scholarly journals Analytic Measures of Adaptability for Wheat Genotypes Evaluated under Restricted Irrigation Timely Sown Conditions for Central Zone of India

2020 ◽  
Author(s):  
Ajay Verma ◽  
G.P. Singh
Keyword(s):  
Mixed Model ◽  
Central Zone ◽  
Graphical Analysis ◽  
Harmonic Mean ◽  
Relative Performance ◽  
High Yield ◽  
Improvement Program ◽  
Wheat Genotypes ◽  
Mixed Model Approach ◽  
The People

Background: Wheat improvement program of the country identify genotypes with specific and general adaptations to ensure sustain yield for food security of the people. Yield behavior of promising wheat genotypes were studied at twelve locations of Central Zone of the country under restricted irrigation timely sown conditions. Methods: Recent analytic measures of adaptability viz., Relative Performance of Genetic Values (PRVG), Harmonic Mean of Genetic Values (MHVG) and Harmonic Mean of the Relative Performance of Genotypes (MHPRVG) were compared by considering Best Linear Unbiased Predictors (BLUP) of genotypes based on mixed model approach. Result: Genotypes MP3288, BRW3775 and DBW110 had been marked by analytic measures PRVG, MHVG, MHPRVG, HM for high yield and better adaptability across locations as per first year (2016-17) findings. HI8791 and DBW110 genotypes occupied places near to the origin in Biplot graphical analysis. Specific adapta­tions of genotype HI8791 for Sagar and Dhanduka locations were observed. DBW110 would be suitable for Jabalpur, Gwalior and Udaipur locations, whereas BRW3775 identified for Kota, Sanosora and Vijapur. Genotypes GW495, GW322, HI8713 and GW1339 had achieved high yield and better adaptability during the year (2017-18). The genotype UAS466 had expressed specific adapta­tions to Jabalpur and Gwalior, whereas HI8627 for Bhopal and Udaipur, NIAW3170 were identified for Indore and Vijapur, DDW47 for Sansora, Dhanduka and Pratapgarh. The recent analytic measures based on harmonic means of the relative performance of predicted genetic values have been observed as an appropriate to identify the better adaptive genotypes with higher yield.

scholarly journals Simultaneous application of AMMI measures and yield for stability analysis of wheat genotypes evaluated under irrigated late sown conditions of Central Zone of India

2020 ◽  
Vol 12 (4) ◽  
pp. 541-549
Author(s):  
Ajay Verma ◽  
G. P. Singh
Keyword(s):  
Relative Proportion ◽  
Central Zone ◽  
High Yield ◽  
First Year ◽  
Simultaneous Application ◽  
Single Measure ◽  
Wheat Genotypes ◽  
Stable Performance ◽  
Simultaneous Use ◽  
The Stability

Reports on biased interpretation for the stability of the genotypes under AMMI analysis, considering only the first two interaction principal components, has been observed in recent past. Simultaneous use of yield and stability of genotypes in a single measure had been advocated for identification of highly productive and broadly adapted genotypes.  The performance of superiority index, allowed variable weighting mechanism for yield and stability, has been compared with AMMI based measures. For the first year (2018-19) Superiority index, weighting 0.65 and 0.35 for yield and stability, found UAS3002, MP3336 and HI1633 as of stable performance with high yield. Recent analytic measures the relative proportion of genotypic value (PRVG) and Harmonic mean of the relative proportion of genotypic value (MHPRVG) selected CG1029, HI1634 and HD2932 wheat genotypes.  Indirect relations were expressed by Superiority Index (SI) with other stability measures.  Superiority index saw stable performance along with high yield of HD2864  and HI1634 for the second year 2019-20. PRVG as well as MHPRVG measures observed suitability of  CG1029 and  HD2864 while MP3336  as unstable wheat genotypes. Values of SI measure had expressed only indirect relations of high degree with stability measures except with yield, PRVG and MHPRVG values.  Stability measures by the simultaneous use of AMMI and yield would be more meaning full and useful as compared to measures consider either the AMMI or yield of genotypes only.

scholarly journals AMMI Appended with BLUP to Assess the Superiority of Hullness Barley Genotypes Evaluated under Coordinated System of the Country

2021 ◽  
pp. 48-61
Author(s):  
Ajay Verma ◽  
R. P. S. Verma ◽  
J. Singh ◽  
L. Kumar ◽  
G. P. Singh
Keyword(s):  
Graphical Analysis ◽  
High Yield ◽  
Improvement Program ◽  
Environment Effects ◽  
Ammi Analysis ◽  
Stable Performance ◽  
Yield Values ◽  
Program Environment ◽  
Cropping Seasons ◽  
Barley Genotypes

