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Note: The papers published below will continue to be available from this page until they are assigned to an issue. To see an article, click its [PDF] link. To review many abstracts, check the boxes to the left of the titles you want, and click the 'Selected articles' button. To see one abstract at a time, click its [Abstract] link. Please wait a minute... For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails Select From elite germplasm to transformation platform: Breaking recalcitrance in Tartary buckwheat Zhen Wang, Tong Su, Kaixuan Zhang, Yuqi He, Zhirong Wang, Alexander Betekhtin, Meiliang Zhou DOI: 10.1016/j.jia.2026.03.022 Online: 10 March 2026 Abstract （1）      PDF in ScienceDirect       Reference | Related Articles | Metrics Select Identification and cloning of the TdBa controlling black awn color in durum wheat (Triticum durum Desf.) Junna Sun, Wei Pan, Yuqi Zhang, Wenxin Wei, Nannan Liu, Zuhuan Yang, Jiarui Zhang, Boyuan Zhang, Jinying Gou, Weilong Guo, Qixin Sun, Chaojie Xie, Jun Ma DOI: 10.1016/j.jia.2026.03.021 Online: 10 March 2026 Abstract （0）      PDF in ScienceDirect       Melanins are a class of dark pigments widely distributed among living organisms. In cereal crops, the black husk-pericarp trait arises from melanin accumulation. The durum wheat (Triticum turgidum L. var. durum Desf.) cultivar Ofanto (Oft) exhibits black awns beginning at the soft dough stage. To identify the genetic loci associated with awn color, we analyzed an F2 population derived from a cross between Oft (black awn) and Langdon (LDN, yellow awn). Genetic mapping revealed a single dominant black awn gene, TdBa, located within an approximately 4.38 Mb interval on the short arm of chromosome 1AS. Among the 34 annotated genes located within this interval, TRITD1Av1G000090, which encodes amino acid transporters homologous to the rice black hull gene OsBh4 and barley black husk/pericarp gene HvBlp, was identified as a candidate gene based on sequence, expression, and gene function prediction analyses. In contrast to its homologous genes OsBh4 and HvBlp, TdBa causes only black awn in wheat. The role of TRITD1Av1G000090 in awn coloration was subsequently confirmed through transgenic assays. Reference | Related Articles | Metrics Select Quantifying the contribution of climate variability to cotton yield changes in Xinjiang: Approximately one-third of interannual variability and predominantly negative impacts across counties Jian Wang, Xin Li, Zhanlei Pan, Guilan Sun, Pengcheng Li, Jing Chen, Wenqi Zhao, Yaopeng Zhang, Menghua Zhai, Junhong Li, Lizhi Wang, Kunfeng Wang, Ao Li, Zhenggui Zhang, Zhanbiao Wang DOI: 10.1016/j.jia.2026.03.020 Online: 10 March 2026 Abstract （1）      PDF in ScienceDirect       Understanding the relative contributions of climatic and non-climatic factors to cotton yield variability is essential for developing climate-resilient production systems. Using county-level yield records from 1990 to 2024 together with gridded climate data, this study quantified the impacts of climate variability on cotton yield across Xinjiang, China, and assessed future yield responses under two CMIP6 scenarios (SSP2-4.5 and SSP5-8.5). Random forest models and a panel regression approach were applied to disentangle climatic and non-climatic yield components and to capture nonlinear climate–yield relationships. The results show that climate variability accounts, on average, for approximately one-third of the interannual yield variation across Xinjiang, while non-climatic factors dominate long-term yield growth. Pronounced spatial heterogeneity is observed in climate impacts: warming conditions are projected to benefit cotton production in southern and eastern Xinjiang, whereas about one-third of cotton-growing counties, predominantly situated in northern Xinjiang and high-altitude regions, are projected to experience negative climate impacts. At the regional scale, the net effect of climate change on cotton yield is projected to remain positive, with stronger yield enhancement under SSP5-8.5, although this overall gain masks substantial county-level disparities. Assuming constant planting areas, adverse climate impacts are projected to result in total production losses of approximately 2.4–3.2×10⁵ t by mid-century and 2.8–3.0×10⁵ t by the end of the century across negatively affected