[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4210":3,"related-4210":132},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":93,"slug":96,"view_count":97,"doi":98,"paper":99,"created_at":131},4210,"Nutrient cycling, environmental outcomes and mitigation pathways in sugarcane agroecosystems: A comparative synthesis of Brazil and Australia","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.agee.2026.110780","Sugarcane is a major tropical crop with strong potential to support climate-smart agriculture through efficient nutrient cycling, improved nitrogen use efficiency, biofuel production and enhanced soil carbon dynamics. However, environmental outcomes vary substantially across production systems. This review compares two leading high-efficiency sugarcane systems, Brazil and Australia, examining nutrient cycling, greenhouse gas emissions, nutrient losses and soil organic carbon storage. In Brazil, large-scale rainfed operations (commonly exceeding 10,000 ha) promote high organic inputs through residue retention and recycling of vinasse and filter cake, enhancing soil carbon stocks and internal nutrient recycling; however, these practices can elevate nitrogen losses and greenhouse gas emissions when poorly synchronised with crop demand. In Australia, smaller family-owned systems (~95 ha) operate under environmental regulations and the Six Easy Steps framework, where soil-test–based management, subsurface fertiliser placement and enhanced-efficiency fertilisers target nutrient transport to Great Barrier Reef catchments. Fertiliser-N use in Australian sugarcane has progressively declined to among the lowest rates globally for the crop; however, nitrogen use efficiency remains relatively low compared with Brazil, and off-site nutrient losses have not been fully resolved at scale. Soil compaction is a critical constraint in both countries, addressed by complementary strategies: satellite-guided controlled traffic farming in Australia and strategic subsoil tillage with GPS-guided traffic in Brazil. Across both systems, residue retention, legume rotations and reduced tillage improve nutrient cycling and soil carbon accumulation. Integrating Brazil's nutrient-recycling scale with Australia's precision management offers a convergent pathway to enhance nitrogen use efficiency, reduce environmental footprints and improve sugarcane agroecosystem sustainability.","甘蔗是一种重要的热带作物，通过高效的养分循环、提高氮利用效率、生物燃料生产以及增强土壤碳动态，具有支持气候智慧型农业的巨大潜力。然而，不同生产体系的环境效益差异显著。本文综述比较了巴西和澳大利亚两个领先的高效甘蔗生产体系，考察了养分循环、温室气体排放、养分损失和土壤有机碳储量。在巴西，大规模雨养作业（通常超过10,000公顷）通过保留残茬以及回收利用酒糟（vinasse）和滤泥（filter cake）促进高有机投入，提升了土壤碳储量和内部养分循环；然而，当这些做法与作物需求同步不佳时，可能导致氮损失和温室气体排放增加。在澳大利亚，较小的家庭经营体系（约95公顷）在环境法规和“六步简易法”（Six Easy Steps）框架下运行，以土壤测试为基础的管理、肥料深施和增效肥料（enhanced-efficiency fertilisers）针对大堡礁集水区的养分迁移进行调控。