Analysis of genotype-by-environment interaction effect in barely genotypes using AMMI and GGE biplot methods.

Genotype-by-environment interaction (GEI) analysis play a key role in any breeding program involving the development of new varieties for cultivation across various environments or in a specific region. The additive main effects and multiplicative interaction (AMMI) method and the GGE biplot are the two main statistical tools that have emerged to analyze GEI in multi-environment trials (METs). The main goal of the present study was to identify the best-performing and stable barley genotypes for the warm regions of Iran. For this purpose, 18 new advanced barley genotypes were investigated in five warm locations in Iran during two cropping seasons (2021-2023). In all experiments, test genotypes were evaluated in a randomized complete block design (RCBD) with three replications. Based on results, grain yield was significantly dependent on environments (E), genotypes (G), and GEI. The GEI effect was further divided into three principal component axes (IPCAs). The AMMI method identified genotypes G3, G9, G10, and G14 as ideal genotypes due to their low IPCA scores and high performances. In the GGE biplot analysis, the initial two PCAs accounted for 49.36 % of the total variation of grain yield, including both G and GEI effects. Based on averaged two-year data, genotypes G3, G4, G10, and G14 showed particular adaptability in the Zabol and Moghan regions. Moreover, the ranking of test environments showed good discriminatory and representative abilities for the Zabol and Moghan regions, so these environments constituted a mega-environment in Iran's warm climate. The genotype ranking indicated G3, G10 and G14 genotypes as the superior genotypes with the highest grain yield and stability in different test environments. Moreover, these results were confirmed by the results obtained by WAASB and WAASBY biplots. In conclusion, genotypes G3, G10 and G14 can be suggested for commercial usage and cultivation in various regions in Iran's warm climate.

Comparison of phytochemical properties and expressional profiling of artemisinin synthesis-related genes in various Artemisia species.

The Artemisia genus belongs to the Asteraceae family and is used in the treatment of many different diseases such as hepatitis and cancer. So far, around 500 species of Artemisia have been found in different regions of the world. Artemisinin is one of the medicinal compounds found in Artemisia species. Hence, this medical feature encourages researchers to pay attention to various species of this genus to discover more genetic and phytochemical information. In the present study, five species of Artemisia including A. fragrans, A. annua, A. biennis, A. scoparia, and A. absinthium were compared to each other in terms of the artemisinin content and other phytochemical components. Moreover, the relative expression profiles of eight genes related to the accumulation and synthesis of artemisinin [including 4FPSF, DBR2, HMGR1, HMGR2, WIRKY, ADS, DXS, and SQS] were determined in investigated species. The result of high-performance liquid chromatography (HPLC) analysis showed that the content of artemisinin in various species was in the order of A. fragrans > A. annua > A. biennis > A. scoparia > A. absinthium. Based on the gas chromatography-mass spectrometry (GC-MS) analysis, 34, 26, 26, 24, and 20 phytochemical compounds were identified for A. scoparia, A. biennis, A. fragrans, A. absinthum, and A. annua species, respectively. Moreover, camphor (38.86%), ß-thujone (68.42%), spathulenol (48.33%), ß-farnesene (48.16%), and camphor (29.04%) were identified as the considerable compounds A. fragrans, A. absinthium, A. scoparia, A. biennis, and A. annua species, respectively. Considering the relative expression of the targeted genes, A. scoparia revealed higher expression for the 4FPSF gene. The highest relative expression of the DBR2, WIRKY, and SQS genes was found in A. absinthium species. Moreover, A. annua showed the highest expression of the ADS and DXS genes than the other species. In conclusion, our findings revealed that various species of Artemisia have interesting breeding potential for further investigation of different aspects such as medicinal properties and molecular studies.

Identification of High-Yielding Genotypes of Barley in the Warm Regions of Iran.

