[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4715":3,"related-4715":63},{"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":22,"tags":24,"primary_topic":30,"secondary_topics":36,"classification":37,"search_phrases":57,"slug":60,"view_count":61,"doi":8,"paper":8,"created_at":62},4715,"山东农科院在东营发布20项盐碱地农业创新成果","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694254110089937434\u002F","山东省农科院在东营举办盐碱地科技成果观摩会,集中发布20项盐碱地创新成果,涵盖耐盐碱种业、高效种植等领域,为推动黄河三角洲盐碱地农业高质量发展提供科技支撑,助力盐碱地综合利用与后备耕地资源开发",null,"[](https:\u002F\u002Fwww.toutiao.com\u002F)\n\n*   关注 \n*   推荐 \n*   北京   \n*   视频 \n*   财经 \n*   科技 \n*   热点 \n*   国际 \n*   更多 \n\n    *   军事 \n    *   体育 \n    *   娱乐 \n    *   历史 \n    *   美食 \n    *   [直播](https:\u002F\u002Flive.ixigua.com\u002F) \n    *   旅游 \n    *   [懂车帝](https:\u002F\u002Fwww.dongchedi.com\u002F?zt=tt_pc_home_channel) \n\n搜索\n\n[消息](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694254110089937434\u002F)\n\n[发布](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7694254110089937434\u002F)\n\n[登录](https:\u002F\u002Fsso.toutiao.com\u002Flogin\u002F?service=https%3A%2F%2Fwww.toutiao.com%2Farticle%2F7694254110089937434%2F%3Fwid%3D1791763883533)\n\n1\n\n评论\n\n收藏\n\n分享\n\n*   转发到头条 \n*   复制链接 \n*   微信  微信扫码分享  \n*   新浪微博 \n*   QQ空间 \n\n# 《山东新闻联播》关注东营：山东省农业科学院发布20项盐碱地创新成果\n\n2026-10-08 19:15·[闪电新闻](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAA3KU9ifwN12G41E6PJRpZgIfzVrXWQ4WPF66ns54c0uw\u002F?source=tuwen_detail)\n\n[Video 3](https:\u002F\u002Fv6-web.toutiaovod.com\u002F13b0c9a2e5873fbd9c321a87bc5a098e\u002F6acc33da\u002Fvideo\u002Ftos\u002Fcn\u002Ftos-cn-ve-31\u002Fo8hg7IHwOY1Ayeu9qB7uBtYBeAvaZg2CoQoOt5\u002F?a=24&ch=0&cr=0&dr=0&er=0&cd=0%7C0%7C0%7C0&br=1161&bt=1161&cs=0&ds=4&ft=hGkwBy6LRR0s~hC32D12Nc.xBiGNbLlNK1RU_4hf~wC9Nv7TGW&mime_type=video_mp4&qs=0&rc=Zjw7Ozk1ZTkzZGUzMzs8OUBpanZrZ2ZvOnJxZTMzNGkzM0BgYWI0YjItXmIxXmA1NGIxYSNwYV4zYWFeajBhLS1kLi9zcw%3D%3D&btag=80000e00010000&dy_q=1791763888&feature_id=59cb2766d89ae6284516c6a254e9fb61&l=2026101208112863D1102055F6562253AA)重播\n\n暂停\n\n00:00\u002F00:00 直播\n\n00:00\n\n进入全屏\n\n50\n\n点击按住可拖动视频\n\n山东省农业科学院盐碱地科技成果观摩会日前在东营举行，集中发布了20项盐碱地创新成果，涵盖耐盐碱种业、高效种植等领域。\n\n举报\n\n评论 0\n\n请先 登录 后发表评论～\n\n今日头条推荐引擎有 9 条更新\n\n[![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002F9458a9ed9e89e244303e5f022d4ffd5e~tplv-tt-cs0:720:1280.jpg?_iz=31826&bid=11&from=article.headline&gid=7695279513906790922&lk3s=06827d14&x-expires=1794355888&x-signature=0igJ8VoWj0TqQica3jZxLsqa7%2Fg%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695279513906790922\u002F \"英国一男子翻入野生动物园老虎区，跳舞与老虎合影，被老虎咬死\")\n\n[英国一男子翻入野生动物园老虎区，跳舞与老虎合影，被老虎咬死](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695279513906790922\u002F)\n\n[齐鲁壹点](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAha-cmGWXuCx_sGK9sH8UvpmE3YBcidADDi4D24veLvM\u002F?source=tuwen_detail)\n\n[1评论](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695279513906790922\u002F#comment)\n\n18小时前\n\n[![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-6w9my0ksvp\u002F8e8b9eedb55d4641b3ac354f78f5a268~tplv-tt-cs0:1080:810.jpg?_iz=31826&bid=11&from=article.headline&gid=7695225592622383616&lk3s=06827d14&x-expires=1794355888&x-signature=mU6uV7oJ0ViDfPlS9PA0ql%2FBHas%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695225592622383616\u002F \"新疆五胞胎（1男4女）在武汉出生，坐36小时火车抵达乌鲁木齐；全车厢组团帮忙带娃，有旅客爱不释手：现在打开手机相册都是这五个宝宝\")\n\n[新疆五胞胎（1男4女）在武汉出生，坐36小时火车抵达乌鲁木齐；全车厢组团帮忙带娃，有旅客爱不释手：现在打开手机相册都是这五个宝宝](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695225592622383616\u002F)\n\n[长江日报](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAmniXb9spoq69J7vUOYDislykglyZEkoIe3CGLKAcFRs\u002F?source=tuwen_detail)\n\n[88评论](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695225592622383616\u002F#comment)\n\n21小时前\n\n[![Image 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凌晨钓鱼“被鱼钓”！江西一男子夜钓失足坠入赣江-图4](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fd90a3fafd41bf9844c187c8aaa498255~tplv-tt-cs0:568:320.jpg?_iz=31826&bid=10&from=article.headline&gid=7695561279640977947&lk3s=06827d14&x-expires=1794355888&x-signature=9HtllE3WGDW3vBy%2B8GB5uofSIYU%3D)](https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7695561279640977947\u002F) \n\n[极目新闻](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAeateBb9Su8I3MJOZozmvyzWktmba5LMlliRDz1KffnM\u002F?source=tuwen_detail)\n\n22分钟前\n\n*   [![Image 15](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-e874c6\u002Fog72Arg0AywE9EvitpAaiCyWaHHzIon3xBIwg~tplv-tt-cs0-jzss2:960:540.jpg?_iz=31127&bid=16&from=ttvideo.headline&gid=7691522977803797031&lk3s=06827d14&x-expires=1792368688&x-signature=j%2BYm1FsEL3Gyy50PD4gkRIB%2F2OY%3D)](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7691522977803797031\u002F \"关于“抗美援朝”，这是我听过最有水平的解读，听完才懂为什么称它为立国之战\")37:19   [关于“抗美援朝”，这是我听过最有水平的解读，听完才懂为什么称它为立国之战](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7691522977803797031\u002F \"关于“抗美援朝”，这是我听过最有水平的解读，听完才懂为什么称它为立国之战\")[正能量的分享](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAauyIU3qYX-2N21aj7Wqnd-8adm_oxZ968VtE2SFf0B5g5XM0qMcOLCfdZc93chmA\u002F?source=tuwen_detail) [30评论](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7691522977803797031\u002F) 10月01日        \n*   [![Image 16](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-e874c6\u002FokWE8zhIIAZgY3NPIsiIApED2Wjwi0ag8gSAB~tplv-tt-cs0-jzss2:640:360.jpg?