澳大利亚甘蔗的肥料氮使用量已逐步下降至全球该作物最低水平之列；然而，与巴西相比，氮利用效率仍然相对较低，且异地养分损失尚未在大规模上得到完全解决。土壤压实是两国共同面临的关键限制因素，通过互补策略加以应对：澳大利亚采用卫星导航控制交通耕作（controlled traffic farming），巴西采用GPS导航交通下的战略性心土耕作（subsoil tillage）。在两个体系中，残茬保留、豆科轮作和减少耕作均改善了养分循环和土壤碳积累。将巴西的养分回收规模与澳大利亚的精准管理相结合，为提升氮利用效率、减少环境足迹和提高甘蔗农业生态系统可持续性提供了一条趋同路径。",null,"Agriculture Ecosystems & Environment","2026-10-04T00:00:00Z","论文",10,false,80,{"impact":17,"substance":18,"depth":17,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,14,8,1,"核心期刊发表的巴西与澳大利亚甘蔗系统对比综述，数据与结论扎实，对养分管理与减排路径有参考价值，但属学术综述、非政策或产业事件，时效性一般。",[24],{"name":10,"url":6},[26,27,28,29,30,31],"甘蔗","巴西","土壤固碳","养分循环","氮肥利用率","澳大利亚",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"A6","cash-crops","棉麻糖与特色经作","\u002Ftopic\u002Ffield-crops\u002Fcash-crops","A",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,52,60,68,75,81,87],{"code":33,"score":46,"supported":47,"title":48,"abstract":50,"tags":51},15,true,[49],"sugarcane",[26,49],[26],{"code":53,"score":54,"supported":47,"title":55,"abstract":56,"tags":59},"H2",7,[],[57,58],"土壤","soil",[28],{"code":61,"score":62,"supported":47,"title":63,"abstract":64,"tags":67},"B7",6,[],[65,66],"温室","greenhouse",[],{"code":69,"score":70,"supported":47,"title":71,"abstract":72,"tags":74},"A7",3,[],[73],"轮作",[],{"code":76,"score":70,"supported":47,"title":77,"abstract":78,"tags":80},"F3",[],[79],"肥料",[],{"code":82,"score":70,"supported":47,"title":83,"abstract":84,"tags":86},"H6",[],[85],"农业生态",[],{"code":88,"score":70,"supported":47,"title":89,"abstract":90,"tags":92},"I1",[],[91],"smart agriculture",[],[94,95],"巴西 澳大利亚 甘蔗 养分循环","甘蔗 氮肥利用率 土壤固碳","巴西澳大利亚甘蔗养分循环-4210",0,"10.1016\u002Fj.agee.2026.110780",{"doi":98,"openalex_id":100,"authors":101,"venue":10,"cited_by_count":97,"oa_url":6,"card":123,"direction":129,"ingested_from":130},"W7218417513",[102,105,108,111,114,117,120],{"name":103,"orcid":104},"Juan Ricardo Rocha","https:\u002F\u002Forcid.org\u002F0000-0003-0590-655X",{"name":106,"orcid":107},"Nicole Robinson","https:\u002F\u002Forcid.org\u002F0000-0001-6285-6179",{"name":109,"orcid":110},"Dalila Lopes da Silva","https:\u002F\u002Forcid.org\u002F0000-0003-4972-5945",{"name":112,"orcid":113},"Kristopher Woodrow-Smith","https:\u002F\u002Forcid.org\u002F0009-0008-4475-7108",{"name":115,"orcid":116},"Prakash Lakshmanan","https:\u002F\u002Forcid.org\u002F0000-0003-1725-0391",{"name":118,"orcid":119},"Cassio Hamilton Abreu–Junior","https:\u002F\u002Forcid.org\u002F0000-0002-5955-4652",{"name":121,"orcid":122},"Susanne Schmidt","https:\u002F\u002Forcid.org\u002F0000-0001-8369-1238",{"tldr":124,"method":125,"finding":126,"direction":127,"opportunity":128},"综述比较巴西与澳大利亚甘蔗农业生态系统的养分循环、环境效应及减排路径。","文献综述，对比两国甘蔗系统的养分管理、温室气体与土壤碳数据。","巴西靠规模回收、澳大利亚靠精准管理，整合二者可提升氮效率并减排。","农业绿色发展与碳","可量化整合巴西养分回收与澳大利亚精准管理对氮效率及碳汇的协同效应。","智慧农业 \u002F 