Nutritional and bioactive properties and antioxidant potential of Amaranthus tricolor, A. lividus, A viridis, and A. spinosus leafy vegetables

Sarker, Umakanta; Oba, Shinya; Ullah, Riaz; Bari, Ahmed; Ercisli, Sezai; Skrovankova, Sona; Adamkova, Anna; Zvonkova, Magdalena; Mlcek, Jiri

doi:10.1016/j.heliyon.2024.e30453

Cited by 7 publications

(1 citation statement)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Literature has also shown corroborative results across genotypes in rice [53][54][55] Zea may 56 , mung bean 57 and A. spp. [58][59][60][61][62][63][64][65] . The noteworthy interplay resulting from G × E serves as a gauge for the diverse reactions of rice genotypes to quantitative attributes in both scenarios.…”

Section: The Multi-trait Genotype-ideotype Distance Index (Mgidi) Sel...mentioning

confidence: 99%

Climate-smart rice (Oryza sativa L.) genotypes identification using stability analysis, multi-trait selection index, and genotype-environment interaction at different irrigation regimes with adaptation to universal warming

Habib,

Azam,

Haque

et al. 2024

Sci Rep

Self Cite

View full text Add to dashboard Cite

Climate change has brought an alarming situation in the scarcity of fresh water for irrigation due to the present global water crisis, climate variability, drought, increasing demands of water from the industrial sectors, and contamination of water resources. Accurately evaluating the potential of future rice genotypes in large-scale, multi-environment experiments may be challenging. A key component of the accurate assessment is the examination of stability in growth contexts and genotype-environment interaction. Using a split-plot design with three replications, the study was carried out in nine locations with five genotypes under continuous flooding (CF) and alternate wet and dry (AWD) conditions. Utilizing the web-based warehouse inventory search tool (WIST), the water status was determined. To evaluate yield performance for stability and adaptability, AMMI and GGE biplots were used. The genotypes clearly reacted inversely to the various environments, and substantial interactions were identified. Out of all the environments, G3 (BRRI dhan29) had the greatest grain production, whereas G2 (Binadhan-8) had the lowest. The range between the greatest and lowest mean values of rice grain output (4.95 to 4.62 t ha-1) was consistent across five distinct rice genotypes. The genotype means varied from 5.03 to 4.73 t ha-1 depending on the environment. In AWD, all genotypes out performed in the CF system. With just a little interaction effect, the score was almost zero for several genotypes (E1, E2, E6, and E7 for the AWD technique, and E5, E6, E8, and E9 for the CF method) because they performed better in particular settings. The GGE biplot provided more evidence in support of the AMMI study results. The study's findings made it clear that the AMMI model provides a substantial amount of information when evaluating varietal performance across many environments. Out of the five accessions that were analyzed, one was found to be top-ranking by the multi-trait genotype ideotype distance index, meaning that it may be investigated for validation stability measures. The study's findings provide helpful information on the variety selection for the settings in which BRRI dhan47 and BRRI dhan29, respectively, performed effectively in AWD and CF systems. Plant breeders might use this knowledge to choose newer kinds and to design breeding initiatives. In conclusion, intermittent irrigation could be an effective adaptation technique for simultaneously saving water and mitigating GHG while maintaining high rice grain yields in rice cultivation systems.

show abstract

Section: The Multi-trait Genotype-ideotype Distance Index (Mgidi) Sel...mentioning

confidence: 99%

Climate-smart rice (Oryza sativa L.) genotypes identification using stability analysis, multi-trait selection index, and genotype-environment interaction at different irrigation regimes with adaptation to universal warming

Habib,

Azam,

Haque

et al. 2024

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

Varietal influence on bioactive compounds and antioxidant activity in chilies during development stages

Akhter,

Islam

et al. 2024

Heliyon

View full text Add to dashboard Cite

Phenotypic diversity in qualitative and quantitative traits for selection of high yield potential field pea genotypes

Azam,

Sarker,

Hossain

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Field pea (Pisum sativum L.) needs improvement to increase productivity due to its high price and demand. However, the incidence of powdery mildew (PM) disease limits its production. This study aimed to analyze the diversity of qualitative and quantitative traits against powdery mildew resistance by utilizing cluster and principal component analysis to explore PM resistance high-yield potential field peas. Shannon–Weaver's diversity index (Hʹ) displayed high intra-genotype diversity for quantitative and qualitative aspects. Heterogeneity was identified for resistance against powdery mildew infections. Eighty-five genotypes were divided into five groups using Mohalanobis generalized distance (D2) statistics. The highest inter-cluster D2 value was observed between clusters 2 and 3 (11.89) while the lowest value was found between clusters 3 and 4 (2.06). Most of the genotypes had noticeable differences, so these could be employed in a crossing scheme. Twelve genotypes were extremely resistant, 29 genotypes were resistant, 25 genotypes were moderately resistant, 18 genotypes were fairly susceptible, and 1 genotype was susceptible to powdery mildew disease. Among 29 resistant genotypes, BFP77, BFP74, BFP63, BFP62, BFP43, and BFP80 were high yielders and, could be used directly and/or transferred through hybridization to high-yielding disease-susceptible genotypes. Among the 25 moderately resistant genotypes, BFP78, BFP45, BFP79, and BFP48 were found to be high yielders. In principal component analysis (PCA), the first four PCs with Eigen values > 1 accounted for 88.4% variability for quantitative traits. Clustering sorted genotypes into five groups, where groups 1 to 5 assembled 37, 28, 1, 8, and 11 genotypes, respectively. Genotypes of cluster 4 were identified as high yielders with its attributes. Pearson correlation significantly and positively correlated across all traits except for PM. This variation suggested that there is a mechanism to select promising genotypes for field pea breeding. Considering all features, BFP78, BFP77, BFP74, BFP63, BFP62, BFP45, BFP79, and BFP80 could be preferred as high yielders and PM resistance owing to longer pod lengths, seeds per pod and pods per plant.

show abstract

Nutritional and bioactive properties and antioxidant potential of Amaranthus tricolor, A. lividus, A viridis, and A. spinosus leafy vegetables

Cited by 7 publications

References 84 publications

Climate-smart rice (Oryza sativa L.) genotypes identification using stability analysis, multi-trait selection index, and genotype-environment interaction at different irrigation regimes with adaptation to universal warming

Climate-smart rice (Oryza sativa L.) genotypes identification using stability analysis, multi-trait selection index, and genotype-environment interaction at different irrigation regimes with adaptation to universal warming

Varietal influence on bioactive compounds and antioxidant activity in chilies during development stages

Phenotypic diversity in qualitative and quantitative traits for selection of high yield potential field pea genotypes

Contact Info

Product

Resources

About