Search Results (1,016)

Wheat is a major staple crop, and storage mold growth poses a severe threat to grain safety and quality stability. Natural mold development in stored wheat exhibits subtle, localized, and highly heterogeneous characteristics. Existing unimodal methods and global fusion approaches generally suffer from insufficient local feature sensitivity, hindering fine-grained mold severity grading. To address this limitation, we propose a Mask-Guided Fine-Grained Fusion Network, a weakly supervised framework based on local RGB–HSI fusion. This framework employs a dynamic parallel A/B experimental design to construct time-matched proxy labels via weakly supervised learning. A standardized preprocessing pipeline including single-kernel extraction, foreground segmentation, and cross-modal registration is established to resolve RGB–HSI spatial misalignment, ensuring physical-level spatial consistency of multimodal features. The model incorporates a Foreground-Aware Spectral Recalibration (FASR) module to suppress background noise, a Mask-Guided Dilated Cross-modal Local Attention (MDCLA) mechanism to establish fine-grained local mappings between RGB visual phenotypes and hyperspectral responses, and a sample-level adaptive fusion strategy to dynamically weight features by modal reliability, enhancing representation of complex samples across all mold stages. Experiments show that the Mask-Guided Fine-Grained Fusion Network achieves 0.9689 classification accuracy, 0.9698 Macro-F1 score, and 0.0593 Mean Absolute Error (MAE), significantly outperforming state-of-the-art unimodal deep models and global attention fusion baselines. This work provides a proof-of-principle framework for fine-grained non-destructive mold risk assessment in stored wheat. Full article

Identifying superior salt-tolerant germplasm and resistance genes is crucial, as wheat (Triticum aestivum L.) seedlings are highly vulnerable to salt stress. Here, using an optimized 150 mM NaCl treatment, we screened 137 Chinese wheat accessions via an organ-specific method. Phenotyping analysis revealed extensive organ-specific divergence, with 48.91% of accessions displaying inconsistent performance between shoot and root length. We then performed comparative transcriptomics on three representative phenotypes at the seedling stage: Gaoyou 2018, representing the salt dual-sensitive group; Huapei 5, representing the salt dual-tolerant group; and Jimai 60, representing the divergent group with higher tolerance in shoots rather than in roots. Analysis of overlapping differentially expressed genes (DEGs) across all three accessions revealed a basal stress response—characterized by induced osmotic defense and suppressed primary growth—exemplifying a classical growth–defense trade-off. Genotype-specific DEG profiling demonstrated that the divergent Jimai 60 maintains its shoot advantage by reinforcing physical barriers and inhibiting apoptosis. Conversely, transcriptomic profiling implies that the systemically tolerant Huapei 5 maintains coordinated shoot and root tolerance at the seedling stage by strongly activating below-ground Na⁺ homeostasis (efflux and compartmentalization) while simultaneously down-regulating non-essential immune responses to optimize defense energy reallocation. Collectively, our findings provide novel insights into the organ-differentiated salt tolerance of wheat, offering well-characterized elite germplasm and compelling genetic targets for future molecular breeding. Full article

Soil salinity is a major constraint on global wheat productivity, yet the genetic and molecular determinants of root system architecture (RSA) adaptation under salt stress remain poorly characterized. We integrated a genome-wide association study (GWAS) of 566 wheat accessions with comparative RNA-seq transcriptomics to identify the genetic and transcriptional determinants of RSA adaptation under 200 mM NaCl. GWAS identified a candidate locus on chromosome 7B harboring TaIAO, which encodes a protein with predicted aldehyde oxidase-like activity consistent with a role in tryptophan-dependent auxin biosynthesis. Accessions carrying the favorable CC allele exhibited significantly greater root volume retention than those carrying the GG genotype (p < 0.001). Comparative RNA-seq revealed that the salt-tolerant Sarajevo 1 exhibited coordinated transcriptional repression of three distinct modules—cell wall expansion (TaExpansin), auxin redistribution (TaPIN-like), and stress-associated ROS defense (TaPOD1)—whereas the sensitive genotype CI 17260 aberrantly induced or incompletely repressed these modules under stress. ELISA-based IAA quantification, ROS imaging, and qRT-PCR analysis provided independent physiological and transcriptional support for these patterns. These findings support a two-tier adaptive model in which constitutive genetic variation at the TaIAO locus may contribute to a developmental baseline, coupled with coordinated stress-responsive transcriptional repression of energy-consuming modules, providing promising targets for marker-assisted breeding of salt-tolerant wheat. Full article

