In order to investigate the solutes accumulation associated with salt tolerance of rice (Oryza sativa L.), two rice genotypes including IR651 (salt-tolerant) and IR29 (salt-sensitive) were grown hydroponically in the Youshida nutrient solution. Salinity treatment was imposed 3 weeks after sowing using NaCl in two levels 0 and 100 mmol. Samples were separately collected from the youngest (sixth) leaves, leaf sheaths and roots at 72 and 240 h after salinization; then Na + , K + , Ca 2+ , Mg 2+ , P, Mn 2+ , Cl -and total soluble sugars concentration and Na + /K + ratio were determined. Total dry weight of both genotypes decreased with the application of NaCl. Salinity caused higher accumulation of Na + and Cl -in the sixth leaf and leaf sheath of IR29 than in IR651 while their concentration in root of IR651 was higher. K + concentration was decreased in the sixth leaf and leaf sheath of IR29 under NaCl stress. Reduction in Ca 2+ and Mg 2+ concentrations were observed in sixth leaves of both genotypes. P concentration was increased in leaf sheath and root of IR29 under saline conditions while it showed no changes in IR651. Our results indicated that the tolerant genotype had mechanisms to prevent high Na + and Cl -accumulation in the sixth leaf. High total soluble sugars concentration in shoot of IR651 is probably for adjusting osmotic potential and better water uptake under salinity. These mechanisms help plant to avoid tissue death and enable to continue its growth and development under saline conditions.
Cell membrane thermal stability, antioxidant activity, phenolics content, Paraquat tolerance and kernel weight were compared for their ability to identify heat tolerant genotypes. Four wheat (Triticum aestivum L.) genotypes, Kauz, MTRWA116, Opata and W7984 were used in this study, Kauz and MTRWA116 being thermotolerant and thermosensitive, respectively. Plants were exposed to high temperatures of 39 and 35 degrees C and then their measurements form different techniques were compared to each other and to the controls. The experiments were run several times to measure the repeatability of the measurements. Although the amount of phenolic compounds increased under stress condition, there was no significant difference between tolerant and susceptible varieties. Membrane thermal stability, antioxidant activity, phenolics content and Paraquat tolerance did not provide repeatable data. Nor did they discriminate among tolerant and susceptible genotypes. Kernel weight, however, varied between tolerant and susceptible genotypes. The results indicate that kernel weight is more suited for heat stress screening than other physioloical techniques evaluated in this study.
Contamination of soils by lead (Pb) is of widespread occurrence as result of human, agricultural and industrial activities. A pot study was carried out to evaluate physio-biochemical responses (chlorophyll content, soluble protein, proline content and activities of enzymatic antioxidants) of 10 bread wheat genotypes to inoculation of plant growth promoting rhizobacteria (combination of Azospirillum brasilense and Azotobacter chroococcum) under Pb stress (0 and 65 mg kg-1). Result revealed that lead stress averagely decreased grain yield of wheat cultivars by 41.4 %. Lead stress increased lipid peroxidation and induced a significant accumulation of proline in leaves. Protein content decreased from 8-25.4% in different cultivars in Pbcontaminated soils. Activities of antioxidant enzymes, such as, ascorbate peroxidase, superoxide dismutase and catalase were significantly increased in the presence of lead. An increase in total hydrogen peroxide (H2O2) content was noticed under lead stress in all cultivars, which was similar to production of malondialdehyde (MDA). However, promotion of growth was evident in most cultivars as a consequence of rhizobacterial inoculation, since plant growth promoting rhizobacteria could improve grain yield, proline content and membrane integrity, while significantly reduced the production of MDA and H2O2. Total chlorophyll content considerably declined with Pb stress. Between cultivars the best performance under lead stress was observed in Sardari, Shahriyar and Gaspard which had the highest yield and antioxidants activity. Obtained results showed that inoculation with Azotobacter and Azospirillium possibly through bioremediation strategy can stimulate plant growth under adverse environmental conditions, such as heavy metal contamination.
Background High-throughput phenotyping and genomic selection accelerate genetic gain in breeding programs by advances in phenotyping and genotyping methods. This study developed a simple, cost-effective high-throughput image analysis pipeline to quantify digital images taken in a panel of 286 Iran bread wheat accessions under terminal drought stress and well-watered conditions. The color proportion of green to yellow (tolerance ratio) and the color proportion of yellow to green (stress ratio) was assessed for each canopy using the pipeline. The estimated tolerance and stress ratios were used as covariates in the genomic prediction models to evaluate the effect of change in canopy color on the improvement of the genomic prediction accuracy of different agronomic traits in wheat. Results The reliability of the high-throughput image analysis pipeline was proved by three to four times of improvement in the accuracy of genomic predictions for days to maturity with the use of tolerance and stress ratios as covariates in the univariate genomic selection models. The higher prediction accuracies were attained for days to maturity when both tolerance and stress ratios were used as fixed effects in the univariate models. The results of this study indicated that the Bayesian ridge regression and ridge regression-best linear unbiased prediction methods were superior to other genomic prediction methods which were used in this study under terminal drought stress and well-watered conditions, respectively. Conclusions This study provided a robust, quick, and cost-effective machine learning-enabled image-phenotyping pipeline to improve the genomic prediction accuracy for days to maturity in wheat. The results encouraged the integration of phenomics and genomics in breeding programs.
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