Banner
Current IssueEditorial BoardOnline First ArticlesArchive
Current IssueEditorial BoardOnline First ArticlesArchive

Research Article

volume 54 issue 4 (august 2020) : 495-500,   Doi: 10.18805/IJARe.A-5365

BLUP’s to Quantify Yield Gain under Wheat Coordinated System for Northern Hills Zone by Factor Analytic Approach

A
Ajay Verma
R
Ravish Chatrath
G
G.P. Singh
1ICAR-Indian Institute of Wheat and Barley Research, Karnal-132 001, Haryana, India.
Cite article:- Verma Ajay, Chatrath Ravish, Singh G.P. (2020). BLUP’s to Quantify Yield Gain under Wheat Coordinated System for Northern Hills Zone by Factor Analytic Approach . Indian Journal of Agricultural Research. 54(4): 495-500. doi: 10.18805/IJARe.A-5365.

ABSTRACT

Trend in linear manner has been observed for wheat production under irrigated timely and late sown along with rainfed timely sown trials of Northern Hills Zone of country. Production elevated to the level of 53, 30 and 36q/ha for irrigated timely, late sown and rainfed timely sown trials. By the end of considered period 0.81, 0.61 and 2.06 quintal per hectare could be added in subsequent trials. Low values of R2 for irrigated timely and late sown trials suggested marginal increase in linear fashion in production values. More over consistent improvement observed in rainfed timely sown trials as justified by highly significant value of R2.

REFERENCES


  1. Baretta D., Nardino, M., Carvalho, I.R., Pelegrin, A.J., Ferrari, M., Szareski, V.J., (2017). Estimates of genetic parameters and genotypic values prediction in maize landrace populations by REML/BLUP Procedure. Genetics and Molecular Research. 16: 1-14.

  2. Borges V, Ferreira PV, Soares L, Santos GM, Santos AMM. (2010). Sweet potato clone selection by REML/BLUP procedure. Acta Sci Agron. 32(4):643–649

  3. Burgueño J., J. Crossa, P.L. Cornelius and R.C. Yang. (2008). Using factor analytic models for joining environments and genotypes without crossover genotype x environment interac­tion. Crop Sci, 48:1291–1305. 

  4. Crespo-Herrera, L.A., J. Crossa, J. Huerta-Espino, E. Autrique, S. Mondal, G. Velu,. et al (2017). Genetic yield gains in CIM­MYT’s international Elite Spring Wheat Yield Trials by modeling the genotype x environment interaction. Crop Sci. 57:789–801. 

  5. de Pelegrin, A.J., Carvalho, I.R., Nunes, A.C.P., Demari, G.H., Szareski, V.J., et al (2017). Adaptability, stability and multivariate selection by mixed Models. American Journal of Plant Sciences. 8: 3324.

  6. Eileen Azevedo Santos, Alexandre Pio Viana, Josie Cloviane de Oliveira Freitas, et al (2015). Genotype selection by REML/BLUP methodology in a segregating population from an interspecific Passiflora spp. Crossing. Euphytica. 204:1–11.

  7. Gustavo H.F. Oliveira, Camila B. Amaral, Flávia A.M. Silva, Sophia M.F. Dutra, et al (2016). Mixed models and multivariate analysis for selection of superior maize genotypes. Chilean Journal of Agricultural Research 76:427-431.

  8. Mohan D., Tiwari, V. and Gupta R. K. (2017). Progression in yield and value addition of Indian bread wheat – An Analysis. Indian J. Genet. 77(1): 16-24.

  9. Mendes F.F.; Guimarães, L.J.M.; Souza, J.C.; Guimarães, P.E.O.; Pacheco, C.A.P.; et al (2012). Adaptability and stability of maize varieties using mixed models methodology. Crop Breeding and Applied Biotechnology. 12: 111-117.

  10. Olivoto T., Nardino, M., Carvalho, I.R., Follmann, D.N., Ferrari, M., Szareski, V.J., et al (2017). REML/BLUP and sequential path analysis in estimating genotypic values and inter relationships among simple maize grain yield-related traits. Genetics and Molecular Research. 16: 1-10.

  11. Piepho HP, Möhring J, Melchinger AE and Büchse A. (2008). BLUP for phenotypic selection in plant breeding and variety testing. Euphytica. 161: 209-228.

  12. Piepho H.P. (1998). Empirical best linear unbiased prediction in cul­tivar trials using factor analytic variance–covariance structures. Theor. Appl. Genet. 97:195–201. 