Modeling crop development under different agrotechnologies is important not only for assessing the factors that affect their yields but also because of the role of vegetation in regulation of the hydrology regime. For this reason, interest in the plant module in the semi-distributed hydrological model SWAT is increasing. The model has to be supplied with a lot of information for running and testing, which can be achieved with ground-based, statistical and satellite data. The aim of the study is to determine the accuracy of the SWAT model to predict crop development by using ground-based and satellite data for LAI in the case of a 5-year field experiment. Two staple crops in rotation were monitored—winter wheat and maize—under different erosion control technologies (up-and-down conventional tillage, conventional contour tillage, and minimum contour tillage with inclusion of cover crop before maize) on sloping terrain on moderately eroded Epicalcic Chernozem in the region of Ruse, north Bulgaria. The remote sensing data from the Copernicus Sentinel-2 mission were used for estimation of LAI of both crops and verified against ground-based data in two ways—via a custom LAI script available through the Sentinel Hub cloud platform and as input to a machine learning quantile regression forests (QRF) model. The calibrated satellite-derived LAI, ground-based soil moisture and yields data were used to calibrate several SWAT model parameters (EPCO, ESCO, CN2, LAImax, HU, HI) and assess the model performance regarding these variables. Although a good temporal fit of the SWAT-modeled LAI data with the satellite data was achieved, the accuracy of predicted LAI is moderately high only in the last two years of the rotation (R² = 60.4%). The accuracy of calibrated yields (R² = 55.5%) is acceptable in four of the years. On average for the period, the applied erosion control agrotechnologies did not cause significantly different yields, but they are 14% higher compared to the up-and-down conventional tillage. The most sensitive SWAT parameters accounting for this effect are EPCO and ESCO. Full article

Heat stress severely constrains wheat productivity, yet the mechanisms underlying thermotolerance remain incompletely understood. This study integrated physiological, biochemical, molecular, and ultrastructural analyses to characterize heat-stress responses in four bread wheat (Triticum aestivum L.) genotypes contrasting in heat tolerance. Membrane injury was assessed by membrane damage rate, lipid peroxidation by malondialdehyde accumulation, antioxidant defense by SOD, CAT, GPX, and BPX activities, and stress-responsive regulation by qRT-PCR analysis of DREB, HSP16.9, and SOD isoforms. HSP16.9 protein accumulation was further evaluated by Western blotting. Heat stress increased membrane damage and MDA accumulation in all genotypes; however, tolerant Murov 2 and Zirva 85 showed lower oxidative membrane injury than sensitive Aran and Gyzyl bugda. Thermotolerance was associated with stronger antioxidant activation, enhanced DREB and HSP16.9 induction, and more coordinated FeSOD and MnSOD expression. The HSP16.9 protein accumulated after heat treatment, supporting its role as a stress-responsive molecular chaperone. Separate correlation analyses of tolerant and sensitive genotypes revealed stronger coordination among transcriptional, chaperone-related, and antioxidant markers in tolerant genotypes, whereas sensitive genotypes showed a more fragmented response. Microscopy further showed better preservation of chloroplast, mitochondrial, and mesophyll organization in the tolerant genotype relative to the sensitive counterpart, indicating integrated cellular protection. Together, these responses define a coordinated tolerance strategy that may guide the selection of heat-resilient wheat genotypes. Full article

Mediterranean agricultural systems are highly vulnerable to increased climatic variability, which threatens soil water availability and the functionality of the soil carbon (C) cycle. Soil management practices strongly influence water dynamics and C-substrate quality, thus potentially affecting the temperature sensitivity of soil respiration. We evaluated the combined effects of tillage (traditional tillage, TT; reduced tillage, RT), fertilization (mineral, MF; addition of biosolid compost, BC), and rainfall inputs (ambient conditions, C; reduction of 30% rainfall inputs, EX) on soil water content (SWC) and storage (SWS), and in situ soil respiration (Resp) dynamics over three agricultural seasons in a Mediterranean legume–wheat rotation, using a factorial field experiment. We also evaluated how the sensitivity of soil respiration to temperature could be affected by tillage and fertilization types in a complementary laboratory experiment under controlled moisture and temperature conditions. RT was effective in improving SWS and mitigating surface desiccation, although this advantage was attenuated in wet years due to homogenization of moisture along the soil profile. Soil Resp was primarily controlled by SWC. BC stimulated soil respiration mainly during the first crop season, with a residual non-significant trend in the third season. This effect appeared constrained under dry periods, although no significant fertilization × rainfall exclusion interaction was detected. The diurnal cycle of Resp showed a clear decoupling from diurnal soil temperature. Crucially, the intrinsic thermal sensitivity of respiration (Q₁₀) remained stable across all tillage and fertilization treatments, suggesting that field variability is driven by water dynamics and crop phenology and not by microbial responses to changes in substrate availability. Our results confirmed the hierarchical role of climate on C-cycling processes. Full article

