Induction of volatile organic compounds in chrysanthemum plants following infection by Rhizoctonia solani.

This study investigated the effects of Rhizoctonia solani J.G. Kühn infestation on the volatile organic compound (VOC) emissions and biochemical composition of ten cultivars of chrysanthemum (Chrysanthemum × morifolium /Ramat./ Hemsl.) to bring new insights for future disease management strategies and the development of resistant chrysanthemum cultivars. The chrysanthemum plants were propagated vegetatively and cultivated in a greenhouse under semi-controlled conditions. VOCs emitted by the plants were collected using a specialized system and analyzed by gas chromatography/mass spectrometry. Biochemical analyses of the leaves were performed, including the extraction and quantification of chlorophylls, carotenoids, and phenolic compounds. The emission of VOCs varied among the cultivars, with some cultivars producing a wider range of VOCs compared to others. The analysis of the VOC emissions from control plants revealed differences in both their quality and quantity among the tested cultivars. R. solani infection influenced the VOC emissions, with different cultivars exhibiting varying responses to the infection. Statistical analyses confirmed the significant effects of cultivar, collection time, and their interaction on the VOCs. Correlation analyses revealed positive relationships between certain pairs of VOCs. The results show significant differences in the biochemical composition among the cultivars, with variations in chlorophyll, carotenoids, and phenolic compounds content. Interestingly, R. solani soil and leaf infestation decreased the content of carotenoids in chrysanthemums. Plants subjected to soil infestation were characterized with the highest content of phenolics. This study unveils alterations in the volatile and biochemical responses of chrysanthemum plants to R. solani infestation, which can contribute to the development of strategies for disease management and the improvement of chrysanthemum cultivars with enhanced resistance to R. solani.

Hesperidin as a Species-Specific Modifier of Aphid Behavior.

Hesperidin is a highly bioactive natural flavonoid whose role in ecological interactions is poorly known. In particular, the effects of hesperidin on herbivores are rarely reported. Flavonoids have been considered as prospective biopesticides; therefore, the aim of the present study was to examine the influence of hesperidin on the host plant selection behavior of three aphid (Hemiptera: Aphididae) species: Acyrthosiphon pisum Harrris, Rhopalosiphum padi (L.), and Myzus persicae (Sulz.). The aphid host plants were treated with 0.1% and 0.5% ethanolic solutions of hesperidin. Aphid probing behavior in the no-choice experiment was monitored using electropenetrography and aphid settling on plants in the choice experiment was recorded. The results demonstrated that hesperidin can be applied as a pre-ingestive, ingestive, and post-ingestive deterrent against A. pisum, as an ingestive deterrent against R. padi, and as a post-ingestive deterrent against M. persicae using the relatively low 0.1% concentration. While in A. pisum the deterrent effects of hesperidin were manifested as early as during aphid probing in peripheral plant tissues, in M. persicae, the avoidance of plants was probably the consequence of consuming the hesperidin-containing phloem sap.

Using NGS Technology and Association Mapping to Identify Candidate Genes Associated with Fusarium Stalk Rot Resistance.

Stalk rot caused by Fusarium fungi is one of the most widespread and devastating diseases of maize, and the introduction of resistant genotypes is one of the most effective strategies for controlling the disease. Breeding genotypes with genetically determined resistance will also allow less use of crop protection products. The aim of the research was to identify molecular markers and associated candidate genes determining maize plant resistance to Fusarium stalk rot. The plant material for this study consisted of 122 maize hybrids. The experiment was conducted in two localities: Smolice and Kobierzyce. The Fusarium stalk rot values ranged from 1.65% (for genotype G01.10) to 31.18% (for genotype G03.07) in Kobierzyce and from 0.00% (for 58 genotypes) to 6.36% (G05.03) in Smolice. The analyzed genotypes were simultaneously subjected to next-generation sequencing using the Illumina platform. Illumina sequencing identified 60,436 SilicoDArT markers and 32,178 SNP markers (92,614 in total). For association mapping, 32,900 markers (26,234 SilicoDArT and 6666 SNP) meeting the criteria (MAF > 0.25 and the number of missing observations <10%) were used. The results of the observation of the degree of infection and sequencing were used for association mapping, which ultimately resulted in the selection of ten molecular markers important at both places. Among the identified markers, two SNP markers that are located inside candidate genes play an important role. Marker 4772836 is located inside the serine/threonine-protein kinase bsk3 gene, while marker 4765764 is located inside the histidine kinase 1 gene. Both genes can be associated with plant resistance to Fusarium stalk rot, and these genes can also be used in breeding programs to select resistant varieties.