  13. Smith A., A. Ganesalingam, H. Kuchel and B.R. Cullis. (2015). Factor analytic mixed models for the provision of grower infor­mation from national crop variety testing programs. Theor. Appl. Genet. 128:55–72. 
Published In
Indian Journal of Agricultural Research
Article Metrics
Metrics Icon
0
Views
0
Citations
Reviewed By
Share Article
Download Article
In this Article
    Contact us
    Follow us

    Research Article

    volume 54 issue 4 (august 2020) : 495-500,   Doi: 10.18805/IJARe.A-5365

    BLUP’s to Quantify Yield Gain under Wheat Coordinated System for Northern Hills Zone by Factor Analytic Approach

    A
    Ajay Verma
    R
    Ravish Chatrath
    G
    G.P. Singh
    1ICAR-Indian Institute of Wheat and Barley Research, Karnal-132 001, Haryana, India.
    Cite article:- Verma Ajay, Chatrath Ravish, Singh G.P. (2020). BLUP’s to Quantify Yield Gain under Wheat Coordinated System for Northern Hills Zone by Factor Analytic Approach . Indian Journal of Agricultural Research. 54(4): 495-500. doi: 10.18805/IJARe.A-5365.

    ABSTRACT

    Trend in linear manner has been observed for wheat production under irrigated timely and late sown along with rainfed timely sown trials of Northern Hills Zone of country. Production elevated to the level of 53, 30 and 36q/ha for irrigated timely, late sown and rainfed timely sown trials. By the end of considered period 0.81, 0.61 and 2.06 quintal per hectare could be added in subsequent trials. Low values of R2 for irrigated timely and late sown trials suggested marginal increase in linear fashion in production values. More over consistent improvement observed in rainfed timely sown trials as justified by highly significant value of R2.

    REFERENCES


    1. Baretta D., Nardino, M., Carvalho, I.R., Pelegrin, A.J., Ferrari, M., Szareski, V.J., (2017). Estimates of genetic parameters and genotypic values prediction in maize landrace populations by REML/BLUP Procedure. Genetics and Molecular Research. 16: 1-14.

    2. Borges V, Ferreira PV, Soares L, Santos GM, Santos AMM. (2010). Sweet potato clone selection by REML/BLUP procedure. Acta Sci Agron. 32(4):643–649

    3. Burgueño J., J. Crossa, P.L. Cornelius and R.C. Yang. (2008). Using factor analytic models for joining environments and genotypes without crossover genotype x environment interac­tion. Crop Sci, 48:1291–1305. 

    4. Crespo-Herrera, L.A., J. Crossa, J. Huerta-Espino, E. Autrique, S. Mondal, G. Velu,. et al (2017). Genetic yield gains in CIM­MYT’s international Elite Spring Wheat Yield Trials by modeling the genotype x environment interaction. Crop Sci. 57:789–801. 

    5. de Pelegrin, A.J., Carvalho, I.R., Nunes, A.C.P., Demari, G.H., Szareski, V.J., et al (2017). Adaptability, stability and multivariate selection by mixed Models. American Journal of Plant Sciences. 8: 3324.

    6. Eileen Azevedo Santos, Alexandre Pio Viana, Josie Cloviane de Oliveira Freitas, et al (2015). Genotype selection by REML/BLUP methodology in a segregating population from an interspecific Passiflora spp. Crossing. Euphytica. 204:1–11.

    7. Gustavo H.F. Oliveira, Camila B. Amaral, Flávia A.M. Silva, Sophia M.F. Dutra, et al (2016). Mixed models and multivariate analysis for selection of superior maize genotypes. Chilean Journal of Agricultural Research 76:427-431.

    8. Mohan D., Tiwari, V. and Gupta R. K. (2017). Progression in yield and value addition of Indian bread wheat – An Analysis. Indian J. Genet. 77(1): 16-24.

    9. Mendes F.F.; Guimarães, L.J.M.; Souza, J.C.; Guimarães, P.E.O.; Pacheco, C.A.P.; et al (2012). Adaptability and stability of maize varieties using mixed models methodology. Crop Breeding and Applied Biotechnology. 12: 111-117.

    10. Olivoto T., Nardino, M., Carvalho, I.R., Follmann, D.N., Ferrari, M., Szareski, V.J., et al (2017). REML/BLUP and sequential path analysis in estimating genotypic values and inter relationships among simple maize grain yield-related traits. Genetics and Molecular Research. 16: 1-10.

    11. Piepho HP, Möhring J, Melchinger AE and Büchse A. (2008). BLUP for phenotypic selection in plant breeding and variety testing. Euphytica. 161: 209-228.

    12. Piepho H.P. (1998). Empirical best linear unbiased prediction in cul­tivar trials using factor analytic variance–covariance structures. Theor. Appl. Genet. 97:195–201. 

    13. Smith A., A. Ganesalingam, H. Kuchel and B.R. Cullis. (2015). Factor analytic mixed models for the provision of grower infor­mation from national crop variety testing programs. Theor. Appl. Genet. 128:55–72. 
    In this Article
      Contact us
      Follow us
      Published In
      Indian Journal of Agricultural Research

      Editorial Board

      View all (0)