[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-703":3,"related-703":72},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":29,"secondary_topics":35,"classification":36,"search_phrases":67,"slug":70,"view_count":50,"doi":8,"paper":8,"created_at":71},703,"国内外玉米专家齐聚成都——四川省农科院承办第十四届亚洲玉米大会专题研讨","https:\u002F\u002Fscnews.newssc.org\u002Fsystem\u002F20260817\u002F001634345.html","四川省农业科学院党委书记刘永红出席第十四届亚洲玉米大会闭幕总结。专题研讨设玉米遗传多样性利用、基因组解密、生物技术创新与种质精准创制三大分会,川单99与大豆-玉米带状复合种植技术(三次写入中央一号文件)成为大会亮点。会议首次落地四川,聚焦科技创新应对气候变化主题,推动亚洲玉米种业协同升级。",null,"四川新闻网-首屏新闻记者 刘文君\n\n8月14-17日，第十四届亚洲玉米大会在成都召开。大会由中国农业科学院主办，四川省作物学会承办“玉米生物育种与种质精准改良”系列专题研讨。专题研讨设置“玉米遗传多样性利用”“玉米基因组解密”和“生物技术创新与种质精准创制”三个分会，邀请8名海外专家和21名国内玉米专家作报告，吸引海内外300余名专家参会交流。\n\n![Image 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四川省农科院","大豆玉米带状复合种植 亚洲玉米大会","大豆玉米带状复合种植亚洲玉米大会四川省农科院-703","2026-08-18T23:59:17.029595Z",{"total":73,"page":21,"page_size":73,"items":74},6,[75,135,199,293,348,387],{"id":76,"title":77,"url":78,"summary":79,"summary_zh":8,"content":80,"source_name":81,"source_url":8,"published_at":82,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":83,"score_detail":84,"sources":89,"tags":91,"primary_topic":95,"secondary_topics":96,"classification":97,"search_phrases":129,"slug":132,"view_count":133,"doi":8,"paper":8,"created_at":134},901,"第十四届亚洲玉米大会在四川成都举行 推动科研成果走向田间地头","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7676257675889443379","第十四届亚洲玉米大会8月16-21日在四川成都举行，中国农科院主办，来自菲律宾\u002F孟加拉国\u002F越南\u002F尼泊尔等31个国家科研机构、育种专家、种业从业者以及国际组织代表参会。8月16日下午与会专家走进四川省农科院简阳玉米综合试验站，实地观摩玉米种质资源与新品种、抗逆高产技术示范、丘陵适用农机装备、玉米烘干加工中心。四川常年玉米播种面积超2800万亩、总产量突破千万吨；研发适配坡耕地的机械化免耕高效种植技术、\"一拌一喷\"绿色防控技术、移动式精准灌溉技术。","原标题：第十四届亚洲玉米大会在四川成都举行推动科研成果走向田间地头\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F638a1275132b4c55aa28b496545ca7ee~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1788134815&x-signature=37BisyPU4lDNYZK9jdWD2TClWz4%3D)\n参加第十四届亚洲玉米大会的专家在四川省农业科学院简阳玉米综合试验站的田间考察。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fbe8f3d2aa1e2a8b2bbcae36278b5ae78~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1788134815&x-signature=h9wB1MaqJ%2FAV7wbhvTiWr%2FbW3JE%3D)\n参加第十四届亚洲玉米大会的专家在察看移动式水肥药一体机。\n\n眼下，正是夏播玉米灌浆的时节，这一株株挺拔的作物，正托举着从农户增收、肉蛋奶供给到绿色新材料的产业链。如何以科技创新赋能产业升级？国内外专家在近日于四川成都举行的第十四届亚洲玉米大会上对此进行了探讨。\n\n第十四届亚洲玉米大会由中国农科院主办，来自菲律宾、孟加拉国、越南、尼泊尔等31个国家的科研机构负责人、育种专家、种业从业者以及国际组织代表会聚一堂，直面亚洲玉米生产面临的气候变化加剧、极端天气频发、跨境病虫害传播等各类现实风险，共同推动科研成果从实验室走向田间地头。\n\n生活中离不开的玉米\n\n提到玉米，很多人的第一印象，可能是早餐中的煮玉米、零食中的爆米花，又或者是玉米面窝头、玉米糊等传统食用形态。实际上，在日常生活里，这种普遍存在于我们的餐桌和生活中的谷物，早已超越了单纯的食材角色。\n\n在接受记者采访时，四川农业大学玉米研究所所长高世斌介绍，玉米消费主要有三个部分，饲料、加工、食用。其中，饲料用是最大的消费。高世斌举例说明：早晨起来使用的牙膏中，可能含有玉米淀粉衍生产品；我们吃的肉类、喝的牛奶、吃的鸡蛋，背后的养殖业离不开玉米饲料。除此之外，汽水里的果葡糖浆、沙拉酱里的稳定剂，很多是以玉米淀粉为原料加工而来。超市货架上的玉米油，更是很多家庭的常备烹饪用油。我们身上穿的衣服、手里拿的快递盒、桌上的一次性可降解餐具，也可能和玉米有关，通过现代生物化工技术，玉米中的淀粉可以被加工成聚乳酸，也就是我们常说的PLA材料。\n\n“这株从田野里长出来的作物，早已成为我们每一天生活里离不开的‘伙伴’。”高世斌说。\n\n中国农业科学院党组书记杨振海指出，中国是亚洲最大的玉米生产和消费国，玉米产业在国家粮食安全格局中占有重要位置。“面对日益严峻的全球性挑战，要共筑遗传资源与科技创新两大基石；共推具备气候韧性的绿色可持续生产体系；共建开放包容的亚洲玉米协作共同体，共同书写亚洲玉米产业高质量发展的新篇章。”杨振海说。\n\n国际玉米小麦改良中心亚洲区域主任博杜帕利·M·普拉萨纳回顾了国际玉米小麦改良中心（CIMMYT）与中国的合作历程。他表示，双方在种质交换、联合育种、人才培养上产出诸多实效，期待依托规划建设的中国—CIMMYT南方玉米小麦研究中心，进一步挖掘耐热、耐旱、抗病优异基因，推动基因编辑、基因组选择等新技术落地，打通从科研创新到农户生产的转化链条。\n\n以科技创新赋能产业升级\n\n玉米产业地位如此重要，以科技创新赋能产业升级、以国际合作筑牢安全底线，是各国稳定粮食供给、应对风险挑战的共同选择。\n\n“当前正在经历科技创新范式变革，中国着眼这个重大机遇与挑战，始终将玉米科技创新作为粮油作物科技攻关的核心重点，通过大力实施玉米单产提升工程和科技融合，针对不同产区生态短板完善科技创新机制和技术推广体系建设，推动玉米产业从单纯追求产量，向稳产抗逆、优质高效、绿色智能多元升级。”农业农村部科学技术司副司长张振华说。\n\n深入推进种业振兴，夯实玉米产能提升的种源根基。\n\n中国坚守玉米种源自主可控底线，系统开展种质资源保护、精准鉴定与创新利用，重点筛选培育抗旱耐高温、抗病抗逆、宜机收、养分高效的优质种质材料。持续升级迭代现代育种技术，改造传统育种模式，有效破解育种周期长、抗逆性不足、专用品种匮乏等突出问题，以自主科创能力稳固玉米种源安全底座。\n\n“我们实施了玉米种质资源精准鉴定和改良计划，发掘出一批优异种质，年均分发超2000份次，有效服务育种创新主体。开展育种中关键性状的遗传解析，加速融合基因编辑、分子标记、全基因组选择、人工智能育种等前沿技术，构建中国特色的玉米商业化育种体系。成功选育并推广了一批耐密宜机收、抗病耐逆、优质高产的突破性新品种。”中国农科院作科所所长周文彬说。\n\n大力实施玉米单产提升工程，推动大面积均衡增产。\n\n2023年，农业农村部启动实施全国粮油作物大面积单产提升行动，立足国内不同产区生态条件与生产短板，因地制宜集成创新栽培技术与种植模式。例如，在西南丘陵等区域推广轻简化、抗逆稳产种植方案，充分挖掘区域增产潜力，持续提升玉米产业气候韧性与可持续发展能力。\n\n中国农科院作物科学研究所研发的“玉米密植高产精准调控技术”作为全国单产提升工程核心技术，在新疆、内蒙古等地成功创建3个百万亩“吨粮田”示范区，累计推广面积达2.41亿亩，亩均增产113公斤、增收120元以上。“我们组建产业专家团，深入生产一线，因地制宜推广密植精播、水肥一体、抗逆稳产、绿色防控等高产关键技术，快速制定应对极端天气的防灾减灾技术方案，有力支撑了玉米稳产保收。”玉米育种专家、中国农业科学院作物科学研究所研究员黎亮说。\n\n发展精深加工与高值利用，提升玉米产业链韧性与附加值。\n\n中国的玉米专家聚焦玉米深加工关键技术，有效提升了玉米的加工转化率与附加值，构建了完善的质量安全标准体系，建立了快速准确的检测技术平台，为玉米及其制品从田间到餐桌的全链条质量安全保驾护航。\n\n“中国农科院持续深耕种质资源挖掘、育种技术革新、高产栽培模式示范，有力支撑了中国玉米产业高质量发展，也为亚洲玉米产业协同升级贡献了中国力量。”杨振海说。\n\n书写田间的丰收答卷\n\n8月16日下午，参加第十四届亚洲玉米大会的专家走进四川省农业科学院简阳玉米综合试验站，实地观摩玉米种质资源与新品种、抗逆高产技术示范、丘陵适用农机装备、玉米烘干加工中心，实地了解西南地区玉米“新品种、新技术、新模式、新农机、新加工”的落地成效，并围绕科企协同创新，分子检测、AI育种等产业技术，打通科研与产业之间的通道。\n\n田野里，成片的玉米进入灌浆中期，茎秆挺拔齐整，叶片宽大且在阳光下泛着光泽，显示出旺盛的生机，果穗饱满充实，农户与农技人员忙碌的身影穿梭其中，正在进行繁忙管护，田地里一片丰收在望的气象。\n\n四川作为全国粮食主产省之一、西南地区玉米生产大省，常年玉米播种面积超2800万亩，总产量突破千万吨。据介绍，四川省内科研团队立足丘陵山地特色，培育出成单、川单等系列适配西南生态的玉米品种，在宜机化品种选育、抗逆栽培技术上积累了大量实践经验。\n\n“品种是基础，配套技术是保障。”四川省农业科学院党委书记、国家玉米产业技术体系岗位科学家刘永红研究员介绍，针对四川丘陵山地的地形特点，当地研发和采用了三大核心技术：适配坡耕地的机械化免耕高效种植技术、“一拌一喷”绿色防控技术，以及适合山地的移动式精准灌溉技术。良种与良法配套，让四川玉米在今年高温伏旱的考验下，依然实现了稳产高产，部分区域还达成了超高产目标。\n\n广西壮族自治区玉林师范学院智慧农业学院副院长白彩虹是一位育种专家，她表示对简阳玉米综合试验站的种质资源圃很感兴趣。“一些杂交品种，田间表现很不错。农机设备的智能化程度也在不断提高，种类和型号多样，为农户提供了多种选择，为农业增产增收提供了支持。”白彩虹说。\n\n简阳是典型的川中浅丘地区，也是成都粮食主产区。过去，耕地散落山间，大机械进不来，好技术推不开。对此，简阳大力推进高标准农田建设，同时，针对浅丘地形，重点推广小型收割机、山地旋耕机等农机。\n\n在平武镇高坡村川中丘陵夏玉米抗逆免耕水肥精准调控稳产技术示范片，与会专家观摩了履带自走式电动玉米播种机、履带电动遥控玉米播种机、无人电动玉米播种机和移动式水肥药一体机等的现场示范。