Identification and Analysis of Candidate Genes Associated with Maize Fusarium Cob Resistance Using Next-Generation Sequencing Technology.

The pressure to reduce mineral fertilization and the amount of pesticides used has become a factor limiting production growth, as has the elimination of many crop protection chemicals from the market. A key condition for this to be an effective form of protection is the use of varieties with higher levels of resistance. The most effective and fastest way to assist in the selection and control of pathogens is the conducting of genome-wide association studies. These are useful tools for identifying candidate genes, especially when combined with QTL mapping to map and validate loci for quantitative traits. The aim of this study was to identify new markers coupled to genes that determine maize plant resistance to fusarium head blight through the use of next-generation sequencing, association and physical mapping, and to optimize diagnostic procedures to identify selected molecular markers coupled to plant resistance to this fungal disease. As a result of field experiments and molecular analyses, molecular markers coupled to potential genes for resistance to maize ear fusariosis were selected. The newly selected markers were tested against reference genotypes. As a result of the analyses, it was found that two markers (11801 and 20607) out of the ten that were tested differentiated between susceptible and resistant genotypes. Marker number 11801 proved to be the most effective, with a specious product of 237 bp appearing for genotypes 1, 3, 5, 9 and 10. These genotypes were characterized by a field resistance of 4-6 on the 9° scale (1 being susceptible, 9 being resistant) and for all genotypes except 16 and 20, which were characterized by a field resistance of 9. In the next step, this marker will be tested on a wider population of extreme genotypes in order to use it for the preliminary selection of fusarium-resistant genotypes, and the phosphoenolpyruvate carboxylase kinase 1 gene coupled to it will be subjected to expression analysis.

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.

The use of weighted multiple linear regression to estimate QTL × QTL × QTL interaction effects of winter wheat (Triticum aestivum L.) doubled-haploid lines.

Knowledge of the magnitude of gene effects and their interactions, their nature, and contribution to determining quantitative traits is very important in conducting an effective breeding program. In traditional breeding, information on the parameter related to additive gene effect and additive-additive interaction (epistasis) and higher-order additive interactions would be useful. Although commonly overlooked in studies, higher-order interactions have a significant impact on phenotypic traits. Failure to account for the effect of triplet interactions in quantitative genetics can significantly underestimate additive QTL effects. Understanding the genetic architecture of quantitative traits is a major challenge in the post-genomic era, especially for quantitative trait locus (QTL) effects, QTL-QTL interactions, and QTL-QTL-QTL interactions. This paper proposes using weighted multiple linear regression to estimate the effects of triple interaction (additive-additive-additive) quantitative trait loci (QTL-QTL-QTL). The material for the study consisted of 126 doubled haploid lines of winter wheat (Mandub × Begra cross). The lines were analyzed for 18 traits, including percentage of necrosis leaf area, percentage of leaf area covered by pycnidia, heading data, and height. The number of genes (the number of effective factors) was lower than the number of QTLs for nine traits, higher for four traits and equal for five traits. The number of triples for unweighted regression ranged from 0 to 9, while for weighted regression, it ranged from 0 to 13. The total aaagu effect ranged from - 14.74 to 15.61, while aaagw ranged from - 23.39 to 21.65. The number of detected threes using weighted regression was higher for two traits and lower for four traits. Forty-nine statistically significant threes of the additive-by-additive-by-additive interaction effects were observed. The QTL most frequently occurring in threes was 4407404 (9 times). The use of weighted regression improved (in absolute value) the assessment of QTL-QTL-QTL interaction effects compared to the assessment based on unweighted regression. The coefficients of determination for the weighted regression model were higher, ranging from 0.8 to 15.5%, than for the unweighted regression. Based on the results, it can be concluded that the QTL-QTL-QTL triple interaction had a significant effect on the expression of quantitative traits. The use of weighted multiple linear regression proved to be a useful statistical tool for estimating additive-additive-additive (aaa) interaction effects. The weighted regression also provided results closer to phenotypic evaluations than estimator values obtained using unweighted regression, which is closer to the true values.

Effect of Soil Drought Stress on Selected Biochemical Parameters and Yield of Oat × Maize Addition (OMA) Lines.

