Caryologia. International Journal of Cytology, Cytosystematics and Cytogenetics 75(1): 29-39, 2022 Firenze University Press www.fupress.com/caryologia ISSN 0008-7114 (print) | ISSN 2165-5391 (online) | DOI: 10.36253/caryologia-1419 Caryologia International Journal of Cytology, Cytosystematics and Cytogenetics Citation: Tao Shu, Chao Li, Chen She, Huan-Ping Zhao (2022) Morphometric analysis and genetic diversity in Glau- cium (Papaveraceae) using sequence related amplified polymorphism. Caryo- logia 75(1): 29-39. doi: 10.36253/caryolo- gia-1419 Received: September 29, 2021 Accepted: January 25, 2022 Published: July 6, 2022 Copyright: © 2022 Tao Shu, Chao Li, Chen She, Huan-Ping Zhao. This is an open access, peer-reviewed article published by Firenze University Press (http://www.fupress.com/caryologia) and distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distri- bution, and reproduction in any medi- um, provided the original author and source are credited. Data Availability Statement: All rel- evant data are within the paper and its Supporting Information files. Competing Interests: The Author(s) declare(s) no conflict of interest. Morphometric analysis and genetic diversity in Glaucium (Papaveraceae) using sequence related amplified polymorphism Tao Shu1,*, Chao Li2,+, Chen She3,*, Huan-Ping Zhao4 1 Modern Information Technology Center, Sichuan Vocational and Technical College, Suining 629000, China 2 School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500,China 3 School of Economics and Management, Tiangong University, Tianjin, 300387, China 4 School of Computer and Software, Nanyang Institute of Technology, Henan 473004, Chi- na +Corresponding author. E-mail: super123sb@163.com *Co-first author Abstract. Glaucium belongs to the Papaveraceae family. Glaucium is a genus of annual, biennial, and perennial herbaceous plants that thrive on salty soils and near the sea. Glaucium is represented by a total of 10 taxa in Iran. Sequence-related amplified poly- morphism was used to estimate genetic diversity. A combination of morphological and genomic data was used to identify genetic diversity and species features in Glau- cium species. In eight provinces, 65 people connected to five Glaucium were gathered. Through polymerase chain reaction (PCR) amplification of five Glaucium species, a total of 144 (Number of total loci) (NTL) DNA bands were obtained. These bands were created by combining 10 different selective primers. The total number of amplified fragments varied from seven to twenty-six. The expected unbiased heterozygozity (H) ranged from 0.19 (G. grandiflorum subsp. grandiflorum var. grandiflorum) to 0.33 (G. grandiflorum subsp. grandiflorum var. grandiflorum) (G. oxylobum var. oxylobum). The genetic similarities between five species range from 0.63 to 0.88. The findings of clus- tering revealed two large groupings. The SRAP (Sequence-related amplified polymor- phism) markers study revealed that G. grandiflorum and G. oxylobum var. oxylobum had the least similarity. This investigation also discovered a substantial indication of distance isolation (Mantel test results). The current findings indicate that sequence- related amplified polymorphism can discover and understand genetic affinity in Glau- cium species. The current findings have consequences for biodiversity and conservation efforts. Aside from that, the current findings may pave the way for identifying accept- able ecotypes for grazing and pasture uses in Iran. Keywords: population structure, gene flow, network, genetic admixture. 30 Tao Shu, Chao Li, Chen She, Huan-Ping Zhao INTRODUCTION: SRAP (sequence-related amplified polymorphism) is a PCR-based marker system (Gondal et al 2021; Dadzie et al 2021; Chimwamurombe et al 2020; Abeshu & Zewdu 2020). It is one of the most efficient and straightforward marker systems for studying gene mapping and gene tagging in plant species (Si et al, 2020; Sun et al, 2021; Sun and Khayatnezhad 2021; Tao et al., 2021; Wang et al., 2021), and SRAP are potential markers for plant systematics and genetic diversity studies (Robarts and Wolfe 2014 Khayatnezhad and Gholamin 2021; Ghola- min and Khayatnezhad 2020; 2021; Guo et al., 2021). Poppy family (Papaveraceae) comprises of approxi- mately 26 to 42 genera and 690 to 800 species in the world (Judd et al., 1999). The members of Papaveraceae are shrub, herbaceous perennials and annuals distributed in the temperate and the subtropical regions of the world. Among five genera of family Papaveraceae in Iran, Glau- cium, Hypecoum, Chelidonium and Roemeria consist of 10, 1, 1 and 2 species, respectively (Rechinger and Cul- len, 1966). Glaucium is found mostly in Atlantic Europe and Central Asia (Kaderiet 1993). The genus is divided into two sections, each containing four species, four sub- species, and two varieties: sect. Acropetala Mory has four species, four subspecies, two varieties and sects. Glauci- um, which has 19 species, eight subspecies, and 16 