scholarly journals Delineation of genotype × environment interaction for identification of stable genotypes for tillering phase drought stress tolerance in sugarcane

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
C. Mahadevaiah ◽  
Prakash Hapase ◽  
V. Sreenivasa ◽  
Ramesh Hapase ◽  
H. K. Mahadeva Swamy ◽  
...  
Keyword(s):  
Drought Stress ◽  
Principal Component ◽  
Stability Index ◽  
Biomass Accumulation ◽  
Moisture Stress ◽  
High Yield ◽  
Cane Yield ◽  
Environment Interaction ◽  
Sugarcane Varieties ◽  
Genotype Environment Interaction

AbstractSugarcane is a trans-seasonal long-duration crop and tillering phase (60–150 days) is the most sensitive phase for moisture stress, causing significant reduction in biomass accumulation. The study focussed to assess the Genotype × Environment Interaction (GEI) for tillering phase moisture stress and to identify the stable genotypes in sugarcane. The study dealt with 14 drought tolerant genotypes and two standards (Co 86032 and CoM 0265) which were evaluated in two plant and one ratoon trials at four locations in Maharashtra, India. The moisture stress was imposed for 60 days from 90 to 150 days after planting and corresponded to tillering phase by withholding the irrigation. The AMMI ANOVA showed significant GEI for cane and CCS yield accounting 18.33 and 19.45 percent of variability respectively. Drought and genotype main effects were highly significant accounting 49.08 and 32.59 percent variability for cane yield and, 52.45 and 28.10 percent variability for CCS yield respectively. The first two interactive principal component (IPCA) biplots of AMMI showed diverse nature of all four environments and the Discriminative vs Mean biplots of Genotype + genotype × environment interaction (GGE) model showed that ‘Pune’ as the highly discriminating environment. The genotype ranking biplots of GGE showed that Co 85019 was the most stable genotype followed by Co 98017. Similar results were also observed in Yield vs IPCA1 biplot of AMMI, which revealed Co 85019 and Co 98017 as high yielding stable varieties. Yield related environmental maximum (YREM) showed thirteen and nine percent loss due to crossover interactions in Co 85019 for cane yield and CCS yield respectively. The multi-environment BLUP and genotype stability index (GSI) has reaffirmed that Co 85019 as a drought proof and stable genotype with high yield under tillering phase drought stress. The results suggested using Co 85019 for cultivation in drought prone regions and the usefulness of the methodology for identifying more such sugarcane varieties for the benefit of resource poor famers in drought affected regions.

scholarly journals ADAPTIBILITY PERFORMANCES OF CHICKPEA (CICER ARIETINUM L.) GENOTYPES UNDER DIFFERENT ENVIRONMENTS FOR STABILITY OF QUANTITATIVE TRAITS

2020 ◽  
Vol 53 (1) ◽  
pp. 62-72
Author(s):  
M. G. AZAM ◽  
M. A. HOSSAIN ◽  
J. HOSSAIN ◽  
M. A. HOSSAIN ◽  
M. O. ALI
Keyword(s):  
Regression Analysis ◽  
Cicer Arietinum ◽  
Block Design ◽  
Principal Component ◽  
High Yield ◽  
Environment Interaction ◽  
Phenotypic Characters ◽  
Cicer Arietinum L ◽  
Genotype Environment Interaction ◽  
Wide Range

The evaluation and computation of yield stability of a genotype over environments is a critical component of a certain breeding program. The present study was intended to screen 11 advance chickpea (Cicer arietinum L.) genotypes and one check for genotype × environment interaction (G × E) at six locations with varying micro and macro climatic conditions for yield correlated phenotypic characters. A number of 11 advanced genotypes of chickpea and one check variety were assessed for their adaptability at six different locations of Bangladesh. The randomized complete block design (RCBD) with three replications was chosen to experiment. The means were used to compute Additive Main Effects and Multiplicative Interaction (AMMI) analysis of variance, followed by regression analysis to measure × E. The regression analysis showed significant genotype × environment interaction for all the phenotypic characters. The mean values of days to flowering, days to maturity, plant height, number of pods per plant and seed yield were highly significant for linear, as well as non-linear components of G × E. Chickpea yield was significantly (p< 0.01) affected by genotypes, the environments and G × E interaction, indicating that the varieties and the test environments were diverse. G × E was further partitioned by principal component axes. The first two principal components cumulatively explained 86.59% of the total variation, of which 53.34% and 33.25% were contributed by IPCA1 and IPCA2, respectively. The AMMI stability value discriminated genotypes G2 (BCX 09010-9), G3 (BCX 09010-2) and G8 (BCX 01008-4) the stable genotypes. The investigated genotypes exhibited varying adaptability in different environments. Genotypes G3 (BCX 09010-9) and G9 (BCX 01008-3) were stable genotypes with high yield over a wide range of environments are promising candidate chickpea varieties.

