Advanced Online Publication

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 Methylation dynamics modified by GhDMT9, playing an vital role in drought response of cotton Xuke Lu, Junjuan Wang, Shuai Wang, Xiugui Chen, Delong Wang, Zujun Yin, Lanjie Zhao, Lixue Guo, Waqar Afzal Malik, Maohua Dai, Wuwei Ye DOI: 10.1016/j.jia.2026.02.011 Online: 07 February 2026 Abstract （10）      PDF in ScienceDirect       DNA methylation is a stable epigenetic modification with essential roles in plant drought response. It is known that methyltransferase mutant is necessary for the regulation of methylation variations, but this epigenetic molecular mechanism based on methyltransferase mutant in responding to drought stress was still unclear in cotton. In this study, we aim to decipher the epigenetic code of drought response regulated by methyltransferase gene GhDMT9 in cotton, providing valuable information for the molecular research of drought resistance in cotton. We successfully created the first cotton methyltransferase mutant ghdmt9 using CRISPR/Cas9 method and performed methylation variations analysis with whole-genome bisulfite sequencing (WGBS) and transcriptome analysis based on ghdmt9 mutant. In addition, specific antibody of methyltransferase GhDMT9 was prepared and used for Chromatin Immunoprecipitation (ChIP-seq) analysis. The results indicated that ghdmt9 mutant interpreted approximately 2.06% methylation variations under drought stress. Demethylation variations, mainly derived from the CHG and CHH contexts, were closely correlated with drought response. Whether at normal growth stage or under drought stress, the number of up-regulated genes induced by demethylation variations was apparently higher than the number of down-regulated genes, especially genes regulating lipids and lipid-like molecules and hormone-related genes. In addition, fiber quality of ghdmt9 mutant was obviously better than that of wild type (WT). Interestingly, a transcription factor lsh (lysine-specific histone) was found to interact with methyltransferase gene GhDMT9 to activate its hyper-methylation function of target genomic regions by ChIP-seq analysis. Overall, our results extend our understanding of the epigenetic regulation of methyltransferase GhDMT9 in drought response and contribute to further investigations of the epigenetic mechanisms underlying abiotic stresses in cotton.  Reference | Related Articles | Metrics Select Combining cost-effective germination imaging and genome-wide association study to unravel genetic variation of temporal salinity responses in wheat Qing Li, Zhuangzhuang Sun, Xiaofang Li, Zihan Jing, Xiaomiao Tian, Yinchen Zhang, Yingyin Yao, Zhen Zhang, Meng Wang, Xiao Wang, Qin Zhou, Jian Cai, Yingxin Zhong, Mei Huang, Wenliang Wan, Jiawei Chen, Dong Jiang DOI: 10.1016/j.jia.2026.02.010 Online: 07 February 2026 Abstract （6）      PDF in ScienceDirect       Salt stress is a major limiting factor for global wheat production, especially during the germination stage. Traditional methods for evaluating salt resistance at the germination stage are limited by low throughput and their inability to capture dynamic phenotypic changes. In this study, a low-cost and high-throughput seed germination phenotyping platform was developed by integrating side-view RGB imaging with image analysis algorithms. Organ segmentation and germination related traits extraction processes was built via a deep learning pipeline for comprehensive phenotyping of the germination process of diverse varieties under different salt levels. Organ-level segmentation achieved a mean precision of 89.08%, a mean recall of 91.65%, a pixel accuracy of 91.65%, and a mean intersection over union of 83.20%. The 13 image-derived traits were highly consistent with manual measurements. Salt stress significantly inhibited the growth of roots and seedlings, with inhibitory effects intensifying as salt concentration increased. Further analysis revealed seed size shows no correlation with germination capacity and radicle growth rate significantly surpasses that of the coleoptile. Clustering analysis based on dynamic image-derived indices classified the 210 wheat materials into two groups with significantly different salt tolerance. GWAS identified 429 loci associated with salt stress response during germination, including one potential candidate gene, TraesCS7A03G007080, known to play a role in salt tolerance mechanisms. This study provides important genetic materials for the evaluation of salt-tolerant wheat varieties at the germination stage and offers a low-cost, high-throughput, and reliable technical approach for dissecting the genetic basis of salt tolerance during wheat germination. Reference | Related Articles | Metrics Select Proactive optimization of drip-applied DPC based on cultivar sensitivity: Increasing machine-harvested cotton yield and reducing DPC residues Feng Shi, Yu Tian, Xiaojuan Shi, Liwen Tian, Xianzhe Hao, Nannan Li, Hongxia Zhang, Humei Zhang, Houxiu Zhao, Shijie Deng, Xuan Liu, Guoxing Ma, Jing Li, Jun Wang, Honghai Luo DOI: 10.1016/j.jia.2026.02.009 Online: 07 February 2026 Abstract （4）      PDF in ScienceDirect       Within the context of modern cotton cultivation, which emphasizes cost savings and efficiency