counties. These findings highlight the critical role of non-climatic drivers, including agronomic innovations and irrigation management, in sustaining yield growth and buffering adverse climate effects. From a policy perspective, the results underscore the need for region-specific adaptation strategies that enhance climate resilience in major production zones while guiding the spatial optimization of cotton production under future climate change. Reference | Related Articles | Metrics Select A novel labor-saving strategy for hybrid rice seed production Quan Gan, Ran Zhou, Hao Yu, Cuixiang Lin, Bin Teng, Fengshun Song, Dahu Ni DOI: 10.1016/j.jia.2026.03.019 Online: 10 March 2026 Abstract （0）      PDF in ScienceDirect       Reference | Related Articles | Metrics Select Intraspecific competition promotes plant disease induced by an oomycete pathogen Wenjing Wang, Xiaxia Wang, Yanping Wang, Ejiao Wu, Menghan He, Ge Zhao, Lina Yang, Jiasui Zhan DOI: 10.1016/j.jia.2026.03.018 Online: 10 March 2026 Abstract （0）      PDF in ScienceDirect       Competition is a fundamental driver of evolution, shaping species' adaptive trajectories and ecological dynamics, where interspecific competition influences community structure and niche differentiation, while intraspecific competition plays a critical role in functional development and adaptive evolution, particularly in agroecosystems where competition among pathogen genotypes, combined with host-pathogen interactions, significantly impacts the evolution of virulence. Through laboratory experiments involving single and mixed inoculations, this study investigates intraspecific competition in Phytophthora infestans, the causal agent of late blight in potatoes and tomatoes, to understand the impact of genotype frequency, genetic relatedness, and genetic variation on transmission and pathogenicity. Results revealed that strains with higher field frequencies exhibited greater competitive ability, while increased genotypic complexity and genetic distance between coinfecting strains enhanced disease severity and reduced incubation periods, highlighting the role of intraspecific competition in shaping pathogen evolution and virulence, with implications for disease management. Strategies such as crop diversification, biocontrol agents and microbiome applications are proposed to mitigate the evolution of highly virulent strains and promote sustainable agricultural practices. This study bridges theoretical and empirical insights into competitive interactions, offering a deeper understanding of the mechanisms driving pathogen evolution and their ecological consequences. Reference | Related Articles | Metrics Select A Caseinolytic proteases ATPase family gene OsClpI3 contributes to thermotolerance in rice Fengfeng Fan, Zihan Yang, Huanran Yuan, Ayaz Ahmad, Kai Lv, Fei Xu, Manman Liu, Yu Guo, Fengfeng Si, Nengwu Li, Shaoqing Li, Mingxing Cheng DOI: 10.1016/j.jia.2026.03.017 Online: 10 March 2026 Abstract （1）      PDF in ScienceDirect       The continuous rise in global temperatures and the increasing frequency of extreme heat events pose severe challenges to rice production due to heat stress. Exploring heat tolerance genes and developing heat-tolerant rice varieties represent effective strategies to address this issue. In this study, we identified a novel heat tolerance gene, OsClpI3, through analysis of the Caseinolytic proteases (Clp) ATPase gene family. OsClpI3 is predominantly expressed in leaves, encodes a chloroplast-localized protein, and positively regulates heat tolerance during both the seedling and heading stages. OsClpI3 exhibits ATPase activity, which is markedly reduced in mutant lines. Integrated transcriptomic and metabolomic analyses revealed that OsClpI3 contributes to rice thermotolerance by maintaining photosynthetic electron transport efficiency and overall photosynthetic performance under high-temperature conditions. Furthermore, natural variation in OsClpI3 affects heat tolerance, and haplotype analysis revealed a superior haplotype, Type4. These findings provide new insights into the molecular mechanisms underlying heat tolerance in rice and offer valuable genetic resources for breeding heat-tolerant rice varieties. Reference | Related Articles | Metrics Select Pathogenicity evaluation and gut microbiota dysbiosis analysis in piglets infected with a novel recombinant mammalian