Search Results (13,888)

Managing invasive alien species (IAS) is a major challenge for conserving ecosystems because of their deleterious impacts. This study evaluated the efficacy of five selective herbicides and wheat straw mulch against six invasive alien plant (IAP) species in Iran. Field observations from 2021 to 2025 showed that these species are concentrated in agricultural regions, particularly in summer crops in northern Iran. Five available herbicides (pendimethalin 3 lit h⁻¹, imazethapyr 0.75 lit h⁻¹, nicosulfuron 2 lit h⁻¹, bentazone 2 lit h⁻¹, and 2,4-D+MCPA 1.5 lit h⁻¹) and wheat straw mulch (2 tons ha⁻¹) were used to reduce the growth of six IAP species during summer 2025. Pendimethalin (as a pre-emergence herbicide) was effective (>90%) against all species apart from Ipomoea hederacea (≈60%). While 2,4-D+MCPA (as a post-emergence herbicide) effectively controlled five species, bentazone was effective only against Sida rhombifolia and I. hederacea. Nicosulfuron showed high efficacy (80%) only against I. hederacea. Straw mulch was more effective against Euphorbia nutans but was not effective properly against Ipomoea species. The efficacy of mulch and some herbicides depended on species identity, even within the same genera (Ipomoea and Euphorbia). Our results can help in the successful management of these invasive plants in northern Iran to minimize their impact on yield and quality of crops. As IAPs in environmental areas, this result will also be advantageous. Full article

The outbreak of pests seriously affects the yield and quality of wheat crops. The accurate recognition and detection play an essential role in the early warning of crop pests. While some limitations, like insufficient dataset, imbalanced samples of pests with dense distribution, and dense distribution and tinyof crop pests, pose significant challenges to the precise detection. Thus, in this work, we first spent two years collecting real-world wheat pest images with four types of pests, including three grain aphids, and one mite species, to obtain a high-quality crop pest dataset for network optimization. Secondly, to alleviate insufficiency of samples of pests with dense distribution, we have developed a cut-up data augmentation strategy that separates dense pest targets from complex backgrounds. Furthermore, to address the challenge of pest detection with tiny body size and dense distribution, we introduce the Multiple Kernel Attention Network (MKA-Net), which further integrates the multi-scale features of pests to improve detection accuracy. Our method achieved the best detection precision, with AP50 reaching its peak at 67.1%, which is a significant improvement of nearly 6.9 points in wheat pest detection compared with the baseline. In summary, our proposed method can assist in the prevention and control of wheat pests and promote the progress of intelligent agriculture. Full article

Wheat (Triticum aestivum L.) is an economically important cereal crop. Its genetic diversity is a prerequisite for successful breeding for resistance to leaf and stem rust, as well as for other important traits. Therefore, the main objective of the study was to determine the level of genetic diversity of a file of 185 wheat accessions chosen to represent a wide range of resistance levels to leaf and stem rusts. They were evaluated at two locations in three years (2023–2025) for leaf and stem rust resistance by means of visual evaluation and fungus content using real-time PCR. BLUP values were then computed from these multi-environmental data. In addition, data on other traits such as heading time, plant height, and grain quality were collected. In the PCA, grain quality variables represented the first factor, explaining 41% of the total variability. Rust resistance was mainly associated with the second and the third factor. Population analysis revealed primary two (K = 2) and secondary six (K = 6) clusters, computed by using 13,274 DArT markers. The correlation between genotype and phenotype data was high (R = 0.89) when all traits were analyzed, and lower (R = 0.58) when only leaf and stem rust resistance variables were considered. Genetic diversity was also studied through an association analysis between markers and phenotypic traits using GLMs and MLMs. As a result, 300 statistically significant marker-trait associations (MTAs) were identified (p ≤ 3.77 × 10⁻⁶). Of these MTAs, 180 were associated with rust resistance variables and 120 with other traits. A BLAST search of rust resistance MTAs identified 128 putative genes; 47 of them can be taken for candidate genes related to fungal resistance. The results show that association analysis can help to explain the genetic diversity of selected wheat accessions, and that leaf and stem rust resistance are complex traits involving many non-specific resistance genes. Full article