improvements, drip application of 1,1-dimethyl piperidinium chloride (DPC) provides potential advantage such as reducing the labour and mechanical costs associated with the chemical regulation of conventional DPC foliar spraying in arid cotton-growing areas. However, the appropriate drip DPC dose and its regulatory effects on cotton growth and yield, and particularly the responses to cultivars with different sensitivities to DPC, remain uncertain. A two-year (2023–2024) field experiment was conducted to evaluate the influences of various cultivars and drip DPC doses on cotton phenology, agronomic traits, canopy development, defoliation, boll opening, yield and residual DPC levels. The cultivars Huiyuan 720 (H720, DPC-sensitive) and Xinluzao 74 (L74, DPC-insensitive) were chosen, the D0 (no DPC) and S1 (DPC foliar spraying at 330 g ha−1 in 2023 and 375 g ha−1 in 2024) treatments were used as controls, and the drip DPC doses were D1 (the same dose as that in S1), D4 (four times the dose in S1) and D6 (six times the dose in S1). The results indicated that compared with those in D0, the growth periods of H720 in D4 and L74 in decreased by 9 days; in particular, the number of growth days from the peak flowering stage to the late peak bolling stage decreased by 6 days. The plant height, the height of the first fruiting branch, and plant width decreased significantly, by 10.1–19.1%. The diffuse non-interceptance and canopy light transmittance in the middle and upper parts from the peak squaring stage to the boll opening stage increased by 7.9–55.9% and 0.4–7.0%, respectively. The defoliation and boll opening rates increased by 1.5–3.4%. The boll numbers in the middle part increased by 16.7–36.4%, and the yield increased by 4.9–7.6%. Compared with those in S1, the yields of H720 in D4 and of L74 in D6 were comparable but the levels of DPC residues in the cotton plants significantly decreased by 36.3–71.0%. Moreover, the levels of DPC residues in D6 were minimal in soil. These results indicated that an appropriate drip DPC dose can optimize cotton growth and development and reduce the levels of DPC residues based on the cultivar characteristics. This study provides valuable practical insights into the potential of a drip DPC regulation system to replace the foliar spraying method and to advance light and simplified cotton cultivation. Reference | Related Articles | Metrics Select A weak OsBRI1 allele in Zhonghua 11 as a genetic tool for brassinosteroid signaling research in rice Yanzhao Feng, Qingfeng Zhu, Qiuyue Yuan, Pei Chen, Xielian Tan, Ning Huang, Jiao Xue, Yang Yu DOI: 10.1016/j.jia.2026.02.008 Online: 07 February 2026 Abstract （4）      PDF in ScienceDirect       Reference | Related Articles | Metrics Select Simultaneous silencing of ten essential Sclerotinia sclerotiorum genes via spray- and host-induced gene silencing enhances against Sclerotinia stem rot resistance in oilseed rape Sichao Ren, Ying Zhang, Yi Ye, Wenjing Huang, Wenxin Liu, Shengliang Yin, Yang Yang, Yu Liu, Jialin Fan, Yumei Wang, Youping Wang, Li Lin, Jian Wu DOI: 10.1016/j.jia.2026.02.007 Online: 07 February 2026 Abstract （8）      PDF in ScienceDirect       Sclerotinia stem rot (SSR) is caused by the necrotrophic fungus Sclerotinia sclerotiorum and threatens global oilseed rape (Brassica napus) production. Moreover, researchers have not yet identified a gene that confers complete resistance. Here, we developed a multi-target RNA interference (RNAi) strategy to enhance plant resistance by simultaneously silencing eight fungal genes involved in development (SsChsI–VII, SsGas1) and two involved in pathogenicity (SsPG1, SsOAH1) of S. sclerotiorum. Accordingly, we designed a 1,250-bp chimeric double-stranded RNA (dsRNA) consisting of ten 125-bp fragments each targeting a different gene, and evaluated its effectiveness using spray-induced gene silencing (SIGS) and host-induced gene silencing (HIGS) via stable transformation. In vitro application of the chimeric dsRNA resulted in >50% downregulation of nine target genes, indicating efficient uptake and processing by S. sclerotiorum. Both lesion area and fungal biomass were significantly lower in Nicotiana benthamiana and oilseed rape plants following SIGS. Moreover, stable transgenic plants for HIGS effectively generated gene-specific short interfering RNAs and exhibited an increase in resistance from the T2 to T5 generations, with lesions that were 38.9–59.1% smaller in leaves and 43.2–65.8% smaller in stems in the T5 generation compared with the control plants. Gene silencing resulted in lower oxalic acid accumulation, decreased polygalacturonase activity, and impaired hyphal development, suggesting interference with multiple fungal infection pathways. Notably, HIGS conferred stable, heritable resistance without yield penalty, whereas SIGS provided rapid, nontransgenic protection. This study demonstrates the effectiveness of long chimeric dsRNAs for multi-target gene silencing and highlights a promising RNAi-based strategy for improving disease resistance in oilseed rape, possibly in combination with natural quantitative resistance loci. Reference | Related Articles | Metrics Select The TATA-box binding protein-associated factor ZmTAF11 regulates plant architecture in maize Fengzhong