真桑钝绥螨对柑桔全爪螨不同螨态的选择性

真桑钝绥螨对柑桔全爪螨不同螨态的选择性蒲天胜,曾涛,韦德卫（广西农科院植物保护研究所,南宁５３０００７）ＳｅｌｅｃｔｉｖｅＰｒｅｄａｃｉｔｙｏｆＡｍｂｌｙｓｅｉｕｓｍａｋｕｗａｔｏＶａｒｉｏｕｓＭｉｔｅＦｏｒｍｓｏｆＰａｎａｎｙｃｈｕｓｃｉｔｒｉ￥ＰｕＴｉａｎｓｈｅｎｇ;ＺｅｎｇＴａｏ;ＷｅｉＤｅｗｅｉ（ＩｎｓｔｉｔｕｔｅｏｆＰｌａｎｔＰｒｏｌｅｃｔｉｏｎ,ＧｕａｎｇｘｉＡｃａｄｅｍｙｏｆＡｇｒｉｃｕｌｔｕｒａｌＳｃｉｅｎｃｅｓ）．ＣｈｉｎｅｓｅＪｏｕｒ－ｎａｌｏｆＥｃｏｌｏｇｙ,１９９３,１２（１）：３３－３４。ＴｈｅｓｅｌｅｃｔｉｖｅｐｒｅｄａｃｉｔｙｏｆｆｅｍａｌｅａｄｕｌｔｏｆＡ．ｍａｋｕｗａｔｏｃｉｔｒｕｓｍｉｔｅｓｉｓｓｉｍｕｌａｔｅｄｉｎｃｏｍｐａｒｉｓｏｎｗｉｔｈｓｐｅｃｉｅｓｏｆＡｎｉｃｈｏｌｓｉ．Ａ．ｍａｋｕｗａｓｈｏｗｓａｎｅｇａｔｉｖｅｐｒｅｆｅｒｅｎｃｅｔｏｔｈｅａｄｕｌｔｏｆＰ．ｃｉｔｒｉ,ｂｕｔＡ．ｎｉｃｈｏｌｓｉｓｈｏｗｓｎｏｓｅｌｅｃｔｉｖｉｔｙａｎｄｓｗｉｔｃｈｉｎｇ．Ｉｎｍｕｌｔｉ－ｆｏｒｍｃｏｅｘｉｓｔｅｎｔｓｙｓｔｅｍｏｆｍｉｔｅｓ,ｔｈｅｆｕｎｃｔｉｏｎａｌｒｅｓ     

沟稃草属研究札记

本文对沟稃草属Ａｎｉｓｅｂｙｔｒｏｎ Ｍｅｒｒｉｌｌ的系统分类进行了初步的整理与修订。认为Ａｕｌａｃｏｌｅｐｉｓ Ｈａｃｋｅｌ（１９０７）（Ｎｅｏａｕｌａｃｏｌｅｐｉｓ Ｓ．Ｒａｕｓｃｈｅｒｔ（１９８２）ｐｒｏ ｎｏｍ．ｎｏｖ．Ａｕｌａｃｄｅｐｉｓ）ｎｏｎ Ｃ．ｖ．Ｅｉｔｉｎｇｓｈａｕｓｅｎ（１８９３）、Ａｎｉｓｅｌｙｔｒｏｎ Ｍｅｒｒｉｌｌ（１９１０）与Ａｎｉｓａｃｈｎｅ Ｋｅｎｇ（１９５８）是     

