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Câmpus de Jaboticabal. EXPLORATORY MULTIVARIATE TECHNIQUES TO DISCRIMINATE LOTS OF SOYBEAN SEEDS. Proc. Fapesp 2006/57900-0 Rafael Marani Barbosa, Juliana Faria dos Santos, Antônio Sérgio Ferraudo, José Eduardo Corá, Roberval Daiton Vieira

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Câmpus de Jaboticabal

EXPLORATORY MULTIVARIATE TECHNIQUES TO DISCRIMINATE LOTS OF SOYBEAN SEEDS.

Proc. Fapesp 2006/57900-0

Rafael Marani Barbosa, Juliana Faria dos Santos, Antônio Sérgio Ferraudo, José Eduardo Corá, Roberval Daiton Vieira

São Paulo State University - UNESP, Via Ac.. Paulo D. Castellane, s/n, 14884-900 Jaboticabal, SP, Brazil

  • Statistics Procedures :

  • Normality (Shapiro-Wilk test )

  • Homoscedasticity of variances (Cochran test)

  • Anova, completely randomized design, Tukey test, (p<0.05).

  • Multivariate techniques :

  • Cluster Analysis : hierarchical method

  • Euclidean Distance: measure of similarity between pairs of lots.

  • Amalgamation (linkage) rule: UPGMA (Unweighted Pair Group Method with Arithmetic Average).

  • Principal Components : to detect variables with high discriminatory degree.All tests were processed by the STATISTICA software version 7.0.

  • RESULTS AND DISCUSSION

  • Figure 1. Dendrogram resulting from hierarchical cluster analysis showing the formation of groups according to the germination, accelerated aging, electrical conductivity, seedling emergence in the field, and water stress germination on potential of 20, 40 and 60%.

INTRODUCTION

Of ownership a high number of lots, the best choice for sowing can not be addressed in remarks to the potential performance evaluated by germination test or only for a test vigor. A more comprehensive analysis can be useful and necessary for the choice of the lot by considerations involving more than one test available for assessing the potential performance of seed lots.

Therefore, multivariate analysis allows to discriminate lots that have characteristics in common and interpret on the use of such lots.

Multivariate analysis has techniques to understand the dependence structure contained in the variables and characterizing groups of samples in specific standards.

OBJECTIVE

The objective of this study was to discriminate soybean seed lots, using variables observed in the physiological potential analysis of the seeds.

MATERIALS AND METHODS

10 lots cv. BRS Valiosa RR

10 lots cv. M-SOY 7908 RR.

Moisture content: 2×25 seeds 105 °C;

Germination: 4×50 seeds paper roll at 25 °C;

Vigor – Acel. Aging: 250 seeds 42 °C por 48 h;

Vigor – Eletrical Condut.: 4 × 50, 75 mL, read after 24 hours of soaking at 25 °C;

Seedling Emergence: 4 × 50 seeds, grooves with 2 m length, spaced at 0.4 m. Reads taken after 14 days

Water stress: 4 × 50 seeds, plastic box (28.5 × 18.5 × 10 cm); Relation air/water in the proportion of 20, 40, 60 and 80% of pores filled with water, based on particle density and total density:

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Table 1.Water content (before and after aging - MC and MCAA), germination (GE), accelerated aging (AA), electrical conductivity (EC), seedling emergence (SE) and water stress germination on potential of 20, 40 and 60%. of 20 lots of soybean seeds.

Tabela 2. Correlation between each component, and evaluation of physiological performance of soybean seeds cv BRS Valiosa RR and M-SOY 7908 RR.

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Figura 2. Dispersion (Biplot graph) the physiological performance of different seed lots of soybean cv. BRS Valuable RR (initial letter 'V') and M-SOY 7908 RR ('M'). GE: germination; EC: electrical conductivity; SE: seedling emergence in the field, AA: accelerated aging; WS40, WS60 WS80: germination under water stress in the potentials of 40, 60 and 80, respectively.

CONCLUSIONS

  • Cluster analysis allowed the stratification of the lots in groups;

  • The principal component analysis showed that the variables SE, AA and WS 40, 60 and 80 are more associated with BRS Valiosa RR while GE and EC are more associated with the cultivar M-SOY 7908.

ACKNOWLEDGEMENTS


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