Identification of important morphological traits in Mozambican sorghum [Sorghum bicolor (L.) Moench] germplasm using multivariate analysis

Abstract

Classification of sorghum [Sorghum bicolor (L) Moench] breeding material based on multiple crucial characters is important towards the possible formation of homogeneous groups of genotypes and groups that can be exploited in the identification of parents for use in a breeding program. The objective was to determine the morphological characters that distinguish desirable breeding material and group the genotypes of sorghum according to similarity. Principal component analysis (PCA) and cluster analysis were used to establish the relationships among germplasm and the Shannon Diversity index was used to quantify the level of diversity. The experiment involving 26 sorghum genotypes was conducted at Sussundenga Research Station across two seasons and laid out in a 13 × 2 alpha lattice design with four replications. Cluster analysis grouped genotypes into four clusters based on 15 evaluated traits. Five principal components cumulatively accounting for 58.5% of the total variation were estimated from the PCA analysis. The results showed that genotypes 150B, IS 14257R, LARSVYT 46B, TX 631B, TX 630B and 8601B were the early maturity while for late maturity genotypes were MA 6B, A 6352R, ICSA 19B and MZ 30R. The genotypes IS 7179R, SPL 9B, A 6353R, SPL 38B, SDS 6013R and MZ 2R showed a potential for grain yield improvement. Other genotypes presented potential for drought tolerance and birds attack. The multivariate analyses clearly showed the grouping of the genotypes according to the characters outlined in the study. These results have implications in selecting parents for use in sorghum breeding program.

Cluster analysis and genetic variability of sweet sorghum (Sorghum bicolor L. Moench) genotypes using agro-morphological and juice quality traits

“…Results in Table3revealed that genotypes; Willy, William, and Atlas out yielded high values of juice extraction % (34.28, 39.82, and 4.69 %) and juice yield (4.87, 5.24 and 4.69 ton/fed), respectively indicating their magnitude as promising genotypes that may be used in breeding programs of sweet sorghum. The current results are harmonized with many previous investigations reported byAbd El-Raheem et al (2010),Rao et al (2013),Erdurmus et al (2018),Mulima et al (2018),Khidr et al (2021) andYücel et al (2022) who confirmed that the considerable variability among the assessed sweet sorghum genotypes considering the juice quality readings provides a real chance to improve the juice productivity of sweet sorghum crop and its extracts and other products.…”

“…Genotypes that evolved in the same area were grouped into different clusters. Genetic divergence among sweet sorghum genotypes using cluster analysis was reported by (Zhan et al, 2012;Jain and Patel, 2016and Mulima et al, 2018and Naoura et al, 2020.…”

“…Estimation of heritability and genetic advance is a pivotal point to identify the traits amenable to improvement through visual selection. Singh (2001), Zou et al, (2011), Tomar et al, (2012), Mulima et al, (2018), Umakanthm et al, (2019) and Naoura et al, (2020) reported that the heritability estimates would not be practically useful without considering genetic advance. The presence of genetic variability among aimed genotypes is the cornerstone of any targeted genetic improvement of the breeding program.…”

“…(sucrose % and purity %) . In the light of current results, it is exhibited the presence of considerable genetic variability among the aimed sweet sorghum genotypes gives the ability to achieve sufficient improvement of sweet sorghum through the hybridization among genotypes taken from different clusters to get desirable traits (Jain and Patel, 2016;Mulima et al, 2018;Umakanth et al, 2019 andNaoura et al, 2020). taken from different clusters to get desirable traits (Jain and Patel, 2016;Mulima et al, 2018;Umakanth et al, 2019 andNaoura et al, 2020).…”

Variation on morphology and spore characters of Dicranopteris and Sticherus (Gleicheniaceae) from Rokan Hulu District, Riau, Indonesia

“…The eigenvalues indicated the variance accounted for by the corresponding principal components or eigenvectors. Principal component analysis has been known as complementary to cluster analysis (Mulima et al 2018). Therefore, combination of these two methods was commonly applied in plant systematics studies in various plant taxa at any taxonomic level, from species (Fitriana and Susandarini 2019;Singh et al 2020), genus (Alzahrani et al 2021), to family (Arogundade and Adedeji 2019).…”