One of the most important effects of climatic changes is increasing temperatures and expanding water deficit stress in tropical and subtropical regions. As the fourth most important cereal crop, barley (Hordeum vulgare L.) is crucial for food and feed security, as well as for a sustainable agricultural system. The present study investigates 56 promising barley genotypes, along with four local varieties (Norooz, Oxin, Golchin, and Negin) in four locations to identify high-yielding and adapted genotypes in the warm climate of Iran. Genotypes were tested in an alpha lattice design with six blocks, which were repeated three times. Traits measured were the number of days to heading and maturity, plant height, thousand kernels weight, and grain yield. A combined analysis of variance showed the significant effects of genotypes (G), environments (E), and their interaction (GEI) on all measured traits. Application of the additive main-effect and multiplicative interaction (AMMI) model to the grain yield data showed that GEI was divided into three significant components (IPCAs), and each accounted for 50.93%, 30.60%, and 18.47%, respectively. Two selection indices [Smith-Hazel (SH) and multiple trait selection index (MTSI)] identified G18, G24, G29, and G57 as desirable genotypes at the four test locations. Using several BLUP-based indices, such as the harmonic mean of genotypic values (HMGV), the relative performance of genotypic values (RPGV), and the harmonic mean of the relative performance of genotypic values (HMRPGV), genotypes G6, G11, G22, G24, G29, G38, G52, and G57 were identified as superior genotypes. The application of GGE analysis identified G6, G24, G29, G52, and G57 as the high-yielding and most stable genotypes. Considering all statistical models, genotypes G24, G29, and G57 can be used, as they are well-adapted to the test locations in warm regions of Iran.

Investigation of the Influence of Polyamines on Mature Embryo Culture and DNA Methylation of Wheat (Triticum aestivum L.) Using the Machine Learning Algorithm Method.

Numerous factors can impact the efficiency of callus formation and in vitro regeneration in wheat cultures through the introduction of exogenous polyamines (PAs). The present study aimed to investigate in vitro plant regeneration and DNA methylation patterns utilizing the inter-primer binding site (iPBS) retrotransposon and coupled restriction enzyme digestion-iPBS (CRED-iPBS) methods in wheat. This investigation involved the application of distinct types of PAs (Put: putrescine, Spd: spermidine, and Spm: spermine) at varying concentrations (0, 0.5, 1, and 1.5 mM). The subsequent outcomes were subjected to predictive modeling using diverse machine learning (ML) algorithms. Based on the specific polyamine type and concentration utilized, the results indicated that 1 mM Put and Spd were the most favorable PAs for supporting endosperm-associated mature embryos. Employing an epigenetic approach, Put at concentrations of 0.5 and 1.5 mM exhibited the highest levels of genomic template stability (GTS) (73.9%). Elevated Spd levels correlated with DNA hypermethylation while reduced Spm levels were linked to DNA hypomethylation. The in vitro and epigenetic characteristics were predicted using ML techniques such as the support vector machine (SVM), extreme gradient boosting (XGBoost), and random forest (RF) models. These models were employed to establish relationships between input variables (PAs, concentration, GTS rates, Msp I polymorphism, and Hpa II polymorphism) and output parameters (in vitro measurements). This comparative analysis aimed to evaluate the performance of the models and interpret the generated data. The outcomes demonstrated that the XGBoost method exhibited the highest performance scores for callus induction (CI%), regeneration efficiency (RE), and the number of plantlets (NP), with R2 scores explaining 38.3%, 73.8%, and 85.3% of the variances, respectively. Additionally, the RF algorithm explained 41.5% of the total variance and showcased superior efficacy in terms of embryogenic callus induction (ECI%). Furthermore, the SVM model, which provided the most robust statistics for responding embryogenic calluses (RECs%), yielded an R2 value of 84.1%, signifying its ability to account for a substantial portion of the total variance present in the data. In summary, this study exemplifies the application of diverse ML models to the cultivation of mature wheat embryos in the presence of various exogenous PAs and concentrations. Additionally, it explores the impact of polymorphic variations in the CRED-iPBS profile and DNA methylation on epigenetic changes, thereby contributing to a comprehensive understanding of these regulatory mechanisms.

Selection of High-Yielding and Stable Genotypes of Barley for the Cold Climate in Iran.