vari- ants (Mory 1979). It was represented by 11 (Cullen 1966) to 13 in Iran (Mobayen 1985; Gran and Sharifnia 2008). Morover, Mobayen (1985) introduced two subspe- cies G. fimbrilligerum Boiss. subsp. annuum and G. fim- brilligerum subsp. Ophyocarpum. Azizian and Alishahi Norani (1997) studied anatomical characteristics of fruit and blade with emphasis on latex tubes in species of Glaucium. Furthermore, Carlquist and Hoekman (1985) studied anatomical structure of wood in Romneya and Dendromecon. Carlquist and Zona (1988) continued his studies in cooperation with Zona on structure of wood in Papaveraceae. Some anatomical features of midrib and fruit of Glaucium are of diagnostic value (Solered- er, 1908; Metcalfe and Chalk, 1950). Several taxonomic investigations have demonstrated that seed and trichome micromorphology may be used for taxonomic catego- rization and delimitation at all taxonomic levels and across plant families (Ma et al., 2021a; 2021b; Peng et al., 2021; Ren et al., 2021). Arabi et al., 2017; Tavakkoli and Assadi, 2016). Gran and Sharifnia also researched the seed orna- mentations of 14 Glaucium species in Iran (2008). Light microscopy (LM) and scanning electron microscopy (SEM) was used to examine the seeds and trichomes of 15 species of the genus Glaucium found in Iran (Tav- akkoli and Assadi 2019). The seeds are semicircular to reniform in shape. However reniform and elongated reniform seeds have been identified in G. oxylobum and G. elegans, respectively. The most common types of testa surface sculpturing include verrucate–rugulate, verru- cate–granulate, verrucate–perforate, verrucate–lineolate, rugulate–granulate, rugulate, and ocellate. Their find- ings reveal that the micro-morphological properties of seed and ovary trichomes give important and substantial information for species and taxa within species separa- tion, as well as a diagnostic key to the taxa. Glaucium taxa were studied in terms of morphological, palyno- logical, and phylogenetic characteristics, according to Fatma Mungan Kiliç et al. (2019). Their findings reveal that several of these features change across species, par- ticularly in micromorphology and the development of clades in phylogenetic trees based on matK and ITS3-6 DNA sequence data. The genus Glaucium of Turkey was separated into subsections Glabrousae and Pubescentae based on DNA investigations backed by morphological evidence (stem trichomes). The present study investigated the molecular varia- tion of five species in Iran. Objectives of the study were; a) to estimate genetic diversity; b) to evaluate population relationships using WARD approaches. There are conse- quences for breeding and conservation initiatives based on current findings. MATERIALS AND METHODS: Plants collection Sixty-five (65) individuals were sampled. Five Glau- cium species in west Azerbaijan, Mazandaran, Hama- dan, Kurdistan, Esfahan, Semnan, Khorasan and Razavi Khorasan Provinces of Iran were selected and sampled during may-August 2014-2020 (Table 1). Morphometric and SRAP analyses on sixty five plant accessions were carried out. Based on additional eco-geographic criteria, five to twelve samples from each population belonging to five distinct species were chosen. Five samples were stored at - 20 °C till further use. Detailed information about locations of samples and geographical distribution of species are mentioned (Table 1 and Figure 1). Morphological studies Each species was subjected to morphometric analysis and twelve samples per species were processed. Qualita- tive (12) and quantitative (14) morphological characters 31Morphometric analysis and genetic diversity in Glaucium using sequence related amplified polymorphism Table 1. List of the investigated taxa including origin of voucher specimens. Taxa Locality Latitude Longitude Altitude(m) G. fimbrilligerum Boiss. Kurdestan, Sanandaj 35°19’18.75’’ 46°59’10.194’’ 1538 G. corniculatum var. corniculatum (L.) Curtis West-Azarbaijan, Urumieh, Silvana 37.552673 45°4’33.7656’’ 1344 G. oxylobum var. oxylobum Boiss. & Buhse Kurdestan, Sanandaj 38°22’18” 46°37’10” 1523 G. grandiflorum subsp. grandiflorum var. grandiflorum Boiss. & A.Huet A.Huet Semnan, 20km NW of Shahrud 36°25’14” 54°15’32” 1345 G. contortuplicatum var. cantortuplicatum Boiss. Mazandaran, 40 km Tonekabon to Janat abad 35°46’56” 51°23’29” 2383 Figure 1. Provinces and collection sites of Glaucium species. 