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Effect of Different Plant Growth-Promoting Rhizobacteria on Biological Soil Properties, Growth, Yield and Quality of Oregano (Origanum onites L.)
Intensive agriculture uses continuous chemical fertilizers to increase crop yields, but excessive use of fertilizers leads to environmental pollution, permanent changes in physicochemical conditions in soil ecology, deterioration of soil biological health, leaching of nutrients, surface and groundwater pollution and eutrophication. Plant growth-promoting rhizobacteria (PGPR) are becoming increasingly important for ensuring crop safety, increasing nutrient uptake and output, lowering fertilizer costs, preventing environmental contamination and promoting sustainable agriculture and agricultural resources. Therefore, the purpose of this study was to identify and evaluate the effects of fifteen bacteria strains that were isolated from various acidic rhizospheric soils as biofertilizers on soil biological properties. Growth, yield and quality traits were analyzed, and various PGPR were identified using 16S ribosomal RNA of Turkish oregano. Fifteen bacterial inoculations with 1-aminocyclopropane-1-carboxylate (ACC) deaminase, N2-fixing, P-solubilizing and/or IAA-producing genes were used in the experiment, which was carried out in a randomized block design with five replicates (each with three pots) and a control without inoculation. Increased biological activity in soil inoculated with bacteria with multiple traits was confirmed by high C and N content in microbial biomass, urease, dehydrogenase and acid and alkaline phosphatase activities. Essential oil content, oil yield, thymol and carvacrol contents increased by 0.5–40.1%, 5.9–71.9%, 0.07–16.7% and 0.3–9.2%, respectively, as a result of bacterial inoculation. Oil content ranged from 2.02% to 2.83%; carvacrol (66.1–72.2%) was the main constituent, followed by thymol (14.5–16.9%) and linalool (1.38–3.68%). Two large PGPR groups were formed based on genetic distance analysis. Responses were variable and depended on the inoculant strain and the parameters being evaluated. The results indicate PGPR has clear potential for improving the yield of cultivated aromatic and essential oil plants, such as oregano.
Chitosan-mediated mitigation of salt stress in wheat (Triticum aestivum L.) under tissue culture conditions
Abstract Wheat (Triticum aestivum L.) stands as a pivotal cereal crop and ranks among the most extensively cultivated species worldwide. It is productivity, however, is markedly hindered by both abiotic and biotic stressors, with salinity emerging as a predominant abiotic challenge in agricultural systems. Salinity is a pervasive issue in arable lands, necessitating the development of sustainable strategies to mitigate it is adverse effects while prioritizing environmental sustainability. Chitosan, a derivative of chitin, has garnered as an eco-friendly agent for alleviating salt stress due to it is biocompatibility and environmental safety. Studies have demonstrated that chitosan application can enhance plant growth parameters and bolster antioxidant defenses under saline conditions. In this study, the effects of varying chitosan concentrations (0, 1, 2, 4 mg/mL) and exposure durations (2, 4, 8 h) were investigated under different salinity levels (0, 75, 150, 225 mM) using mature embryos of the salinity-sensitive Kırik wheat variety. Key in vitro parameters assessed included the embryogenic callus formation rate (CFR), responding embryogenic callus rate (RECF), shoot formation rate (SFR) root formation rate (RFR), and the number of plants per explant (NP). The findings revealed that chitosan effectively mitigates salt stress. Notably, a 1 mg/mL chitosan concentration significantly improved CFR, RECR, and SFR, whereas a 4 mg/mL concentration was more effective for RFR and NP. The responses of RECR and CFR to salt stress exhibited similar patterns. Analysis of variance indicated that the optimal duration for a 1 mg/mL chitosan treatment was 4 h, while for the 4 mg/mL concentration, a 2-hour exposure was more effective, suggesting that shorter treatment durations are more beneficial at higher chitosan concentrations. Despite the promising results, the limited literature on the role of chitosan in tissue culture highlights the novelty of this research, emphasizing it is potential to make a unique contribution to the field. The findings of this study provide valuable insights for enhancing wheat’s resistance to salinity stress through chitosan treatment, offering practical applications in developing more resilient crop varieties.
