Search Results (1,299)

Drought stress is a major environmental constraint that significantly reduces wheat productivity worldwide. In this study, seventeen wheat genotypes were evaluated under well-watered and drought-stressed conditions across two consecutive years (2023–2024) in a controlled greenhouse experiment. Twenty morphological and agronomic traits were recorded, and their responses to prolonged water limitation were assessed using multivariate statistical methods, including three-way ANOVA, principal component analysis (PCA), and cluster analysis. Drought stress significantly decreased all traits except the harvest index (HI), with the most severe reductions observed in traits related to secondary spikes (e.g., grain weight reduced by 95%). The ANOVA results confirmed significant genotype × treatment (G × T) interactions for key agronomic traits, with the strongest effect observed for total grain weight (F = 7064.30, p < 0.001). A PCA reduced the 20 original variables to five principal components, explaining 87.2% of the total variance. These components reflected distinct trait groups associated with productivity, spike architecture, and development in phenology. Cluster analysis based on PCA scores grouped genotypes into three clusters with contrasting drought response profiles. A yield-based evaluation confirmed the cluster structure, distinguishing genotypes with a stable performance (average yield loss ~58%) from highly sensitive ones (~70% loss). Overall, the findings demonstrate that drought tolerance in wheat is governed by complex trait interactions. Integrating a trait-based multivariate analysis with a yield stability assessment enables the identification of genotypes with superior adaptation to water-limited environments, providing an excellent genotype background for future breeding efforts. Full article

Fumonisins, primarily produced by Fusarium spp. and Aspergillus section nigri, are common contaminants in maize, cereal grains, and other processed and derived products, representing a significant risk to food safety and public health. This study presents the development and optimisation of a high-performance liquid chromatography method with fluorescence detection (HPLC-FLD) for the quantification of fumonisin B1 (FB1) and B2 (FB2) in various food matrices. In contrast with conventional protocols employing potassium phosphate buffers as the mobile phase, the proposed method utilises formic acid, offering enhanced compatibility with liquid chromatography systems. An automated online precolumn derivatisation with o-phthaldialdehyde (OPA) was optimised through experimental design and response surface methodology, enabling baseline separation of FB1 and FB2 derivatives in less than 20 min. The method demonstrated high sensitivity, with limits of detection of 0.006 µg mL⁻¹ for FB1 and 0.012 µg mL⁻¹ for FB2, and excellent repeatability (intraday RSD values of 0.85% and 0.83%, respectively). Several solid-phase extraction (SPE) strategies were evaluated to enhance sample clean-up using a variety of food samples, including dried figs, raisins, dates, corn, cornmeal, wheat flour, and rice. FumoniStar Inmunoaffinity columns were the only clean-up method that provided optimal recoveries (70–120%) across all tested food matrices. However, the MultiSep™ 211 column yielded good recoveries for both fumonisins in dried figs and raisins. Additionally, the C18 cartridge achieved acceptable recoveries for both fumonisins in dried figs and wheat flour. Full article

Since wheats used for use in brewing mainly belong to the winter red hard hybrid endosperm type, this paper examined the influence of different proportions of wheat of this type (seven varieties) in the ratio of 0–100% in the grist, both unmalted and as wheat malt. The quality of the starting wheats, the resulting malts and mashs with different added wheat proportions (100, 80, 60, 40, 20 and 0%) were examined. The obtained results show that the maximum shares of wheat/wheat malt in the infusion are significantly different between varieties of similar initial quality. However, they can differ considerably for the same variety when it is used as unmalted raw material and when it is used as wheat malt. Wheat malt can be added to the mixture in a significantly larger proportion compared to unmalted wheat. Furthermore, when an extended number of criteria (parameters) are applied, some varieties may be acceptable that otherwise would not be if the basic number of parameters were applied (total protein—TP, total soluble protein—TSP and viscosity—VIS) and vice versa. The inclusion of other parameters—filtration speed (FIL), saccharification time (SAC), color (COL), proportion of fine extract (EXT) and fermentability of pomace (FAL) (some of which have the character of so-called “cumulative parameters”)—complicates a clear classification into the aforementioned qualitative groups but also increases the number of varieties acceptable or conditionally acceptable for brewing. Full article

