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  1. Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Mamun A
    Biomed Res Int, 2020;2020:2195797.
    PMID: 33415143 DOI: 10.1155/2020/2195797
    Bambara groundnut (Vigna subterranea L. Verdc.) is considered an emerging crop for the future and known as a crop for the new millennium. The core intention of this research work was to estimate the variation of landraces of Bambara groundnut considering their 14 qualitative and 27 numerical traits, to discover the best genotype fitted in Malaysia. The findings of the ANOVA observed a highly significant variation (p ≤ 0.01) for all the traits evaluated. There was a substantial variation (7.27 to 41.21%) coefficient value, and 14 out of the 27 numerical traits noted coefficient of variation (CV) ≥ 20%. Yield (kg/ha) disclosed positively strong to perfect high significant correlation (r = 0.75 to 1.00; p ≤ 0.001) with traits like fresh pod weight, dry pod weight, and dry seed weight. The topmost PCV and GCV values were estimated for biomass dry (41.09%) and fresh (40.53%) weight with high heritability (Hb) and genetic advance (GA) Hb = 95.19%, GA = 80.57% and Hb = 98.52%, GA = 82.86%, respectively. The topmost heritability was recorded for fresh pod weight (99.89%) followed by yield (99.75%) with genetic advance 67.95% and 62.03%, respectively. The traits with Hb ≥ 60% and GA ≥ 20% suggested the least influenced by the environment as well as governed by the additive genes and direct selection for improvement of such traits can be beneficial. To estimate the genetic variability among accessions, the valuation of variance components, coefficients of variation, heritability, and genetic advance were calculated. To authenticate the genetic inequality, an unweighted pair group produced with arithmetic mean (UPGMA) and principal component analysis was executed based on their measurable traits that could be a steadfast method for judging the degree of diversity. Based on the UPGMA cluster analysis, constructed five distinct clusters and 44 accessions from clusters II and IV consider an elite type of genotypes that produce more than one ton yield per hectare land with desirable traits. This study exposed an extensive disparity among the landraces and the evidence on genetic relatives will be imperative in using the existing germplasm for Bambara groundnut varietal improvement. Moreover, this finding will be beneficial for breeders to choose the desirable numerical traits of V. subterranea in their future breeding program.
  2. Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M
    Sci Rep, 2022 09 19;12(1):15658.
    PMID: 36123374 DOI: 10.1038/s41598-022-19003-z
    This investigation was carried out to explore G × E interaction for yield and its associated attributes in 30 Bambara groundnut genotypes across four environments in tropical Malaysia. Such evaluations are essential when the breeding program's objective is to choose genotypes with broad adaption and yield potential. Studies of trait relationships, variance components, mean performance, and genetic linkage are needed by breeders when designing, evaluating, and developing selection criteria for improving desired characteristics in breeding programs. The evaluation of breeding lines of Bambara groundnut for high yield across a wide range of environments is important for long-term production and food security. Each site's experiment employed a randomized complete block design with three replicates. Data on vegetative and yield component attributes were recorded. The analysis of variance revealed that there were highly significant (p ≤ 0.01) differences among the 30 genotypes for all variables evaluated. A highly significant and positive correlation was identified between yield per hectare and dry seed weight (0.940), hundred seed weight (0.844), fresh pod weight (0.832), and total pod weight (0.750); the estimated correlation between dry weight of pods and seed yield was 1.0. The environment was more important than genotype and G × E in determining yield and yield components.A total of 49% variation is covered by PC1 (33.9%) and PC2 (15.1%) and the genotypes formed five distinct clusters based on Ward hierarchical clustering (WHC) method. The genotypes S5G1, S5G3, S5G5, S5G6, S5G8, S5G7, S5G2, S5G4, S5G10, S5G13, S5G11, and S5G14 of clusters I, II, and III were closest to the ideal genotype with superior yield across the environments. The PCA variable loadings revealed that an index based on dry pod weight, hundred seed weight, number of total pods and fresh pod weight could be used as a selection criteria to improve seed yield of Bambara groundnut.
  3. Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M
    Sci Rep, 2022 01 07;12(1):245.