Lu, You Zhou, Yajie Liu, Xin Zhang, Tao Wan, Jingtao Qu, Wanchen Li, Fengling Fu, Wei Guo, Haijian Lin, Jianfeng Hu, Jie Xu, Guangchao Sun, Yao Wang, Yanli Lu, Haoqiang Yu DOI: 10.1016/j.jia.2026.02.006 Online: 07 February 2026 Abstract （3）      PDF in ScienceDirect       Compact maize architecture is crucial for high planting densities and yields, which is a key breeding objective. In this study, a maize T-DNA insertion mutant with compact plant architecture (cpa) was identified, showing reduced leaf curling, drooping angle, plant and ear height, leaf dimensions, internode and tassel length, tassel branch number, and yield compared to WT. Paraffin section analysis showed reduced vein cross-sectional area, epidermal cell width, and increased vein density in the cpa mutant. Genetic analysis revealed that T-DNA was inserted into the first exon of a gene encoding TATA-box binding protein-associated factor (TAF) in the cpa mutant, which was named ZmTAF11. ZmTAF11 exhibited ubiquitous expression across various tissues and nuclear localization. Loss-of-function Zmtaf11 mutants generated by CRISPR/Cas9 exhibited the characteristic compact phenotype, which was consistent with that of the cpa mutant. ZmTAF11 directly binds to the promoters of leaf morphogenesis-related genes ZmAXL and ZmBOB1, thereby promoting their transcription. Furthermore, four SNPs in ZmTAF11 were significantly associated with ear height index (EHI), and the AGTG haplotype showed a lower EHI. This haplotype was predominantly found in temperate maize lines and geographically distributed across North America. These findings reveal the role of ZmTAF11 in regulating maize architecture and its potential application in high-density maize breeding.  Reference | Related Articles | Metrics Select Identifying limiting factors for maize yield in China’s major maize-producing regions using random forest Liangbing Rong, Qianlan Jia, Kaiyuan Gong, Fengying Duan, Xia Li, Congfeng Li, Peng Liu, Dalei Lu, Gang Zhao, Ning Yao, Yi Li, Hao Feng, Jianqiang He, Qiang Yu, Wenbin Zhou DOI: 10.1016/j.jia.2026.02.005 Online: 07 February 2026 Abstract （3）      PDF in ScienceDirect       Maize (Zea mays L.) is an important food crop worldwide. Understanding yield-limiting factors is essential for optimizing maize productivity under varying agroclimatic conditions. In this study, the relative contributions of climate, soil, and management factors to yield variation in spring and summer maize across 34 sites in China during 2017-2020 were assessed. Random forest (RF) models explained more than 80% of the yield variation, and SHapley Additive exPlanations (SHAP) and Accumulated Local Effects (ALE) were employed to interpret the effects of key variables. Climate emerged as the dominant driver, accounting for nearly 50% of the total feature importance. For spring maize, solar radiation during the establishment stage (ES) had a strong positive effect, whereas the minimum temperature during the grain-filling stage (GFS) had a negative effect. In contrast, summer maize yield was constrained by elevated nighttime temperatures during ES but benefited from increased growing degree days (GDD) during GFS. Among all the variables, planting density (PD) was consistently important across both systems, and increasing PD represented a direct and effective pathway to enhance yield. The results of the yield component analysis further revealed that the significantly higher kernel number per ear (on average 68 kernels more than summer maize) was the main contributor to the superior performance of spring maize. Climate scenario simulations indicated that, without adaptive management, future warming could reduce spring and summer maize yields by 6.1–11.8% and 5.5–9.1%, respectively. These findings underscore the stage-specific climate sensitivity of maize and support the development of targeted adaptation strategies to sustain yields under future climate change. Reference | Related Articles | Metrics Select Development of innovative image descriptors for phenotyping peanut pod constriction and discovery of QTLs underlying this trait Shengzhong Zhang, Feifei Wang, Xiaohui Hu, Huarong Miao, Jun Hong, Shihua Shan, Xiaoyuan Chi, Jing Chen, Xinyou Zhang, Shengzhong Zhang, Feifei Wang, Xiaohui Hu, Huarong Miao, Jun Hong, Shihua Shan, Xiaoyuan Chi, Jing Chen, Xinyou Zhang DOI: 10.1016/j.jia.2026.02.004 Online: 07 February 2026 Abstract （5）      PDF in ScienceDirect       Pod constriction (PC) is a key morphological trait determining both commercial values and yield of in-shell peanuts. Conventional phenotyping metrics (visual scores and pod waist length derived descriptors) suffer from low precision or limited applicability, especially for atypical pod shapes, which have constrained discovery of underlying genes. To address these limitations, this study introduced two novel image descriptors: front and back constriction depth indices (Front_DI and Back_DI). These indices enable accurate and robust evaluation of PC across diverse pod morphologies. Additionally, a Python script employing the deep learning technology was developed to efficiently and precisely extract these metrics. By applying both novel and conventional phenotyping methods to a recombinant inbred line population (Luhua 