Michela Janni, Nicola Coppede, Manuele Bettelli, et al.

https://doi.org/10.34133/2019/6168209

新方法！预测芸薹属植物花期耐热抗旱性的无损表型测量方法 | Article

Nondestructive Phenomic Tools for the Prediction of Heat and Drought Tolerance at Anthesis in Brassica Species

Sheng Chen, Yiming Guo, Xavier Sirault, et al.

https://doi.org/10.34133/2019/3264872

来阵风，就知道！一种植物无损快速振动表型分析方法 | Aticle

Nondestructive and Fast Vibration Phenotyping of Plants

E. de Langre, O. Penalver, P. Hémon, et al.

https://doi.org/10.34133/2019/6379693

利用机器视觉量化葡萄白粉病严重程度的高通量表型系统 | PPhenomics Article

A High-Throughput Phenotyping System Using Machine Vision to Quantify Severity of Grapevine Powdery Mildew

Andrew Bierman, Tim LaPlumm, Lance Cadle-Davidson, et al.

ttps://doi.org/10.34133/2019/9209727

Plant Phenomics | 潜在空间表型：用于抗性研究的自动化图像表型

Latent Space Phenotyping: Automatic Image-Based Phenotyping for Treatment Studies

Jordan Ubbens, Mikolaj Cieslak, Przemyslaw Prusinkiewicz, Isobel Parkin,  Jana Ebersbach,  and Ian Stavness

https://doi.org/10.34133/2020/5801869

Plant Phenomics | 使用高通量表型技术评估拟南芥中热应激诱导造成的变化

The Use of High-Throughput Phenotyping for Assessment of Heat Stress-Induced Changes in Arabidopsis 

Gao G, Tester MA, Julkowska MM

https://doi.org/10.34133/2020/3723916

Plant Phenomics | 一种基于半监督学习的深度状态空间模型在植物生长建模中的应用研究

Semisupervised Deep State-Space Model for Plant Growth Modeling

Shibata S, Mizuno R, Mineno 

Htps://doi.org/10.34133/2020/4261965

Plant Phenomics | 使用基于图像的表型分析法评估和映射葡萄颜色

Evaluating and Mapping Grape Color Using Image-Based Phenotyping

Underhill AN, Hirsch CD, Clark MD

https://doi.org/10.34133/2020/8086309

Plant Phenomics | 对比无人车(UGV)和无人机(UAV)表型系统评估甜菜褐斑病的病害等级

Scoring Cercospora Leaf Spot on Sugar Beet: Comparison of UGV and UAV Phenotyping Systems

Jay S, Comar A, Benicio R, et al.

https://doi.org/10.34133/2020/9452123

Plant Phenomics | 浙江大学黄敬峰教授课题组提出了一种基于地面遥感延时图像的咖啡花识别方法

Coffee Flower Identification Using Binarization Algorithm Based on Convolutional Neural Network for Digital Images

Wei P, Jiang T, Peng H, et al.

https://doi.org/10.34133/2020/6323965

Plant Phenomics | 上海理工大学庄松林院士团队开发了一种基于西洋参标志物F11的无损快速分析方法

Terahertz Spectroscopy for Accurate Identification of Panax quinquefolium Basing on Nonconjugated 24(R)-Pseudoginsenoside F11

Kou T, Ye J, Wang J, et al.

https://doi.org/10.34133/2021/6793457

Plant Phenomics | 对大田和温室栽培苋菜的光合表型、感官和品种界限的分析

Photosynthetic Phenomics of Field- and Greenhouse-Grown Amaranths vs. Sensory and Species Delimits

Sooriyapathirana SDSS, Ranaweera LT, Jayarathne HSM, et al.

https://doi.org/10.34133/2021/2539380

Plant Phenomics | 对八倍体草莓形态的自动化表型和遗传分析

Automatic Fruit Morphology Phenome and Genetic Analysis: An Application in the Octoploid Strawberry

Zingaretti LM, Monfort A, Pérez-Enciso M

https://doi.org/10.34133/2021/9812910

《植物表型组学》（Plant Phenomics）是由南京农业大学和美国科学促进会（AAAS）合作创办的英文学术期刊，于2019年1月正式上线发行，是Science合作出版的第二本期刊。采用开放获取形式，刊载植物表型组学交叉学科热点领域具有突破性科研进展的原创性研究论文、综述、数据集和观点。具体范围涵盖高通量表型分析的最新技术，基于图像分析和机器学习的表型分析研究，提取表型信息的新算法，作物栽培、植物育种和农业实践中的表型组学新应用，与植物表型相结合的分子生物学、植物生理学、统计学、作物模型和其他组学研究，表型组学相关的植物生物学等。期刊已被DOAJ、Scopus、PMC、EI和SCIE等数据库收录。