Search Results (439)

The non-destructive and chemical-free determination of anthocyanin content in single maize kernels is of great importance for plant-breeding programs. Previous studies have mainly relied on Near-Infrared Reflectance (NIR) spectroscopy and color-based approaches, often using conventional or randomly selected modeling techniques. In this study, an Automated Machine Learning (AutoML) framework was employed to predict anthocyanin content using spectral and digital image data obtained from individual maize kernels measured in two orientations (embryo-up and embryo-down). Forty colored maize genotypes representing diverse phenotypic characteristics were analyzed. Digital images were acquired in RGB, HSV, and LAB color spaces, together with NIR spectral data, from a total of 200 kernels. Reference anthocyanin content was determined using a colorimetric method. Ten datasets were constructed by combining different color space and spectral features and were grouped according to kernel orientation. AutoML was used to evaluate nine machine learning algorithms, while Partial Least Squares Regression (PLSR) served as a classical benchmark method, resulting in the development of 1918 predictive models. Kernel orientation had a notable effect on model performance and outlier detection. The best predictions were obtained from the RGB dataset for embryo-up kernels and from the combined RGB+HSV+LAB+NIR dataset for embryo-down kernels. Overall, AutoML outperformed conventional modeling by automatically identifying optimal algorithms for specific data structures, demonstrating its potential as an efficient screening tool for anthocyanin content at the single-kernel level. Full article

Maize (Zea mays L.), a vital crop for global food and economic security, faces intensifying biotic and abiotic stresses driven by climate change, including drought, heat, and erratic rainfall. This review synthesizes emerging biotechnology-driven strategies designed to enhance maize resilience under these shifting environmental conditions. We present an integrated framework that encompasses CRISPR/Cas9 and next-generation genome editing, Genomic Selection (GS), Environmental Genomic Selection (EGS), and multi-omics platforms—spanning transcriptomics, proteomics, metabolomics, and epigenomics. These approaches have significantly deepened our understanding of complex stress-adaptive traits and genotype-by-environment interactions, revealing precise targets for breeding climate-resilient cultivars. Furthermore, we highlight enabling technologies such as high-throughput phenotyping, artificial intelligence (AI), and nanoparticle-based gene delivery—including novel in planta and transformation-free protocols—that are accelerating translational breeding. Despite these technical breakthroughs, barriers such as genotype-dependent transformation efficiency, regulatory landscapes, and implementation costs in resource-limited settings remain. Bridging the gap between laboratory innovation and field deployment will require coordinated policy support and global collaboration. By integrating molecular breakthroughs with practical deployment strategies, this review offers a comprehensive roadmap for developing sustainable, climate-resilient maize varieties to meet future agricultural demands. Full article

Low temperature during early spring severely impairs maize germination, leading to significant yield losses. To elucidate the mechanisms underlying cold tolerance at the germination stage, we compared two cold-tolerant maize inbred lines (AM and CM) with a cold-sensitive line (BM) under control (25 °C) and chilling (6 °C) conditions. Phenotypic observations showed that AM and CM maintained high germination rates and exhibited enhanced coleoptile elongation under cold stress, whereas BM displayed substantial growth inhibition. Cold-tolerant lines accumulated less malondialdehyde and showed markedly higher SOD and POD activities, indicating a stronger antioxidant defense. Transcriptome profiling revealed that cold tolerance is associated with a more robust transcriptional response in AM and CM, characterized by significant activation of the phenylpropanoid and flavonoid biosynthesis pathways. Among the differentially expressed genes, the class III peroxidase gene ZmPER5 was strongly upregulated in AM and CM but only weakly induced in BM, suggesting its central role in reinforcing the cell wall structure and enhancing ROS-scavenging capacity under chilling conditions. Other lignin- and flavonoid-related genes, including ZmHCT4 and ZmCYP75, also exhibited genotype-specific induction patterns consistent with cold tolerance. qRT-PCR validation confirmed the RNA-seq expression trends. These results demonstrate that maize cold tolerance during germination relies on the coordinated enhancement of antioxidant enzyme activity, activation of phenylpropanoid-derived lignin biosynthesis, and accumulation of protective flavonoids. The identified candidate genes, especially ZmPER5, provide valuable targets for improving cold tolerance in maize breeding. Full article