Agro-morphological characterization and machine learning-based prediction of genetic diversity in six-row barley genotypes from Türkiye
Abstract The restricted genetic diversity observed in modern barley represents a significant obstacle to enhancing productivity. This study addresses this issue by characterising 445 six-row barley genotypes from the Osman Tosun Gene Bank in Türkiye. A comprehensive analysis of 22 agro-morphological traits, comprising 11 qualitative and 11 quantitative traits, was conducted to explore morphological, growth and phenological diversity. Principal component analysis identified four principal components, which collectively explained 72.86% of the total variance. Of these, the first two components accounted for 52.45%. Based on agro-morphological similarities, the genotypes were grouped into seven clusters. Clusters 5, 6, and 7 contained genotypes with high-yield traits, including early maturity, increased grain per spike, and higher thousand grain weight. The findings contribute directly to the expansion of the barley gene pool. Moreover, this study provides a comprehensive characterisation of the hitherto overlooked six-row barley germplasm present in Türkiye. This offers invaluable genetic resources for future breeding and molecular studies. Furthermore, the study compares the performance of three machine learning models (XGBoost, MARS, and Gaussian Processes) in predicting the harvest index from various traits. The XGBoost model demonstrated superior predictive ability, with the lowest RMSE (0.137), MAPE (0.222), and MAD (0.101) values, and was able to explain 99.8% of the barley variation. This research highlights the potential of machine learning algorithms in enhancing barley breeding by accurately predicting beneficial traits for yield improvement.
Revealing Genetic Diversity and Population Structure in Türkiye’s Wheat Germplasm Using iPBS-Retrotransposon Markers
Investigating the genetic diversity and population structure of wheat germplasm is crucial for understanding the underlying variability essential for breeding programs and germplasm preservation. This research aims to contribute novel insights with respect to the genetic makeup and relationships among these wheat genotypes, shedding light on the diversity present within the Turkish wheat germplasm. In this study, iPBS-retrotransposon markers were employed to analyze 58 wheat genotypes, encompassing 54 landraces and 4 cultivars sourced from Türkiye. These markers serve as genetic indicators that can be used to evaluate genetic variation, build genealogical trees, and comprehend evolutionary connections. The PCR products were visualized on agarose gel, and bands were scored as present/absent. The ten iPBS primers collectively yielded an average of 16.3 alleles, generating a total of 163 polymorphic bands. The number of alleles produced by individual markers ranged from 4 (iPBS-2386) to 29 (iPBS-2219). The genetic parameters were calculated using the popgen and powermarker programs. The genetic relationships and population structures were assessed using the ntsys and structure programs. Polymorphism information content (PIC) per marker varied from 0.13 (iPBS-2390) to 0.29 (iPBS-2386), with an average value of 0.22. Shannon’s information index (I) was calculated as 1.48, while the number of effective alleles (Ne) and Nei’s genetic diversity (H) were determined to be 0.26 and 0.31, respectively. Genotype numbers 3 (Triticum dicoccum) and 10 (Triticum monococcum) exhibited the maximum genetic distance of 0.1292, signifying the highest genetic disparity. Population structure analysis revealed the segregation of genotypes into three distinct subpopulations. Notably, a substantial portion of genotypes clustered within populations correlated with the wheat species. This population structure result was consistent with the categorization of genotypes based on wheat species. The comprehensive assessment revealed noteworthy insights with respect to allele distribution, polymorphism content, and population differentiation, offering valuable implications for wheat breeding strategies and germplasm conservation efforts. In addition, the iPBS markers and wheat genotypes employed in this study hold significant potential for applications in wheat breeding research and germplasm preservation.
Pre-Harvest Sprouting Resistance in Bread Wheat: A Speed Breeding Approach to Assess Dormancy QTL in Backcross Lines
In this study, BC1F3:4 generation plants derived from the hybrid crosses of Rio Blanco × Nevzatbey, Rio Blanco × Adana99, and Rio Blanco × line 127 were used as experimental material. These hybrids incorporated QTLs associated with pre-harvest sprouting (PHS) resistance through molecular techniques. Key agronomic traits, including plant height, spike length, the number of grains per spike, grain weight, and physiological maturity, were evaluated in both greenhouse and growth room settings under accelerated growth (speed breeding) conditions. Results indicated that plants grown in the fully controlled greenhouse conditions exhibited superior agronomic performance compared with those cultivated in the growth room. Additionally, germination tests were conducted on each hybrid cross to identify genotypes exhibiting dormancy. The analysis revealed that 11 lines from the Rio Blanco × Nevzatbey combination, eight lines from Rio Blanco × Adana99, and six lines from Rio Blanco × Line 127 had notably low germination indices. Among the three hybrid families, the Rio Blanco × Nevzatbey BC1F3:4 hybrids demonstrated the lowest germination index (0.44). Furthermore, Rio Blanco itself recorded the lowest germination index under both greenhouse (0.02) and growth room (0.24) conditions. These findings suggest that environmental conditions exert a significant influence on the expression of dormancy in these genotypes, even when dormancy genes are present. The lines developed in this research have the potential to serve as elite material in breeding programs aimed at enhancing pre-harvest sprouting resistance.