This study identified the fertility alteration characteristics and cytological mechanisms of the thermo-photo-sensitive genic male sterile (TPSGMS) wheat line K64S. The fertility-sensitive stage of K64S extends from pollen mother cell formation to the tetrad development stage, with critical fertility alteration thresholds of 14–14.5 °C for temperature and 9–9.5 h for daylength. Under low-temperature and short-day conditions, K64S exhibits complete male sterility, whereas it returns to fertility under high-temperature and long-day conditions. Cytological analysis shows that K64S undergoes normal meiosis and successfully forms normal uninucleate microspores. 4′,6-diamidino-2-phenylindole (DAPI) staining revealed the uninucleate microspores failed to form binucleate microspores, with abortion occurring during the late uninucleate stage. Transmission electron microscopy indicates the pollen abortion in sterile K64S arises primarily from premature tapetal degeneration (a form of programmed cell death, PCD), initiated at the pollen mother cell stage, which disrupts nutrient supply and leads to abnormal nuclear division during subsequent microspore development. These findings provide insights into the cytological mechanism of pollen abortion in TPSGMS wheat and may guide hybrid wheat breeding and application. Full article

High-temperature stress poses a major threat to wheat productivity across multiple developmental stages, including early seedling growth. Root system architecture (RSA) contributes to stress adaptation; however, its responses to high-temperature stress remain insufficiently characterized in genetically diverse wheat populations. In this study, RSA responses of representative genotypes from a Multiple Synthetic Derivative (MSD) wheat population were evaluated under control and high-air-temperature conditions using a time-resolved, two-dimensional phenotyping platform. High-air-temperature stress significantly affected most root traits, with traits associated with lateral root expansion, including the second-pair seminal root length, root system width, and convex hull area, being more responsive than vertical root traits. MSD417 and MSD034 maintained relatively higher root performance under high-temperature stress, whereas MSD392 showed pronounced sensitivity. In contrast, MSD054 exhibited relatively small changes in root traits but consistently low overall performance. Multivariate analyses and stress indices consistently differentiated tolerant, sensitive, and low-responsive genotypes. These findings highlight the importance of distinguishing active stress tolerance from passive stability and suggest that lateral-root-related traits may serve as useful targets for breeding heat-resilient wheat. Full article

Accurate estimation of crop yield from remote sensing remains challenging due to the crop-specific nature of yield drivers and the difficulty of interpreting spectral indicators across agronomic systems. While many studies prioritise predictive accuracy through complex models, fewer explicitly examine the stability and physiological relevance of individual spectral and phenological indicators under controlled analytical conditions. This study investigates yield–spectral relationships in wheat and cotton using a unified Sentinel-2 indicator framework applied across multiple growing seasons in a Mediterranean agricultural environment. A consistent set of spectral and thermal indicators was derived from two phenologically targeted Sentinel-2 acquisitions per season and analysed using correlation analysis, univariate regression, constrained multivariate modelling, and recurrence analysis within an identical workflow for both crops. Distinct crop-specific patterns were observed. Wheat yield was most strongly associated with water-sensitive and canopy-related indicators, with NDWI-based metrics reaching Pearson correlations up to r = 0.85 and multivariate models explaining a substantial proportion of yield variability (up to R² ≈ 0.70) under controlled analytical conditions. In contrast, cotton yield variability was dominated by thermal accumulation, with growing degree day indicators showing correlations up to |r| = 0.59 and multivariate performance reaching R² = 0.74. Recurrence analysis indicated consistent recurrence of these indicator families across analytical stages under the examined conditions. Overall, the results indicate that parsimonious, physiologically interpretable indicator combinations can account for a meaningful proportion of yield variability without reliance on highly complex or high-dimensional modelling approaches, supporting crop-aware indicator selection for precision agriculture applications. Full article