32 Tao Shu, Chao Li, Chen She, Huan-Ping Zhao were studied. Data were transformed before calculation. Different morphological characters of flowers, leaves, and seeds were studied. Ordination analyses were conducted while using Euclidean distance (Podani 2000). Sequence-related amplified polymorphism method One to twelve plants’ worth of fresh leaves were uti- lized at random. Silica gel powder was used to dry them. Following the prior technique, the DNA was extracted (Esfandani-Bozchaloyi et al. 2019). According to the pro- tocol, we ran the SRAP assays (Li and Quiros 2001). Ten SRAP were employed with various primer combinations (Table 2). Single primers, 20 ng of genomic DNA, and 3 U of Taq DNA polymerase (Bioron, Germany) were used in 25l of Tris-HCl buffer at pH 8; 50 mM of KCL; 1.5 mM of MgCl2; 10 mM of Tris-HCl buffer at pH 8 and 3 U Taq DNA polymerase (Bioron, Germany) were used in PCR reactions. The total volume of the reaction was 25 l. A Techne thermocycler was used for this PCR experi- ment (Germany). Data Analyses To evaluate morphological characteristics, the UPG- MA (Unweighted paired group using average) ordination approach was used. To analyze morphological differenc- es across species, an ANOVA (analysis of variance) was used. To find variable morphological features in Glau- cium species, principal component analysis (PCA) was used. PAST software version 2.17 was used to conduct multivariate statistical studies, often known as PC analy- sis (Hammer et al. 2001). Molecular analyses Sequence-related amplified polymorphism (SRAP) bands were recorded. Presence and absence of bands were scored present (1) and absent (0), respectively. Total loci (NTL) and the number of polymorphism loci (NPL) for each primer were calculated. Mantet test was per- formed with 5000 permutations in PAST, version 2.17 (Hammer et al. 2001). Comparing genetic divergence or genetic distances, as assessed by pairwise FST and related statistics, with geographical distances, as evaluated by the Mantel test, is one of the most used tools for examining spatial dynamics driving population structure. The Mantel test, as originally formulated in 1967, where gij and dij are, are the genetic and geographical distances between populations I and j, respectively. respectively, the genetic and geo-graphic distances between popula- tions i and j, considering populations. Because Zm is is defined as the sum of product distances, its value is affected by the number of populations analyzed as well as the size of their distances. The Zm-value may be compared to a null distribution, and Mantel initially advocated using the standard normal deviation (SND), which is defined as SND =Zm/var(Zm)1/2 (Mantel 1967). PAST ver. 2.17 (Hammer et al. 2012) and DAR- win ver. 5 (2012) software were used for these investi- gations. The AMOVA (Analysis of molecular variance) test (with 1000 permutations) created in GenAlex 6.4 4 (Peakall and Smouse 2006) was used to reveal genetic differences across the populations. RESULTS Morphometery The ANOVA findings showed substantial differ- ences (p<0.01) between the species in terms of quantita- tive morphological characteristics. Principal component analysis results explained 68% cumulative variation. The first PCA axis accounted for 59% of the overall variance. The highest correlation (> 0.7) was shown by mor- phological characters such as calyx length, calyx width, corolla length, corolla color. The morphological charac- ters of Glaucium species are shown in PCoA plot (Fig- ure 2). Each species formed separate groups based on morphological characters. The morphometric analysis showed clear difference among Glaucium species and separated each groups. Species identification and genetic diversity Ten (10) suitable primer combinations (PCs), out of 25 PCs were screened in this research. Figure 3 illus- trates the banding pattern of Em2-Me4, Em3-Me1 and Em5-Me1 primer by the SRAP marker profile. One hun- dered and thirty six (136) amplified polymorphic bands (number of polymorphic loci) were produced. These bands (fragments) had different range i.e. 150bp to 3000 bp. Maximum and minimum numbers of polymorphic bands were 22 for Em2-Me4 and 7 Em5-Me2, respec- tively. Each primer produced 13 polymorphic bands on average. The PIC ranged from 0.14 (Em4-Me1) to 0.63 (Em1-Me4) for the 10 SRAP primers, with an average of 0.42 for each primer The primers’ RP varied from 12.24 (Em3-Me4) to 56.55 (Em3-Me1), with an average of 32.25. (Figure 3, Table 2). 33Morphometric analysis and genetic diversity in Glaucium using sequence related amplified polymorphism The calculated genetic parameters of Glaucium species are shown (Table 3). The unbiased heterozygosity (H) var- ied between 0.19 (G. grandiflorum subsp. grandiflorum var. grandiflorum) and 0.33 (G. oxylobum var. oxylobum) with a mean of 0.28. Shannon’s information index (I) was maxi- mum in G. grandiflorum subsp. grandiflorum var. grandi- florum (0.444), where as we recorded minimum Shannon’s information index in G. oxylobum var. oxylobum (0.231). The observed number of alleles (Na) ranged from 0.22 in G. oxylobum var. oxylobum to 1.445 in G. corniculatum var. corniculatum. The significant number of alleles (Ne) ranged from 1.029 (G. grandiflorum subsp. grandiflorum var. grandiflorum) to 1.88 (G. oxylobum var. oxylobum). Molecular Variance analysis reveals a substantial genetic difference (p = 0.01) between Glaucium species. The bulk of genetic diversity was found between species. Figure 2. Morphological characters analysis of Glaucium species by PCA plot. Figure 3. Electrophoresis gel of studied ecotypes from DNA fragments produced by SRAP profile with primer Em2-Me4. 