基于集成机器学习的大理红花大金元种植适宜性区划

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中图分类号：S572；S126 文献标识码：A文章编号：1007-5119（2025）02-0113-08

¹，1*，²，³，4，¹，¹，1（1.河南农业大学资源与环境学院，郑州450046；2.云南省烟草公司大理州公司，云南大理67100；3.浙江万里学院信息与智能学院，浙江宁波315000；4.河南农业大学烟草学院，郑州450046)

Planting Suitability Zones of Honghuadajinyuan in Dali Prefecture Based on Integrated Machine Learning

WENG Qianwen1, CHEN Weiqiang1*,WANG Dexun², CHEN Yilin³, SHI Hongzhi4, MA Yuehong1, YU Ying1,YUAN Yuke1 (1.College ofResouresandEnviroment,Henan Agrcultural University,Zhengzhou45o46,China; 2.YuanTobaccoCompany Dali PrefectureCompany,Dali7o,Yunnan,Cina;3.ColegeofInformationand IntelligenceEnginering,Zhejng Wanli University,Ningbo350oo,Zhejang,China;4.TobacoColegeofHenanAgriculturalUniversityZhengzhou4546,China)

Abstract:Theflue-cured tobaccovariety“Honghuadajinyuan”exhibitspoorecologicaladaptability.Toestablishaninteligent Zoning methodforitscultivationsuitabilityinDali tobacogrowingarea,sevenecologicalenvironmentalovaratesereselected, includingaltitde,precipiationuringteaturitypriod,eantemperatueduringteaturitypriod,drotealit, soil pH,availablepotassumcontent,andwater-solublechlorieontent.Using752surveydatastsastraiingsamplesandthe ensembleofmachine learming algorithms，weinvestigatedthecultivationsuitabilityzoningof“Honghuadajinyuan”inDali Prefecture.Resultsdemonstratedasthefolows.(1）Thesuitabilityof“Honghuadajinyuan”showsmultidimensionalnonlinear relationshipwithenvironmentalcovariates,validatingtheuseofnonlinearmachneleamingmodels.2)Theoptimalmodelswere CHAIDdecisiontresitegratedwithaggingadbostingalgorits.Inthesuitabilitycassodel,thehydrotheralcoient, soilavailablepotas,ndmatuityperdprcipiatiwereteostiialinicatos;Iteabilityvelodelatity period precipitation,meantemperatureuringthematuritypriodandaltitudewereproritzed.(3)Among1458evalatioits, 471wereclasifiedas“mostsuitable”,456as“moderatelysuitable”and531as“unsuitable”.Suitablecultivationareas were concentratedinJianchanYunlong,Eryan,Dalirefecture,Weishan,Miduandanjiancountiesaswellasteastend western partsofBinchuanandthesouthwesternregionofYongping. (4)Validationusingsensory evaluationdata from48tobacco leaf samples confirmed the alignment of zoning results with actual quality.These findings provide a scientific basis for optimizing “Honghuadajinyuan” cultivation Zoning in Dali Prefecture.

Keywords: machine learning; Honghuadajinyuan; planting suitability assessment; Dali prefecture

红花大金元品种烟叶清香型风格突出，香气质好，香气量足，深受卷烟企业的青睐[1]。（剩余17257字）