11×06B16), this study identified four quantitative trait loci (QTLs) for Front_DI, four for Back_DI, three for visual score, and two for a pod waist length-based descriptor across three environments. A major and co-localized QTL region was consistently detected on chromosome 2. Meta-analysis further refined this region to a 728-kb consensus interval. Within this interval, an InDel was identified in the coding region of Arahy.X14VTN between the two parental lines, resulting in a frameshift mutation and a predicted alteration in protein structure. Diagnostic markers were developed for this candidate gene, confirming the genetic effect on PC variation. The novel image descriptors and genetic loci presented here improve our understanding of the genetic basis of PC in peanut and offer practical tools for molecular breeding aimed at trait improvement. Reference | Related Articles | Metrics Select Physics-informed and prior-data driven: A hybrid Stacking framework for rice growth parameter inversion Tianao Wu, Junjie Zheng, Minghan Cheng, Kaihua Liu, Xiyun Jiao DOI: 10.1016/j.jia.2026.02.003 Online: 07 February 2026 Abstract （7）      PDF in ScienceDirect       Accurate monitoring of rice growth status is essential for scientific water and fertilizer management in paddy fields. Using remote sensing data combined with radiative transfer models and artificial intelligence algorithms can realize the semi-mechanism inversion. However, the commonly used hybrid inversion models have difficulties in adapting to paddy field scenarios covered with water layers. In addition, the data simulation methods often ignore the correlations between parameters, leading to distortion of the simulated data. To address these challenges, by developing the PROSAIL-Dw model considering the influence of the underlying surface moisture state on the canopy reflectance and proposing a multivariable joint prior knowledge data simulation method based on C-Vine Copula, this study proposed a novel hybrid framework based on Stacking model for retrieving rice growth parameters from multispectral imagery. The results indicated that, by introducing two parameters reflecting the presence and depth of the water layer, the PROSAIL-Dw model can more accurately simulate the NIR reflectance with water layer coverage (with R² increased by 0.42 for low nitrogen treatment). The growth parameters simulated by the C-Vine Copula method could retain the correlations, thus effectively improving the accuracy of the Stacking model compared with conventional methods (with rRMSE decreased by 5.81%-15.00%, and R² increased by 0.19-0.30). The hybrid inversion framework constructed in this study has further improved the accuracy and reliability of rice growth parameter inversion, and has important practical value for the scientific management of water and fertilizer in early-stage paddy fields. Reference | Related Articles | Metrics Select The research on LAI estimation of multiple rice varieties based on multi-modal data fusion and machine learning algorithms Aidong Wang, Ruijie Li, Xiangqian Feng, Ziqiu Li, Hengjie Gao, Huaxing Wu, Danying Wang, Song Chen DOI: 10.1016/j.jia.2026.02.002 Online: 07 February 2026 Abstract （5）      PDF in ScienceDirect       Accurate estimation of Leaf Area Index (LAI) in multi-variety rice using optical remote sensing remains challenging due to spectral saturation under dense canopy conditions and inter-varietal physiological differences. To address this, we developed a multimodal data fusion framework integrating RGB and multispectral imagery acquired by unmanned aerial vehicles (UAVs), combined with features derived from Digital Surface Models (DSM), vegetation indices (VIs), texture, and depth representations. Using field data collected across 60 rice varieties, four machine learning models were evaluated for LAI estimation. Our results demonstrate that multimodal fusion substantially outperforms conventional VI-based approaches. Among them, the Random Forest Regression (RFR) model achieved optimal performance (R²=0.76, RMSE=0.57), representing a 26–58% improvement in R² over baseline models. SHAP-based feature importance analysis identified DSM feature, height-stratified vegetation indices, and depth features as key contributors to model accuracy. This study establishes that incorporating canopy structural information and deep features mitigates saturation effects and enhances generalizability across varieties. The proposed approach offers a robust and efficient solution for high-throughput LAI estimation, supporting applications in precision agriculture and rice breeding programs. Reference | Related Articles | Metrics Select Wheat plant architecture modulates radiation use efficiency under regional low-light conditions Tingting Zhu, Zhenyu Liang, Dahai He, Jiabo Chen, Xiulan Huang, Hongkun Yang, Gaoqiong Fan DOI: 10.1016/j.jia.2026.02.001 Online: 07 February 2026 Abstract （2）      PDF in ScienceDirect       Improving radiation use efficiency (RUE) is critical for increasing wheat yield; however, the influence of plant architectural traits on RUE under low-light conditions is poorly understood. In this study, the effects of the architectural traits of wheat plants on RUE under low-light conditions were assessed. Four wheat