34 Tao Shu, Chao Li, Chen She, Huan-Ping Zhao Analysis of Molecular Variance results AMOVA findings revealed that 77% of the total variation was between species and comparatively less genetic variation was recorded at the species level (Table 4). Genetic difference between Glaucium species was highlighted by genetic statistics (Nei’s GST), as evident by significant p values i.e. Nei’s GST (0.699, p = 0.01) and D_est values (0.196, p = 0.01) Because several clustering and ordination approaches yielded comparable findings, NJ clustering is provided here (Figure 4). Plant samples from each species, which belong to a different part, were grouped together and created a single cluster. This find- ing indicates that the molecular characteristics analyzed may separate Glaucium species into two primary clusters or groupings. We found no transitional forms among the specimens analyzed. In general, two large clusters emerged in the NJ tree (Figure 4), populations G. fim- brilligerum; G. contortuplicatum and G. oxylobum were put in the first main cluster and were separated from the other species by a large distance. The second major cluster included two sub-clusters. Plants of G. corniculatum var. corniculatum comprised the first sub-cluster, while plants of G. grandiflorum subsp. grandiflorum var. grandiflorum formed the second sub-cluster. We detected strong correlation between geographi- cal and genetic distances (r = 0.29, p=0.0002) and gene flow (Nm) score of 0.388 was reported among species. Detailed information about genetic distances and genetic identity (Nei’s) are described (Supplementary Table). The results indicated that G. oxylobum var. oxylobum and G. fimbrilligerum had the greatest degree of genetic similar- ity (0.88). On the contrary to this, G. grandiflorum and G. oxylobum var. oxylobum (0.63) had lowest genetic resemblance. To determine the ideal number of genetic groups, we used STRUCTURE analysis followed by the Evanno test. In the species analyzed, we employed the admixture model to show interspecific gene flow or / and ancestral- ly shared alleles. According to pseudo-F, K-Means clus- tering yielded k = 5 and BIC yielded k = 3. K = 5 is con- Table 2. SRAP primer information and results. Primer name NTLa NPLb Pc PICd RPe Em1-Me1 10 8 94.31% 0.33 23.77 Em2-Me2 17 17 100.00% 0.26 39.77 Em1-Me4 11 10 96.4% 0.63 20.46 Em2-Me4 22 22 100.00% 0.29 13.76 Em2-Me5 9 9 100.00% 0.34 40.99 Em3-Me4 13 13 100.00% 0.51 12.24 Em3-Me1 26 18 73.00% 0.20 56.55 Em4-Me1 11 11 100.00% 0.14 34.23 Em5-Me1 15 15 100.00% 0.57 48.55 Em5-Me2 7 7 100.00% 0.45 19.65 Mean 15 13 92.00% 0.42 32.25 Total 144 136 322.99 a: Number of total loci (NTL); b: Number of polymorphic loci (NPL); c: Polymorphic ratio(P %); d: Polymorphic information content (PIC); e: Resolving power (Rp). Table 3. Genetic diversity parameters in the studied Glaucium species. SP N Na Ne I He UHe %P G. fimbrilligerum 16.000 0.113 1.099 0.292 0.27 0.32 48.23% G. corniculatum var. corniculatum 12.000 1.445 1.190 0.271 0.284 0.292 55.91% G. oxylobum var. oxylobum 12.000 0.228 1.880 0.444 0.40 0.33 66.50% G. grandiflorum subsp. grandiflorum var. grandiflorum 10.000 0.288 1.029 0.231 0.17 0.19 44.38% G. contortuplicatum var. cantortuplicatum 15.000 0.772 1.095 0.288 0.35 0.27 62.05% Abbreviations: (N = number of samples, Na= number of different alleles; I= Shannon’s information index, He = gene diversity, UHe = unbi- ased gene diversity, P%= percentage of polymorphism, populations). 35Morphometric analysis and genetic diversity in Glaucium using sequence related amplified polymorphism sistent with the NJ grouping and AMOVA. K = 5 indi- cates the existence of five genetic groups. The Evanno test on STRUCTURE analysis yielded a similar result, with a large peak at k = 5. The Organization plot (Fig. 5, 6) revealed further information about the genetic struc- ture of the species analyzed, as well as common ances- tral alleles and/or gene flow among Glaucium species. This plot demonstrated the genetic difference between species 1 and 2 (which were colored differently), as well as 3 and 4, 5. This is consistent with the Neighbor join- ing dendrogram that was previously provided. The other species’ allele compositions are diverse, and they vary genetically from one another. The low Nm value (0.388) indicates limited gene flow or ancestrally shared alleles between the species studied and supports genetic strati- fication as indicated by K-Means and STRUCTURE analyses. Population assignment test also agreed with Nm result and could not identify significant gene flow among members of the studied species. DISCUSSION We employed morphological and molecular (SRAP) data to determine species relationships in Glaucium spe- Figure 4. Dendrograms of Glaucium species. Figure 5. Evanno’s test of SRAP data in Glaucium populations stud- ied. Figure 6. STRUCTURE plot of SRAP data in Glaucium populations studied. 