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.

Turkey is one of the important gene centers for many crop species. In this research, some ancient wheats such as tetraploid and diploid hulled wheats together with hexaploid tir wheats (Triticum aestivum ssp. leucospermum Korn.) landraces mainly adapted to harsh winter conditions of Eastern Anatolian region of Turkey were characterized at agro-morphological and molecular level. Totally 50 hulled wheat population from Kastamonu, Konya and Kayseri provinces and 15 tir wheats from Kars provinces of Turkey were in-situ collected for characterization in 2013. Some quantitative and qualitative traits of each population were determined. Twenty three hulled wheat population collected from Kastamonu province were distinguished into nine emmer and 14 einkorn wheats at morphological level. Additionally, Konya, Kayseri and Kars population were characterized as einkorn, emmer and tir wheat, respectively. Among the evaluated traits, protein ratios of hulled wheats were strikingly higher than registered cultivars. All the populations were also examined by molecular level by using fluorescently labelled 11 polymorphic SSRs primers. The primers exhibited 104 bands, ranging from 6 to 16 with a mean value 9.45 per loci. The clustering analysis separated the germplasm into two clusters which were also divided into two subclusters based on genetic similarity coefficient. Sixty-five population and five checks were analyzed to estimate mean number of alleles (N), expected and observed heterozygoties (He and Ho), polymorphism information content (PIC), Wright fix index (F), genetic deviation from Hardy-Weinberg expectation (Fit-Fis) and genetic variation (Fst) were determined as 9.45, 0.71, 0.07, 0.67, 0.90, 0.39, 0.87 and 0.39, respectively. A clear genetic deviation from Hardy – Weinberg expectation was observed among population in particular. These results showed considerable genetic variation among landraces rather than within population. These molecular information has revealed genetically diverse einkorn, emmer wheat and tir wheat population could be used as parents for further breeding studies in both Turkey and abroad. Furthermore, the molecular analysis has also generally discriminated the germplasm into ploidy level.

The primary objective of this research was to ascertain the optimal circumstances for the successful growth of black chokeberry (Aronia melanocarpa (Michx.) Elliott) using tissue culture techniques. Additionally, the study aimed to explore the potential use of machine learning algorithms in this context. The present research investigated a range of in vitro parameters such as total number of roots (TNR), longest root length (LRL), average root length (ARL), number of main roots (NMR), number of siblings (NS), shoot length (SL), shoot diameter (SD), leaf width (LW), and leaf length (LL) for Aronia explants cultivated in different media (Murashige and Skoog (MS) and woody plant medium (WPM)) with different concentrations (0, 0.5, 1, 1.5, and 2 mg L⁻¹) of indole-3-butyric acid (IBA). The study showed that IBA hormone levels may affect WPM properties, affecting the LRL and ARL variables. Aronia explant media treated with 2 mg L⁻¹ IBA had the greatest TNR, NMR, NS, SL, and SD values; 31.67 pieces, 2.37 pieces, 5.25 pieces, 66.60 mm, and 2.59 mm, in that order. However, Aronia explants treated with 1 mg L⁻¹ IBA had the highest LW (9.10 mm) and LL (14.58 mm) values. Finally, Aronia explants containing 0.5 mg L⁻¹ IBA had the greatest LRL (89.10 mm) and ARL (57.57 mm) values. In general, the results observed (TNR, LRL, ARL, NMR, NS, SL, SD, LW, and LL) indicate that Aronia explants exhibit superior growth and development in WPM (25.68 pieces, 68.10 mm, 51.64 mm, 2.17 pieces, 4.33 pieces, 57.95 mm, 2.49 mm, 8.08 mm, and 14.26 mm, respectively) as opposed to MS medium (20.27 pieces, 59.92 mm, 47.25 mm, 1.83 pieces, 3.57 pieces, 49.34 mm, 2.13 mm, 6.99 mm, and 12.21 mm, respectively). In the context of the in vitro culturing of Aronia explants utilizing MS medium and WPM, an analysis of machine learning models revealed that the XGBoost and SVM models perform better than the RF, KNN, and GP models when it comes to making predictions about those variables. In particular, the XGBoost model stood out due to the fact that it had the greatest R-squared value, and showed higher predictive ability in terms of properly forecasting values in comparison to actual outcomes. The findings of a linear regression (LR) analysis were used in order to conduct an efficacy study of the XGBoost model. The LR results especially confirmed the findings for the SD, NS, and NMR variables, whose R-squared values were more than 0.7. This demonstrates the extraordinary accuracy that XGboost has in predicting these particular variables. As a consequence of this, it is anticipated that it will be beneficial to make use of the XGboost model in the dosage optimization and estimation of in vitro parameters in micropropagation studies of the Aronia plant for further scientific investigation.

