Plant Phenomics | 园艺植物表型组学研究应用文章合集
Plant Phenomics | 基于光流法分析水分胁迫条件下番茄叶片萎蔫与茎直径变化的关系
Optical Flow-Based Analysis of the Relationships between Leaf Wilting and Stem Diameter Variations in Tomato Plants
Kazumasa Wakamori and Hiroshi Mineno
https://doi.org/10.34133/2019/9136298
Plant Phenomics | 利用体内表型分析进行番茄干旱胁迫的早期检测
In Vivo Phenotyping for the Early Detection of Drought Stress in Tomato
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.
https://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
About Plant Phenomics
《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。
说明：本文由《植物表型组学》编辑部负责组稿。
中文内容仅供参考，一切内容以英文原版为准。
编辑：张威（实习）
审核：卞越、孔敏
