WeChat Mini Program
Old Version Features

Triploidy in Mytilus Edulis Impacts the Mechanical Properties of Byssal Threads

AQUACULTURE(2023)

Univ Quebec Rimouski

Cited 1|Views32
Abstract
A major problem in mussel farming is mussel fall-off from mussel socks due to weakened byssal threads. This weakening is particularly prevalent following spawning events. During the last decades, significant work has been devoted to the production of triploid bivalves, which have a lower reproductive investment. In this study, we compared the byssal properties and energetic rates of triploid and diploid 1-year-old mussels (˂30-mm). To determine the effect of triploidy on byssal threads, diploid and triploid mussels were placed in a recirculating flume to induce the production of byssal filaments. Our results showed that triploid mussels produced up to 65% more threads than the diploids. Furthermore, tensile measurements showed that byssal threads from triploid mussels had higher Young's modulus values (45% increase) and had multiple yield points. Energetic rates and metabolic investments were measured through food assimilation and oxygen consumption. The results showed that triploid mussels had a higher clearance rate (40% increase) and scope for growth (260% increase) when compared to diploids. Morphological comparisons showed variations between the two groups, with triploid mussels having a larger shell height than diploids of the same length.
More
Translated text
Key words
Triploidy,Mytilus edulis,Byssus,Attachment,Scope for growth,VO2
上传PDF
Bibtex
收藏
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined