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Mullualem D, Tsega A, Mengie T, Fentie D, Kassa Z, Fassil A, Wondaferew D, Gelaw TA, Astatkie T. Genotype-by-environment interaction and stability analysis of grain yield of bread wheat ( Triticum aestivum L.) genotypes using AMMI and GGE biplot analyses. Heliyon 2024; 10:e32918. [PMID: 38988541 PMCID: PMC11234031 DOI: 10.1016/j.heliyon.2024.e32918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 07/12/2024] Open
Abstract
Bread wheat is a vital staple crop worldwide; including in Ethiopia, but its production is prone to various environmental constraints and yield reduction associated with adaptation. To identify adaptable genotypes, a total of 12 bread wheat genotypes (G1 to G12) were evaluated for their genotype-environment interaction (GEI) and stability across three different environments for two years using Additive Main Effect and Multiplicative Interaction (AMMI) and genotype main effect plus genotype-by-environment interaction (GGE) biplots analysis. GEI is a common phenomenon in crop improvement and is of significant importance in genotype assessment and recommendation. According to combined analysis of variance, grain yield was considerably impacted by environments, genotypes, and GEI. AMMI and GGE biplots analysis also provided insights into the performance and stability of the genotypes across diverse environmental conditions. Among the 12 genotypes, G6 was selected by AMMI biplot analysis as adaptive and high-yielding genotype; G5 and G7 demonstrated high stability and minimal interaction with the environment, as evidenced by their IPCA1 values. G7 was identified as the most stable and high-yielding genotype. The GGE biplot's polygon view revealed that the highest grain yield was obtained from G6 in environment three (E3). E3 was selected as the ideal environment by the GGE biplot. The top three stable genotypes identified by AMMI stability value (ASV) were G5, G7, and G10, while the most stable genotype determined by Genotype Selection Index (GSI) was G7. Even though G6 was a high yielder, it was found to be unstable according to ASV and ranked third in stability according to GSI. Based on the study's findings, the GGE biplot genotype view for grain yield identified Tay genotype (G6) to be the most ideal genotype due to its high grain yield and stability in diverse environments. G7 showed similar characteristics and was also stable. These findings provide valuable insights to breeders and researchers for selecting high-yielding and stable, as well as high-yielding specifically adapted genotypes.
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Affiliation(s)
- Destaw Mullualem
- Department of Biology, College of Natural and Computational Science, Injibara University, Injibara, Ethiopia
| | - Alemu Tsega
- Department of Biology, College of Natural and Computational Science, Injibara University, Injibara, Ethiopia
| | - Tesfaye Mengie
- Department of Biology, College of Natural and Computational Science, Injibara University, Injibara, Ethiopia
| | - Desalew Fentie
- Department of Plant Science, College of Agriculture, Food and Climate Science, Injibara University, 40, Injibara, Ethiopia
| | - Zelalem Kassa
- Department of Plant Science, College of Agriculture, Food and Climate Science, Injibara University, 40, Injibara, Ethiopia
| | - Amare Fassil
- Department of Biology, College of Natural and Computational Science, Injibara University, Injibara, Ethiopia
| | - Demekech Wondaferew
- Department of Plant Science, College of Agriculture, Food and Climate Science, Injibara University, 40, Injibara, Ethiopia
| | - Temesgen Assefa Gelaw
- Department of Biotechnology, College of Agriculture and Natural Resource Sciences, Debre Birhan University, Debre Birhan, Ethiopia
| | - Tessema Astatkie
- Faculty of Agriculture, Dalhousie University, Truro, Nova Scotia, Canada
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Manjunath KK, Krishna H, Devate NB, Sunilkumar VP, Patil SP, Chauhan D, Singh S, Kumar S, Jain N, Singh GP, Singh PK. QTL mapping: insights into genomic regions governing component traits of yield under combined heat and drought stress in wheat. Front Genet 2024; 14:1282240. [PMID: 38269367 PMCID: PMC10805833 DOI: 10.3389/fgene.2023.1282240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 12/15/2023] [Indexed: 01/26/2024] Open
Abstract
