Genotype-by-Environment Interaction and Yield Stability Analysis in Finger Millet (Elucine coracana L. Gaertn) in Ethiopia (original) (raw)
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African Journal of Agricultural Research, 2018
An experiment was conducted to study the adaptability and genotype × environment interaction of finger millet varieties in the north eastern part of Ethiopia. Eight finger millet varieties and a local check were tested at Sirinka, Kobo, and Jari in 2013 and 2014 cropping season. The experiment was laid out in a randomized complete block (RCB) design with three replicates. The result showed that the year 2013 was relatively better than 2014 for finger millet yield. Variety Bareda ranked first in terms of yield at Sirinka both in 2013 and 2014 (SR13 and SR14), and Kobo in 2013 (KB13). Variety Tadesse ranked first at Jari in 2013 (JR13); however, both the local check and Gute ranked first at Jari in 2014 (JR14). Except at JR14, the local check ranked second in all the environments. The Additive Main-effect and Multiplicative Interaction (AMMI) analysis showed that the best fit model was AMMI1 and it explained 68.54% of the genotype × environment interaction. Genotypes Bareda, the local check and Gute had higher grain yield in that order. Similarly, environments SR13, JR13 and KB13 had above average grain yield. Varieties Tadesse and Padet had small interaction effect; however, Bareda and Gute exerted relatively higher interaction effect. Similarly, environment SR13 contributed minimum interaction effect; whereas KB13 and JR13 contributed higher interaction effect. Genotype and genotype × environment (GGE) biplot identified the local check, Bareda and Gute as more desirable varieties. Based on the overall performance and adaptability of the finger millet varieties across environments, Bareda could be recommended for production at Sirinka and Kobo, whereas the local check could still be used at Jari.
Yield performance and Adaptability of Finger millet landrace in North Western Tigray, Ethiopia
Finger millet (Eleusine coracana L. Gaertn.) is a stable food crop with inherent hardy nature and quality nutritional grain in majority of drought prone areas in several East African and South Asian countries in the world. The experiment was conducted with objectives of determining the effect of genotype, environment and their interaction for grain yield and to identify the most stable finger millet genotypes in north western Tigray, Ethiopia. Forty one finger millet genotypes were grown at three sites in northwestern Tigray, Ethiopia at two season (2015/16 and 2016/2017). The experiment was laid down in RCBD with three replications. The combined ANOVA for grain yield revealed highly significant (P<0.01) for genotypes, environments and their interactions. This indicated that the environments were diverse and variability among the genotypes. The significant interaction showed the genotypes respond differently across the different environments. The mean grain yield value of genotypes averaged over environments indicated that MyARC coll 44 and Tessema had the highest (2599 kg/ha) and lowest (1154 kg/ha) grain yield respectively. The best genotype with respect to site of Tselemti on station was genotype MyARC coll 44; for Tselemti Maiani also MyARC coll 61 and MyARC coll 61. Generally, the result revealed the existence of variability for the characters studied in finger millet landraces. Hence, this is a potential character of interest which could be used in the genetic improvement of finger millet through hybridization and/or selection by involving breeders and farmers' knowledge. Farmers also opined that the new variety has better grain and fodder yield potential and lodging resistance and they would adopt them in future.
Journal of Applied Biosciences, 2014
Background and justification: Lack of stable high yielding cultivars is one of the major bottlenecks for production and productivity of finger millets in Ethiopia. Identification of adaptable, stable and high yielding genotypes under varying environmental conditions prior to release as a cultivar is the first and foremost steps for plant breedingr and this has direct bearing on the adoption of the variety, its productivity and total production of the crop. Objective: The major objectives of the present study were to (i) assess the stability and yield performance of advanced finger millet genotypes evaluated in multiple environments, and (ii) identify stable high yielding candidate cultivar (s) for possible release using different statistical tools. Material and methods: A total of 30 advanced finger millet genotypes were evaluated against two standard checks (Gute and Taddese) across four locations (Arsi Negele, Assosa, Bako and Gute) in 2012 and 2013 main cropping seasons. The trial was arranged in a randomized complete block design (RCBD) replicated three times. Summary result and application of the study: Additive Main effect and Multiplicative Interaction (AMMI), Genotype and Genotype by Environment interaction (GGE) biplot analysis and, Eberhart and Russell model revealed that Acc. 203544 is stable high yielding (3.16 ton ha-1) with a yield advantage of 13.7% over the best standard check, Gute (2.78 ton ha-1), and thus should be recommended for possible release with wider environmental adaptability. Acc. 242111 (3.08 ton ha-1), Acc. BKFM0051 (3.07 ton ha-1) and Acc.229738 (2.99 ton ha-1) were also high yielding, but showed narrow stability and thus should be recommended for verification and possible release for specific environments.
Stability Analysis for Grain Yield Attributing Traits in Finger Millet
Andhra Agricultural Journal , 2020
Stable performance of genotype in different environments is highly considered for development and release of new high yielding varieties. In the present study, thirteen advanced finger millet genotypes along with one local check were evaluated at three locations to identify stable and high yielding genotypes. None of the genotypes showed stable performance for all the traits studied. Linear component of genotype x environment (G x E) reaction was significant for number of productive tillers and grain yield ha-1 revealing the differential reaction of genotypes tested in different environments for these traits. Among the tested genotypes, PPR 1041 recorded average stability for number of productive tillers per plant indicating the wide adoptability of this genotype for number of productive tillers per plant. Average stability for grain yield was found in VR 990 which revealed the wide adaptability of the genotype across different locations.
