Search Results (669)

Soybean (Glycine max (L.) Merrill) is a major oilseed crop rich in phytosterols and tocopherols, compounds associated with functional and nutritional properties of vegetable oils. This study aimed to apply, for the first time, Independent Component Analysis (ICA) to discriminate the composition of phytosterols (β-sitosterol, campesterol, stigmasterol) and tocopherols (α, β, γ, δ) in 20 soybean genotypes—14 non-transgenic and six transgenic—cultivated in two major producing regions of Paraná state, Brazil (Londrina and Ponta Grossa). Lipophilic compounds were extracted from soybean seeds, quantified via gas chromatography and HPLC, and statistically analyzed using ICA with the JADE algorithm. The extracted independent components successfully differentiated soybean varieties based on phytochemical profiles. Notably, transgenic cultivars from Ponta Grossa exhibited higher levels of total tocopherols, including α- and β-tocopherol, while conventional cultivars from both regions showed elevated phytosterol content, particularly campesterol and stigmasterol. ICA proved to be a powerful unsupervised method for visualizing patterns in complex compositional data. These findings highlight the significant influence of genotype and growing region on the nutraceutical potential of soybean, and support the use of multivariate analysis as a strategic tool for cultivar selection aimed at enhancing functional quality in food applications. Full article

Sunflower (Helianthus annuus L.) is an important oilseed crop in Northwest China, exhibiting resistance to salt and drought. Mining its excellent tolerance genes can be used for breeding. However, the current platforms for identifying gene function in sunflower is inadequate. The transient transformation system, which can rapidly validate gene function, shows promising prospects in research. In this study, we established an efficient transient expression transformation system for sunflower using three methods: Agrobacterium-mediated infiltration, injection, and ultrasonic-vacuum. The detailed procedures were as follows: Agrobacterium GV3101 carrying a GUS reporter gene on the pBI121 vector with an OD₆₀₀ of 0.8 as the bacterial suspension and 0.02% Silwet L-77 as the surfactant were utilized in all three approaches. For the infiltration method, seedlings grown hydroponically for 3 days were immersed in a bacterial suspension containing 0.02% Silwet L-77 for 2 h; for the injection method, the same solution was injected into the cotyledons of seedlings grown in soil for 4 to 6 days. Subsequently, the seedlings were cultured in the dark at room temperature for three days; for the ultrasonic-vacuum method, seedlings cultured in Petri dishes for 3 days were first subjected to ultrasonication at 40 kHz for 1 min, followed by vacuum infiltration at 0.05 kPa for 5–10 min. Agrobacterium-mediated transient transformation efficiency achieved by the three methods exceeded 90%, with gene expression being sustained for at least 6 days. Next, we employed the infiltration-based sunflower transient transformation technology with the Arabidopsis stable transformation platform to confirm salt and drought stress tolerance of candidate gene HaNAC76 from sunflower responding to various abiotic stresses. Altogether, this study successfully established an Agrobacterium-mediated transient transformation system for sunflower using these three methods, which can rapidly identify gene function and explore the molecular mechanisms underlying sunflower’s resistance traits. Full article

Agricultural nondestructive testing technology is pivotal in safeguarding food quality assurance, safety monitoring, and supply chain transparency. While conventional optical methods such as near-infrared spectroscopy and hyperspectral imaging demonstrate proficiency in surface composition analysis, their constrained penetration depth and environmental sensitivity limit effectiveness in dynamic agricultural inspections. This review highlights the transformative potential of microwave technologies, systematically examining their operational principles, current implementations, and developmental trajectories for agricultural quality control. Microwave technology leverages dielectric response mechanisms to overcome traditional limitations, such as low-frequency penetration for grain silo moisture testing and high-frequency multi-parameter analysis, enabling simultaneous detection of moisture gradients, density variations, and foreign contaminants. Established applications span moisture quantification in cereal grains, oilseed crops, and plant tissues, while emerging implementations address storage condition monitoring, mycotoxin detection, and adulteration screening. The high-frequency branch of the microwave–millimeter wave systems enhances analytical precision through molecular resonance effects and sub-millimeter spatial resolution, achieving trace-level contaminant identification. Current challenges focus on three areas: excessive absorption of low-frequency microwaves by high-moisture agricultural products, significant path loss of microwave high-frequency signals in complex environments, and the lack of a standardized dielectric database. In the future, it is essential to develop low-cost, highly sensitive, and portable systems based on solid-state microelectronics and metamaterials, and to utilize IoT and 6G communications to enable dynamic monitoring. This review not only consolidates the state-of-the-art but also identifies future innovation pathways, providing a roadmap for scalable deployment of next-generation agricultural NDT systems. Full article