The use of mutagens in plant breeding is used to create new germplasm, increase agricultural yield, quality, and resistance to diseases and pests. Mutagens are physical or chemical factors that can alter the DNA or RNA structure of an organism, causing mutations above the expected level. One of the most common and potent chemical mutagens is EMS (ethyl-methane sulfonate), which produces point mutations in plants, but to a lesser degree can also cause the loss or deletion of a chromosomal region. This study used inter-primer binding site (iPBS) and coupled restriction enzyme digestion inter-primer binding site (CRED-iPBS) technique analysis to determine the effect of EMS mutagens on methylation rates in wheat genotypes at seedling growth stage. Treatments with five different EMS concentrations (0%; control, 0.1%, 0.2%, 0.3%, and 0.4%) at four different times (0; control, 3, 6, and 9 h) were used. Inter-primer binding site (iPBS) markers were employed to assess genomic instability and cytosine methylation in treated wheat. In seeds treated with EMS at different concentrations and times, the disappearance of regular bands and the formation of new bands due to the effects of the EMS mutagen revealed that genetic diversity exists. The CRED-iPBS analysis revealed that the 3 h + 0.1% EMS treatment produced the highest MspI polymorphism value (19.60%), while the 9 h + 0.1% EMS treatment produced the lowest value (10.90%). The mutagenic effects of EMS treatments had considerable polymorphism on a variety of impacts on the cytosine methylation and genomic instability of wheat. According to the current research, EMS mutagenesis may be a practical method for accelerating breeding programs to produce enough genetic diversity in wheat populations. Mutation-assisted breeding and the subsequent selection of desirable mutants using genetic markers may also be carried out in wheat utilizing an integrated strategy.

The objective of this study was to comprehend the efficiency of wheat regeneration, callus induction, and DNA methylation through the application of mathematical frameworks and artificial intelligence (AI)-based models. This research aimed to explore the impact of treatments with AgNO₃ and Ag-NPs on various parameters. The study specifically concentrated on analyzing RAPD profiles and modeling regeneration parameters. The treatments and molecular findings served as input variables in the modeling process. It included the use of AgNO₃ and Ag-NPs at different concentrations (0, 2, 4, 6, and 8 mg L⁻¹). The in vitro and epigenetic characteristics were analyzed using several machine learning (ML) methods, including support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), k-nearest neighbor classifier (KNN), and Gaussian processes classifier (GP) methods. This study’s results revealed that the highest values for callus induction (CI%) and embryogenic callus induction (EC%) occurred at a concentration of 2 mg L⁻¹ of Ag-NPs. Additionally, the regeneration efficiency (RE) parameter reached its peak at a concentration of 8 mg L⁻¹ of AgNO₃. Taking an epigenetic approach, AgNO₃ at a concentration of 2 mg L⁻¹ demonstrated the highest levels of genomic template stability (GTS), at 79.3%. There was a positive correlation seen between increased levels of AgNO₃ and DNA hypermethylation. Conversely, elevated levels of Ag-NPs were associated with DNA hypomethylation. The models were used to estimate the relationships between the input elements, including treatments, concentration, GTS rates, and Msp I and Hpa II polymorphism, and the in vitro output parameters. The findings suggested that the XGBoost model exhibited superior performance scores for callus induction (CI), as evidenced by an R² score of 51.5%, which explained the variances. Additionally, the RF model explained 71.9% of the total variance and showed superior efficacy in terms of EC%. Furthermore, the GP model, which provided the most robust statistics for RE, yielded an R² value of 52.5%, signifying its ability to account for a substantial portion of the total variance present in the data. This study exemplifies the application of various machine learning models in the cultivation of mature wheat embryos under the influence of treatments and concentrations involving AgNO₃ and Ag-NPs.

Wheat, which is scientifically known as Triticum aestivum L., is a very nutritious grain that serves as a key component of the human diet. The use of mutation breeding as a tool for crop improvement is a reasonably rapid procedure, and it generates a variety that may be used in selective breeding programs as well as functional gene investigations. The present experiment was used to evaluate the potential application of a conventional chemical mutagenesis technique via sodium azide (NaN₃) for the germination and seedling growth stage in wheat. Experiments with NaN₃ mutagenesis were conducted using four different treatment periods (0, 1, 2, and 3 h) and five different concentrations (0, 0.5, 1, 1.5, and 2 mM). The genomic instability and cytosine methylation of wheat using its seeds were investigated after they were treated. In order to evaluate the genomic instability and cytosine methylation in wheat that had been treated, interprimer binding site (iPBS) markers were used. The mutagenic effects of NaN₃ treatments had considerable polymorphism on a variety of impacts on the cytosine methylation and genomic instability of wheat plants. The results of the experiment showed considerable changes in the iPBS profiles produced by the administration of the same treatments at different dosages and at different times. Coupled restriction enzyme digestion interprimer binding site (CRED-iPBS) assays identified changes in gDNA cytosine methylation. The highest polymorphism value was obtained during 1 h + 2 mM NaN₃, while the lowest (20.7%) was obtained during 1 h + 1.5 mM NaN₃. Results showed that treatments with NaN₃ had an effect on the level of cytosine methylation and the stability of the genomic template in wheat plants in the germination stage. Additionally, an integrated method can be used to for mutation-assisted breeding using a molecular marker system in wheat followed by the selection of desired mutants.