\n\n孟加拉国小麦玉米研究所专家马哈福兹·巴扎兹在参观时非常认真，表示简阳农业领域的技术发展进步令人赞叹。“当地专家向我们展示了诸多内容，包括如何在丘陵地区种植玉米，以及如何开展玉米品种培育与研究等，我还看到多种玉米种植机械装置。我希望这些机械能够惠及玉米种植农户，以节省时间、劳动力和成本，并提高效率。同时，也希望能将更多这样的农机设备带到孟加拉国，以造福我们的农户。”马哈福兹说。（叶晓楠文\u002F图）\n\n（人民日报海外版）","人民日报海外版 2026-08-21","2026-08-21T00:00:00Z",83,{"impact":85,"substance":86,"depth":87,"authority":19,"freshness":20,"relevant":21,"comment":88},25,20,16,"报道亚洲玉米大会，聚焦玉米产业科技创新与国际合作，内容详实，具有全国性影响。",[90],{"name":81,"url":78},[92,26,93,27,94],"中国农科院","丘陵山区","简阳",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":14,"version":38,"method":39,"evidence":98},{"candidates":99,"agricultural_evidence":44},[100,105,110,117,123],{"code":30,"score":101,"supported":44,"title":102,"abstract":103,"tags":104},11,[32],[32],[],{"code":56,"score":73,"supported":44,"title":106,"abstract":107,"tags":109},[],[59,108],"种质资源",[],{"code":111,"score":73,"supported":44,"title":112,"abstract":113,"tags":116},"F5",[],[114,115],"农机","机械化",[],{"code":118,"score":50,"supported":44,"title":119,"abstract":120,"tags":122},"F4",[],[121],"绿色防控",[],{"code":124,"score":50,"supported":44,"title":125,"abstract":126,"tags":128},"H3",[],[127],"灌溉",[],[130,131],"亚洲玉米大会 四川省农科院 中国农科院 丘陵山区","亚洲玉米大会 四川省农科院","亚洲玉米大会四川省农科院中国农科院丘陵山区-901",2,"2026-08-24T00:06:10.765383Z",{"id":136,"title":137,"url":138,"summary":139,"summary_zh":8,"content":140,"source_name":141,"source_url":8,"published_at":142,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":143,"score_detail":144,"sources":148,"tags":150,"primary_topic":155,"secondary_topics":156,"classification":161,"search_phrases":194,"slug":197,"view_count":50,"doi":8,"paper":8,"created_at":198},2569,"江苏省农业科学院 经作所玉米大豆带状种植增产减排取得新进展","https:\u002F\u002Fjaas.ac.cn\u002Fxww\u002Fxsky\u002Fart\u002F2026\u002Fart_a7782c6b7622405b860ca117804e97f9.html","李志康和高真真为European Journal of Agronomy期刊论文第一作者，李志康和张国伟为Journal of Agriculture and Food Research论文第一作者，刘瑞显研究员为通讯作者。研究得到国家自然科学基金(32401437)、国家重点研发计划(2022YFD2300904)、江苏省重点研发计划(BE2023346)及江苏省现代作物生产省部共建协同创新中心支持。","近日，经作所经作栽培团队在国际期刊《European Journal of Agronomy》（中科院一区Top，IF=6.7）和《Journal of Agriculture and Food Research》（中科院二区，IF=7.2）上连续发表研究成果，系统揭示了大豆玉米带状间作结合秸秆深埋还田通过调控土壤铁碳氮耦合过程实现作物增产与N₂O减排的新机制。\n\n大豆玉米带状复合种植是我国提升大豆产能的重点推广技术。团队在江苏连云港和徐州开展两年田间试验，设置单作与4:4带状间作，并对比不还田、旋耕还田和条带深埋（20–30厘米）三种方式。结果表明，间作本身土地当量比达1.23，增产23%；秸秆深埋使系统产量再提升16.1%，并将边行大豆减产幅度从15.4%降至8.75%。\n\n研究从碳氮动态与铁价态变化揭示内在机制。土壤有机碳在大豆结荚期和玉米抽雄期达峰值，灌浆阶段下降，真菌残体碳因与铁氧化物结合力强，在长期碳封存中贡献突出。铁价态变化成为N₂O排放的关键“开关”：生殖生长阶段，秸秆深埋使土壤Fe(II)含量飙升68.7%，Fe(II)\u002FFe(III)比值暴涨112%，通过厌氧亚铁氧化过程加速N₂O向N₂转化，使N₂O排放降低超55%，全球增温潜势降低超20%，排放强度降低超60%。微生物层面，秸秆深埋选择性富集功能菌群，大豆侧碳流向真菌残体碳，玉米侧同时促进微生物和植物残体碳积累，共同支撑系统碳汇功能。\n\n基于上述发现，研究团队提出实践建议：在黄淮海南部地区黏质或砂壤质土壤条件下，建议将前茬小麦秸秆全量条带深埋至20–30厘米土层，配合4:4大豆玉米带状间作配置。该组合优势在于延缓秸秆分解速率，促进碳素向稳定矿物结合态有机质转化，同时为生殖生长阶段的氮素供应提供了“缓释”保障。\n\n李志康和高真真为European Journal of Agronomy期刊论文第一作者，李志康和张国伟为Journal of Agriculture and Food Research论文第一作者，刘瑞显研究员为通讯作者。研究得到了国家自然科学基金（32401437）、国家重点研发计划（2022YFD2300904）、江苏省重点研发计划（BE2023346）及江苏省现代作物生产省部共建协同创新中心的支持。\n\n![Image 1](https:\u002F\u002Fjaas.ac.cn\u002Fcms_files\u002Ffilemanager\u002F2092031400\u002Fpicture\u002F20268\u002Fc3fba006c930468a8c6e81bda05421d3.png)\n\n**论文链接**\n\n[1] Li ZK, Gao ZZ, Zhang GW, Jiang ZH, Shu HM, Yang CQ, Du XB, Liu RX.Soybean–maize intercropping and straw returning change soil iron-associated nitrogen dynamics to increase crop yield and reduce N₂O emissions, European Journal of Agronomy, 2006,180:128255. https:\u002F\u002Fdoi.org\u002F[10.1016\u002Fj.eja.2026.128255](https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.eja.2026.128255)\n\n[2] Li ZK, Zhang GW, Jiang ZH, Liu K, Shu HM, Yang CQ, Gao ZZ, Du XB, Liu RX. Soybean–maize intercropping with straw deep burial modulates soil organic carbon dynamics to enhance system yield, Journal of Agriculture and Food Research, 2026, 30: 103192. [https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jafr.2026.103192](https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jafr.2026.103192 \"Persistent link using digital object identifier\")","江苏农科院 2026-09","2026-09-12T00:00:00Z",81,{"impact":86,"substance":145,"depth":18,"authority":146,"freshness":73,"relevant":21,"comment":147},23,14,"省级科研机构在国际一区期刊发表的大田试验成果，数据翔实、机制清晰，对黄淮海地区大豆产能提升与农业减排具有实践指导价值，值得进入每日精选。",[149],{"name":141,"url":138},[151,28,152,153,154],"秸秆还田","农业减排","土壤固碳","绿色增产",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[157],{"code":49,"slug":158,"name":159,"path":160,"parent_code":34},"soybean-oilseeds","大豆与油料","\u002Ftopic\u002Ffield-crops\u002Fsoybean-oilseeds",{"status":37,"locked":14,"version":38,"method":39,"evidence":162},{"candidates":163,"agricultural_evidence":44},[164,169,174,179,184,189],{"code":30,"score":165,"supported":44,"title":166,"abstract":167,"tags":168},9,[32],[],[28],{"code":49,"score":170,"supported":44,"title":171,"abstract":172,"tags":173},8,[53],[],[],{"code":175,"score":21,"supported":14,"title":176,"abstract":177,"tags":178},"H2",[],[],[153],{"code":180,"score":21,"supported":14,"title":181,"abstract":182,"tags":183},"H4",[],[],[152],{"code":185,"score":21,"supported":14,"title":186,"abstract":187,"tags":188},"H5",[],[],[151],{"code":190,"score":21,"supported":14,"title":191,"abstract":192,"tags":193},"H8",[],[],[154],[195,196],"大豆玉米带状复合种植 农业减排 土壤固碳 秸秆还田","大豆玉米带状复合种植 农业减排","大豆玉米带状复合种植农业减排土壤固碳秸秆还田-2569","2026-09-16T00:03:47.300752Z",{"id":200,"title":201,"url":202,"summary":203,"summary_zh":204,"content":8,"source_name":205,"source_url":202,"published_at":206,"category":207,"cover_url":8,"hotness":13,"is_selected":14,"score":208,"score_detail":209,"sources":212,"tags":214,"primary_topic":219,"secondary_topics":220,"classification":227,"search_phrases":259,"slug":262,"view_count":263,"doi":264,"paper":265,"created_at":292},2501,"Numerical analysis of droplet deposition and drift patterns for multi-rotor UAVs in soybean-maize strip intercropping system","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112407","Numerical analysis of droplet deposition and drift patterns for multi-rotor UAVs in soybean-maize strip intercropping system。