36 Tao Shu, Chao Li, Chen She, Huan-Ping Zhao cies in this work. Morphological analyses of Glaucium species showed that quantitative indicators (ANOVA test results) and qualitative characteristics are well differen- tiated from each other. PCA analysis suggests that mor- phological characters such as corolla color, pedicel hair, stem hair, leaf hair, petiole hair, width of petal have the potentials to identify and delimitate Glaucium species. Principal component analysis results suggests the utilization of morphological characters to identify and delimitate Glaucium species. Morphological characters including corolla color, the pedicel hair, the stem hair, the leaf hair, the petiole hair,width of petal play key role in plant systematics and taxonomy. Our work also highlighted the significance of morphological characters and molecular data to identify and study species genet- ic diversity. In general, genetic relationships obtained from SRAP data coincides with morphometric results. This is in accordance with the parameters of AMOVA and genetic diversity results. SRAP molecular markers detected clear genetic difference among species. These results indicate that SRAP have potentials to study plant systematics and taxonomy in Glaucium members. Given the negative impact of biodiversity threats and overexploitation of Glaucium plant species in Iran, it is necessary to conduct genetic diversity studies on Glau- cium species. Genetic diversity based studies pave our understanding to develop conservation strategies (Esfan- dani-Bozchaloyi et al. 2017). Genetic diversity studies are conducted through appropriate selection of primers and indexes including Polymorphic information con- tent (PIC) and marker index (MI) are important indexes to fathom genetic variation in species (Hou et al., 2021; Huang et al., 2021). Common logic suggests that dif- ferent makers have different abilities to assess genetic diversity, and usually, genetic diversity is linked with polymorphism (Jia et al., 2020; Karasakal et al., 2020a; 2020b; Khayatnezhad and Gholamin 2020a; 2020b). In this research, we reported PIC values of SRAP primers from 0.14 to 0.63, with a mean value of 0.42. PIC values indeed show low and high genetic diversity among geno- types. Values between zero and 0.25 indicate minimal genetic diversity; values between 0.25 and 0.50 indicate moderate genetic diversity. Additionally, values greater than 0.5 are linked with a high level of genetic diversity (Tams et al. 2005; Wasana et al 2021; Hopla et al 2021; Fikirie et al 2020). Present results highlighted the effi- ciency of SRAP markers to estimate genetic diversity in Glaucium species. In our study, SRAP markers detected average percentage of polymorphism (92%). Additionally, the current study findings indicated the average PIC val- ues of SRAP makers (0.42) and the average RP (resolving power) values of SRAP markers (32.25). Current research results also described average PIC values of SRAP Glau- cium species have a lot more markers that show how well they’re doing now than other species have had (Maria et al. 2007; Dana et al. 2007). These current reported val- ues are higherIn the recent study, low gene flow (Nm) was detected among Glaucium species. The present study also depicted a significant correlation between genetic and geographical distances. Our findings revealed that isola- tion by distance (IBD) existed between Glaucium species (Mantet test results). Several mechanisms, such as isola- tion, local adaptation, and genetic drift, shape the species or population differentiation (Frichot et al. 2013; De Kort et al. 2014). The amount of variation in Na, Ne, H, and I indices showed that there was a lot of genetic variation in Glaucium species. The magnitude of variability among Dendrogram and principal component analysis results showed clear difference among Glaucium species. This shows the high utilization of the SRAP technique to identify Glaucium species. Our results have implications for conservation and breeding programs. Furthermore, it may identify suitable ecotypes for forage and pasture. There are two possible explanations for why isolated populations don’t have any differences from each other. The first hypoth- esis said that genetic diversity within and between pop- ulations shows how gene flow happens, which led to smaller populations (Dostálek et al., 2010). The second hypothesis is that people who live close to each other are better connected through gene flow than people who live far away. The morphological, palynological, and phylogenetic features of ten Glaucium taxa were studied (Fatma Mun- gan Kiliç et al., 2019). A total of 10 Although some of the morphological characters of the taxa examined were following the information contained in Flora of Turkey (Cullen 1965), it was noticed that some of their proper- ties were different. In addition, the data yielded from Mory’s (1979) study and those yielded as a result of our measurements were compared. In this comparison, the major similarity was observed in terms of the morpho- Table 4. Molecular variance analysis Source df SS MS Est. Var. % ΦPT Among Pops 11 1221.364 88.789 12.164 77% 77% Within Pops 170 114.443 6.88 5.238 23% Total 181 1385.807 17.060 100% df: degree of freedom; SS: sum of squared observations; MS: mean of squared observations; EV: estimated variance; ΦPT: proportion of the total genetic variance among individuals within an accession, (P < 0.001). 