新疆农业绿洲生态建设的探讨

新疆农业绿洲生态建设的探讨夏爱林（新疆农业科学院土壤肥料研究所,乌鲁木齐８３００００）ＡｎＡｐｐｒｏａｃｈｔｏｔｈｅＥｃｏｌｏｇｉｃａｌＣｏｎｓｔｒｕｃｔｉｏｎｏｆＡｇｒｉｃｕｌｔｕｒａｌＯａｓｃｓｉｎＸｉｎｊｉａｎｇ￥ＸｉａＡｉｌｉｎ（ＩｎｓｔｉｔｕｔｅｏｆＳｏｉｌａｎｄＦｅｒｔｉｌｉｚｅｒｓ,ＸｉｎｊｉａｎｇＡｃａｄｅｍｙｏｆＡｇｒｉｃｕｌｔｕｒａｌＳｃｉｅｎｃｅｓ,Ｕｒｏｍｑｉ８３００００）．ＣｈｉｎｅｓｅＪｏｕｒｎａｌｏｆＥｃｏｌｏ－ｇｙ,１９９３,１２（１）：６７－７０。Ｃｏｍｐａｒｅｄｗｉｔｈｏｔｈｅｒａｒｉｄａｒｅａｓｏｆｔｈｅｗｏｒｌｄ,ｔｈｅａｇｒｉｃｕｌｔｕｒａｌｏａｓｅｓｉｎＸｉｎｊｉａｎｇｐｏｓｓｅｓｓｔｈｅｆｏｌｌｏｗｉｎｇｃｈａｒａｃｔｅｒｓ：１．ｔｈｅｙａｒｅｄｅｓｅｒｔａｎｄｉｒｒｉｇａｔｅｄ,ａｎｄｗａｔｅｒｉｓｔｈｅｍａｉｎｆａｃｔｏｒｆｏｒｔｈｅｉｒｓｕｂｓｉｓｔｅｎｃｅａｎｄｄｅｖｅｌ－ｏｐｒｎｅｎｔ,２．ｔｈｅｒｅａｒｅａｂｕｎｄａｎｔｌｉｇｈｔ,ｈｅａｔａｎｄｗａｔｅｒｒｅｓｏｕｒｃｅｓａｎｄｇｒｅａｔｐｏｔｅｎｔｉａｌｆｏｒｉｎｃｒｅａｓｉｎｇｔｈｅｉｒｐｒｏｄ     

生态农业与乡村经济持续发展

生态农业与乡村经济持续发展张壬午,计文瑛,孙鸿良（天津农业部环境保护研究所,３００１９１）（中国农科院,北京１０００８１）ＥｃｏｌｏｇｉｃａｌＡｇｒｉｃｕｌｔｕｒｅａｎｄＳｕｓｔａｉｎａｂｌｅＤｅｖｅｌｏｐｍｅｎｔｏｆＲｕｒａｌＥｃｏｎｏｍｙ￥．ＺｈａｎｇＲｅｎｗｕ;ＪｉＷｅｎｙｉｎｇ（Ａｇｒｏ－ｅｎｖｉｒｏｎｍｅｎｔＰｒｏｔｅｃｌｉｏｎＩｎｓｔｉｔｕｔｅ,Ｔｉａｎｊｉｎ３００１９１）,ＳｕｎＨｏｎｇｌｉａｎｇ（ＣｈｉｎｅｓｅＡｃａｄｅｍｙｏｆＡｇｒｉｃｕｌｔｕｒａｌＳｃｉｅｎｃｃｓ,Ｂｅｉｊｉｎｇ１０００８１）．ＣｈｉｎｅｓｅＪｏｕｒｎａｌｏｆＥｃｏｌｏｇｙ,１９９３,１２（２）：１９—２０．ＴｈｉｓｐａｐｅｒｂｒｉｅｆｌｙｐｒｅｓｅｎｔｓｔｈｅｃｕｒｒｅｎｔｄｅｖｅｌｏｐｍｅｎｔｏｆｅｃｏｌｏｇｉｃａｌａｇｒｉｃｕｌｔｕｒｅｉｎＣｈｉｎａａｎｄｃｏｍｐａｒｅｓｗｉｔｈｔｈｅ＇＇ｓｕｓｔａｉｎａｂｌｅａｇｒｉｃｕｌｔｕｒｅａｎｄｒｕｒａｌｄｅｖｅｌｏｐｍｅｎｔ＇＇（ＳＡＲＤ）ｐｕｔｆｏｒｗａｒｄｂｙＦＡＯ,Ｃｈｉｎａ’ｓｓｕｓｔａｉｎａｂｌｅａ－ｇｒｉｃｕｌｔｕｒｅｉｓｎｏｔｏｎｌｙａｎｉｎｇｅｎｉｏｕｓ     