Computers and Electronics in Agriculture","多旋翼无人机在大豆-玉米带状间作系统中的雾滴沉积与飘移模式数值分析。","Computers and Electronics in Agriculture","2026-09-14T00:00:00Z","论文",69,{"impact":43,"substance":18,"depth":210,"authority":146,"freshness":170,"relevant":21,"comment":211},17,"核心期刊论文，用数值模拟揭示多旋翼无人机在大豆玉米带状复合种植中的雾滴沉积与飘移规律，方法新颖、结论对精准植保有参考价值，但属细分技术进展，公共影响有限。",[213],{"name":205,"url":202},[215,216,217,28,218],"智慧农业","农业遥感","精准施药","植保无人机",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[221,222],{"code":49,"slug":158,"name":159,"path":160,"parent_code":34},{"code":223,"slug":224,"name":225,"path":226,"parent_code":34},"A7","forage-cropping","饲草与耕作制度","\u002Ftopic\u002Ffield-crops\u002Fforage-cropping",{"status":37,"locked":14,"version":38,"method":39,"evidence":228},{"candidates":229,"agricultural_evidence":44},[230,234,239,245,249,254],{"code":30,"score":19,"supported":44,"title":231,"abstract":232,"tags":233},[31],[32,31],[28],{"code":49,"score":146,"supported":44,"title":235,"abstract":237,"tags":238},[236],"soybean",[53,236],[],{"code":223,"score":146,"supported":44,"title":240,"abstract":242,"tags":244},[241],"intercropping",[243,241],"间作",[],{"code":118,"score":133,"supported":14,"title":246,"abstract":247,"tags":248},[],[],[218,217],{"code":250,"score":21,"supported":14,"title":251,"abstract":252,"tags":253},"I1",[],[],[215],{"code":255,"score":21,"supported":14,"title":256,"abstract":257,"tags":258},"I3",[],[],[216],[260,261],"大豆玉米带状复合种植 植保无人机 农业遥感 智慧农业","大豆玉米带状复合种植 植保无人机","大豆玉米带状复合种植植保无人机农业遥感智慧农业-2501",4,"10.1016\u002Fj.compag.2026.112407",{"doi":264,"openalex_id":266,"authors":267,"venue":205,"cited_by_count":284,"oa_url":8,"card":285,"direction":289,"ingested_from":291},"W7212969118",[268,270,272,274,276,279,282],{"name":269,"orcid":8},"Xinghua Liu",{"name":271,"orcid":8},"Lei Yang",{"name":273,"orcid":8},"Zhi Li",{"name":275,"orcid":8},"Yang Li",{"name":277,"orcid":278},"Qiaolin Chen","https:\u002F\u002Forcid.org\u002F0000-0002-3878-0001",{"name":280,"orcid":281},"Yanping Tian","https:\u002F\u002Forcid.org\u002F0000-0003-4303-6524",{"name":283,"orcid":8},"Xiang-Dong Li",0,{"tldr":286,"method":287,"finding":288,"direction":289,"opportunity":290},"用数值模拟分析多旋翼无人机在大豆-玉米带状间作系统中的雾滴沉积与飘移规律。","基于CFD数值模拟，结合多旋翼无人机下洗气流与作物冠层结构建模。","揭示了间作系统下无人机喷雾沉积分布与飘移特征，为精准施药提供依据。","智慧农业 \u002F 农业物联网","可结合田间实测与机器学习，构建间作系统无人机变量喷雾决策模型。","openalex","2026-09-15T23:30:01.587453Z",{"id":294,"title":295,"url":296,"summary":297,"summary_zh":8,"content":298,"source_name":299,"source_url":8,"published_at":300,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":301,"score_detail":302,"sources":304,"tags":306,"primary_topic":314,"secondary_topics":315,"classification":321,"search_phrases":343,"slug":346,"view_count":263,"doi":8,"paper":8,"created_at":347},993,"四川农科院自主选育玉米新品种‘成单372’首创推广遭遇梅雨高温干旱『三道坎』 测产仍比对照每亩多产225.28公斤","https:\u002F\u002Fnews.10jqka.com.cn\u002Ffield\u002F20260826\u002F679319660.shtml","8月24日，遂宁市安居区石洞镇玉米种植大户李永杰忙完春玉米盘点——其中120亩地的平均亩产量比其他380亩地高了50—75公斤。这120亩地种植的玉米品种是『成单372』，由四川省农业科学院自主选育，是粮饲通用型高产新品种，去年创造了我国西南区域玉米亩产1419.48公斤的高产纪录。8月8日专家组严格按照《全国粮食高产创建测产验收办法(试行)》，采用玉米联合收割机进行全田籽粒机收测产。测产田块的玉米种植密度达到4500株\u002F亩，远高于当地平均水平。李永杰表示，连续经历花期阴雨、灌浆高温、后期干旱『三道坎』还能有这样的产量，明年可以放心大规模种植。","[![Image 1](https:\u002F\u002Fcountry.scol.com.cn\u002Fpaperdata\u002Fscncrb\u002F20260827\u002F2ab7bd2d2de3c2ece156e5eb6c4dc6f9.jpg)](https:\u002F\u002Fcountry.scol.com.cn\u002Fpaperdata\u002Fscncrb\u002F20260827\u002F2ab7bd2d2de3c2ece156e5eb6c4dc6f9.jpg) 高密种植的玉米新品种“成单372”。\n\n[![Image 2](https:\u002F\u002Fcountry.scol.com.cn\u002Fpaperdata\u002Fscncrb\u002F20260827\u002Fab8d6acb8dcc62ffb9a6f6952838bcf3.jpg)](https:\u002F\u002Fcountry.scol.com.cn\u002Fpaperdata\u002Fscncrb\u002F20260827\u002Fab8d6acb8dcc62ffb9a6f6952838bcf3.jpg) 玉米新品种“成单372”测产现场。\n\n□四川农村日报全媒体记者 徐灿红\n\n 8月24日，遂宁市安居区石洞镇玉米种植大户李永杰正忙着盘账。他的500亩春玉米已收完，翻看称重记录，一个数字让他兴奋不已——其中120亩地的平均亩产量比其他380亩地高了50—75公斤。\n\n 这120亩地种植的玉米品种是“成单372”。该品种由四川省农业科学院自主选育，是粮饲通用型高产新品种，去年创造了我国西南区域玉米亩产1419.48公斤的高产纪录。\n\n 今年，该品种通过国审后第一次进行规模化种植，实际产量如何？种植大户如何评价？记者进行了采访。推广首年 遇到“三道坎”\n\n 8月8日，四川省科学技术厅组织的专家组对李永杰种植的“成单372”进行测产验收。\n\n 专家组严格按照《全国粮食高产创建测产验收办法（试行）》，采用玉米联合收割机进行全田籽粒机收测产。结果显示：“成单372”（亩植密度4500株）机收平均亩产750.11公斤，较相邻地块种植的当地主栽品种（亩植密度3200株）524.83公斤的平均亩产量多了225.28公斤。\n\n 这一产量的取得殊为不易。李永杰说，今年5月中旬到6月下旬，正逢玉米拔节期至扬花期，当地经历了长时间的梅雨天气。7月5日至28日，持续36℃—42℃的高温天气让玉米灌浆遭受最大考验。面对旱情，他曾考虑从远处的水库调水，但因设施不全，只能放弃。\n\n “一个新品种，连续经历花期阴雨、灌浆高温、后期干旱‘三道坎’，还能有这样的产量，明年可以放心地大规模种植！”李永杰说。\n高密高产被写进基因里\n\n 一个数据值得关注：测产田块的玉米种植密度达到4500株\u002F亩，远高于当地平均水平。种植密度的变化中，藏着新品种高产的密码。\n\n 西南丘陵山区，日照少、湿度大、病害多。