The interaction between genotypes and environments plays an important role in selecting superior genotypes for target locations. The main objectives of the present study were to analyze the effect of the genotype-by-environment interaction (GEI) and identify superior, newly developed, and promising barley genotypes for cold regions in Iran. For these purposes, a set of genotypes obtained from breeding programs for cold climates in Iran, along with two reference genotypes, were investigated at eight research stations (Tabriz, Ardabil, Arak, Miandoab, Mashhad, Jolge Rokh, Karaj, and Hamadan) during two consecutive growing seasons (2019-2020 and 2020-2021). The results of the freezing test (LT50) showed that most of the tested genotypes had significant cold tolerance at the seedling stage. Based on the additive main effect and multiplicative interaction (AMMI) analysis, environment (E) and GEI effects explained 49.44% and 16.55% of the total variation in grain yield, respectively. Using AMMI1 and AMMI2 models, G2 and G20 were found to be superior genotypes in terms of grain yield and stability. Moreover, AMMI-based stability parameters considered the G20 genotype to be the ideal genotype. A two-plot analysis of the genotype-by-environment interaction (GGE) biplot showed that the 16 experimental environments were grouped into 2 mega-environments. Of the test environments, ARK1 and KAJ2 had the highest discriminating power and representativeness ability, and these were identified as ideal environments for testing advanced genotypes for yield and stability performance during early barley breeding practices in cold areas in Iran. In conclusion, both AMMI and GGE biplot models identified several superior genotypes, among which G20, with a high average yield relative to the overall average yield and the lowest IPC1 score, was found to have high yield stability and is recommended for inclusion in breeding programs for cold climates in Iran.

Genetic Diversity and Population Structure in Türkiye Bread Wheat Genotypes Revealed by Simple Sequence Repeats (SSR) Markers.

Wheat genotypes should be improved through available germplasm genetic diversity to ensure food security. This study investigated the molecular diversity and population structure of a set of Türkiye bread wheat genotypes using 120 microsatellite markers. Based on the results, 651 polymorphic alleles were evaluated to determine genetic diversity and population structure. The number of alleles ranged from 2 to 19, with an average of 5.44 alleles per locus. Polymorphic information content (PIC) ranged from 0.031 to 0.915 with a mean of 0.43. In addition, the gene diversity index ranged from 0.03 to 0.92 with an average of 0.46. The expected heterozygosity ranged from 0.00 to 0.359 with a mean of 0.124. The unbiased expected heterozygosity ranged from 0.00 to 0.319 with an average of 0.112. The mean values of the number of effective alleles (Ne), genetic diversity of Nei (H) and Shannon's information index (I) were estimated at 1.190, 1.049 and 0.168, respectively. The highest genetic diversity (GD) was estimated between genotypes G1 and G27. In the UPGMA dendrogram, the 63 genotypes were grouped into three clusters. The three main coordinates were able to explain 12.64, 6.38 and 4.90% of genetic diversity, respectively. AMOVA revealed diversity within populations at 78% and between populations at 22%. The current populations were found to be highly structured. Model-based cluster analyses classified the 63 genotypes studied into three subpopulations. The values of F-statistic (Fst) for the identified subpopulations were 0.253, 0.330 and 0.244, respectively. In addition, the expected values of heterozygosity (He) for these sub-populations were recorded as 0.45, 0.46 and 0.44, respectively. Therefore, SSR markers can be useful not only in genetic diversity and association analysis of wheat but also in its germplasm for various agronomic traits or mechanisms of tolerance to environmental stresses.

Identification of Superior Barley Genotypes Using Selection Index of Ideal Genotype (SIIG).