农业物联网","openalex","2026-10-05T23:30:08.942071Z",{"total":62,"page":21,"page_size":62,"items":133},[134,196,242,329,374,419],{"id":135,"title":136,"url":137,"summary":138,"summary_zh":139,"content":9,"source_name":140,"source_url":137,"published_at":141,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":142,"score_detail":143,"sources":149,"tags":151,"primary_topic":156,"secondary_topics":157,"classification":158,"search_phrases":175,"slug":178,"view_count":21,"doi":179,"paper":180,"created_at":195},5234,"A smart agriculture-oriented cross-attention multiscale CNN for sugarcane disease diagnosis","https:\u002F\u002Fdoi.org\u002F10.1080\u002F23080477.2026.2749739","Sugarcane leaf diseases can adversely affect crop health and yield, making timely disease identification important for smart agriculture. Manual inspection of leaf diseases is time-consuming and requires expert knowledge, particularly when large cultivation areas need to be monitored. To tackle this problem, this study proposes a Cross-Attention Multiscale Parallel Convolutional Neural Network for automatic classification of sugarcane leaf diseases. This framework comprises a Parallel Feature Extraction Stem, cross-attention mechanism, Dense Connection Blocks, and Inception Blocks to learn disease features at various spatial scales. The PFES extracts fine and broad disease patterns using parallel convolutional branches, while the cross-attention mechanism refines the extracted features by emphasizing disease-related information. The DCB supports feature propagation and reuse, and the IB further captures multi-scale feature representations. The proposed model was tested on two benchmark datasets of leaf diseases for sugarcane plants. The proposed framework obtained an accuracy (98.79%), precision (98.31%), recall (97.81%), specificity (98.60%), and F1-Score (98.05%). For assessing the classification accuracy and consistency of the framework, the comparative study, ablation studies, and five-fold cross-validation are carried out. The results show that CA-MPCNN provides accurate sugarcane leaf disease classification and can support automated disease diagnosis in smart agriculture applications.","甘蔗叶片病害会对作物健康与产量造成不利影响，因此及时识别病害对智慧农业具有重要意义。人工检查叶片病害耗时且需要专业知识，尤其是在需要监测大面积种植区域时。为解决该问题，本研究提出一种用于甘蔗叶片病害自动分类的交叉注意力多尺度并行卷积神经网络（Cross-Attention Multiscale Parallel Convolutional Neural Network）。该框架由并行特征提取主干（Parallel Feature Extraction Stem）、交叉注意力机制、密集连接块（Dense Connection Blocks）和Inception块组成，用于学习不同空间尺度上的病害特征。PFES通过并行卷积分支提取细粒度与广域病害模式，而交叉注意力机制通过强调病害相关信息对提取的特征进行细化。DCB支持特征传播与复用，IB进一步捕获多尺度特征表示。所提出的模型在两个甘蔗植株叶片病害基准数据集上进行了测试。该框架取得了准确率（98.79%）、精确率（98.31%）、召回率（97.81%）、特异性（98.60%）和F1分数（98.05%）。为评估该框架的分类准确性和一致性，开展了对比研究、消融研究和五折交叉验证。