Lodging is a major agricultural hazard that can substantially reduce crop yields. Timely and accurate monitoring of winter wheat lodging is important for assessing potential yield losses, guiding field management, and mitigating further lodging damage. Recent advances in unmanned aerial vehicle (UAV) remote sensing and artificial intelligence have provided new opportunities for lodging assessment. In this study, a novel monitoring framework was proposed by integrating deep features extracted from UAV multi-spectral images with machine learning algorithms. Sensitivity analysis was conducted to identify vegetation indices (VIs), which are highly correlated with lodging. These sensitive VIs were combined with original multi-spectral bands, and YOLOv8, YOLO12, SAM1, and SAM2 were used for feature extraction. The SHAP method was applied to analyze feature importance and model interpretability. The results indicated that VARI, EXG, and MCARI were the most effective VIs for lodging monitoring. Furthermore, three feature representations, including a spectral feature set, deep features, and fused features, were evaluated. The highest accuracy was achieved using YOLO12 deep features combined with a BP classifier, reaching an accuracy of 98.20%, a precision of 98.38%, a recall of 98.56%, and an F1-score of 98.56%. Overall, incorporating deep features significantly improved monitoring performance. The proposed framework provides an accurate and effective approach for crop lodging monitoring using UAV multi-spectral imagery. Full article

Although soil fungi play a crucial role in straw decomposition, mineralization, nutrient cycling, and soil fertility, soil nitrogen and carbon stoichiometry across crop growth stages under long-term straw retention and wheat–soybean rotation remains poorly understood. We assessed the dynamic changes in soil fungal communities under no straw (NS) retention, half straw (HS) retention, and total straw (TS) retention in winter wheat and summer soybean rotation. Compared with the NS treatment, average total nitrogen (TN) increased by 11.86% and 17.71% and mean soil organic carbon (SOC) increased by 4.10% and 13.08% under the HS and TS treatments, respectively. NO₃⁻-N/TN and microbial biomass nitrogen (MBN)/TN ratios increased with the increase in straw retention; NH₄⁺-N/TN and dissolved organic carbon/SOC ratios decreased. Microbial biomass carbon (MBC)/SOC increased and subsequently decreased as straw retention increased. The mean soil C:N ratio increased, and the MBC/MBN ratio decreased as straw retention increased. Crop growth stage and straw retention treatments significantly influenced soil fungal diversity and abundance; while they did not induce changes in the dominant species, they affected relative abundance. Soil fungal relative abundance and community dynamics were more sensitive to crop growth than to straw retention treatments. Mantel’s r statistic and Pearson correlation coefficient suggest that soil chemical stoichiometric ratios are useful indicators of relationships among the fungal community, soil nutrient status, and crop cultivation. Therefore, straw retention may be suitable for long-term wheat–soybean rotation. Full article

Soil near urban areas may be burdened with numerous environmental pollutants including potentially toxic elements (PTEs). In this context, samples near the highway infrastructure in Larissa, Central Greece were examined for pseudo-total concentrations of Cr, Cu, Zn, Pb and Ni, and enrichment, ecological risk and human risk indices were calculated. Co-variation structure between PTEs and key soil properties was assessed through Principal Component Analysis (PCA). Screening for the pollution status of this area would quantify the possible risk, and therefore whether our subsequent rehabilitation trials would be of use. In this context, the most polluted sample was chosen to undergo a variety of remediation alternatives in a pot experiment, incorporating wheat and manure–attapulgite mixtures. Results showed enrichment of soil mainly with Ni, a low probability (9%) of risk exceedance for children for non-carcinogenic health effects and strong associations between the PTEs, indicating common sources. The greenhouse experiments showed that the application of manure–attapulgite reduced PTE concentrations in soil and wheat plant, with the greatest decrease observed for Pb, Cr and Ni. BCF values indicated strong accumulation of Ni (BCF > 1), while Cr and Cu showed limited uptake. Coefficient of contamination level (CCL) values (<1) for Cr and Cu confirmed reduced plant uptake, whereas Ni, Pb and Zn remained above 1. Taken together, the research shows that the fields chosen here are subjected to significant PTE input from lithogenic and anthropogenic sources, which may even become dangerous for sensitive sub-populations. Experimental cultivation of wheat shows that the combined amendments effectively reduced metal bioavailability and soil-to-plant transfer. Full article