orthoreovirus type 3 strain HN2019-01 Fangfang Han, Jinhui Hou, Yuxin Tang, Guozheng Li, Hui Hu, Jin Yuan, Zhanyong Wei DOI: 10.1016/j.jia.2026.03.016 Online: 10 March 2026 Abstract （1）      PDF in ScienceDirect       Mammalian orthoreoviruses (MRVs) have been identified in various mammalian species, including humans. Although there have been numerous reports on the cross-species transmission and genetic reassortment of MRVs among humans, livestock and wildlife, the prevalence and pathogenicity of MRVs on swine herds in China remain largely unknown. In this study, a novel MRV type 3 (MRV3) HN2019-01 strain was isolated on Vero cells from a clinical porcine epidemic diarrhea virus-positive intestinal content of a diarrheic piglet, and was identified using the small RNA deep sequencing, electron microscopic observation and the immunofluorescence assays. This isolated strain was able to replicate in multiple cell lines and showed the best replicative efficiency on Vero cells. Genetic analysis revealed that MRV HN2019-01 was a recombinant strain with gene segments from the swine MRV2 and MRV3, and has a close phylogenetic relationship with the MRV2/117 RNA, MRV2/CH/GX/PReoV/2435/2018, MRV3/ZJ2013 and MRV3/BM-100 strains. Subsequently, the pathogenicity of MRV HN2019-01 was evaluated in 5-day-old piglets. The results showed that the MRV HN2019-01 strain caused diarrhea and intestinal villi damage in piglets. Meanwhile, MRV HN2019-01 infection was shown to affect both the diversity and composition of the colonic microbiota in piglets, with a significant increase in Collinsella and Enterococcus and a notable decrease in Lactobacillus, Desulfovibrio and Ruminococcus. Metabolomic analysis revealed that MRV HN2019-01 infection in piglets induced alterations in multiple intestinal metabolites, including carbohydrates, bile acids, 3-hydroxy-L-tyrosine-AMP and short-chain fatty acids. KEGG pathway enrichment analysis indicated significant differences between the infected group and the control group in pathways such as thiamine metabolism, protein digestion and absorption, tyrosine metabolism and phenylalanine metabolism. This study provided important foundational data for investigating the pathogenic mechanisms and evolutionary characteristics of MRV and for the development of vaccines against MRV.This study provided important foundational data for investigating the pathogenic mechanisms of MRV and for the development of vaccines against MRV. Reference | Related Articles | Metrics Select Under reduced nitrogen fertilizer conditions, increasing wheat planting density to enhance sink capacity for achieving high productivity Yakun Li, Jianli Liu, Jianping Tang, Yimou Zuo, Aqing Gao, Xiaoyan Gu, Vinay Nangia, Yang Liu DOI: 10.1016/j.jia.2026.03.015 Online: 10 March 2026 Abstract （0）      PDF in ScienceDirect       Nitrogen reduction is an effective strategy for improving nitrogen use efficiency (NUE) in crops, but it often leads to a decrease in grain number per unit area. Increasing planting density can enhance sink capacity by raising the number of grains per unit area. However, it remains unclear whether the combined strategy of reducing nitrogen input while increasing planting density can sustain or improve wheat yield, as well as the underlying source-sink regulatory mechanisms. In this study, two wheat cultivars with contrasting sink characteristics were selected: the multi-spike cultivar XN20 (Xinong 20) and the large-spike cultivar LKAZ8 (Lankaoaizao 8). A split-plot experimental design was adopted, involving three nitrogen levels and two planting densities. The results showed that the combined strategy of reducing nitrogen and increasing density significantly enhanced aboveground dry matter, grain yield, and NUE. While nitrogen reduction decreased the leaf area index (LAI) by 1.61–22.39%, increased planting density raised LAI by 2.99–14.13%, sink capacity by 3.08–27.58%, and improved the grain-to-leaf area ratio (GN-LAR). GN-LAR was significantly positively correlated with post-anthesis dry matter accumulation and nitrogen remobilization. Compared with conventional nitrogen and density management, the integrated strategy enhanced source supply, improved the source-sink relationship by increasing sink capacity and optimizing GN-LAR, and thereby promoted post-anthesis dry matter accumulation and nitrogen remobilization, strengthening the