Vegetable oils are essential for human nutrition and industrial applications. With growing global demand, increasing oil content in oilseed crops has become a top priority. This review synthesizes recent progress in understanding the genetic, environmental, and molecular mechanisms regulating oil content, and presents biotechnological strategies to enhance oil accumulation in major oilseed crops. Oil biosynthesis is governed by intricate genetic–environmental interactions. Environmental factors and agronomic practices significantly impact oil accumulation dynamics. Quantitative trait loci (QTL) mapping and genome-wide association studies (GWAS) have identified key loci and candidate genes involved in lipid biosynthesis pathways. Transcription factors and epigenetic regulators further fine-tune oil accumulation. Biotechnological approaches, including marker-assisted selection (MAS) and CRISPR/Cas9-mediated genome editing, have successfully generated high-oil-content variants. Future research should integrate multi-omics data, leverage AI-based predictive breeding, and apply precision genome editing to optimize oil yield while maintaining seed quality. This review provides critical references for the genetic improvement and breeding of high- and ultra-high-oil-content varieties in oilseed crops. Full article

Soil organic carbon (SOC) mineralization plays the critical role of regulating carbon sequestration potential. This process is strongly influenced by agricultural practices, particularly tillage regimes and straw management. However, the complex interactions between tillage methods, straw types, and application rates in terms of SOC dynamics, especially in semi-arid agroecosystems like eastern Inner Mongolia, remain poorly understood. In this study, we assessed the combined effects of no tillage (NT) vs. rotary tillage (RT), three straw types (maize/MS, wheat/WS, and oilseed rape/OS), and three application rates (0.4%/low, 0.8%/medium, and 1.2%/high) on SOC concentration and mineralization using controlled laboratory incubation with soils from long-term plots. The key findings revealed that NT significantly increased the SOC concentration in the topsoil (0–20 cm) by an average of 14.5% compared to that in the RT. Notably, combining NT with medium-rate wheat straw (0.8%) resulted in the achievement of the highest SOC accumulation (28.70 g/kg). SOC mineralization increased with straw inputs, exhibiting significant straw type × rate interactions. Oilseed rape straw showed the highest specific mineralization rate (33.9%) at low input, while maize straw mineralized fastest under high input with RT. Therefore, our results demonstrate that combining NT with either 0.8% wheat straw or 1.2% maize straw represents an optimal application strategy, as the SOC concentration is enhanced by 12–18% for effective carbon sequestration in this water-limited semi-arid region. Therefore, optimizing SOC sequestration requires the integration of appropriate crop residue application rates and tillage methods tailored to different cropping systems. Full article

During a prolonged domestication and environmental selection, Brassica rapa has formed diverse morphological types during a cultivation process of up to 8000 years, such as root-type turnips (Brassica rapa var. rapa), leaf-type Chinese cabbage (Brassica rapa var. pekinensis), oil-type rapeseed (Brassica rapa L.), and other rich types. China is one of the origins of Brassica rapa L., which is spread all over the east, west, south, and north of China. Studying its origin and evolution holds significant importance for unraveling the cultivation history of Chinese oilseed crops, intraspecific evolutionary relationships, and the utilization value of genetic resources. This article summarizes the cultivation history, evolution, classification research progress, and germplasm resource diversity of Brassica rapa var. oleifera in China. Combining karyotype analysis, genomic information, and wild relatives of Brassica rapa var. oleifera discovered on the Qinghai–Tibet Plateau, it is proposed that Brassica rapa var. oleifera has the characteristic of polycentric origin, and Gansu Province in China is one of the earliest regions for its cultivation. Brassica rapa var. oleifera, originating from the Mediterranean region, was diffused to the East Asian continent through two independent transmission paths (one via the Turkish Plateau and the other via Central Asia and Siberia). Analyzing the genetic diversity characteristics and evolutionary trajectories of these two transmission paths lays a foundation for clarifying the origin and evolutionary process of Brassica rapa var. oleifera and accelerating the breeding of Brassica rapa var. oleifera in China. Despite existing research on the origin of Brassica rapa L., the domestication process of this species remains unresolved. Future studies will employ whole-genome resequencing to address this fundamental question. Full article