The main objective of the study was to evaluate and select the superior barley genotypes based on grain yield and some pheno-morphological traits using a new proposed selection index (SIIG). For this purpose, one-hundred-eight pure and four local cultivars (Norouz, Auxin, Nobahar, and WB-97-11) were evaluated as reference genotypes in four warm regions of Iran, including Ahvaz, Darab, Zabol, and Gonbad, during the 2020-2021 cropping seasons. The results of REML analysis showed that the heritability of all traits (except plant height) was higher in Gonbad than in other environments, while the lowest values were estimated in Ahvaz and Zabol environments. In addition, among the measured traits, the thousand kernel weight and grain filling period showed the highest and lowest values of heritability (0.83 and 0.01, respectively). The results showed that the seed yield of genotypes 1, 108, 3, 86, 5, 87, 19, 16, 15, 56, and 18 was higher than the four reference genotypes, and, on the other hand, the SIIG index of these genotypes was greater than or equal to 0.60. Based on the SIIG discriminator index, 4, 8, 31, and 28 genotypes with values greater than or equal to 0.60 were identified as superior for Darab, Ahvaz, Zabol, and Gonbad environments, respectively. As a conclusion, our results revealed that the SIIG index has ideal potential to identify genotypes with high yield and desirable traits. Therefore, the use of this index can be beneficial in screening better genotypes in the early stages of any breeding program for any crop.

Deciphering the level of genetic diversity in some aegilops species using CAAT box-derived polymorphism (CBDP) and start codon target polymorphism (SCoT) markers.

BACKGROUND: Maintaining genetic diversity is of the most essential principle for a long-term conservation of plant genetic resources and could play a crucial role in their management. The genus Aegilops is one important member of wheat germplasm, and there are evidences that novel genes of this genus' species can be studied/utilized as ideal sources for the wheat cultivar improvement. The objective of this study was to dissect the genetic diversity and population structure among a set of Iranian Aegilops using two gene-based molecular markers. METHODS AND RESULTS: This study investigated the level of genetic diversity among 157 Aegilops accessions consisting of Ae. tauschii Coss. (DD genome), Ae. crassa Boiss. (DDMM genome), and Ae. cylindrica Host. (CCDD genome) belonging to NPGBI using two sets of CBDP and SCoT markers. The SCoT and CBDP primers yielded 171 and 174 fragments, out of which 145 (90.23%) and 167 (97.66%) fragments were polymorphic, respectively. The average of polymorphism information content (PIC)/ marker index (MI)/resolving power (Rp) for SCoT and CBDP markers were 0.32/3.59/16.03 and 0.29/3.01/16.26, respectively. Results of AMOVA revealed the genetic variability within species was greater than the variation observed among them (SCoT: 88% vs. 12%; CBDP: 72% vs. 28%; SCoT + CBDP: 80% vs. 20%). Based on the information obtained from both markers, the higher level of genetic diversity was found in Ae. tauschii as compared to other species. The grouping patterns obtained by Neighbor-joining algorithms, principal coordinate analysis (PCoA), and Bayesian-model-based structure were consistent with each other and resulted in grouping all studied accessions according to their genomic constitutions. CONCLUSION: The results of this study revealed a high level of genetic diversity among Iranian Aegilops germplasm. Moreover, SCoT and CBDP marker systems were efficient in deciphering DNA polymorphism and classification of Aegilops germplasm.

The Influence of Methyl Jasmonate on Expression Patterns of Rosmarinic Acid Biosynthesis Genes, and Phenolic Compounds in Different Species of Salvia subg. Perovskia Kar L.

Salvia yangii B.T. Drew and Salvia abrotanoides Kar are two important fragrant and medicinal plants that belong to the subgenus Perovskia. These plants have therapeutic benefits due to their high rosmarinic acid (RA) content. However, the molecular mechanisms behind RA generation in two species of Salvia plants are still poorly understood. As a first report, the objectives of the present research were to determine the effects of methyl jasmonate (MeJA) on the rosmarinic acid (RA), total flavonoid and phenolic contents (TFC and TPC), and changes in the expression of key genes involved in their biosynthesis (phenylalanine ammonia lyase (PAL), 4-coumarate-CoA ligase (4CL), and rosmarinic acid synthase (RAS)). The results of High-performance liquid chromatography (HPLC) analysis indicated that MeJA significantly increased RA content in S. yungii and S. abrotanoides species (to 82 and 67 mg/g DW, respectively) by 1.66- and 1.54-fold compared with untreated plants. After 24 h, leaves of Salvia yangii and Salvia abrotanoides species treated with 150 M MeJA had the greatest TPC and TFC (80 and 42 mg TAE/g DW, and 28.11 and 15.14 mg QUE/g DW, respectively), which was in line with the patterns of gene expression investigated. Our findings showed that MeJA dosages considerably enhanced the RA, TPC, and TFC contents in both species compared with the control treatment. Since increased numbers of transcripts for PAL, 4CL, and RAS were also detected, the effects of MeJA are probably caused by the activation of genes involved in the phenylpropanoid pathway.

Physiological and Molecular Responses of Barley Genotypes to Salinity Stress.

Among cereals, barley is tolerant to high levels of salinity stress; however, its performance and global production are still dramatically affected by salinity. In this study, we evaluated the behavior of a set of advanced genotypes of barley with aim of assessing the physiological and molecular mechanisms involved in salinity tolerance. The experiment was conducted using a hydroponic system at optimal growing temperature and photoperiod conditions. The results of the analysis of variance (ANOVA) showed significant effects for salinity treatments and genotypes in terms of all measured traits. Salinity stress significantly increased the root and shoot Na+ contents and root-to-shoot Na+ and K+ translocations. In contrast, other physiological features, gas exchange-related traits, as well as root and shoot biomasses were significantly decreased due to salinity stress. Based on the results of the multi-trait genotype ideotype distance index (MGIDI) as a multiple-traits method, G12 and G14 were identified as the superior salt-tolerant advanced genotypes. In the molecular analysis, salinity stress significantly increased the mean relative expression of HvSOS1, HvSOS3, HvHKT2, HvHKT3, HvNHX1, and HvNHX3 genes by 12.87-, 3.16-, 3.65-, 2.54-, 2.19-, and 3.18-fold more than the control conditions, respectively. The results of heatmap-based correlation and principal component analysis (PCA) revealed a clear association pattern among measured traits and expression data. Indeed, these associations confirmed relationships between tolerance pathways and physiological functions. In conclusion, the genotype G14 (D10*2/4/Productive/3/Roho//Alger/Ceres362-1-1) responded well to salinity stress and showed a better expression pattern of studied genes than other genotypes. Hence, this promising genotype can be a candidate for further assessments before commercial introduction.

Methyl Jasmonate Induces Genes Involved in Linalool Accumulation and Increases the Content of Phenolics in Two Iranian Coriander (Coriandrum sativum L.) Ecotypes.

The medicinal herb coriander (Coriandrum sativum L.), with a high linalool (LIN) content, is widely recognized for its therapeutic benefits. As a novel report, the goals of this study were to determine how methyl jasmonate (MeJA) affects total phenolic content (TPC), LIN content, flavonoid content (TFC), and changes in gene expression involved in the linalool biosynthesis pathway (CsγTRPS and CsLINS). Our findings showed that, in comparison to the control samples, MeJA treatment substantially enhanced the TPC, LIN, and TFC content in both ecotypes. Additionally, for both Iranian coriander ecotypes, treatment-induced increases in CsγTRPS and CsLINS expression were connected to LIN accumulation in all treatments. A 24 h treatment with 150 µM MeJA substantially increased the LIN content in the Mashhad and Zanjan ecotypes, which was between 1.48 and 1.69 times greater than that in untreated plants, according to gas chromatography-mass spectrometry (GC-MS) analysis. Our findings demonstrated that MeJA significantly affects the accumulation of LIN, TPC, and TFC in Iranian C. sativum treated with MeJA, which is likely the consequence of gene activation from the monoterpene biosynthesis pathway. Our discoveries have improved the understanding of the molecular mechanisms behind LIN synthesis in coriander plants.

Association Analysis for Some Biochemical Traits in Wild Relatives of Wheat under Drought Stress Conditions.

