{"id":7113,"date":"2026-07-24T22:01:42","date_gmt":"2026-07-24T14:01:42","guid":{"rendered":"http:\/\/172.30.27.2\/?p=7113"},"modified":"2026-07-24T22:22:33","modified_gmt":"2026-07-24T14:22:33","slug":"guanyuzhaokai2025niandufrontiers-in-plant-sciencekechixuzhihuizhibaozhuanlanbanjiangyishijiqikanluna","status":"publish","type":"post","link":"http:\/\/172.30.27.2\/index.php\/guanyuzhaokai2025niandufrontiers-in-plant-sciencekechixuzhihuizhibaozhuanlanbanjiangyishijiqikanluna\/","title":{"rendered":"\u5173\u4e8e\u53ec\u5f002025\u5e74\u5ea6Frontiers in Plant Science\u53ef\u6301\u7eed\u667a\u6167\u690d\u4fdd\u4e13\u680f\u9881\u5956\u4eea\u5f0f\u66a8\u671f\u520a\u8bba\u575b\u7684\u901a\u77e5"},"content":{"rendered":"

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2026\u5e748\u670811\u65e5-13\u65e5\uff0c\u201c2026 CCF\u6570\u5b57\u519c\u4e1a\u5206\u4f1a\u5e74\u4f1a\u66a8\u7b2c\u56db\u5c4a CCF\u6570\u5b57\u519c\u4e1a\u5927\u4f1a\u201d\u671f\u95f4\uff0c\u540c\u671f\u53ec\u5f00\u201c\u53ef\u6301\u7eed\u667a\u6167\u690d\u4fdd\u671f\u520a\u8bba\u575b\u201d\u3002\u8bba\u575b\u73b0\u573a\u5c06\u9881\u53d12025\u5e74\u5ea6Frontiers in Plant Science\u671f\u520a\u53ef\u6301\u7eed\u667a\u6167\u690d\u4fdd\u4e13\u680fOutstanding Editor\u8bc1\u4e66\u548c2023\u5e74\u5ea6Best Article\u8bc1\u4e66\u3002\u8bda\u631a\u9080\u8bf7\u5404\u4f4d\u83b7\u5956\u7f16\u59d4\u548c\u83b7\u5956\u6587\u7ae0\u4f5c\u8005\u8385\u4e34\u51fa\u5e2d\u9881\u5956\u4eea\u5f0f\uff0c\u5171\u540c\u89c1\u8bc1\u8fd9\u4e00\u8363\u8a89\u65f6\u523b\u3002<\/p>\n

\u9664\u9881\u5956\u73af\u8282\u5916\uff0c\u4e3a\u4e30\u5bcc\u8bba\u575b\u5b66\u672f\u4ea4\u6d41\uff0c\u73b0\u9762\u5411\u83b7\u5956\u7f16\u59d4\u3001\u83b7\u5956\u8bba\u6587\u4f5c\u8005\u4ee5\u53ca\u76f8\u5173\u9886\u57df\u5f81\u96c68-10\u4f4d\u62a5\u544a\u4eba\uff0c\u8bb2\u8005\u4fe1\u606f\u5c06\u540c\u6b65\u66f4\u65b0\u81f3\u8bba\u575b\u5b98\u65b9\u7f51\u7ad9\uff0c\u5f81\u96c6\u622a\u6b62\u65e5\u671f\u4e3a2026\u5e748\u67081\u65e5\u3002<\/p>\n

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\u76f8\u5173\u83b7\u5956\u4fe1\u606f\u53ca\u7f16\u59d4\u4f1a\u5177\u4f53\u5b89\u6392\u5df2\u901a\u8fc7\u90ae\u4ef6\u53d1\u9001\u81f3\u5404\u4f4d\u5b66\u8005\uff0c\u656c\u8bf7\u60a8\u7559\u610f\u67e5\u6536\uff0c\u5e76\u53ca\u65f6\u53cd\u9988\u53c2\u4f1a\u610f\u5411\u3002\u5982\u6709\u610f\u53c2\u4e0e\u672c\u6b21\u8bba\u575b\u6216\u6709\u4efb\u4f55\u7591\u95ee\uff0c\u8bf7\u8054\u7cfb\u6234\u82b3\u8001\u5e08\uff08\u7535\u8bdd\/\u5fae\u4fe1\uff1a13912964288\uff09\u3002\u8bf7\u6301\u7eed\u5173\u6ce8\u4f1a\u8bae\u5b98\u7f51\uff08https:\/\/ccf.org.cn\/2026CCFDA\uff09\u53ca\u8bba\u575b\u5b98\u7f51\uff08https:\/\/ccf.org.cn\/2026CCFDA\/news_d_3123\uff09\uff0c\u83b7\u53d6\u6700\u65b0\u52a8\u6001\u3002<\/p>\n

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\u83b7\u5956\u540d\u5355\u5982\u4e0b\uff1a<\/strong><\/p>\n