varieties with distinct canopy architectures were examined: CM88 (erect and involute flag leaves, high spike density), SM1963 (semierect flag leaves, high spike density), SM1868 (drooping flag leaves, small spike size), and SM830 (prostrate flag leaves, large spike size). Their influence on RUE was evaluated via processes of light interception, photosynthetic capacity, and assimilate utilization. The canopy light distribution uniformity decreased progressively: CM88>SM1963 and SM1868>SM830. In contrast, the radiation interception rate in the middle and lower layers was highest in SM1963, followed by CM88/SM1868, and then SM830. CM88 exhibited the highest stomatal area, stomatal conductance (gs), and net photosynthetic rate (Pn), indicating superior photosynthetic capacity. SM1963 and SM1868 showed intermediate gs and Pn (moderate photosynthetic capacity), while SM830 exhibited the lowest gs and Pn (weakest photosynthetic capacity). The key processes governing assimilate utilization—peak activities of sucrose phosphate synthase and sucrose synthase, and the consequent grain filling rate—were highest in SM1963 and SM830. CM88 displayed intermediate levels for these parameters, whereas SM1868 showed the lowest level. Integrating these processes, CM88 and SM1963 achieved the highest overall RUE. This high performance was driven by divergent strengths: CM88 excelled in light interception and photosynthetic capacity with moderate assimilate utilization performance, whereas SM1963 exhibited superior interception and assimilate utilization with moderate photosynthetic capacity. Importantly, light interception contributed the largest share to both RUE and yield, significantly exceeding the contributions from photosynthetic capacity and assimilate utilization, with specific proportions of 51.4 and 74.2%, respectively. This well-coordinated balance among processes, free of any major bottleneck, enabled CM88 and SM1963 to achieve the highest RUE and yield. In conclusion, under low-light conditions, an optimal wheat architecture for high RUE combines erect or semi-erect flag leaves (to optimize light interception) with high spike density (to ensure strong sink capacity). Reference | Related Articles | Metrics Select Multi-omics analysis revealed adaptation mechanisms in roots of different nitrogen-efficiency peanut genotypes under low-nitrogen stress Ping Zhang, Yongqi Liu, Xiuli Wang, Pei Guo, Fei Liu, Xinhua Zhao, He Zhang, Jing Wang, Chao Zhong, Xiaoguang Wang, Chunji Jiang, Haiqiu Yu DOI: 10.1016/j.jia.2026.01.046 Online: 02 February 2026 Abstract （14）      PDF in ScienceDirect       Overapplication of nitrogen (N) is an important limiting factor in sustainable agricultural development. Breeding N-efficient genotypes is an effective approach to reduce crop N input, increase N-efficiency, and improve crop productive. However, the molecular mechanisms underlying low-N adaptations in peanut (Arachis hypogaea L.) roots are unknown. Herein, we compared root adaptation mechanisms to low-N stress between the N-efficient genotype JH15 (JH) and the N-inefficient genotype HY20 (HY), focusing on N metabolism and antioxidant capacity. Under N deficiency, JH exhibited a more developed root architecture, higher antioxidant activity, and higher N-metabolic enzyme levels under N deficiency. The expression of both high- and low-affinity nitrate transporter proteins (NRT2.5, NRT1.6), and the chloride channel protein CLC was upregulated in JH, with higher expression of genes encoding glutamine synthetase and asparagine synthase. However, only the low-affinity N transporters (NPF5.2, NPF7.3) were upregulated in HY. Flavonoid and isoflavonoid biosynthesis were the main metabolic pathways underlying the differences between the two genotypes under low-N treatment. The results of weighted gene co-expression network analysis and correlation network analysis revealed that differential expression of the key genes encoding caffeoyl-CoA O-methyltransferase, chalcone synthase, 2'-hydroxyisoflavone reductase, and shikimate hydroxycinnamoyl-CoA transferase affected key metabolites levels (epicatechin, kaempferol, calycosin, and biochanin A). We also found that WRKY40 and MYB30, MYB4, and bHLH35 may regulate flavonoids accumulation as positive and negative regulators, respectively. In summary, enhanced N uptake and assimilation and flavonoid accumulation in JH enhanced N metabolism and antioxidant capacity, improving N-efficiency. Reference | Related Articles | Metrics Select Quantitative evaluation of storage tolerance in the eating and cooking quality of rice varieties from southern China Dawei Zhu, Xin Zheng, Huiying Dong, Wenting Xu, Yafang Shao, Mingxue Chen DOI: 10.1016/j.jia.2026.01.047 Online: 02 February 2026 Abstract （11）      PDF in ScienceDirect       This study aimed to characterize variation in the storage tolerance of eating and cooking quality (ECQ) among rice varieties from Southern China and to establish a quantitative evaluation framework. Indica, japonica, and indica–japonica hybrid rice varieties were subjected to accelerated aging under high-temperature and high-humidity conditions (35°C, 75% RH) for 90 days. Nineteen indices encompassing ECQ traits, chemical composition, pasting properties, amylase