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Safflower (Carthamus tinctorius L.) is a promising oilseed crop with potential applications in the food, pharmaceutical, and industrial sectors. Understanding the oil content and fatty acid composition of safflower germplasm is crucial for breeding programs aimed at enhancing its agronomic and nutritional traits. This study assessed the oil content and fatty acid composition in 87 safflower accessions. Significant variations were observed, with the oil content ranging from 36.88% to 18.44%. Genotype Egypt 1 exhibited the highest oil content. Among fatty acids, China 1 had the highest myristic acid (0.170%) content, while Remzibey had the lowest (0.100%). Palmitic acid ranged from 6.13% to 8.20%, with Egypt 3 and Bangladesh 3 at the extremes. For palmitoleic acid, Jordan 5 had the highest content (0.53%) and Bangladesh 2/Portugal 2 the lowest (0.03%). Linoleic acid varied from 37.7% (China 7) to 77.73% (Iran 1). A correlation analysis indicated strong positive correlations between protein and oil content, as well as between palmitic and myristic acids, and between palmitic and linoleic acids. Conversely, protein exhibited highly negative correlations with myristic, palmitic, and palmitoleic acids. The protein percentage showed a high heritability but a low genetic advance, while palmitic acid, oil percentage, stearic acid, linoleic acid, palmitoleic acid, and oleic acid showed a high heritability and a moderate genetic advance as a percentage of the mean. These findings can aid in developing cultivars with enhanced fatty acids, oil quality, and nutritional value, facilitating sustainable production for a wide range of industrial applications. [ABSTRACT FROM AUTHOR]

Apple (Malus domestica [Suckow] Borkh) holds global economic and cultural value, particularly in temperate regions. This study investigates the genetic variations among 52 apple accessions from three research centre's in Kazakhstan, employing the iPBS-retrotransposons marker system. Of the 35 markers initially screened, 12 highly polymorphic markers were selected for PCR amplification, producing 280 bands, 279 of which were polymorphic, yielding a polymorphism rate of 99.64%. Genetic diversity indices revealed notable variability with the effective number of alleles (ne = 1.655), Shannon's information index (I = 0.373), gene diversity (h = 0.549), and an average genetic distance of 1.2. Analysis of molecular variance (AMOVA) demonstrated that 97% of the genetic variation occurred within the population. STRUCTURE analysis divided the germplasm into two distinct populations and one unclassified population based on collection centers. Both the neighbor-joining tree and principal coordinate analysis (PCoA) supported these results, confirming the genetic separation into two groups. This study highlighted the significant genetic diversity among apple accessions, demonstrating the effectiveness of the iPBS-retrotransposons marker system. Additionally, the highest genetic distance (1.2) observed between the Tyulpan and Red Chief samples, positions these accessions as suitable and promising candidates for future breeding initiatives. [ABSTRACT FROM AUTHOR]

In modern plant breeding, molecular markers have become indispensable tools, allowing the precise identification of genetic loci linked to key agronomic traits. These markers provide critical insight into the genetic architecture of crops, accelerating the selection of desirable traits for sustainable agriculture. This review focuses on the advancements in quantitative trait locus (QTL) mapping and genome-wide association studies (GWASs), highlighting their effective roles in identifying complex traits such as stress tolerance, yield, disease resistance, and nutrient efficiency. QTL mapping identifies the significant genetic regions linked to desired traits, while GWASs enhance precision using larger populations. The integration of high-throughput phenotyping has further improved the efficiency and accuracy of QTL research and GWASs, enabling precise trait analysis across diverse conditions. Additionally, next-generation sequencing, clustered regularly interspaced short palindromic repeats (CRISPR) technology, and transcriptomics have transformed these methods, offering profound insights into gene function and regulation. Single-cell RNA sequencing further enhances our understanding of plant responses at the cellular level, especially under environmental stress. Despite this progress, however, challenges persist in optimizing methods, refining training populations, and integrating these tools into breeding programs. Future studies must aim to enhance genetic prediction models, incorporate advanced molecular technologies, and refine functional markers to tackle the challenges of sustainable agriculture. [ABSTRACT FROM AUTHOR]