Organic production systems impose strong environmental constraints on silage maize, yet the relative contributions of genotype, environment and their interaction (G × E) to key performance traits remain insufficiently resolved. This study evaluated six maize cultivars across 11 organically managed environments (location × year combinations) in Poland, assessing weed infestation, plant height, fresh matter yield, dry matter content and dry matter yield. Genotype × environment interaction was explicitly analyzed using AMMI-based models, and cultivar adaptability and stability were evaluated using complementary indices. Environmental effects consistently dominated all traits, explaining 78–91% of total variation, while G × E interactions, though smaller, were significant and altered cultivar rankings. Weed infestation ranged widely across environments, from below 10% to over 90%, and was almost entirely environment-driven. Yield-related traits followed a strong precipitation gradient, with Pawłowice and Śrem showing the highest biomass potential. SM Perseus produced the greatest dry matter yields (13.53 t·ha⁻¹), whereas SM Mieszko combined high dry matter content (37.73%) with outstanding stability. Mega-environment analysis identified distinct adaptive niches, confirming that no genotype performed consistently best across all conditions. These findings close a key knowledge gap regarding cultivar performance under organic management and demonstrate the necessity of multi-environment evaluation that integrates performance, stability and adaptability analyses to support site-specific cultivar recommendations that enhance biomass productivity and silage quality in ecologically managed maize systems. Full article

Pericarp characteristics are key factors determining the eating quality of fresh-eating maize. This study aimed to elucidate the genetic basis of traits such as pericarp thickness, break force, and brittleness in fresh-eating maize, identify key genes regulating these traits, and provide a theoretical foundation for improving mouthfeel quality through molecular marker-assisted breeding. Using 196 fresh-eating maize inbred lines with diverse genetic backgrounds, pericarp-related traits were phenotypically measured using a texture analyzer. Genotyping was performed using the GenoBaits Maize 45K Panel chip (MolBreeding, Shijiazhuang City, China). Genome-wide association studies (GWAS) were conducted to identify significantly associated SNP loci, and candidate genes were screened for functional annotation. Phenotypic analysis revealed a significant positive correlation between pericarp thickness and break force, and a significant negative correlation between break force and brittleness. GWAS detected 21, 2, and 1 stable SNPs significantly associated with pericarp thickness, break force, and brittleness, respectively. A total of 47 candidate genes for pericarp thickness, 7 for break force, and 4 for brittleness were identified. Functional annotation indicated that the candidate gene Zm00001eb314860 (ZmbZIP130), annotated as a member of the bZIP transcription factor family, may function as a pleiotropic gene involved in regulating pericarp-related traits. These findings demonstrate that pericarp traits in fresh-eating maize are controlled by multiple genes. The significant loci and candidate genes identified in this study lay a foundation for further elucidating the molecular mechanisms underlying pericarp quality formation and for molecular breeding. Full article