37Morphometric analysis and genetic diversity in Glaucium using sequence related amplified polymorphism logical and palynological characters. In a micromacro- morphological study performed by Gran and Sharifnia (2008) of 18 Glaucium taxa, the species G. haussknech- tii has been recognized as synonymous with G. grandi- florum based on the analyses of 28 qualitative and 37 quantitative characters. According to Fatma Mungan Kiliç et al (2019) the Glaucium taxa were divided into two groups with respect to stem hairs. Taxa with pubes- cence stems were G. corniculatum subsp. corniculatum and G. corniculatum subsp. refractum, G. grandiflorum var. grandiflorum, G. grandiflorum var. torquatum, G. grandiflorum var. haussknechtii and G. secmenii, while the taxa with hairless stems were G. flavum, G. leiocar- pum, G. acutidentatum and G. cappadocicum. The find- ings of phylogenetic analysis revealed that the Glaucium taxa were classified into two major clades using matK and ITS3-6 DNA sequences, which is consistent with the hairiness of their stems, petal color, and seed testa out- line. The taxa included in these two sub-clades were also compatible with ovary tubercle. ACKNOWLEDGEMENT Funding: The Science and Technology Research Pro- ject of Henan Province(No: 142102210554). REFERENCES Abeshu, Y., Zewdu, A. 2020. Developing Calibration Model for Prediction of Malt Barley Genotypes Quality Traits using Fourier Transform near Infra- red Spectroscopy. Agriculture and Food Sciences Research, 7(1), 38-45. Arabi, Z. et al. 2017. Seed micromorphology and its sys- tematic significance in tribe Alsineae (Caryophyllace- ae). Flora 234: 41-59. Azizian, D. and Alishahi Norani, F. (1997) Introduction of Latcifers in the poppy family emphasis on anatom- ical structures contains laticifer. Quarterly education- al expert journal of ministry of construction Jahad. Pajohesh and Sazandegi 34: 52-57. Cullen, J., 1966: Glaucium. In: Rechinger, K. H. (ed.), Flo- ra Iranica 34, 2 –7. Akad. Druck- und Verlagsanstalt. Carlquist, S. and Hoekman, D.A. (1985) Ecological wood anatomy of southern Californian flora. Internation- al Associantion of Wood Anatomists Bulletin New Series 6: 319-347. Carlquist, S. and Zona, S. (1988) Wood anatomy of Papa- veraceae, with comments on vessel restriction pat- terns. International Associantion of Wood Anato- mists Bulletin New Series 9: 253-267. Chimwamurombe, P.M., Luchen, C.C., Mataranyika, P.N. 2020. Redefining Global Food Security: Do we real- ly have a Global Food Crisis?. Agriculture and Food Sciences Research, 7(1), 105–112. De Kort H, Vandepitte K, Mergeay J, Honnay O (2014). Isolation, characterization and genotyping of single nucleotide polymorphisms in the non-model tree species Frangula alnus (Rhamnaceae). Conserva- tion Genetics Resources 6(2):267-269. https://doi. org/10.1007/s12686-013-0083-6 Dostálek T, Münzbergová Z, Plačková I. 2010. Genetic diversity and its effect on fitness in an endangered plant species, Dracocephalum austriacum L. Conserv Genet. 11:773–783. Dadzie, R.G., Amoah, R.S., Ampofo-Asiama, J., Quaye, B., Kizzie-Hayford, N., Abano, E.E. 2021. Improving the Storage Quality of Eggplants (Solanum Aethiopi- cum L.) Fruit using Aloe Vera Gel Coating . Journal of Food Technology Research, 8(2), 58–66. Esfandani -Bozchaloyi S, Sheidai M, Keshavarzi M, Noor- mohammadi Z. (2018c) Morphometric and ISSR- analysis of local populations of Geranium molle L. from the southern coast of the Caspian Sea. Cytol Genet. 52(4):309–321. Esfandani -Bozchaloyi S, Sheidai M. (2018d) Molecu- lar diversity and genetic relationships among Gera- nium pusillum and G. pyrenaicum with inter sim- ple sequence repeat (ISSR) regions. Caryologia. 71(4):1-14. Esfandani-Bozchaloyi S, Sheidai M, Kalalegh M (2019). Comparison of DNA extraction methods from Gera- nium (Geraniaceae). Acta Bot. Hung. 61(3-4):251- 266. Esfandani-Bozchaloyi S, Sheidai M, Keshavarzi M, Noor- mohammadi Z. (2018a) Species Relationship and Population Structure Analysis In Geranium Subg. Robertium (Picard) Rouy With The Use of ISSR Molecular Markers. Act Bot Hung. 60(1–2):47–65. Esfandani-Bozchaloyi S, Sheidai M, Keshavarzi M, Noor- mohammadi Z. (2018b) Species Identification and Population Structure Analysis In Geranium Subg. Geranium (Geraniaceae) . Hacquetia. 17(2):235–246. Esfandani-Bozchaloyi S, Sheidai M, Keshavarzi M, Noor- mohammadi Z. (2017) Genetic and morphological diversity in Geranium dissectum (Sec. Dissecta, Gera- niaceae) populations. Biologia. 