activity, lipoxygenase (LOX) activity, and antioxidant enzyme activities were determined before and after storage. The storage variation coefficient of individual indices (SVCI) and a newly developed paddy rice storage tolerance index (PRSI) were used for integrated evaluation. Principal component analysis, grey relational analysis, and stepwise regression analysis were applied to identify key indicators and construct a predictive model. ECQ deteriorated significantly after storage, with pronounced changes (mean SVCI>0.2) observed in fatty acid value (FAV), cooked rice appearance (CRA), cooked rice texture (CRT), comprehensive taste value (CTV), and antioxidant enzyme activities. PRSI values ranged from 0.257 to 0.609, with higher PRSI values indicating more rapid ECQ deterioration during storage. Cluster analysis classified the varieties into storage-tolerant, moderately storage-tolerant, and storage-sensitive groups. Compared with storage-sensitive varieties, storage-tolerant varieties showed markedly smaller declines in CRA, CRT, and CTV (mean reductions lower by 45.8, 40.9, and 49.3%, respectively), a weaker increase in FAV (mean lower by 28.3%), and consistently higher antioxidant enzyme activities, with SOD and POD activities exceeding those of storage-sensitive varieties by 19.7 and 10.0%, respectively, in both fresh and stored samples. These results demonstrate that PRSI is an effective index for evaluating ECQ storage tolerance. The SVCIs of CTV, FAV, and POD activity were identified as key predictors of PRSI. This work provides a robust methodological basis for breeding storage-tolerant rice varieties and for developing quality-preserving storage strategies in southern rice-growing regions.  Reference | Related Articles | Metrics Select Knockdown of OsCOI1 increases rice yield under normal conditions and compromises thermotolerance during panicle differentiation Dongling Ji, Xiaowu Yan, Yu Wei, Yunxia Han, Weiyang Zhang, Lijun Liu, Hao Zhang, Zhiqing Wang, Zujian Zhang, Jianchang Yang, Weilu Wang DOI: 10.1016/j.jia.2026.01.048 Online: 02 February 2026 Abstract （10）      PDF in ScienceDirect       Although jasmonate (JA) signaling participates in heat stress (HS) responses, the mechanism by which it balances spikelet development and yield stability via the OsCOI1 gene remains unclear, particularly under HS during the panicle differentiation stage (PDS). This study comprehensively examined the influence of HS on panicle architecture, carbon (C) and nitrogen (N) metabolism, accumulation and allocation, root oxidative activity, antioxidant enzyme activity, JA and methyl jasmonate (MeJA) contents, yield and yield components using wild-type rice (WT, Nipponbare) and the coi1-18 mutant (OsCOI1 knockdown mutant, blocked JA signaling). The results demonstrated that under normal temperature (NT) conditions, the coi1-18 mutant exhibited significantly higher grain number per panicle, grain setting rate, and 1000-grain weight relative to the WT, collectively increasing grain yield by 23.2%. Conversely, under HS, reduced JA and MeJA contents in the coi1-18 mutant resulted in enhanced heat sensitivity, diminished antioxidant capacity, and dysregulated C-N metabolism. These effects markedly suppressed spikelet differentiation, thereby causing a yield reduction in the coi1-18 mutant that was 16.1 percentage points greater than in WT. Exogenous MeJA application effectively mitigated HS-induced suppression of spikelets differentiation in WT but failed to significantly rescue the phenotype in the coi1-18 mutant. This study reveals OsCOI1 as a context-dependent regulator: knockdown of OsCOI1 enhances yield under NT but impairs HS tolerance during PDS. This indicates a breeding-relevant trade-off and suggests that modulating JA signaling could balance yield under NT with panicle protection under HS. Reference | Related Articles | Metrics Select Commentary: Roles of metal-organic frameworks in sustainable agriculture - A critical overview Wei Zhou DOI: 10.1016/j.jia.2026.01.045 Online: 30 January 2026 Abstract （6）      PDF in ScienceDirect       Related Articles | Metrics Select Regulation mechanism of parental row ratio on seed-setting rate in hybrid rice seed production based on pollination Bangchao Huang, Tao Wang, Youfeng Tao, Qin Qin, Boteng Sun, Jinyue Guo, Hui Li, Ruicen Liu, Tiantian Deng, Qi Liu, Xiaolong Lei, Wei Zhou, Yong Chen, Fei Deng, Wanjun Ren DOI: 10.1016/j.jia.2026.01.044 Online: 30 January 2026 Abstract （13）      PDF in ScienceDirect        Mechanized seed production with a large restorer-to-sterile parental row ratio is a developmental trend; however, the effects of different parental row ratios on spikelet pollination effectiveness and seed-setting rates remain unclear. In this study, a single-factor randomized block experiment was conducted in Sichuan, China, to evaluate the influence of parental row ratio designs on spikelet pollination effectiveness and seed-setting rate in sterile lines under unmanned aerial vehicle-assisted pollination conditions. In 2021 and 2022, R2 treatment significantly reduced the number of pollen grains and pollen grain number per spikelet position in the middle (M) and far (F) rows of the plot. However, this treatment yielded a significantly higher pollination