福建农业学报2025，Vol.40Issue(11)：1185-1194,10.DOI:10.19303/j.issn.1008-0384.2025.11.011
机器学习融合植物表型的生菜氮素亏缺诊断研究
Detecting Nitrogen Deficiency on Lettuce by Phenotype Observation Integrated with Machine-learning Technology
摘要
Abstract
[Objective]An improved method over the conventional phenotype observation in detecting nitrogen deficiency(NO)on lettuce for facility agriculture was developed with the aid of machine-learning technology.[Method]The purple-leaf lettuce,'Red Crinkle',was hydroponically grown in a greenhouse with varied degrees of deficient N supply for the experiment.Multi-dimensional indicators on plant morphology,color,and texture of lettuce canopy were monitored.After standardization,collected data were screened by the principal component and correlation analyses to construct a mathematical model with the aid of various machine-learning methods.[Results]The PCA analysis on the measured indicators showed a significant clustering on the increasing NO in lettuce.Ten morphological,color,and texture indicators on lettuce canopy were selected by a correlation analysis for data entry of the machine-learning with redundancy eliminated.Different machine-learning methods varied in performance in differentiating the normal from NO plants,during the entire growth cycle or at specific stage.The random forest model outperformed on comprehensive diagnosis and detecting NO at early growth stage of lettuce.[Conclusion]A method of detecting NO in hydroponically grown Red Crinkle Lettuce by integrating the observation of phenotypic characteristics of lettuce canopy with a machine-learning method was developed.A mathematical model capable of reliably differentiating NO plants from normal ones was established for an improved facility agriculture operation of the vegetable.关键词
紫叶生菜/氮素亏缺/机器学习/表型特征/营养诊断Key words
Purple-leaf lettuce/machine-learning technology/nitrogen deficiency/phenotypic characteristics/nutritional diagnosis分类
农业科技引用本文复制引用
陈佩强,林黄昉,赵博,申宝营,潘鹤立,李添佑,张梁,林碧英..机器学习融合植物表型的生菜氮素亏缺诊断研究[J].福建农业学报,2025,40(11):1185-1194,10.基金项目
福建省教育厅中青年教师教育科研项目(JAT210076) （JAT210076）
福建农林大学乡村振兴服务团队项目(11899170126) （11899170126）
