Miftahur Rizqi Akbar
Department of Agronomy and Horticulture, Faculty of Agriculture, Institut Pertanian Bogor. Jl. Meranti, Kampus IPB Darmaga, Bogor 16680, West Java, Indonesia

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Short Communication: Selection of doubled haploid lines of rainfed lowland rice in preliminary yield trial Miftahur Rizqi Akbar; Bambang Sapta Purwoko; Iswari Saraswati Dewi; Willy Bayuardi Suwarno; Sugiyanta
Biodiversitas Journal of Biological Diversity Vol. 20 No. 10 (2019)
Publisher : Society for Indonesian Biodiversity

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/biodiv/d201003

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