Plant growth and the process of yield formation in crops are moderated by surrounding conditions, as well as the interaction of the genetic background of plants and the environment. In the last two decades, significant climatic changes have been observed, generating unfavorable and harmful impacts on plant development. Drought stress can be considered one of the most dangerous environmental factors affecting the life cycle of plants, reducing biomass production and, finally, the yield. Plants can respond to water deficit in a wide range, which depends on the species, genetic variability within the species, the plant's ontogenesis stage, the intensity of the stress, and other potential stress factors. In plants, it is possible to observe hybrids between different taxa that certain traits adopted to tolerate stress conditions better than the parent plants. Oat × maize addition (OMA) plants are good examples of hybrids generated via wide crossing. They can exhibit morphological, physiological, and biochemical variations implemented by the occurrence of extra chromosomes of maize, as well as the interaction of maize and oat chromatin. The initial goal of the study was to identify OMA lines among plants produced by wide crossing with maize. The main goal was to investigate differences in OMA lines according to the Excised Leaf Water Loss (ELWL) test and to identify specific biochemical changes and agronomic traits under optimal water conditions and soil drought. Additionally, detection of any potential alterations that are stable in F2 and F3 generations. The aforementioned outcomes were the basis for the selection of OMA lines that tolerate growth in an environment with limited water availability. The molecular analysis indicated 12.5% OMA lines among all tested descendants of wide oat-maize crossing. The OMA lines significantly differ according to ELWL test results, which implies some anatomical and physiological adaptation to water loss from tissues. On the first day of drought, plants possessed 34% more soluble sugars compared to control plants. On the fourteen day of drought, the amount of soluble sugars was reduced by 41.2%. A significant increase of phenolic compounds was observed in the fourteen day of drought, an average of 6%, even up to 57% in line 9. Soil drought substantially reduced stem biomass, grains number, and mass per plant. Lower water loss revealed by results of the ELWL test correlated with the high yield of OMA lines. Phenolic compound content might be used as a biochemical indicator of plant drought tolerance since there was a significant correlation with the high yield of plants subjected to soil drought.

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.

Expression Profiling of the Slow Rusting Resistance Genes Lr34/Yr18 and Lr67/Yr46 in Common Wheat (Triticum aestivum L.) and Associated miRNAs Patterns.

The main efforts in common wheat (Triticum aestivum L.) breeding focus on yield, grain quality, and resistance to biotic and abiotic stresses. One of the major threats affecting global wheat cultivation and causing significant crop production losses are rust diseases, including leaf rust caused by a biotrophic fungus Puccinia triticina Eriks. Genetically determined resistance to leaf rust has been characterized in young plants (seedling resistance) as well as in plants at the adult plant stage. At the seedling stage, resistance is controlled vertically by major R genes, conferring a race-specific response that is highly effective but usually short-lived due to the rapid evolution of potentially virulent fungi. In mature plants, horizontal adult plant resistance (APR) was described, which provides long-term protection against multiple races of pathogens. A better understanding of molecular mechanisms underlying the function of APR genes would enable the development of new strategies for resistance breeding in wheat. Therefore, in the present study we focused on early transcriptomic responses of two major wheat APR genes, Lr34 and Lr67, and three complementary miRNAs, tae-miR9653b, tae-miR9773 and tae-miR9677b, to inoculation with P. triticina. Plant material consisted of five wheat reference varieties, Artigas, NP846, Glenlea, Lerma Rojo and TX89D6435, containing the Lr34/Yr18 and Lr67/Yr46 resistance genes. Biotic stress was induced by inoculation with fungal spores under controlled conditions in a phytotron. Plant material consisted of leaf tissue sampled before inoculation as well as 6, 12, 24 and 48 h postinoculation (hpi). The APR gene expression was quantified using real-time PCR with two reference genes, whereas miRNA was quantified using droplet digital PCR. This paper describes the resistance response of APR genes to inoculation with races of leaf rust-causing fungi that occur in central Europe. The study revealed high variability of expression profiles between varieties and time-points, with the prevalence of downregulation for APR genes and upregulation for miRNAs during the development of an early defense response. Nevertheless, despite the downregulation initially observed, the expression of Lr34 and Lr67 genes in studied cultivars was significantly higher than in a control line carrying wild (susceptible) alleles.

The Influence of Lead and Acyrthosiphon pisum (Harris) on Generation of Pisum sativum Defense Signaling Molecules and Expression of Genes Involved in Their Biosynthesis.