Potato (Solanum tuberosum L.) is one of the most important food crops in the world, ranking fourth after rice, maize, and wheat. Potatoes are exposed to biotic and abiotic environmental factors, which lead to economic losses and increase the possibility of food security threats in many countries. Traditional potato breeding faces several challenges, primarily due to its genetic complexity and the time-consuming nature of the process. Therefore, gene editing—CRISPR-Cas technology—allows for more precise and rapid changes to the potato genome, which can speed up the breeding process and lead to more effective varieties. In this review, we consider CRISPR-Cas technology as a potential tool for plant breeding strategies to ensure global food security. This review summarizes in detail current and potential technological breakthroughs that open new opportunities for the use of CRISPR-Cas technology for potato breeding, as well as for increasing resistance to abiotic and biotic stresses, and improving potato tuber quality. In addition, the review discusses the challenges and future perspectives of the CRISPR-Cas system in the prospects of the development of potato production and the regulation of gene-edited crops in different countries around the world. Full article

Zinc (Zn) deficiency poses a major global health challenge, and wheat grains generally contain low Zn concentrations. In this study, the wheat cultivar ‘Zhongmai 175’ was identified as zinc-efficient. Hydroponic experiments demonstrated that Zn deficiency induced the secretion of oxalic acid and malic acid in root exudates and significantly increased total root length in ‘Zhongmai 175’. To elucidate the underlying regulatory mechanisms, transcriptome profiling via RNA sequencing was conducted under Zn-deficient conditions. A total of 2287 and 1935 differentially expressed genes (DEGs) were identified in roots and shoots, respectively. Gene Ontology enrichment analysis revealed that these DEGs were primarily associated with Zn ion transport, homeostasis, transmembrane transport, and hormone signaling. Key DEGs belonged to gene families including VIT, NAS, DMAS, ZIP, tDT, HMA, and NAAT. KEGG pathway analysis indicated that phenylpropanoid biosynthesis, particularly lignin synthesis genes, was significantly downregulated in Zn-deficient roots. In shoots, cysteine and methionine metabolism, along with plant hormone signal transduction, were the most enriched pathways. Notably, most DEGs in shoots were associated with the biosynthesis of phytosiderophores (MAs, NA) and ethylene. Overall, genes involved in Zn ion transport, phytosiderophore biosynthesis, dicarboxylate transport, and ethylene biosynthesis appear to play central roles in wheat’s adaptive response to Zn deficiency. These findings provide a valuable foundation for understanding the molecular basis of Zn efficiency in wheat and for breeding Zn-enriched varieties. Full article

Excavating new salt tolerance genes and utilizing them to improve salt-tolerant wheat varieties is an effective way to utilize salinized soil. The NAC gene family plays an important role in plant response to salt stress. In this study, 446 NAC sequences were isolated from the whole genome of common wheat and classified into 118 members based on subgenome homology, named TaNAC1 to TaNAC118. Transcriptome analysis of salt-tolerant wheat breeding line CH7034 roots revealed that 144 of the 446 TaNAC genes showed significant changes in expression levels at least two time points after NaCl treatment. These differentially expressed TaNACs were divided into four groups, and Group 4, containing the largest number of 78 genes, exhibited a successive upregulation trend after salt treatment. Single nucleotide polymorphisms (SNPs) of the TaNAC gene family in 114 wheat germplasms were retrieved from the public database and were subjected to further association analysis with the relative salt-injury rates (RSIRs) of six root phenotypes, and then 20 SNPs distributed on chromosomes 1B, 2B, 2D, 3B, 3D, 5B, 5D, and 7A were correlated with phenotypes involving salt tolerance (p < 0.0001). Combining the results of RT-qPCR and association analysis, we further selected three NAC genes from Group 4 as candidate genes that related to salt tolerance, including TaNAC26-D3.2, TaNAC33-B, and TaNAC40-B. Compared with the wild type, the roots of the tanac26-d3.2 mutant showed shorter length, less volume, and reduced biomass after being subjected to salt stress. Four SNPs of TaNAC26-D3.2 formed two haplotypes, Hap1 and Hap2, and germplasms with Hap2 exhibited better salt tolerance. Snp3, in exon 3 of TaNAC26-D3.2, causing a synonymous mutation, was developed into a Kompetitive Allele-Specific PCR marker, K3, to distinguish the two haplotypes, which can be further used for wheat germplasm screening or marker-assisted breeding. This study provides new genes and molecular markers for improvement of salt tolerance in wheat. Full article

