Acta Scientific Agriculture (ISSN: 2581-365X)

Research ArticleVolume 5 Issue 6

Selection for Improving Field Resistance to Capsicum Chlorosis Virus and Yield-related Traits Using Selection Indices in Peanut Breeding

Jetsada Authrapun1, Udomsak Lertsuchatavanich2 and Dingming Kang1*

1College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
2Department of Plant Pathology, Faculty of Agriculture, Kasetsart University, Bangkok, Thailand

*Corresponding Author: Dingming Kang, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China.

Received: April 15, 2021; Published: May 11, 2021

Citation: Dingming Kang., et al. “Selection for Improving Field Resistance to Capsicum Chlorosis Virus and Yield-related Traits Using Selection Indices in Peanut Breeding”. Acta Scientific Agriculture 5.6 (2021): 02-10.


  Capsicum chlorosis virus (CaCV) is a pathogen causing a severe disease in peanut. Therefore, the aim of this study was to select peanut genotypes for improving field resistance to CaCV disease and yield using two selection indices, including a multitrait index based on factor analysis and ideotype-design (FAI-BLUP index) and a multi-trait stability index (MTSI). The 121 genotypes were evaluated under natural infection at the disease hotspots in Thailand from 2017 to 2018, totalling three environments. The experimental design was a randomized complete block with two replications. The 11 traits related to disease resistance and yields such as percentage of disease incidence (DisInc), the area under disease progress curve (AUDPC), pod yield (PY), harvest index (HI), number of pod per plant (PdPt), pod weight per plant (PWPt), seed weight per plant (SWPt), shelling percentage (SH), hundred seed weight (100SW), seed length (SdLgth) and seed width (SdWdth) were collected and used for simultaneous selection. After the selection considering a selection intensity of 15%, the selection differentials and selection gains obtained by the FAI-BLUP and MTSI indices were positive for almost yield-related traits except for SH and negative for DisInc and AUDPC, which want to be increased and decreased, respectively, indicating that these selection indices provide desirable genetic gains for all traits simultaneously. The genotypes selected by the two selection indices had a good performance for both disease resistance and yield characters. The FAI-BLUP and MTSI indices are efficient method for multi-trait selection and can be used as a tool in selecting promising genotypes based on several targeted traits in plant breeding programs.

Keywords: Arachis hypogaea L; Field Resistance; FAI-BLUP Index; Multi-trait Stability Index; Selection Gain


  1. Pandey KM., et al. “Translational genomics for achieving higher genetic gains in groundnut”. Theoretical and Applied Genetics 133 (2020): 1679-1702.
  2. Sreenivasulu P., et al. “Virus Diseases of Groundnut”. International Institute of Tropical Agriculture, Ibadan, Nigeria (2008): 52.
  3. Chen K., et al. “Characterization of a new strain of Capsicum chlorosis virus from peanut (Arachis hypogaea L.) in China”. Journal of Phytopathology 155 (2007): 178-181.
  4. Chiemsombat P., et al. “Biological and molecular characterization of tospoviruses in Thailand”. Archives of Virology 153 (2008): 571-577.
  5. Riley D G., et al. “Thrips vectors of Tospoviruses”. Journal of Integrated Pest Management2 (2011): 1-10.
  6. Srinivasan R., et al. “Resistance to thrips in peanut and implications for management of thrips and thrips-transmitted Orthotospoviruses in peanut”. Frontiers in Plant Science 9 (2018): 1604.
  7. Acquaah G. “Principles of Plant Genetics and Breeding 2ndedition”. Wiley and Sons, Hoboken, NJ, USA (2012): 740.
  8. Hazel L N. “The genetic basis for constructing selection indexes”. Genetics 28 (1943): 476-490.
  9. Smith H F. “A discriminant function for plant selection”. Annals of Eugenics 7 (1936): 240-250.
  10. Cerón-Rojas JJ and Crossa J. “Linear selection indices in modern plant breeding”. Springer, Cham, Switzerland (2018): 256.
  11. Cerón-Rojas JJ., et al. “A selection index method based on eigen analysis”. Crop Science 46 (2006): 1711-1721.
  12. Prunier J G., et al. “Multicollinearity in spatial genetics: separating the wheat from the chaff using commonality analyses”. Molecular Ecology 24 (2015): 263-283.
  13. Rocha J R d A S d C., et al. “Multitrait index based on factor analysis and ideotype-design: proposal and application on elephant grass breeding for bioenergy”. GCB Bioenergy 10 (2018): 52-60.
  14. Olivoto T., et al. “Mean performance and stability in multi-environment trials II: selection based on multiple traits”. Agronomy Journal 111 (2019): 1-9.
  15. Silva M J., et al. “Evaluation of the potential of lines and hybrids of biomass sorghum”. Industrial Crops and Products 125 (2018): 379-385.
  16. Woyann L G., et al. “Multiple-trait selection of soybean for biodiesel production in Brazil”. Industrial Crops and Products 140 (2019): 1-7.
  17. Puttha R., et al. “Heritability phenotypic and genotypic correlation of peanut bud necrosis virus resistance and agronomic traits in peanut”. Asian Journal of Plant Sciences 7 (2008): 276-283.
  18. Jeger M J and Viljanea-Rollinson S L H. “The use of the area under the disease progress curve (AUDPC) to assess quantitative disease resistance in crop cultivars”. Theoretical and Applied Genetics 102 (2001): 32-40.
  19. Henderson C R “Best linear unbiased prediction under a selection model”. Biometrics 31 (1975): 423-447.
  20. Olivoto T and Lúcio AD. “metan: an R package for multi-environment trial analysis”. Methods in Ecology and Evolution 11 (2020): 783-789.
  21. Piepho H P., et al. “BLUP for phenotypic selection in plant breeding and variety testing”. Euphytica 161 (2008): 209-228.
  22. Pattee H E., et al. “Parent selection in breeding for roasted peanut flavor quality”. Peanut Science 28 (2001): 51-58.
  23. Pattee H E., et al. “Prediction of parental genetic compatibility to enhance flavor attribute of peanuts”. ACS Symposium Series 829 (2002): 217-230.
  24. Milla-Lewis S R and Isleib T G. “Best linear unbiased prediction of breeding values for tomato spotted wilt virus (TSWV) incidence in virginia-type peanuts”. Peanut Science 32 (2005): 57-67.
  25. Burdon R D and Li Y. “Genotype-environment interaction involving site differences in expression of genetic variation along with genotypic rank changes: simulations of economic significance”. Tree Genetics and Genomes 15 (2019): 1-10.

Copyright: © 2021 Dingming Kang., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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