Multivariate genetic analyses unveil the complexity of grain yield and attributing traits diversity in Oryza sativa L. landraces from North-Eastern India
In the North-Eastern region of India, rice stands as the predominant staple,
with diverse cultivars evolving over the past six decades. This study syste-
matically evaluated 20 rice landraces, analyzing eleven variables related to
yield and its attributing traits. The aim was to identify promising genotypes
for potential breeding programs and to ascertain the minimum number of
components essential for explaining the total diversity. Among the eleven
principal components (PCs) examined, four PCs exhibited eigenvalues sur-
passing 1.0, collectively contributing to 80.45% of the total variability in the
traits. PC1, which explained 31.19% of the overall variance, was associated
with plant height, days to 50% flowering, panicle length, grain breadth, and
grain length-to-breadth ratio. Utilizing cluster analysis, the 20 rice landraces
were categorized into seven distinct clusters. Maximum inter-cluster diver-
gence was observed between clusters VI and I, as well as clusters VI and V,
indicating greater genetic distinctiveness among genotypes in these clus-
ters compared to others. Notably, rice landraces such as Borosolpana,
Phougak, Satyaranjan, Kakcheng Phou, Moniram, Kanaklata, and Bahadur
were identified as genetically divergent. These genotypes hold promise for
generating segregating populations, serving as valuable source materials
for targeted yield improvement through meticulous selection, as indicated
by inter-cluster distances.
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Description:
In the North-Eastern region of India, rice stands as the predominant staple,
with diverse cultivars evolving over the past six decades. This study syste-
matically evaluated 20 rice landraces, analyzing eleven variables related to
yield and its attributing traits. The aim was to identify promising genotypes
for potential breeding programs and to ascertain the minimum number of
components essential for explaining the total diversity. Among the eleven
principal components (PCs) examined, four PCs exhibited eigenvalues sur-
passing 1.0, collectively contributing to 80.45% of the total variability in the
traits. PC1, which explained 31.19% of the overall variance, was associated
with plant height, days to 50% flowering, panicle length, grain breadth, and
grain length-to-breadth ratio. Utilizing cluster analysis, the 20 rice landraces
were categorized into seven distinct clusters. Maximum inter-cluster diver-
gence was observed between clusters VI and I, as well as clusters VI and V,
indicating greater genetic distinctiveness among genotypes in these clus-
ters compared to others. Notably, rice landraces such as Borosolpana,
Phougak, Satyaranjan, Kakcheng Phou, Moniram, Kanaklata, and Bahadur
were identified as genetically divergent. These genotypes hold promise for
generating segregating populations, serving as valuable source materials
for targeted yield improvement through meticulous selection, as indicated
by inter-cluster distances.