Purple corn (Zea mays L.) is a nutraceutical crop of increasing economic importance in Peru, yet its productivity is highly influenced by genotype × environment (G × E) interactions across heterogeneous agro-ecological zones. Therefore, selecting suitable genotypes for specific environments is essential to optimize variety deployment and maximize site-specific yield. Five purple-maize genotypes (INIA-601, INIA-615, Canteño, PMV-581, and Sintético-MM) were evaluated in four contrasting Peruvian sites using a randomized complete-block design. Grain yield, field weight, anthesis–silking interval (ASI), plant height, and ear-rot incidence were analyzed with combined analysis of variance (ANOVA), the additive main effects and multiplicative interaction (AMMI), genotype and genotype-by-environment (GGE) biplots, Weighted Average of Absolute Scores (WAAS), weighted average of absolute scores and best yield index (WAASBY), and Y × WAAS indices. Environment accounted for 90.1% of field-weight variation (p < 0.0001) and 50.2% of grain-yield variation (p < 0.001), while significant G × E interactions (3.93% and 18.14%, respectively) justified bilinear modeling. AMMI1 and GGE “which-won-where” biplots identified INIA-615 and PMV-581 as broadly adapted, with INIA-615 achieving the highest WAASBY and positioning in quadrant IV of Y × WAAS (high yield, high stability). INIA-601 and Sintético-MM exhibited exceptional stability (low ASV) but moderate productivity; Canteño showed limited adaptability. Chumbibamba emerged as a key discriminating, high-productivity location. From an agronomic perspective, INIA-615 is recommended for high-productivity valleys such as Sulluscocha and Santa Rita, where its yield potential and stability are maximized. These findings underscore the potential of integrating multivariate stability metrics with physiological and disease-resistance traits to guide the selection of superior purple corn cultivars. Overall, INIA-615 represents a robust candidate for enhancing yield stability, supporting sustainable intensification, and expanding the nutraceutical value chain of purple corn in the Andean highlands. Full article

Identifying superior genotypes in multi-environment trials is crucial for accelerating cultivar improvement and breeding innovation. This study evaluated the yield potential of 29 maize hybrids (including the control) across 10 trial locations in mid-to-high altitude regions of Yunnan Province from two growing seasons (2023–2024), aiming to recommend high-yielding, stable, and widely adapted maize varieties. Analysis of variance indicated that genotype, environment, and their interaction all had highly significant effects (p < 0.001) on maize yield, with environmental factors accounting for the primary source of variation; in 2023 and 2024, 63.79% and 64.15% of the total variation were explained, respectively. The grain yield of the maize hybrids ranged from 8873 kg/ha to 12,089 kg/ha, with the highest yield over the two consecutive years being 11,783 kg/ha (XR-399). Yield mean analysis identified the top-performing hybrids annually: in 2023, these were G28, G13, G22; in 2024, they included G5, G13, G4. In the GGE biplot analysis, E2 (Binchuan), E5 (Lijiang), E7 (Shilin), and E8 (Xuanwei) were the most distinguishable and representative test environments. The “mean vs. stability” GGE biplot indicated that G22 (LS-2305), G9 (LS-2303), and G13 (XR-399) exhibited consistent high yields and stability across years. Based on the “Which-Won-Where” GGE biplot, G27 (SS-2205) and G13 (XR-399) were identified as the optimal hybrids for each mega-environment, with G13 (XR-399) emerging as the most outstanding. Therefore, these findings confirm that the GGE biplot method is effective for screening high-yielding, stable hybrids and identifying representative test environments, thereby providing a scientific foundation for maize breeding work in the region. Full article

Popcorn (Zea mays everta) is a special type of flint maize that boasts several unique popping characteristics highly valued worldwide. Water-limiting conditions strongly influence the major popcorn quality attributes: expansion volume, popability, and nutritional composition. The objectives of this study were to identify rainfed popcorn genotypes with superior popping quality, nutritional quality, and agronomic performance. Seven diverse popcorn genotypes, including a check cultivar, were evaluated for two consecutive years (2023–2024) using a randomized complete block design with three replications at the university research farm, PMAS-AAUR. Significant genetic variations were observed across all morphological, physiological, and quality-related traits. Among the evaluated materials, Pop-2 consistently exhibited outstanding performance in key agronomic and physiological attributes as well as in popping quality, while Pop-5 and Pop-3 also showed promising potential. Overall, Pop-2, Pop-5, and Pop-3 were identified as the most suitable genotypes for cultivation and are recommended as candidates for future breeding programs targeting improved popcorn performance under rainfed conditions. Full article

