Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Rebecca J Nelson"'
Publikováno v:
Forensic Science International: Mind and Law, Vol 5, Iss , Pp 100131- (2024)
The insanity defense remains one of the most difficult evaluations for a forensic examiner because it requires a retrospective reconstruction of an individual's mental state and extracting that mental state to specific psycholegal criteria (e.g., cap
Externí odkaz:
https://doaj.org/article/2d4e64469684443ca8159e938862243a
Publikováno v:
PLoS Genetics, Vol 11, Iss 3, p e1005045 (2015)
Gray leaf spot (GLS), caused by Cercospora zeae-maydis and Cercospora zeina, is one of the most important diseases of maize worldwide. The pathogen has a necrotrophic lifestyle and no major genes are known for GLS. Quantitative resistance, although p
Externí odkaz:
https://doaj.org/article/0c8814db5c134266a5fcc1b074cc54f6
Autor:
Christopher B. Barrett, Tim Benton, Jessica Fanzo, Mario Herrero, Rebecca J. Nelson, Elizabeth Bageant, Edward Buckler, Karen Cooper, Isabella Culotta, Shenggen Fan, Rikin Gandhi, Steven James, Mark Kahn, Laté Lawson-Lartego, Jiali Liu, Quinn Marshall, Daniel Mason-D'Croz, Alexander Mathys, Cynthia Mathys, Veronica Mazariegos-Anastassiou, Alesha Miller, Kamakhya Misra, Andrew Mude, Jianbo Shen, Lindiwe Majele Sibanda, Claire Song, Roy Steiner, Philip Thornton, Stephen Wood
This open access book is the result of an expert panel convened by the Cornell Atkinson Center for Sustainability and Nature Sustainability. The panel tackled the seventeen UN Sustainable Development Goals (SDGs) for 2030 head-on, with respect to the
Publikováno v:
The Plant Genome, Vol 16, Iss 1, Pp n/a-n/a (2023)
Abstract Brown midrib (BMR) maize (Zea mays L.) harbors mutations that result in lower lignin levels and higher feed digestibility, making it a desirable silage market class for ruminant nutrition. Northern leaf blight (NLB) epidemics in upstate New
Externí odkaz:
https://doaj.org/article/c9abf7906e2d43b58abf1e63fd19e767
Autor:
Judith M. Kolkman, Josh Strable, Kate Harline, Dallas E. Kroon, Tyr Wiesner-Hanks, Peter J. Bradbury, Rebecca J. Nelson
Publikováno v:
G3: Genes, Genomes, Genetics, Vol 10, Iss 10, Pp 3611-3622 (2020)
Plant disease resistance is largely governed by complex genetic architecture. In maize, few disease resistance loci have been characterized. Near-isogenic lines are a powerful genetic tool to dissect quantitative trait loci. We analyzed an introgress
Externí odkaz:
https://doaj.org/article/a4f46adb313b4962bbf596519efcd8b9
Autor:
Madleina Manetsch, Rebecca J. Nelson Aguiar, Daniel Hermann, Claudia van der Put, Thomas Grisso, Cyril Boonmann
Publikováno v:
Frontiers in Psychology, Vol 12 (2021)
Female juvenile offenders have only recently shifted into the focus of research. Moreover, a specific subgroup, female juveniles who sexually offended (JSO) are greatly overlooked. Therefore, there is a dearth of knowledge regarding the characteristi
Externí odkaz:
https://doaj.org/article/cf02aab2e1804bfa8c27ff784d0c25d5
Publikováno v:
Toxins, Vol 13, Iss 9, p 652 (2021)
Fumonisin mycotoxins are a persistent challenge to human and livestock health in tropical and sub-tropical maize cropping systems, and more efficient methods are needed to reduce their presence in food systems. We constructed a novel, low-cost device
Externí odkaz:
https://doaj.org/article/9be588c126e94519a0006633c720227a
Akademický článek
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Autor:
Tyr Wiesner-Hanks, Ethan L. Stewart, Nicholas Kaczmar, Chad DeChant, Harvey Wu, Rebecca J. Nelson, Hod Lipson, Michael A. Gore
Publikováno v:
BMC Research Notes, Vol 11, Iss 1, Pp 1-3 (2018)
Abstract Objectives Automated detection and quantification of plant diseases would enable more rapid gains in plant breeding and faster scouting of farmers’ fields. However, it is difficult for a simple algorithm to distinguish between the target d
Externí odkaz:
https://doaj.org/article/141d4ae8ded24defb1c5cedad37a4eb1
Autor:
Tyr Wiesner-Hanks, Harvey Wu, Ethan Stewart, Chad DeChant, Nicholas Kaczmar, Hod Lipson, Michael A. Gore, Rebecca J. Nelson
Publikováno v:
Frontiers in Plant Science, Vol 10 (2019)
Computer vision models that can recognize plant diseases in the field would be valuable tools for disease management and resistance breeding. Generating enough data to train these models is difficult, however, since only trained experts can accuratel
Externí odkaz:
https://doaj.org/article/532813fb826a425dbb29e3eb3e252ba7