_iz=31127&bid=16&from=ttvideo.headline&gid=7694665717601403421&lk3s=06827d14&x-expires=1792368688&x-signature=QcljyBvBGhSwH6Wxnmi4CtZ9w2k%3D)](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7694665717601403421\u002F \"一口气听完乾隆的一生。\")30:26   [一口气听完乾隆的一生。](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7694665717601403421\u002F \"一口气听完乾隆的一生。\")[睡前听历史](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAA8OMozRzweKv6cbKRxGP_CAGbBypzqd7dQzZs19FgetSAW_Em0RsIftysnN9mxodD\u002F?source=tuwen_detail) [1评论](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7694665717601403421\u002F) 3天前        \n\n[![Image 17](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-ezhpy3drpa\u002F7d82204471474576b798021b39354fc0~tplv-tt-post:640:360.jpeg?_iz=97245&bid=15&from=post.headline&gid=1878650580417676&lk3s=06827d14&x-expires=1799539200&x-signature=Nn56OEH7Yvz%2Bvxhud%2BmYOYHvRiQ%3D)](https:\u002F\u002Fwww.toutiao.com\u002Fw\u002F1878650580417676\u002F)\n\n[![Image 18](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Fuser-avatar\u002F4b1ee93d07c81d146fe0b05b3d8a8a62~300x300.image?_iz=112761&from=tt_user.headline_wtt&lk3s=06827d14&x-expires=1792454400&x-signature=oajSqY%2FzDIuv3S5JpKj9ux%2Bxq80%3D)名扬史海](https:\u002F\u002Fwww.toutiao.com\u002Fc\u002Fuser\u002Ftoken\u002FMS4wLjABAAAAXaOOsPRE-AZlpYA14uEzRTG4dG6s_bxru34xTmHLRLLI2_E0720YTsSR4ZaSdWrf\u002F?source=tuwen_detail \"名扬史海\")\n\n前天22:49\n\n关注\n\n[2009年，李冰冰开出12万月薪招保姆，其中一位保姆应聘，将菜里里外外洗了5、6遍，才给李冰冰看。而李冰冰只看了一眼，直接将菜连带菜篮子一起扔进了垃圾桶，因此，李冰冰3年面试20多人却始终没有找到合适人选。 参考资料：中国网--《李冰冰透露自己的身体状态不佳，因吃药无用感到绝望》 说实话，李冰冰这个洁癖，真不是一般人能想象的。 2009年那会儿，她曾开出12万的月薪招保姆。 你没听错，12万，搁那年头在小县城都够付个首付了。 可结果呢？前前后后面了50多号人，愣是一个都没留下。 一位阿姨把菜叶子翻来覆去地揉搓了五六遍，叶片都快被搓烂了，才忐忑地端过去给她过目。 李冰冰眼皮都没抬，只扫了一眼，便连菜带篮子直接丢进了垃圾桶。 阿姨当场愣住，心里直犯嘀咕：这洗得还不够透亮？ 其实症结出在第一步，没戴手套。 李冰冰的逻辑很\"刚\"：手上的细菌早就沾上去了，后面再怎么洗都是白费功夫。 她的要求是先用盐水泡上几个钟头杀菌，全程必须戴手套，洗完立刻下锅，一步都错不得。 三年光景，她前前后后打发了20多位保姆。 有个保姆擦拭门把手时漏了消毒这一环，她当晚便将家里所有门锁尽数换掉。 还有一位擦地板没按\"横三竖六遍\"的死规矩来，干了三天便被请走。 朋友去她家吃顿饭更是如履薄冰。 进门须套鞋套，落座要垫隔离垫，长发必须束起裹进头套，掉一根都算不合格。 有位圈内人曾去蹭过一顿饭，事后吐槽说那感觉活像进了无菌手术室，吃完还得来一轮全屋消杀。 2017年上《向往的生活》，节目组铺好的床铺她碰都不碰，非得从行李箱里拽出自己带的床单被褥换上。 旁边的人问她出个门怎么连被子都扛着，她说睡不惯外边的，枕着自己家的枕头才踏实。 去好莱坞拍戏行李箱塞两百片湿巾，片场道具不消毒不碰。 2010年金马奖领完奖，下台第一件事掏湿巾把奖杯底座擦三遍。 但你以为她天生就这样？不是的。 1973年，她降生于黑龙江五常一个清寒之家。 儿时记忆里，隆冬的工人宿舍连一丝暖气都没有，她和妹妹只能轮流裹那件补丁摞补丁的旧棉袄。 吃食永远短缺，衣裳常年散发着霉味。 那种逼仄、杂乱、什么都攥不住的无助感，早早便在她心底扎了根。 后来心理学将这种现象定义为\"补偿性控制\"。 早年越是失控，成年后便越渴望通过死抠细节来填补内心的空洞。 于她而言，\"洁净\"便是抵御不安的那面盾牌。 更何况，她所承受的工作强度，非常人所能扛。 《风声》里连拍三天酷刑戏，她愣是没合过眼。 《狄仁杰》的武打戏份让她摔断过腿骨。 初闯好莱坞时语言不通，每天仅靠三小时睡眠硬撑。 2015年拍《谜巢》，她连续高烧十七天不退，一度怀疑自己染上了重症肺炎。 2018年《巨齿鲨》全球狂揽超五亿美元票房，可辉煌背后，失眠、畏寒、浑身乏力如附骨之疽。 最严重的时候，连呼吸都成了一种折磨。 工作压力越大，她对生活里那点\"能自己说了算\"的事就越较真。 当工作和身体都管不了的时候，碗洗没洗干净、门把手有没有细菌，成了她唯一能掌控的东西。 这股劲儿在家里也闹过不少矛盾。 2015年有一回，她爸洗碗不用洗洁精，用钢丝球刷刷就完事。 她盯着碗沿觉得浑身难受，非说不用洗洁精冲不干净。 七十多岁的老爷子把碗一摔：\"今天我不洗了！\"她还嘟囔着说父亲不听劝。 父女俩争的根本不是洗碗，是一个要简单利落，一个要一尘不染的确定感。 2021年她第一次公开说自己\"病了\"，有焦虑症和强迫症。 那些年她把自己活成了上发条的机器人，用条条框框囚着自己，也折腾着身边的人。 好在这几年她开始接受心理干预，学着爬山、静坐，慢慢松手。 2024年公司年会上，有人看到她还是会掏湿巾擦椅子，但动作比以前慢了，少了当年的慌张。 以前非得绝对干净的地方，现在也能接受\"差不多就行\"了。 从把菜篮子扔垃圾桶，到如今能跟自己和解，这条路她走了十几年。 说实话，一个人能正视自己的问题、慢慢走出来，挺不容易的。 您身边有没有那种对干净特别讲究的人呢？您怎么看待李冰冰从当年的严苛到如今慢慢松弛下来的这种转变？欢迎在评论区聊聊您的看法。](https:\u002F\u002Fwww.toutiao.com\u002Fw\u002F1878650580417676\u002F)\n\n分享\n\n*   转发到头条 \n*   复制链接 \n*   微信  微信扫码分享  \n*   新浪微博 \n*   QQ空间 \n\n[77](https:\u002F\u002Fwww.toutiao.com\u002Fw\u002F1878650580417676\u002F#comment)\n\n89\n\n热门：\n*   [#维护婚姻正能](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694982124088384177 \"#维护婚姻正能量 #家家有本难念的经 #家庭情感短剧 #别在爱情里当傻瓜 #轮椅勇哥\")\n*   [男子发现货车的](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694982093876595994 \"男子发现货车的漏洞，组团疯狂薅羊毛，10天狂赚600万暴富 \")\n*   [夏雨荷那样的白](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694982041938562367 \"夏雨荷那样的白富美是怎么被乾隆骗了一辈子的？ #还珠格格 #好剧推荐 #一代人的回忆 #影娱漫谈编辑部\")\n*   [中国人中国心一](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694981994098645105 \"中国人中国心一家亲 #抖音直播正能量分享 #主播正能量传播 #传递正能量直播 #直播传递正能量 #郝大帅 @DOU+小助手\")\n*   [沙漠初体验！](https:\u002F\u002Fm.ixigua.com\u002Fdx\u002F7694981973329514890 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\"文明的漂泊者，解剖鸣潮最深的秘密，鸣潮剧情解读02\")\n12万次播放\n\n[03:00](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7457706494557946380\u002F)\n\n[新余，绿意盎然的城市，仙女湖畔波光潋滟，抱石公园文化深邃……](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7457706494557946380\u002F \"新余，绿意盎然的城市，仙女湖畔波光潋滟，抱石公园文化深邃……\")\n12万次播放\n\n[00:58](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7457893919833981475\u002F)\n\n[这里蕴藏长春的一段故事记录着的人情冷暖](https:\u002F\u002Fwww.toutiao.com\u002Fvideo\u002F7457893919833981475\u002F \"这里蕴藏长春的一段故事记录着的人情冷暖\")\n7万次播放\n\n*   点击回到头条首页 首页\n*   反馈\n*   下载 扫码下载今日头条  \n*   顶部\n\n登录后内容更精彩","闪电新闻 2026-10-08","2026-10-08T00:00:00Z","报道",10,false,58,{"impact":17,"substance":18,"depth":13,"authority":13,"freshness":19,"relevant":20,"comment":21},18,14,6,1,"省级科研机构在东营集中发布20项盐碱地农业创新成果，属细分领域实质进展，但报道内容较简略，时效性一般。",[23],{"name":10,"url":6},[25,26,27,28,29],"耐盐碱种业","山东省农科院","盐碱地农业","成果发布","东营",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},"H2","soil","土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",[],{"status":38,"locked":14,"version":39,"method":40,"evidence":41},"classified","2026-10-22.2","rules",{"candidates":42,"agricultural_evidence":45},[43,50],{"code":31,"score":44,"supported":45,"title":46,"abstract":48,"tags":49},11,true,[47],"盐碱地",[47],[],{"code":51,"score":52,"supported":45,"title":53,"abstract":54,"tags":56},"F1",3,[],[55],"种业",[],[58,59],"山东农科院 盐碱地 创新成果","东营 盐碱地 耐盐碱种业","山东农科院盐碱地创新成果-4715",0,"2026-10-12T00:11:04.689412Z",{"total":19,"page":20,"page_size":19,"items":64},[65,121,184,256,341,424],{"id":66,"title":67,"url":68,"summary":69,"summary_zh":8,"content":70,"source_name":71,"source_url":8,"published_at":72,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":73,"score_detail":74,"sources":78,"tags":80,"primary_topic":84,"secondary_topics":90,"classification":92,"search_phrases":116,"slug":119,"view_count":19,"doi":8,"paper":8,"created_at":120},3290,"亩产687.5公斤！