农业系统生产力（ASP）的量化及其现状分析

农业系统生产力（ＡＳＰ）的量化及其现状分析卢进登,韩纯儒（北京农业大学农学系,１０００９４）ＱｕａｎｔｉｆｉｃａｔｉｏｎｏｆＡｇｒｏｓｙｓｔｅｍＰｒｏｄｕｃｔｉｖｉｔｙ（ＡＳＰ）ａｎｄＡｎａｌｙｓｉｓｏｎｉｔｓＣｕｒｒｅｎｔＳｉｔｕａｔｉｏｎｉｎＣｂｉｎａ￥．ＬｕＪｉｎ－ｄｅｎｇ;ＨａｎＣｈｕｎｒｕ（ＢｅｉｊｉｎｇＡｇｒｉｃｕｌｔｕｒａｌＵｎｉｖｅｒｓｉｔｙｆＢｅｉｊｉｎｇ１０００９４）．ＣｈｉｎｅｓｅＪｏｕｒｎａｌｏｆＥｃｏｌｏｇｙ,１９９３,１２（２）：２１－２２．ＢａｓｅｄｏｎａｂｒｉｅｆａｎａｌｙｓｉｓｏｎｔｈｅｆｏｒｍａｔｉｏｎｐｒｏｃｅｓｓｏｆＡＳＰ,ｉｔｓｃｏｎｃｅｐｔｉｓｄｅｓｃｒｉｂｅｄａｎｄａｎｉｎｔｅｇｒａｔｅｄｉｎｄｉ－ｃａｔｏｒｆｏｒｉｔｓｑｕａｎｔｉｆｉｃａｔｉｏｎ—ＡＳＰ２ｉｓｐｕｔｆｏｒｗａｒｄｓ．Ｆｒｏｍｔｈｏｓｅ,ｔｈｅＡＳＰｌｅｖｅｌｓｉｎｖａｒｉｏｕｓｒｅｇｉｏｎｓｏｆＣｈｉｎａａｒｅａｎａｌｙｚｅｄａｎｄ８ｌｅｖｅｌｓａｒｅｄｉｖｉｄｅｄｂｙｕｓｉｎｇ．Ｈｉｅｒａｒｃｈｉｃｃｌｕｓｔｅｒｉｎｇｍｅｔｈｏｄ．Ｉｔ’ｓ：ｃｌａｒｉｆｉｅｄｔｈａｔＡＳ－ＰＩｉｓａｍｏｒｅ     

