Exploration of relationships between physiological parameters and growth performance of rice (Oryza sativa L.) seedlings under salinity stress using multivariate analysis

Abstract

Knowledge of relationships between physiological parameters and growth performance of seedlings and respective genotypic differences would permit selection of salt tolerance at early growth stages. The goals of this study were to investigate the relationships between physiological parameters and growth performance and quantify the respective genotypic differences using multivariate analysis.. Plants of thirty-one genotypes were grown in sand tanks in a greenhouse and irrigated with Yoshida nutrient solution. Two salinity treatments were imposed at 0.9 dS m −1 (control) and 6.4 dS m −1 with sodium chloride and calcium chloride (∼ 6:1 molar ratio). Seedlings were sampled 34 days after planting (7 th to 8 th leaf stage). The characters of Na + , K + , Ca 2+ , K-Na selectivity (SK,Na) and Na-Ca selectivity (S Na,Ca ) were measured as physiological parameters. The characters of tiller number, leaf area, plant height and shoot dry weight were measured as growth performance. Under salinity stress, S K,Na increased whereas S Na,Ca decreased compared to the controls. Canonical correlation analysis indicates a strong relationship between physiological parameters and growth performance. Tiller number is a desirable parameter among the growth parameters analyzed to predict seedling growth under salinity stress. Genotypes grouped into four clusters based on ion contents and ion selectivity using Ward's minimum-variance cluster analysis. S K,Na and shoot Na + content contributed the most to the cluster formation. Similarly, genotypes grouped into four clusters based on growth performance. Genotypes were classified into three categories based on ion cluster rankings: Category 1 with high S K,Na and low shoot Na + content; Category 2 with intermediate S K,Na and shoot Na + content; Category 3 with low S K,Na and high shoot Na + content. The classification of the genotypes into Categories 1 and 3 based on their high or low S K,Na was generally consistent with their growth performance under salt stress. In contrast, ion selectivity was a less dominant mechanism controlling salt tolerance in Category 2 with intermediate S K,Na . It was concluded that ion selectivity was a relatively dominant mechanism controlling salt tolerance among rice genotypes although multiple mechanisms may be involved under moderate salt stress. The results also provide the first example of the effectiveness of cluster analysis for physiological responses to salinity stress.

Differential Salinity Tolerance amongOryza glaberrima, Oryza sativa and Their Interspecies Including NERICA

“…Since the interspecifi c group is the product of the crosses between the O. sativa and O. glaberrima species (Jones et al, 1997), some of the genotypes in this group may have acquired mechanisms for salt tolerance from the O. sativa parent. There exist genotypic differences in salt tolerance among O. sativa genotypes (Zeng, 2005). Our result suggested that some salt-tolerant interspecific progeny produced from the crosses between CG14 and WAB56-104 have acquired its salt tolerance from the O. sativa parent.…”

“…However, there exist genotypic differences among rice genotypes in the response to salinity (Zeng, 2005). Seedling and fl owering stages are most sensitive to salinity stress (Lutts et al, 1996;Gregorio et al, 1997).…”

Evaluating the growth performance of eleven Salicornia bigelovii populations under full strength seawater irrigation using multivariate analyses

“…Using conventional approaches, genotypes are scored on single characters and the ranking is often inaccurate and cumbersome (Zeng et al, 2002;Zeng, 2005;Lee at al., 2005). Cluster analysis constitutes a multivariate statistical method that can be effectively used to characterize, classify and rank numerous plant cultivars (Jolliffe et al, 1989).…”

“…Cluster analysis constitutes a multivariate statistical method that can be effectively used to characterize, classify and rank numerous plant cultivars (Jolliffe et al, 1989). Such technique has been used successfully to screen wheat, rice and potato genotypes under drought or salinity stress conditions which were further grouped into homogeneous groups based on their growth performance (Yasir et al, 2013;El-Hendawy et al, 2011, 2005Zeng et al, 2002;Zeng, 2005;Khrais et al, 1998). It is also interesting to explore the relationships among the growth traits in order to define those that are highly correlated with high yield so that they can be further incorporated in a breeding program.…”

Comparison of Salt Tolerance in Brassicas and Some Related Species

“…Therefore efficient and accurate indices and criteria for identifying salt-tolerance in Brassicas and related species are needed. The multivariate cluster analysis method was recommended as the best criteria for the identification of salt tolerance in crop species such as rice [18,28,29], green gram [30], wheat [19], tomato [31], sugarcane [32], peanut [33], cauliflower [34]. As pointed out by Khrais et al [35] and Zeng et al [18], the advantages of using a multivariate analysis in the evaluation of salt tolerance are hat it allows: 1) a simultaneous analysis of multiple t Table 3. parameters to increase the accuracy of the genotype ranking; 2) the ranking of genotypes even when plants are evaluated at different salt levels and salt tolerance varies with salinity levels, especially when the salt tolerance indices are averaged across salt levels; and 3) a more convenient and accurate estimation of salt tolerance among genotypes by simply adding the numbers in cluster group ranking at different salt levels.…”