山东盐碱地花生创下高产新突破——山东省农科院选育花育9131、9135、9136三个高油酸花生新品种","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7687500267012637190\u002F","9月18日，位于省黄三角农高区的山东省农科院东营基地内传来丰收喜讯：依托优质耐盐碱品种与先进栽培技术，示范区种植的三个高油酸花生新品种实现盐碱地高产突破，单品种荚果亩产量均突破600公斤，最高亩产量达687.5公斤。这三个品种是团队在东营盐碱地上历经多年筛选出来的耐盐碱高油酸花生：花育9131、花育9135、花育9136。今年山东气候特殊，花生下果针的7月、荚果充实的8月遭遇持续干旱，可示范田里花生秧蔓虽不算高大，拔起一株根须上挂满密密实实的荚果，捏开外壳果仁饱满厚实。土壤盐分含量2.8‰、PH值7.56。","视频加载中...\n\n9月18日，位于省黄三角农高区的山东省农科院东营基地内传来丰收喜讯，依托优质耐盐碱品种与先进栽培技术，示范区种植的三个高油酸花生新品种实现盐碱地高产突破，单品种荚果亩产量均突破600公斤，最高亩产量达687.5公斤。\n\n秋风掠过的盐碱试验田，泥土裹挟着花生果实的清香扑面而来。田垄之间，测产专家、科研人员、田间工人忙中有序，丈量地块、刨秧甩果、捡拾落果、去杂称重，一场耐盐碱高油酸花生新品种的测产验收正在紧张进行。\n\n脚下这片示范田，为典型滨海盐渍化土壤，土壤盐分含量2.8‰、PH值7.56，种植条件一般。今年山东气候特殊，花生下果针的7月、荚果充实的8月遭遇持续干旱，全省不少地块花生株高受限，出现“果大仁空”现象。可眼前示范田里，花生秧蔓虽不算高大，拔起一株，根须上挂满密密实实的荚果，捏开外壳，果仁饱满厚实。\n\n![Image 1](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-axegupay5k\u002F7c75be662afd4eddbda3c60cf768a161~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1790813093&x-signature=ceo9xNT5tnTa9T4D8DBWDnNp16I%3D)\n“这三个品种，是我们团队在东营盐碱地上历经多年筛选出来的耐盐碱高油酸花生，分别是花育9131、花育9135、花育9136。”国家花生产业技术体系遗传改良研究室主任、山东省花生研究所遗传育种创新团队负责人迟晓元蹲在田垄边，随手捧起一把刚刨出的花生介绍道。迟晓元2008年参加工作便投身花生育种，她们课题组从2013年起扎根滨州、东营开展花生耐盐碱筛选试验，一晃已是十余个年头。\n\n盐碱地育种，绝非一年试验就能下定论。“不同地块盐分分布不均匀，必须常年连续筛选，积累多年试验数据，反复比对，才能甄别真正耐盐碱的好品种。”迟晓元说。试验基地划分两块田地，一块是示范田，另一块筛选圃常年放置多份花生种质材料，不间断开展抗逆鉴定。材料要经过多轮考验，表现稳定后，才进入示范种植环节。\n\n本次测产验收由专业专家组全程核验，专家组由山东省种子管理总站、青岛农业大学、东营市农业综合服务中心等单位的农技推广、作物栽培、种子管理领域专家组成。 测产严格按照相关规范执行：专家组在听取课题组总体情况介绍后，每个品种地块选取3个测产点，每样点面积0.01亩，人工刨秧摘果、去杂后称重。测产结果出炉：按折干率55%计算，花育9131、花育9135和花育9136荚果产量分别为679.25、609.58和687.50公斤\u002F亩。\n\n“三个新品种果实饱满，单株结果数量多，在中度盐碱地叠加当年持续干旱的不利条件下，取得这样的产量，充分展现品种优异的耐盐、抗旱、高产特性，产业化应用前景广阔。”来自青岛农业大学的测产专家柳新伟现场点评。试验采用的一垄四行根域微地形种植模式，形成田间微地形，下雨时水流顺着垄沟排走，垄面保持相对低盐环境，抗涝抑盐，良种良法配套，进一步释放产量潜力。花生属于豆科作物，自身具备固氮能力，无需额外土壤改良，可作为盐碱地改良先锋作物，持续改善地力，为后续其他作物种植打下基础。\n\n记者了解到，花育9131、花育9135、花育9136均为高油酸品种，其中花育9135、花育9136为今年登记的新品种。三个品种已经完成独家品种权转让，分别授权给两家河南企业、一家山东企业，企业拿到授权后正加紧繁育推广，打通了从实验室试验田走向市场的成果转化通道。\n\n![Image 2](https:\u002F\u002Fp3-sign.toutiaoimg.com\u002Ftos-cn-i-tjoges91tu\u002Fc10dea7011178b18cff9cf5afe81e9e1~tplv-tt-origin-web:gif.jpeg?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1790813093&x-signature=fa2EWkbEGIGM24I%2BzragFRZZ3J8%3D)\n“高油酸花生有两大优点。”迟晓元介绍，营养价值高、耐储性好。高油酸花生中油酸含量高达75%以上，能有效降低低密度脂蛋白胆固醇水平，有益心血管健康；同时油酸性质稳定，花生及制品不易氧化酸败，货架期更长。与普通花生果相比，高油酸花生果农民增收1元\u002F公斤，榨油企业增收6000-8000元\u002F吨。”\n\n“花生单位面积产量、产油量和种植效益均居国内大宗油料作物首位，且耐瘠薄、抗旱耐盐碱，不与粮食作物争地，盐碱地正是扩种花生的重要阵地。”迟晓元感慨。山东拥有近900万亩盐碱地，仅东营就有约300万亩。落实“扩面积、提单产、提品质”的花生发展方向，把沉睡的盐碱地利用起来，发展耐盐碱花生，正是践行大食物观，实现“以种适地”，提升油料供给保障能力的重要路径。（大众新闻记者 杨珂 李明 通讯员 王敏 宋少双）","大众日报 2026年09月20日","2026-09-20T06:27:00Z",77,{"impact":75,"substance":75,"depth":76,"authority":13,"freshness":19,"relevant":20,"comment":77},22,17,"山东盐碱地高油酸花生新品种亩产突破687.5公斤，耐盐抗旱数据翔实，成果转化路径清晰，对盐碱地综合利用和油料产能提升有示范意义。",[79],{"name":71,"url":68},[81,26,82,27,83],"种业振兴","高油酸花生","耐盐碱品种",{"code":85,"slug":86,"name":87,"path":88,"parent_code":89},"A4","soybean-oilseeds","大豆与油料","\u002Ftopic\u002Ffield-crops\u002Fsoybean-oilseeds","A",[91],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"status":38,"locked":14,"version":39,"method":40,"evidence":93},{"candidates":94,"agricultural_evidence":45},[95,100,106,112],{"code":31,"score":18,"supported":45,"title":96,"abstract":97,"tags":99},[47],[98,47],"土壤",[],{"code":85,"score":101,"supported":45,"title":102,"abstract":104,"tags":105},12,[103],"花生",[103],[82],{"code":107,"score":52,"supported":45,"title":108,"abstract":109,"tags":111},"H7",[],[110],"干旱",[],{"code":51,"score":20,"supported":14,"title":113,"abstract":114,"tags":115},[],[],[81],[117,118],"山东农科院 花育9131 花生","盐碱地 高油酸花生 亩产","山东农科院花育9131花生-3290","2026-09-24T00:03:56.972784Z",{"id":122,"title":123,"url":124,"summary":125,"summary_zh":8,"content":126,"source_name":127,"source_url":8,"published_at":128,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":129,"score_detail":130,"sources":135,"tags":137,"primary_topic":141,"secondary_topics":142,"classification":143,"search_phrases":178,"slug":181,"view_count":182,"doi":8,"paper":8,"created_at":183},1475,"中国农科院发布 2026 国际盐碱地农业大会（ICSA-2026）一号通知：10 月 20 日山东黄河三角洲农高区启幕","https:\u002F\u002Fcaas.cn\u002Ftzgg\u002Fxshy\u002Ffcbf0157e5954cc1890e7e0c428ceed2.htm","2026 国际盐碱地农业大会（ICSA-2026）定于 2026 年 10 月 20—23 日在山东省黄河三角洲农业高新技术产业示范区召开。全体会议将邀请盐碱地农业、旱地农业、水资源管理领域国内外知名专家作主旨报告；平行会议设七大专题方向（盐碱地生物育种、盐碱地精准监测与生态管理、节水与旱作农业、智慧设施与农机装备、INSAS 专题、盐碱地特色农产品精深加工与高值利用、人才与学科建设）；大会工作语言为英语，并面向各界征集原创研究论文。","**2026国际盐碱地农业大会（ICSA-2026）**\n\n**“盐碱地可持续利用与全球粮食安全”**\n\n**中国东营，2026年10月20日至23日**\n\n**一、会议背景**\n\n受全球气候变化与人类活动加剧的双重影响，土壤盐渍化已成为全球干旱、半干旱及滨海地区分布最广、危害最突出的土地退化问题之一。联合国粮食及农业组织2023年数据显示，全球盐渍化土壤总面积达13.81亿公顷，占陆地总面积的10.7%。此外，全球另有10.38亿公顷土壤存在潜在盐渍化风险。现阶段，全球约20%的耕地和33%的灌溉农田已受土壤盐渍化影响，且多地盐渍化程度每年以10%的速率加剧。据预测，到2050年，全球超过半数的耕地或将面临盐渍化威胁。\n\n我国盐碱地体量庞大、类型多样，分布于华北、东北、西北及东部沿海地区。受土地、粮食、人口三重矛盾制约，我国始终高度重视盐碱地综合利用工作，并已将其上升为国家战略。中共中央办公厅、国务院办公厅联合印发《关于推动盐碱地综合利用的意见》，并由科技部于2022年12月批复组建国家盐碱地综合利用技术创新中心（NTICSA），围绕盐碱地生物育种、盐碱地改良与产能提升、盐碱地生态化及高值化利用三大科研创新重点方向开展全国协同攻关。