coordination between source supply and sink demand. These findings provide new insights into the regulatory mechanisms of the source-sink relationship in wheat under conditions of reduced nitrogen and increased planting density, offering a scientific basis for achieving a balance between high yield and high NUE in wheat production. Reference | Related Articles | Metrics Select Plant disease phenotype captioning via zero-shot learning with semantic correction based on LLM Yushan Xie, Xinyu Dong, Kejun Zhao, G.M.A.D Sirishantha, Yuanyuan Xiao, Peijia Yu, Changyuan Zhai, Qi Wang DOI: 10.1016/j.jia.2026.03.014 Online: 10 March 2026 Abstract （1）      PDF in ScienceDirect       Agriculture is the foundation of global food security and quality of life, with staple crops such as rice, wheat, and maize meeting the dietary needs of the majority of the world's population. These crops are susceptible to diseases that can lead to significant yield losses; for example, wheat rust disease causes annual losses that exceed $2.9 billion. Accurate captioning of the phenotypic characteristics of plant diseases plays a crucial role in supporting diagnosis, which is essential for ensuring food security. Existing methods in agriculture struggle to adequately address the heterogeneity in visual phenotypes and disease descriptions, which leads to inadequate focus on key disease characteristics. To address this issue, we propose a zero-shot image captioning framework named PDPC. PDPC employs an extensive descriptive corpus, syntactic analysis, and optimization of semantic structures to significantly improve the quality and generalization of disease descriptions. Additionally, we construct a dataset comprising 20,943 image captions that describe the characteristics of plant diseases in more than 60 plant species and 300 diseases. Experimental results demonstrate that the PDPC framework outperforms existing models in accurately describing the characteristics of plant disease. The introduction of this innovative framework enhances the accuracy of disease descriptions and provides robust support for the intelligent diagnosis and management of plant diseases, ultimately paving the way for better plant health and higher agricultural yields.  Reference | Related Articles | Metrics Select Calibration strategies for rice model: phenology selection under various nitrogen applications Chenyao Yang, Siyuan Wang, Christoph Menz, Andrej Ceglar, Zhitao Hu, Bing Liu, Feng Yang, Wei Zhou, Xianming Tan, Zhaohong Lu, Peng Qin, Shigui Li, Wanjun Ren, Helder Fraga, Joao A. Santos DOI: 10.1016/j.jia.2026.03.013 Online: 10 March 2026 Abstract （0）      PDF in ScienceDirect       Crop models have been widely used to optimize nitrogen (N) applications for agronomic decision-making, but uncertainties in model calibration under varying N levels, particularly the effects of phenology choice for calibration, remain underexplored. This study employed the ORYZA v3 model, coupled with a global optimization algorithm, to assess how different calibration strategies affected predictions of leaf area index (LAI) and biomass in two rice varieties under four N levels (0, 90, 180, and 270 kg ha-1). The results indicate when the model is calibrated separately for each N level, predictive accuracy varies considerably for both LAI and biomass, reflecting the difference in crop response to N availability. When calibrating the model simultaneously with multiple N levels from a single phenology phase, variability from different selected phenology phases becomes the dominant source of model uncertainty, rather than N levels. Specifically, calibrations using measured data from the stem elongation to anthesis (SA) and anthesis to maturity (AM) phases across N levels provide the most accurate predictions for LAI (RMSE: 0.51–1.92 m² m-²; R²≥0.88) and biomass (RMSE: 551–2619 kg ha-1; R²≥0.96), respectively. In contrast, calibrations using measured data from early-season (transplanting to stem elongation) result in the least reliable predictions. Combined-phase calibrations using SA and AM phases result in the best predictions for both LAI and biomass, owing to their balanced representation of pre- and post-anthesis growth dynamics. This approach significantly reduces uncertainty from phase selection. However, variability in N application rates emerges as the primary uncertainty source in model