结果表明，CA-MPCNN能够实现准确的甘蔗叶片病害分类，并可支持智慧农业应用中的自动化病害诊断。","Smart Science","2026-10-17T00:00:00Z",69,{"impact":144,"substance":145,"depth":146,"authority":144,"freshness":147,"relevant":21,"comment":148},12,20,16,9,"该研究提出一种面向甘蔗叶部病害自动分类的交叉注意力多尺度CNN，在两个基准数据集上准确率达98.79%，方法新颖、实验充分，但属于细分作物应用研究，产业影响有限，时效性强，值得进入每日精选。",[150],{"name":140,"url":137},[152,153,26,154,155],"智慧农业","农业人工智能","深度学习","病害诊断",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":159},{"candidates":160,"agricultural_evidence":47},[161,165,169],{"code":33,"score":46,"supported":47,"title":162,"abstract":163,"tags":164},[49],[26,49],[26],{"code":88,"score":46,"supported":47,"title":166,"abstract":167,"tags":168},[91],[152,91],[152],{"code":170,"score":171,"supported":14,"title":172,"abstract":173,"tags":174},"I2",2,[],[],[153,154],[176,177],"甘蔗 叶部病害 智能诊断","CA-MPCNN 甘蔗 病害","甘蔗叶部病害智能诊断-5234","10.1080\u002F23080477.2026.2749739",{"doi":179,"openalex_id":181,"authors":182,"venue":140,"cited_by_count":97,"oa_url":9,"card":189,"direction":129,"ingested_from":130},"W7222832245",[183,185,187],{"name":184,"orcid":9},"Bala Subramanian Chokkalingam",{"name":186,"orcid":9},"Uvarani Meenrajan",{"name":188,"orcid":9},"Shanmugapriya Sankaran",{"tldr":190,"method":191,"finding":192,"direction":193,"opportunity":194},"提出交叉注意力多尺度并行CNN，实现甘蔗叶病自动分类。","并行卷积分支、交叉注意力、密集连接与Inception块，两个基准数据集验证。","模型准确率达98.79%，消融与五折交叉验证证明其有效稳定。","农业人工智能与决策模型","可探索田间复杂背景与轻量化部署，并扩展到多作物病害实时诊断。","2026-10-18T23:30:07.777036Z",{"id":197,"title":198,"url":199,"summary":200,"summary_zh":9,"content":9,"source_name":201,"source_url":9,"published_at":202,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":142,"score_detail":203,"sources":207,"tags":209,"primary_topic":212,"secondary_topics":213,"classification":214,"search_phrases":229,"slug":232,"view_count":21,"doi":9,"paper":233,"created_at":241},4965,"Uncertainty-Aware Semi-Supervised Framework with Supervised Contrastive Learning for Sugarcane Leaf Disease Detection [预印本]","https:\u002F\u002Farxiv.org\u002Fabs\u002F2610.17996","Shalini Dangi等提出基于Mean-Teacher半监督学习的不确定性感知病害检测网络U-SSDNet,用于甘蔗叶病检测。论文针对(i)同一病害在不同生育期表现差异大,(ii)病健组织类间相似,(iii)标签噪声等问题,先以离散小波变换增强病斑并降低类内差异,再用KL散度优化伪标签减轻确认偏差,同时引入监督对比学习提升类间区分度。甘蔗叶病数据集上的实验显示,U-SSDNet仅需少量标注即可接近全监督模型精度,显著优于当前主流监督与半监督方法。","arXiv 2610.17996 2026 年 10 月 13 日","2026-10-13T00:00:00Z",{"impact":144,"substance":145,"depth":204,"authority":205,"freshness":147,"relevant":21,"comment":206},17,11,"预印本提出不确定性感知半监督框架，方法新颖且少标注下接近全监督精度，对作物病害智能识别有参考价值，但尚属实验室阶段成果。",[208],{"name":201,"url":199},[152,153,26,210,211],"病害检测","半监督学习",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":215},{"candidates":216,"agricultural_evidence":47},[217,221,225],{"code":33,"score":144,"supported":47,"title":218,"abstract":219,"tags":220},[49],[26],[26],{"code":88,"score":21,"supported":14,"title":222,"abstract":223,"tags":224},[],[],[152],{"code":170,"score":21,"supported":14,"title":226,"abstract":227,"tags":228},[],[],[153],[230,231],"甘蔗叶病 检测 半监督学习","U-SSDNet 