This review represent plants genetic diversity (PDG) generally in crop plant and especially in Barley  (Hordeum vulgare), can be studied (PDG) and stored as a (PGR) plant genetic resources as gene bank , DNA library for saved genetic material at long time and crops improvement can be utilized in breeding programs strategies in future. In this  study observed the significance of plant genetic diversity (PGD) and (PGR) especially on agriculturally important crops , analysis of plant genomic using molecular markers. Barley is a well important studies crops using as a model for study genetic plant, cultivated barley Hordeum vulgare easily hybridization by genetic fingerprinting with wiled barley Hordeum spontaneum. The molecular markers showed their relation with locus of geographic factors and imposed stresses. Here, discussed barley genomic through relationship between genotype and phenotype traits using molecular markers useful for genetic physiological maps construction.

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This article refers to viewing the role of molecular markers during analyzing the genome of plants and their importance in plant biotechnology. In recent years, we observed the role of molecular techniques in programs for improving plant breeding and preserving genetic resources has been observed, and molecular and biochemical indicators which represent basic material through determining the diversity between genotypes for indicators it is never affected by external surrounding conditions as always in the phenotype features. Molecular markers of DNA have been widely applied to answer a range of questions related to taxonomy, molecular evolution, population genetics, and genetic diversity, as well as monitoring trade in plants and food products , in addition to its having a role in studying gene expression , genetic mapping, and studies of species evolution providing fast and accurate results. In this work, the advantages and limitations of the molecular techniques applied in plant sciences such as: RAPD (Random Amplification Polymorphic DNA Marker); ISSR (Inter Simple Sequence Repeat Marker); SSR (Simple Sequence Repeat Marker); AFLP (Amplified Fragment Length Polymorphic Marker); RFLP (Restriction Fragment Length Polymorphism Marker); SNP (Single Nucleotide Polymorphism) and Real Time PCR.

Abstract. Al-Hadeithi ZSM, Jasim SA, Salahdin OD. 2022. Relation between resistance of Klebsiella pneumoniae to certain antibiotics and ESBL/PBP genes. Biodiversitas 23: 3902-3906. One of the most effective antibiotics on microbes or in treating infections caused by these most resistant microbes, as it belongs to the beta-lactam group such as cephalosporin and carbapenems, which are considered among the most important antibiotics that have wide activity compared to the rest of the other antibiotics and their effectiveness against two types of negative and positive bacteria. Antibiotic resistance is a major public health concern because it happens when antibiotics are used too much or not in the right way. The improved resistance of Klebsiella pneumoniae against the antibiotics because of the virulence factors make K. pneumoniae is the most prevalent pathogenic bacteria behind nosocomial infections. Finding demonstrates that ?-lactamase is implicated in K. pneumoniae antimicrobial resistance to ?-lactam antibiotics. The purpose of this study was to look into the relation among Extended-spectrum beta-lactamase (ESBL), and the molecular biological mechanisms of antibiotic resistance in K. pneumoniae. Through the period from February to July 2021 a total of 100 out of 350 isolates were found to be K. pneumoniae. Cultural, morphological, and biochemical studies were used to identify growth on blood agar and MacConkey agar. The results revealed that the tested isolates were highly resistant to Imipenem (63%) and Amikacin (24%), while Amoxi-clav exhibited poor resistance (2%). The qualitative real-time approach was used to detect BlaR1 and Bla1 genes for positive isolates that’s possess gene/ resistant isolate , and the findings revealed that 2 (16%), 4 (33%), 16 (88%), 7 (38%), 24 (100%), 20 (83%), 2 (66%), 2 (100%), 2 (100%), 60 (95%), and 57 (90%) for CIP, CRO, AK, TMP, AMC, and IMP respectively.