{"title":"利用微环境和呼吸角多模态传感技术对无水低温胁迫下的鲟鱼呼吸进行无损检测","authors":"","doi":"10.1016/j.biosystemseng.2024.07.008","DOIUrl":null,"url":null,"abstract":"<div><p>Waterless and low temperature transportation is a green and efficient way for the transportation of live fish. However, waterless and low temperature conditions could lead to a stress response in live fish, resulting in reduced transport survival rates. It is still a challenge to intelligently monitor the breath stress state of live fish under adversity stress. Temperature (T), relative humidity (RH), oxygen (O<sub>2</sub>) and carbon dioxide (CO<sub>2</sub>) signals can reflect changes in adversity stress environment; while the breath angle sensors can monitor the gill opening and closing angle (breath angle) to reflect changes in fish breath. In this work, microenvironment and breath angle sensor systems were designed and developed to comprehensively evaluate the breath stress state of fish. Meanwhile, the Kalman filter-quaternion-fast Fourier transform method was established to process the breath angle signal. The breath angle signal indicated that the sturgeon had three levels of breath stress: acute fluctuation stage (0–2.5h), organismal regulation stage (2.5–16h) and cumulative stress stage (>16h). In addition, linear regression (LR), back propagation neural network (BPNN), support vector regression (SVR), and radial basis function neural network (RBFNN) models were established for breath efficiency signal prediction. The R<sup>2</sup> of the RBFNN (0.9544) model was significantly higher than the LR (0.8092), BPNN (0.9289), and SVR (0.9428) models. This study provided a reference for further intelligent monitoring and management of the fish breath stress state under waterless and low temperature conditions.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Non-destructive detection of sturgeon breath under waterless low temperature stress using microenvironment and breath angle multi-modal sensing\",\"authors\":\"\",\"doi\":\"10.1016/j.biosystemseng.2024.07.008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Waterless and low temperature transportation is a green and efficient way for the transportation of live fish. However, waterless and low temperature conditions could lead to a stress response in live fish, resulting in reduced transport survival rates. It is still a challenge to intelligently monitor the breath stress state of live fish under adversity stress. Temperature (T), relative humidity (RH), oxygen (O<sub>2</sub>) and carbon dioxide (CO<sub>2</sub>) signals can reflect changes in adversity stress environment; while the breath angle sensors can monitor the gill opening and closing angle (breath angle) to reflect changes in fish breath. In this work, microenvironment and breath angle sensor systems were designed and developed to comprehensively evaluate the breath stress state of fish. Meanwhile, the Kalman filter-quaternion-fast Fourier transform method was established to process the breath angle signal. The breath angle signal indicated that the sturgeon had three levels of breath stress: acute fluctuation stage (0–2.5h), organismal regulation stage (2.5–16h) and cumulative stress stage (>16h). In addition, linear regression (LR), back propagation neural network (BPNN), support vector regression (SVR), and radial basis function neural network (RBFNN) models were established for breath efficiency signal prediction. The R<sup>2</sup> of the RBFNN (0.9544) model was significantly higher than the LR (0.8092), BPNN (0.9289), and SVR (0.9428) models. This study provided a reference for further intelligent monitoring and management of the fish breath stress state under waterless and low temperature conditions.</p></div>\",\"PeriodicalId\":9173,\"journal\":{\"name\":\"Biosystems Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2024-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biosystems Engineering\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1537511024001612\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURAL ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems Engineering","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1537511024001612","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
Non-destructive detection of sturgeon breath under waterless low temperature stress using microenvironment and breath angle multi-modal sensing
Waterless and low temperature transportation is a green and efficient way for the transportation of live fish. However, waterless and low temperature conditions could lead to a stress response in live fish, resulting in reduced transport survival rates. It is still a challenge to intelligently monitor the breath stress state of live fish under adversity stress. Temperature (T), relative humidity (RH), oxygen (O2) and carbon dioxide (CO2) signals can reflect changes in adversity stress environment; while the breath angle sensors can monitor the gill opening and closing angle (breath angle) to reflect changes in fish breath. In this work, microenvironment and breath angle sensor systems were designed and developed to comprehensively evaluate the breath stress state of fish. Meanwhile, the Kalman filter-quaternion-fast Fourier transform method was established to process the breath angle signal. The breath angle signal indicated that the sturgeon had three levels of breath stress: acute fluctuation stage (0–2.5h), organismal regulation stage (2.5–16h) and cumulative stress stage (>16h). In addition, linear regression (LR), back propagation neural network (BPNN), support vector regression (SVR), and radial basis function neural network (RBFNN) models were established for breath efficiency signal prediction. The R2 of the RBFNN (0.9544) model was significantly higher than the LR (0.8092), BPNN (0.9289), and SVR (0.9428) models. This study provided a reference for further intelligent monitoring and management of the fish breath stress state under waterless and low temperature conditions.
期刊介绍:
Biosystems Engineering publishes research in engineering and the physical sciences that represent advances in understanding or modelling of the performance of biological systems for sustainable developments in land use and the environment, agriculture and amenity, bioproduction processes and the food chain. The subject matter of the journal reflects the wide range and interdisciplinary nature of research in engineering for biological systems.