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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.

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Presentation on theme: "Table 1. Water content (before and after aging - MC and MCAA), germination (GE), accelerated aging (AA), electrical conductivity (EC), seedling emergence."— Presentation transcript:

1 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.. 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:. 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 Câmpus de Jaboticabal EXPLORATORY MULTIVARIATE TECHNIQUES TO DISCRIMINATE LOTS OF SOYBEAN SEEDS. ACKNOWLEDGEMENTS LotsMCMCAAGEAAECSEWS40WS60WS80 ------------------- % ----------------- µS.cm -1.g -1 ------------------- % ----------------- BRS Valiosa RR L1 12.3 28.6 95 a*85 a68 a86 a90 aA 87abA69 aB L2 12.2 29.494 a88 a70 a86 a91 aA 88abA63 abcB L3 12.6 28.094 a87 a70 a83 a93 aA84 bB61 abcC L4 12.3 28.890 a82 a68 a89 a89 aA94 aA63 abcB L5 12.0 28.692 a90 a70 a87 a87 aA 87abA65 abB L6 12.2 28.893 a91 a66 a84 a88 aA94 aA57 bcdB L7 12.1 28.794 a81 a67 a86 a90 aA96 aA58 bcdB L8 11.6 28.893 a84 a72 a83 a90 aA95 aA58 bcdB L9 11.8 29.295 a87 a69 a82 a91 aA95 aA50 dB L10 12.2 29.095 a85 a72 a86 a87 aA94 aA55 cdB CV (%)--4.76.86.74.27.25 M-SOY 7908 RR L1 12.0 28.896 a75 a90 a81 a86 abA93 aA46 cdB L2 12.0 28.795 a79 a77 a83 a96 aA92 aA47 cdB L3 11.9 27.697 a79 a91 a83 a89 abA85 aA55 bcdB L4 11.1 27.897 a72 a86 a81 a78 bA77 aA42 dB L5 11.7 28.397 a72 a87 a78 a86 abA85 aA60 abcB L6 12.5 29.197 a78 a77 a84 a93 abA87 aA68 abB L7 12.8 27.896 a81 a85 a83 a96 aA92 aA44 cdB L8 11.6 27.894 a75 a84 a79 a93 abA93 aA75 aB L9 11.5 28.994 a78 a94 a83 a91 abA87 aA59 bcdB L10 12.1 29.795 a79 a99 a82 a93 abA87 aA44 cdB CV (%)--2.35.812.33.213.4 VariablesCP1CP2 Germination-0.84-0.02 Accelerated Aging0.830.11 Seedling Emergence0.810.27 Electrical Conductivity-0.84-0.26 Water Stress 40%0.30-0.83 Water Stress 60%0.58-0.59 Water Stress 80%0.470.10 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.


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