这一系列举措，为我国盐碱地农业发展提供了坚实科技支撑与技术方案。\n\n盐碱地是重要的耕地后备资源，对保障粮食与营养安全、应对气候变化、遏制土地退化、推进可持续发展具有重大战略意义。因此，统筹推进盐碱地综合利用、发展盐碱地农业，是维护区域乃至全球民生与粮食安全的关键举措。\n\n科技创新是盐碱地农业可持续发展的核心驱动力，国际合作则是重要催化剂。为进一步深化盐碱地农业发展领域国际合作，国家盐碱地综合利用技术创新中心（NTICSA）与联合国粮食及农业组织（FAO）携手各方合作伙伴，将于2026年10月在中国山东省东营市共同举办2026国际盐碱地农业大会（ICSA-2026）。\n\n本次大会致力于搭建重要交流平台，促进各方合作伙伴共享理论知识、实践经验与创新技术方案，共同推动盐碱地农业的可持续发展。会议将汇聚国内外政府部门、科研机构、高校、农技推广服务机构及相关企业代表，围绕前沿技术、创新实践模式、配套政策及学术合作开展研讨交流，共同推动全球盐碱地农业产业发展。\n\n**二、会议目标**\n\n1.梳理盐碱地综合利用领域最新科研进展与创新技术；\n\n2.交流盐碱地可持续治理与综合利用的实践模式及工作经验；\n\n3.明确推动可持续气候韧性盐碱地农业规模化发展的关键驱动因素与条件；\n\n4.确定重点行动方向，推动各方凝聚共识，共同发起全球可持续气候韧性盐碱地农业行动倡议。\n\n**三、会议组织机构**\n\n1.主办单位\n\n国家盐碱地综合利用技术创新中心（NTICSA），中国东营\n\n联合国粮食及农业组织土地与水资源司（FAO-NSL），意大利罗马\n\n2.承办单位\n\n盐碱地综合利用技术创新中心（CTISA），中国东营\n\n中国农业科学院[农业资源与农业区划研究所](http:\u002F\u002Fiarrp.caas.cn\u002F)（IARRP）\n\n中国农业科学院[农业环境与可持续发展研究所](http:\u002F\u002Fieda.caas.cn\u002F)（IEDA）\n\n中国农业科学院盐碱地农业中心（CESA）\n\n北方干旱半干旱耕地高效利用全国重点实验室（SKL-EUALC）\n\n农业水资源高效利用全国重点实验室（SKL-EUAWR）\n\n3.协办单位\n\n全球土壤伙伴关系—国际盐渍土壤网络（GSP-INSAS）\n\n全球农业水资源短缺框架（WASAG）\n\n国际生物盐碱农业中心（ICBA）\n\n国际干旱地区农业研究中心（ICARDA）\n\n国际水资源管理研究所（IWMI）\n\n国际半干旱热带地区作物研究所（ICRISAT）\n\n国家盐碱地农业科技创新联盟（NASTISA）\n\n国家旱地农业科技创新联盟（NASTIDA）\n\n山东省农业科学院（SAAS）\n\n中国农业科学院[作物科学研究所](http:\u002F\u002Fics.caas.cn\u002F)（ICS）\n\n中国农业科学院农业基因组研究所（AGIS）\n\n山东农业大学（SDAU）\n\n青岛农业大学（QAU）\n\n黄三角智能农机装备产业研究院（YRDIA）\n\n农业农村部旱作节水农业重点实验室（KLDA,MARA）\n\n农业农村部基因数据分析重点实验室（GAL,MARA)\n\n农业农村部盐碱地生物资源评价与利用重点实验室()\n\n4.支持单位（定期更新）\n\n金正大生态工程集团股份有限公司（中国临沭）\n\n青岛海大生物集团股份有限公司（中国青岛）\n\n山东省农业集团有限公司（中国济南）\n\n5.组织委员会（定期更新）\n\n联合主席：梅旭荣（NTICSA），李利锋（FAO）\n\n委员：Nora Berrahmouni（FAO），Jean Boroto（FAO），Thorunn Wolfram Petursdottir（FAO），佟玉欣（FAO），贡锡锋（CGIAR），艾超（CAAS），郝卫平（CAAS），贾曦（SAAS），姜奇彦（CAAS），冷畅俭（SDAU），李向东 （SAAS），李玉义（CAAS），刘录祥（CAAS），商连光（CAAS），王东伟（YRDIA），王韧（CAAS），杨长军（NTICSA），赵金山（QAU）\n\n秘书处：杨会娟（AHIDAYRD），荣子国（AHIDAYRD），张浩（AHIDAYRD），石雪萍（AHIDAYRD），李昊儒（CAAS），李生平（CAAS），刘思（CAAS），陆苗（CAAS）\n\n6.学术委员会（定期更新）\n\n联合主席：[唐华俊](https:\u002F\u002Fwww.caas.cn\u002Fzzjg\u002Flrld\u002Flryc\u002F29781f81c9594f7bb7f247581d6357d1.htm)（CAAS），Jorge Batlle-Sales（INSAS）\n\n委员：康绍忠（CAU），曹晓风（CAS），种康（CAS），徐明岗（SXAU），喻景权（ZJU），王立春（JAAS），路战远（IMAAAHS），George Papadakis (AUA)，傅向东（CAS），Aly Abousabaa（ICARDA），Mark Smith（IWMI），Tarifa Alzaabi（ICBA），Himanshu Pathak (ICRISAT)，Vinay Nangia（ICARDA），吴文斌（CAAS），易可可（CAAS），周文彬（CAAS），王桂荣（CAAS），刘开昌（SAAS）\n\n**四、专题会议主要内容**\n\n2026国际盐碱地农业大会设置全体会议、平行会议、高端对话及圆桌会议。\n\n全体会议将邀请盐碱地农业、旱地农业、水资源管理领域国内外知名专家作主旨报告。\n\n平行会议设置七大专题方向，邀请行业专家分享研究成果：\n\n1.盐碱地生物育种\n\n（1）耐盐碱植物基因大数据库及AI设计育种\n\n（2）耐盐种质资源鉴定、筛选与创新利用\n\n（3）耐盐关键基因挖掘与分子育种技术创新\n\n（4）适配盐碱环境的耐盐作物\u002F牧草优质高产品种培育\n\n（5）耐盐碱作物良种良法配套技术及应用\n\n2.盐碱地精准监测与生态管理\n\n（1）盐碱地智能监测、评估与预警技术\n\n（2）盐碱地生态化治理与土壤质量产能提升\n\n（3）盐碱地生态化治理利用模式\n\n3.节水与旱作农业\n\n（1）旱灾防控与气候韧性旱地农业\n\n（2）农业水资源智慧管控与节水灌溉\n\n（3）多水源优化配置与节水控盐\n\n（4）节水与旱地农业技术集成与区域实践\n\n4.智慧设施与农机装备\n\n（1）盐碱地智能农机装备创新应用\n\n（2）盐碱地智慧农业集成与创新应用\n\n5.依托政策、多方合作推进盐碱地可持续治理（INSAS专题）\n\n（1）盐渍土可持续治理政策与治理体系\n\n（2）盐渍土可持续治理能力建设、技术推广与国际合作\n\n（3）多方主体合作机制，加速可持续土壤治理技术落地，助力粮食安全与气候韧性提升\n\n6.盐碱地特色农产品精深加工与高值利用\n\n（1）盐碱地农产品品质特性与绿色加工技术\n\n（2）盐碱地特色农产品功能化开发与健康食品创制\n\n（3）盐碱地特色农产品副产物高值化利用与产业化应用\n\n7.人才与学科建设\n\n（1）盐碱地农业高端创新人才培育\n\n（2）盐碱地相关理工交叉学科建设\n\n（3）盐碱地农业国际教育与合作交流\n\n高端对话与圆桌会议将围绕科技创新、经济政策、人才培养与国际合作等议题展开交流。\n\n**五、会议语言**\n\n大会工作语言为英语。\n\n六、会议时间与地点\n\n本次会议的举办时间、地点及交通推荐详见下文：\n\n1.会议时间：2026年10月20日—23日\n\n2.会场地点：中国山东省黄河三角洲农业高新技术产业示范区智慧路8号\n\n3.大会推荐到达站点：\n\n机场：东营胜利机场、济南遥墙国际机场、青岛胶东国际机场，出站后可乘坐出租车或网约车前往会议地点（车程分别约40、110、140分钟）。\n\n高铁站：青州北站、青州市站、济南西站，出站后可乘坐出租车或网约车前往会议地点（车程分别约50、55、140分钟）。\n\n**七、征稿通知**\n\n现面向各界征集与盐渍土治理、改良修复技术、可持续利用相关的原创研究论文。所有投稿稿件均将开展同行评审，评审录用论文将收录至大会正式论文集，并择优推荐至SBB等国际刊物。\n\n投稿截止日期：2026年9月15日\n\n**八、咨询与注册**\n\n如有任何问题，可咨询大会秘书处。\n\n电话：+86-546-8908119\n\n电子邮件：icsa2026@126.com\n\n请通过链接（https:\u002F\u002Fwww.wenjuanjia.com\u002Fi\u002Fyuyunert）完成2026国际盐碱地农业大会注册，注册截止日期为2026年9月10日。\n\n可通过该链接（[http:\u002F\u002Fwww.nctisa.cn\u002Flist.html?listId=45）查看大会最新详情与更新信息。](http:\u002F\u002Fwww.nctisa.cn\u002Flist.html?listId=45%EF%BC%89%E6%9F%A5%E7%9C%8B%E5%A4%A7%E4%BC%9A%E6%9C%80%E6%96%B0%E8%AF%A6%E6%83%85%E4%B8%8E%E6%9B%B4%E6%96%B0%E4%BF%A1%E6%81%AF%E3%80%82)\n\n暂定会议日程（内容持续更新）\n\n**Time (UTC+8)****10 月 20 日（星期二）：****报到****日**\n**08:00-21:00****报到**\n**09:00–20:00****10 月 21 日（星期三）：第 1 天**\n**09:00-10:30****开幕式**\n**09:00-09:40**1.**欢迎致辞**\n\n国家盐碱地中心代表\n\n2.**开幕致辞**\n\n联合国粮食及农业组织代表\n\n相关部门代表\n**09:40-10:10**3.**报告\u002F出版物正式发布**\n\n从数据到决策：《2026 年盐碱地综合利用技术发展报告》发布，中国\n\n《盐碱地区适宜作物与种植模式农户指南》，联合国粮食及农业组织\n**10:10-10:20**4.**开场背景阐述**\n\n全球盐渍土现状（FAO 与 NCITSA）\n\n现状、挑战与机遇\n\n会议目标、预期成果及议程\n**10:20-10:30**5.**合作意向书\u002F谅解备忘录签约仪式**\n\n联合国粮食及农业组织与国家盐碱地中心签署合作意向书\n\n中国农科院与国际水资源管理研究所签署谅解备忘录\n**10:30-10:50****茶歇**\n**10:50-12:10****全体会议：主旨报告**\n**12:10-13:30****午餐休息**\n**13:30-16:00****全体会议：主旨报告**\n\n**圆桌会议：促进全球盐碱地农业发展倡议（与全体会议平行举办）**\n**16:00-16:30****茶歇**\n**16:30-18:00****高端对话：围绕盐碱地科技创新****、****政策环境与多方参与开展研讨**\n**18:30-20:00****欢迎晚宴**\n**09:00-18:00****10 月 22 日（星期四）：第 2 天**\n**09:00-16:00****平行会议**\n**09:00-12:00**平行会议一：盐碱地生物育种\n\n平行会议二：盐碱地精准监测与生态管理\n\n平行会议三：节水与旱作农业\n\n平行会议五：依托政策、多方合作推进盐碱地可持续治理\n\n平行会议六：盐碱地特色农产品精深加工与高值利用\n\n平行会议七：人才与学科建设\n\n圆桌会议：经济、政策专题\n**12:00-13:30****午餐**\n**13:30-16:00****平行会议**\n平行会议一：盐碱地生物育种\n\n平行会议二：盐碱地精准监测与生态管理\n\n平行会议三：节水与旱作农业\n\n平行会议四：智慧设施与农机装备\n\n平行会议七：人才与学科建设\n\n圆桌会议：人才培养与国际合作专题\n**16:00-16:30****茶歇**\n**16:30-18:00****闭幕式**\n\n平行会议、圆桌会议成果汇总汇报\n\n发布促进全球盐碱地农业发展倡议\n\n主办方总结展望、致闭幕辞\n**10 月 23 日（星期五）：第 3 天**\n**09:00-17:00****实地考察**\n\nl 上午场次：参观国家盐碱地中心平台、实验室与试验田\n\nl 