scholarly journals Analysis of Genotype-Environment Interaction and Yield Stability of Introduced Upland Rice in the Groundnut Basin Agroclimatic Zone of Senegal

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ghislain Kanfany ◽  
Mathieu Anatole Tele Ayenan ◽  
Yedomon Ange Bovys Zoclanclounon ◽  
Talla Kane ◽  
Malick Ndiaye ◽  
...  
Keyword(s):  
Grain Yield ◽  
Upland Rice ◽  
Block Design ◽  
Principal Component ◽  
Stability Index ◽  
Rice Production ◽  
Yield Stability ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype Environment Interaction

Identification of highly performing varieties under Senegalese environment is crucial to sustain rice production. Genotype-environment interaction and stability performance on the grain yield of ten upland rice genotypes were investigated across 11 environments in Senegal during the rainy seasons of 2016 and 2017 to identify adapted varieties. The experiment was conducted using a randomized complete block design with three replications at each environment. Data on grain yield were recorded and analyzed using the additive main effects and multiplicative interaction (AMMI) model. The combined analysis of variance revealed that the grain yield was significantly affected by environment (67.9%), followed by genotype × environment (G × E) interaction (23.6%) and genotype (8.5%). The first two principal component axes were highly significant with 37.5 and 26% of the total observed G × E interaction variation, respectively. GGE biplot grouped the environments into four potential megaenvironments. Based on the yield stability index parameter and ranking GGE biplot, NERICA 8 and ART3-7-L9P8-1-B-B-1 were stable and high-yielding varieties compared to the local check NERICA 6. These varieties should be proposed for cultivation in order to sustain the rice production in the southern part of the groundnut basin of Senegal and used as parental lines in rice breeding program for grain yield improvement.

scholarly journals Delineation of Genotype × Environment Interaction for Identification of Stable Genotypes to Grain Yield in Mungbean

2020 ◽  
Vol 2 ◽  
Author(s):  
Santhi Madhavan Samyuktha ◽  
Devarajan Malarvizhi ◽  
Adhimoolam Karthikeyan ◽  
Manickam Dhasarathan ◽  
Arumugam Thanga Hemavathy ◽  
...  
Keyword(s):  
Grain Yield ◽  
Tamil Nadu ◽  
Stability Index ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype Environment Interaction ◽  
South Indian ◽  
Indian State ◽  
Wide Adaptation ◽  
High Yields

In the present study, fifty-two mungbean (Vigna radiata) genotypes were evaluated for seven morphological traits at three different environments in South Indian state Tamil Nadu, namely Virinjipuram (E1), Eachangkottai (E2), and Bhavanisagar (E3) during Kharif 2017, 2018, and 2019, respectively. The data collected were subjected to variability and correlation analyses, followed by stability analysis using additive main effects and multiplicative interaction (AMMI) model, genotype and genotype × environment interaction effects (GGE) biplot. Variablility was observed among the genotypes for the following traits viz., plant height, days to fifty per cent flowering, number of pods per plant, pod length, number of seeds per pod, hundred seed weight and grain yield. Correlation analysis showed that the trait number of pods per plant was significantly associated with grain yield. The G × E was smaller than the genetic variation of grain yield as it portrayed the maximum contribution of genotypic effects (61.07%). GGE biplot showed E3 as a highly discriminating and representative environment. It also identified environment-specific genotypes viz., EC 396111 for E1, EC 396125 for E2 and EC 396101 for E3 environments. The genotypes with minimum genotype stability index (GSI) viz., V2802BG (7), HG 22 (13), and EC 396098 (13) were observed with wide adaptation and high yields across all the three environments. In summary, we identified stable genotypes adapted across environments for grain yield. These genotypes can be used as parent/pre-breeding materials in future mungbean breeding programs.