    PMID: 34996953 DOI: 10.1038/s41598-021-03692-z
    In a breeding program, studies of genotypic and phenotypic relationships among agricultural crop traits are useful to design, evaluate, and develop selection criteria for desirable traits. Using path coefficient analysis, the present study was executed to estimate the phenotypic, genotypic, and environmental correlation coefficients between yield and yield-related traits and to determine the direct and indirect effects of yield-related traits on yield per plant. A total of 30 genotypes of Vigna subterranea were studied under tropical conditions at two sites over two planting seasons (considered as four environments). The experiment at each site used a randomized complete block design with three replicates. Data were collected on vegetative and yield component attributes. Based on analysis of variance, pooled results showed that there were positive and highly significant differences (p ≤ 0.01) among the 30 genotypes for all attributes studied. Highly significant and positive strong correlation at phenotypic level was observed for dry seed weight (0.856), hundred seed weight (0.754), fresh pod weight (0.789), and total pod weight (0.626) with yield in kg per hectare, while moderate positive correlations were observed for harvest cut (0.360) and days to maturity (0.356). However, a perfect positive correlation was observed for the dry weight of pods with seed yield. In contrast, days to 50% flowering (- 0.350) showed a negative significant relationship with yield per hectare. The dried pod weight attribute (1.00) had a high positive direct effect on yield. Fresh pod weight had the greatest indirect effect on yield per hectare, followed by the number of total pods by dry pod weight. As a result, dry pod weight, hundred seed weight, number of total pods, and fresh pod weight could be used as selection criteria to improve the seed yield of Bambara groundnut (Vigna subterranea).
  4. Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M
    Sci Rep, 2021 Nov 23;11(1):22791.
    PMID: 34815427 DOI: 10.1038/s41598-021-01411-2
    The stability and high yielding of Vigna subterranea L. Verdc. genotype is an important factor for long-term development and food security. The effects of G × E interaction on yield stability in 30 Bambara groundnut genotypes in four different Malaysian environments were investigated in this research. The experiment used a randomized complete block design with three replications in each environment. Over multiple harvests, yield component traits such as the total number of pods per plant, fresh pods weight (g), hundred seeds weight (g), and yield per hectare were evaluated in the main and off-season in 2020 and 2021. Stability tests for multivariate stability parameters were performed based on analyses of variance. For all the traits, the pooled analysis of variance revealed highly significant (p 
  5. Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M, Kundu BC
    Mol Biol Rep, 2023 Sep;50(9):7619-7637.
    PMID: 37531035 DOI: 10.1007/s11033-023-08693-x
    BACKGROUND: A set of 44 selected Bambara groundnut (Vigna subterranea [L.] Verdc.) accessions was sampled from 11 distinct populations of four geographical zones to assess the genetic drift, population structure, phylogenetic relationship, and genetic differentiation linked with ISSR primers.

    METHODS AND RESULTS: The amplification of genomic DNA with 32 ISSR markers detected an average of 97.64% polymorphism while 35.15% and 51.08% polymorphism per population and geographical zone, respectively. Analysis of molecular variance revealed significant variation within population 75% and between population 25% whereas within region 84% and between region 16%. The Bidillali exposed greater number of locally common band i.e., NLCB (≤ 25%) = 25 and NLCB (≤ 50%) = 115 were shown by Cancaraki while the lowest was recorded as NLCB (≤ 25%) = 6 and NLCB (≤ 50%) = 72 for Roko and Maibergo, accordingly. The highest PhiPT value was noted between Roko and Katawa (0.405*) whereas Nei's genetic distance was maximum between Roko and Karu (0.124). Based on Nei's genetic distance, a radial phylogenetic tree was constructed that assembled the entire accessions into 3 major clusters for further confirmation unrooted NJ vs NNet split tree analysis based on uncorrected P distance exposed the similar result. Principal coordinate analysis showed variation as PC1 (15.04%) > PC2 (5.81%).

    CONCLUSIONS: The current study leads to prompting the genetic improvement and future breeding program by maximum utilization and better conservation of existing accessions. The accessions under Cancaraki and Jatau are population documented for future breeding program due to their higher genetic divergence and homozygosity.

