This study evaluated the potential of chitosan-based silicon nanoparticles (CBSNs) to reduce arsenic (As) accumulation in rice grown in As contaminated paddy soils, with a specific focus on their influence on element redistribution at the root-soil interface. Rice was cultivated in As-contaminated soils treated with different CBSNs concentrations. As, iron (Fe), manganese (Mn), and silicon (Si) concentrations were measured in porewater, rhizosphere soil, root iron plaque (IP), and various plant tissues. Root surface elemental distribution was characterized by Scanning electron microscopy-energy dispersive spectroscopy-element mapping (SEM–EDS-mapping), and rhizosphere bacterial communities were profiled via 16S rRNA sequencing. CBSNs application reduced As uptake by rice roots by 35.27
Abstract Background Weaning piglets are highly susceptible to enterotoxigenic Escherichia coli (ETEC) infections, which can cause intestinal barrier function dysfunction and death. However, there is still a lack of efficient, economical, and safe nutritional interventions. This study aimed to investigate the effects of combining butyrate with niacin on intestinal barrier function repair and resistance to ETEC infection in weaned piglets. In this study, two 14-d animal experiments were designed to observe the optimal butyrate-to-niacin ratio and assess their responses to the ETEC challenge. Results Supplementation with butyrate and niacin at a ratio of 100:2 (2,000 mg/kg butyrate and 40 mg/kg niacin, BN2) increased the average daily gain (ADG) and reduced the diarrhea incidence. We also observed an increase in the levels of nicotinamide adenine dinucleotide (NAD) in the colon of weaned piglets. Notably, BN2 promoted amino acid anabolism in the colon and enhanced glycolysis and the tricarboxylic acid (TCA) cycle by increasing the acetylation of key enzymes in the TCA. Furthermore, BN2 enhanced the expression of indispensable genes for the colonic mucosal barrier, including antimicrobial peptides such as porcine β defensin 1 (pBD1), porcine β defensin 2 (pBD2), and proline-arginine rich 39-amino acid peptide (PR39), tight junction proteins, and improved colonic microbiome composition. Based on these findings, we found that BN2 alleviated growth restriction and diarrhea, and modulated the expression of antimicrobial peptides, tight junction proteins, and cytokines to reduce colonic barrier function dysfunction in weaned piglets challenged with ETEC. Mechanistically, we confirmed that BN2 elevated the protein expression of acetylation of histone 3 lysin 27 (H3K27ac) and enhanced the binding of acH3K27 to the promoter regions of pBD1 and PR39. Conclusions Supplementation with BN2 improved growth performance, supported colonic barrier function repair, and enhanced disease resistance in weaned piglets challenged with ETEC. This offers new insights into nutritional strategies for intestinal barrier function repair of piglets infected with ETEC.
The clamp-hanging method for conveying strawberries by their stems offers distinct advantages for online detection of soluble solids content (SSC) by visible/near-infrared (Vis/NIR) spectroscopy. It minimizes fruit damage compared to traditional tray conveyance and facilitates non-destructive sorting in industrial applications. However, variations in hanging height and fruit size can alter detection zones and effective optical path length, while the inherent spatial heterogeneity of SSC distribution collectively compromises measurement accuracy for the whole-fruit. To tackle these obstacles, this study developed a refined clamp-hanging prototype and advanced spectral correction techniques for accurate Vis/NIR spectroscopy-based SSC prediction. A visual imaging module was integrated to monitor fruit size and hanging height in real time. Building on this, single spectral correction methods, including extinction coefficient correction (ECC) and correlation coefficient correction (CCC), were evaluated, with ECC delivering the best performance. A combined ECC-CCC approach further improved accuracy, achieving a determination coefficient of prediction (R2p) of 0.916 and a root mean square error of prediction (RMSEP) of 0.287 degrees Brix using competitive adaptive reweighted sampling-partial least squares regression (CARS-PLSR), effectively reducing optical path fluctuations. Innovatively, a joint strategy incorporating SSC distribution correction with these spectral correction methods yielded superior results with R2p = 0.945 and RMSEP = 0.229 degrees Brix, thereby enhancing overall prediction reliability. Additionally, a onedimensional convolutional neural network-long short-term memory (1D-CNN-LSTM) model applied directly to raw spectra achieved optimal outcomes with R2p = 0.948 and RMSEP = 0.225 degrees Brix, promoting robustness without preprocessing. Collectively, these innovations advance non-destructive, automated SSC detection, outperforming existing methods in accuracy and efficiency for strawberry quality assessment, potentially advancing online internal quality evaluation for small, delicate fruits.