几十年来，大部分种植户更相信种得稀 一点，棒子大一点，产量才有保障。\n\n 这种需求从种植端传导到种子企业，导致多年来西南地区缺乏耐密品种。四川省农业科学院作物研究所玉米中心副主任杨麟介绍，在四川，传统的稀植大穗玉米品种种植密度为每亩 2600 株左右，超过 3200株就容易出现倒伏和病害等抗逆问题。\n\n “世界各地玉米育种的方向，都是往适度高密发展。”四川丰大种业有限公司董事长章存均在近日举办的第十四届亚洲玉米大会上接受采访时说，气候变化带来的不确定性，恰恰对品种的抗逆性提出了更高要求。而高密种植，正是用“群体优势”来保障产量提升。\n\n院企协同锚定“战略大单品”\n\n “成单372”是四川院企协同的成果转化样板。\n\n 2025年3月，“成单372”作为四川重大科技成果完成成果转化签约，从科研育种阶段正式进入产业化开发与应用阶段。\n\n 章存均看中的，是这个玉米新品种成为战略大单品的潜力。“战略大单品对于种子企业而言，相当于球队有一名著名球星一样，是必须要打造的。”他定义的战略大单品有两个基本特征：一是广适性强，二是播种面积要200万亩起步。\n\n “成单372”正在朝这个方向走。它已通过国家西南区中低海拔及中高海拔组审定、四川省青贮玉米审定，其示范种植点位将遍布全国。\n\n 在第十四届亚洲玉米大会上，多位国外育种专家被展位上展示的“成单372”果穗吸引，不断追问品种特性和配套栽培技术。\n\n “推动科技创新，应对气候变化”是本届大会的主题。今年，四川春玉米刚刚经历了一个花期阴雨寡照、灌浆期持续极端高温的生长季。如何应对极端气候是世界各地玉米种植者共同面对的课题和需要攻克的育种难题。而这个“四川造”玉米新品种，给出了一个可供参考的答案。\n\n 受访者供图","四川农村日报 2026-08-27 · 2026-08-26","2026-08-27T00:00:00Z",78,{"impact":86,"substance":17,"depth":87,"authority":13,"freshness":13,"relevant":21,"comment":303},"报道四川农科院玉米新品种推广首年遭遇极端天气仍增产，含具体测产数据，体现农业科技抗逆性，具行业参考价值。",[305],{"name":299,"url":296},[26,307,308,309,310,311,312,313],"测产","玉米新品种","成单372","高密种植","4500株","粮饲通用","750.11公斤",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[316],{"code":62,"slug":317,"name":318,"path":319,"parent_code":320},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"status":37,"locked":14,"version":38,"method":39,"evidence":322},{"candidates":323,"agricultural_evidence":44},[324,328,333,338],{"code":30,"score":43,"supported":44,"title":325,"abstract":326,"tags":327},[32],[32],[308],{"code":62,"score":101,"supported":44,"title":329,"abstract":331,"tags":332},[330],"干旱",[330],[],{"code":111,"score":50,"supported":44,"title":334,"abstract":335,"tags":337},[],[336],"收割机",[],{"code":339,"score":21,"supported":14,"title":340,"abstract":341,"tags":342},"A8",[],[],[307],[344,345],"四川省农科院 玉米新品种 粮饲通用 高密种植","四川省农科院 玉米新品种","四川省农科院玉米新品种粮饲通用高密种植-993","2026-08-27T00:05:19.082258Z",{"id":349,"title":350,"url":351,"summary":352,"summary_zh":8,"content":353,"source_name":354,"source_url":8,"published_at":355,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":356,"sources":358,"tags":360,"primary_topic":363,"secondary_topics":364,"classification":365,"search_phrases":383,"slug":385,"view_count":170,"doi":8,"paper":8,"created_at":386},837,"[四川省农科院]第十四届亚洲玉米大会田间考察走进简阳——90个杂交品种、上百份地种与自交系接受\"田间大考\"","https:\u002F\u002Fwww.farmer.com.cn\u002F2026\u002F08\u002F20\u002F991026453.html","丘陵地区玉米何以丰产?亚洲专家走进四川的高温\"考场\"。从1996年四川省农科院与简阳市开启院地合作算起,三代科研人扎根坡地,攒出一套适配丘区的\"组合拳\"。本次大会设置四个田间观摩点:禾丰镇元吉社区品种展示区90个杂交品种、上百份地种与自交系;平武镇高坡村夏玉米示范田展示\"轻简高效\"\"两机一带\"技术(免耕灭茬播种机、移动式水肥药一体机、喷灌带);青龙镇联合村示范田玉米秆下紫苏、花生、大豆长势正旺。现场展示\"蜀花9号\"\"川豆155\"等主推品种对西南5种主要病害达到中抗以上。","平武镇尤安烘干中心给出了另一重答案。总投资2345万元、日烘干峰值600吨、年仓储1.2万吨，产后损耗降低8%，玉米干燥品质提高10%——解决了丘区“雨天晒粮难、粮食霉变损耗”的老大难。\n\n在加工品鉴台上，玉米早已不只是一根棒子。鲜食玉米、玉米薄片、玉米汁、玉米啤酒，还有玉米糊糊等产品一字排开。四川省农科院农产品加工研究所研究员曾晓丹介绍，四川玉米一大半流向饲料领域，但精深加工方向已经十分清晰：跟着消费需求往营养、健康方向走。育种端聚焦花青素、叶黄素、叶酸等营养强化及甜糯同体等特色口感；加工端通过工艺优化和创新，提升口感、营养保持率和吸收率，开发更具市场活力的食品和功能性食品。“健康属性不是只靠终端加工做出来的，源头品种就可以把营养做进籽粒里。”当品种和加工形成合力，玉米的价值链才能真正拉长。简阳本地已建成玉米收储与初加工基地，实现“全收全销”闭环。","中国农网\u002F农民日报 2026年8月20日","2026-08-20T00:00:00Z",{"impact":18,"substance":86,"depth":19,"authority":43,"freshness":20,"relevant":21,"comment":357},"报道了玉米育种与加工结合提升价值链的进展，含具体数据，但属省级科研动态，影响有限。",[359],{"name":354,"url":351},[26,361,27,94,362],"玉米抗逆","丘区",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[],{"status":37,"locked":14,"version":38,"method":39,"evidence":366},{"candidates":367,"agricultural_evidence":44},[368,372,377],{"code":30,"score":101,"supported":44,"title":369,"abstract":370,"tags":371},[32],[32],[],{"code":49,"score":73,"supported":44,"title":373,"abstract":374,"tags":376},[],[53,375],"花生",[],{"code":378,"score":50,"supported":44,"title":379,"abstract":380,"tags":382},"G1",[],[381],"院地合作",[],[384,131],"亚洲玉米大会 四川省农科院 玉米抗逆 丘区","亚洲玉米大会四川省农科院玉米抗逆丘区-837","2026-08-22T00:05:59.691471Z",{"id":388,"title":389,"url":390,"summary":391,"summary_zh":8,"content":392,"source_name":393,"source_url":8,"published_at":355,"category":207,"cover_url":8,"hotness":13,"is_selected":14,"score":394,"score_detail":395,"sources":397,"tags":399,"primary_topic":404,"secondary_topics":405,"classification":408,"search_phrases":424,"slug":427,"view_count":263,"doi":8,"paper":8,"created_at":428},790,"基于处方图的变量喷药系统设计与试验(大豆-玉米带状复合种植):实时处方图解析、时空喷嘴匹配与延时补偿(原标题:Design and Experiment of a Prescription-Map-Based Variable-Rate Spraying System for Soybean-Maize Strip Intercropping)","https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784","为满足大豆-玉米带状复合种植中差异化施药需求,本研究开发了基于实时处方图解析、时空喷嘴匹配与延时补偿的带状变量喷药系统。使用ArcMap生成具有预定施药量级别的模拟处方图,基于高精度RTK-BDS定位建立田间坐标转换模型并结合SRAM预加载实现快速处方矩阵寻址;开发喷嘴空间位置预测模型与前向延时补偿控制算法,减少动态作业中由定位偏移、执行器响应滞后和液压延迟引起的边界错位。