  6. Boo KBW, El-Shafie A, Othman F, Khan MMH, Birima AH, Ahmed AN
    Water Res, 2024 Mar 15;252:121249.
    PMID: 38330715 DOI: 10.1016/j.watres.2024.121249
    Groundwater, the world's most abundant source of freshwater, is rapidly depleting in many regions due to a variety of factors. Accurate forecasting of groundwater level (GWL) is essential for effective management of this vital resource, but it remains a complex and challenging task. In recent years, there has been a notable increase in the use of machine learning (ML) techniques to model GWL, with many studies reporting exceptional results. In this paper, we present a comprehensive review of 142 relevant articles indexed by the Web of Science from 2017 to 2023, focusing on key ML models, including artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), support vector regression (SVR), evolutionary computing (EC), deep learning (DL), ensemble learning (EN), and hybrid-modeling (HM). We also discussed key modeling concepts such as dataset size, data splitting, input variable selection, forecasting time-step, performance metrics (PM), study zones, and aquifers, highlighting best practices for optimal GWL forecasting with ML. This review provides valuable insights and recommendations for researchers and water management agencies working in the field of groundwater management and hydrology.
  7. Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M, Halidu J
    Sci Rep, 2021 Jul 15;11(1):14527.
    PMID: 34267249 DOI: 10.1038/s41598-021-93867-5
    As a new crop in Malaysia, forty-four Bambara groundnut (Vigna subterranea L. verdc.) genotypes were sampled from eleven distinct populations of different origins to explore the genetic structure, genetic inconsistency, and fixation index. The Bambara groundnut, an African underutilized legume, has the capacity to boost food and nutrition security while simultaneously addressing environmental sustainability, food availability, and economic inequalities. A set of 32 ISSRs were screened out of 96 primers based on very sharp, clear, and reproducible bands which detected a total of 510 loci with an average of 97.64% polymorphism. The average calculated value of PIC = 0.243, RP = 5.30, H = 0.285, and MI = 0.675 representing the efficiency of primer set for genetic differentiation among the genotypes. The ISSR primers revealed the number of alleles (Na = 1.97), the effective number of alleles (Ne = 1.38), Nei's genetic diversity (h = 0.248), and a moderate level of gene flow (Nm = 2.26) across the genotypes studied. The estimated Shannon's information index (I = 0.395) indicates a high level of genetic variation exists among the accessions. Based on Nei's genetic dissimilarity a UPMGA phylogenetic tree was constructed and grouped the entire genotypes into 3 major clusters and 6 subclusters. PCA analysis revealed that first principal component extracted maximum variation (PC1 = 13.92%) than second principal component (PC2 = 12.59%). Bayesian model-based STRUCTURE analysis assembled the genotypes into 3 (best ΔK = 3) genetic groups. The fixation-index (Fst) analysis narrated a very great genetic diversity (Fst = 0.19 to 0.40) exists within the accessions of these 3 clusters. This investigation specifies the effectiveness of the ISSR primers system for the molecular portrayal of V. subterranea genotypes that could be used for genetic diversity valuation, detection, and tagging of potential genotypes with quick, precise, and authentic measures for this crop improvement through effective breeding schemes.
  8. Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Al Mamun M
    Sci Rep, 2021 Apr 07;11(1):7597.
    PMID: 33828137 DOI: 10.1038/s41598-021-87039-8
    As a crop for the new millennium Bambara groundnut (Vigna subterranea [L.] Verdc.) considered as leading legumes in the tropical regions due to its versatile advantages. The main intent of this study was to find out the high yielding potential genotypes and considering these genotypes to develop pure lines for commercial cultivation in Malaysia. Considering the 14 qualitative and 27 quantitative traits of fifteen landraces the variation and genetic parameters namely, variability, heritability, genetic advance, characters association, and cluster matrix were determined. ANOVA revealed significant variation for all the agronomic traits (except plant height). Among the accessions, highly significant differences (P ≤ 0.01) were found for almost all the traits excluding fifty percent flowering date, seed length, seed width. The 16 traits out of the 27 quantitative traits had a coefficient of variation (CV) ≥ 20%. A positive and intermediate to perfect highly significant association (r = 0.23 to 1.00; P 
  9. Hasan NMS, Sobuz MHR, Khan MMH, Mim NJ, Meraz MM, Datta SD, et al.
    Materials (Basel), 2022 Nov 17;15(22).