simulations, emphasizing the importance of careful selection of N levels in calibration datasets, particularly when measured data span two-thirds of the growing season. These findings offer valuable insights into improved calibration practice for precise N management, highlighting the critical role of both phenology phase and N treatment selection. Reference | Related Articles | Metrics Select An odorant receptor from Spodoptera frugiperda is tuned to the plant volatile linalyl acetate Xiaoqing Wang, Yutong Zhang, Lei Liu, Yujie Yang, Yang Liu DOI: 10.1016/j.jia.2026.03.012 Online: 10 March 2026 Abstract （0）      PDF in ScienceDirect       Insects depend on sophisticated olfactory systems for essential behaviors, with odorant receptors (ORs) lying at the core of odor detection. Spodoptera frugiperda is a major global agricultural pest, but the response profiles of its ORs remain largely unresolved. Here we focused on the functional characterization of SfruOR37 in S. frugiperda, an ortholog of Helicoverpa armigera HarmOR50 – which responds to (±)-camphor, an important plant volatile. Tissue expression analysis showed that SfruOR37 is specific expressed in the antennae of both sexes. Using Xenopus laevis oocytes, we functionally screened candidate ligands and identified linalyl acetate as the most potent activator of SfruOR37. To elucidate the binding mechanism between this receptor and its ligand, we performed molecular docking and dynamics simulations, which highlighted several non-conserved residues (notably S151, Y155, and Y325) likely shaping the SfruOR37 binding pocket and mediating the binding affinity to linalyl acetate. Electroantennogram (EAG) recordings demonstrated that linalyl acetate effectively elicits significant electrophysiological responses in adult antennae. In behavioral assays, linalyl acetate elicited a pronounced repellent effect on adult S. frugiperda. Together, our results illuminate how conserved ORs can diverge functionally within Lepidoptera and how such divergence contributes to ecologically relevant olfactory coding. Finally, by establishing linalyl acetate as a behaviorally active repellent for S. frugiperda, this study provides a theoretical basis for developing odorant-based, eco-friendly pest control strategies. Reference | Related Articles | Metrics Select Dual modes of Zn2+-dependent and independent virulence regulation by CzcSR in Pseudomonas syringae pv. actinidiae Mengsi Zhang, Mingming Yang, Heyan Shen, Yuncong Wang, Yarong Luo, Shuaiwu Wang, Xihui Shen, Lili Huang, Yao Wang DOI: 10.1016/j.jia.2026.03.011 Online: 10 March 2026 Abstract （0）      PDF in ScienceDirect       Bacterial pathogens harbor numerous two-component systems (TCSs) in their genomes, which enable rapid sensing and response to environmental fluctuations, thereby facilitating dynamic adaptation to diverse ecological niches. Pseudomonas syringae pv. actinidiae (Psa) is the causal agent of kiwifruit bacterial canker (KBC), a devastating disease threatening global kiwifruit production. However, the biological function of the metal-responsive TCS CzcSR in Psa remains largely uncharacterized. In this study, we demonstrated that CzcSR plays a crucial role in regulating Psa pathogenicity in the host plant and the hypersensitive response (HR) in the non-host plant. Under zinc ion (Zn2+) stress, Psa exhibited suppressed motility and enhanced oxidative stress tolerance; notably, this phenotype depends on the Zn2+-binding sites of CzcS and the phosphorylation status of CzcR. However, the key virulence factor type III secretion system (T3SS) of Psa is unaffected by Zn2+ stress, and CzcSR-mediated regulation of the T3SS is independent of both the Zn2+-binding sites of CzcS and the phosphorylation status of CzcR. Instead, CzcR controls T3SS expression by binding to the promoter region of hrpR and modulates the c-di-GMP level via interacting with diguanylate cyclase (DGC) PSA_4781. Collectively, our findings expand CzcSR’s functional repertoire, highlight TCS complexity, and deepen understanding of TCS versatility—CzcSR integrates Zn2+ signals for canonical regulation of phenotypes (e.g., motility, antioxidant defense) while using a signal-independent mechanism for T3SS control. Reference | Related Articles | Metrics Select ACC1 mutations in wheat for quizalofop-p-ethyl resistance: An expansion and their incorporation into Chinese breeding lines