Drought and heat frequently co-occur during crop growth leading to devastating yield loss. The knowledge of the genetic loci governing component traits of yield under combined drought and heat stress is essential for enhancing the climate resilience. The present study employed a mapping population of 180 recombinant inbred lines (RILs) derived from a cross between GW322 and KAUZ to identify quantitative trait loci (QTLs) governing the component traits of yield under heat and combined stress conditions. Phenotypic evaluation was conducted across two consecutive crop seasons (2021-2022 and 2022-2023) under late sown irrigation (LSIR) and late sown restricted irrigation (LSRI) conditions at the Indian Council of Agricultural Research Institute-Indian Agricultural Research Institute (ICAR-IARI), New Delhi. Various physiological and agronomic traits of importance were measured. Genotyping was carried out with 35K SNP Axiom breeder's genotyping array. The linkage map spanned a length of 6769.45 cM, ranging from 2.28 cM/marker in 1A to 14.21 cM/marker in 5D. A total of 35 QTLs were identified across 14 chromosomes with 6B containing the highest (seven) number of QTLs. Out of 35 QTLs, 16 were major QTLs explaining the phenotypic variance greater than 10%. The study identified eight stable QTLs along with two hotspots on chromosomes 6B and 5B. Five QTLs associated with traits thousand-grain weight (TGW), normalized difference vegetation index (NDVI), and plant height (PH) were successfully validated. Candidate genes encoding antioxidant enzymes, transcription factors, and growth-related proteins were identified in the QTL regions. In silico expression analysis highlighted higher expression of transcripts TraesCS2D02G021000.1, TraesCS2D02G031000, TraesCS6A02G247900, and TraesCS6B02G421700 under stress conditions. These findings contribute to a deeper understanding of the genetic architecture underlying combined heat and drought tolerance in wheat, providing valuable insights for wheat improvement strategies under changing climatic conditions.
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Affiliation(s)
| | - Hari Krishna
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Narayana Bhat Devate
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - V. P. Sunilkumar
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Sahana Police Patil
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Divya Chauhan
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Shweta Singh
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Sudhir Kumar
- Division of Plant Physiology, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Neelu Jain
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | | | - Pradeep Kumar Singh
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
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Melash AA, Bogale AA, Mengstu SG, Aberra DA, Tsegay A, Mengistu DK. Sustainable management practices for durum wheat production: Analyzing specific agronomic interventions on productivity, grain micronutrient content, and quality. Heliyon 2023; 9:e18733. [PMID: 37609412 PMCID: PMC10440465 DOI: 10.1016/j.heliyon.2023.e18733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 07/14/2023] [Accepted: 07/25/2023] [Indexed: 08/24/2023] Open
Abstract
As compared with single agronomic crop management practices during grain formation, knowledge about integrated agronomic management practices on grain mineral composition and grain technological properties in durum wheat is limited. This knowledge is important for determining management strategies aimed at increasing grain yield without affecting grain nutritional quality. Integrated agronomic practices such as foliar nutrient application × seeding rate × varieties combined with growing locations were investigated to evaluate the dynamics of yield and grain quality traits. Two durum wheat varieties, three-level of micronutrients (i.e. control, FeSO4, and ZnSO4), and four levels of seeding rate (i.e. 100, 125, 150, and 175 kg ha-1) were arranged in split-split plot design under two different growing locations (environments). The main plots were assigned to the varieties, subplots to micronutrients, and sub-sub plots to the seeding rate treatments. Zinc and iron were applied in a form of ZnSO4 and FeSO4 at the early flowering stage, both at a rate of 25 kg ha-1. Results showed a linear increment in biomass (21.5%) and grain yield (23.5%) under a high seeding rate, even though the 1000-grain weight, the number of grains spike-1, spike length, and the number of grains spike-1 were decreased. Higher varietal and environmental response of seeding rate was observed between varieties. The grain protein content, gluten, and zeleyn index decreased as the seeding rate increased. Grain micronutrient content was significantly influenced by seeding rate and varietal difference. The grain protein content was higher in a dryland environment than in a wet environment. A combined use of density-tolerant varieties, high seeding rate, and foliar-based iron application can improve the grain yield from 2.01 to 3.20 t ha-1 under a potential environment. Hence, all stakeholders should consider the genotype (G), environment (E), management (M), and their synergies, as far as grain yield and quality are considered simultaneously.