Peanut (Arachis hypogaea L.) is a globally important oilseed cash crop, yet its limited genetic diversity and unique reproductive biology present persistent challenges for conventional crossbreeding. Traditional breeding approaches are often time-consuming and inadequate, mitigating the pace of cultivar development. Essential for double fertilization and programmed cell death (PCD), DUF679 membrane proteins (DMPs) represent a membrane protein family unique to plants. In the present study, a comprehensive analysis of the DMP gene family in peanuts was conducted, which included the identification of 21 family members. Based on phylogenetic analysis, these genes were segregated into five distinct clades (I–V), with AhDMP8A, AhDMP8B, AhDMP9A, and AhDMP9B in clade IV exhibiting high homology with known haploid induction genes. These four candidates also displayed significantly elevated expression in floral tissues compared to other organs, supporting their candidacy for haploid induction in peanuts. Subcellular localization prediction, confirmed through co-localization assays, demonstrated that AhDMPs primarily localize to the plasma membrane, consistent with their proposed roles in the reproductive signaling process. Furthermore, chromosomal mapping and synteny analyses revealed that the expansion of the AhDMP gene family is largely driven by whole-genome duplication (WGD) and segmental duplication events, reflecting the evolutionary dynamics of the tetraploid peanut genome. Collectively, these findings establish a foundational understanding of the AhDMP gene family and highlight promising targets for future applications in haploid induction-based breeding strategies in peanuts. Full article

Camelina sativa (CS) is an emerging sustainable oilseed crop with interesting feed application potentialities. The research assessed the potentiality of Camelina sativa (CS) in the diet for free-range laying hens, aiming at reaching a nutritional claim. To this purpose, two feeding groups of hens (n = 100 Livorno hens, n = 25 hens/pen) were farmed outdoor and received either a Control diet, which was a commercial diet for laying hens, or a CS diet. The latter was formulated to include the 5% CS cake and 1% CS oil, replacing conventional feedstuffs. Diets were isoprotein and isoenergy and were available ad libitum throughout the laying period (February–September). At day 1, n = 12 eggs/diet were sampled to assess the initial proximate composition and FA profile. Every 7 days the sampling was repeated to analyze the eggs’ FA profile, up to day 35. At the end of the laying season, n = 6 hens/dietary treatment were slaughtered and subjected to meat quality evaluations. Results highlighted that a 28-day feeding was the period required to obtain 227 mg of C18:3 n-3 and 81 mg of C20:5 n-3 + C22:6 n-3/100 g egg, whereas a further 7 days of feeding trial were ineffective in further enhancing the omega-3 FA content of eggs. CS eggs were comparable to Control ones for overall physical traits, proximate composition, and shelf-life. In addition, at the end of the laying period, the meat of CS hens was also found to be healthier than that of Control ones, thanks to a higher omega-3 FA proportion (p < 0.01), which was, however, not sufficient to reach any nutritional claim. Instead, the proximate composition of CS meat was overall comparable to Control hens. In conclusion, the present research demonstrated that feeding Camelina sativa meal and oil to laying hens is feasible and allows to reach the nutritional claim in eggs “rich in omega-3 FA” after a feeding period of 28 days, without any negative effects on other eggs’ quality trials. Camelina sativa can thus be defined as a promising sustainable feedstuff for the poultry sector for diversification purposes and to enhance the nutritional quality of eggs. Full article

Sclerotinia sclerotiorum (S. sclerotiorum), a necrotrophic phytopathogen, causes sclerotinia stem rot (SSR) in many crops like oilseed rape, resulting in severe economic losses. Developing eco-friendly compound fungicides has become a critical research priority. This study explored the combination of sodium selenite and cuminic acid to screen for the optimal mixing ratio and investigate its inhibitory effects and mechanisms against S. sclerotiorum. The results demonstrated that synergistic effects were observed with a 1:3 combination ratio of sodium selenite to cuminic acid. After treatment with the selenium compound agent, ultrastructural observations revealed that the hyphae of S. sclerotiorum became severely shriveled, deformed, and twisted. The agent significantly reduced oxalic acid production and the activities of polymethylgalacturonide (PMG) and carboxymethylcellulose enzymes (Cx), while increasing the exocytosis of nucleic acids and proteins from the mycelium. Foliar application of the selenium compound agent significantly reduced lesion areas in rapeseed. Combined with the results of transcriptome sequencing, this study suggests that the compound agent effectively inhibits the growth of S. sclerotiorum by disrupting its membrane system, reducing the activity of cell wall-degrading enzymes, and suppressing protein synthesis, etc. This research provides a foundation for developing environmentally friendly and effective fungicides to control S. sclerotiorum. Full article