72(10):1121- 1130. Esfandani-Bozchaloyi S, Sheidai M, Kalalegh M (2019) Comparison of DNA extraction methods from Gera- nium (Geraniaceae). Acta Botanica Hungarica 61(3- 4):251-266. https://doi.org/10.1556/034.61.2019.3-4.3 Fikirie, K., Bezu, A., Eshetu, M., Bekele, D., Rabo, M. 2020. Evaluate Technical Standards of Implement- ed Soil Bund in Central Rift Valley of Ethiopia: The 38 Tao Shu, Chao Li, Chen She, Huan-Ping Zhao Case of Adama, Lume and Dodota Districts. Agricul- ture and Food Sciences Research, 7(1), 51–57. Frankham R (2005) Stress and adaptation in conservation genetics. J Evol Biol. 18(4):750-755. Frichot E, Schoville SD, Bouchard G, François O (2013) Testing for Associations between Loci and Environ- mental Gradients Using Latent Factor Mixed Models. Molecular Biology and Evolution 30(7):1687-1699. https://doi.org/10.1093/molbev/mst063 Gondal, A.H., Farooq, Q., Sohail, S., Kumar, S.S., Toor, M.D., Zafar, A., Rehman, B. 2021. Adaptability of Soil pH through Innovative Microbial Approach. Current Research in Agricultural Sciences, 8(2), 71–79. Gran, A., Sharifnia, F., 2008: Micro–macrophological studies of the genus Glaucium (Papaveraceae) in Iran. The Iranian Journal of Botany 14, 22–38. Gholamin, R. and M. Khayatnezhad 2020. “The Study of Path Analysis for Durum Wheat (Triticum durum Desf.) Yield Components.” Bioscience Biotechnology Research Communications 13: 2139-2144. Gholamin, R. and M. Khayatnezhad 2021. “Impacts of PEG-6000-induced Drought Stress on Chlorophyll Content, Relative Water Content (RWC), and RNA Content of Peanut (Arachis hypogaea L.) Roots and Leaves.” Bioscience Research 18: 393-402. Guo, L.-N., C. She, D.-B. Kong, S.-L. Yan, Y.-P. Xu, M. Khayatnezhad And F. Gholinia 2021. “Predic- tion of the effects of climate change on hydroelec- tric generation, electricity demand, and emissions of greenhouse gases under climatic scenarios and optimized ANN model.” Energy Reports 7: 5431- 5445. Hou, R., S. Li, M. Wu, G. Ren, W. Gao, M. Khayatnezhad And F. Gholinia 2021. “Assessing of impact climate parameters on the gap between hydropower supply and electricity demand by RCPs scenarios and opti- mized ANN by the improved Pathfinder (IPF) algo- rithm.” Energy 237: 121621. Hopla, G.A., Sun, Y., Sun, C., Onautshu, O. 2021. Impact of the Aerobic Mesophilic Microorganisms on Black Sigatoka of Bananas According to the Cropping Sys- tems in the Region of Kisangani (Case of the old secondary forest). Agriculture and Food Sciences Research, 8(1), 1–9. Huang, D., J. Wang And M. Khayatnezhad 2021. “Estima- tion of Actual Evapotranspiration Using Soil Mois- ture Balance and Remote Sensing.” Iranian Journal of Science and Technology, Transactions of Civil Engi- neering: 1-8. Hammer O, Harper D, Ryan P (2001) PAST: Paleonto- logical Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica 4(1):1-9. Judd, W. S., Campbell, C. S., Kellogg, E. A. and Stevens, P. F. (1999) Plant systematics: A phylogenetic Approach. Sinauer, Sunderland. Jaccard P (1908) Nouvelles Recherches Sur la Distribu- tion Florale. Bulletin de la Societe Vaudoise des Sci- ences Naturelles 44(163):223-270. https://doi.org/ 10.5169/seals-268384 Jia, Y., M. Khayatnezhad and S. Mehri 2020. “Population differentiation and gene flow in Rrodium cicutarium: A potential medicinal plant.” Genetika 52: 1127-1144. Karasakal, A., M. Khayatnezhad and R. Gholamin 2020a. “The Durum Wheat Gene Sequence Response Assessment of Triticum durum for Dehydration Situ- ations Utilizing Different Indicators of Water Defi- ciency.” Bioscience Biotechnology Research Commu- nications 13: 2050-2057. Karasakal, A., M. Khayatnezhad and R. Gholamin 2020b. “The Effect of Saline, Drought, and Presowing Salt Stress on Nitrate Reductase Activity in Varieties of Eleusine coracana (Gaertn).” Bioscience Biotechnol- ogy Research Communications 13: 2087-2091. Khayatnezhad, M. and R. Gholamin 2020a. “A Modern Equation for Determining the Dry-spell Resistance of Crops to Identify Suitable Seeds for the Breed- ing Program Using Modified Stress Tolerance Index (MSTI).” Bioscience Biotechnology Research Com- munications 13: 2114-2117. Khayatnezhad, M. and R. Gholamin 2020b. “Study of Durum Wheat Genotypes’ Response to Drought Stress Conditions.” Helix 10: 98-103 Khayatnezhad, M. and R. Gholamin 2021. “The Effect of Drought Stress on the Superoxide Dismutase and Chlorophyll Content in Durum Wheat Genotypes.” Advancements in Life Sciences 8: 119-123. Kadereit, J. W., 1993: Glaucium. In: Kubitzki, K. Rohwer, J. C., Bittrichotteidedelberg (eds.), The families and Genera of Vascular Plants, 1–663. Springer Verlag, Berlin. Kadereit, J. W., Blattner, F. R., Jork, K. B., Schwarzbach, A. E., 1994: Phylogenetic analysis of the Papaver- ceae s. 1. (including Fumariaceae, Hypecoaceae and Pteridophyllum) based on morphological characters. Botanische Jahrbücher für Systematik und Pflanz- engeographie 116, 