Highly significant effects of environments (E), G×E interaction and genotypes (G) had expressed by AMMI analysis for hulless barley genotypes under coordinated barley improvement program. Environment effects explained 69.9% and 59.7% whereas Interaction effects accounted for 17% and 20.9% during cropping seasons of 2018-19 and 2019-20, respectively. Stability measure WAASB based on all significant interaction principal components ranked suitability of DWRB204, K1149 genotypes. Superiority index while weighting 0.65 and 0.35 for mean yield & stability ranked DWRB204, Karan 16 as of stable performance with high yield barley genotypes. Ranks as per composite measures MASV1 and MASV found NDB943, KB1750 as desirable genotypes. Lower values ASTAB measure achieved by Karan 16, NDB943. Biplot graphical analysis as per 40.4% of variation of the measures exhibited MASV1 clubbed with ASTAB, EV, SIPC, Za, W6, WAASB and MASV measures. Measure IPCA1 clubbed with SI corresponding yield based.  W2, W3, W4 measures observed in different group.  For the second-year lower value of WAASB measure had observed for PL891, KB1843, NDB943. Ranking of genotypes as per Superiority index found Karan16, UPB1086 as of stable performance with high yield. MASV1 and MASV identified Karan16, DWRB216 genotypes of choice for these locations. Barley genotypes Karan16, DWRB216 were selected as per values of ASTAB measure accounted AMMI analysis with BLUP of genotypes yield values. About 78.1% of variation of the measures under biplot analysis observed MASV1 grouped with ASTAB, EV, SIPC, and MASV. While Za joined together with W2, W3, W4, W5, W6, WAASB to form separate group.

Simultaneous Use of AMMI Model and Yield for Stability Analysis of Wheat Genotypes Evaluated Under Central Zone of the India

2020 ◽  
Vol 2 (6) ◽  
Author(s):  
Ajay Verma ◽  
Gyanendra Pratap Singh
Keyword(s):  
Central Zone ◽  
High Yield ◽  
First Year ◽  
Wheat Genotypes ◽  
Gxe Interaction ◽  
Ammi Analysis ◽  
Stable Performance ◽  
Ammi Model ◽  
Simultaneous Use ◽  
High Degree

AMMI analysis had observed highly significant effects of environment (E), GxE interaction and genotypes (G) during 2018-19 and 2019-20 years of study. Suitability of PBW822, HI8811 & HI8713 genotypes as compared to HD3345 by WAASB measure for first year. Superiority index found HD3345, PBW822 & NIDW1158 as of stable performance with high yield. PRVG measures settled for HI8811, GW322 & HI 8737 and MHPRVG considered HI8811, HI8713 & GW322 wheat genotypes. All negative values of correlations exhibited by SI measure whereas WAASB measure exhibited direct relationships as well as negative values with SI, PRVG, MHPRVG and yield. WAASB measure observed suitability of GW513, HI1636 & MACS6747 wheat genotypes for the second year. Superiority index found GW513, HI1636 & HI1544 as of stable performance along with high yield. PRVG as well as MHPRVG measures observed suitability of GW513, HI1636, & MP1361 while HD3377 as unstable wheat genotype. SI measure had expressed only indirect relations of high degree with other measures except of positive values with yield, PRVG and MHPRVG. Measure WAASB had exhibited direct relations with most of measures along with negative correlation for SI, yield, PRVG and MHPRVG values. Stability measures by simultaneous use of AMMI analysis and average yield of genotypes would be more meaningful as compared to measures based either on the AMMI or yield only.

scholarly journals Malt Barley Genotypes Assessed by Analytic Adaptability Measures for NWPZ of the Country

2021 ◽  
Vol 4 (2) ◽  
Keyword(s):  
Graphical Analysis ◽  
Harmonic Mean ◽  
Relative Performance ◽  
First Year ◽  
Gxe Interaction ◽  
Environment Effects ◽  
Cropping Season ◽  
Malt Barley ◽  
Barley Genotypes ◽  
Analysis Environment