GROUPING LOCATIONS FOR EFFICIENT CASSAVA EVALUATION IN MALAWI

2003 ◽  
Vol 39 (2) ◽  
pp. 167-179 ◽  
Author(s):  
J. MKUMBIRA ◽  
N. M. MAHUNGU ◽  
U. GULLBERG
Keyword(s):  
Environmental Heterogeneity ◽  
Principal Component ◽  
Environment Interaction ◽  
Scatter Plot ◽  
Genotype Environment Interaction ◽  
Breeding Zone ◽  
Adverse Environmental Conditions ◽  
The Tropics ◽  
Pair Wise Comparison ◽  
Better Than

Cassava, a crop widely adapted in the tropics, has the important attribute of withstanding adverse environmental conditions better than do many other staple crops. The performance of an individual genotype, however, is influenced by the environment in which it grows. In Malawi, the heterogeneity of agro-ecologies requires the cumbersome and costly assessment of new cassava genotypes at many sites. This study was conducted, therefore, to test the feasibility of selecting only a few locations for cassava evaluation that would be representative of all the agro-ecologies in which cassava is grown in Malawi. Enormous environmental effects, largely contributed by the interaction between season and location, were manifested. Genotype×environment interaction, due largely to a third level interaction (genotype×season×location), was highly significant for all the traits studied. A principal component analysis scatter plot showed no particular grouping of environments, but a pair-wise comparison showed that some of the locations had limited genotype×environment interaction, indicating that it would be sufficient to use one of these sites for evaluating these traits. The value of the residual was often large, probably as an effect of environmental heterogeneity in the test sites. The authors conclude that cassava genetic improvement will continue to be slow if Malawi is used as a single breeding zone. They recommend a much finer grouping of the locations and the use of smaller plot sizes to allow more clones to be tested at more sites for the same cost. Locations may be selected for intensive cassava breeding work from those that give the best discrimination between genotypes while having insignificant genotype×environment interactions in a relatively large number of environments.

Genetic variation in winter barley and selection of high yielding lines

2015 ◽  
Vol 49 (6) ◽  
Author(s):  
Adnan Al-Yassin ◽  
Murari Singh ◽  
Michael Baum
Keyword(s):  
Genetic Material ◽  
Winter Barley ◽  
High Yield ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Heritable Trait ◽  
Genetic Mechanisms ◽  
Yield Gain ◽  
Food Grain ◽  
Yield Trials

Barley (<italic>Hordeum vulgare</italic> L.) is an important crop with excellent nutritious feed and food grain. Winter barley, in particular, is predominantly grown in highland under rainfed systems due to its ability to tolerate cold. However, it has low productivity due to complex genetic mechanisms and limitations in determining an optimal environment for its selection and evaluation. This study evaluated the genetic variability, heritability and genetic gain for yield in barley, using preliminary un-replicated yield trials in 2011 at two locations and followed by replicated sets of yield trials in 2012, all in Syria. Significant genotypic variability was found at both stages of the evaluation/selection. During 2011, the best linear unbiased predictor means of test genotypes adjusted for spatial variability were found in the range of 1.75–3.75 t/ha at Tel Hadya and 0.03–1.58 t/ha at Breda. A set of 22 advanced yield trials comprising a total of 601 lines at Tel Hadya in 2012 yielded in the range of 1.85–3.13 t/ha. Based on the mean over these set of trials, the highest heritable trait was days to heading (broad-sense heritability on mean-basis= 0.64) followed by yield (the heritability = 0.30). The yield gain due to selection, at 20% intensity of selection, was 5.66% at Tel Hadya and 27.1% at Breda in 2011 using un-replicated genetic material, while it was 7.01 % for the replicated trials at Tel Hadya in 2012. We recommend use of the best lines selected in 2012 at Tel Hadya for further exploitation in genotype × environment interaction studies for high yield and specific and broad adaptation.