Plant molecular marker technologies have reshaped crop genetics and breeding by making it possible to analyse genome-wide variation with a precision that phenotype-based selection, even in experienced programmes, cannot reach in routine practice. This review summarises recent progress in marker platforms from classical RFLP and SSR systems to high-throughput SNP genotyping, with emphasis on KASP, multiple nucleotide polymorphism and multi-gene panel technologies, and on sequencing-based methods such as GBS, GBTS and Hyper-seq that often serve as an upstream discovery layer for targeted assays and databases. These platforms are increasingly integrated into practical workflows for marker-assisted and genomic selection, DNA fingerprinting, germplasm characterisation and plant variety protection, and multi-locus markers have become a central tool for high-resolution DUS testing and EDV determination that adds an independent layer of evidence to morphology-based assessments. Key challenges now include cross-platform standardisation, design of marker panels that balance cost with information content, interoperability of databases across institutions and countries, and the definition of molecular distance thresholds that are acceptable both biologically and in legal and regulatory settings. The review also considers the rapid integration of molecular marker data with artificial intelligence, including AI-driven marker discovery and panel optimisation, genomic prediction in multi-environment trials and the concept of an intelligent seed-industry operating system that links genotypic, phenotypic and environmental information in a coherent data framework. These developments collectively point to a shift from isolated marker assays towards platform-level, AI-supported infrastructures that can accelerate variety innovation and contribute to the modernisation and quality improvement of the seed industry.
Soil organic carbon (SOC) stability is crucial for sustaining long-term carbon sequestration in agricultural ecosystems. Although straw return effectively enhances SOC sequestration, it primarily elevates the active fraction-particulate organic carbon (POC)-potentially undermining SOC stability. How to balance the trade-off between SOC sequestration and stability through the synergistic management of straw and nitrogen (N)-fertilizer remains unclear. To fill this knowledge gap, we integrated 831 paired field observations from 84 studies across China and established a comprehensive framework combining meta-analysis, machine learning, and optimization algorithm. The results indicate that straw return significantly increased SOC content by 13.94% (95% confidence intervals, CIs: 12.54-15.34%), POC content by 26.36% (95% CIs: 23.40-29.54%), and mineral-associated organic carbon (MAOC) content by 10.00% (95% CIs: 8.73-11.36%), respectively. However, it also increased the POC/SOC ratio by 12.56% (95% CIs: 10.32-14.98%), confirming the inherent trade-off between SOC sequestration and stability. Random forest and restricted spline analyses revealed that N-fertilizer and straw input are key drivers with significant synergistic effects. The natural log-transformed response ratio of SOC (Ln RRSOC) failed to increase continuously with cumulative straw return, while the effect of N-fertilizer on SOC dynamics was mediated by the straw input level, producing contrasting outcomes. When straw return was divided into high and low groups based on the median value, analysis showed that under high straw return, increasing N-fertilizer enhanced both SOC sequestration (increased Ln RRSOC) and POC-to-MAOC conversion (decreased Ln RRPOC/SOC and increased Ln RRMAOC), with P < 0.05. Conversely, under low straw return, additional N-fertilizer suppressed these outcomes. Leveraging these mechanisms, we developed a nationwide synergistic management strategy using particle swarm optimization. By regionally reducing straw inputs and spatially reallocating N-fertilizer, this strategy effectively mitigates the sequestration-stability trade-off. The optimized scenario-with annual inputs of 271.33 kg N ha(-1) and 9,466.33 kg straw ha(-1)-increased SOC sequestration by 3.94% while significantly curbing the POC/SOC rise by 24.92% relative to baseline. These findings highlight the critical role of coordinated exogenous carbon and nitrogen inputs in securing both SOC sequestration and stability, offering a spatially tailored approach to guide sustainable agricultural management.
