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Phenotypic Variation and Correlation of Traits in Philippine Hybrid Rice Varieties

Aldrin Y. Cantila,
Philippine Rice Research Institute, Bual Norte, Midsayap 9410, Philippines

Aizel Mae L. Fordan
Philippine Rice Research Institute, Bual Norte, Midsayap 9410, Philippines

Isagane V. Boholano
Philippine Rice Research Institute, Bual Norte, Midsayap 9410, Philippines

Abstract/ Executive Summary:

Understanding the phenotypic variation and correlation in hybrid rice varieties will lead to proper utilization of these genetic resources. Grain yield (GY), the primary trait, and its secondary traits such as days to 50% flowering (DF), days to maturity (DM), grain length (GL), grain weight (GW), number of filled grains panicle^-1 (NFGP), one thousand grain weight (OTGW) panicle length (PL), panicle weight (PW), spikelet fertility (SF), and spikelet number panicle^-1 (SNP) of 13 hybrid rice in two environments (E1 and E2) were analyzed using combined analysis of variance (ANOVA) and correlation analysis. High significant variation was found among hybrids (G) in all traits except for GW while there was at least significant result among environments (E) in DF, DM, GL, GW, PW, and OTGW, and in GxE in DF, DM, GW, NFGP, PW, and SNP. Therefore, E1 hybrids were early flowering and maturing, had longer, wider, and more grains, had longer panicles, and higher yield while in E2 hybrids were late flowering and maturing, and had heavier grains. However, among the 13 hybrid rice, M1 had the highest GY and GL in each environment with a mean of 9.57 t ha^–1 and 9.75 mm, respectively. M1, therefore, can be recommended to farmers for varietal utilization. Correlation analysis, on the other hand, found 15 and 17 significant correlations in E1 and E2, respectively. Of the correlation results, it was found out that among the secondary traits, only NFGP was consistently, significantly and positively correlated with GY in two environments. The result implied that attaining higher yield in hybrid rice cultivation can be possible by giving more attention to the plants during the grain filling stage.

Keywords: Hybrid phenotypes, The relationship of traits, Phenotypic variation, correlation of traits, Hybrid rice

Location: Philippine-Sino Center for Agricultural Technology

Start Date:

End Date:

Program Area: Variety and Species

Commodity: Rice

Objectives:

The study was done aiming to define the phenotypic analysis on 13 hybrid rice, to determine one or more suitable hybrid/s, and to find correlation in hybrid traits.

Methodology:

Hybrid varieties were acquired from different institutions of the country that are registered and commercially released by the NSIC-Philippines. These varieties have a common name of Mestizo (M). M1 and M32 were developed from IRRI, M12 and M13 from Philippine-Sino Center for Agricultural Technology (Phil SCAT), M20 and M55 from Phil Rice, M28 and M51 from Seed works, M52 and M59 from Syngenta, M6 from SL Agritech, M46 from Bayer Crop Science, and M60 from Advanta India Limited. IRRI, Phil SCAT, and Phil Rice are considered public institutions while Seed works, Syngenta, SL Agritech, Bayer Crop Science, and Advanta India Limited are private firms. These 13 hybrid rice varieties were considered as experimental materials.

The environment and field layout

The set-up had two environments. One was located at Midsayap, Cotabato with global positioning system (GPS) points of 7°10'42.5"N 124°30'04.5"E (E1) and another was at Isulan, Sultan Kudarat with corresponding GPS points of 6°34'33.7"N 124°36'47.7"E 9 (E2). E1 experimental materials were planted from April 16 to July 18, 2018, while E2 experimental materials were from June 25 to September 28, 2018. Every 13 experimental materials were carried out in randomized complete block design in three replications.

Data gathered

The primary trait GY was computed in this formula: [Panicle number per m² x spikelet number panicle-¹ x spikelet fertility (%) x 1000 grain weight (g) x 10^-2] ÷ 1000 ( Phil Rice, 2007) while the secondary traits such as days to 50% flowering (DF), days to maturity (DM), grain length (GL) in mm, grain width (GW) in mm, number of filled grains panicle^-1 (NFGP), one thousand grain weight (OTGW) in g, panicle length (PL) in cm, panicle weight (PW) in g, spikelet fertility (SF) in % and spikelet number panicle^-1 (SNP) was gathered following the methodology in the standard evaluation system for rice (IRRI, 2013). On the other hand, temperature data was taken from the environment’s weather station

Statistical analyses

XLstat software (Addinsoft, 2010) gave the overall mean, means with its standard error and Kolmogorov-Smirnov (K-S) normality test for the data of each trait per environment. Mantel’s and correlation tests were also derived using the same software. STAR 2.01 (2014) software, on the other hand, computed the combined analysis of variance (ANOVA) with corresponding F-test of each trait in two environments.

Source of Information: J Bangladesh Agril Univ 17(2): 179–186, 2019

Article Link (Online Journal): https://doi.org/10.3329/jbau.v17i2.41941

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

High significant variation (1%) was found among hybrids in all traits except for GW while at the least significance (5%) among environments (E) in six traits and in GxE in six traits. Hybrids in each environment, therefore, showed different phenotypes. The most notable was M1 among the 13 hybrid rice. M1 had the highest GY and GL in each environment with a mean of 9.57 tha^-1 and 9.75 mm, respectively. This variety can be recommended to farmers for varietal utilization. On the other hand, correlation analysis found 32 significant correlations in two environments but the most noted was that NFGP was consistently, significantly and positively correlated with GY in two environments. The result implied that increasing higher yield in hybrid rice cultivation can be possible by giving more attention to the plants during the grain filling stage.

Knowledge Management: Journal