A recombinant inbred population developed from a cross between high-yielding lowland rice (Oryza sativa L.) subspecies indica cv. IR64 and upland tropical rice subspecies japonica cv. Cabacu was used to identify quantitative trait loci (QTLs) for grain yield (GY) and component traits under reproductive-stage drought stress. One hundred fifty-four lines were grown in field trials in Indonesia under aerobic conditions by giving surface irrigation to field capacity every 4 days. Water stress was imposed for a period of 15 days during pre-flowering by withholding irrigation at 65 days after seeding. Leaf rolling was scored at the end of the stress period and eight agronomic traits were evaluated after recovery. The population was also evaluated for root pulling force, and a total of 201 single nucleotide polymorphism markers were used to construct the molecular genetic linkage map and QTL mapping. A QTL for GY under drought stress was identified in a region close to the sd1 locus on chromosome 1. QTL meta-analysis across diverse populations showed that this QTL was conserved across genetic backgrounds and co-localized with QTLs for leaf rolling and osmotic adjustment (OA). A QTL for percent seed set and grains per panicle under drought stress was identified on chromosome 8 in the same region as a QTL for OA previously identified in three different populations.Electronic supplementary materialThe online version of this article (doi:10.1007/s11032-013-0012-0) contains supplementary material, which is available to authorized users.

The genotype–environment interaction causes difficulties in selecting stable and ideal soybean cultivars across crop rotation models. Thus, this study aimed to provide the best estimates of soybean yields in every crop rotation model for recommendations in the rainfed agroforestry system using GGE biplot and EBLUP. In this study, the productivity and stability of 15 soybean cultivars were evaluated using four crop rotation models, that is, soybean planting after fallow (F–S), soybean planting after maize (M–S), soybean planting after rice (R–S), and continuous soybean (S–S) in dry and wet seasons at Menggoran Forest Resort, Playen District, Gunungkidul Regency, Special Province of Yogyakarta, Indonesia. Results in the dry season revealed that the Dering I cultivar had the highest yield in F–S and R–S of 1.267 and 1.375 tons ha−1 and the Grobogan cultivar in M–S and S–S of 1.200 and 1.349 tons ha−1, respectively. During the wet season, the Grobogan cultivar showed the highest yields in F–S, M–S, and S–S of 2.187, 2.435, and 2.247 tons ha−1, and the Dega I cultivar in R–S of 2.049 tons ha−1. Based on the GGE biplot and Shukla model, Dering I and Grobogan cultivars were classified as fairly and relatively stable in dry and wet seasons. The cultivars that are well suited to the environment can maximize the yield potential of these cultivars and help to build a sustainable production system.

Abstract. Alam T, Suryanto P, Supriyanta, Basunanda P, Wulandari RA, Kastono D, Widyawan MH, Nurmansyah, Taryono. 2021. Rice cultivar selection in an agroforestry system through GGE-biplot and EBLUP. Biodiversitas 22: 4750-4757. Genotype-by-environment interaction (GEI) causes differences in the productivity of rice cultivars in agroforestry systems. For this reason, the stability of rice cultivars is an important aspect that should be considered before a cultivar is recommended to farmers. Superior genotypes and ideal environments are commonly identified using two statistical models, namely, genotype–genotype-by-environment biplot (GGE-biplot) and empirical best linear unbiased prediction (EBLUP). In this study, 15 rice cultivars were evaluated in terms of their productivity and stability in three soil types (Lithic Haplusterts, Ustic Epiaquerts, and Vertic Haplustalfs) in an agroforestry system with kayu putih (Melaleuca cajuputi) in 2019 and 2020 at the Menggoran Forest Resort, Playen Forest Section, Yogyakarta Forest Management District, Indonesia. The cultivars were treated as random effects to select and obtain the EBLUP of the best cultivars in each soil type. The EBLUP revealed that Situ Patenggang showed the highest yields of 4.887 and 5.456 tons ha?1 in Lithic Haplusterts and Vertic Haplustalfs, respectively. GM 28 exhibited the highest yield of 6.492 tons ha?1 in Ustic Epiaquerts. Ciherang, GM 2, GM 8, GM 11, GM 28, Inpari 6 Jete, Inpari 33, IR-64, and Way Apo Buru were classified as stable and fairly stable cultivars, whereas the other cultivars were unstable. Therefore, rice cultivars with high yields in specific soil types should be selected.

Extreme climate change requires rice varieties adaptable to drought condition. Adaptation will play an important role in ensuring the sustainability of food security. This research aimed to improve drought tolerance of Inpari 30 and Situ Bagendit varieties through Spike-Stalk Injection Method (SIM). DNAs from several plant species, such as rice (cv. Cabacu), grasses (Echinochloa crusgalli/E. colona, elephant grass/Pennisetum purpureum, Bothriochloa pertusa, Cenchrus echinatus, Sorghum nitidum, Ischamemum timorensis and Guinea grass), sugarcane, wild rice (Oryza nivara), maize and sorghum were injected to tillers of cultivar Inpari 30 and Situ Bagendit. The first set of M1 Situ Bagendit-SIM and M1 Inpari 30-SIM seeds were treated with 20% of PEG 8000 solution for 10 days. Some of the well germinated seeds were planted in pots and maintained untill harvest. The selected M2 Situ Bagendit-SIM and M2 Inpari 30-SIM and the second set of M1 Situ Bagendit-SIM and M1 Inpari 30-SIM seeds were planted at Muara Experimental Station, Bogor (West Java). The result of PEG 8000 assay showed that M1 Situ Bagendit-SIM-elephant grass, sugarcane and O. nivara had significantly longer radicle length and higher fresh weight compared to Situ Bagendit, while M1 Inpari 30-SIM-sugarcane, sorghum and elephant grass had significantly longer radicle and plumule length, and higher radicle weight compared to Inpari 30. Field trial showed that the mutant lines of Situ Bagendit-SIM performed better than those of Inpari 30-SIM. The grain weight of M1 Situ Bagendit-SIM-Cabacu, jajagoan grass, maize, sugarcane, O. nivara and B. pertusa, and M2 Situ Bagendit-SIM-O. nivara and elephant grass were higher than that of Situ Bagendit. The grain weight of M1 Inpari 30-SIM-jajagoan grass was also higher than that of Inpari 30. Therefore, SIM could be an alternative way to develop genetic variation of rice plant.