimento,João Pedro Garcia Nogueira,Silvana Da Costa Ferreira,Ronaldo Machado Junior,Eder Matsuo

doi:10.1590/0103-8478cr20180300

Guilherme Ferreira Alves, Moysés Nascimento + Show 4 more

Open Access

https://doi.org/10.1590/0103-8478cr20180300

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Journal: Ciência Rural	Publication Date: Jan 1, 2019
Citations: 7	License type: CC BY 4.0

Affiliation: Universidade Federal de Viçosa

Abstract

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.

Highlights

From 1997 onwards, soybean cultivars (Glycine max (L.) Merr.) were protected under the Law of Protection of Cultivars (LPC), Law n. 9,456 of April 25, 1997 (BRASIL, 1997a) regulated by Decree no. 2,366, published on November 5, 1997 (BRASIL, 1997b)
Characteristics including a potential descriptor for the soybean crop
As the effect of the interaction was significant, there is a possibility that the best genotype in one environment may not be as good in another genotype (CRUZ et al, 2012). This demonstrated that a cultivar can present different hypocotyl lengths according to the planting environment evaluated

Summary

INTRODUCTION

From 1997 onwards, soybean cultivars (Glycine max (L.) Merr.) were protected under the Law of Protection of Cultivars (LPC), Law n. 9,456 of April 25, 1997 (BRASIL, 1997a) regulated by Decree no. 2,366, published on November 5, 1997 (BRASIL, 1997b). Studies on genotype-environment interaction are of great importance for the genetic improvement of cultivars and development of crops, these studies do not provide detailed information about the behavior of each genotype against environmental variations (CRUZ et al, 2012). To that end, these authors recommend adaptability and stability analyses through which individuals are able to identify cultivars of predictable behavior that are responsive to environmental variations under specific or broad conditions. In view of the above-mentioned, our goal in this study was to identify soybean cultivars with stability and predictability of behavior regarding hypocotyl length through neural networks and traditional methodologies of adaptability and stability

MATERIALS AND METHODS

RESULTS AND DISCUSSION

CONCLUSION