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Clustering based on morphological marker through linear discriminant analysis targeting potent yield enhancers in mini-core collections of chickpea (Cicer arietinum L.)

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Abstract

Mini core collections of chickpea, which represent the entire spectrum of diversity were evaluated and discriminated based on the morphological marker, corolla colour. With this objective, 71 accessions were subjected to discriminant function analysis and principal component analysis. From the box’s M test and normal Q–Q plot, the curve was normally distributed and the percentage of separation achieved was 83.12%, 9.54% and 7.34% for LD1, LD2 and LD3, respectively. Confusion matrix indicated that the accuracy level was 72.9% and 56.5% for the training and testing data sets, respectively. The results indicated that corolla colour might not be an effective parameter in discriminating chickpea accessions. From PCA, three components contributed to 72.41% of variability with the maximum PC 1 (45.69%). Factor analysis disclosed that the first two factors contributed to 80% of the variation and the first one is termed as ‘yield predictors’ and the second factor as ‘morphotype predictors’. The accessions ICC4567 and ICC2884 deserve due attention for enhancing yield while ICC4182 could be adjudged as a yield enhancer as well as a superior material for chickpea ideotype breeding. The communalities for all the traits were high [0.9967 (Days to 50% flowering) to 0.6720 (Pod yield per plant)] and indicated the reliability of the investigated variables. The outcomes of the current research adjudged that due weight had to be given during selection upon the mentioned traits and accessions in chickpea yield enhancing projects.

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Acknowledgements

The authors express their gratitude to Dr. R.S. Paroda Gene Bank, ICRISAT, Hyderabad and Ramiah Gene Bank, TNAU, Coimbatore for sharing the seeds of the chickpea mini-core collection to carry out the present research work.

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The authors declare that no funds, grants, or other support were received during the entire research work.

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Authors and Affiliations

  1. Department of Genetics and Plant Breeding, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, 641 003, India

    C. Deepika, V. Thiruvengadam, M. Vanitha & V. Nithya

  2. Department of Genetics and Plant Breeding, Agricultural College and Research Institute, Kudumiyanmalai, Pudukkottai, Tamil Nadu, 622 104, India

    V. Thiruvengadam

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  1. C. Deepika
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Contributions

All authors contributed to study conception and design. Performance of field experiments, data analysis, writing up the manuscript and following up the publication with the journal (correspondence) were performed by CD. Data analysis and upgrading the manuscript were done by VT. Performance of the field experiment was done by MV and VN. The first draft of the manuscript was written by CD and all authors commented on previous versions of the manuscript. The authors read and approved the final version of the manuscript.

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Correspondence to C. Deepika.

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Deepika, C., Thiruvengadam, V., Vanitha, M. et al. Clustering based on morphological marker through linear discriminant analysis targeting potent yield enhancers in mini-core collections of chickpea (Cicer arietinum L.). Vegetos (2023). https://doi.org/10.1007/s42535-023-00716-z

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