The objective of this study is to evaluate the potential of airborne spore monitoring for predicting the severity of foliar diseases in winter wheat by developing variety-dependent disease models that account for variety susceptibility and applying a statistical procedure that accommodates the hierarchical structure of panel data. The experiments were conducted in the fields of the FSBSI Federal Research Center of Biological Plant Protection on plots sown with five winter wheat varieties exhibiting varying susceptibility to foliar diseases, while the processing of the data was carried out in 2025–2026. The concentration of spores in the air was estimated using a portable spore trap. Along with air sampling, visual assessments of the development of major fungal pathogens on plants were performed. The hypothesis of variety-specific susceptibility was tested using moderation analysis. The analysis revealed a relationship between leaf disease severity and the number of detected spores, with the strength of correlation varying depending on the pathogen species and variety susceptibility. Using pairwise comparisons of regression slopes for each variety, it was demonstrated that the development of Blumeria graminis depends primarily on spore concentration levels and climatic conditions rather than on variety identity. In contrast, for Puccinia striiformis, Puccinia triticina, and Pyrenophora tritici-repentis, variety susceptibility/resistance was shown to exert a statistically significant influence on disease development. These findings will serve as the foundation for a novel phytosanitary monitoring methodology, which is essential for generating forecasts and informing decision-making regarding plant protection measures. Full article

Industrial processing of tomato generates large amounts of tomato pomace (TP), whose disposal and stabilization are challenging due to its high moisture content. This study evaluated, for the first time, the effects of increasing inclusion levels of enzymatic pre-treatment, vacuum paddle-dehydrated TP (ETP), in extruded diets for adult dogs. Three diets containing 0%, 2% or 4% ETP, replacing wheat bran and sunflower meal, were produced. Three two-bowl tests assessed palatability, and a feeding trial was performed using a four 3 × 3 Latin square design with 12 healthy adult Beagle dogs across three 28-day periods. Inclusion of ETP had negligible effects on the chemical composition of diets and kept unaffected palatability, body weight, food intake, fecal consistency and output. Fecal pH was lower, and valerate proportion was higher, in dogs fed the 2% ETP diet. All diets exhibited high digestibility (>90%) without effects of dietary treatments. Overall, ETP, a locally sourced co-product of the food industry, may represent a more sustainable alternative to imported raw materials, although further studies are needed to explore its effects on fecal microbiota and health-related parameters. Full article

The increasing threat posed by wheat rust diseases caused by Puccinia spp. necessitates the development of resistance strategies that extend beyond conventional race-specific mechanisms. Although recent reviews (2023–2025) have emphasized gene discovery and genomic approaches, comparatively less attention has been given to the potential roles of metabolic regulation and micronutrient homeostasis in host–pathogen interactions. Here, we present a narrative synthesis of current evidence and propose a conceptual framework in which induced mutagenesis (ethyl methanesulfonate, EMS, and γ-irradiation) serves as a tool for investigating interactions among redox regulation, iron (Fe) homeostasis, and disease resistance. A key component of this framework is the proposed interplay between reactive oxygen species (ROS) signaling and Fe partitioning. Vacuolar iron transporters (VITs), ferritins, and associated transport networks regulate intracellular Fe distribution and may influence Fe availability at the host–pathogen interface, potentially affecting fungal development and host defense responses. This concept of “iron-withholding immunity” may operate alongside ROS-mediated defense processes, linking metabolism with immune function. Observations from mutant wheat populations are broadly consistent with the hypothesis that these processes may contribute to durable adult-plant resistance (APR), which is characterized by reduced disease development, coordinated defense responses, and relative stability across environments. In some studies, Fe-enriched mutant lines have been associated with enhanced expression of pathogenesis-related genes and the occurrence of combined APR and seedling-resistance phenotypes, suggesting possible links between micronutrient homeostasis and immunity. Integration of high-throughput phenotyping with genotype × environment × time (G × E × T) frameworks may further improve our understanding of quantitative resistance and disease-associated traits. Overall, this review highlights the potential importance of nutrient homeostasis, redox regulation, and susceptibility modulation as components of future research aimed at developing climate-resilient and nutritionally improved wheat cultivars. Full article