Prediction of Grain Yield in Wheat by CHAID and MARS Algorithms Analyses
Genetic information obtained from ancestral species of wheat and other registered wheat has brought about critical research, especially in wheat breeding, and shown great potential for the development of advanced breeding techniques. The purpose of this study was to determine correlations between some morphological traits of various wheat (Triticum spp.) species and to demonstrate the application of MARS and CHAID algorithms to wheat-derived data sets. Relationships among several morphological traits of wheat were investigated using a total of 26 different wheat genotypes. MARS and CHAID data mining methods were compared for grain yield prediction from different traits using cross-validation. In addition, an optimal CHAID tree structure with minimum RMSE was obtained and cross-validated with nine terminal nodes. Based on the smallest RMSE of the cross-validation, the eight-element MARS model was found to be the best model for grain yield prediction. The MARS algorithm proved superior to CHAID in grain yield prediction and accounted for 95.7% of the variation in grain yield among wheats. CHAID and MARS analyses on wheat grain yield were performed for the first time in this research. In this context, we showed how MARS and CHAID algorithms can help wheat breeders describe complex interaction effects more precisely. With the data mining methodology demonstrated in this study, breeders can predict which wheat traits are beneficial for increasing grain yield. The adaption of MARS and CHAID algorithms should benefit breeding research.
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.
Analysis of Physio-Biochemical Responses and Expressional Profiling Antioxidant-Related Genes in Some Neglected Aegilops Species under Salinity Stress
Wild common wheat species represent a significant pool of resistance genes to various environmental stresses. In this study, we examined several physiological traits and the activity of three antioxidant enzymes—namely, catalase (CAT), superoxide dismutase (SOD), and ascorbate peroxidase (APX)—as well as the expression patterns of their encoding genes in three neglected Aegilops species with alien genomes (including Ae. triuncialis (UUCC-genome), Ae. neglecta (UUMM-genome) and Ae. umbellulata (UU-genome)) under two control (0 mM NaCl) and salinity (250 mM NaCl) conditions. The results of the analysis of variance (ANOVA) showed highly significant effects of salinity stress, accessions, and their interaction on most physio-biochemical traits, root and shoot dry biomasses, and antioxidant-related gene expression level. As a result of comparison between Aegilops species and a bread wheat cultivar (cv. Narin as a salt-tolerant reference variety), Ae. triuncialis responded well to salinity stress, maintaining both ionic homeostasis capability and biochemical ability. Moreover, transcriptional data revealed the prominence of Ae. triuncialis over other Aegilops species and salt-tolerant bread wheat [cv. Narin] in terms of the level of expression of antioxidant genes (APX, SOD, and CAT). This result was further supported by a biplot rendered based on principal component analysis (PCA), where this wild relative showed a positive association with most measured traits under salinity stress. Moreover, we speculate that this accession can be subjected to physiological and molecular studies, and that it can provide new insights into the use of the alien genomes in future wheat breeding programs.
Mammalian Sex Hormones as Steroid-Structured Compounds in Wheat Seedling: Template of the Cytosine Methylation Alteration and Retrotransposon Polymorphisms with iPBS and CRED-iBPS Techniques
Phytohormones are chemical compounds found naturally in plants that have a significant effect on their growth and development. The increase in research on the occurrence of mammalian sex hormones (MSHs) in plants has prompted the need to investigate the functions performed by these hormones in plant biology. In the present study, we investigated the effects of MSHs on DNA damage and DNA methylation of wheat (Triticum aestivum L.) during the seedling growth stage, using the CRED-iPBS (coupled restriction enzyme digestion/inter primer binding site) assay and iPBS analysis to determine DNA methylation status. Exogenous treatment with four MSHs (17-β-estradiol, estrogen, progesterone, and testosterone) was carried out at four different concentrations (0, 0.05, 0.5, and 5 µM). The highest genomic template stability (GTS) value (80%) was observed for 5 µM 17-β-estradiol, 0.5 µM testosterone, and 0.05 µM estrogen, while the lowest value (70.7%) was observed for 5 µM progesterone and 0.5 µM estrogen. The results of the CRED-iPBS analysis conducted on MspI indicate that the 0.05 µM estrogen-treated group had the highest polymorphism value of 40%, while the 5 µM progesterone-treated group had the lowest value of 20%. For HpaII, treatment with 0.5 µM 17-β-estradiol had the highest polymorphism value of 33.3%, while the group treated with 0.05 µM 17-β-estradiol and 0.05 µM progesterone had the lowest value of 19.4%. In conclusion, MSH treatments altered the stability of the genomic template of wheat plants and affected the cytosine methylation status at the seedling growth stage. Upon comprehensive examination of the results, it was seen that the employed methodology successfully detected alterations in cytosine methylation of genomic DNA (gDNA), as well as changes in the pattern of genomic instability.