Plant Phenomics | 基于光流法分析水分脅迫條件下番茄葉片萎蔫與莖直徑變化的關系

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 | 利用體內表型分析進行番茄干旱脅迫的早期檢測

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！預測蕓薹屬植物花期耐熱抗旱性的無損表型測量方法 | 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

來陣風，就知道！一種植物無損快速振動表型分析方法 | Aticle

Nondestructive and Fast Vibration Phenotyping of Plants

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

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

利用機器視覺量化葡萄白粉病嚴重程度的高通量表型系統 | 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 | 潛在空間表型：用于抗性研究的自動化圖像表型

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 | 使用高通量表型技術評估擬南芥中熱應激誘導造成的變化

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 | 一種基于半監督學習的深度狀態空間模型在植物生長建模中的應用研究

Semisupervised Deep State-Space Model for Plant Growth Modeling

Shibata S, Mizuno R, Mineno 

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

Plant Phenomics | 使用基于圖像的表型分析法評估和映射葡萄顏色

Evaluating and Mapping Grape Color Using Image-Based Phenotyping

Underhill AN, Hirsch CD, Clark MD

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

Plant Phenomics | 對比無人車(UGV)和無人機(UAV)表型系統評估甜菜褐斑病的病害等級

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 | 浙江大學黃敬峰教授課題組提出了一種基于地面遙感延時圖像的咖啡花識別方法

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 | 上海理工大學莊松林院士團隊開發了一種基于西洋參標志物F11的無損快速分析方法

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 | 對大田和溫室栽培莧菜的光合表型、感官和品種界限的分析

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 | 對八倍體草莓形態的自動化表型和遺傳分析

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

《植物表型組學》（Plant Phenomics）是由南京農業大學和美國科學促進會（AAAS）合作創辦的英文學術期刊，于2019年1月正式上線發行，是Science合作出版的第二本期刊。采用開放獲取形式，刊載植物表型組學交叉學科熱點領域具有突破性科研進展的原創性研究論文、綜述、數據集和觀點。具體范圍涵蓋高通量表型分析的最新技術，基于圖像分析和機器學習的表型分析研究，提取表型信息的新算法，作物栽培、植物育種和農業實踐中的表型組學新應用，與植物表型相結合的分子生物學、植物生理學、統計學、作物模型和其他組學研究，表型組學相關的植物生物學等。期刊已被DOAJ、Scopus、PMC、EI和SCIE等數據庫收錄。

說明：本文由《植物表型組學》編輯部負責組稿。

中文內容僅供參考，一切內容以英文原版為準。

編輯：張威（實習）

審核：卞越、孔敏