Genetic studies of soybean [Glycine max (L.) Merr.] response to seed storage stress factors

Abstract

<p>Soybean [<em>Glycine max</em> (L.) Merr.] responded differently to storage stress factors. This research work aimed at assessing genetic potentials of fifteen soybean varieties to storage stress via accelerated aging technique and grouping them based on their levels of tolerance to storage stress using simple sequence repeat (SSR). Tolerance of the seed of 15 soybean varieties to storage stress was assessed by subjecting them to accelerated aging for 0, 6, 12, and 24 hours at 42 °C temperature and 100 % relative humidity (RH), after which their quality was assessed to determine their tolerance to storage stress. Same varieties were also stored for 6 months under ambient environment at 65 ± 5 % R.H and 25 ± 2 °C and they were genotyped with 19 simple sequence repeat (SSR) markers. The varieties were grouped on the basis of their levels of tolerance to storage stress. The principal components analysis (PCA) showed that germination rate index (GRI) and germination index (GI) were the major indices responsible for the significant variation in the seedling vigor characters. TGX1835-10E and TGX1448-2E were identified as varieties with good storage ability and therefore recommended for storage improvement in soybean breeding programs. Six SSR markers (Satt 565, Satt 175, Satt 281, Satt 600, Satt 160 and Satt 281) were identified as candidate markers for detection of alleles for tolerance to storage stress.</p>

Response of groundnut (Arachis hypogaea L.) genotypes to accelerated ageing treatment

“…Kapoor et al (2010) has reported that varieties of chickpea responded differently with reference to physiological and biochemical changes occurring due to seed ageing. Similarly, Okunlola et al, (2020) attributed significant variation in germination and other seedling vigor parameters recorded under artificial aging treatments to different genetic makeup of the soybean varieties.…”

“…(Akande et al, 2012) where Nx is the number of normal seedlings that emerged on day x after seeding and DAP is days after planting Germination Rate Index (GRI) This reflects the percentage of germination on each day of the germination period and was calculated as follows: Esechi, 1994) where, G = germination on each day after seed placement 1, 2, x = corresponding day of germination Seedling vigour Index (SVI) The estimation of the seedling vigour index, involved the measurement of seedling length of five randomly selected seedlings of each replicate from the soil level at 8 and 14 days after planting. The SVI was then calculated as follows: SVI = " % $ * #++ (Adetumbi et al, 2019) Accelerated ageing procedure with corresponding germination and vigor test Clean seeds of the twelve genotypes were selected and subjected to accelerated ageing using a modified procedure of Ghosh et al (2013) and Okunlola et al (2020). A hundred seeds in three replicates of each genotype was counted and placed in an improvised plastic ageing box (11.0 × 11.0 × 3.5 cm), ensuring the seeds form a single layer.…”

Characterization of African Yam Bean (Sphenostylis stenocarpa) Mutant Lines using Phenotypic Markers

“…To validate the extent of genetic variability in germplasm, some scientists have used many statistical techniques, among which are principal components (PCA) and cluster analyses. PCA and cluster analyses are statistical methods for the characterization of germplasm based on their origins, genetic constitutions, and contributions of traits to the total variations (Ogunbodede, 1997;Akinyosoye et al, 2017;Okunlola et al, 2020). PCA and cluster analyses have been used to determine the extent of phenotypic variability in germplasm collections, namely maize, mungbean, pea, soybean, alfalfa, and AYB, among others (Matus et al, 1999;Akinyosoye et al, 2017;Okunlola et al, 2020).…”

“…PCA and cluster analyses are statistical methods for the characterization of germplasm based on their origins, genetic constitutions, and contributions of traits to the total variations (Ogunbodede, 1997;Akinyosoye et al, 2017;Okunlola et al, 2020). PCA and cluster analyses have been used to determine the extent of phenotypic variability in germplasm collections, namely maize, mungbean, pea, soybean, alfalfa, and AYB, among others (Matus et al, 1999;Akinyosoye et al, 2017;Okunlola et al, 2020). Also, understanding the relationships among important traits is very useful in indirect selection (Kumar et al, 2015;Sesay et al, 2017).…”