Short Communication: Selection of doubled haploid lines of rainfed lowland rice in preliminary yield trial

Abstract

Abstract. Akbar MR, Purwoko BS, Dewi IS, Suwarno WB, Sugiyanta. 2019. Short Communication: Selection of doubled haploid lines of rainfed lowland rice in preliminary yield trial. Biodiversitas 20: 2796-2801. Yield trial is an important step in rice breeding program. This research was aimed at evaluating agronomic characters and selecting the best doubled haploid rainfed rice lines for next advanced yield trial. An experiment was conducted in Indramayu from March to August 2017. The research was arranged in randomized complete block design (RCBD) with three replications. Materials used were fifty-eight doubled haploid lines and two check varieties namely Ciherang and Inpari 18. The results revealed that all observed characters had broad genetic variability and high heritability. The number of productive tillers and the number of filled grains per panicle had a positive correlation and direct effect on productivity. Based on index selection, thirty lines were selected to have good agronomic characters and high yield. These lines had characteristics of plant height (85.7-124.7 cm), number of productive tillers (8.6-14.8 tillers), day to harvest (104.0-117.3 days), number of filled grains per panicle (136.7-264.7 grains), number of total grains per panicle (152.0-305.7 grains), weight of 1000 grain (21.5-31.3 g), and productivity (4.1-6.8 tons ha-1).
 Keywords: good agronomic trait, high yield potential, selection index

Multivariate analysis to determine secondary characters in selecting adaptive hybrid corn lines under drought stress

“…Meanwhile, the characters influenced by genotype and environmental interactions were plant height, the height of ear cobs, number of green leaves, male flowering days, female flowering days, anthesis silking interval, diameter of cob, number of grains per cob row, weight of harvested cob, yield, productivity, and weight of 1000 seed. The apparent interaction variances showed that the differences in responses between tolerant and sensitive genotypes to environmental differences (Ali et al 2015;Safitri et al 2016), which becomes the fundamental basis in the selection of secondary characters (Al-Naggar et al 2015;Anshori et al 2019;Akbar et al 2019). Therefore, significant characters to interactions variance were continued for the next analysis in determining secondary characters that are adaptive to drought stress.…”

“…To generate the adaptive corn variety, many corn genotypes must be selected and grown under normal and stress condition in order to evaluate their responses to those conditions properly and effectively. This concept is widely applied by Anshori et al (2019) and Anshori et al (2020) on rice under salinity stress, Akbar et al (2019) and Farid and Ridwan (2018) on rice under drought stress, Adhikari et al (2019); Sah et al (2020) and Badr et al (2020) on corn under drought.…”

“…Multivariate analysis can simplify, reduce, and predict the relationship between many variables and objects (Mattjik and Sumertajaya 2011). This approach has been widely used in determining character selection (Hasan et al 2016;Kose et al 2018;Anshori et al 2019;Akbar et al 2019). Multivariate analyses that can be used in identifying the best secondary characters are the biplot analysis based on principal components analysis and the path analysis.…”

“…Multivariate analyses that can be used in identifying the best secondary characters are the biplot analysis based on principal components analysis and the path analysis. Several researchers have widely reported both analyzes in determining secondary characters, reported by Anshori et al (2018) and Anshori et al (2019) in determining the secondary character of rice under salinity stress, Akbar et al (2019) in adaptive rice under drought stress, and Mollasadeghi et al (2011), Seyedzavar et al (2015) and Ali et al (2017) in maize against drought stress. Based on this, The use of multivariate analysis in this study is expected to determine the characters which effective in the selection of adaptive hybrid corn lines to drought stress.…”

Interaction of rice salinity screening in germination and seedling phase through selection index based on principal components

“…Based on the results of the PCA, PC1 in all character groups had a high proportion variance (PV) value, i.e., above 70%. According to Mattjik et al (2011), Rehman et al (2019, Akbar et al (2019) and Anshori et al (2019), optimizing the representative PC assessment is based on the cumulative proportion which reaches 0.8. By seeing the comparison of the PC1, PV value against the CP standard, the use of PC1 as the basis for the selection index was considered sufficient to represent the variance of tolerance properties.…”