甘蔗","甘蔗叶病检测半监督学习-4965",{"doi":9,"openalex_id":9,"authors":234,"venue":9,"cited_by_count":97,"oa_url":9,"card":235,"direction":193,"ingested_from":240},[],{"tldr":236,"method":237,"finding":238,"direction":193,"opportunity":239},"提出半监督不确定性感知网络U-SSDNet，用少量标注实现甘蔗叶病高精度检测。","Mean-Teacher半监督、离散小波变换、KL散度伪标签优化、监督对比学习。","仅需少量标注即接近全监督精度，显著优于主流监督与半监督方法。","可将该不确定性半监督框架迁移至其他作物病害，并探索田间复杂光照与多生育期泛化。","agent","2026-10-15T00:06:08.498104Z",{"id":243,"title":244,"url":245,"summary":246,"summary_zh":247,"content":9,"source_name":248,"source_url":245,"published_at":249,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":250,"score_detail":251,"sources":254,"tags":256,"primary_topic":261,"secondary_topics":262,"classification":267,"search_phrases":294,"slug":297,"view_count":97,"doi":298,"paper":299,"created_at":328},4797,"Beyond single-element toxicity: chromium-salinity interactions, food-chain transfer and mitigation in sugarcane agroecosystems","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1942892","Chromium contamination in sugarcane soils is often combined with co-metals and salinity caused by tannery effluent, electroplating effluent, paper mill wastewater, vinasse fertigation and filter cake. Hence, single element toxicity assessment does not provide realistic assessment of its exposure. The present review summarizes research on chromium behaviour along the soil, root, stalk and cane juice in sugarcane. Cr mobility depends on soil pH and redox potential (Eh), while salinity adds an additional control through ionic strength and chloride complexation. Sequential extraction and speciation analysis prove that bioavailable fraction is more important for plant toxicity than total Cr concentration. Cr(VI) enters roots via sulphate and phosphate transporters via mimicking oxyanions and this mechanism differs from that of other metal ions that use ion channels, a route that salt-induced PHT1 expression could plausibly modulate, although this has not been tested in sugarcane. In proxy species, combined Cr and salinity exposure raises reactive oxygen species production and membrane damage beyond the level induced by either stress alone, whereas in sugarcane the downregulation of PEP carboxylase, pyruvate orthophosphate dikinase and photosystem proteins has so far been documented only under salinity applied by itself. Whether the two stresses interact on C4 carbon assimilation in cane remains untested. Root-to-stalk transfer of Cr is low at most sites examined, but not at all of them, and measurable Cr reaches cane juice at concentrations that have driven hazard quotients above unity in two of the four field studies assessed. Bagasse biochar, biochar with nZVI, halotolerant Cr-reducing microorganisms and water management based on redox reactions all reduce Cr bioavailability, but field experiments in cane are lacking. Factorial experiments investigating Cr behaviour depending on salinity gradient, juice level speciation and field trials in ratoons are required.","甘蔗土壤中的铬污染通常与制革废水、电镀废水、造纸厂废水、酒糟灌溉和滤泥带入的伴生金属及盐分复合存在。