High-Throughput Phenotyping in Soybean-Reference-Cited by-同舟云学术

High-Throughput Phenotyping in Soybean

Published:2021 Issue: Volume: Page:129-163
ISSN:2662-3188
Container-title:Concepts and Strategies in Plant Sciences
language:
Short-container-title:

Author:

Singh Asheesh K.,Singh Arti,Sarkar Soumik,Ganapathysubramanian Baskar,Schapaugh William,Miguez Fernando E.,Carley Clayton N.,Carroll Matthew E.,Chiozza Mariana V.,Chiteri Kevin O.,Falk Kevin G.,Jones Sarah E.,Jubery Talukder Z.,Mirnezami Seyed V.,Nagasubramanian Koushik,Parmley Kyle A.,Rairdin Ashlyn M.,Shook Johnathon M.,Van der Laan Liza,Young Therin J.,Zhang Jiaoping

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-73734-4_7

Reference185 articles.

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2. Adu MO, Chatot A, Wiesel L, Bennett MJ, Broadley MR, White PJ et al (2014) A scanner system for high-resolution quantification of variation in root growth dynamics of Brassica rapa genotypes. J Exp Bot 65:2039–2048

3. Ahmad IS, Reid JF, Paulsen MR, Sinclair JB (1999) Color classifier for symptomatic soybean seeds using image processing. Plant Dis 83:320–327

4. Akintayo A, Tylka GL, Singh AK, Ganapathysubramanian B, Singh A, Sarkar S (2018) A deep learning framework to discern and count microscopic nematode eggs. Sci Rep 8:9145

5. Allen TW, Bradley CA, Sisson AJ, Byamukama E, Chilvers MI, Coker CM et al (2017) Soybean yield loss estimates due to diseases in the United States and Ontario, Canada, from 2010 to 2014. Plant Health Prog 18:19–27

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