Wenqiang Wang, Yong Gan, Jifa Zhang, Qunqun Hao, Zhigang Wang, Chunhao Zou, Daolin Fu DOI: 10.1016/j.jia.2026.03.010 Online: 10 March 2026 Abstract （0）      PDF in ScienceDirect       Reference | Related Articles | Metrics Select Discovery of the genomic region and candidate gene for qELSB02.1, a novel and stable major QTL associated with peanut early leaf spot resistance Zhijun Xu, Sheng Zhao, Xuejiao Zhang, Qibiao Li, Lei Xu, Qian Yang, Li Huang, Huifang Jiang DOI: 10.1016/j.jia.2026.03.009 Online: 06 March 2026 Abstract （4）      PDF in ScienceDirect       Early leaf spot (ELS) is one of peanut’s prominent and widespread foliar fungal diseases, causing severe yield losses and forage quality deterioration in South China. Discovery of the genomic region and the underlying candidate gene controlling ELS resistance will promote progress in resistance breeding and facilitate uncovering its genetic basis. In this study, a major genomic region, qELSB02.1, was identified using a bulked segregant RNA-Seq (BSR-seq) approach in a RIL population derived from a cross between a susceptible cultivar ZH10 and a resistant line ICG12625. It was further confirmed via simple sequence repeat genetic map-based linkage analysis, explaining 20.13-35.27% of the phenotypic variation. Using a partial genetic map and a segregation mapping population, qELSB02.1 was fine-mapped into a 465 kb genomic region by linkage analysis and substitution mapping. Furthermore, an NB-ARC-LRR gene (Arahy.V6I7WA) was identified as the most probable candidate gene for qELSB02.1 and was named Arachis hypogaea ELS resistance 1 (AhELSR1) based on functional annotation, sequence variation analysis, expression profiling, and protein structure prediction. Allelic variation analysis using 244 global peanut germplasm accessions identified four haplotypes, providing valuable clues for understanding ELS resistance evolution mediated by AhELSR1. Five SNPs, located in the first exon of AhELSR1, altering four encoding amino acids, were used to develop a diagnostic marker. The marker was further validated using diverse peanut germplasm and through introgression of AhELSR1 into a susceptible cultivar. Our results provide new insights into the genetic basis of ELS resistance regulation and benefit the breeding efforts for developing improved cultivars with enhanced ELS resistance.  Reference | Related Articles | Metrics Select Overexpression of ZmNAC118 narrows auricle size and leaf angle in maize Qiuyue Yang, Jihu Song, Xianting Huang, Han Lv, Jie Yang, Qilin Liu, Litao Yi, Shuang Li, Le Chen, Jiayi Liu, Jiuguang Wang, Chaofeng Li, Chaoxian Liu, Xiupeng Mei DOI: 10.1016/j.jia.2026.03.008 Online: 06 March 2026 Abstract （4）      PDF in ScienceDirect       Leaf angle critically influences maize canopy structure and yield. NAC transcription factors regulate various developmental processes, yet their role in maize leaf angle remains poorly understood. In this study, we demonstrate that modulating the expression level of ZmNF-YC13 significantly alters the expression of ZmNAC118, suggesting that these two genes likely function within a common regulatory pathway. ZmNAC118 shows preferential expression in leaf tissues and encodes a nuclear-localized protein capable of transcriptional activation. Phenotypic analyses demonstrated that overexpression of ZmNAC118 leads to a pronounced reduction in auricle size and leaf angle. Transcriptomic profiling further revealed that ZmNAC118 modulates the expression of CYP450 genes associated with brassinosteroid (BR) and auxin (IAA) metabolic pathways. These CYP450 genes clustered into hormone-related phylogenetic clades, with a subset overlapping targets of ZmNF-YC13, indicating co-regulation within a shared pathway. Our study identifies ZmNAC118 as a key regulator of leaf angle and a promising candidate for maize architectural improvement. Reference | Related Articles | Metrics Select CRISPR/Cas9-mediated SiYABBY1 mutagenesis enhances cleistogamy and seed number and size in foxtail millet (Setaria italica) Lingqian Zhang, Xuan Zhou, Jiaxuan Hu, Hejing Wu, Xiangyang Yuan, Xiaoqian Chu, Jia-Gang Wang DOI: 10.1016/j.jia.2026.03.007 Online: 06 March 2026 Abstract （5）      PDF in ScienceDirect       Reference | Related Articles | Metrics Select Silicon fertilization drives metabolite–microbe synergy to stabilize rhizosphere nitrogen supply and improve drought