rate of exposed stigma florets at each spikelet position in the near (N) and middle rows when compared to the results of the R1 and R3 treatments, resulting in a greater seed-setting rate. The number of pollen grains per stigma (1–3) did not significantly differ among the R1, R2, and R3 patterns in 2022. Over 50% of successfully pollinated florets had pollen loaded on a single stigma. In the C1 combination, the seed-setting rate of R2 increased by 43.07% (vs. R1) and 34.23% (vs. R3), with yield increases of 42.35% (vs. R1) and 18.53% (vs. R3). In the C2 combination, R2 seed-setting rate increased by 13.75% (vs. R1) and 34.62% (vs. R3), with final yield increases by 14.87% (vs. R1) and 29.80% (vs. R3). The R2 pattern reduced pollen loss by optimizing the matching degree between pollination wind field and parental strip width, providing a stable pollen supply for the sterile lines (N, M). This supply enhanced stigma pollen capture, thereby significantly increasing floret pollination rates, seed-setting rates, and yield. This study provides a theoretical basis and practical guidance for pollination strategies and optimization of parental row ratios in mechanized seed production. Reference | Related Articles | Metrics Select Phased dynamic analysis and prediction of rice Chilo suppressalis integrating remote sensing physiological indices and environmental factors Yuchen Wu, Lihua Wang, Yanxiao Bao, Weiwei Sun, Zhiyuan Yao, Gang Yang, Yumiao Wang DOI: 10.1016/j.jia.2026.01.043 Online: 30 January 2026 Abstract （13）      PDF in ScienceDirect       Chilo suppressalis is a major pest in rice-producing regions, posing serious threats to rice yield and quality. Existing pest prediction research generally ignore the stage-specific heterogeneity in population dynamics and neglect the synergistic effects among meteorological, soil, and rice physiological information. This makes it challenging to accurately characterize the complete dynamic changes in pest populations. In this study, we explicitly highlight three methodological innovations: (1) the use of a LOESS-based curve fitting and slope-change detection framework to objectively partition C. suppressalis population dynamics into three stages—population establishment, expansion, and outbreak; and (2) the integration of multi-source data, including trap monitoring, rice physiological indices derived from remote sensing, and ERA5 meteorological and soil variables, to construct stage-specific prediction models.; and (3) building upon this stage-based framework, we designed a targeted sensitivity-parameter screening scheme and developed daily dynamic prediction models using the Random Forest (RF) algorithm, which incorporate meteorological, soil, and crop physiological indicators. The results demonstrate that the proposed stage-specific prediction model achieves excellent performance. During the outbreak stage, the R2 for all three experimental fields exceeds 0.9, with MAE below 23.16 and RMSE under 32.86. In the Jiulong field, stage-specific predictions show R2 values above 0.89. Compared with Long Short Term Memory (LSTM) and Prophet models, RF exhibits superior stability and generalization, with test set R² consistently above 0.69, highlighting its robustness and reliability for stage-specific prediction of C. suppressalis population dynamics. These findings highlight the practical value of our approach for enhancing comprehensive pest forecasting and supporting targeted pest management. Reference | Related Articles | Metrics Select Implementing strip configurations in cotton-soybean intercropping systems improves crop productivity and optimizes land use efficiency Qiyuan Guo, Zhitao Liu, Wenchao Zhao, Jianli Zhou, Xuanshuang Zhang, Lunxiao Shang, Jiaxue Zhao, Han Wang, Longhao Zhou, Yuanchao Fang, Lingyan Dong, Hongxin Qi, Ruming Wang, Baltaevich Ahmedov Miraziz, Xiaopei Zhang, Aziz Khan, Lili Mao, Xianliang Song DOI: 10.1016/j.jia.2026.01.042 Online: 30 January 2026 Abstract （6）      PDF in ScienceDirect       Strip configurations play a crucial role in mediating crop productivity and resource utilization in intercropping systems. However, there remains a substantial knowledge gap concerning the mechanization-adaptive strip widths for cotton-soybean intercropping systems. Specifically, understanding how these strip widths can enhance synergies in crop productivity and land use efficiency is imperative. This study evaluated the impact of row ratio (strip) configurations on crop growth, physiology, productivity and land use efficiency in intercropped and monoculture systems. Treatments included two intercropping treatments (two rows of cotton plants alternating with three rows of soybean plants (2C3S), and three rows of cotton alternating with five rows of soybean (3C5S)), and two monoculture controls (monoculture cotton (MC), and monoculture soybean (MS)). Compared with monoculture cotton, the 3C5S system significantly increased both years averaged based chlorophyll content (SPAD value) by 6.64% at the peak boll-setting stage with increased leaf area index (LAI) and canopy photosynthetically active radiation interception ratio (In) during the early flowering stage. Furthermore, at the boll-opening stage, this system further enhanced boll and total plant