带状变量喷药试验中延时补偿后平均边界偏移由0.69米降至0.29米;大豆与玉米带不同施药量级下平均流量控制精度均超95%,流量变异系数均低于6%。","## 1. Introduction\n\nMaize and soybean are globally important food, feed, and oilseed crops, playing vital roles in ensuring food security, supporting livestock production, and facilitating agricultural processing and utilization. Over time, maize–soybean cropping systems have been continuously optimized [[1](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B1-agriculture-16-01784),[2](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B2-agriculture-16-01784),[3](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B3-agriculture-16-01784),[4](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B4-agriculture-16-01784)]. Soybean–maize strip intercropping optimizes the spatial arrangement of the two crops, enabling stable maize production while expanding soybean cultivation, thereby improving land-use efficiency and promoting coordinated grain and oilseed production [[5](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B5-agriculture-16-01784),[6](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B6-agriculture-16-01784),[7](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B7-agriculture-16-01784)]. However, soybean and maize differ markedly in inter-row canopy structure, crop-protection requirements, and herbicide tolerance, making conventional large-scale uniform spraying prone to crop injury and missed applications [[8](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B8-agriculture-16-01784),[9](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B9-agriculture-16-01784)]. Prescription-map-based variable-rate spraying enables real-time adjustment of application rates according to field weed distribution, crop growth status, and machinery operating parameters, providing an important approach to advancing precision crop protection [[10](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B10-agriculture-16-01784),[11](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B11-agriculture-16-01784),[12](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B12-agriculture-16-01784)].\n\nWith the development of precision agriculture, variable-rate pesticide application has become an important research direction in agricultural engineering. In recent years, it has attracted extensive attention from researchers worldwide and has gradually emerged as a research hotspot [[13](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B13-agriculture-16-01784),[14](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B14-agriculture-16-01784),[15](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B15-agriculture-16-01784),[16](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B16-agriculture-16-01784)].\n\nExisting studies show that variable-rate pesticide application has achieved clear progress in prescription map generation, remote-sensing image recognition, spray actuator control, and improvement of application effectiveness [[17](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B17-agriculture-16-01784)]. Hamouz et al. constructed field-zoned application maps, and their experiments showed that site-specific weed control reduced herbicide use by 15.6–100% compared with conventional whole-field uniform herbicide application [[18](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B18-agriculture-16-01784)]. With advances in remote sensing and aerial operation technologies, prescription map generation has gradually expanded from traditional manual sampling and grid surveys to airborne platforms, unmanned aerial vehicles, and multispectral image recognition. Yang et al. integrated an airborne multispectral imaging system to generate prescription maps and used the imaging system to evaluate post-application effects [[19](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B19-agriculture-16-01784)]. Campos et al. used an unmanned aerial vehicle equipped with a multispectral camera to acquire crop canopy information for prescription-map generation and conducted field evaluations of prescription-map-based variable-rate spraying [[20](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B20-agriculture-16-01784)]. Guan et al. reviewed advances in variable-rate spraying from two perspectives: information acquisition based on prescription maps or real-time sensors, and three variable-rate control strategies involving pressure regulation, direct injection, and pulse-width modulation [[21](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B21-agriculture-16-01784)]. Yin et al. developed an indoor prescription-map-based variable-rate herbicide spraying system, in which weed images were acquired to generate prescription maps, and precise targeted spraying was achieved by selectively controlling individual nozzles [[22](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B22-agriculture-16-01784)]. Abioye et al. developed a deep-learning-guided variable-rate spraying robot that integrates visual perception and deep learning for target plant identification, enabling targeted and variable-rate spraying and providing a new approach to integrating prescription maps, machine vision, and robotic actuation [[23](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B23-agriculture-16-01784)].\n\nDespite substantial advances in variable-rate spraying, offline prescription-map-based application still involves time-consuming preparatory steps, including data acquisition, processing, and prescription map generation [[10](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B10-agriculture-16-01784)]. During dynamic field operations, the microcontroller must continuously parse positioning data, perform spatial matching, and retrieve prescription values, placing stringent real-time demands on online prescription map interpretation under limited computational and memory resources [[24](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B24-agriculture-16-01784)]. Moreover, inherent response delays from control-command output to solenoid-valve actuation and spray formation can translate into spatial application offsets as the sprayer moves, thereby compromising flow-rate control accuracy [[25](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B25-agriculture-16-01784),[26](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B26-agriculture-16-01784)].