Effects of phosphorus availabilities on growth and yield of foxtail millet: insights from high-throughput phenotyping platforms

被引：0

作者：

Tharanya Murugesan ^{[1
]}

Sivasakthi Kaliamoorthy ^{[1
]}

Sunita Choudhary ^{[1
]}

Keerthi Vysyaraju ^{[1
]}

Devan Sai Gudela ^{[2
]}

Annepu Anusha ^{[1
]}

Kommireddypally Sowmya Goud ^{[2
]}

Sara Loftus ^{[1
]}

Michaela A. Dippold ^{[2
]}

Suresh Kanuri ^{[3
]}

Rekha Baddam ^{[4
]}

Alison Baker ^{[4
]}

S. Antony Ceasar ^{[1
]}

Jana Kholova ^{[1
]}

机构：

[1] International Crops Research Institute for the Semi-Arid Tropics (ICRISAT),Geo

[2] Crops Physiology Laboratory,Biosphere Interactions, Department of Geosciences and Department of Biology

[3] Centurion University of Technology and Management (CUTM),Centre for Plant Sciences and School of Molecular and Cellular Biology

[4] Professor Jayashankar Telangana State Agricultural University,Department of Information Technologies, Faculty of Economics and Management

[5] University of Tuebingen,undefined

[6] University of Leeds,undefined

[7] Department of Biosciences,undefined

[8] Rajagiri College of Social Sciences,undefined

[9] Czech University of Life Sciences,undefined

[10] Prague,undefined

来源：

Planta | 2025年 / 261卷 / 5期

关键词：

Foxtail millet; Grain P content; High-throughput phenotyping platforms; Nutrient deficiency; Phosphorus stress; Phosphorus use efficiency; Resource poor soil;

D O I：

10.1007/s00425-025-04672-7

中图分类号：

学科分类号：

摘要：

引用

共 50 条

[1] Integrating dynamic high-throughput phenotyping and genetic analysis to monitor growth variation in foxtail millet
Wang, Zhenyu
Hao, Jiongyu
Shi, Xiaofan
Wang, Qiaoqiao
Zhang, Wuping
Li, Fuzhong
Mur, Luis A. J.
Han, Yuanhuai
Hou, Siyu
Han, Jiwan
Sun, Zhaoxia
PLANT METHODS, 2024, 20 (01)
[2] Pitfalls and potential of high-throughput plant phenotyping platforms
Poorter, Hendrik
Hummel, Gregoire M.
Nagel, Kerstin A.
Fiorani, Fabio
von Gillhaussen, Philipp
Virnich, Olivia
Schurr, Ulrich
Postma, Johannes A.
van de Zedde, Rick
Wiese-Klinkenberg, Anika
FRONTIERS IN PLANT SCIENCE, 2023, 14
[3] High-throughput phenotyping platforms for pulse crop biofortification
Madurapperumage, Amod
Naser, M. Z.
Boatwright, Lucas
Bridges, William
Vandemark, George
Thavarajah, Dil
PLANTS PEOPLE PLANET, 2025, 7 (01) : 49 - 61
[4] Measuring growth rate in high-throughput growth phenotyping
Blomberg, Anders
CURRENT OPINION IN BIOTECHNOLOGY, 2011, 22 (01) : 94 - 102
[5] High-throughput phenotyping of rice growth traits
Esther Lau
Nature Reviews Genetics, 2014, 15 (12) : 778 - 778
[6] RGB picture vegetation indexes for High-Throughput Phenotyping Platforms (HTPPs)
Kefauver, Shawn C.
El-Haddad, George
Vergara-Diaz, Omar
Luis Arausa, Jose
REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XVII, 2015, 9637
[7] Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping
Shafiekhani, Ali
Kadam, Suhas
Fritschi, Felix B.
DeSouza, Guilherme N.
SENSORS, 2017, 17 (01)
[8] High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms
Jin, Xiuliang
Zarco-Tejada, Pablo J.
Schmidhalter, Urs
Reynolds, Matthew P.
Hawkesford, Malcolm J.
Varshney, Rajeev K.
Yang, Tao
Nie, Chengwei
Li, Zhenhai
Ming, Bo
Xiao, Yonggui
Xie, Yongdun
Li, Shaokun
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2021, 9 (01) : 200 - 231
[9] Estimation of soybean yield based on high-throughput phenotyping and machine learning
Li, Xiuni
Chen, Menggen
He, Shuyuan
Xu, Xiangyao
He, Lingxiao
Wang, Li
Gao, Yang
Tang, Fenda
Gong, Tao
Wang, Wenyan
Xu, Mei
Liu, Chunyan
Yu, Liang
Liu, Weiguo
Yang, Wenyu
FRONTIERS IN PLANT SCIENCE, 2024, 15
[10] High-throughput phenotyping platforms enhance genomic selection for wheat grain yield across populations and cycles in early stage
Jin Sun
Jesse A. Poland
Suchismita Mondal
José Crossa
Philomin Juliana
Ravi P. Singh
Jessica E. Rutkoski
Jean-Luc Jannink
Leonardo Crespo-Herrera
Govindan Velu
Julio Huerta-Espino
Mark E. Sorrells
Theoretical and Applied Genetics, 2019, 132 : 1705 - 1720

← 1 2 3 4 5 →