The aim of this study was to evaluate the agronomic performance of eight maize hybrids under different plant densities for grain yield in the North and Northwest regions of Rio de Janeiro State, Brazil. Maize productivity is strongly influenced by planting density, which affects light interception, resource competition, and grain yield. Understanding the optimal density for specific hybrids is essential to maximizing production under varying environmental conditions. The hybrids were evaluated in two locations (Campos dos Goytacazes and Itaocara) using four plant densities (50,000; 66,667; 83,333; and 100,000 plants ha⁻¹). The experimental design was a randomized complete block with three replications in a split-plot arrangement. Traits evaluated included plant height, ear height, ear length and diameter, 100-grain weight, and grain yield. Planting density significantly affected ear length, ear diameter, 100-grain weight, and grain yield, with higher densities generally reducing morphological traits but increasing overall yield. No significant genotype × density interaction was detected, but some hybrids, such as UENF 506-16 and UENF 506-11, performed better at specific densities, standing out for productivity and economic return. These results indicate that increasing plant density can be an effective strategy for maximizing maize yield in the studied environments. Full article

The production and quality of wheat and maize grain can be significantly affected by various pests and pathogens, with phytoplasmas posing a particular threat due to their rapid spread and potential to cause severe damage to cultivated crops. The objective of this investigation was to evaluate the risk associated with these wall-less bacteria in wheat and maize crops. To achieve this, a survey was conducted in commercial fields located in southwestern Poland. Samples of winter wheat and fodder maize were collected at two distinct developmental stages, including both symptomatic and asymptomatic plants. Symptoms observed in wheat included yellowing, stunting, and excessive tillering, while maize plants showed yellow leaf striping, red discoloration, and stunted growth. Polymerase chain reaction (PCR) assays using phytoplasma-specific primers, followed by Sanger sequencing and sequence analysis, confirmed phytoplasma infections in 2% of wheat and 1.5% of maize samples. Virtual restriction fragment length polymorphism (RFLP) analysis identified the wheat-infecting phytoplasmas as belonging to subgroup 16SrI-C (‘Candidatus Phytoplasma tritici’-related strain)—a pathogen of major concern for wheat, while maize-infecting phytoplasmas were classified into subgroups 16SrI-B and 16SrV-C. Additionally, wheat plants collected during the early elongation phase were tested for Mastrevirus hordei (former wheat dwarf virus, WDV) using double antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA), which confirmed the presence of WDV in all tested samples. Preliminary screening of field-collected leafhoppers revealed that 7.5% of Psammotettix alienus, the predominant species in wheat fields, carried 16SrI-C phytoplasmas. In maize fields, Zyginidia scutellaris was the most prevalent species, with 1.7% of individuals carrying 16SrV-C phytoplasma. These findings suggest that these insect species may contribute to the transmission of phytoplasmas in wheat and maize. This study provides the first documented evidence of 16SrI-C phytoplasma infecting wheat in Poland, and of 16SrV-C and 16SrI-B phytoplasmas infecting maize, expanding the known host range of these subgroups in the country and highlighting their potential phytosanitary importance. Full article

Low temperature exerts severe adverse effects on maize growth, particularly during the seedling stage. Screening for cold-tolerant maize genotypes is highly significant for identifying genes associated with cold tolerance and enhancing maize performance under low, suboptimal temperature conditions. The identification of representative cold tolerance-related genes is of great significance for the breeding of cold-resistant maize varieties. In this study, a diversity panel of 205 materials was evaluated and classified for cold tolerance at the seedling stage. The coefficients of variation of all materials ranged from 14.53% to 35.71%, reflecting considerable genetic diversity within the panel. The correlation coefficients for each phenotypic trait between the cold-treated (CT) and control (CK) maize materials ranged from 0.60 to 0.90, further indicating that all traits displayed varying degrees of sensitivity to cold stress. A comprehensive evaluation of cold tolerance using the D value was conducted. The D values of all materials ranged from 0.355 to 0.863, with a mean value of 0.64. A hierarchical clustering analysis was performed to classify all materials into five categories based on their cold tolerance. Further, 17 SNPs were identified using GWAS analysis, and 12 candidate genes were located within the regions related to the SNPs. Some candidate genes were closely associated with cold tolerance, such as genes encoding MYB and GRAS transcription factors, leucine-rich repeat (LRR) proteins, and protein kinases. Validation by qRT-PCR confirmed that the expression of some genes was induced under cold stress conditions. These findings lay a crucial foundation for breeding cold-tolerant maize varieties and for further exploration of genes associated with cold tolerance. Full article