In the present study, we estimated genetic diversity and population structure in 186 accessions of Triticum and Aegilops species using 24 simple sequence repeat markers (SSR). Furthermore, an association analysis was performed for antioxidant activities, including guaiacol peroxidase (GPX), ascorbate peroxidase (APX), peroxidase (POX), catalase (CAT), and dry matter (DM) under two control and drought stress conditions. Our findings showed that drought treatment significantly decreased DM, whereas activities of all antioxidant enzymes were increased compared to the control conditions. The results of correlation analysis indicated that, under drought stress conditions, all biochemical traits had a positive and significant association with each other and with dry matter. In the molecular section, the results of the analysis of molecular variance (AMOVA) indicated that the molecular variation within species is more than within them. The dendrogram obtained by cluster analysis showed that grouping the investigated accessions was in accordance with their genomic constitutions. The results of association analysis revealed 8 and 9 significant marker-trait associations (MTA) under control and drought stress conditions, respectively. Among identified MTAs, two associations were simultaneously found in both growing conditions. Moreover, several SSR markers were associated with multiple traits across both conditions. In conclusion, our results could provide worthwhile information regarding marker-assisted selection for the activity of antioxidant enzymes in future breeding programs.

An Analysis of Genetic Variability and Population Structure in Wheat Germplasm Using Microsatellite and Gene-Based Markers.

Knowledge of the natural patterns of genetic variation and their evolutionary basis is required for sustainable management and conservation of wheat germplasm. In the current study, the genetic diversity and population structure of 100 individuals from four Triticum and Aegilops species (including T. aestivum, Ae. tauschii, Ae. cylindrica, and Ae. crassa) were investigated using two gene-based markers (start codon targeted (SCoT) polymorphism and CAAT-box derived polymorphism (CBDP)) and simple-sequence repeats (SSRs). The SCoT, CBDP, and SSR markers yielded 76, 116, and 48 polymorphism fragments, respectively. The CBDP marker had greater efficiency than the SCoT and SSR markers due to its higher polymorphism content information (PIC), resolving power (Rp), and marker index (MI). Based on an analysis of molecular variance (AMOVA) performed using all marker systems and combined data, there was a higher distribution of genetic variation within species than among them. Ae. cylindrica and Ae. tauschii had the highest values for all genetic variation parameters. A cluster analysis using each marker system and combined data showed that the SSR marker had greater efficiency in grouping of tested accessions, such that the results of principal coordinate analysis (PCoA) and population structure confirmed the obtained clustering patterns. Hence, combining the SCoT and CBDP markers with polymorphic SSR markers may be useful in genetic fingerprinting and fine mapping and for association analysis in wheat and its germplasm for various agronomic traits or tolerance mechanisms to environmental stresses.

Change in Secondary Metabolites and Expression Pattern of Key Rosmarinic Acid Related Genes in Iranian Lemon Balm (Melissa officinalis L.) Ecotypes Using Methyl Jasmonate Treatments.

The medicinal herb, lemon balm (Melissa officinalis L.), which is high in rosmarinic acid (RA), has well-known therapeutic value. The goals of this study were to investigate the effects of methyl jasmonate (MeJA) on RA content, total phenolic content (TPC), and total flavonoid content (TFC), as well as changes in expression of their biosynthesis-related key genes (MoPAL, Mo4CL, and MoRAS) in Iranian lemon balm ecotypes, as first reported. Our results revealed that MeJA doses significantly increase the RA content, TPC, and TFC in both ecotypes compared with the control samples. Additionally, the higher expression levels of MoPAL, Mo4CL, and MoRAS following treatment were linked to RA accumulation in all treatments for both Iranian lemon balm ecotypes. After 24 h of exposure to 150 µM MeJA concentration, HPLC analysis showed that MeJA significantly increased RA content in Esfahan and Ilam ecotypes, which was about 4.18- and 7.43-fold higher than untreated plants. Our findings suggested that MeJA has a considerable influence on RA, TPC, and TFC accumulation in MeJA-treated Iranian M. officinalis, which might be the result of gene activation from the phenylpropanoid pathway. As a result of our findings, we now have a better understanding of the molecular processes behind RA production in lemon balm plants.

