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(guān)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(nèi)表型分析進(jìn)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(yù)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(fēng)，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(jī)器視覺量化葡萄白粉病嚴(yán)重程度的高通量表型系統(tǒng) | 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(shù)評估擬南芥中熱應(yīng)激誘導(dǎo)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(jiān)督學(xué)習(xí)的深度狀態(tài)空間模型在植物生長建模中的應(yīng)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(jī)(UAV)表型系統(tǒng)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(xué)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(xué)莊松林院士團(tuán)隊(duì)開發(fā)了一種基于西洋參標(biāo)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(tài)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(xué)》（Plant Phenomics）是由南京農(nóng)業(yè)大學(xué)和美國科學(xué)促進(jìn)會（AAAS）合作創(chuàng)辦的英文學(xué)術(shù)期刊，于2019年1月正式上線發(fā)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(xué)交叉學(xué)科熱點(diǎn)領(lǐng)域具有突破性科研進(jìn)展的原創(chuàng)性研究論文、綜述、數(shù)據(jù)集和觀點(diǎn)。具體范圍涵蓋高通量表型分析的最新技術(shù)，基于圖像分析和機(jī)器學(xué)習(xí)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(nóng)業(yè)實(shí)踐中的表型組學(xué)新應(yīng)用，與植物表型相結(jié)合的分子生物學(xué)、植物生理學(xué)、統(tǒng)計(jì)學(xué)、作物模型和其他組學(xué)研究，表型組學(xué)相關(guān)的植物生物學(xué)等。期刊已被DOAJ、Scopus、PMC、EI和SCIE等數(shù)據(jù)庫收錄。

說明：本文由《植物表型組學(xué)》編輯部負(fù)責(zé)組稿。

中文內(nèi)容僅供參考，一切內(nèi)容以英文原版為準(zhǔn)。

編輯：張威（實(shí)習(xí)）

審核：卞越、孔敏