\n\nAccordingly, this study developed a variable-rate spraying system for soybean–maize strip intercropping that innovatively integrates fast embedded prescription-matrix addressing, nozzle-level spatial position prediction, and dynamic delay compensation to achieve precise spatiotemporal matching between prescription information and actual spray locations. The main contributions are as follows: A prescription-map-based strip-specific variable-rate spraying system was proposed for soybean–maize strip intercropping, providing technical support for differentiated and potentially more efficient pesticide application; a rapid prescription-map interpretation method was implemented on the embedded controller to enable real-time matching between machine position and target application rate, thereby improving prescription retrieval efficiency; and a prescription map–nozzle matching delay-compensation method was developed and validated through outdoor droplet-deposition, delay-compensation, and strip-specific variable-rate spraying tests, demonstrating the feasibility of the proposed system.\n\n## 2. Materials and Methods\n\n### 2.1. System Architecture\n\n#### 2.1.1. Overall System Design\n\nThe overall design of the strip-specific variable-rate spraying system for soybean–maize strip intercropping is shown in [Figure 1](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#fig_body_display_agriculture-16-01784-f001). Because maize and soybean differ markedly in pesticide tolerance and application requirements, the system adopts two independent pesticide delivery pipelines to enable separate strip-specific application for maize and soybean. To prevent spray liquid from drifting between different crop zones during application, anti-drift nozzles were selected, and cover structures were installed outside the soybean nozzles to reduce the risk of droplet drift.\n\n**Figure 1.** Overall structure of the variable-rate spraying system. 1. water tank; 2. return valve; 3. check valve; 4. maize pesticide tank; 5. peristaltic pump; 6. Venturi injector; 7. pesticide mixer; 8. pressure sensor; 9. flow sensor; 10. high-speed solenoid valve; 11. anti-drift nozzle; 12. shroud; 13. microcontroller; 14. GNSS receiver; 15. water pump; 16. RTK-BDS; 17. soybean pesticide tank.\n\nBefore field operation, strip-specific variable-rate prescription maps are generated on a GIS platform using crop growth information and converted into a format suitable for embedded processing. During operation, the main controller receives real-time RTK-BDS positioning data, calculates the spatial position of each nozzle based on the boom geometry, and retrieves the corresponding target application rate through prescription-map addressing. Flow and pressure sensors in the two independent spray circuits provide real-time feedback, and the controller adjusts the PWM duty cycles of the high-speed solenoid valves according to the deviation between the target and measured flow rates, thereby enabling independent variable-rate application to the maize and soybean strips. In the hydraulic system, the spray solution sequentially passes through the pressure sensor, flow sensor, and high-speed solenoid valve before being delivered to the drift-reducing nozzles, with every three nozzles forming an independent control unit.\n\n#### 2.1.2. Control System Design\n\nSTM32 series microcontrollers are characterized by high performance, low power consumption, and low cost, and are therefore commonly used as core controllers in control systems [[27](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B27-agriculture-16-01784),[28](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B28-agriculture-16-01784),[29](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B29-agriculture-16-01784)]. Based on the prescription map construction and interpretation method described above, together with the variable-rate pesticide application control algorithm, a soybean–maize variable-rate pesticide application control system was designed with an STM32F103ZET6 microcontroller (STMicroelectronics, Geneva, Switzerland) as the core. The system mainly consists of a power supply module, signal acquisition module, main controller module, actuator module, and communication module.