Highly significant effects of the environment (E), genotypes (G), and GxE interaction had been observed by AMMI analysis. Environment explained 51.4% whereas GxE interaction accounted for 22.1% of treatment variations in yield during first year. Harmonic Mean of Genotypic Values (HMGV) expressed higher values for DWRB160, DWRB184, and BH902. Ranking of genotype as per IPCA-1 were BH902, DWRB182, DWRB101. While IPCA-2, selected DWRB101, DWRB123, DWRB184 genotypes. Values of ASV1 selected DWRB101, DWRB182, BH902 and ASV identified DWRB101, DWRB123, DWRB182 barley genotypes. Adaptability measures Harmonic Mean of Relative Performance of Genotypic Values (HMPRVG) and Relative Performance of Genotypic Values (RPGV) identified DWRB160, DWRB184, and BH902 as the genotypes of performance among the locations. Biplot graphical analysis exhibited adaptability measures PRVG, HMPRVG along with IPC3, mean, GM, HM grouped in a cluster. During 2019-20 cropping season Environment effects accounted 79.7% whereas GxE interaction contributed for 7.7% % of treatment variations in yield. HMGV expressed higher values for DWRB196, DWRB123, and RD2849. IPCA-1 scores, desired ranking of genotypes was DWRB182, PL908, RD2849. While IPCA-2 pointed towards PL908, RD2849, DWRB196, as genotypes of choice. Analytic measures ASV and ASV1 selected PL908, RD2849, DWRB123 barley genotypes. HMRPGV along with PRVG settled for DWRB196, DWRB123, and RD2849. Adaptability measures PRVG, HMPRVG clustered with mean, GM, HM and observed in different quadrant of biplot analysis.

Genetic progress in upland rice breeding program for grain yield and plant height

2021 ◽  
Vol 45 ◽  
Author(s):  
Amanda Mendes de Moura ◽  
Flávia Barbosa Silva Botelho ◽  
Laís Moretti Tomé ◽  
Cinthia Souza Rodrigues ◽  
Camila Soares Cardoso da Silva ◽  
...  
Keyword(s):  
Grain Yield ◽  
Plant Height ◽  
Mixed Model ◽  
Upland Rice ◽  
Breeding Program ◽  
High Yield ◽  
Joint Analysis ◽  
Rice Breeding ◽  
Genetic Progress ◽  
Mixed Model Approach

ABSTRACT In the context of plant breeding programs, it is necessary to evaluate the efficiency of genotype selection over successive years. However, evaluating the genotype selection efficiency is not an easy task, since there is not just a single way to precede it. Besides that, the programs need to be dynamic; that is, they should be able to track the introduction and discard of genotypes each year. As a result, the available data is quite unbalanced, leading to difficulties in certain analyses. Thus, the present study aims to propose some approaches to verify the genetic progress in the preliminary trial of the Federal University of Lavras (UFLA) upland rice breeding program. We utilized mixed models for grain yield and plant height. Trials were performed with a total of 120 genotypes in seven environments, defined by the interaction between locations and years. Due to the imbalance in the available data, the mixed model approach, i.e., Restricted Maximum Likelihood/Best Linear Unbiased Prediction (REML/BLUP), was adopted for the joint analysis. Besides the genetic and phenotypic parameters, the expected gains were also obtained with the selection, genetic progress, renewal rate (RR%), and dynamism of preliminary trials. The efficiency of the selection of superior genotypes per year was verified, with genetic progress favorable for reducing the medium-sized plants associated with high yield.

scholarly journals A Fumonisin Prevention Tool for Targeting and Ranking Agroclimatic Conditions Favoring Exposure in French Maize-Growing Areas

Toxins ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 214
Author(s):  
Agathe Roucou ◽  
Christophe Bergez ◽  
Benoît Méléard ◽  
Béatrice Orlando
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Fusarium Verticillioides ◽  
Agricultural Practices ◽  
Climatic Conditions ◽  
Agricultural Cooperatives ◽  
Mixed Model Approach ◽  
Food And Feed ◽  
Model Approach

The levels of fumonisins (FUMO)—mycotoxins produced by Fusarium verticillioides—in maize for food and feed are subject to European Union regulations. Compliance with the regulations requires the targeting of, among others, the agroclimatic factors influencing fungal contamination and FUMO production. Arvalis-Institut du végétal has created a national, multiyear database for maize, based on field survey data collected since 2003. This database contains information about agricultural practices, climatic conditions and FUMO concentrations at harvest for 738 maize fields distributed throughout French maize-growing regions. A linear mixed model approach highlights the presence of borers and the use of a late variety, high temperatures in July and October, and a water deficit during the maize cycle as creating conditions favoring maize contamination with Fusarium verticillioides. It is thus possible to target a combination of risk factors, consisting of this climatic sequence associated with agricultural practices of interest. The effects of the various possible agroclimatic combinations can be compared, grouped and classified as promoting very low to high FUMO concentrations, possibly exceeding the regulatory threshold. These findings should facilitate the creation of a national, informative and easy-to-use prevention tool for producers and agricultural cooperatives to manage the sanitary quality of their harvest.

scholarly journals Male and female fertility and hatchability in chickens: a longitudinal mixed model approach

2004 ◽  
Vol 83 (8) ◽  
pp. 1253-1259 ◽  
Author(s):  
R.L. Sapp ◽  
R. Rekaya ◽  
I. Misztal ◽  
T. Wing
Keyword(s):  
Mixed Model ◽  
Female Fertility ◽  
Male And Female ◽  
Mixed Model Approach ◽  
Model Approach
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