Wheat anther culture-mediated embryogenesis is strongly influenced by genotype responsiveness and remains limited by low embryo-like structure (ELS) conversion efficiency, frequent albino formation, and unstable developmental progression. In this study, the effects of DNA methylation inhibitors (5-azacytidine (AZC), 5-aza-2′-deoxycytidine (DEC), and zebularine (ZEB)) and the histone deacetylase inhibitor trichostatin A (TSA) on ELS induction, ELS conversion into green regenerants (GRs), albino frequency, and spontaneous genome doubling were evaluated in wheat anther cultures with contrasting embryogenic responsiveness. The results revealed strong genotype-dependent responses to treatments with epigenetic inhibitors. The spring wheat cultivar AC Abbey showed the highest overall anther culture response, whereas winter wheat genotypes displayed limited and variable ELS conversion competence. ELS formation was observed even in recalcitrant genotypes but was not consistently associated with efficient ELS conversion into GR. Multivariate analyses indicated stronger genotype differentiation at the conversion stage than during ELS induction, suggesting that this stage represents a major bottleneck in wheat anther culture-mediated embryogenesis. Among the tested compounds, AZC and TSA most effectively stimulated ELS induction, while AZC was associated with the lowest albino frequency. DEC showed the highest proportion of spontaneous doubled haploids. Overall, treatment with epigenetic inhibitors may enhance ELS induction but does not overcome genotype-dependent recalcitrance at the conversion stage under the applied anther culture conditions. Full article

Wheat straw (WS) is an abundant crop residue with considerable potential as a ruminant feed; however, its utilization is severely constrained by a recalcitrant lignocellulosic structure. This study evaluated the effects of five alkali-resistant cellulolytic bacterial inoculants on the structural carbohydrate composition and in vitro ruminal fermentation characteristics of ammoniated wheat straw. A 6 × 3 factorial arrangement was employed, with six treatments (ammoniated WS as a control and five cellulolytic bacterial strains: X67, C72, S87, D100, and X107) and three storage durations (7, 14, and 21 days). The results showed that the bacterial treatments caused moderate losses of dry matter (DM), neutral detergent fiber (NDF), acid detergent fiber (ADF), hemicellulose, and cellulose at 7 and 14 days. The X107 treatment exhibited the lowest hemicellulose content, 2.1% lower than the ammoniated control. After 48 h of in vitro incubation, all bacterial treatments significantly increased potential gas production, 48 h methane production, in vitro DM digestibility (IVDMD), and in vitro NDF digestibility (IVNDFD). The S87 treatment achieved the highest IVDMD and IVNDFD, exceeding the ammoniated control by 14.9% and 32.5%, respectively, at 7 days (p < 0.05). All bacterial treatments maintained relatively high total volatile fatty acid (VFA) concentrations. Furthermore, the bacterial treatments increased the relative proportions of ruminal cellulolytic microbes at 7 and 14 days. By 21 days, no significant differences were observed in DM loss or microbial proportions among treatments. These findings indicate that the application of cellulolytic bacterial additives, with appropriate selection of bacterial strain and storage duration, exerts synergistic positive effects on the feeding value of alkali-pretreated wheat straw. The S87 treatment with a 7-day storage duration proved most effective. Full article

The aim of this study was to evaluate the enrichment in the soluble protein and bioactive components of wheat bread by Polish bee pollen or bee bread addition, applying a previously reported recipe. The research phase included a baking trial and laboratory analyses, including water and soluble protein content, total acidity, crumb color of the fresh bread, sensory evaluation and texture profile (TPA) (fresh and after 4 days of storage). The bioactivity of 80% ethanol extracts (1% w/v) of used additives and enriched breads was assessed in terms of total phenolic and flavonoid content as well as antioxidant activity. The results confirmed that both additives (at percentages: 1%, 3%, and 5%) enhanced bread’s properties in a dose-dependent manner, and the bread with 5% bee bread addition achieved the highest acidity, a 3.7-fold increase in soluble protein content, a 10-fold increase in iron-reducing capacity, and a 6-fold increase in antiradical activity compared to the control. Moreover, in texture tests, the same variant demonstrated the most effective delay in the staling process, maintaining the highest softness after 4 days. However, consumers rated the bread with 5% bee bread variant too intense in flavor. In general, the technological repeatability of the fortification degree of wheat bread with Polish bee products with the recipe used was confirmed; however, the quality of raw additives can deteriorate sensory qualities. Full article