Chlorophyll plays a vital role in wheat growth and fertilization management. Accurate and efficient estimation of chlorophyll content is crucial for providing a scientific foundation for precision agricultural management. Unmanned aerial vehicles (UAVs), characterized by high flexibility, spatial resolution, and operational efficiency, have emerged as effective tools for estimating chlorophyll content in wheat. Although multi-source data derived from UAV-based multispectral imagery have shown potential for wheat chlorophyll estimation, the importance of multi-source deep feature fusion has not been adequately addressed. Therefore, this study aims to estimate wheat chlorophyll content by integrating spectral and textural features extracted from UAV multispectral imagery, in conjunction with partial least squares regression (PLSR), random forest regression (RFR), deep neural network (DNN), and a novel multi-source deep feature neural network (MDFNN) proposed in this research. The results demonstrate the following: (1) Except for the RFR model, models based on texture features exhibit superior accuracy compared to those based on spectral features. Furthermore, the estimation accuracy achieved by fusing spectral and texture features is significantly greater than that obtained using a single type of data. (2) The MDFNN proposed in this study outperformed other models in chlorophyll content estimation, with an R² of 0.850, an RMSE of 5.602, and an RRMSE of 15.76%. Compared to the second-best model, the DNN (R² = 0.799, RMSE = 6.479, RRMSE = 18.23%), the MDFNN achieved a 6.4% increase in R², and 13.5% reductions in both RMSE and RRMSE. (3) The MDFNN exhibited strong robustness and adaptability across varying years, wheat varieties, and nitrogen application levels. The findings of this study offer important insights into UAV-based remote sensing applications for estimating wheat chlorophyll under field conditions. Full article

Understanding future changes in crop phenology and climate suitability is essential for sustaining winter wheat production in the Huang-Huai-Hai (3H) Plain under climate change. This study integrates bias-corrected CMIP6 climate projections, the DSSAT CERES-Wheat crop model, and Random Forest analysis to assess spatiotemporal shifts in winter wheat phenology and climate suitability. The assessment focuses on the mid- (2041–2060) and late 21st century (2081–2100) under the SSP2-4.5 and SSP5-8.5 scenarios. The results indicate that the vegetative and whole growing periods (VGP and WGP) will be extended in the mid-century but shorten by the late century. In contrast, the reproductive growing period (RGP) will be slightly reduced in the mid-century and extended under high emissions in the late century. Temperature suitability is projected to increase during the VGP and WGP but decline during the RGP. Precipitation suitability generally improves, except for a decrease during the reproductive period south of 32° N. Solar radiation suitability is expected to decline across all stages. Temperature is identified as the primary driver of phenological changes, with solar radiation and precipitation playing increasingly important roles in the mid- and late 21st century, respectively. Adaptive strategies, including the adoption of heat-tolerant varieties, longer reproductive periods, and earlier sowing, are recommended to enhance yield stability under future climate conditions. Full article

Accurately estimating leaves’ relative chlorophyll contents (widely represented by Soil and Plant Analysis Development (SPAD) values) across growth stages is crucial for assessing crop health, particularly in regions characterized by varying sowing dates. Unlike previous studies focusing on high-resolution UAV imagery or specific growth stages, this research incorporates satellite-derived texture indices (TIs) into a SPAD value estimation model applicable across multiple growth stages (from tillering to grain-filling). Field experiments were conducted in Jiangsu Province, China, where winter wheat sowing dates varied significantly from field to field. Sentinel-2 imagery was employed to extract vegetation indices (VIs) and TIs. Following a two-step variable selection method, Random Forest (RF)-LassoCV, five machine learning algorithms were applied to develop estimation models. The newly developed model (SVR-RBF_VIs+TIs) exhibited robust estimation performance (R² = 0.8131, RMSE = 3.2333, RRMSE = 0.0710, and RPD = 2.3424) when validated against independent SPAD value datasets collected from fields with varying sowing dates. Moreover, this optimal model also exhibited a notable level of transferability at another location with different sowing times, wheat varieties, and soil types from the modeling area. In addition, this research revealed that despite the lower resolution of satellite imagery compared to UAV imagery, the incorporation of TIs significantly improved estimation accuracies compared to the sole use of VIs typical in previous studies. Full article

