These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
158 related articles for article (PubMed ID: 35069637)
1. Exploiting High-Throughput Indoor Phenotyping to Characterize the Founders of a Structured Ebersbach J; Khan NA; McQuillan I; Higgins EE; Horner K; Bandi V; Gutwin C; Vail SL; Robinson SJ; Parkin IAP Front Plant Sci; 2021; 12():780250. PubMed ID: 35069637 [TBL] [Abstract][Full Text] [Related]
2. Root morphology and seed and leaf ionomic traits in a Brassica napus L. diversity panel show wide phenotypic variation and are characteristic of crop habit. Thomas CL; Alcock TD; Graham NS; Hayden R; Matterson S; Wilson L; Young SD; Dupuy LX; White PJ; Hammond JP; Danku JM; Salt DE; Sweeney A; Bancroft I; Broadley MR BMC Plant Biol; 2016 Oct; 16(1):214. PubMed ID: 27716103 [TBL] [Abstract][Full Text] [Related]
3. A real-time phenotyping framework using machine learning for plant stress severity rating in soybean. Naik HS; Zhang J; Lofquist A; Assefa T; Sarkar S; Ackerman D; Singh A; Singh AK; Ganapathysubramanian B Plant Methods; 2017; 13():23. PubMed ID: 28405214 [TBL] [Abstract][Full Text] [Related]
4. Phenomics based prediction of plant biomass and leaf area in wheat using machine learning approaches. Singh B; Kumar S; Elangovan A; Vasht D; Arya S; Duc NT; Swami P; Pawar GS; Raju D; Krishna H; Sathee L; Dalal M; Sahoo RN; Chinnusamy V Front Plant Sci; 2023; 14():1214801. PubMed ID: 37448870 [TBL] [Abstract][Full Text] [Related]
5. High-throughput phenotyping-based quantitative trait loci mapping reveals the genetic architecture of the salt stress tolerance of Brassica napus. Zhang G; Zhou J; Peng Y; Tan Z; Zhang Y; Zhao H; Liu D; Liu X; Li L; Yu L; Jin C; Fang S; Shi J; Geng Z; Yang S; Chen G; Liu K; Yang Q; Feng H; Guo L; Yang W Plant Cell Environ; 2023 Feb; 46(2):549-566. PubMed ID: 36354160 [TBL] [Abstract][Full Text] [Related]
6. Image-Based Phenotyping of Flowering Intensity in Cool-Season Crops. Zhang C; Craine WA; McGee RJ; Vandemark GJ; Davis JB; Brown J; Hulbert SH; Sankaran S Sensors (Basel); 2020 Mar; 20(5):. PubMed ID: 32155830 [TBL] [Abstract][Full Text] [Related]
7. High-throughput field crop phenotyping: current status and challenges. Ninomiya S Breed Sci; 2022 Mar; 72(1):3-18. PubMed ID: 36045897 [TBL] [Abstract][Full Text] [Related]
9. Precision phenotyping across the life cycle to validate and decipher drought-adaptive QTLs of wild emmer wheat ( Lauterberg M; Saranga Y; Deblieck M; Klukas C; Krugman T; Perovic D; Ordon F; Graner A; Neumann K Front Plant Sci; 2022; 13():965287. PubMed ID: 36311121 [TBL] [Abstract][Full Text] [Related]
10. High-throughput phenotyping (HTP) identifies seedling root traits linked to variation in seed yield and nutrient capture in field-grown oilseed rape (Brassica napus L.). Thomas CL; Graham NS; Hayden R; Meacham MC; Neugebauer K; Nightingale M; Dupuy LX; Hammond JP; White PJ; Broadley MR Ann Bot; 2016 Oct; 118(4):655-665. PubMed ID: 27052342 [TBL] [Abstract][Full Text] [Related]
11. Comparison of Various Drought Resistance Traits in Soybean ( Kim J; Lee C; Park J; Kim N; Kim SL; Baek J; Chung YS; Kim K Plants (Basel); 2023 Jun; 12(12):. PubMed ID: 37375956 [TBL] [Abstract][Full Text] [Related]
12. Diverse regulatory factors associate with flowering time and yield responses in winter-type Brassica napus. Schiessl S; Iniguez-Luy F; Qian W; Snowdon RJ BMC Genomics; 2015 Sep; 16():737. PubMed ID: 26419915 [TBL] [Abstract][Full Text] [Related]
13. Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses. Xiang L; Nolan TM; Bao Y; Elmore M; Tuel T; Gai J; Shah D; Wang P; Huser NM; Hurd AM; McLaughlin SA; Howell SH; Walley JW; Yin Y; Tang L Plant J; 2021 Sep; 107(6):1837-1853. PubMed ID: 34216161 [TBL] [Abstract][Full Text] [Related]
17. Mapping a major QTL responsible for dwarf architecture in Brassica napus using a single-nucleotide polymorphism marker approach. Wang Y; Chen W; Chu P; Wan S; Yang M; Wang M; Guan R BMC Plant Biol; 2016 Aug; 16(1):178. PubMed ID: 27538713 [TBL] [Abstract][Full Text] [Related]
18. A spatio temporal spectral framework for plant stress phenotyping. Khanna R; Schmid L; Walter A; Nieto J; Siegwart R; Liebisch F Plant Methods; 2019; 15():13. PubMed ID: 30774703 [TBL] [Abstract][Full Text] [Related]
19. Combining UAV-RGB high-throughput field phenotyping and genome-wide association study to reveal genetic variation of rice germplasms in dynamic response to drought stress. Jiang Z; Tu H; Bai B; Yang C; Zhao B; Guo Z; Liu Q; Zhao H; Yang W; Xiong L; Zhang J New Phytol; 2021 Oct; 232(1):440-455. PubMed ID: 34165797 [TBL] [Abstract][Full Text] [Related]
20. Stress phenotyping analysis leveraging autofluorescence image sequences with machine learning. Das Choudhury S; Guadagno CR; Bashyam S; Mazis A; Ewers BE; Samal A; Awada T Front Plant Sci; 2024; 15():1353110. PubMed ID: 38708393 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]