Salinity is a major factor limiting the increase in crop yield around the world. Wheat starch and straw are important raw materials for producing bioethanol, and their productivity is adversely affected by salinity. Polyacrylic acid-modified Mn₃O₄ nanoparticles (PMO) have been reported to improve crop tolerance to stressors, including salt stress. Therefore, this study aimed to elucidate the mechanism by which seed soaking with PMOs enhances wheat salt tolerance. PMO seed soaking promoted wheat germination (increase of 30.9%) under salt stress, and seedlings treated with PMO seed soaking had a higher fresh weight (increase of 31.4%). PMO seed soaking increased the POD activity (by 31.9%) but decreased superoxide dismutase and catalase activities of wheat seeds and the O₂⁻ and H₂O₂ contents (by 25.0 and 71.4%, respectively). Furthermore, PMO soaking increased the ATP, NADPH, and NADH contents (by 367.6, 212.0, and 283.2%, respectively) by regulating sugar metabolism and enhanced the ascorbic acid–glutathione cycle. Additionally, the PMO soaking treatment optimized energy allocation in wheat under salt stress and increased yield (by 9.7%). PMO modulated sugar metabolism, thereby optimizing energy allocation to plant growth and the antioxidant system, which enhanced wheat germination and yield formation under salt stress. Full article

Sustaining maize–cereal production under intensive agricultural systems is becoming increasingly challenging because of declining soil quality, low nutrient-use efficiency, and escalating abiotic and biotic stresses. In many regions, long-term rice–wheat cultivation has intensified these constraints, prompting greater interest in diversified production systems such as maize–wheat rotations. Within this context, bio-organic fertilizers (BOF) and microbial biostimulants are increasingly recognized not merely as nutrient inputs but as biologically active regulators of plant–soil interactions. This review synthesizes current knowledge on the role of BOF in maize–cereal production systems, with particular emphasis on maize–wheat rotations. It examines their effects on crop productivity, soil health, nutrient dynamics, and resilience to abiotic and biotic stresses. Current evidence indicates that BOF and microbial biostimulants improve crop performance through interconnected mechanisms, including nutrient mobilization, root development, rhizosphere regulation, and microbial-mediated soil processes. Collectively, these mechanisms enhance nutrient-use efficiency, strengthen stress tolerance, and contribute to more stable crop yields. Importantly, the benefits of BOF extend beyond single growing seasons by promoting soil biological activity, nutrient availability, and system resilience across successive crop cycles. Overall, BOF should be regarded not simply as alternatives to mineral fertilizers but as multifunctional regulators of plant–soil processes that support the sustainability of maize–wheat and other cereal-based cropping systems. Full article

To address the issues of low water and fertilizer use efficiency and limited yield potential in traditional winter wheat cultivation in Henan Province, and to determine the optimal drip irrigation frequency for wide-row precision sowing under a constant total irrigation amount, this study was conducted based on a field experiment in Zhengzhou, Henan, during the 2024–2025 season. Four treatments were set up: border irrigation with wide-row precision sowing (QK40), and single-drip irrigation events of 25 mm (DK25, high frequency), 40 mm (DK40, medium frequency), and 55 mm (DK55, low frequency). The effects of drip irrigation frequency on photosynthetic accumulation after anthesis (AUC), source–sink coordination index (SSCI), and the synergy among water, grain, and quality in wide-row precision-sown winter wheat were quantitatively analyzed. The results showed that DK25 significantly delayed leaf senescence and extended the green leaf functional period by 9 days by stabilizing moisture in the 0–40 cm root zone. Post-anthesis photosynthetic accumulation increased by 23.39% and was highly significantly positively correlated with yield. The leaf area index at the heading stage increased by 23.54%, and the source–sink coordination index (SSCI) improved by 45.1%. Over the whole growth period, water consumption was reduced by 10.38%, water use efficiency increased by 23.5%, and yield increased by 8.9%, while grain quality remained stable. Entropy Weight-TOPSIS evaluation showed that DK25 performed the best. This study can provide a cultivation pattern and technical parameters for water-saving, high-yield, and high-quality wide-row precision-sown winter wheat in the Huang-Huai-Hai Plain. Full article