Performance of tropical early-maturing maize cultivars in multiple stress environments

2010 ◽  
Vol 90 (6) ◽  
pp. 831-852 ◽  
Author(s):  
B. Badu-Apraku ◽  
A. Menkir ◽  
S. Ajala ◽  
R. Akinwale ◽  
M. Oyekunle ◽  
...  
Keyword(s):  
Drought Stress ◽  
Striga Hermonthica ◽  
Environment Interaction ◽  
Maize Productivity ◽  
Maize Cultivars ◽  
Genotype Environment Interaction ◽  
Maize Varieties ◽  
Early Maturing ◽  
Use Efficiency ◽  
Growing Conditions

Maize (Zea mays L.) production in west Africa (WA) is constrained by drought, Striga hermonthica infestation and low soil nitrogen (N). Maize varieties resistant to Striga, drought, and low N are ideal for WA, but genotype × environment interaction on these traits are usually significant due to differential responses of cultivars to growing conditions. Three studies were conducted from 2007 to 2009 at five locations in Nigeria to evaluate the performance of selected early-maturing cultivars under drought stress versus well-watered, Striga-infested versus Striga-free, and in low- versus high-N environments. Drought stress reduced grain yield by 44%, Striga infestation by 65%, and low N by 40%. GGE biplot analysis showed that the genotypes TZE-W DT STR C4, Tillering Early DT, TZE-W DT STR QPM C0 and TZE-Y DT STR C4 performed relatively well in all study environments. TZE-W DT STR C4 and TZE Comp3 C1F2 were outstanding under drought, TZE-W DT STR C4, EVDT-W 99 STR QPM C0 and TZE-W DT STR QPMC0 under Striga infestation and Tillering Early DT, EVDT 97 STRC1, TZE-W DT STR C4, and TZE Comp3 C3 under N deficiency. Maize productivity in WA can be significantly improved by promoting cultivation of genotypes that combine high resistance/tolerance to Striga and drought with improved N-use efficiency.

scholarly journals Genotype environment interaction analysis for fruit yield in okra (Abelmoschus esculentus L.) under alkaline environments

2021 ◽  
Vol 81 (01) ◽  
pp. 101-110
Author(s):  
Satish Kumar Sanwal ◽  
Anita Mann ◽  
Hari Kesh ◽  
Gurpreet Kaur ◽  
Raj Kumar ◽  
...  
Keyword(s):  
Interaction Analysis ◽  
Stability Index ◽  
Genotype By Environment Interaction ◽  
Fruit Yield ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Alkaline Environments ◽  
Prone Area ◽  
Marketable Fruit ◽  
Ph Range

Twenty four Okra genotypes were evaluated for marketable fruit yield and its related traits for genotype environment interaction during 2015-16 and 2016-17. The genotypes were exposed to alkaline environment with a pH range of 8.0±0.2, 8.5±0.2, 9.0±0.2 and 9.5±0.2. A significant level of deviation in expression of different traits was observed in all the genotypes with increasing pH. Based on Additive Main Effects and Multiplicative Interaction (AMMI), Genotype and Genotype Environment Interaction (GGE) biplot, Wrick’s ecovalence (Wi2 ), AMMI Stability Value (ASV) and Yield Stability Index (YSi) stable genotypes with high fruit yield were identified over the eight environments. The combined AMMI analysis of variance indicated that genotype main effect, environment and genotype-by-environment interaction effects showed variation of 19.83%, 63.07% and 17.10%, respectively for fruit yield. On the basis of different stability measures, VRO-112, VRO-110, Kashi Kranti, VROB178, AE-70 and VRO-108 were differentiated as high yielding and stable genotypes over the tested environments. This study will be helpful for selecting alkali tolerant okra parents for further breeding programme and recommending the suitable genotypes for alkalinity prone area

scholarly journals AMMI and GGE Biplot Analysis for Stability of Yield in Mid-early Pigeonpea [Cajanus cajan (L.) Millspaugh] Genotypes

2022 ◽  
Author(s):  
P. Jagan Mohan Rao ◽  
N. Sandhyakishore ◽  
S. Sandeep ◽  
G. Neelima ◽  
A. Saritha ◽  
...  
Keyword(s):  
Block Design ◽  
High Yield ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Genotype Environment Interaction ◽  
Single Location ◽  
Randomized Complete Block Design ◽  
Advanced Stages ◽  
Superior Genotypes