False cleavers (Galium spurium L.) is a broadleaf weed species that affects wheat productivity because of its strong competition for resources. It has developed resistance to acetolactate synthase (ALS) inhibitors, such as sulfonylureas and triazolopyrimidines, which are herbicides widely used in durum wheat. Integrated weed management programs can contribute to the control of this species and delay the evolution of herbicide resistance. Thus, a two-year field experiment was conducted to evaluate the effects of sowing time, variety, and herbicides on crop yield, density, and dry weight of a false cleavers population with resistance to ALS inhibitors. In both growing seasons, a split-split-plot design was used with three replicates. The sowing date was chosen as the main plot factor, durum wheat varieties as the subplot factor, and herbicides as the sub-subplot factor. The herbicide treatments were: (1) metsulfuron-methyl/bensulfuron-methyl (4/50 g a.i. ha⁻¹), (2) aminopyralid/florasulam (9.9/4.95 g a.i. ha⁻¹), (3) pyroxsulam and florasulam/2,4-D (18.75 + 4.725/225 g a.i. ha⁻¹), (4) 2,4-D/bromoxynil (633.15/601.2 g a.i. ha⁻¹), non-treated control, and hand-weeded control for the first season, while in the second season one more herbicide treatment (halauxifen-methyl/florasulam, 5.6/5.15 g a.i. ha⁻¹) was added. Herbicide application was performed on 10 March 2021 and 28 March 2022, when the crop was at the end of tillering and the beginning of stem elongation. The results showed that the density of false cleavers was not affected by the variety or sowing time. However, its dry weight was 17.3–23.4% higher in early sowing (16 November in 2020 and 8 November 2021) than in late sowing (24 December 2020 and 2 December 2021). Among the herbicides tested, 2,4-D/bromoxynil and halauxifen-methyl/florasulam effectively controlled false cleavers, showing greater efficacy in late sowing (>88%), which ultimately led to a higher yield. In conclusion, our two-year findings demonstrate that delayed sowing as part of an integrated weed management strategy can contribute to controlling resistant populations of false cleavers to ALS-inhibiting herbicides without affecting the quantity and quality of durum wheat yield in areas with a Mediterranean climate. Full article

Auxin (IAA), a key natural signaling molecule, plays a pivotal role in regulating plant growth, development, and stress responses. Understanding its signal transduction mechanisms is crucial for improving crop yields. In this study, we conducted a comparative transcriptome analysis of wheat leaf and root tissues treated with different concentrations of IAA (0, 1, and 50 μM). Functional enrichment analysis revealed that differentially expressed genes (DEGs) exhibited tissue-specific regulatory patterns in response to auxin. Weighted Gene Co-expression Network Analysis (WGCNA) identified receptor-like kinase genes within the MEgreen module as highly correlated with auxin response, suggesting their involvement in both root and leaf regulation. Among them, TaPBL7-2B, a receptor-like kinase gene significantly upregulated under 50 μM IAA treatment, was selected for functional validation. Ectopic overexpression of TaPBL7-2B in Arabidopsis thaliana (Col-0) enhanced auxin sensitivity and inhibited plant growth by suppressing root development and leaf expansion. In contrast, knockout of the Arabidopsis homolog AtPBL7 reduced auxin sensitivity and promoted both root and leaf growth. Transcriptome analysis of Col-0, the TaPBL7-2B overexpression line, and the pbl7 mutant indicated that TaPBL7-2B primarily functions through the MAPK signaling pathway and plant hormone signal transduction pathway. Furthermore, qRT-PCR analysis of wheat varieties with differing auxin sensitivities confirmed a positive correlation between TaPBL7-2B expression and auxin response. In conclusion, TaPBL7-2B acts as a negative regulator of plant growth, affecting root development and leaf expansion in both Arabidopsis and wheat. These findings enhance our understanding of auxin signaling and provide new insights for optimizing crop architecture and productivity. Full article

Late sowing and spring low temperatures have a great impact on the growth and maturation of wheat in the rice–wheat rotation region. In order to analyze the impacts of cold stress in February in early spring on yield formation and agronomic traits of wheat on different sowing dates, a controlled pot experiment was performed using the widely promoted and applied spring-type wheat variety Yangmai23 (YM23). The yield of wheat treated with late sowing date II (SDII, 21 November) and overly late sowing date III (SDIII, 9 December) were both lower than that of wheat sown on the suitable date I (SDI, 1 November). The yield of late-sown wheat decreased by 40.82% for SDII and by 66.77% for SDIII, compared with SDI, and these three treatments of wheat all grew under the natural conditions as the control treatments. The plant height, stem diameter of the internode below the ear, flag leaf length and area, and total awn length of the spike, as well as the spike length of late-sown wheat, were all significantly lower than those of wheat in SDI treatment. Early spring low temperatures exacerbated the decline in yield of wheat sown on different dates, to some extent. Despite showing higher net photosynthetic rate, stomatal conductance, and transpiration rate in flag leaves of the SDIII treatment under low-temperature stress than those of the other treatments at anthesis, overly late sowing led to minimal leaf area, shorter plant height, fewer tillers, and smaller ears, ultimately resulting in the lowest yield. Our study suggested that additional focus and some regulation techniques are needed to be studied further to mitigate the combined negative impacts of late sowing and low-temperature stress in early spring on wheat production. Full article