\n\nThe overall architecture of the variable-rate spraying control system is shown in [Figure 2](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#fig_body_display_agriculture-16-01784-f002). During operation, the RTK-BDS positioning terminal continuously outputs the sprayer’s longitude, latitude, heading, and travel speed, which are transmitted to the main controller via a serial interface. Using the preloaded prescription-map data and real-time positioning information, the controller performs field-coordinate transformation, grid identification, and prescription-map addressing to determine the target application rate for the current or predicted spray position. Meanwhile, flow-rate and pressure measurements from the two independent spray circuits are fed back to the main controller. An Improved Beetle Antennae Search (IBAS)-optimized Fuzzy-PID controller calculates the control output from the deviation between the target and measured flow rates. The resulting PWM duty cycles are transmitted to the actuator module via the communication bus, enabling independent variable-rate application to the soybean and maize strips.\n\n**Figure 2.** Overall structure of the variable-rate pesticide application control system.\n\nThe system software employs a hybrid task-scheduling architecture that combines a main-loop routine with interrupt-driven processing. Time-critical signals, such as flow-meter pulses, are processed using timer input-capture interrupts. The main loop sequentially performs RTK-BDS positioning updates, nozzle-position calculation and prescription-map addressing, sensor-data processing for the two spray circuits, flow-control computation, and command output. To reduce the computational burden of multichannel actuation on the MCU, the main controller only calculates and updates the PWM duty cycle for each channel, while the actual PWM signals are generated independently by an external multichannel PWM module to drive the high-speed solenoid valves. This architecture reduces the real-time processing load associated with continuous PWM generation on the main controller.\n\nIn terms of hardware, an NZ510G high-precision intelligent positioning terminal (Yanshi Zhikong, Beijing, China) was selected as the GNSS receiver positioning device for the variable-rate spraying system. Spray output was regulated by pulse-width modulation (PWM), whereby the duty cycle of the solenoid valve at each nozzle was adjusted by controlling its opening and closing durations. Consequently, the response speed, corrosion resistance, and operational stability of the solenoid valves directly affect spray-control performance. Considering the field operating environment and the properties of pesticide solutions, normally closed 2WA030-08B solenoid valves (AirTAC (China) Co., Ltd., Ningbo, China) were selected.\n\n### 2.2. Prescription Map Construction\n\n#### 2.2.1. Overview of ArcMap Software\n\nArcMap is a geographic information system software developed by Esri and is one of the major desktop applications of the ArcGIS 10.8.1 platform. ArcMap supports various spatial data formats, including vector data, raster data, and spatial database data, and has been widely applied in geographic information-related fields such as environmental management, urban planning, agricultural monitoring, disaster risk assessment, and emergency management [[30](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B30-agriculture-16-01784),[31](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B31-agriculture-16-01784),[32](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#B32-agriculture-16-01784)].\n\nThe proposed system requires a GIS platform with high spatial accuracy and compatibility with the data structure used by the embedded controller. ArcMap provides coordinate registration, projection transformation, regular grid generation, and attribute-data processing, enabling spatial alignment between prescription maps and RTK positioning data. Regular grids generated using the Fishnet tool facilitate spatial matching and prescription-value retrieval, while attribute data can be exported and converted into binary files for embedded processing. Thus, ArcMap satisfies the system requirements for spatial accuracy, grid-based processing, and data export.\n\n#### 2.2.2. Acquisition of Field Position Information\n\nField position information is a prerequisite for prescription map construction and variable-rate pesticide application control. In this study, a set of simulated prescription map data conforming to the spatial distribution pattern of soybean–maize strips was generated for testing. The dataset included the spatial position information of the operating area and the corresponding prescription values, as shown in [Table 1](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#table_body_display_agriculture-16-01784-t001). These coordinates were used for prescription-map construction.\n\n**Table 1.** Longitude, latitude, and prescription values used for constructing the simulated prescription map.\n\nTo facilitate subsequent prescription map interpretation and invocation by the pesticide application control system, the above data were imported into ArcMap for organization and preprocessing, including spatial extent inspection, attribute field verification, and coordinate reference system unification. Through data preprocessing, the prescription map data and BeiDou positioning information were aligned to a unified spatial reference, and the correspondence between the spatial positions of the operating area and the prescription values was established.