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Affiliation(s)
- Anteneh Agezew Melash
- Department of Horticulture, College of Agriculture and Environmental Science, Debark University, P.O. Box 90, Debark, North Gondar, Ethiopia
| | - Amare Assefa Bogale
- Department of Horticulture, College of Agriculture and Natural Resource, Mekdela Amba University, P.O. Box 32, Tulu Awuliya, South Wollo, Ethiopia
| | - Shegaw Getu Mengstu
- Department of Horticulture, College of Agriculture and Environmental Science, University of Gondar, P.O. Box 196, Central Gondar, Ethiopia
| | - Dereje A. Aberra
- Mekelle University, Department of Dryland Crop and Horticultural Sciences, P.O. Box 231, Mekelle, Ethiopia
| | - Alemtsehay Tsegay
- Mekelle University, Department of Dryland Crop and Horticultural Sciences, P.O. Box 231, Mekelle, Ethiopia
| | - Dejene K. Mengistu
- Alliance of Biodiversity International and CIAT, ILRI, P.O. Box 5689, Addis Ababa, Ethiopia
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Yannam VRR, Lopes M, Guzman C, Soriano JM. Uncovering the genetic basis for quality traits in the Mediterranean old wheat germplasm and phenotypic and genomic prediction assessment by cross-validation test. FRONTIERS IN PLANT SCIENCE 2023; 14:1127357. [PMID: 36778676 PMCID: PMC9911887 DOI: 10.3389/fpls.2023.1127357] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 01/16/2023] [Indexed: 06/18/2023]
Abstract
The release of new wheat varieties is based on two main characteristics, grain yield and quality, to meet the consumer's demand. Identifying the genetic architecture for yield and key quality traits has wide attention for genetic improvement to meet the global requirement. In this sense, the use of landraces represents an impressive source of natural allelic variation. In this study, a genome-wide association analysis (GWAS) with PCA and kinship matrix was performed to detect QTLs in bread wheat for fifteen quality and agronomic traits using 170 diverse landraces from 24 Mediterranean countries in two years of field trials. A total of 53 QTL hotspots containing 165 significant marker-trait associations (MTAs) were located across the genome for quality and agronomical traits except for chromosome 2D. The major specific QTL hotspots for quality traits were QTL_3B.3 (13 MTAs with a mean PVE of 8.2%) and QTL_4A.3 (15 MTAs, mean PVE of 11.0%), and for yield-related traits were QTL_2B.1 (8 MTAs, mean PVE of 7.4%) and QTL_4B.2 (5 MTAs, mean PVE of 10.0%). A search for candidate genes (CG) identified 807 gene models within the QTL hotspots. Ten of these CGs were expressed specifically in grain supporting the role of identified QTLs in Landraces, associated to bread wheat quality traits and grain formation. A cross-validation approach within the collection was performed to calculate the accuracies of genomic prediction for quality and agronomical traits, ranging from -0.03 to 0.64 for quality and 0.46 to 0.65 for agronomic traits. In addition, five prediction equations using the phenotypic data were developed to predict bread loaf volume in landraces. The prediction ability varied from 0.67 to 0.82 depending on the complexity of the traits considered to predict loaf volume.