The main aim of this study was to understand the regulation of the biosynthesis of phytohormones as signaling molecules in the defense mechanisms of pea seedlings during the application of abiotic and biotic stress factors. It was important to identify this regulation at the molecular level in Pisum sativum L. seedlings under the influence of various concentrations of lead-i.e., a low concentration increasing plant metabolism, causing a hormetic effect, and a high dose causing a sublethal effect-and during feeding of a phytophagous insect with a piercing-sucking mouthpart-i.e., pea aphid (Acyrthosiphon pisum (Harris)). The aim of the study was to determine the expression level of genes encoding enzymes of the biosynthesis of signaling molecules such as phytohormones-i.e., jasmonates (JA/MeJA), ethylene (ET) and abscisic acid (ABA). Real-time qPCR was applied to analyze the expression of genes encoding enzymes involved in the regulation of the biosynthesis of JA/MeJA (lipoxygenase 1 (LOX1), lipoxygenase 2 (LOX2), 12-oxophytodienoate reductase 1 (OPR1) and jasmonic acid-amido synthetase (JAR1)), ET (1-aminocyclopropane-1-carboxylate synthase 3 (ACS3)) and ABA (9-cis-epoxycarotenoid dioxygenase (NCED) and aldehyde oxidase 1 (AO1)). In response to the abovementioned stress factors-i.e., abiotic and biotic stressors acting independently or simultaneously-the expression of the LOX1, LOX2, OPR1, JAR1, ACS3, NCED and AO1 genes at both sublethal and hormetic doses increased. Particularly high levels of the relative expression of the tested genes in pea seedlings growing at sublethal doses of lead and colonized by A. pisum compared to the control were noticeable. A hormetic dose of lead induced high expression levels of the JAR1, OPR1 and ACS3 genes, especially in leaves. Moreover, an increase in the concentration of phytohormones such as jasmonates (JA and MeJA) and aminococyclopropane-1-carboxylic acid (ACC)-ethylene (ET) precursor was observed. The results of this study indicate that the response of pea seedlings to lead and A. pisum aphid infestation differed greatly at both the gene expression and metabolic levels. The intensity of these defense responses depended on the organ, the metal dose and direct contact of the stress factor with the organ.

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.

A Comparison of Methods to Estimate Additive-by-Additive-by-Additive of QTL×QTL×QTL Interaction Effects by Monte Carlo Simulation Studies.

The goal of the breeding process is to obtain new genotypes with traits improved over the parental forms. Parameters related to the additive effect of genes as well as their interactions (such as epistasis of gene-by-gene interaction effect and additive-by-additive-by-additive of gene-by-gene-by-gene interaction effect) can influence decisions on the suitability of breeding material for this purpose. Understanding the genetic architecture of complex traits is a major challenge in the post-genomic era, especially for quantitative trait locus (QTL) effects, QTL-by-QTL interactions and QTL-by-QTL-by-QTL interactions. With regards to the comparing methods for estimating additive-by-additive-by-additive of QTL×QTL×QTL interaction effects by Monte Carlo simulation studies, there are no publications in the open literature. The parameter combinations assumed in the presented simulation studies represented 84 different experimental situations. The use of weighted regression may be the preferred method for estimating additive-by-additive-by-additive of QTL-QTL-QTL triples interaction effects, as it provides results closer to the true values of total additive-by-additive-by-additive interaction effects than using unweighted regression. This is also indicated by the obtained values of the determination coefficients of the proposed models.

The Use of DArTseq Technology to Identify Markers Related to the Heterosis Effects in Selected Traits in Maize.

Spectacular scientific advances in the area of molecular biology and the development of modern biotechnological tools have had a significant impact on the development of maize heterosis breeding. One technology based on next-generation sequencing is DArTseq. The plant material used for the research consisted of 13 hybrids resulting from the crossing of inbred maize lines. A two-year field experiment was established at two Polish breeding stations: Smolice and Lagiewniki. Nine quantitative traits were observed: cob length, cob diameter, core length, core diameter, number of rows of grain, number of grains in a row, mass of grain from the cob, weight of one thousand grains, and yield. The isolated DNA was subjected to DArTseq genotyping. Association mapping was performed using a method based on the mixed linear model. A total of 81602 molecular markers (28571 SNPs and 53031 SilicoDArTs) were obtained as a result of next-generation sequencing. Out of 81602, 15409 (13850 SNPs and 1559 SilicoDArTs) were selected for association analysis. The 105 molecular markers (8 SNPs and 97 SilicoDArTs) were associated with the heterosis effect of at least one trait in at least one environment. A total of 186 effects were observed. The number of statistically significant relationships between the molecular marker and heterosis effect varied from 8 (for cob length) and 9 (for yield) to 42 (for the number of rows of grain). Of particular note were three markers (2490222, 2548691 and 7058267), which were significant in 17, 8 and 6 cases, respectively. Two of them (2490222 and 7058267) were associated with the heterosis effects of yield in three of the four environments.