Wheat is a major staple crop in Xinjiang, China; however, comprehensive data on Fusarium mycotoxin contamination in wheat from this region remain limited. Despite recent observations of Fusarium head blight (FHB), few studies have characterized the mycotoxin profiles in wheat from Xinjiang, especially regarding emerging mycotoxins. This study aimed to systematically investigate the occurrence of both conventional and emerging mycotoxins in freshly harvested wheat from Xinjiang, to evaluate the effects of sampling year and geographical region on mycotoxin contamination levels, and to identify the Fusarium species responsible for mycotoxin production. A total of 151 freshly harvested wheat samples were collected from Southern and Northern Xinjiang in 2023 and 2024. Mycotoxins were quantified using high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS). Fusarium isolates were obtained and identified through the translation elongation factor 1-alpha (TEF-1α) gene sequencing. Genotyping was assessed by genotype-specific multiplex PCR, and mycotoxigenic potential was detected by rice culture assays. A high incidence (72.9%) of co-contamination with multiple mycotoxins was observed. Conventional mycotoxins such as deoxynivalenol (DON) and zearalenone (ZEN) were detected in 31.1% and 41.1% of samples. Notably, emerging mycotoxins, including enniatins (ENNs) and beauvericin (BEA), were present at significantly higher concentrations than those reported in some regions of China. Significant spatiotemporal variation was observed, with markedly higher contamination levels of emerging mycotoxins in 2024, particularly in Northern Xinjiang, where the symptoms of FHB epidemic occurred due to the humid climate and maize–wheat rotation system. Fusarium graminearum was identified as the primary producer of conventional mycotoxins, while F. acuminatum and F. avenaceum were mainly associated with emerging mycotoxins except BEA. This study provides the first comprehensive dataset on the co-occurrence of conventional and emerging Fusarium mycotoxins in wheat from Xinjiang and highlights significant spatiotemporal variations influenced by environmental factors. These findings underscore the necessity for continuous, region-specific monitoring and effective risk management strategies to address the evolving mycotoxin threat in Xinjiang’s wheat. Future research should focus on characterizing the populations of Fusarium toxin-producing fungi and the long-term impacts of mycotoxin exposure on food safety. Full article

Next-generation sequencing (NGS) has revolutionized genetic research, enabling the massive, rapid, and relatively inexpensive analysis of the genomes, transcriptomes, and epigenomes of various organisms, including maize. Therefore, this paper uses NGS, association mapping, and physical mapping to identify candidate genes associated with yield structure traits and yield in maize (Zea mays L.). Furthermore, expression analysis of selected candidate genes was performed to confirm their contribution to yield formation. The plant material used for the study was 186 F1 hybrids and 20 reference genotypes (high-yielding and low-yielding). Field experiments were conducted simultaneously in two locations (in Smolice and Kobierzyce). NGS yielded a total of 45,876 molecular markers (24,437 SilicoDArT markers and 21,439 SNP markers) relevant to yield and crop structure. The largest number of markers in both localities (Smolice and Kobierzyce) was related to: the number of grain rows (6960), dry matter content after harvest (6616), the number of grains in a row (6721), mass of grain from the cob (6616), and cob length (6564). The smallest number of markers in both localities was related to yield (t ha⁻¹) (1114) and yield from the plot (1237). To narrow down the number of markers for physical mapping, ten were selected from all the significant ones associated with the same traits in both localities (Kobierzyce and Smolice). Significant markers included eight silicoDArT markers (459199, 2447305, 4768759, 4579916, 4764335, 2448946, 2492509, 4774802) and two SNP markers (9692004, 5587791). These markers were used for physical mapping. These markers are located on chromosomes 7, 8, and 10. Some of these markers are located at a considerable distance from characterized genes or within uncharacterized genes. Two markers caught our attention: SNP 5587791 and silicoDArT 4774802. The first one is located on chromosome 8 inside exon 5 of the LOC100383455 U-box domain-containing protein 7 gene, the second marker is also located on chromosome 8 near (300 bp) the LOC103635953 putative WUSCHEL-related homeobox 2 protein gene. Our own research and literature reports indicate the usefulness of next-generation sequencing, association mapping, and physical mapping for identifying candidate genes associated with economically important traits in maize. Furthermore, two genes characterized in detail in the publication, LOC100383455 U-box domain-containing protein 7 gene and LOC103635953 putative WUSCHEL-related homeobox 2 protein gene, may be involved in processes related to maize yield. Full article