Improvement of Plant Responses by Nanobiofertilizer: A Step towards Sustainable Agriculture.

Drastic changes in the climate and ecosystem due to natural or anthropogenic activities have severely affected crop production globally. This concern has raised the need to develop environmentally friendly and cost-effective strategies, particularly for keeping pace with the demands of the growing population. The use of nanobiofertilizers in agriculture opens a new chapter in the sustainable production of crops. The application of nanoparticles improves the growth and stress tolerance in plants. Inoculation of biofertilizers is another strategy explored in agriculture. The combination of nanoparticles and biofertilizers produces nanobiofertilizers, which are cost-effective and more potent and eco-friendly than nanoparticles or biofertilizers alone. Nanobiofertilizers consist of biofertilizers encapsulated in nanoparticles. Biofertilizers are the preparations of plant-based carriers having beneficial microbial cells, while nanoparticles are microscopic (1-100 nm) particles that possess numerous advantages. Silicon, zinc, copper, iron, and silver are the commonly used nanoparticles for the formulation of nanobiofertilizer. The green synthesis of these nanoparticles enhances their performance and characteristics. The use of nanobiofertilizers is more effective than other traditional strategies. They also perform their role better than the common salts previously used in agriculture to enhance the production of crops. Nanobiofertilizer gives better and more long-lasting results as compared to traditional chemical fertilizers. It improves the structure and function of soil and the morphological, physiological, biochemical, and yield attributes of plants. The formation and application of nanobiofertilizer is a practical step toward smart fertilizer that enhances growth and augments the yield of crops. The literature on the formulation and application of nanobiofertilizer at the field level is scarce. This product requires attention, as it can reduce the use of chemical fertilizer and make the soil and crops healthy. This review highlights the formulation and application of nanobiofertilizer on various plant species and explains how nanobiofertilizer improves the growth and development of plants. It covers the role and status of nanobiofertilizer in agriculture. The limitations of and future strategies for formulating effective nanobiofertilizer are mentioned.

Stability Indices to Deciphering the Genotype-by-Environment Interaction (GEI) Effect: An Applicable Review for Use in Plant Breeding Programs.

Experiments measuring the interaction between genotypes and environments measure the spatial (e.g., locations) and temporal (e.g., years) separation and/or combination of these factors. The genotype-by-environment interaction (GEI) is very important in plant breeding programs. Over the past six decades, the propensity to model the GEI led to the development of several models and mathematical methods for deciphering GEI in multi-environmental trials (METs) called "stability analyses". However, its size is hidden by the contribution of improved management in the yield increase, and for this reason comparisons of new with old varieties in a single experiment could reveal its real size. Due to the existence of inherent differences among proposed methods and analytical models, it is necessary for researchers that calculate stability indices, and ultimately select the superior genotypes, to dissect their usefulness. Thus, we have collected statistics, as well as models and their equations, to explore these methods further. This review introduces a complete set of parametric and non-parametric methods and models with a selection pattern based on each of them. Furthermore, we have aligned each method or statistic with a matched software, macro codes, and/or scripts.

Molecular and Physiological Variability in Bread Wheat and Its Wild Relative (Aegilops tauschii Coss.) Species under Water-Deficit Stress Conditions.

Aegilops and Triticum spp. are two ideal gene pools for the breeding purposes of wheat. In this study, a set of Iranian accessions of Aegilops tauschii Coss. and Triticum aestivum L. species were evaluated in terms of some physiological and biochemical features under control and water-deficit stress conditions. Moreover, several simple sequence repeat (SSR) markers were employed to identify marker loci associated with the measured traits. The results indicated that water-deficit stress significantly affected all measured traits and the highest reductions due to water-deficit were recorded for shoot fresh and dry biomasses (SFB and SDB), stomatal conductance (Gs), leaf relative water content (RWC), and chlorophyll b content (Chl b). In molecular analysis, 25 SSR markers generated 50 fragments, out of which 49 fragments (98%) were polymorphic. Furthermore, the genetic variation observed within species is more than between species. The results of cluster and Bayesian model analysis classified all evaluated accessions into three main clusters. Under control and water-deficit stress conditions, 28 and 27 significant marker-trait associations (MTAs) were identified, respectively. Furthermore, 10 MTAs showed sufficiently stable expression across both growth conditions. Of these, the markers Xgwm-111, Xgwm-44, Xgwm-455, Xgwm-272, and Xgwm-292 were associated with multiple traits. Hence, these markers could serve as useful molecular tools for population characterization, gene tagging, and other molecular breeding studies.