因此，单一元素毒性评估无法对其暴露状况作出符合实际的评价。本文综述了铬在甘蔗土壤、根系、茎秆及蔗汁中行为的研究进展。铬的迁移性取决于土壤pH和氧化还原电位（Eh），而盐分通过离子强度和氯络合作用对其施加额外调控。连续提取和形态分析表明，生物有效态组分对植物毒性的意义大于总铬浓度。Cr(VI)通过模拟含氧阴离子经硫酸盐和磷酸盐转运蛋白进入根系，这一机制不同于其他利用离子通道的金属离子，而盐诱导的PHT1表达可能调控该途径，但尚未在甘蔗中验证。在替代物种中，铬与盐分复合暴露引起的活性氧产生和膜损伤超过单一胁迫诱导的水平，而在甘蔗中，磷酸烯醇式丙酮酸羧化酶、丙酮酸磷酸双激酶和光系统蛋白的下调目前仅在单独盐胁迫下得到证实。两种胁迫是否在甘蔗C4碳同化过程中发生交互作用仍未经检验。在多数已考察的位点，铬从根系向茎秆的转移量较低，但并非所有位点均如此；在所评估的四项田间研究中，有两项显示可检测到的铬到达蔗汁，其浓度已使危害商数超过1。蔗渣生物炭、负载纳米零价铁（nZVI）的生物炭、耐盐铬还原微生物以及基于氧化还原反应的水分管理均可降低铬的生物有效性，但甘蔗田间试验尚属缺乏。有必要开展考察铬行为随盐度梯度变化的析因实验、蔗汁水平上的形态分析以及宿根蔗田间试验。","Frontiers in Sustainable Food Systems","2026-10-12T00:00:00Z",74,{"impact":144,"substance":18,"depth":17,"authority":252,"freshness":147,"relevant":21,"comment":253},13,"综述系统梳理铬-盐交互、食物链迁移与阻控手段，指出甘蔗田间试验空白，对污染蔗区安全利用有参考价值，但属机理综述、非产业级突破。",[255],{"name":248,"url":245},[26,257,258,259,260],"食品安全","盐渍化","土壤重金属","生物炭修复",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[263],{"code":53,"slug":58,"name":264,"path":265,"parent_code":266},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",{"status":40,"locked":14,"version":41,"method":42,"evidence":268},{"candidates":269,"agricultural_evidence":47},[270,274,278,283,289],{"code":33,"score":46,"supported":47,"title":271,"abstract":272,"tags":273},[49],[26,49],[26],{"code":53,"score":20,"supported":47,"title":275,"abstract":276,"tags":277},[],[57,58],[259,258],{"code":76,"score":70,"supported":47,"title":279,"abstract":280,"tags":282},[],[281],"fertigation",[],{"code":284,"score":70,"supported":47,"title":285,"abstract":286,"tags":288},"H3",[],[287],"灌溉",[],{"code":290,"score":21,"supported":14,"title":291,"abstract":292,"tags":293},"E4",[],[],[257],[295,296],"甘蔗 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**二、活动时间**\n\n2026年9月23日\n\n上午场：8:30-10:30\n\n下午场：14:30-17:00\n\n## **三、活动地点**\n\n云南省开远市灵泉东路 363号 云南省农业科学院甘蔗研究所\n\n核心体验区域：专题科普讲座会议室、国家甘蔗种质资源圃、育种创新基地、分子细胞实验室、蔗糖深加工及副产物综合利用实验室\n\n## **四、邀约对象**\n\n1.青少年群体：开远及周边中小学师生（重点邀约）；\n\n2.社会群体：市民家庭、农业科普爱好者；\n\n3.行业群体：种业企事业单位技术人员、甘蔗育种科研工作者、基层农技人员。\n\n## **五、活动内容**\n\n本次活动采用**专题讲座+导览参观+实物展示+科研演示+互动品鉴**的沉浸式科普模式，全程由一线科研人员现场讲解答疑。\n\n**1. 分层专题科普讲座**\n\n面向青少年开设趣味科普课堂，讲解甘蔗起源传播、种质资源保护、育种基础知识、良种赋能产业丰收等内容，以通俗语言解锁甘蔗种业科技奥秘；面向行业同仁开展专项交流，重点推介抗逆、抗病、高糖等优异甘蔗种质资源，分享种质性状数据与育种应用方向，搭建种质资源共享合作桥梁。\n\n**2. 全场景科研观摩体验**\n\n实地参观国家甘蔗种质资源圃，直观感受甘蔗种质资源多样性；走进育种创新基地，观摩实生苗群体、优质新品系及突破性主栽品种田间表现；走进科研实验室，近距离观看种质 DNA提取、分子细胞鉴定等科研实操过程；体验蔗糖深加工产品及副产物综合利用成果，参与产品品鉴互动。\n\n**3. 专属导览答疑服务**\n\n由研究所核心科研团队全程带队导览，针对种质保护、育种创新、产业应用等问题一对一答疑，普及种业科学知识，传播现代农业科技理念。\n\n## **六、参与须知**\n\n1. **公益免费参与**：本次活动全程免费，无任何参观、体验、品鉴费用；\n\n2. **实名预约报名**：活动实行实名制线上预约（微信扫描下发二维码），名额有限，报满即止，报名时间截止 2026年9月18日22:00，欢迎大家积极报名参与；\n\n![Image 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