最大概率原理在农田生态系统中的应用

最大概率原理在农田生态系统中的应用姚建民（山西省农科院农业资源综合考察研究所,太原０３０００６）马蓉丽（山西省农科院蔬菜研究所,太原０３０００６）ＡｐｐｌｉｃａｔｉｏｎｏｆＭａｘｉｍｕｍＰｒｏｂａｂｉｌｉｔｙＰｒｉｎｃｉｐｌｅｉｎＦａｒｍｌａｎｄＥｃｏｓｙｓｔｅｍ￥．ＹａｏＪｉａｎｍｉｎ（ＩｎｓｌｉｌｕｔｅｆｏｒＣｏｍ－ｐｒｅｈｅｎｓｉｖｅＳｕｒｖｅｙｏｆＡｇｒｉｃｕｌｔｕｒａｌＲｅｓｏｕｒｃｅｓ,ＳｈａｎｘｉＡｃａｄｅｍｙｏｆＡｇｒｉｃｕｌｔｕｒａｌＳｃｉｅｎｃｅｓ,Ｔａｉｙｕａｎ０３０００６）,ＭａＲｏｎｇｌｉ（ＩｎｓｌｉｔｕｔｅｏｆＶｅｇｅｔａｂｌｅＲｅｓｅａｒｃｇｈ,ＳｈａｎｘｉＡｃａｄｅｍｙｏｆａｇｒｉｃｕｌｔｕｒａｌＳｃｉｅｎｃｅｓ,Ｔａｉｙｕａｎ（０３０００６）．Ｃｈｉｎｅｓｅ,ＪｐｕｒｎａｌｏｆＥｃｏｌｏｇｙ,１９９３,１２（４）：５８－６０．Ｉｎｏｒｄｅｒｔｏｓｔｒｅｎｇｔｈｅｎｔｈｅｐｒａｃｔｉｃａｂｉｌｉｔｙｏｆｍａｘｉｍｕｍｐｒｏｂａｂｉｌｉｔｙｐｒｉｎｃｉｐｌｅ,ｔｈｉｓｐａｐｅｒｇｉｖｅｓｏｕｔｓｏｍｅｅｓ－ｓｅｎｔｉａｌｃｏｎｄｉｔｉｏｎｓｎｅｅｄｅｄｆｏｒａｐｐｌｙｉｎｇｔｈ     

生物固氮─—生态农业的一个重要启动因素

生物固氮─—生态农业的一个重要启动因素陈士平（辽宁省农业科学院土壤肥料研究所,沈阳１１０１６１）ＢｉｏｌｏｇｉｃａｌＮｉｔｒｏｇｅｎＦｉｘａｔｉｏｎ—ＡｎＩｍｐｏｒｔａｎｔＲｕｎｎｉｎｇＦａｃｔｏｒｏｆＥｃｏｌｏｇｉｃａｌＡｇｒｉｃｕｌｔｕｒｅ￥．ＣｈｅｎＳｈｉｐｉｎｇ（ＳｏｉｌａｎｄＦｅｒｔｉｌｉｚｅｒＩｎｓｔｉｌｕｔｅ,ＬｉａｏｎｉｎｇＡｃａｄｅｍｙｏｆＡｇｒｉｃｕｌｔｕｒａｌＳｃｉｅｎｃｅｓ,Ｓｈｅｎｙａｎｇ１１０１６１）．ＣｈｉｎｅｓｅＪｏｕｒｎａｌｏｆＥｃｏｌｏｇｙ,１９９３,１２（２）：３１—３３．ＬｅｇｕｍｉｎｏｕｓｇｒｅｅｎｍａｎｕｒｅｃｒｏｐｓｓｕｃｈａｓｓｗｅｅｔｃｌｏｖｅｒａｎｄＡｓｔｒａｇａｌｕｓｈｕａｎｇｈｅｅｎｓｉｓ,ｃａｎｐｒｏｖｉｄｅｄｅｆｉｎｉｔｅａｍｏｕｎｔｏｆｂｉｏｌｏｇｉｃａｌｌｙｆｉｘｅｄ－ＮｔｏｍａｋｅＮ－ｂｕｄｇｅｔｂａｌａｎｃｅ,ｐｒｏｍｏｔｅｓｏｉｌｐｈｙｓｉｃａｌａｎｄｃｈｅｍｉｃａｌｐｒｏｐｅｒ－ｔｉｅｓ,ｒｅｄｕｃｅｓｏｉｌａｎｄｗａｔｅｒｅｒｏｓｉｏｎ,ａｎｄｔｈｕｓ,ｉｎｃｒｅａｓｅｐｅｒｕｎｉｔａｒｅａｙｉｅｌｄａｎｄｔｏｔａｌｏｕｔｐｕｔｗｈｅ     

