基于大数据的桔梗类植物种子萌发特征分析  

An Analysis of Germination Characteristics of Platycodon Grandiflorus Seeds Based on Big Data

作　　者：丁群英[1] 梁佳雨 陈坤 杨雪 张博凯 DING Qunying;LIANG Jiayu;CHEN Kun

机构地区：[1]西安文理学院生物与环境工程学院,西安710065

出　　处：《智慧农业导刊》2025年第6期27-30,共4页JOURNAL OF SMART AGRICULTURE

基　　金：陕西省大学生创新创业训练计划项目(20236526)。

摘　　要：运用大数据分析技术对5种主要桔梗类植物种子的萌发特征进行系统研究。通过建立多维数据采集系统,采集温度、湿度、光照等18个环境因子数据,结合种子萌发率、萌发势等表型数据,构建桔梗类植物种子萌发预测模型。数据挖掘结果显示,光照强度与温度的交互作用对萌发率影响最显著(P<0.01)。基于机器学习算法优化种子萌发条件,使平均萌发率提升31.2%,为桔梗类植物种质资源保护提供数据支撑。Big data analysis technology was used to systematically study the germination characteristics of five main platycodon grandiflorum seeds.By establishing a multi-dimensional data collection system,data on 18 environmental factors such as temperature,humidity,and light were collected,and combined with phenotypic data such as seed germination rate and germination potential,a prediction model for seed germination of platycodon grandiflorum plants was constructed.Data mining results showed that the interaction between light intensity and temperature had the most significant impact on germination rate(P<0.01).Seed germination conditions were optimized based on machine learning algorithms,increasing the average germination rate by 31.2%,providing data support for the protection of platycodon grandiflorum germplasm resources.

关 键 词：桔梗类植物 种子萌发 大数据分析 机器学习 环境因子 

分 类 号：Q944.59[生物学—植物学]