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Affiliation(s)
- Venkata Rami Reddy Yannam
- Sustainable Field Crops Program, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
| | - Marta Lopes
- Sustainable Field Crops Program, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
| | - Carlos Guzman
- Departamento de Genética, Escuela Técnica Superior de Ingeniería Agronómica y de Montes, Universidad de Córdoba, Córdoba, Spain
| | - Jose Miguel Soriano
- Sustainable Field Crops Program, Institute for Food and Agricultural Research and Technology (IRTA), Lleida, Spain
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Molecular and Physiological Evaluation of Bread Wheat ( Triticum aestivum L.) Genotypes for Stay Green under Drought Stress. Genes (Basel) 2022; 13:genes13122261. [PMID: 36553528 PMCID: PMC9778276 DOI: 10.3390/genes13122261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 11/24/2022] [Accepted: 11/24/2022] [Indexed: 12/02/2022] Open
Abstract
Water availability is considered as the main limiting factor of wheat growth illuminating the need of cultivars best adapted to drought situations for better wheat production and yield. Among these, the stay-green trait is thought to be related to the ability of wheat plants to maintain photosynthesis and CO2 assimilation, and a detailed molecular understanding of this trait may help in the selection of high-yielding, drought-tolerant wheats. The current study, therefore, evaluated the physiological responses of the selected wheat genotypes under pot-induced water stress conditions through different field capacities. The study also focused on exploring the molecular mechanisms involved in drought tolerance conferred due to the stay-green trait by studying the expression pattern of the selected PSI-associated light-harvesting complex I (LHC1) and PSII-associated LHCII gene families related to pigment-binding proteins. The results revealed that the studied traits, including relative water content, membrane stability index and chlorophyll, were variably and negatively affected, while the proline content was positively enhanced in the studied wheats under water stress treatments. Molecular diagnosis of the selected wheat genotypes using the expression profile of 06 genes, viz. TaLhca1, TaLhca2, TaLhca3, TaLhcb1, TaLhcb4 and TaLhcb6 that encodes for the LHCI and LHCII proteins, indicated variable responses to different levels of drought stress. The results obtained showed the relation between the genotypes and the severity of the drought stress condition. Among the studied genotypes, Chirya-1 and SD-28 performed well with a higher level of gene expression under drought stress conditions and may be used in genetic crosses to enrich the genetic background of common wheat against drought stress.
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Khan H, Krishnappa G, Kumar S, Mishra CN, Krishna H, Devate NB, Rathan ND, Parkash O, Yadav SS, Srivastava P, Biradar S, Kumar M, Singh GP. Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.). Front Genet 2022; 13:982589. [PMID: 36092913 PMCID: PMC9458894 DOI: 10.3389/fgene.2022.982589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 07/20/2022] [Indexed: 11/25/2022] Open
Abstract
Genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association studies (GWAS) panel was genotyped using a 35K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 27 Bonferroni-corrected marker-trait associations (MTAs) on 15 chromosomes representing all three wheat subgenomes. The GFD showed the highest MTAs (8), followed by GWPS (7), GY (4), GNPS (3), PH (3), and DH (2). Furthermore, 20 MTAs were identified with more than 10% phenotypic variation. A total of five stable MTAs (AX-95024590, AX-94425015, AX-95210025 AX-94539354, and AX-94978133) were identified in more than one environment and associated with the expression of DH, GFD, GNPS, and GY. Similarly, two novel pleiotropic genomic regions with associated MTAs i.e. AX-94978133 (4D) and AX-94539354 (6A) harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the SNPs were located on important putative candidate genes such as F-box-like domain superfamily, Lateral organ boundaries, LOB, Thioredoxin-like superfamily Glutathione S-transferase, RNA-binding domain superfamily, UDP-glycosyltransferase family, Serine/threonine-protein kinase, Expansin, Patatin, Exocyst complex component Exo70, DUF1618 domain, Protein kinase domain involved in the regulation of grain size, grain number, growth and development, grain filling duration, and abiotic stress tolerance. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).