辽宁省灾害区划初探

辽宁省灾害区划初探尹功成,梁文举（辽宁省农业区划研究所,沈阳１１００３１）（中国科学院沈阳应用生态研究所,１１００１５）ＡｎＡｐｐｒｏａｃｈｔｏＣａｌａｍｉｔｙＤｉｖｉｓｉｏｎｉｎｇｏｆＬｉａｏｎｉｎｇＰｒｏｖｉｎｃｅ￥．ＹｉｎＧｏｎｇｃｈｅｎｇ（ＬｉａｏｎｉｎｇＩｎｓｌｉｔｕｔｅｏｆＡｇｒｉ－ｃｕｌｔｕｒａｌＤｉｖｉｓｉｏｎｉｎｇ,Ｓｈｅｎｙａｎｇ１１００３１）,ＬｉａｎｇＷｅｎｊｕ（ＩｎｓｌｉｌｕｔｅｏｆＡｐｐｌｉｅｄＥｃｏｌｏｇｙ,ＡｃａｄｅｍｉａＳｉｎｉｃａ,Ｓｈｅｎｙａｎｇ１１００１５）．ＣｈｉｎｅｓｅＪｏｕｒｎａｌｏｆＥｃｏｌｏｇｙ,１９９３,１２（４）：６１－６５．ＮａｔｕｒａｌｃａｌａｍｉｔｉｅｓｏｃｃｕｒｗｈｅｎｖａｒｉＯｕｓｎａｔｕｒａｌｐｈｅｎｏｍｎａｅｎｄａｎｇｅｒｌｉｆｅ,ｍｉｎｄｓａｎｄｐｒｏｐｅｒｔｉｅｓ,ｂｕｔｓｏｍｅｐｏｔｅｎｔｉａｌｅｎｖｉｒｏｎｍｅｎｔａｌｄｉｓａｓｔｅｒｓｓｕｃｈａｓｒｎａｎ－ｍａｄｅａｎｄａｎｔｈｒｏｐｏｇｅｎｏｕｓｎａｔｕｒａｌｄｉｓａｓｔｅｒｓｄｅｖｅｌｏｐｓｌｏｗ－ｌｙａｎｄｐｒｏｆｏｕｎｄｌｙ,ｗｈｌｃｈａｒｅｕｎｏｂｖｉｏｕｓａｎｄｎｏｔｒ     

持续农业是生态农业的继续与发展

持续农业是生态农业的继续与发展袁从,赵强基（江苏省农业科学院,南京２１００１４）ＳｕｓｔａｉｎａｂｌｅＡｇｒｉｃｕｌｔｕｒｅ—ＴｈｅＣｏｎｔｉｎｕａｔｉｏｎａｎｄＤｅｖｅｌｏｐｍｅｎｔｏｆＥｃｏｌｏｇｉｃａｌＡｇｒｉｃｕｌｔｕｒｅ．￥ＹｕａｎＣｏｎｇｙｉ;ＺｈａｏＱｉａｎｇｊｉ（ＪｉａｎｇｓｕＡｃａｄｅｎｚｙｏｆＡｇｒｉｃｕｌｔｕｒａｌＳｃｉｅｎｃｅｓ,Ｎａｎｊｉｎｇ２１００１４）．ＣｈｉｎｅｓｅＪｏｕｍａｌｏｆＥｃｏｌｏｇｙ,１９９３,１２（２）：１３－１５．Ｉｎｌｉｇｈｔｏｆｔｈｅｃｏｎｄｉｔｉｏｎｏｆｏｕｒｃｏｕｎｔｒｙ,ｔｈｉｓｐａｐｅｒｉｎｔｒｏｄｕｃｅｓｔｈｅｃｏｎｃｅｐｔｓａｎｄｃｏｎｔｅｎｔｓｏｆｓｕｓｔａｉｎａｂｌｅａ－ｇｒｉｃｕｌｔｕｒｅａｎｄｉｔｓｑｕａｎｔｉｔａｔｉｖｅｅｖａｌｕａｔｉｏｎｉｎｄｉｃｅｓ──ｓｕｓｔａｉｎａｂｉｌｉｔｙ,ｓｔａｂｉｌｉｔｙ,ｅｑｕａｌｉｔｙａｎｄｈａｒｍｏｎｉｔｙ（ｄｉ－ｖｅｒｓｉｔｙ）．Ｓｉｍｐｌｉｆｉｅｄｓｙｓｔｅｍｉｎｐｕｔ—ｏｕｔｐｕｔｅｑｕｉｌｉｂｒｉｕｍｉｓｕｓｅｄｔｏｅｓｔｉｍａｔｅｔｈｅｄｙｎａｍｉｃｓｏｆｓｏｉｌｆｅｒｔｉｌｉｔｙ．Ｐ     