A dataset on multi-trait selection approaches for screening desirable wild relatives of wheat.

Wild relatives of common wheat are an extraordinary source of tolerance to various environmental stresses. The dataset herein presents the effect of water-deficit stress on a core collection of landraces and wild relatives of wheat (including 180 samples belonging to four Triticum and eight Aegilops species [T. boeoticum Bioss., T. urartu Gandilyan., T. durum Def., T. aestivum L., Ae. speltoides Tausch., Ae. tauschii Coss., Ae. caudata L., Ae. umbellulata Zhuk., Ae. neglecta L., Ae. cylindrica Host., Ae. crassa Boiss., and Ae. triuncialis]) in terms of several physiological traits, root and shoot biomasses, and features of root system architecture (RSA). All genetic materials were subjected to water-stress treatment using a pot experiment under greenhouse conditions. To screen the most tolerant accessions, three selection indices, such as Smith and Hazel (SH), factor analysis and ideotype-design (FAI), and the multi-trait genotype-ideotype distance index (MGIDI) were computed. The obtained data can highlight the role of some features of RSA in increasing water-deficit tolerance in some wild relatives of wheat. Moreover, the use of selection indices in the early stage of growth can be highlighted for future research.

Effect of Methyl Jasmonate on Thymol, Carvacrol, Phytochemical Accumulation, and Expression of Key Genes Involved in Thymol/Carvacrol Biosynthetic Pathway in Some Iranian Thyme Species.

Thyme species are a good source of thymol and carvacrol, which play a key role in controlling diseases. For the first time, the expression patterns of γ-terpinene synthase (TPS2), CYP71D178, and CYP71D180 genes and the amount of phenolics compounds were evaluated in T. migricus and T. daenensis after different methyl jasmonate (MeJA) treatments. The highest thymol and carvacrol contents were observed in T. migricus (86.27%) and T. daenensis (17.87%) at MeJA 100 µM, which was consistent with the expression patterns of the three investigated genes. All species treated showed high total phenolic and flavonoid content compared to control plants for which the highest amounts were observed in T. vulgaris treated with 100 µM and 10 µM MeJA. Furthermore, in the 100 µM MeJA treatment, the relative expression of TPS2 and CYP71D178 in T. migricus increased 7.47 and 9.86-fold compared with the control, respectively. The highest level of CYP71D180 transcripts (5.15-fold) was also observed for T. daenensis treated. This finding highlights the notion that thymol was known as the dominant component of the essential oil rather than carvacrol in diffident thyme species. This implies that MeJA at different concentrations influenced metabolic pathways and induced expression changes, resulting in a rise in essential oil levels.

Dataset on the use of MGIDI index in screening drought-tolerant wild wheat accessions at the early growth stage.

The dataset herein indicated the novelty of the article entitled "Dataset on the use of MGIDI in screening drought-tolerant wild wheat accessions at the early growth stage". Data were gathered during 2018-2019 on a set of wild wheat germplasm under two control and water deficit stress conditions. One hundred and forty-six accessions belonging to Ae. tauschii, Ae. cylindrica, and Ae. crassa were assessed under optimal glasshouse conditions to screen the drought-tolerant samples at the early growth stage. Nine drought tolerance and susceptibility indices along with the multi-trait genotype-ideotype distance index (MGIDI) were used to visualize the dataset. The obtained data can highlight the potential of the MGIDI index in accelerating screening of a large number of plant materials using multiple traits or selection indices in crop breeding programs, especially at the early growth stage.