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.

Effect of Vicia sativa L. on Motility, Mortality and Expression Levels of hsp Genes in J2 Stage of Meloidogyne hapla.

Assuming that the seeds of Vicia sativa L. have a stressful effect on J2 stage Meloidogyne hapla, we undertook research on the effect of these seeds on the motility and mortality of J2 and determined the expression levels of selected hsp genes in J2. The assessment of the effect of V. sativa seeds on the motility of M. hapla specimens consisted of observing the movement of J2 immersed in a seed diffusate or in a tomato root filtrate at temperatures of 10, 17, and 21°C. In J2 treated with V. sativa (cv. Ina) seed diffusates, the expression level of hsp genes was determined by qPCR. J2 exposed to V. sativa diffusates were found to lose their motility, while their mortality did not exceed 30%. J2 in the seed diffusate were characterized by an increase in the expression levels of the Mh-hsp90, Mh-hsp1, and Mh-hsp43 genes. It is suggested that the hsp90 gene may be a potential bioindicator of the environmental impact on Meloidogyne nematodes. The impaired ability to move in J2 of M. hapla is attributable to the occurrence of V. sativa seeds in their habitat. These studies may contribute to developing methods of reducing crop damage caused by M. hapla.

The effect of herbicides on morphological features of pollen grains in Prunus serotina Ehrh. in the context of elimination of this invasive species from European forests.

Prunus serotina Ehrh. is an alien invasive neophyte widespread in European forests. So far, no effective methods of its elimination have been developed. For this reason, the aim of our study was to determine how herbicides affect the morphological characteristics of pollen grains. This knowledge may be crucial to control this invasive species. The current study was carried out in a research area of 2.7 ha located in the Zielonka Forest near Poznan, Poland (N 52°31'58.016″, E 17°05'55.588″). We tested morphological differences among ten features of P. serotina pollen, based on the samples collected from 15 control trees compared to the 50 trees treated with five different herbicides. In total 1950 pollen grains were measured. We confirmed the adopted hypotheses of long-term herbicide influence on P. serotina pollen. Pollen grains from the control trees had a longer equatorial axis, were more elongated in shape and had the largest range of exine thickness compared to the pollen from the herbicide-treated samples. Exine thickness in the control sample was on average 0.74 µm, ranging from 0.42 to 1.19 µm. The average values and the ranges of this trait in the samples treated with herbicides were larger (e.g. average exine thickness was from 0.90 to 0.95 µm). There were differences in the P/E ranges of variability between the control and herbicide-treated samples. In the control sample the P/E ratio was 1.32-2.04 and elongated forms of pollen shapes prevailed, while in the herbicide-treated samples it ranged from 1.03 to 1.47. The share of deformed pollen grains in the herbicide-treated samples was lower than expected, ranging from 8.7 to 25.3%, while in the control samples it was 6%. Logo and Mustang turned out to be the most effective among the herbicides used in the described research. The two used application methods were found to have an effect on pollen quality.

Plant Metabolites Affect Fusarium proliferatum Metabolism and In Vitro Fumonisin Biosynthesis.

Fusarium proliferatum is a common hemi-biotrophic pathogen that infect a wide range of host plants, often leading to substantial crop loss and yield reduction. F. proliferatum synthesizes various mycotoxins, and fumonisins B are the most prevalent. They act as virulence factors and specific effectors that elicit host resistance. The effects of selected plant metabolites on the metabolism of the F. proliferatum strain were analyzed in this study. Quercetin-3-glucoside (Q-3-Glc) and kaempferol-3-rutinoside (K-3-Rut) induced the pathogen's growth, while DIMBOA, isorhamnetin-3-O-rutinoside (Iso-3-Rut), ferulic acid (FA), protodioscin, and neochlorogenic acid (NClA) inhibited fungal growth. The expression of seven F. proliferatum genes related to primary metabolism and four FUM genes was measured using RT-qPCR upon plant metabolite addition to liquid cultures. The expression of CPR6 and SSC1 genes was induced 24 h after the addition of chlorogenic acid (ClA), while DIMBOA and protodioscin reduced their expression. The transcription of FUM1 on the third day of the experiment was increased by all metabolites except for Q-3-Glc when compared to the control culture. The expression of FUM6 was induced by protodioscin, K-3-Rut, and ClA, while FA and DIMBOA inhibited its expression. FUM19 was induced by all metabolites except FA. The highest concentration of fumonisin B1 (FB1) in control culture was 6.21 µg/mL. Protodioscin did not affect the FB content, while DIMBOA delayed their synthesis/secretion. Flavonoids and phenolic acids displayed similar effects. The results suggest that sole metabolites can have lower impacts on pathogen metabolism and mycotoxin synthesis than when combined with other compounds present in plant extracts. These synergistic effects require additional studies to reveal the mechanisms behind them.