普通小麦基因组最可能的4个供体的ITS1和ITS2序列及其亲缘关系

对普通小麦（ＴｒｉｔｉｃｕｍａｅｓｔｉｖｕｍＬ．）基因组（ＡＡＢＢＤＤ）最可能的供体－Ｔ．ｕｒａｔｒｔｕＴｈｕｍ．（ＡＡ）、Ｔ．ｍｏｎｏｃｃｕｍｖａｒ．ｂｏｅｏｔｉｃｕｍ（Ｂｏｉｓｓ．）ＭＫ（ＡＡ）、ＡｅｇｉｌｏｐｓｓｐｅｌｔｏｉｄｅｓＴａｕｓｃｈ．和Ａｅ．ｔａｕｓｃｈｉｉ（Ｃｏｓｓ．（ＤＤ）的核糖体ＲＮＡ基因ＩＴＳ区进行了ＰＣＲ扩增和克隆,并测定了ＩＴＳ１和ＩＴＳ２的ＤＮＡ序列,讨论和纠正了前人     

优势种植被分类系统的逻辑分析与示例方案化

逻辑学原理是各种分类系统科学性及规范性的必要检验工具。本文采用逻辑学原理检验基于优势种的《中国植被》的植被分类系统, 结果发现目前常用的植被分类系统存在较多逻辑错误, 需要予以纠正。于是, 在强调植物生活型分类系统和植被分类系统一致性的基础上, 依据逻辑学原理给出建立植被分类系统的步骤和方法, 提出规范的植物生活型分类系统和植被分类系统示例方案。鉴于多建群种植被的客观存在及其存在形式多样, 在分类系统中给出相应的位置——多建群种植被纲。同时, 针对国内植被分类学界从未形成统一的植被命名规则, 且又有多种命名方式并存的现状, 提出了函数命名法。     

不同稀有种处理对双向指示种分析分类结果影响的比较

为探讨不同稀有种处理对TWINSPAN分类结果的影响,以北京小龙门林场华北落叶松林调查数据为例,采用2×2列联表比较了剔除频度＜5%、盖度＜5%的稀有种前后TWINSPAN分类结果的异同,同时结合引入的DBI重点对比了最佳分类等级的吻合性。结果表明：(1)在相同的分类终止原则下,剔除稀有种前后的最大分类结果分别分为12、11个群落类型;(2)基于结合系数r,剔除稀有种前后TWINSPAN在低分类等级的结果差异较大,随着分类等级的增加,二者的吻合度增大,表明稀有种对低分类等级的结果影响较为明显;(3)引入的DBI适用于确定TWINSPAN分类的最佳分类等级,尽管剔除稀有种前后的最佳分类等级不同,但分类结果的吻合度较高。因此,在TWINSPAN分类应用中,建议引入DBI指数辅助确定最佳分类等级,同时取低分类等级结果时必须做删除稀有种处理。     

关于植物群丛划分的探讨

在传统的植物群落分类系统中,群丛是植物群落分类的基本单位.从群丛分类的必要性出发,综述了传统植物群落分类系统中对群丛的定义及其划分方法,即在群丛的划分中主要依据群落中不同层片的优势种或特征种;但是在利用传统植物群落分类方法划分群丛时也存在一些不确定性因素,主要表现在确定群丛的特征种(组)时需要人为确定;同时,论述了当前植物群落数量分类的研究现状,分析了利用双向指示种分析法(TWINSPAN)、主成分分析(PCA)等数量分类方法划分群丛时存在的一些问题,主要表现在数量分类结果与传统分类单位的对应关系不能达到协调一致,无法判断是否划分到了群丛的水平.最后提出了群丛划分方法的展望:数量方法是基础,特征种(组)是及其数量特征是关键.     