Drought stress is one of the most severe constraints affecting wheat production worldwide. Under these conditions, the development of sustainable and economically viable strategies, such as seed priming, is essential to improve wheat performance and drought resilience. The present study carried out a greenhouse experiment on four Mediterranean durum wheat cultivars (Triticum turgidum ssp. durum Desf), i.e., Karim (Kr) and Khiar (Kh) from Tunisia and Espelta (Esp) and Mocho (Mo) from Spain, subjected to drought stress conditions, and using primed abscisic acid (ABA), indole-3-acetic acid (IAA), melatonin (Mlt), and salicylic acid (SA), and non-primed seeds. In order to assess the physio-biochemical responses of durum wheat, such as plant growth, chlorophyll, relative water content (RWC), water potential (Ψw), osmotic potential (Ψs), proline, soluble sugars, starch, glycine betaine, hydrogen peroxide, malondialdehyde, and antioxidant enzyme activities. The results showed that water stress significantly reduced plant growth, SPAD index, RWC, Ψw, and Ψs, while upregulating H₂O₂ and MDA levels, depending on the wheat cultivars. Soluble sugars decreased, whereas starch, glycine betaine, and proline accumulated in all cultivars. Superoxide dismutase activity was reduced (24–37%) under water stress as compared to the control condition, while APX, CAT, and POD activities significantly increased. Among the cultivars, Esp exhibited the greatest plasticity in response to water deficit, whereas Kh appeared to be most sensitive. Furthermore, the present results revealed that the priming durum wheat seeds with ABA, IAA, Mlt, and SA improved leaf hydration, particularly through soluble sugar accumulation. Seed priming also alleviated oxidative stress by reducing H₂O₂ and MDA levels and stimulating APX, CAT, POD, and SOD activities. Plants grown from non-primed seeds of Spanish and Tunisian cultivars exhibited differential responses to drought stress, and those derived from primed seeds showed varying degrees of enhanced drought tolerance. Espelta demonstrated a high potential for stress tolerance and responsiveness to priming, followed by Karim, whereas Khiar was the most sensitive cultivar. Overall, the cultivars can be ranked in decreasing order of stress tolerance as Esp > Kr > Mo > Kh. These findings highlight the potential of phytohormone-based seed priming as an efficient and practical approach to enhance drought resilience in durum wheat, offering promising prospects for improving crop performance and stability under increasingly water-limited conditions in the era of climate change. Full article

A significant abiotic stressor that negatively impacts plant seed germination and seedling establishment is soil salinization, especially in staple crops like wheat (Triticum aestivum L.). The complex ionic stressors that make up salinity include divalent salts (MgCl₂), alkaline salts (NaHCO₃), and neutral salts (NaCl, KCl), each of which has unique effects on osmotic and ionic toxicity. The present understanding of how various ionic salt stressors affect the dynamics of wheat germination and the early development of seedlings is summarized in this article. We talk about physiological and biochemical reactions, possible adaptive mechanisms, and the ionic specificity of toxicity. Important research findings show that: (1) germination rate and seedling vigor are reduced in response to salt content; (2) growth parameters are affected by ionic composition; and (3) genotypic variability in salt sensitivity is observed in response to salinity stress. Improving wheat performance in saline soils and developing breeding plans for salt tolerance require an understanding of these dynamics. Full article

Electromechanical systems operating under viscoelastic loads require precise modeling due to the highly nonlinear behavior of the load. An automatic bread machine is a practical example where dough represents a dynamic viscoelastic load sensitive to hydration. As found in this paper, increasing the water content leads to a decrease in the torque and the required mechanical power. An integrated approach combining MATLAB/Simulink and Simscape modeling, experimental measurements, and a PCA-based regression model is presented. The tests were conducted with three types of flour (type 500, type 1850, and rye–wheat) at hydrations of 52%, 58%, and 63% with over 6000 measurements recorded for each combination. The regression models achieve moderate predictability (R² = 0.64–0.96) model performance that varies across flour types. Increasing the dough hydration from 52% to 63% reduces the torque by approximately 22–46% across the tested flour types, while the angular velocity rises slightly (from about 147.9 to 151.9 rad/s). A descriptive decrease in energy consumption of up to around 6% was observed within the sampled batches with the system efficiency remaining within a narrow range around η ≈ 0.67. Within the studied levels (52–63%), the minimum load was observed at 58%. The proposed integrated model reliably describes the interaction between the electric motor, the mechanical gear, and the viscoelastic load, and it offers a basis for energy optimization and the implementation of low-cost sensor systems for intelligent control in the bread-making process. Full article