Groundwater-fed irrigation sustains global food production but drives chronic aquifer depletion, creating an urgent need for quantitative tools that link irrigation intensity to groundwater response. This study proposes a gray-box machine learning (ML) framework that learns the parametric coefficients of polynomial irrigation–groundwater response functions—rather than predicting state variables directly—thereby embedding physical interpretability into the ML output. Using a well-validated SWAT-GW model of a representative over-exploited piedmont plain in the North China Plain as the training data generator, gradient irrigation scenarios were constructed for 70 hydrological response units over 20 years, producing 21,000 paired records of winter-wheat irrigation intensity versus three groundwater response variables: vertical recharge, aquifer storage change, and water table depth change. Quadratic polynomials were identified as the optimal functional form through joint evaluation of fitting accuracy (R² > 0.994) and ML learnability. Ensemble boosting algorithms predicted the three quadratic coefficients, with R² ranging from 0.74 to 0.97, and retained acceptable accuracy even when input features were restricted to readily available meteorological and soil data. Four management-critical hydrogeological parameters—the precipitation infiltration coefficient (α), irrigation infiltration coefficient (β), natural recharge (R_nat), and recharge–abstraction equilibrium point (IRR_eq)—were successfully inverted from the predicted coefficients and validated against independent regional groundwater resource assessments. The SHapley Additive exPlanations and Causal Forest analyses confirmed that the learned relationships are governed by physically interpretable drivers. The framework advances groundwater machine learning from state-variable prediction toward functional-structure extraction, offering a transferable approach for deriving irrigation–groundwater response curves and sustainability thresholds in over-exploited aquifer systems. Full article

Uneven seed placement in nursery trays reduces seedling uniformity and can reduce the reliability of mechanical transplanting in hybrid rice, but the optimum printed seeding density remains unclear. This study evaluated the effects of printed seeding density on seed distribution, seedling quality, transplanting performance, canopy productivity and yield formation in machine-transplanted hybrid indica rice. A two-year split-plot field experiment was conducted in Xuzhou, China, using Runliangyou 313 and Yangxianyou 903. Five printed seeding densities (1400–2600 printed points tray⁻¹) were compared with two local weight-based broadcasting controls, representing practical establishment systems rather than seed-number-matched contrasts. Moderate printed densities improved seed distribution uniformity, strengthened the seedling mat, reduced transplanting defects and supported productive tiller formation. T3 and T4 produced the highest harvested yields, increasing yield by 13.3–15.5% over the standard broadcasting control. These gains were associated with higher panicle number, greater post-anthesis dry matter accumulation and higher harvest index. The results indicate that moderate-density printed seeding can improve establishment quality and grain yield under wheat-rice rotation conditions. Full article

To advance crop type mapping in support of global food and water security, this study compared three spectral configurations: (A) the full 60-band DLR Earth Sensing Imaging Spectrometer (DESIS) hyperspectral narrowband (HNB) dataset, (B) a 14-band subset of DESIS-derived HNBs aligned with the planned Landsat 10 (formerly Landsat Next) spectral configuration (400–1000 nm), and (C) DESIS-based simulations of Landsat 10 superspectral broadbands. The analysis was conducted in California’s Central Valley, hereafter referred to as “the Central Valley”, during the peak growing month of August. DESIS imagery from August 2021, 2022, and 2023 was used sequentially for model development, testing, and independent validation. Over these three years, DESIS provided extensive hyperspectral coverage of much of the 4 million hectares in the Central Valley’s. Analyses were performed on Google Earth Engine using two pixel-based supervised classifiers, Random Forest (RF) and Support Vector Machine (SVM), to differentiate three major crop classes: row crops, grapes and tree crops, and winter wheat/fallow/other. The highest overall accuracy (86%) was achieved using SVM in combination with either the full DESIS hyperspectral dataset or the 14 DESIS narrowbands corresponding to Landsat 10. This finding aligns with earlier studies showing a small number of strategically positioned narrowbands can be optimal for crop type classification. Use of the narrowband datasets resulted in substantially higher accuracy (overall accuracy of 86%) compared to the simulated Landsat 10 broadbands (overall accuracy of 75%), supporting previous studies highlighting the utility of narrowbands. Despite the high accuracy using August imagery, the study indicates more granular crop type classification will require multi-temporal observations spanning the full phenological cycle (June–October), especially for a large number of crop classes. Acquiring task-based hyperspectral imagery over such large areas throughout the growing season remains operationally challenging. In contrast, Landsat 10 superspectral imagery could provide routine coverage across seasons and years that is practical and scalable for future large area crop type mapping and agricultural monitoring. Full article