Are habitat types compatible with floristically‐derived associations?

Abstract. The habitat type system developed by R. Daubenmire has been widely adopted throughout the western United States. Habitat types result from a site classification derived from the classification of late seral plant communities using selected indicator species. It has been suggested that the classification of late successional vegetation used to derive habitat types does not substantially differ from phytosociological classification in the sense of Braun‐Blanquet approach, and that habitat types can be adopted in their present form into floristically‐based vegetation classifications. Despite the many commonalities between the two systems, however, the classification methods, and specifically the use of indicator species in the habitat type system, yield a significantly different classification than the phytosociological approach. This is demonstrated in the comparison of a habitat type classification with the results of a recent phytosociological classification of forest vegetation in the northern Salish Mountains of Montana.     

基于地形限制特征的泾河流域遥感地表覆被分类

由于在分类方法和空间分辨率等方面存在局限性,基于粗分辨率遥感数据的传统非监督分类结果在不同地物过渡带内往往误差较大。该文提出了基于地形限制特征的分类方法,在非监督分类的基础上,将非监督分类结果按照像元进行细分,并运用地形限制条件对细分后的像元进行二次判别分类。结果表明,分类精度明显提高,其中,农田和居民点分类精度的提高最为明显。这一方法使得完全同质的单元可以进行属性的变更,改善了像元空间分辨率差造成的误差;而地形限制特征的引入减少了传统非监督分类的不确定性,使模糊区域的分类有了较为明确的区分特征,提高了分类的精度。     

基于多组学数据的早期宫颈鳞状细胞癌分类

从分子层面对泛癌进行研究已经得到了很大的进展,但是对宫颈鳞状细胞癌的分子分类研究仍然需要更多的探索.为了找到宫颈鳞状细胞癌潜在的子类,本文提出了一个基于多维组学数据的癌症亚型分类分析流程.通过统计学方法对癌症基因组图谱(The Cancer Genome Atlas,TCGA)宫颈鳞状细胞癌的mRNA表达数据、小分子核糖核酸(microRNA,miRNA)表达数据、DNA甲基化数据以及拷贝数变异数据4个维度包含的分子进行筛选,然后对筛选后的分类特征进行整合聚类,进一步筛选能够区分不同子类的关键分类特征,并使用这些关键分类特征建立宫颈鳞状细胞癌分类模型.本研究为宫颈鳞状细胞癌分子层面子类的识别提供了分析流程,得到了两个临床生存水平具有显著性差异的宫颈鳞状细胞癌子类,并确定了8个宫颈鳞状细胞癌的关键分类特征.本研究中识别的宫颈鳞状细胞癌子类和关键分类特征为宫颈鳞状细胞癌早期分类及分类标志物的鉴定提供了重要参考.     

Automated identification of diseases related to lymph system from lymphography data using artificial immune recognition system with fuzzy resource allocation mechanism (fuzzy-AIRS)