Outstanding Editors\uff1a<\/strong><\/p>\n

    \n
  1. \n
      \n
    1. Dr.Xing Yang\uff0cAnhui Science and Technology University, China<\/li>\n
    2. Dr.Fan Yang, Jiangsu Normal University, China<\/li>\n
    3. Dr.Chengcheng Chen, College of Computer Science, Shenyang Aerospace University, China<\/li>\n
    4. Dr.Pei Wang, Southwest University, China<\/li>\n
    5. Dr.Wen-Hao Su, China Agricultural University, China<\/li>\n
    6. Dr.Alvaro Fuentes, Jeonbuk National University, Republic of Korea<\/li>\n
    7. Dr.Ning Yang, Jiangsu University,China<\/li>\n
    8. Dr.ELIO ROMANO, Centro di ricerca per l’Ingegneria e le Trasformazioni agroalimentari (CREA-IT), Italy<\/li>\n
    9. Dr.Kai Huang, Institute of Agricultural Facilities and Equipment, Jiangsu Academy of Agricultural Sciences, China<\/li>\n
    10. Dr.Jun Ni, Laboratory of Intelligent Control and Robotics, Shanghai University of Engineering Science, China<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

      Best Articles\uff1a<\/strong><\/p>\n

        \n
      1. \n
          \n
        1. Khan F, Zafar N, Tahir MN, Aqib M, Waheed H and Haroon Z (2023) A mobile-based system for maize plant leaf disease detection and classification using deep learning. Front. Plant Sci. 14:1079366. doi: 10.3389\/fpls.2023.1079366<\/li>\n
        2. Nahiduzzaman M, Chowdhury MEH, Salam A, Nahid E, Ahmed F, Al-Emadi N, Ayari MA, Khandakar A and Haider J (2023) Explainable deep learning model for automatic mulberry leaf disease classification. Front. Plant Sci. 14:1175515. doi: 10.3389\/fpls.2023.1175515<\/li>\n
        3. Batz P, Will T, Thiel S, Ziesche TM and Joachim C (2023) From identification to forecasting: the potential of image recognition and artificial intelligence for aphid pest monitoring. Front. Plant Sci. 14:1150748. doi: 10.3389\/fpls.2023.1150748<\/li>\n
        4. Thilakarathne NN, Bakar MSA, Abas PE and Yassin H (2023) Towards making the fields talks: A real-time cloud enabled IoT crop management platform for smart agriculture. Front. Plant Sci. 13:1030168. doi: 10.3389\/fpls.2022.1030168<\/li>\n
        5. Hu Y, Ma B, Wang H, Zhang Y, Li Y and Yu G (2023) Detecting different pesticide residues on Hami melon surface using hyperspectral imaging combined with 1D-CNN and information fusion. Front. Plant Sci. 14:1105601. doi: 10.3389\/fpls.2023.1105601<\/li>\n
        6. Wang J, Huang Y, Huang L, Dong Y, Huang W, Ma H, Zhang H, Zhang X, Chen X and Xu Y (2023) Migration risk of fall armyworm (Spodoptera frugiperda) from North Africa to Southern Europe. Front. Plant Sci. 14:1141470. doi: 10.3389\/fpls.2023.1141470<\/li>\n
        7. Sun X, Yang Z, Su P, Wei K, Wang Z, Yang C, Wang C, Qin M, Xiao L, Yang W, Zhang M, Song X and Feng M (2023) Non-destructive monitoring of maize LAI by fusing UAV spectral and textural features. Front. Plant Sci. 14:1158837. doi: 10.3389\/fpls.2023.1158837<\/li>\n
        8. Xu M, Kim H, Yang J, Fuentes A, Meng Y, Yoon S, Kim T and Park DS (2023) Embracing limited and imperfect training datasets: opportunities and challenges in plant disease recognition using deep learning. Front. Plant Sci. 14:1225409. doi: 10.3389\/fpls.2023.1225409.<\/li>\n
        9. Liu J, Zhu Y, Song L, Su X, Li J, Zheng J, Zhu X, Ren L, Wang W and Li X (2023) Optimizing window size and directional parameters of GLCM texture features for estimating rice AGB based on UAVs multispectral imagery. Front. Plant Sci. 14:1284235. doi: 10.3389\/fpls.2023.1284235<\/li>\n
        10. Dai M, Sun W, Wang L, Dorjoy MMH, Zhang S, Miao H, Han L, Zhang X and Wang M (2023) Pepper leaf disease recognition based on enhanced lightweight convolutional neural networks. Front. Plant Sci. 14:1230886. doi: 10.3389\/fpls.2023.1230886<\/li>\n
        11. Wang Y, Zhao R, Zhou X, Zhang X, Zhao G and Zhang F (2023) Prediction of potential distribution areas and priority protected areas of Agastache rugosa based on Maxent model and Marxan model. Front. Plant Sci. 14:1200796. doi: 10.3389\/fpls.2023.1200796<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

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