Genetic variability and genome‐wide marker association studies for starch traits contributing to low glycaemic index in pearl millet

Yadav, Chandra Bhan; Srivastava, Rakesh K.; Beynon, Sarah; Englyst, Klaus; Gangashetty, Prakash; Yadav, Rattan

doi:10.1002/fes3.341

Cited by 7 publications

(7 citation statements)

References 40 publications

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“…No correlation of starch traits with yield was evident, indicating yield is not affected by these component starch traits. This confirms that the best hybrids identified based on starch traits in our earlier study by Yadav et al. (2022) hold high promise for further on-farm testing, release, and promotion to combat type 2 diabetes ( Table 4 ).…”

Section: Resultssupporting

confidence: 80%

“…The experimental pearl millet hybrids used in this study comprised 20 lines identified from within the 166 PMiGAP accessions, primarily based on the higher slowly digestible starch (SDS) and resistant starch (RS) content reported by Yadav et al. (2022) in their grains ( Supplementary Table S1 ).…”

Section: Methodsmentioning

confidence: 99%

“…Pearl millet grain starch was digested to quantify the rapidly digestible starch (RDS), SDS, and RS fractions ( Englyst et al., 1992 ; Englyst et al., 1999 ; Yadav et al., 2022 ). All analyses for starch measurements were performed in duplicate (two replicates) for each hybrid from the milled samples.…”

Section: Methodsmentioning

confidence: 99%

“…The samples were milled in a centrifugal miller with a 0.5-mm sieve (Fritsch Pulverisette). After the pretreatment of samples under gastric conditions, the samples were digested using amylolytic enzymes under condition-controlled conditions as described by Yadav et al. (2022) .…”

Section: Methodsmentioning

confidence: 99%

“…The current study focused on testing pearl millet hybrids on parental lines that are known to possess the best combination of starch traits ( Yadav et al., 2022 ). The study’s primary aim was to understand the effects of G×E on starch, yield, and grain nutritional traits and if they can be combined in future varieties.…”

Section: Introductionmentioning

confidence: 99%

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Genotype-by-environment interactions for starch, mineral, and agronomic traits in pearl millet hybrids evaluated across five locations in West Africa

Gangashetty,

Yadav,

Riyazaddin

et al. 2023

Front. Plant Sci.

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IntroductionPearl millet is a staple cereal grown in the harshest environments of arid and semi-arid regions of Asia and sub-Saharan Africa. It is the primary source of calories for millions of people in these regions because it has better adaptation to harsh environmental conditions and better nutritional traits than many other cereals. By screening the pearl millet inbred germplasm association panel (PMiGAP), we earlier reported the best genotypes with the highest concentration of slowly digestible and resistant starch in their grains.MethodsIn the current study, we tested these 20 top-performing pearl millet hybrids, identified based on starch data, in a randomised block design with three replications at five locations in West Africa, viz. Sadore and Konni (Niger), Bambey (Senegal), Kano (Nigeria), and Bawku (Ghana). Phenotypic variability was assessed for agronomic traits and mineral traits (Fe and Zn).Results and discussionAnalysis of variance demonstrated significant genotypic, environmental, and GEI effects among five testing environments for agronomic traits (days to 50% flowering, panicle length, and grain yield), starch traits (rapidly digestible starch, slowly digestible starch, resistant starch, and total starch), and mineral trait (iron and zinc). Starch traits, such as rapidly digestible starch (RDS) and slowly digestible starch (SDS), showed nonsignificant genotypic and environmental interactions but high heritability, indicating the lower environmental influence on these traits in the genotype × testing environments. Genotype stability and mean performance across all the traits were estimated by calculating the multi-trait stability index (MTSI), which showed that genotypes G3 (ICMX207070), G8 (ICMX207160), and G13 (ICMX207184) were the best performing and most stable among the five test environments.

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Section: Resultssupporting

confidence: 80%

Section: Methodsmentioning

confidence: 99%