Artificial immune recognition system (AIRS) classification algorithm, which has an important place among classification algorithms in the field of artificial immune systems, has showed an effective and intriguing performance on the problems it was applied. AIRS was previously applied to some medical classification problems including breast cancer, Cleveland heart disease, diabetes and it obtained very satisfactory results. So, AIRS proved to be an efficient artificial intelligence technique in medical field. In this study, the resource allocation mechanism of AIRS was changed with a new one determined by fuzzy-logic. This system, named as fuzzy-AIRS was used as a classifier in the diagnosis of lymph diseases, which is of great importance in medicine. The classifications of lymph diseases dataset taken from University of California at Irvine (UCI) Machine Learning Repository were done using 10-fold cross-validation method. Reached classification accuracies were evaluated by comparing them with reported classifiers in UCI web site in addition to other systems that are applied to the related problems. Also, the obtained classification performances were compared with AIRS with regard to the classification accuracy, number of resources and classification time. While only AIRS algorithm obtained 83.138% classification accuracy, fuzzy-AIRS classified the lymph diseases dataset with 90.00% accuracy. For lymph diseases dataset, fuzzy-AIRS obtained the highest classification accuracy according to the UCI web site. Beside of this success, fuzzy-AIRS gained an important advantage over the AIRS by means of classification time. By reducing classification time as well as obtaining high classification accuracies in the applied datasets, fuzzy-AIRS classifier proved that it could be used as an effective classifier for medical problems.     

生长型分类方案不同导致森林生态系统植物功能性状的统计偏差

将植物划分为不同的生长型来统计植物功能性状特征,是当前植物性状研究中常用的方法;但生长型分类方案的不同很可能造成植物功能性状统计分析的偏差,对此偏差的评估却尚未见报道。根据植物志描述及野外调查实际情况,将生长型划分为3种不同的分类方案：分类1：根据植物志信息划分为传统意义的乔木和灌木;分类2：根据树高和胸径划分乔木、小乔木和灌木;分类3：仅根据树高划分乔木层与灌木层的乔木和灌木。以东部亚热带常绿阔叶林区域的浙江金华北山35种优势阔叶木本植物的枝叶性状为研究对象,比较不同生长型分类对植物枝叶性状统计数据的影响。结果表明：（1）与传统的分类1相比,分类2对乔木植物枝叶性状影响的显著程度要高于分类3,而对灌木植物枝叶性状的影响程度低于分类3;但不同生长型分类方案中乔木和灌木的枝叶性状总体差异不显著。而与分类2小乔木相比,分类1以及分类2内部的乔木和灌木生长型的性状与分类2小乔木差异非常明显;（2）将不同生长型植物再划分为不同生活型后,不同生长型分类方案对性状统计的影响增大。无论是常绿还是落叶生活型的小乔木,其与不同生活型乔木和灌木的性状差异仍然显著。可见,不同的生长型分类方案可造成植物功能性状统计的差异;把小乔木植物这一功能类群划分出来,能更好地反映森林生态系统性状特征的差异性。     

On the predictive power of numerical and Braun-Blanquet classification: an example from beechwoods

Abstract. A numerical classification method and the Braun-Blanquet method, based on external criteria, were compared with the aim of clarifying the differences in predictive power. The numerical analysis leads to a changed perspective on the floristic data and produces, as a whole, an ecologically more differentiated classification. The groups produced by numerical analysis are almost identical with the Braun-Blanquet classification with respect to marginal site conditions but they may differ in cases of intermediate site conditions. Nevertheless, a classification emerges which is on the whole, both floristically and as to site, very similar to the Braun-Blanquet classification. The discriminatory importance of the external variables is, to a large extent, the same in both methods, but discriminant analysis shows that the numerical classification is somewhat more predictive.     

Fine hyperspectral classification of rice varieties based on self-attention mechanism

The accurate identification of rice varieties using rapid and nondestructive hyperspectral technology is of practical significance for rice cultivation and agricultural production. This paper proposes a convolutional neural network classification model based on a self-attention mechanism (self-attention-1D-CNN) to improve accuracy in distinguishing between crop species in fields using canopy spectral information. After experimental materials were planted in the research area, portable equipment was used to collect the canopy hyperspectral data for rice during the booting stage. Five preprocessing methods and three extraction methods were used to process the data. A comparison of the classification accuracy of different classification models showed that the self-attention-1D-CNN proposed in this study achieved the best classification with an accuracy of 99.93%. The research demonstrated the feasibility of using hyperspectral technology for the fine classification of rice varieties, and the feasibility of using the CNN model as a potential classification method for near-ground crop monitoring and classification.