Optimizing in vitro shoot regeneration conditions in wheat is one of the important steps in successful micropropagation and gene transformation. Various factors such as genotypes, explants, and phytohormones affect in vitro regeneration of wheat, hindering the ability to tailor genotype-independent protocols. Novel computational approaches such as artificial neural networks (ANNs) can facilitate modeling and predicting outcomes of tissue culture experiments and thereby reduce large experimental treatments and combinations. In this study, generalized regression neural network (GRNN) were used to model and forecast in vitro shoot regeneration outcomes of wheat on the basis of 10 factors including genotypes, explants, and different concentrations of 6-benzylaminopurine (BAP), kinetin (Kin), 2,4-dichlorophenoxyacetic acid (2,4-D), indole-3-acetic acid (IAA), indole-3-butyric acid (IBA), 1-naphthaleneacetic acid (NAA), zeatin, and CuSO4. In addition, GRNN was linked to a genetic algorithm (GA) to identify an optimized solution for maximum shoot regeneration. Results indicated that GRNN could accurately predict the shoot regeneration frequency in the validation set with a coefficient determination of 0.78. Sensitivity analysis demonstrated that shoot regeneration frequency was more sensitive to variables in the order of 2,4-D > explant > genotype < zeatin < NAA. Results of this study suggest that GRNN-GA can be used as a tool, besides experimental approaches, to develop and optimize in vitro genotype-independent regeneration protocols.

Garlic (Allium sativum L.) is an economically important, monocotyledonous plant with a strong taste and odor. Drought stress adversely affects its growth, development, and yield, particularly during the bolting/bulbing stage. Herein we performed RNA-seq to assess transcriptomic changes induced by drought stress in bolting/bulbing hardneck garlic plants (Purple Glazer). We observed that drought stress significantly reduced photosynthesis rate, fresh weight, and leaf water content. Transcriptomic analysis of garlic leaves under normal conditions and drought stress led to the identification of 5215 differentially expressed genes (2748 up- and 2467 downregulated). The upregulated DEGs were primarily involved in “biological process”, “metabolic process”, “oxidation-reduction process”, carbohydrate and lipid metabolism, and “proteolysis”, whereas the downregulated DEGs were mainly involved in “biological process” and metabolism of various molecules. In addition, genes encoding abscisic acid biosynthetic and catabolic enzymes, heat shock proteins, and E3 ubiquitin ligases were significantly altered by drought stress, indicating involvement in drought tolerance. A further comparison with the DEGs related to salinity stress-treated garlic revealed 867 and 305 DEGs with a similar and reverse expression alteration tendency, respectively.

Crop growth analysis is used for the assessment of crop yield potential and stress tolerance. Capturing continuous plant growth has been a goal since the early 20th century; however, this requires a large number of replicates and multiple destructive measurements. The use of machine vision techniques holds promise as a fast, reliable, and non-destructive method to analyze crop growth based on surrogates for plant traits and growth parameters. We used machine vision to infer plant size along with destructive measurements at multiple time points to analyze growth parameters of spring wheat genotypes. We measured side-projected area by machine vision and RGB imaging. Three traits, i.e., biomass (BIO), leaf dry weight (LDW), and leaf area (LA), were measured using low-throughput techniques. However, RGB imaging was used to produce side projected area (SPA) as the high throughput trait. Significant effects of time point and genotype on BIO, LDW, LA, and SPA were observed. SPA was a robust predictor of leaf area, leaf dry weight, and biomass. Relative growth rate estimated using SPA was a robust predictor of the relative growth rate measured using biomass and leaf dry weight. Large numbers of entries can be assessed by this method for genetic mapping projects to produce a continuous growth curve with fewer replicates.

Vascular bundles play important roles in transporting nutrients, growth signals, amino acids, and proteins between aerial and underground tissues. In order to understand these sophisticated processes, a comprehensive analysis of the roles of the components located in the vascular tissues is required. A great deal of data has been obtained from proteomic analyses of vascular tissues in plants, which mainly aim to identify the proteins moving through the vascular tissues. Here, different aspects of the phloem and xylem proteins are reviewed, including their collection methods, and their main biological roles in growth, and biotic and abiotic stress responses. The study of vascular proteomics shows great potential to contribute to our understanding of the biological mechanisms related to development and defense in plants.

To examine physiological responses of garlic to salinity, 17-day-old seedlings of eight soft-neck accessions were treated with 200 mM NaCl for seven days in a hydroponic system. Several morphological and physiological traits were measured at the end of the treatment, including shoot height, shoot fresh weight, shoot dry weight, root length, root fresh weight, root dry weight, photosynthesis rate, and concentrations of Na+ and K+ in leaves. The principal component analysis showed that shoot dry weight and K+/Na+ ratio contribute the most to salt tolerance among the garlic accessions. As a result, salt-tolerant and sensitive accessions were grouped based on these two parameters. Furthermore, to investigate the molecular mechanisms in garlic in response to salinity, the transcriptomes of leaves and roots between salt-tolerant and salt-sensitive garlic accessions were compared. Approximately 1.5 billion read pairs were obtained from 24 libraries generated from the leaves and roots of the salt-tolerant and salt-sensitive garlic accessions. A total of 47,509 genes were identified by mapping the cleaned reads to the garlic reference genome. Statistical analysis indicated that 1282 and 1068 genes were upregulated solely in the tolerant leaves and roots, whereas 1505 and 1203 genes were downregulated exclusively in the tolerant leaves and roots after NaCl treatment, respectively. Functional categorization of these genes revealed their involvement in a variety of biological processes. Several genes important for carotenoid biosynthesis, auxin signaling, and K+ transport were strongly altered in roots by NaCl treatment and could be candidate genes for garlic salt tolerance improvement.