\n\nAfter processing, the basic spatial dataset required for subsequent prescription unit division, prescription map construction, and addressing-based matching was obtained, providing data support for real-time prescription retrieval by the variable-rate spraying system.\n\n#### 2.2.3. Prescription Unit Division and Application-Rate Assignment\n\nTo enable the spatial representation of prescription map data and subsequent invocation by the variable-rate spraying system, the original longitude, latitude, and prescription value data of the operating area must be converted into prescription units with spatial position attributes, and the correspondence between prescription units and application rates must be established. The original data used in this study were stored in tabular form and mainly included fields such as longitude, latitude, and the corresponding prescription value.\n\nTo spatially represent the prescription data for subsequent variable-rate spraying, the raw dataset containing longitude, latitude, and prescription values was imported into ArcMap 10.8.1. As shown in [Figure 3](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#fig_body_display_agriculture-16-01784-f003), a prescription-point layer was generated using the Add XY Data function, and the coordinate reference system was standardized to ensure spatial consistency with RTK-BDS positioning data. The resulting event layer was then exported as a vector layer, and the correspondence between spatial locations and prescription values was verified, providing the basis for subsequent prescription-cell delineation, prescription-map generation, and spatial addressing.\n\n**Figure 3.** Generation of the operating-area layer.\n\nAs shown in [Figure 4](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#fig_body_display_agriculture-16-01784-f004), a regular rectangular grid was generated over the operating area using the Fishnet tool in ArcMap. For the 4:2 soybean–maize strip intercropping configuration, the transverse grid resolution, Δx, was set equal to the actual crop-strip width to accurately represent strip-specific application boundaries. Prescription values were then assigned to the corresponding grid cells, establishing a one-to-one correspondence between spatial location and target application rate. Each grid cell therefore contained a unique spatial location and application attribute, representing the target application requirement for the corresponding area.\n\n**Figure 4.** Generation of the regular rectangular grid.\n\n#### 2.2.4. Construction of the Simulated Prescription Map\n\nAfter prescription-cell delineation and assignment of application rates, a prescription map of the operating area was generated to visualize the spatial distribution of application requirements and provide input data for subsequent prescription-map interpretation and variable-rate spraying control. In ArcMap, the operating area was discretized into regular grid cells based on the assigned prescription-cell layer, and the cells were classified according to their prescription values and displayed using different colors to distinguish application-rate levels, as shown in [Figure 5](https:\u002F\u002Fwww.mdpi.com\u002F2077-0472\u002F16\u002F16\u002F1784#fig_body_display_agriculture-16-01784-f005). The completed prescription map was then visually inspected to verify the prescription-cell delineation and spatial distribution of prescription values, thereby confirming the completeness and consistency of the prescription-map data.\n\n**Figure 5.** Prescription map for soybean–maize strip intercropping.\n\nOn the basis of the visualized prescription map, the structured attribute data of the prescription map must be further exported to meet the requirements of the subsequent prescription map interpretation system for grid identification and rapid addressing. In this study, row number r and column number c fields were established for each grid cell in ArcMap and saved together with the prescription value field, forming an attribute table containing both grid index information and prescription value information. The relevant attribute data were then exported as a .csv file and further converted into a .bin file readable by the microcontroller. Through this process, the visualized prescription map generated in ArcMap was converted in","MDPI Agriculture 16(16):1784 2026-08-20",80,{"impact":18,"substance":17,"depth":18,"authority":146,"freshness":170,"relevant":21,"comment":396},"针对大豆-玉米带状复合种植的处方图变量喷药系统研究，方法新颖，数据详实，对精准农业有实质贡献。",[398],{"name":393,"url":390},[400,401,28,402,403],"处方图","MDPI Agriculture","变量喷药","延时补偿",{"code":30,"slug":31,"name":32,"path":33,"parent_code":34},[406,407],{"code":49,"slug":158,"name":159,"path":160,"parent_code":34},{"code":223,"slug":224,"name":225,"path":226,"parent_code":34},{"status":37,"locked":14,"version":38,"method":39,"evidence":409},{"candidates":410,"agricultural_evidence":44},[411,415,420],{"code":30,"score":86,"supported":44,"title":412,"abstract":413,"tags":414},[32,31],[32],[28],{"code":49,"score":416,"supported":44,"title":417,"abstract":418,"tags":419},19,[53,236],[53],[],{"code":223,"score":170,"supported":44,"title":421,"abstract":422,"tags":423},[241],[],[],[425,426],"大豆玉米带状复合种植 变量喷药 延时补偿 处方图","大豆玉米带状复合种植 变量喷药","大豆玉米带状复合种植变量喷药延时补偿处方图-790","2026-08-21T00:05:57.531874Z"]