Identification and Analysis of Candidate Genes Associated with Yield Structure Traits and Maize Yield Using Next-Generation Sequencing Technology.

The main challenge of agriculture in the 21st century is the continuous increase in food production. In addition to ensuring food security, the goal of modern agriculture is the continued development and production of plant-derived biomaterials. Conventional plant breeding methods do not allow breeders to achieve satisfactory results in obtaining new varieties in a short time. Currently, advanced molecular biology tools play a significant role worldwide, markedly contributing to biological progress. The aim of this study was to identify new markers linked to candidate genes determining grain yield. Next-generation sequencing, gene association, and physical mapping were used to identify markers. An additional goal was to also optimize diagnostic procedures to identify molecular markers on reference materials. As a result of the conducted research, 19 SNP markers significantly associated with yield structure traits in maize were identified. Five of these markers (28629, 28625, 28640, 28649, and 29294) are located within genes that can be considered candidate genes associated with yield traits. For two markers (28639 and 29294), different amplification products were obtained on the electrophorograms. For marker 28629, a specific product of 189 bp was observed for genotypes 1, 4, and 10. For marker 29294, a specific product of 189 bp was observed for genotypes 1 and 10. Both markers can be used for the preliminary selection of well-yielding genotypes.

The Use of DArTseq Technology to Identify Markers Linked to Genes Responsible for Seed Germination and Seed Vigor in Maize.

Seed vigor and seed germination are very important traits, determined by several factors including genetic and physical purity, mechanical damage, and physiological condition, characterized by maintaining a high seed vigor and stable content after storage. The search for molecular markers related to improvement in seed vigor under adverse condition is an important issue in maize breeding currently. Higher sowing quality of seeds is necessary for the development of the agriculture production and better ability to resist all kinds of adversity in the seeds' storage. Condition is a very important factor affecting the yield of plants, thanks to the construction of their vitality. Identification of molecular markers associated with seed germination and seed vigor may prove to be very important in the selection of high-yielding maize varieties. The aim of this study was to identify and select new markers for maize (SNP and SilicoDArT) linked to genes influencing the seed germination and seed vigor in inbred lines of maize (Zea mays L.). The plant material used for the research was 152 inbred maize lines. The seed germination and seed vigor were analyzed. For identification of SNP and SilicoDArT markers related to the seed germination and seed vigor, the SilicoDarT technique developed by Diversity Arrays Technology was used. The analysis of variance indicated a statistically significant differentiation between genotypes for both observed traits. Positive (r = 0.41) correlation (p < 0.001) between seed germination and seed vigor was observed. As a result of next-generation sequencing, the molecular markers SilicoDArT (53,031) and SNP (28,571) were obtained. Out of 81,602 identified SilicoDArT and SNP markers, 15,409 (1559 SilicoDArT and 13,850 SNP) were selected as a result of association mapping, which showed them to be significantly related to the analyzed traits. The 890 molecular markers were associated with seed vigor, and 1323 with seed germination. Fifty-six markers (47 SilicoDArT and nine SNP) were significant for both traits. Of these 56 markers, the 20 most significant were selected (five of these markers were significant at the level of 0.001 for seed vigor and at the level of 0.05 for seed germination, another five markers were significant at the level of 0.001 for seed germination and at the level of 0.05 for seed vigor, five markers significant at the level of 0.001 only for seed vigor and five significant at the level of 0.001 only for seed germination also selected). These markers were used for physical mapping to determine their location on the genetic map. Finally, it was found that six of these markers (five silicoDArT­2,435,784, 4,772,587, 4,776,334, 2,507,310, 25,981,291, and one SNP­2,386,217) are located inside genes, the action of which may affect both seed germination and seed vigor. These markers can be used to select genotypes with high vigor and good seed germination.