下午场次：湿地与盐生植物调研（自愿参加，费用自理）\n**09:00-17:00****10 月 24 日（星期六）：离会日**","中国农业科学院·学术会议","2026-09-02T00:00:00Z",88,{"impact":131,"substance":75,"depth":17,"authority":132,"freshness":133,"relevant":20,"comment":134},25,15,8,"国家级科研机构与FAO联合主办的国际大会，聚焦盐碱地可持续利用，信息详实，具有较高产业与政策影响。",[136],{"name":127,"url":124},[138,139,27,140],"粮食安全","国际合作","学术会议",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":144},{"candidates":145,"agricultural_evidence":45},[146,150,156,162,168,173],{"code":31,"score":44,"supported":45,"title":147,"abstract":148,"tags":149},[47],[47],[],{"code":151,"score":52,"supported":45,"title":152,"abstract":153,"tags":155},"F2",[],[154],"生物育种",[],{"code":157,"score":52,"supported":45,"title":158,"abstract":159,"tags":161},"F5",[],[160],"农机",[],{"code":163,"score":52,"supported":45,"title":164,"abstract":165,"tags":167},"H3",[],[166],"水资源",[],{"code":169,"score":20,"supported":14,"title":170,"abstract":171,"tags":172},"A8",[],[],[138],{"code":174,"score":20,"supported":14,"title":175,"abstract":176,"tags":177},"J3",[],[],[139],[179,180],"盐碱地农业 国际合作 学术会议 粮食安全","盐碱地农业 国际合作","盐碱地农业国际合作学术会议粮食安全-1475",5,"2026-09-03T00:06:42.198165Z",{"id":185,"title":186,"url":187,"summary":188,"summary_zh":189,"content":8,"source_name":190,"source_url":187,"published_at":191,"category":192,"cover_url":8,"hotness":13,"is_selected":14,"score":193,"score_detail":194,"sources":198,"tags":200,"primary_topic":206,"secondary_topics":207,"classification":214,"search_phrases":234,"slug":237,"view_count":61,"doi":238,"paper":239,"created_at":255},5583,"Active-Labeling Evaluation for Computer Agriculture Nematode-Cyst Detection Under Sparse Soil-Sample Ground Truth: An Artificial Intelligence Annotation-Efficiency Bound","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23544145","Active learning promises to reduce the annotation burden of training nematode-cyst detection models for precision agriculture, but the size of that reduction is not known when ground truth comes from sparse soil samples rather than exhaustive visual inspection. the present analysis derives an annotation-efficiency bound for pool-based active learning under sparse soil-sample ground truth. The detection task is formalised as a two-stage process in which a classifier selects candidate cysts from soil imagery and a laboratory assay confirms a small labelled subset. Under a declared variance structure with between-cluster standard deviation 6.0, residual standard deviation 4.5 and intraclass correlation 0.64, the bound is evaluated across a design grid of 8, 16, 24 and 32 clusters and effect sizes of 3, 5 and 8 percentage points, with 2000 replications per cell. The annotation-efficiency gain is bounded by the ratio of label noise to cluster-level variance, and that 52 clusters are required to detect a 5-percentage-point improvement at 80% power. The bound provides a design rule for allocating annotation effort between active selection and confirmatory soil sampling.","主动学习有望减轻精准农业中训练线虫囊检测模型所需的标注负担，但当真实标签来自稀疏土壤样本而非详尽的视觉检查时，这种负担减轻的幅度尚不清楚。本分析推导了在稀疏土壤样本真实标签下基于池的主动学习的标注效率界限。检测任务被形式化为两阶段过程：分类器从土壤图像中筛选候选线虫囊，实验室检测确认一个小的已标注子集。在设定的方差结构下——组间标准差为6.0、残差标准差为4.5、组内相关系数为0.64——该界限在8、16、24和32个簇的设计网格以及3、5和8个百分点的效应量下进行评估，每个单元格重复2000次。标注效率增益受标签噪声与簇级方差之比的约束，并且在80%检验功效下检测5个百分点的改进需要52个簇。该界限为在主动选择与验证性土壤采样之间分配标注工作量提供了设计规则。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z","论文",64,{"impact":133,"substance":195,"depth":76,"authority":196,"freshness":13,"relevant":20,"comment":197},20,9,"该研究给出稀疏土壤样本下主动学习标注效率的理论边界与聚类设计规则，方法新颖、结论具体，但属细分方法学研究，产业影响有限，适合作为专业精选而非头条。",[199],{"name":190,"url":187},[201,202,203,204,205],"智慧农业","农业人工智能","主动学习","线虫检测","土壤采样",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[208],{"code":209,"slug":210,"name":211,"path":212,"parent_code":213},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",{"status":38,"locked":14,"version":39,"method":40,"evidence":215},{"candidates":216,"agricultural_evidence":45},[217,221,226],{"code":31,"score":18,"supported":45,"title":218,"abstract":219,"tags":220},[32],[98,32],[],{"code":209,"score":196,"supported":45,"title":222,"abstract":224,"tags":225},[223],"artificial intelligence",[],[202],{"code":227,"score":228,"supported":45,"title":229,"abstract":230,"tags":233},"I1",7,[],[231,232],"精准农业","precision agriculture",[201],[235,236],"线虫孢囊 检测 主动学习","稀疏土壤样本 标注效率","线虫孢囊检测主动学习-5583","10.5281\u002Fzenodo.23544145",{"doi":238,"openalex_id":240,"authors":241,"venue":190,"cited_by_count":61,"oa_url":187,"card":248,"direction":252,"ingested_from":254},"W7223082195",[242,244,246],{"name":243,"orcid":8},"Amine Ben Salah",{"name":245,"orcid":8},"Ines Trabelsi",{"name":247,"orcid":8},"Mohamed Aziz Khelifi",{"tldr":249,"method":250,"finding":251,"direction":252,"opportunity":253},"推导稀疏土壤样本真值下主动学习标注效率的理论上界。","基于方差结构与设计网格的统计模拟，2000次重复。","标注效率增益受标签噪声与簇间方差之比限制，检测5个百分点提升需52簇。","农业人工智能与决策模型","可将该上界推广到其他稀疏真值农业检测任务，并探索主动选择与确认采样的最优分配策略。","openalex","2026-10-22T11:20:58.901747Z",{"id":257,"title":258,"url":259,"summary":260,"summary_zh":261,"content":8,"source_name":262,"source_url":259,"published_at":263,"category":192,"cover_url":8,"hotness":13,"is_selected":14,"score":264,"score_detail":265,"sources":268,"tags":270,"primary_topic":276,"secondary_topics":277,"classification":278,"search_phrases":302,"slug":305,"view_count":61,"doi":306,"paper":307,"created_at":340},5576,"Land cover change and soil salinization in Mozambique: A