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Affiliation(s)
- Hanif Khan
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | - Gopalareddy Krishnappa
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
- ICAR-Sugarcane Breeding Institute, Coimbatore, India
- *Correspondence: Gopalareddy Krishnappa, ; Gyanendra Pratap Singh,
| | - Satish Kumar
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | | | - Hari Krishna
- ICAR-Indian Agricultural Research Institute, New Delhi, India
| | | | | | - Om Parkash
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | - Sonu Singh Yadav
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | | | - Suma Biradar
- University of Agricultural Sciences, Dharwad, India
| | - Monu Kumar
- ICAR-Indian Agricultural Research Institute, Jharkhand, India
| | - Gyanendra Pratap Singh
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
- *Correspondence: Gopalareddy Krishnappa, ; Gyanendra Pratap Singh,
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Mahpara S, Bashir MS, Ullah R, Bilal M, Kausar S, Latif MI, Arif M, Akhtar I, Brestic M, Zuan ATK, Salama EAA, Al-Hashimi A, Alfagham A. Field screening of diverse wheat germplasm for determining their adaptability to semi-arid climatic conditions. PLoS One 2022; 17:e0265344. [PMID: 35303032 PMCID: PMC8932620 DOI: 10.1371/journal.pone.0265344] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 02/28/2022] [Indexed: 12/29/2022] Open
Abstract
Wheat (Triticum aestivum L.) is an important staple food crop for one third of global population and important crop for securing future food security. Rapid changes in the climate on global scale could be a threat for future food security. This situation urges plant breeders to explore the genetic potential of existing wheat germplasm. This study screened forty diverse wheat genotypes for their yield under two different agroclimatic conditions, i.e., Layyah and Dera Ghazi Khan, Pakistan. Data relating to plant height, peduncle length, flag leaf area, spike length, number of spikelets, number of grains per spike, thousand grain weight, chlorophyll content and grain yield were recorded. The tested wheat genotypes significantly differed for grain yield and related traits. Grain yield was positively correlated with plant height, spike length, spike number, flag leaf length, number of grains per spike, and 1000-grain weight. Biplot obtained from the cluster analysis by Euclidean method grouped the studied genotypes in 3 different groups. The genotypes exhibited 10.77% variability within quadrants, whereas 72.36% variability was recorded between quadrants according to clustering. Dendrogram grouped the tested genotypes into two main clusters. The main cluster “I” comprised of 2 genotypes, i.e., ‘Seher-2006’ and ‘AS-2002’. The cluster “II” contained 38 genotypes based on Euclidian values. Genotypes within same cluster had smaller D2 values compared to those belonging to other clusters. The genetic relationships of genotypes provide useful information for breeding programs. Overall, the results revealed that genotypes ‘Line 9733’, ‘Bhakar-2002’, ‘Line A9’ and ‘SYN-46’ had better yield and yield stability under climatic conditions of southern Punjab. Therefore, these genotypes could be recommended for general cultivation in the study region.
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Affiliation(s)
- Shahzadi Mahpara
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, Ghazi University Dera Ghazi Khan, Dera Ghazi Khan, Pakistan
- * E-mail: (MSB); (SM); (ATKZ)
| | - Muhammad Shafqat Bashir
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, Ghazi University Dera Ghazi Khan, Dera Ghazi Khan, Pakistan
- * E-mail: (MSB); (SM); (ATKZ)
| | - Rehmat Ullah
- Soil and Water Testing Laboratory for Research, Dera Ghazi Khan, Punjab, Pakistan
| | - Muhammad Bilal
- Soil and Water Testing Laboratory for Research, Dera Ghazi Khan, Punjab, Pakistan
| | - Salma Kausar
- Senior Scientist (Agri Chemistry), Soil and Water Testing Laboratory, Lodhran, Pakistan
| | | | - Muhammad Arif
- Scientific Officer (Lab), Soil and Water Testing Laboratory, Layyah, Pakistan
| | - Imran Akhtar
- Senior scientist (Ento), Regional Agriculture Research Institute, Bahawalpur, Pakistan
| | - Marian Brestic
- Department of Plant Physiology, Slovak University of Agriculture, Nitra, Slovakia
- Department of Botany and Plant Physiology, Czech University of Life Sciences, Prague, Czechia
| | - Ali Tan Kee Zuan
- Department of Land Management, Faculty of Agriculture, Universiti Putra Malaysia, Selangor, Malaysia
- * E-mail: (MSB); (SM); (ATKZ)
| | - Ehab A. A. Salama
- Agricultural Botany Department, Faculty of Agriculture Saba Basha, Alexandria University, Alexandria, Egypt
| | - Abdulrahman Al-Hashimi
- Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia
| | - Alanoud Alfagham
- Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia
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