In recent years, heavy metal contamination in agricultural products has become a growing concern in the field of food safety. Copper (Cu) stress in crops not only leads to significant reductions in both yield and quality but also poses potential health risks to humans. This study proposes an efficient and precise non-destructive detection method for Cu stress in oilseed rape, which is based on hyperspectral false-color image construction using principal component analysis (PCA). By comprehensively capturing the spectral representation of oilseed rape plants, both the one-dimensional (1D) spectral sequence and spatial image data were utilized for multi-class classification. The classification performance of models based on 1D spectral sequences was compared from two perspectives: first, between machine learning and deep learning methods (best accuracy: 93.49% vs. 96.69%); and second, between shallow and deep convolutional neural networks (CNNs) (best accuracy: 95.15% vs. 96.69%). For spatial image data, deep residual networks were employed to evaluate the effectiveness of visible-light and false-color images. The RegNet architecture was chosen for its flexible parameterization and proven effectiveness in extracting multi-scale features from hyperspectral false-color images. This flexibility enabled RegNetX-6.4GF to achieve optimal performance on the dataset constructed from three types of false-color images, with the model reaching a Macro-Precision, Macro-Recall, Macro-F₁, and Accuracy of 98.17%, 98.15%, 98.15%, and 98.15%, respectively. Furthermore, Grad-CAM visualizations revealed that latent physiological changes in plants under heavy metal stress guided feature learning within CNNs, and demonstrated the effectiveness of false-color image construction in extracting discriminative features. Overall, the proposed technique can be integrated into portable hyperspectral imaging devices, enabling real-time and non-destructive detection of heavy metal stress in modern agricultural practices. Full article

Soil salinization poses a critical threat to global agriculture, necessitating innovative strategies for sustainable remediation. This review synthesizes advances in leveraging plant–microbe interactions to remediate saline–alkali soils, focusing on oilseed crops—Brassica napus, Glycine max, Arachis hypogaea, Helianthus annuus, and Sesamum indicum—as keystone species for ecosystem restoration. These crops exhibit unique adaptive strategies, including root architectural plasticity and exudate-mediated recruitment of stress-resilient microbiomes (Proteobacteria, Actinobacteria, and Ascomycota), which collectively stabilize soil structure and enhance nutrient cycling, ion homeostasis, and soil aggregation to mitigate soil salinity and alkalinity. Emerging technologies further amplify these natural synergies: nanomaterials optimize nutrient delivery and microbial colonization, while artificial intelligence (AI) models predict optimal plant growth-promoting rhizobacteria (PGPR) combinations and simulate remediation outcomes. This integration establishes a roadmap for precision microbiome engineering, offering scalable strategies to restore soil health and ensure food security in saline–alkali ecosystems. Full article

Sunflower is one of the four most important oilseed crops in the world, and its edible oil is of high nutritional quality. However, the molecular regulatory mechanism of oil accumulation in sunflowers is still unclear. In this study, we selected two inbred lines with significant differences in oleic acid content and similar agronomic traits: the high oleic acid content (82.5%) inbred line 227 and the low oleic acid content (30.8%) inbred line 228. Sunflower seeds were selected for transcriptome experiments at 10, 20, and 30 days after full bloom (DAFB). There were 21, 225, and 632 differentially expressed genes (DEGs) identified at the three times, respectively. The Gene Ontology (GO) analysis showed that DEGs from two sunflower cultivars at three stages were significantly enriched in the activities of omega-6 fatty acid desaturase and glucosyltransferase. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that at 10, 20, and 30 DAFB, DEGs were significantly enriched in the unsaturated fatty acid synthesis pathway, glutathione metabolism pathway, and pyruvate metabolism pathway. Through mapping analysis of GO in the KEGG pathway, it was found that the omega-6 fatty acid desaturase gene FAD6/FAD2, diacylglyceroyltransferase gene DGAT, glycerol-3-phosphate acyltransferase gene GPAT, and long-chain acyl-CoA synthase gene LACS may play important roles in regulating sunflower oleic acid content. Our research provides candidate genes and a research basis for breeding high oleic sunflowers. Full article