nitrogen uptake. Intercropping significantly increased cotton boll density by enhancing dry matter translocation to reproductive organs with high lint yield. The 3C5S configuration outperformed 2C3S, increased the land equivalent ratio by 9.2% and net revenue by 15.87% over both years. The PCA results showed stronger relationships between cotton harvest index and other physiological parameters in 3C5S. The Mantel test indicates that yield of cotton-soybean intercropping was closely associated with cotton leaf area index and soybean aboveground biomass. Structural equation modeling identified nitrogen uptake as the key driver of yield in 3C5S. Overall, 3C5S improved crop productivity and land use efficiency compared to both 2C3S and monoculture systems, representing the optimal cotton-soybean intercropping strategy. The 2C3S and 3C5S intercropping systems were designed with a standard 2:1 row spacing (76 cm for cotton and 38 cm for soybean), compatible with mainstream agricultural machinery in China. A 55 cm operational clearance was maintained between crop strips to support fully mechanized sowing and harvesting, thereby reducing labor cost with high production revenue. Reference | Related Articles | Metrics Select Stellera chamaejasme L. induced changes to soil in Chinese grasslands vary with context and location Wei He, Jiahuan Li, John Scullion, Na Li, Congcong Xu, Jun Luo, Mike Wilkinson, Lifen Hao, Yuyu Li, Kejian Lin, Lizhu Guo DOI: 10.1016/j.jia.2026.01.041 Online: 29 January 2026 Abstract （8）      PDF in ScienceDirect       Stellera chamaejasme is a pernicious plant of grasslands in China. Its expansion has been linked to changes in the soil microbial community structure and to nitrogen accumulation. Increased nitrogen availability may enhance competitiveness of the weed and disrupt plant community structure. We sought to establish whether presence of this species evokes the same changes to soil properties and microbiome community structure in regions with divergent native soil properties. For this, we compared soil samples collected from under native vegetation (controls) with those taken from beneath S. chamaejasme plants in grasslands of eastern Qinghai–Tibet Plateau (QT) and the middle Inner Mongolia Plateau (IM). In QT, soil beneath S. chamaejasme contained higher nitrogen levels than controls, but not phosphorus. In contrast, S. chamaejasme and control soil samples from IM did not differ in nitrogen content, but S. chamaejasme soil samples had raised soil P. Soil bacterial community responses to S. chamaejasme also differed between regions. S. chamaejasme soils from QT had increased relative abundances of some diazotrophs (Bradyrhizobium, Mesorhizobium, Phyllobacterium) that positively correlated with soil nitrogen but no similar tends were detected in IM soils. Redundancy analysis revealed significant associations between soil ammonium and bacterial genera implicated in soil N-cycles. In QT, modelling suggested that S. chamaejasme increased N-cycling soil bacteria linked to increased available nitrogen. However, in IM soil N-cycling soil bacteria and soil nitrogen levels were unaffected by S. chamaejasme and its presence did not link to N-based soil changes. We conclude that S. chamaejasme evokes different changes to the native soils of these two regions. We postulate that S. chamaejasme may exhibit plasticity in response to soil conditions it encounters and that this may be one reason for its soil impact being context dependent. This divergent interaction between S. chamaejasme and host soils may facilitate further expansion of its current range.  Reference | Related Articles | Metrics Select Identification and functional validation of five cytochrome P450 monooxygenase genes conferring cyantraniliprole resistance in Bemisia tabaci Xiaolan Liu, Zhuang Zhang, Kaixin Li, Zanrong Wen, Wei Xu, Huiwen Tan, Xichao Hu, Lei Guo DOI: 10.1016/j.jia.2026.01.040 Online: 29 January 2026 Abstract （11）      PDF in ScienceDirect       The whitefly, Bemisia tabaci, is a major agricultural pest that has developed resistance to a broad range of insecticides. Despite the promising efficacy of cyantraniliprole (CYA) against B. tabaci, medium to high levels of resistance have emerged after prolonged field use. However, the mechanisms driving CYA resistance remain poorly understood. In this study, four B. tabaci strains exhibiting 24.9-fold to 28.9-fold resistance ratio to CYA were investigated. Synergist assays and enzyme activity measurements indicated cytochrome P450 enzymes contribute to this resistance. RNA sequencing and RT-qPCR analysis identified five P450 genes (CYP305H2, CYP6EM1, CYP3133D3, CYP3133D5, and CYP3133E2) as significantly overexpressed in resistant strains. Targeted silencing of these genes led to a 22.3% to 50.3% increase in CYA toxicity. The metabolic rates of these P450 enzymes against CYA were 2.5- to 6.0-fold higher than that in the control group within two hours. These results provide new insights into the molecular basis of CYA resistance in B. tabaci and highlight the pivotal role of cytochrome P450 enzymes in metabolic adaptation to diamide insecticides. Reference | Related Articles | Metrics page Page 1 of 20 Total 390 records First page Prev page Next page Last page