An experiment was conducted to study the adaptability and genotype x environment interaction of finger millet varieties in the north eastern part of Ethiopia. Eight finger millet varieties and a local check were tested at Sirinka, Kobo and Jari in 2013 and 2014 cropping season. The experiment was laid out in a randomized complete block (RCB) design with three replicates. The result showed that the year 2013 was relatively better than 2014 for finger millet yield. Variety Bareda ranked first at Sirinka both in 2013 and 2014 (SR13 and SR14), and Kobo in 2013 (KB13). Variety Tadesse ranked first at Jari in 2013(JR13); however, both the local check and Gute ranked first at Jari in 2014 (JR14). Except JR14, the local check ranked second in all the environments. The Additive Main-effect and Multiplicative Interaction (AMMI) analysis showed that the best fit model was AMMI1 and it explained 68.54% of the genotype x environment interaction. Genotypes Bareda, Local check and Gute had higher grain yield in that order. Similarly, environments SR13, JR13 and KB13 had above average grain yield. Varieties Tadesse and Padet had small interaction effect; however, Bareda and Gute exerted relatively higher interaction effect. Similarly, environment SR13 contributed minimum interaction effect; whereas, KB13 and JR13 contributed higher interaction effect.Based on the overall performance and adaptability of the finger millet verities across environments, Bareda could be recommended for production at Sirinka and Kobo, whereas the local check could still be used at Jari.
Evaluation of Recently Released Finger Millet Varieties for Their Adaptability in West Haraghe Zone, Eastern Ethiopia, 2024
Finger millet is a major grain crop in the west hararghe zone. However, due to major constraints like lack of improved varieties and drought, the productivity is by far lower than the genetic potential of a crop in the study areas. Thus, current study initiated to obtain high-yielding and stable varieties. The study was conducted in districts of Habro, Mechara, and Gamachis of the west hararghe zone, using eight improved and one standard check finger millet varieties at 2020 main cropping seasons. The experiment was laid down in a randomized completely block design with three replications. Analysis of variance for grain yield across locations showed significant differences at p< 0.05. Further analysis of AMMI indicated that environments, varieties, and their interaction effects were significantly different. Even if, tested materials showed a significantly different grain yield across locations nevertheless, the GGE bi-plot analyses implied relatively high yielding and consistent across environments for varieties Bako-09, Gudetu, and Addis-01. Therefore, these varieties of finger millet were recommended for further evaluation at the farmer's field.
Identification of high yielding finger millet RILs with wide/specific adaptation
Electronic Journal of Plant Breeding, 2017
Finger millet (Elucine coracana L. Gaertn), is one of the most important cereals in the sub-Saharan Africa and south Asia. Finger millet in India is grown in a wide range of agro-climatic zones which are highly variable resulting in complex genotype (G) × environment (E) interactions (I). Significant GEI challenge the breeders to identify genotypes suitable for a wide range of environments/specific environments. Twelve selected recombinant inbred lines (RILs) along with four checks were evaluated to characterize genotype × location interaction (GLI) and identify those that are widely/specifically adapted. The AMMI ANOVA showed significant mean squares due to genotype, location and GLI for days to 50 per cent flowering, plant height, finger length and grain yield plant-1. Near perfect fit of interaction principal component (IPC)1 and IPC2 to the total GLI variation for most of the traits suggested a good approximation of the bi-plot with respect to the patterns of GLI and good predictability of RIL performance across four locations. The RILs such as RIL-3, RIL-104, RIL-143, RIL-183 and RIL-303 were found widely adapted. The RILs such as RIL-104, RIL-94, RIL-185 and RIL-302 were found specifically adapted to GKVK, Bengaluru and RIL-143 to Mandya for grain yield plant-1 .
2018
Finger millet (Eleusine coracana (L.) Gaertn.) is one of the most important food cereals in the sub-Saharan Africa and south Asia. It is the most widely cultivated millet in the semi-arid tropical and subtropical regions of the world after pearl millet (Pennisetum glaucum) and foxtail millet (Setaria italica). It is also one of the critical plant genetic resources for the agriculture and food security of farmers inhabiting arid, infertile and marginal lands (Barbeau and Hilu, 1993).
Uganda Journal of Agricultural Sciences, 2017
Pearl millet (Pennisetum glaucum (L.) R. Br.) is an important food security and income crop for households living in semi-arid zones in Uganda. However, the genotype by environment interaction, in addition to the several methods used for its assessment, complicates selection of varieties adapted to such semi-arid areas. The objective of this study, therefore, was to compare common methods used to assess stability and adaptability of improved genotypes. Seventy six genotypes were planted in four environments in an alpha experimental design with two replications. Results showed that genotype by environment interactions were significant at p<0.05 for grain yield, days to 50% flowering and 50% physiological maturity, percentage of productive tillers and panicle area. Results further showed inconsistency in ranking of genotypes between methods; although Cultivar Superiority, REML, Yield Stability Index and GGE biplot were consistently correlated and identified high yielding and stable genotypes.