## 4 Discussion  
The morphological and physiological variations between genotypes are relatively unexplored resources that can not only provide crucial data on the capacity and performance of various crops under various climatic conditions but are also an invaluable genetic resource that could be used to improve yields [28]. Awareness of this natural diversity should encourage the use of modern (with  
Figure 5: Principal component analysis (PCA) plot showing the distribution and relationship between rice genotypes and studied traits. (**A**). normal condition, (**B**). T0.50 stress, (**C**). T1.00 stress, and (**D**). T1.50 stress. Figure 6: Pearson correlation (r) of nine growth and biochemical characters based on their values in unstressed and stressed conditions. (**A**). T0.00, (**B**). T0.50, (**C**). T1.00, and (**D**). T1.50. desirable traits) genotypes to improve crop yields. The present results showed natural diversity among the analyzed genotypes, indicating differential growth properties in control conditions for the six genotypes. For genotype screening, an investigation was conducted using 12 SSR markers, of which 11 were polymorphic bands. Similarly, [29] tested 16 rice genotypes with different drought sensitivity with SSR markers and found 60 polymorphic bands. Different rice genotypes of Heilongjiang Province were analyzed by [30] using SSR markers under stress conditions and the authors found, on average, three alleles that are comparable to our results. On the contrary, [18] reported an average of five alleles per locus in rice genotypes from Bangladesh and [31] reported nine alleles per locus in Ecuadorian rice genotypes. This difference was probably due to the genetic makeup, higher number of genotypes, and types of SSR markers analyzed. The mean of the PIC value in this study was higher than the PIC value (0.33) reported by [32] but lower than those reported by [29; 31], who observed an average of 0.62. The genetic distance between genotypes used in our study ranged from 0.33 to 0.88, which indicated high genetic divergence among the rice genotypes. Similarly, 314 rice genotypes from northern Laos were analyzed by SSR and a high distance was found [33]. Based on DNA analyses, it was proven that the six genotypes differ genetically each from other, and two SSR markers (RM443 and RM287) can be used for the identification of six rice genotypes due to their high PIC value. The data of the drought-tolerant response confirmed that there was a significant decrease in CI, CFW, CDW, and CL in all genotypes after PEG treatment; these responses were dose dependent. In stress conditions, a substantial decrease in the CIP, CFW, CDW, and CL parameters was observed in callus obtained from all of the genotypes, while an increase of CWT was displayed. These results followed similar trends to those observed in the callus of rice by [34; 35; 36]. In terms of results, Choman and Shawre showed similar performances under the non-stressed condition, and grew better than the other genotypes under the stress condition, exhibiting superior tolerance to osmotic stress. On the other hand, Kalar and Gwll Swr appeared to be the most sensitive to PEG stress. Concerning the ranking of genotypes based on phenotypic characterizations, the order of rice genotypes was: PEG resistant \(>\) susceptible, Choman \(>\) Shawre \(>\) White Bazyan \(>\) Red Bazyan \(>\) Gwll Swr \(=\) Kalar. Decreased growth of callus is caused by the negative impacts of PEG on the metabolic function of cells, including enzyme, nucleic acid, and protein synthesis, and the stability of the cell membrane. This negative effect of PEG decreases the rates of plant hormones and turgor pressure, which is considered a critical factor in regulating the growth and enlargement of cells [37; 38]. In addition, drought stress induces free radical formation by lipid peroxidation and therefore damages the membrane.