Azospirillum is a well-studied genus of plant growth-promoting rhizobacteria (PGPR) and one of the most extensively researched diazotrophs. This genus can colonize rhizosphere soil and enhance plant growth and productivity by supplying essential nutrients to the host. Azospirillum–plant interactions involve multiple mechanisms, including nitrogen fixation, the production of phytohormones (auxins, cytokinins, indole acetic acid (IAA), and gibberellins), plant growth regulators, siderophore production, phosphate solubilization, and the synthesis of various bioactive molecules, such as flavonoids, hydrogen cyanide (HCN), and catalase. Thus, Azospirillum is involved in plant growth and development. The genus Azospirillum also enhances membrane activity by modifying the composition of membrane phospholipids and fatty acids, thereby ensuring membrane fluidity under water deficiency. It promotes the development of adventitious root systems, increases mineral and water uptake, mitigates environmental stressors (both biotic and abiotic), and exhibits antipathogenic activity. Biological nitrogen fixation (BNF) is the primary mechanism of Azospirillum, which is governed by structural nif genes present in all diazotrophic species. Globally, Azospirillum spp. are widely used as inoculants for commercial crop production. It is considered a non-pathogenic bacterium that can be utilized as a biofertilizer for a variety of crops, particularly cereals and grasses such as rice and wheat, which are economically significant for agriculture. Furthermore, Azospirillum spp. influence gene expression pathways in plants, enhancing their resistance to biotic and abiotic stressors. Advances in genomics and transcriptomics have provided new insights into plant-microbe interactions. This review explored the molecular mechanisms underlying the role of Azospirillum spp. in plant growth. Additionally, BNF phytohormone synthesis, root architecture modification for nutrient uptake and stress tolerance, and immobilization for enhanced crop production are also important. A deeper understanding of the molecular basis of Azospirillum in biofertilizer and biostimulant development, as well as genetically engineered and immobilized strains for improved phosphate solubilization and nitrogen fixation, will contribute to sustainable agricultural practices and help to meet global food security demands. Full article

Accurate and timely wheat yield prediction is valuable globally for enhancing agricultural planning, optimizing resource use, and supporting trade strategies. Study addresses the need for precision in yield estimation by applying machine-learning (ML) regression models to high-resolution Unmanned Aerial Vehicle (UAV) multispectral (MS) and Red-Green-Blue (RGB) imagery. Research analyzes five European wheat cultivars across 400 experimental plots created by combining 20 nitrogen, phosphorus, and potassium (NPK) fertilizer treatments. Yield variations from 1.41 to 6.42 t/ha strengthen model robustness with diverse data. The ML approach is automated using PyCaret, which optimized and evaluated 25 regression models based on 65 vegetation indices and yield data, resulting in 66 feature variables across 400 observations. The dataset, split into training (70%) and testing sets (30%), was used to predict yields at three growth stages: 9 May, 20 May, and 6 June 2022. Key models achieved high accuracy, with the Support Vector Regression (SVR) model reaching R² = 0.95 on 9 May and R² = 0.91 on 6 June, and the Multi-Layer Perceptron (MLP) Regressor attaining R² = 0.94 on 20 May. The findings underscore the effectiveness of precisely measured MS indices and a rigorous experimental approach in achieving high-accuracy yield predictions. This study demonstrates how a precise experimental setup, large-scale field data, and AutoML can harness UAV and machine learning’s potential to enhance wheat yield predictions. The main limitations of this study lie in its focus on experimental fields under specific conditions; future research could explore adaptability to diverse environments and wheat varieties for broader applicability. Full article

Climate change resulting from human development necessitates increased land use, food, and energy consumption, underscoring the need for sustainable development. Incorporating various feedstocks into value-added liquid fuels and bioproducts is essential for achieving sustainability. Most biomass consists of cell walls, which serve as a primary carbon source for bioenergy and biorefinery processes. This structure contains a cellulose core, where lignin and hemicelluloses are crosslinked and embedded in a pectin matrix, forming diverse polysaccharide architectures across different species and tissues. Nineteen agro-industrial waste products were analyzed for their potential use in a circular economy. The analysis included cell wall composition, saccharification, and calorific potential. Thermal capacity and degradation were similar among the evaluated wastes. The feedstocks of corn cob, corn straw, soybean husk, and industry paper residue exhibited a higher saccharification capacity despite having lower lignin and uronic acid contents, with cell walls comprising 30% glucose and 60% xylose. Therefore, corn, soybeans, industrial paper residue, and sugarcane are more promising for bioethanol production. Additionally, duckweed, barley, sorghum, wheat, rice, bean, and coffee residues could serve as feedstocks for other by-products in green chemistry, generating valuable products. Our findings show that agro-industrial residues display a variety of polymers that are functional for various applications in different industry sectors. Full article