resilience and yield stability in upland rice Bin Qin, Jiahui Song, Zhenghao Yin, Danyang Li, Yijiang Hu, Shaofei Ye, Hailong Xu, Jinying Li, Bianhong Zhang, Jingnan Zou, Yazhou Liu, Zhixing Zhang, Lihua Shen, Changxun Fang, Wenxiong Lin DOI: 10.1016/j.jia.2026.03.006 Online: 06 March 2026 Abstract （4）      PDF in ScienceDirect       Metabolite–microbe interactions are pivotal hubs for maintaining crop productivity under abiotic stress, and silicon (Si) fertilization has been widely recognized for enhancing plant stress tolerance. However, the mechanisms by which Si mediates rhizosphere metabolic reprogramming and microbial regulation to synergistically improve crop drought resilience remain unclear. Here, a two-year field experiment (2023–2024) was conducted using upland rice cultivar “Hanyou 73”. Treatments included well-watered conditions (CK), drought stress (D), and four Si application rates under drought (DS1-DS4, 25, 50, 75, and 100 kg ha-1, respectively). We systematically investigated the coupled effects of Si on rhizosphere metabolites, microbial communities, and plant stress responses. Drought stress disrupted oxidative homeostasis, reduced photosynthetic capacity, and inhibited carbon and nitrogen metabolism, resulting in yield reductions of 27.96 and 20.37% in 2023 and 2024, respectively. Compared with D, DS3 significantly increased the levels of rhizosphere N- and sugar-related metabolites and enhanced soil microbial diversity, thereby stabilizing soil nitrogen cycling and enriching beneficial taxa (g_Bacillus). Consequently, nitrogen use efficiency increased by 26.21%, leaf superoxide dismutase (SOD) activity increased by 40.31%, and grain yield increased by 22.98 and 20.90% across the two years. Validation experiments further demonstrated that the combined application of Si and N/sugar-related metabolites (Ethanamine, Tagatose, Urea, Sorbose, and Fumaric acid) significantly promoted upland rice growth and soil nutrient accumulation, stimulated the proliferation of strain BT021, strengthened soil N cycling, increased soil N-related enzyme activities, and enhanced plant growth and antioxidant capacity. Structural equation modeling (SEM) revealed that Si directly regulated yield variation under drought through metabolite–microbiome coupling–driven nutrient cycling. Overall, Si fertilization reshapes rhizosphere processes via metabolite–microbe synergy, improves soil N cycling and rhizosphere environmental quality under drought, promotes plant nutrient transport, and stabilizes yield, providing new mechanistic insights and an applicable paradigm for green, stress-resilient yield improvement in upland agriculture. Reference | Related Articles | Metrics Select Early prediction of faba bean yield and yield categories based on spectral-texture fusion of UAV hyperspectral imaging Yishan Ji, Yue Song, Ying Jin, Yuxing Cui, Yu Jin, Mingquan Ding, Tao Yang DOI: 10.1016/j.jia.2026.03.005 Online: 06 March 2026 Abstract （4）      PDF in ScienceDirect       Accurate and nondestructive prediction of crop yield and yield categories are crucial for advancing precision. This study presented an integrated framework combining unmanned aerial vehicle (UAV) based hyperspectral imaging and machine learning to predict the early yield and yield categories of faba bean. Field experiments were conducted across three key growth stages—branching, early budding and mid budding—using high-resolution hyperspectral data. Full-band reflectance (FBR) and texture features (TF) were extracted and fused to enhance model sensitivity to canopy spectral-structural variations. The results revealed that FBR achieved higher coefficients of determination (R2>0.60) and lower root mean square errors (RMSE<0.93 t ha-1) across all stages than vegetation indices (VIs), indicating its superior capacity to capture subtle physiological dynamics. The integration of TF with FBR further improved model accuracy, especially based on deep neural network in the mid budding stage (R2=0.8254, RMSE=0.4732 t ha-1). Compared with the traditional method, the R2 was increased by about 15-27%, and the RMSE was reduced by 38-49%, which highlighted the synergistic effect of spectral-spatial fusion. For predicting the yield categories, the XGBoost algorithm presented outstanding performance (F1-score>0.86). Spatial analyses confirmed strong consistency between measured and predicted