counterfactual analysis over two decades (2001−2022)","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.catena.2026.110691","Soil salinization is a major issue that constrains the sustainable development of agriculture in arid, semi-arid, and coastal lowland areas. It is of great importance for regional land management and climate adaptation to clarify the influence of land cover change on soil salinization. This study aims to quantitatively assess the contribution of land cover change to soil salinization in Mozambique, where both rapid land cover transformation and salinization issues are evident. Firstly, we integrated soil profile electrical conductivity (EC) data, Landsat time-series remote sensing imagery, TerraClimate meteorological data, and the 30 m resolution land cover data, to construct a remote sensing-based EC inversion model for Mozambique. Secondly, we applied a spatially and environmentally constrained counterfactual matching method to quantitatively identify the contributions of different land cover changes on soil salinization trends. Our results reveal that: (1) the spatial distribution of soil salinization in Mozambique exhibits distinct a clear association with proximity to water bodies, with high EC areas primarily concentrated around Lake Malawi in the north and in the coastal regions of Greater Maputo in the south. (2) 26.98% of Mozambique's territory showed a trend of intensifying soil salinization, while 10.88% exhibited a decreasing trend. Areas with intensifying trends are primarily concentrated in the central alluvial plains, localized agricultural development zones, and coastal lowlands. (3) Urbanization was significantly associated with an increasing salinization trend after false discovery rate correction, suggesting that the expansion of impervious surfaces, changes in drainage patterns, and soil compaction may exacerbate localized salt accumulation. Agricultural expansion showed a negative trend difference, consistent with the potential influence of crop cover, tillage, and wet-season leaching, although this association was not significant after false discovery rate correction. The effects of ecological restoration and other factors were not statistically significant. In addition to elucidating the heterogeneous impacts of land cover changes in Mozambique on soil salinization trends, this study also provides methodological guidance and a scientific basis for monitoring\u002Fmanaging soil salinity risks in other coastal lowlands.","土壤盐渍化是制约干旱、半干旱及沿海低地地区农业可持续发展的主要问题。阐明土地覆盖变化对土壤盐渍化的影响，对区域土地管理和气候适应具有重要意义。本研究旨在定量评估土地覆盖变化对莫桑比克土壤盐渍化的贡献，该国土地覆盖转型迅速且盐渍化问题突出。首先，我们整合了土壤剖面电导率（EC）数据、Landsat时间序列遥感影像、TerraClimate气象数据以及30 m分辨率土地覆盖数据，构建了基于遥感的莫桑比克EC反演模型。其次，我们采用空间与环境约束的反事实匹配方法，定量识别不同土地覆盖变化对土壤盐渍化趋势的贡献。研究结果表明：（1）莫桑比克土壤盐渍化的空间分布与水体邻近性呈现明显的关联，高EC区域主要集中于北部的马拉维湖周边以及南部大马普托沿海地区。（2）莫桑比克26.98%的国土面积呈现土壤盐渍化加剧趋势，而10.88%呈现减轻趋势。加剧趋势区域主要集中于中部冲积平原、局部农业开发区及沿海低地。（3）经错误发现率校正后，城市化与盐渍化加剧趋势显著相关，表明不透水面扩张、排水格局改变及土壤压实可能加剧局部盐分累积。农业扩张呈现负向趋势差异，与作物覆盖、耕作及湿季淋洗的潜在影响一致，但该关联经错误发现率校正后不显著。生态恢复及其他因素的影响在统计上不显著。本研究不仅阐明了莫桑比克土地覆盖变化对土壤盐渍化趋势的异质性影响，还为其他沿海低地土壤盐渍化风险的监测与管理提供了方法学指导和科学依据。","CATENA","2026-10-20T00:00:00Z",79,{"impact":266,"substance":75,"depth":17,"authority":18,"freshness":196,"relevant":20,"comment":267},16,"该研究基于遥感与反事实匹配方法，定量评估土地覆盖变化对盐渍化的贡献，方法新颖、结论可靠，对沿海低地盐渍化监测具有参考价值，但属境外区域研究，国内政策与产业影响有限。",[269],{"name":262,"url":259},[271,272,273,274,275],"遥感监测","莫桑比克","土壤盐渍化","土地覆盖变化","盐分反演",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":279},{"candidates":280,"agricultural_evidence":45},[281,285,292,297],{"code":31,"score":18,"supported":45,"title":282,"abstract":283,"tags":284},[32],[98,32],[],{"code":286,"score":228,"supported":45,"title":287,"abstract":288,"tags":291},"I3",[],[289,290],"遥感","remote sensing",[271],{"code":107,"score":19,"supported":45,"title":293,"abstract":294,"tags":296},[],[295,110],"气候适应",[],{"code":298,"score":20,"supported":14,"title":299,"abstract":300,"tags":301},"H6",[],[],[274],[303,304],"莫桑比克 土壤盐渍化 遥感","土地覆盖变化 盐渍化 反事实分析","莫桑比克土壤盐渍化遥感-5576","10.1016\u002Fj.catena.2026.110691",{"doi":306,"openalex_id":308,"authors":309,"venue":262,"cited_by_count":61,"oa_url":259,"card":334,"direction":338,"ingested_from":254},"W7223069171",[310,312,314,316,319,321,324,327,329,331],{"name":311,"orcid":8},"Yue Li",{"name":313,"orcid":8},"Mengfei Shi",{"name":315,"orcid":8},"Fei Zhang",{"name":317,"orcid":318},"Brian Alan Johnson","https:\u002F\u002Forcid.org\u002F0000-0003-1911-3585",{"name":320,"orcid":8},"Gowhar Meraj",{"name":322,"orcid":323},"Jaime Carlos Macuácua","https:\u002F\u002Forcid.org\u002F0000-0002-4822-6098",{"name":325,"orcid":326},"Pankaj Kumar","https:\u002F\u002Forcid.org\u002F0000-0002-5264-3951",{"name":328,"orcid":8},"Yuanfang Chai",{"name":330,"orcid":8},"Hongtao Xu",{"name":332,"orcid":333},"Xu Ma","https:\u002F\u002Forcid.org\u002F0000-0003-0644-7498",{"tldr":335,"method":336,"finding":337,"direction":338,"opportunity":339},"量化莫桑比克2001-2022年土地覆盖变化对土壤盐渍化的贡献。","融合EC剖面、Landsat时序与气候数据反演EC，并用空间环境约束的反事实匹配","26.98%区域盐渍化加剧；城市化显著关联盐渍化上升，农业扩张关联不显著。","农业遥感与作物表型","可将反事实匹配框架迁移至其他滨海低地，并引入作物类型与灌溉制度细化农业扩张的盐渍化效应。","2026-10-22T11:20:42.713789Z",{"id":342,"title":343,"url":344,"summary":345,"summary_zh":346,"content":8,"source_name":347,"source_url":344,"published_at":191,"category":192,"cover_url":8,"hotness":13,"is_selected":14,"score":73,"score_detail":348,"sources":352,"tags":354,"primary_topic":358,"secondary_topics":363,"classification":366,"search_phrases":400,"slug":403,"view_count":61,"doi":404,"paper":405,"created_at":423},5558,"Estimation