ABSTRACT Micronutrient deficiencies, such as manganese (Mn), pose significant global health risks, affecting millions of people worldwide and leading to serious health conditions. Biofortifying crops, notably common beans, offer a sustainable solution to combat these deficiencies. This study aimed to uncover the genetic basis associated with Mn content in Turkish common bean (Phaseolus vulgaris) germplasm through a genome‐wide association study (GWAS), which is crucial for developing nutrient‐rich bean varieties. Here, we examined variation among 183 common bean accessions, collected from 19 provinces of Turkey and identified the genetic basis linked to seed Mn content. Genotype by environment interaction significantly influenced Mn content (p < 0.05). The mean Mn content was observed 31.69 mg kg−1 across the germplasm. Bingol‐16 had the lowest, while Malatya‐59 had the highest Mn contents. Stability analysis was performed using the ‘STABILITYSOFT’ method and found 10 stable accessions. The cluster constellation plot was generated using JMP statistical software. A total of 7900 DArTseq markers were used for association analysis, identifying 16 markers across four chromosomes (Pv2, Pv5, Pv7 and Pv11). Notably, markers DArT‐3374915 and DArT‐3375187 exhibited consistent associations across different environments, making them promising candidates for Mn‐focused breeding programmes. Gene annotation and interactome analysis, including BLAST searches and protein–protein interaction analysis, revealed associations of candidate genes with Mn concentration regulation, shedding light on potential mechanisms underlying Mn accumulation in common beans. Our findings lay a foundation for marker‐assisted breeding efforts in common bean improvement. [ABSTRACT FROM AUTHOR]

With the development of new technologies in recent years, researchers have made significant progress in crop breeding. Modern breeding differs from traditional breeding because of great changes in technical means and breeding concepts. Whereas traditional breeding initially focused on high yields, modern breeding focuses on breeding orientations based on different crops' audiences or by-products. The process of modern breeding starts from the creation of material populations, which can be constructed by natural mutagenesis, chemical mutagenesis, physical mutagenesis transfer DNA (T-DNA), Tos17 (endogenous retrotransposon), etc. Then, gene function can be mined through QTL mapping, Bulked-segregant analysis (BSA), Genome-wide association studies (GWASs), RNA interference (RNAi), and gene editing. Then, at the transcriptional, post-transcriptional, and translational levels, the functions of genes are described in terms of post-translational aspects. This article mainly discusses the application of the above modern scientific and technological methods of breeding and the advantages and limitations of crop breeding and diversity. In particular, the development of gene editing technology has contributed to modern breeding research. [ABSTRACT FROM AUTHOR]

Industrial hemp (Cannabis sativa L.) is a highly recalcitrant plant under in vitro conditions that can be overcome by employing external stimuli. Hemp seeds were primed with 2.0–3.0% hydrogen peroxide (H2O2) followed by culture under different Light Emitting Diodes (LEDs) sources. Priming seeds with 2.0% yielded relatively high germination rate, growth, and other biochemical and enzymatic activities. The LED lights exerted a variable impact on Cannabis germination and enzymatic activities. Similarly, variable responses were observed for H2O2 × Blue-LEDs combination. The results were also analyzed by multiple regression analysis, followed by an investigation of the impact of both factors by Pareto chart and normal plots. The results were optimized by contour and surface plots for all parameters. Response surface optimizer optimized 2.0% H2O2 × 918 LUX LEDs for maximum scores of all output parameters. The results were predicted by employing Multilayer Perceptron (MLP), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Moreover, the validity of these models was assessed by using six different performance metrics. MLP performed better than RF and XGBoost models, considering all six-performance metrics. Despite the differences in scores, the performance indicators for all examined models were quite close to each other. It can easily be concluded that all three models are capable of predicting and validating data for cannabis seeds primed with H2O2 and grown under different LED lights.Key message: Chemical priming of H2O2 with LED lights regulates the cannabis plant growth. Use of Pareto chart and normal plots to rank the input factor, their impact, and efficiency in percentage. Use of optimizing tools like contour plots, surface plots, and response optimizers to optimize H2O2 and LED lights for cannabis. Data validation and prediction using AI/ML-based MLP, RF, and XGBoost models. [ABSTRACT FROM AUTHOR]