    PMID: 36431656 DOI: 10.3390/ma15228171
    The incorporation of waste materials generated in many industries has been actively advocated for in the construction industry, since they have the capacity to lessen the pollution on dumpsites, mitigate environmental resource consumption, and establish a sustainable environment. This research has been conducted to determine the influence of different rice husk ash (RHA) concentrations on the fresh and mechanical properties of high-strength concrete. RHA was employed to partially replace the cement at 5%, 10%, 15%, and 20% by weight. Fresh properties, such as slump, compacting factor, density, and surface absorption, were determined. In contrast, its mechanical properties, such as compressive strength, splitting tensile strength and flexural strength, were assessed after 7, 28, and 60 days. In addition, the microstructural evaluation, initial surface absorption test, = environmental impact, and cost-benefit analysis were evaluated. The results show that the incorporation of RHA reduces the workability of fresh mixes, while enhancing their compressive, splitting, and flexural strength up to 7.16%, 7.03%, and 3.82%, respectively. Moreover, incorporating 10% of RHA provides the highest compressive strength, splitting tensile, and flexural strength, with an improved initial surface absorption and microstructural evaluation and greater eco-strength efficiencies. Finally, a relatively lower CO2-eq (equivalent to kg CO2) per MPa for RHA concrete indicates the significant positive impact due to the reduced Global Warming Potential (GWP). Thus, the current findings demonstrated that RHA can be used in the concrete industry as a possible revenue source for developing sustainable concretes with high performance.
  10. Tao H, Aldlemy MS, Homod RZ, Aksoy M, Mohammed MKA, Alawi OA, et al.
    Sci Rep, 2024 Aug 27;14(1):19882.
    PMID: 39191833 DOI: 10.1038/s41598-024-69648-1
    This research explores the feasibility of using a nanocomposite from multi-walled carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) for thermal engineering applications. The hybrid nanocomposites were suspended in water at various volumetric concentrations. Their heat transfer and pressure drop characteristics were analyzed using computational fluid dynamics and artificial neural network models. The study examined flow regimes with Reynolds numbers between 5000 and 17,000, inlet fluid temperatures ranging from 293.15 to 333.15 K, and concentrations from 0.01 to 0.2% by volume. The numerical results were validated against empirical correlations for heat transfer coefficient and pressure drop, showing an acceptable average error. The findings revealed that the heat transfer coefficient and pressure drop increased significantly with higher inlet temperatures and concentrations, achieving approximately 45.22% and 452.90%, respectively. These results suggested that MWCNTs-GNPs nanocomposites hold promise for enhancing the performance of thermal systems, offering a potential pathway for developing and optimizing advanced thermal engineering solutions.
  11. Luedtke JA, Chanson J, Neam K, Hobin L, Maciel AO, Catenazzi A, et al.
    Nature, 2024 Jan;625(7993):E2.
    PMID: 38040869 DOI: 10.1038/s41586-023-06851-6
  12. Luedtke JA, Chanson J, Neam K, Hobin L, Maciel AO, Catenazzi A, et al.
    Nature, 2023 Oct;622(7982):308-314.
    PMID: 37794184 DOI: 10.1038/s41586-023-06578-4
    Systematic assessments of species extinction risk at regular intervals are necessary for informing conservation action1,2. Ongoing developments in taxonomy, threatening processes and research further underscore the need for reassessment3,4. Here we report the findings of the second Global Amphibian Assessment, evaluating 8,011 species for the International Union for Conservation of Nature Red List of Threatened Species. We find that amphibians are the most threatened vertebrate class (40.7% of species are globally threatened). The updated Red List Index shows that the status of amphibians is deteriorating globally, particularly for salamanders and in the Neotropics. Disease and habitat loss drove 91% of status deteriorations between 1980 and 2004. Ongoing and projected climate change effects are now of increasing concern, driving 39% of status deteriorations since 2004, followed by habitat loss (37%). Although signs of species recoveries incentivize immediate conservation action, scaled-up investment is urgently needed to reverse the current trends.
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