of Soil Water Content in Winter Wheat Field at Jointing Stage Using Multi-Source Features and Machine Learning","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fagronomy16202071","Accurate and timely monitoring of soil water content (SWC) plays an essential supporting role in crop irrigation management and smart agricultural practice. Remote sensing technology provides rapid and convenient approaches to large-scale farmland SWC estimation or inversion. However, existing mechanistic modeling methods are limited by parameter localization and land surface heterogeneity, while machine learning data-driven methods lack quite good physical interpretability. To address deficiencies in single data-driven methods and single vegetation microwave scattering models, and explore the estimation effect of different feature variables in machine learning. This study proposes an innovative estimation model that integrates machine learning strategies and multi-source features, including spectral indices and features derived from the classic water cloud model (WCM). The novelty of the proposed model lies in balancing physical interpretability and data-driven accuracy, namely extracting relevant soil backscattering parameters through WCM, which are then used as input features in the machine learning. A combination of field-measured data and unmanned aerial vehicle (UAV) multi-source remote sensing data, including multispectral and synthetic aperture radar (SAR) data, was acquired synchronously at the jointing stage of winter wheat. Through extracting variables such as the SAR microwave backscattering coefficient and the optical vegetation index, and conducting feature screening and parameter sensitivity analysis, we optimized the input variable sets of models based on back-propagation (BP) neural network, support vector regression (SVR) and random forest (RF) algorithms. The study results showed that the established estimation model had excellent estimation performance, especially for the RF algorithm, with the highest R2 of 0.855, lowest MAE of 0.0212 cm3\u002Fcm3, and lowest RMSE of 0.0253 cm3\u002Fcm3. It was also shown that different feature input schemes have obvious effects on SWC estimation performance. On the whole, RF had the best estimation accuracy, followed by SVR and then BPNN. This study demonstrated that models integrating multi-source remote sensing data and machine learning could enhance SWC estimation ability for winter wheat fields, and could also serve as a promising approach for SWC monitoring in winter wheat fields in the North China Plain.","准确、及时地监测土壤含水量（SWC）对作物灌溉管理和智慧农业实践具有重要的支撑作用。遥感技术为大规模农田土壤含水量估算或反演提供了快速便捷的手段。然而，现有机理建模方法受参数本地化和地表异质性限制，机器学习数据驱动方法则缺乏良好的物理解释性。针对单一数据驱动方法和单一植被微波散射模型的不足，并探究不同特征变量在机器学习中的估算效果，本研究提出了一种融合机器学习策略与多源特征的创新估算模型，所采用特征包括光谱指数和经典水云模型（WCM）衍生的特征。该模型的新颖性在于平衡物理解释性与数据驱动精度，即通过WCM提取相关土壤后向散射参数，再将其作为机器学习的输入特征。研究在冬小麦拔节期同步获取了田间实测数据与无人机（UAV）多源遥感数据，包括多光谱和合成孔径雷达（SAR）数据。通过提取SAR微波后向散射系数和光学植被指数等变量，并进行特征筛选和参数敏感性分析，优化了基于反向传播（BP）神经网络、支持向量回归（SVR）和随机森林（RF）算法的模型输入变量集。研究结果表明，所建立的估算模型具有优良的估算性能，尤其是RF算法，最高R²为0.855，最低MAE为0.0212 cm³\u002Fcm³，最低RMSE为0.0253 cm³\u002Fcm³。研究还表明，不同特征输入方案对土壤含水量估算性能有明显影响。总体而言，RF估算精度最佳，SVR次之，BPNN再次之。本研究证明，融合多源遥感数据与机器学习的模型能够提升冬小麦田土壤含水量估算能力，也可为华北平原冬小麦田土壤含水量监测提供一种有前景的方法。","Agronomy",{"impact":266,"substance":349,"depth":76,"authority":350,"freshness":13,"relevant":20,"comment":351},21,13,"该研究融合多源遥感与机器学习估算冬小麦拔节期土壤含水量，方法有创新、结论可靠，对智慧灌溉有参考价值，但属细分领域论文，影响范围有限。",[353],{"name":347,"url":344},[201,355,271,356,357],"机器学习","土壤墒情","冬小麦",{"code":359,"slug":360,"name":361,"path":362,"parent_code":89},"A2","wheat","小麦","\u002Ftopic\u002Ffield-crops\u002Fwheat",[364,365],{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},{"code":209,"slug":210,"name":211,"path":212,"parent_code":213},{"status":38,"locked":14,"version":39,"method":40,"evidence":367},{"candidates":368,"agricultural_evidence":45},[369,375,379,384,389,395],{"code":359,"score":370,"supported":45,"title":371,"abstract":373,"tags":374},26,[372,360],"winter wheat",[361,372,360],[357],{"code":31,"score":132,"supported":45,"title":376,"abstract":377,"tags":378},[32],[98,32],[356],{"code":209,"score":132,"supported":45,"title":380,"abstract":382,"tags":383},[381],"machine learning",[355,381],[355],{"code":286,"score":13,"supported":45,"title":385,"abstract":386,"tags":388},[],[289,290,387],"multispectral",[271],{"code":163,"score":19,"supported":45,"title":390,"abstract":391,"tags":394},[],[392,393],"灌溉","irrigation",[],{"code":227,"score":396,"supported":45,"title":397,"abstract":398,"tags":399},4,[],[201],[201],[401,402],"冬小麦 土壤含水量 遥感","多源遥感 机器学习 墒情","冬小麦土壤含水量遥感-5558","10.3390\u002Fagronomy16202071",{"doi":404,"openalex_id":406,"authors":407,"venue":347,"cited_by_count":61,"oa_url":344,"card":417,"direction":422,"ingested_from":254},"W7223156204",[408,411,413,415],{"name":409,"orcid":410},"Mingliang Jiang","https:\u002F\u002Forcid.org\u002F0000-0002-6486-6087",{"name":412,"orcid":8},"Yi Zhang",{"name":414,"orcid":8},"WEI Lei",{"name":416,"orcid":8},"Chengcai Zhang",{"tldr":418,"method":419,"finding":420,"direction":338,"opportunity":421},"融合WCM物理特征与多源遥感，用机器学习估算冬小麦拔节期土壤含水量。","无人机多光谱与SAR数据，WCM参数+光谱指数，BP\u002FSVR\u002FRF建模。","RF最优，R²达0.855，RMSE为0.0253 