distributions of yield and yield categories, validating the robustness of the proposed approach. In this study, the hyperspectral and machine learning prediction models were developed for early prediction of faba bean yield and yield categories, which provided a scalable data-driven tool for high-throughput phenotypic analysis and sustainable crop management. Reference | Related Articles | Metrics Select Highly efficient Agrobacterium rhizogenes-mediated hairy root transformation for gene function analysis in cotton without tissue culture Mengyuan Yan, Ziwei Ye, Ming Tan, Yan Zhou, Meijie Chai, Huan Yu, Wen Li, Libei Li, Zhen Feng, Shuxun Yu DOI: 10.1016/j.jia.2026.03.003 Online: 06 March 2026 Abstract （8）      PDF in ScienceDirect       Efficient genetic transformation technologies are crucial for exploring plant gene functions and promoting molecular breeding. However, the widely used genetic transformation technology mediated by Agrobacterium tumefaciens is time-consuming and genotype-dependent, which limits the high-throughput functional characterization of cotton genes. The transformation system mediated by Agrobacterium rhizogenes (ARM) presents a rapid and effective alternative, but previous ARM techniques in cotton suffered from low efficiency and complicated operation. Here, we optimized the traditional ARM method suitable for nonsterile environments. The two-step ARM technology we used effectively enhanced the transformation efficiency within the upland cotton. The entire process only takes one month, and this system is applicable to various upland cotton varieties, with a maximum transformation efficiency of up to 100%. Results have shown that the ARM method only produces transgenic roots rather than whole transgenic plants. The obtained transgenic hairy roots can be employed to endogenous gene silencing and gene overexpression, enabling subcellular localization analysis and in-depth exploration of gene functions. In summary, we have first described a rapid, universal, efficient, and nonsterile ARM system in cotton, offering a reliable foundation for the cotton gene functional study and the advancement of genetic improvement breeding. Reference | Related Articles | Metrics Select Rice-fish coculture contributes to improve nutrient availability, carbon sequestration and maintain rice yield under minimal tillage/no-tillage condition in double-season rice farming of South China Xing Liu, Daolin Sun, Qi Jia, Shengbao Wei, Jiaen Zhang, Hongjun Zheng, Huaqiao Huang DOI: 10.1016/j.jia.2026.03.002 Online: 06 March 2026 Abstract （2）      PDF in ScienceDirect       Rice-fish coculture (RFC) is widely recognized for increasing soil fertility and crop yield. However, the introduction of fish in double-season rice planting areas of South China to balance relationship between rice yield, soil function and ecosystem services, and to develop an optimal model between RFC and minimal tillage/no-tillage (NT) practices in a complementary form need to be further investigated. Hence, we conducted a two-year field experiment through a combination between RFC and several tillage types including CT (conventional tillage), NT (no-tillage), Minimal tillage (e.g. ECT+LNT. ECT refers CT used in early rice phase; LNT refers NT used in late rice phase following the ECT of early rice phase) to evaluate soil nutrients, rice yields, carbon (C) components and C-related enzymes activities. Our study found that RFC significantly increased contents of available phosphorus (P) by 9.52-11.42%, nitrate nitrogen (N) by 11.90-12.82%, and rice yield by 3.25-10.13%, while NT significantly increased contents of available P by 26.96-35.64%, ammonium N by 9.40-12.33%, and organic C by 10.26-15.08%. We also found that the interaction between RFC and NT significantly took effect on rice yield and C process. Also, available N and P contributed to improve rice yield, while available P, partial organic C, pH, dissolved organic C and bulk density drove C process. Moreover, LNT treatment significantly improved rice yield than that of CT treatment. These findings suggest that rice-fish coculture combining with minimal tillage/no-tillage is a promising eco-farming model to improve nutrient availability and carbon sequestration, and maintain rice yield.  Reference | Related Articles | Metrics page Page 1 of 20 Total 396 records First page Prev page Next page Last page