361–390. Li G, Quiros CF(2001) Sequence-related amplified poly- morphism (SRAP), a new marker system based on a simple PCR reaction: its application to mapping and gene tagging in Brassica. Theoretical and Applied Genetics103(2): 455-461. https://doi.org/ 10.1007/ s001220100570 Mobayen, S., 1985: Glaucium. In: Flora of Iran, vascular plants 3, 154 –170. Tehran University, Iran. 39Morphometric analysis and genetic diversity in Glaucium using sequence related amplified polymorphism Metcalfe, C. R. and Chalk, L. (1950) Anatomy of dicoty- ledons 1: 74-78. Clarendon Press, Oxford. Mory, B., 1979: Beitragezur Kenntnis der Sippenstruktur der Gattung Glaucium Miller (Papaveraceae). Feddes Repertorium 39, 499–595. Ma, A., J. Ji and M. Khayatnezhad 2021a. “Risk-con- strained non-probabilistic scheduling of coordinated power-to-gas conversion facility and natural gas stor- age in power and gas based energy systems.” Sustain- able Energy, Grids and Networks: 100478. Ma, S., M. Khayatnezhad and A. A. Minaeifar 2021b. “Genetic diversity and relationships among Hyperi- cum L. species by ISSR Markers: A high value medic- inal plant from Northern of Iran.” Caryologia 74: 97-107. Peng, X., M. Khayatnezhad and L. Ghezeljehmeidan 2021. “Rapd profiling in detecting genetic variation in stellaria l. (caryophyllaceae).” Genetika-Belgrade 53: 349-362. Podani J (2000) Introduction to the exploration of multi- variate data. Backhuyes, Leide, Netherlands. Prevost A, Wilkinson MJ (1999) A new system of com- paring PCR primers applied to ISSR fingerprinting of potato cultivars. Theoretical and Applied Genetics 98(1):107-112. https://doi.org/10.1007/s001220051046 Peakall R, Smouse PE (2006) GENALEX 6: Genetic Anal- ysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes 6(1):288-295. https://doi.org/10.1111/j.1471-8286.2005.01155.x Robarts DWH, Wolfe AD (2014) Sequence-related amplified polymorphism (SRAP) markers: A poten- tial resource for studies in plant molecular biology. Applications in Plant Sciences 2(7):apps.1400017. htt- ps://doi.org/10.3732/apps.1400017 Roldán-Ruiz I, Dendauw J, Van Bockstaele E, Depicker A, De Loose M (2000) AFLP markers reveal high polymorphic rates in ryegrasses (Lolium spp.). Molecular Breeding 6(2): 125-134. https://doi. org/10.1023/A:1009680614564 Ren, J. and M. Khayatnezhad 2021. “Evaluating the stormwater management model to improve urban water allocation system in drought conditions.” Water Supply. Rechinger, K. H. and Cullen, J. (1966) Papaveraceae. In: Flora Iranica (ed. Rechinger, K. H.) 34: 1-26. Akad- emische Druck-u. Verlagsanstalt, Graz. Solereder, H. (1908) Systematic anatomy of the dicotyle- dons (English edition) 1. 823-824. Clarendon Press, Oxford Si, X., L. Gao, Y. Song, M. Khayatnezhad and A. A. Minaeifar 2020. “Understanding population differen- tiation using geographical, morphological and genet- ic characterization in Erodium cicunium.” Indian J. Genet 80(4): 459-467. Sun, Q., D. Lin, M. Khayatnezhad and M. Taghavi 2021. “Investigation of phosphoric acid fuel cell, linear Fresnel solar reflector and Organic Rankine Cycle polygeneration energy system in different climatic conditions.” Process Safety and Environmental Pro- tection 147: 993-1008. Sun, X. and M. Khayatnezhad 2021. “Fuzzy-probabilistic modeling the flood characteristics using bivariate frequency analysis and α-cut decomposition.” Water Supply. Tao, Z., Z. Cui, J. Yu and M. Khayatnezhad 2021. “Finite Difference Modelings of Groundwater Flow for Constructing Artificial Recharge Structures.” Irani- an Journal of Science and Technology, Transactions of Civil Engineering.Tavakkoli, Z. and Assadi, M. 2016. Evaluation of seed and leaf epidermis charac- ters in the taxonomy of some annual species of the genus Papaver (Papaveraceae). – Nord. J. Bot. 34: 302–321. Tavakkoli, Z. and Assadi, M. 2019. A taxonomic revision of the genus Glaucium (Papaveraceae) in Iran. – Acta Bot. Croat. 78: 57–65. Tams SH, Melchinger AE, Bauer E (2005) Genetic simi- larity among European winter triticale elite germ- plasms assessed with AFLP and comparisons with SSR and pedigree data. Plant Breeding 124(2):154- 160. https://doi.org/10.1111/j.1439-0523.2004.01047.x Wu Y-G, Guo Q-S, He J-C, Lin Y-F, Luo L-J, Liu G-D (2010) Genetic diversity analysis among and within populations of Pogostemon cablin from China with ISSR and SRAP markers. Biochemical Systematics and Ecology 38(1):63-72. https://doi.org/10.1016/j. bse.2009.12.006 Wang, C., Y. Shang and M. Khayatnezhad 2021. “Fuzzy Stress-based Modeling for Probabilistic Irrigation Planning Using Copula-NSPSO.” Water Resources Management. Wasana, W.L.N., Ariyawansha, R., Basnayake, B. 2021. Development of an Effective Biocatalyzed Organic Fertilizer Derived from Gliricidia Sepium Stem Bio- char. Current Research in Agricultural Sciences, 8(1), 11–30. Yeh FC, Yang R, Boyle T (1999). POPGENE. Microsoft Windows-based freeware for population genetic anal- ysis. Release 1.31. University of Alberta, 1-31.