Betaine Aldehyde Dehydrogenase (BADH) vs. Flavodoxin (Fld): Two Important Genes for Enhancing Plants Stress Tolerance and Productivity.

Abiotic stresses, mainly salinity and drought, are the most important environmental threats that constrain worldwide food security by hampering plant growth and productivity. Plants cope with the adverse effects of these stresses by implementing a series of morpho-physio-biochemical adaptation mechanisms. Accumulating effective osmo-protectants, such as proline and glycine betaine (GB), is one of the important plant stress tolerance strategies. These osmolytes can trigger plant stress tolerance mechanisms, which include stress signal transduction, activating resistance genes, increasing levels of enzymatic and non-enzymatic antioxidants, protecting cell osmotic pressure, enhancing cell membrane integrity, as well as protecting their photosynthetic apparatus, especially the photosystem II (PSII) complex. Genetic engineering, as one of the most important plant biotechnology methods, helps to expedite the development of stress-tolerant plants by introducing the key tolerance genes involved in the biosynthetic pathways of osmolytes into plants. Betaine aldehyde dehydrogenase (BADH) is one of the important genes involved in the biosynthetic pathway of GB, and its introduction has led to an increased tolerance to a variety of abiotic stresses in different plant species. Replacing down-regulated ferredoxin at the acceptor side of photosystem I (PSI) with its isofunctional counterpart electron carrier (flavodoxin) is another applicable strategy to strengthen the photosynthetic apparatus of plants under stressful conditions. Heterologous expression of microbially-sourced flavodoxin (Fld) in higher plants compensates for the deficiency of ferredoxin expression and enhances their stress tolerance. BADH and Fld are multifunctional transgenes that increase the stress tolerance of different plant species and maintain their production under stressful situations by protecting and enhancing their photosynthetic apparatus. In addition to increasing stress tolerance, both BADH and Fld genes can improve the productivity, symbiotic performance, and longevity of plants. Because of the multigenic and complex nature of abiotic stresses, the concomitant delivery of BADH and Fld transgenes can lead to more satisfying results in desired plants, as these two genes enhance plant stress tolerance through different mechanisms, and their cumulative effect can be much more beneficial than their individual ones. The importance of BADH and Fld genes in enhancing plant productivity under stress conditions has been discussed in detail in the present review.

Characterization of specific DNA markers at VRN-H1 and VRN-H2 loci for growth habit of barley genotypes.

Requirement of vernalization is an important factor which plays a crucial role in cereals to transit from vegetative to reproductive phase. There are three types of growth habit in barley: winter, spring and facultative types; in which spring type does not require vernalization but winter and facultative genotypes require full and partial vernalization, respectively. Combination of two loci, Vrn-h1 and Vrn-h2, regulates vernalization in barley genotypes. Specific DNA markers have been identified for growth habit regulator genes in barley. In this study, we examined 24 barley genotypes using specific primers for detecting Vrn-h1and Vrn-h2 loci. Results showed that among all differently suggested primer combinations, a few markers were precisely correlated with seasonal growth habit in barley. The specific markers of 600, 600 and 200 bps were verified for ZCCT-Ha, ZCCT-Hb and ZCCT-Hc loci, respectively. Our field growth habit test showed that cultivar Bahman as a winter growth habit, where all the others genotypes exhibited spring growth habit. By using specific primers for Vrn-h1, only Bahman cultivar produced 616 bp and 830 bp fragments and spring genotypes showed 574 bp or 616 bp alleles without any amplification for 830 bp fragments. Therefore, presence of 616 bp and 830 bp alleles together in each genotype can be considered as an informative marker for winter growth habit in barley. These informative markers can be used easily in barley breeding programmes for detection of growth habit types in the seedling stage.

Chemical Compositions, Somatic Embryogenesis, and Somaclonal Variation in Cumin.

This is the first report evaluating the relationship between the chemical compositions of cumin seeds (based on the analysis of the content of catalase, ascorbate peroxidase, proline, protein, terpenic compounds, alcohol/phenols, aldehydes, and epoxides) and the induction efficiency of somatic embryogenesis in two Iranian superior cumin landraces (Golestan and North Khorasan). Cotyledons isolated from Golestan landrace seeds cultivated on MS medium supplemented with 0.1 mg/L kinetin proved to be the best primary explant for the induction of somatic embryogenesis as well as the regeneration of the whole plantlet. Results indicated that different developmental stages of somatic embryos were simultaneously observed on a callus with embryogenic potential. The high content of catalase, ascorbate peroxidase, proline, and terpenic hydrocarbons and low content of alcoholic and phenolic compositions had a stimulatory effect on somatic embryogenesis. Band patterns of RAPD markers in regenerated plants were different from those of the mother plants. This may be related to somaclonal variations or pollination system of cumin. Generally, measurement of chemical compositions can be used as a marker for evaluating the occurrence of somatic embryogenesis in cumin. Also, somaclonal variations of regenerated plants can be applied by the plant breeders in breeding programs.

An artificial intelligence approach for modeling volume and fresh weight of callus - A case study of cumin (Cuminum cyminum L.).

Cumin (Cuminum cyminum Linn.) is valued for its aroma and its medicinal and therapeutic properties. A supervised feedforward artificial neural network (ANN) trained with back propagation algorithms, was applied to predict fresh weight and volume of Cuminum cyminum L. calli. Pearson correlation coefficient was used to evaluate input/output dependency of the eleven input parameters. Area, feret diameter, minor axis length, perimeter and weighted density parameters were chosen as input variables. Different training algorithms, transfer functions, number of hidden nodes and training iteration were studied to find out the optimum ANN structure. The network with conjugate gradient fletcher-reeves (CGF) algorithm, tangent sigmoid transfer function, 17 hidden nodes and 2000 training epochs was selected as the final ANN model. The final model was able to predict the fresh weight and volume of calli more precisely relative to multiple linear models. The results were confirmed by R(2)≥0.89, R(i)≥0.94 and T value ≥0.86. The results for both volume and fresh weight values showed that almost 90% of data had an acceptable absolute error of ±5%.