Seyed Ahmad Sadat-Noori

TL;DR: In this paper, artificial neural network (ANN) along with multiple regression model (MLR) were applied to predict the seed yield of ajowan through seed yield components, such as number of secondary branches, shoot dry weight, number of umbellets in an inflorescence, and biological yield.

TL;DR: A high-precision image-processing approach was successfully applied to measure physical properties of embryogenic callus in Trachyspermum ammi (L.) Sprague (Ajowan) and the number of somatic embryos produced.

TL;DR: In this paper, two methods namely artificial neural network (ANN) and multiple regression model (MLR) were conducted to predict the oil content of ajowan from readily measurable plant characters.

TL;DR: Tissue culture-based and in planta Agrobacterium-mediated gene transformation methods were applied to enhance drought and salinity tolerance in ajowan medicinal plant using betaine aldehyde dehydrogenase (BADH) gene and the obtained transgenic plants are cultivable in unfavorable environments to give an acceptable level of useful secondary metabolites.

TL;DR: The importance of BADH and Fld genes in enhancing plant productivity under stress conditions has been discussed in detail in the present review as mentioned in this paper, and the concomitant delivery of these 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.