Difference between revisions of "Template:Article of the week"

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text.)
(Updated article of the week text)
(351 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig14 Baker BiodiversityDataJournal2014 2.JPG|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab1 Williamson F1000Res2023 10.png|240px]]</div>
'''"[[Journal:Open source data logger for low-cost environmental monitoring|Open source data logger for low-cost environmental monitoring]]"'''
'''"[[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Data management challenges for artificial intelligence in plant and agricultural research]]"'''


The increasing transformation of biodiversity into a data-intensive science has seen numerous independent systems linked and aggregated into the current landscape of [[biodiversity informatics]]. This paper outlines how we can move forward with this program, incorporating real-time environmental monitoring into our methodology using low-power and low-cost computing platforms.  
[[Artificial intelligence]] (AI) is increasingly used within plant science, yet it is far from being routinely and effectively implemented in this domain. Particularly relevant to the development of novel food and agricultural technologies is the development of validated, meaningful, and usable ways to integrate, compare, and [[Data visualization|visualize]] large, multi-dimensional datasets from different sources and scientific approaches. After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in [[Information management|data management]] that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of [[machine learning]] (ML), which holds much promise for this domain ... ('''[[Journal:Data management challenges for artificial intelligence in plant and agricultural research|Full article...]]''')<br />
 
''Recently featured'':
Low power and cheap computational projects such as Arduino and Raspberry Pi have brought the use of small computers and micro-controllers to the masses, and their use in fields related to biodiversity science is increasing (e.g. Hirafuji shows the use of Arduino in agriculture. There is a large amount of potential in using automated tools for monitoring environments and identifying species based on these emerging hardware platforms, but to be truly useful we must integrate the data they generate with our existing systems. This paper describes the construction of an open-source environmental data logger based on the Arduino platform and its integration with the web content management system [[Drupal]] which is used as the basis for Scratchpads among other biodiversity tools. ('''[[Journal:Open source data logger for low-cost environmental monitoring|Full article...]]''')<br />
{{flowlist |
<br />
* [[Journal:A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model|A blockchain-driven IoT-based food quality traceability system for dairy products using a deep learning model]]
''Recently featured'':  
* [[Journal:Effect of good clinical laboratory practices (GCLP) quality training on knowledge, attitude, and practice among laboratory professionals: Quasi-experimental study|Effect of good clinical laboratory practices (GCLP) quality training on knowledge, attitude, and practice among laboratory professionals: Quasi-experimental study]]
: ▪ [[Journal:Evaluating health information systems using ontologies|Evaluating health information systems using ontologies]]
* [[Journal:GitHub as an open electronic laboratory notebook for real-time sharing of knowledge and collaboration|GitHub as an open electronic laboratory notebook for real-time sharing of knowledge and collaboration]]
: ▪ [[Journal:From the desktop to the grid: Scalable bioinformatics via workflow conversion|From the desktop to the grid: Scalable bioinformatics via workflow conversion]]
}}
: ▪ [[Journal:Terminology spectrum analysis of natural-language chemical documents: Term-like phrases retrieval routine|Terminology spectrum analysis of natural-language chemical documents: Term-like phrases retrieval routine]]

Revision as of 17:50, 15 April 2024

Tab1 Williamson F1000Res2023 10.png

"Data management challenges for artificial intelligence in plant and agricultural research"

Artificial intelligence (AI) is increasingly used within plant science, yet it is far from being routinely and effectively implemented in this domain. Particularly relevant to the development of novel food and agricultural technologies is the development of validated, meaningful, and usable ways to integrate, compare, and visualize large, multi-dimensional datasets from different sources and scientific approaches. After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in data management that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of machine learning (ML), which holds much promise for this domain ... (Full article...)
Recently featured:

Retrieved from "https://www.limswiki.org/index.php?title=Template:Article_of_the_week&oldid=63298"