Background: The genotype × environment interaction greatly influences the success of breeding and in multi-location trials complicates the identification of superior genotypes for a single location, due to magnitude of genotype by location interaction are often greater than genotype by year interaction. This necessitates genotype evaluation in multi environments trials in the advanced stages of selection. Methods: Nine elite pigeonpea genotypes of mid-early duration were evaluated in six diverse locations in randomized complete block design with three replications during kharif, 2019 to ascertain the stable genotypes, environments discrimination and genotype by environment crossovers using AMMI and GGE biplot stability models. Result: The results in the present investigation revealed that first two principal components explained 73.4% of variation interaction, while, 80.50% in GGE biplot. Both the models identified WRGE-126 (G6) as stable performer with high yield (1733 kg ha-1) and among the locations Tandur (E1) measured as the ideal environment. Whereas, the environments, Adilabad (E3) and Warangal (E4) were observed representative with better discriminating ability.

Genotype × environment interaction and genetic association of grain iron and zinc content with other agronomic traits in RIL population of pearl millet

2018 ◽  
Vol 69 (11) ◽  
pp. 1092
Author(s):  
Tripti Singhal ◽  
C. Tara Satyavathi ◽  
Aruna Kumar ◽  
S. Mukesh Sankar ◽  
S. P. Singh ◽  
...  
Keyword(s):  
Pearl Millet ◽  
Agronomic Traits ◽  
Pennisetum Glaucum ◽  
Recombinant Inbred Lines ◽  
Selection Index ◽  
Principal Component ◽  
Zinc Content ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Zn Content

Biofortification of lines of pearl millet (Pennisetum glaucum (L.) R.Br.) with increased iron (Fe) and zinc (Zn) will have great impact because pearl millet is an indispensable component of food and nutritional security of inhabitants of arid and semi-arid regions. The aim of the present study was to assess the stability of Fe and Zn content in recombinant inbred lines (RILs) developed for grain Fe and Zn content, and to use these lines in developing micronutrient-rich pearl millet hybrids. A mapping population consisting of 210 RILs along, with parents and checks, was assessed in three consecutive years (2014–16) under rainfed conditions at the same experimental location in an alpha design with two repetitions. Significant differences were observed in genotype, environment and genotype × environment interaction mean squares for all variables, particularly grain micronutrients. The first two principal components of an interaction principal component analysis cumulatively explained 100% of the total variation; respective contributions of the first and second components were 64.0% and 36.0% for Fe, and 58.1% and 41.9% for Zn. A positive and moderately high correlation (0.696**) between Fe and Zn contents suggests good prospects of simultaneous improvement for both micronutrients. Among the 210 RILs, RIL 69, RIL 186, RIL 191, RIL 149 and RIL 45 were found to be more stable with higher mean micronutrient content, additive main effects and multiplicative interaction stability value (ASV) and genotype selection index (GSI) under rainfed condition. These RILs are promising and can be tested further for their combining ability for yield as well as grain micronutrient content for developing superior biofortified, heterotic pearl millet hybrids.

Effect of genotype-environment interaction on grain yield of exotic rice (Oryza sativa L.) hybrids

2018 ◽  
Vol 44 (4) ◽  
pp. 507-514
Author(s):  
MU Kulsum ◽  
MJ Hasan ◽  
MN Haque ◽  
M Shalim Uddin ◽  
KM Iftekharduddaula
Keyword(s):  
Oryza Sativa L ◽  
Major Complication ◽  
Genotype By Environment Interaction ◽  
Yield Potential ◽  
High Yield ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Wide Range ◽  
Main Effects ◽  
Moderate Yield

Genotype by environment interaction (GEI) is a major complication in plant breeding. Authors used additive main effects and multiplicative interaction (AMMI) to evaluate the effects of GEI in hybrid rice genotype and their adaptation in three years at four locations. Among rice hybrid genotypes ACI93024 was stable in all environments with high yield potential. Using AMMI analysis AMMI 1 biplot showed the genotypes HS-273, Heera-2, ACI-2 and HRM-02 were highly stable with moderate yield potential but the genotype ACI93024 was more adapted to a wide range of environment than the rest of the genotypes, while BRRI dhan28 indices the lowest stability. ACI-2, LP-70 and Mayna were specifically adapted to the environment of Rangpur, Jessore and Gazipur, respectively. Comilla was identified as stable environment for all the genotypes.

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