cm³\u002Fcm³，特征方案影响显著。","可探索物理约束与深度学习耦合，并迁移至多生育期、多作物及不同土壤质地验证。","智慧农业 \u002F 农业物联网","2026-10-22T11:20:18.887301Z",{"id":425,"title":426,"url":427,"summary":428,"summary_zh":429,"content":8,"source_name":430,"source_url":427,"published_at":191,"category":192,"cover_url":8,"hotness":13,"is_selected":14,"score":431,"score_detail":432,"sources":434,"tags":436,"primary_topic":442,"secondary_topics":443,"classification":444,"search_phrases":464,"slug":467,"view_count":61,"doi":468,"paper":469,"created_at":493},5549,"Characterising climate mitigation and adaptation performance in oil palm plantation: evidence from Indonesia","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1871877","Despite growing demand for ‘climate-friendly’ palm oil, little is known about how existing soil and management conditions align with climate mitigation and adaptation goals. This study characterised the climate mitigation and adaptation performance of oil palm (OP) production across different soil and management conditions based on simulated carbon balance and productivity. The Agricultural Production Systems SIMulator (APSIM)-OilPalm model was used to simulate productivity and carbon balance in 25 industrial OP sites on mineral soils in North Sumatra, Indonesia. K-means clustering was used to group similarity patterns between simulated carbon balance and productivity with observed soil and management conditions data. The model has good skill in simulating OP productivity at sites with standard plant density, achieving coefficient of determination (R 2 ) yield up to 0.79, though performance is poor at plantations with plant density outside the standard range or very low observed yields. Simulated OP productivity exhibits moderate variability from 15.38 to 28.67 t fresh fruit bunch (FFB) ha −1 yr. −1 . Simulated carbon balance, which is comparable to measured values in the region, indicates that all observed OP sites serve as a carbon sink with low variability from −2.09 to −3.86 t C eq. ha −1 yr. −1 , driven by uniformity in climate factors and plant density. Eleven of 25 sites have good mitigation and adaptation performance, indicated by high carbon sinks, yield and soil organic carbon (SOC) increment. These sites are characterised by greater plant density and moderate levels of N fertilisation, sand content and Ganoderma boninense (G. boninense) infection, with low carbon nitrogen (CN) ratio. Over half of sites face climate adaptation challenges, indicated by either low productivity or SOC increment and characterised by low plant density and nitrogen fertiliser with high G. boninense infection and sandy soils. This study contributes information about mitigation and adaptation in determining the management of OP and supports the tracking of climate-friendly palm oil within broader supply chains.","尽管对“气候友好型”棕榈油的需求日益增长，但人们对现有土壤和管理条件如何与气候减缓及适应目标相协调知之甚少。本研究基于模拟碳平衡和生产力，表征了油棕（OP）生产在不同土壤和管理条件下的气候减缓与适应表现。研究采用农业生产系统模拟器（APSIM）-OilPalm模型，模拟了印度尼西亚北苏门答腊25个矿质土壤工业油棕样点的生产力和碳平衡。运用K均值聚类方法，将模拟碳平衡与生产力之间的相似性模式与观测到的土壤和管理条件数据进行分组。该模型在标准种植密度样点的油棕生产力模拟中具有良好能力，决定系数（R²）最高达0.79，但在种植密度超出标准范围或观测产量极低的种植园中表现较差。模拟油棕生产力呈现中等变异性，范围为15.38至28.67 t鲜果串（FFB）ha⁻¹ yr.⁻¹。模拟碳平衡与该地区实测值相当，表明所有观测油棕样点均为碳汇，变异性较低，范围为−2.09至−3.86 t C eq. ha⁻¹ yr.⁻¹，这归因于气候因子和种植密度的一致性。25个样点中有11个具有良好的减缓和适应表现，表现为高碳汇、产量和土壤有机碳（SOC）增量。这些样点的特征是种植密度较大，氮肥施用量、砂含量和灵芝（Ganoderma boninense，G. boninense）感染程度适中，碳氮（CN）比低。超过半数样点面临气候适应挑战，表现为生产力或SOC增量较低，其特征是种植密度和氮肥用量低、灵芝感染率高及砂质土壤。本研究为确定油棕管理中的减缓和适应提供了信息，并支持在更广泛供应链中追踪气候友好型棕榈油。","Frontiers in Sustainable Food Systems",80,{"impact":17,"substance":75,"depth":17,"authority":350,"freshness":196,"relevant":20,"comment":433},"基于APSIM模型对印尼25个油棕园碳平衡与生产力的模拟研究，方法清晰、数据具体，对气候友好型油棕管理与供应链追踪有参考价值，但属区域性论文，影响范围有限。",[435],{"name":430,"url":427},[437,438,439,440,441],"作物模型","气候智慧农业","油棕","碳汇","可持续种植",{"code":31,"slug":32,"name":33,"path":34,"parent_code":35},[],{"status":38,"locked":14,"version":39,"method":40,"evidence":445},{"candidates":446,"agricultural_evidence":45},[447,451,456,460],{"code":31,"score":19,"supported":45,"title":448,"abstract":449,"tags":450},[],[98,32],[],{"code":452,"score":396,"supported":45,"title":453,"abstract":454,"tags":455},"H4",[],[440],[440],{"code":107,"score":396,"supported":45,"title":457,"abstract":458,"tags":459},[],[295],[438],{"code":209,"score":20,"supported":14,"title":461,"abstract":462,"tags":463},[],[],[437],[465,466],"APSIM-OilPalm 油棕 碳平衡","印尼 油棕 气候适应","APSIM-OilPalm油棕碳平衡-5549","10.3389\u002Ffsufs.2026.1871877",{"doi":468,"openalex_id":470,"authors":471,"venue":430,"cited_by_count":61,"oa_url":427,"card":487,"direction":491,"ingested_from":254},"W7223112249",[472,475,478,481,484],{"name":473,"orcid":474},"Lisma Safitri","https:\u002F\u002Forcid.org\u002F0000-0002-7188-1058",{"name":476,"orcid":477},"Marcelo Valadares Galdos","https:\u002F\u002Forcid.org\u002F0000-0002-6080-0726",{"name":479,"orcid":480},"Iput Pradiko","https:\u002F\u002Forcid.org\u002F0000-0001-7877-8400",{"name":482,"orcid":483},"Alexis Comber","https:\u002F\u002Forcid.org\u002F0000-0002-3652-7846",{"name":485,"orcid":486},"Andrew Juan Challinor","https:\u002F\u002Forcid.org\u002F0000-0002-8551-6617",{"tldr":488,"method":489,"finding":490,"direction":491,"opportunity":492},"用APSIM模型模拟印尼油棕园碳平衡与产量，评估其气候减缓与适应表现。","APSIM-OilPalm模型模拟25个站点，结合K-means聚类分析土壤与管","所有站点均为碳汇，11个站点减缓与适应表现良好，过半站点面临适应挑战。","农业绿色发展与碳","可扩展至不同气候带与泥炭地油棕园，结合遥感数据构建区域尺度气候友好型油棕认证体系。","2026-10-22T11:20:15.883770Z"]