Accurate identification of non-food crops underpins food security by clarifying land-use dynamics, promoting sustainable farming, and guiding efficient resource allocation. Proper identification and management maintain the balance between food and non-food cropping, a prerequisite for ecological sustainability and a healthy agricultural economy. Distinguishing large-scale non-food crops—such as oilseed rape, tea, and cotton—remains challenging because their canopy reflectance spectra are similar. This study proposes a novel phenology-aware Vision Transformer Model (PVM) for accurate, large-scale non-food crop classification. PVM incorporates a Phenology-Aware Module (PAM) that fuses multi-source remote-sensing time series with crop-growth calendars. The study area is Hunan Province, China. We collected Sentinel-1 SAR and Sentinel-2 optical imagery (2021–2022) and corresponding ground-truth samples of non-food crops. The model uses a Vision Transformer (ViT) backbone integrated with PAM. PAM dynamically adjusts temporal attention using encoded phenological cues, enabling the network to focus on key growth stages. A parallel Multi-Task Attention Fusion (MTAF) mechanism adaptively combines Sentinel-1 and Sentinel-2 time-series data. The fusion exploits sensor complementarity and mitigates cloud-induced data gaps. The fused spatiotemporal features feed a Transformer-based decoder that performs multi-class semantic segmentation. On the Hunan dataset, PVM achieved an F1-score of 74.84% and an IoU of 61.38%, outperforming MTAF-TST and 2D-U-Net + CLSTM baselines. Cross-regional validation on the Canadian Cropland Dataset confirmed the model’s generalizability, with an F1-score of 71.93% and an IoU of 55.94%. Ablation experiments verified the contribution of each module. Adding PAM raised IoU by 8.3%, whereas including MTAF improved recall by 8.91%. Overall, PVM effectively integrates phenological knowledge with multi-source imagery, delivering accurate and scalable non-food crop classification. Full article

Plant diseases caused by Rhizoctonia solani present a significant challenge in agriculture. While chemical pesticides remain a common control strategy, their use leads to health and environmental problems. In contrast, endophytic bacteria with plant growth-promoting (PGP) activity offer a promising, sustainable alternative. In this context, a novel endophytic Priestia megaterium strain, KW16, originated from the bluegrass (Poa pratensis L.), demonstrated distinct biocontrol potential against R. solani. in vitro assays showed that KW16 inhibited R. solani growth by up to 58%, primarily by releasing volatile compounds. In planta experiments further highlighted KW16′s ability to colonize oilseed rape internal tissues, significantly enhancing its growth and development. In the presence of the pathogen, KW16 abolished the negative impact of R. solani and promoted plant growth, increasing shoot and root biomass by 216% and 1737%, respectively, when compared to the plants grown in fungal-infested soil. Biochemical and genome analyses confirmed the strain’s metabolic versatility, resistance to biotic and abiotic factors, and a whole spectrum of PGP and biocontrol traits such as biofilm formation, production of phytohormones, and synthesis of lytic enzymes, siderophores, and volatiles, alongside its ability to survive in the presence of autochthonous soil microflora. These findings position KW16 as a potent biological alternative to synthetic fungicides, with significant potential for sustainable crop protection. Full article

Drought including both meteorological drought and water deficiency stress conditions is a major constraint on global agricultural productivity, particularly affecting Brassica species, which are vital oilseed and vegetable crops. As climate change intensifies, understanding plant responses to drought is crucial for improving drought resilience. Drought stress impacts Brassica crops at multiple levels, reducing germination rates, impairing physiological functions such as photosynthesis and water-use efficiency, and triggering oxidative stress due to the accumulation of reactive oxygen species. To counteract these effects, Brassica plants employ various adaptive mechanisms, including osmotic adjustment, antioxidant defense activation, and hormonal regulation. Recent research has explored molecular and physiological pathways involved in drought tolerance, revealing key physiological changes and biochemical markers that could be targeted for crop improvement. This review summarizes the latest findings on the physiological, biochemical, and molecular responses of Brassica crops to drought stress, with an emphasis on adaptive mechanisms and potential drought mitigation strategies. Additionally, future research directions are proposed, focusing on integrating molecular and agronomic approaches to enhance drought resilience in Brassica species. Full article