Maize stalk lodging causes substantial yield losses worldwide. Although stalk strength is a genetically determined trait, its molecular mechanisms—particularly the dynamic changes during key developmental stages—remain inadequately characterized due to limitations of single-omics approaches. This study employed an integrated transcriptomic and metabolomic analysis strategy to compare stalk tissues from three maize genotypes with contrasting lodging resistance: the highly resistant inbred line PHB1M, the susceptible inbred line Chang 7-2, and their recombinant inbred line 23NWZ561 (abbreviated as P, C, and Z, respectively). Dynamic sampling of all three genotypes was conducted at both grain-filling and maturity stages, with simultaneous measurement of physiological traits related to stalk strength. Phenotypic analysis revealed that the resistant genotype PHB1M exhibited superior rind penetration strength, cell wall composition (cellulose, hemicellulose, and lignin) content, and vascular bundle development. Multi-omics analysis indicated that the molecular basis of lodging resistance is primarily established during the maturity stage. The transcriptomic and metabolomic profiles of the recombinant inbred line Z shifted from clustering with the susceptible parent C at the grain-filling stage to grouping with the resistant parent P at maturity. Key pathways including phenylpropanoid biosynthesis were significantly enriched specifically at maturity, accompanied by upregulation of related genes (PAL, HCT, CCR) and accumulation of metabolites such as lignin precursors in PHB1M. Integrated analysis identified a core co-expression network within the phenylpropanoid pathway comprising three genes and three metabolites. This study systematically demonstrates that lodging resistance in maize is regulated by transcriptional and metabolic reprogramming during late stalk developmental stages, particularly at maturity, where enhanced activation of the phenylpropanoid biosynthesis pathway plays a central role. These findings provide valuable candidate genes and metabolic markers for breeding lodging-resistant maize varieties. Full article

Molecular marker identification is a technique used to ensure fairness when submitting innovative crop varieties. Based on data from a collaborative experiment, our study appraised the reliability of the SNP molecular marker method applied simultaneously to China’s five major crops (wheat, rice, maize, cotton, and soybean) and proposed improved methods to (1) estimate detection uncertainty statistics and (2) graphically represent the detection results. We found that the detection method was quite reliable, as the average trueness rates for wheat, rice, cotton, soybean, and maize were 99.5%, 99.2%, 98.1%, 97.2%, and 96.2%, respectively, in sequence. The laboratory effect, genotype effect, and the effect of the interaction between the laboratory and the genotype all reached highly significant levels in the detection results, but their significance differed between crops. The proposed multi-genotype method confirmed the overestimation of the uncertainty statistics by up to 13% through the single-genotype method currently recommended in ISO 5725. The proposed Lab plus Lab by Genotype interaction (LLG) biplot provides a simple, intuitive, and efficient way to present, in two distinct and complementary biplot views, the trueness–precision of the detection results and the accuracy of the laboratories involved, respectively. Full article