[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127650-en":3,"doc-seo-127650-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},127650,962084925636,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","Remote physiological monitoring of the giant panda and red panda using near infrared spectroscopy and machine learning","Appropriate conservation decisions require real-time, accurate information on wildlife populations, yet direct observation and capture are difficult for many threatened and secretive species. This dissertation evaluates whether near infrared spectroscopy (NIRS) can serve as a remote analytical tool by detecting animal “signs” without seeing or capturing animals. Using giant pandas and red pandas as case studies, it tests NIRS combined with mode-cloning and machine learning for nutritional foodscape and demographic analysis, including calibration transfer to field conditions and prediction of reproductive status from minimally processed fecal and forage samples.","Mississippi State University  \nScholars Junction  \n\n| Theses and Dissertations | Theses and Dissertations |\n| --- | --- |\n| 5-12-2023\u003Cbr>Remote physiological monitoring of the giant panda and red panda using near infrared spectroscopy and machine learning\u003Cbr>Qingyu Sheng\u003Cbr>Mississippi State University, [qingyusheng00@gmail.com](qingyusheng00@gmail.com)\u003Cbr>Follow this and additional works at: [https://scholarsjunction.msstate.edu/td](https://scholarsjunction.msstate.edu/td)\u003Cbr> Part of the Other Animal Sciences Commons, Other Physiology Commons, and the Zoology Commons |  |\n\nRecommended Citation  \nSheng, Qingyu, \"Remote physiological monitoring of the giant panda and red panda using near infrared spectroscopy and machine learning\" (2023) . Theses and Dissertations. 5821.  \n[https://scholarsjunction.msstate.edu/td/5821](https://scholarsjunction.msstate.edu/td/5821)  \nThis Dissertation-Open Access is brought to you for free and open access by the Theses and Dissertations at Scholars Junction. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of Scholars Junction. For more information, please contact scholcomm@msstate. libanswers.com.  \nRemote physiological monitoring of the giant panda and red panda using near infrared  \nspectroscopy and machine learning  \nBy  \nQingyu Sheng  \nApproved by:  \nCarrie Kim Vance (Major Professor/Graduate Coordinator) Andrew J. Kouba  \nGuiming Wang  \nAshli E. Brown  \nScott T. Willard (Dean, College of Agriculture and Life Sciences)  \nA Dissertation  \nSubmitted to the Faculty of  \nMississippi State University  \nin Partial Fulfillment of the Requirements  \nfor the Degree of Doctor of Philosophy  \nin Life Sciences (Animal Physiology)  \nin the Department of Biochemistry, Molecular Biology, Entomology & Plant Pathology  \nMississippi State, Mississippi  \nMay 2023  \nCopyright by Qingyu Sheng 2023  \nName: Qingyu Sheng  \nDate of Degree: May 12, 2023  \nInstitution: Mississippi State University  \nMajor Field: Life Sciences (Animal Physiology)  \nMajor Professor: Carrie Kim Vance  \nTitle of Study: Remote physiological monitoring of the giant panda and red panda using near infrared spectroscopy and machine learning  \nPages in Study: 192  \nCandidate for Degree of Doctor of Philosophy  \nAppropriate conservation decisions and efforts must be based on real−time and accurate information about wildlife populations. However, it is extremely challenging to monitor the population demography and physiological traits of many threatened and secretive animal species through direct observation and capture. Near infrared spectroscopy (NIRS) has the potential to bea remote tool to address questions concerning wildlife physiology and demography by analyzing“signs” of animals without seeing or capturing them. In this dissertation, two species, the giant panda (Ailuropoda melanoleuca) and red panda (Ailurus fulgens) are used as a case study, to demonstrate NIRS’ feasibility in studying their physiological properties. The aim of this study is to test NIRS’ potential as a real−time analytical tool for in the nutritional foodscape and demographic analysis using less processed or non−processed field fecal and forage samples with the help of the mode−cloning technique to transfer the master model (dry and ground samples) under laboratory conditions to satellite modes (wet or dry but unground) in field conditions. Mode−cloning is conducted using either slope and bias correction (SBC) or two spectral correction methods, piecewise direct standardization (PDS) and external parameter orthogonalization (EPO) .  \nThe following four hypotheses are tested this dissertation: (1) by using mode−cloning with both SBC and PDS, unprocessed wet or unground dry bamboo leaves (pandas’ food) can be used to determine the crude protein contents; (2) machine learning−based classification models using less processed field feces after mode−cloning with spectral correction approaches (PDS and EPO) can differentiate betw","cbCaipyRdPIdWSAq","https://ap.wps.com/l/cbCaipyRdPIdWSAq","pdf",5103421,1,206,"English","en",105,"# Hypotheses and Objectives\n## Mode-cloning and calibration transfer approach\n## Machine learning classification tasks\n# Research Findings and Implications\n## Real-time monitoring potential\n## Decision support for in situ and ex situ efforts","[{\"question\":\"Why is real-time physiological monitoring important for wildlife conservation?\",\"answer\":\"Accurate conservation decisions depend on real-time information about wildlife populations, but direct monitoring of demography and physiology is difficult for many threatened and secretive species.\"},{\"question\":\"How does near infrared spectroscopy (NIRS) support remote monitoring in this dissertation?\",\"answer\":\"NIRS is explored as a remote tool that can analyze animal “signs” without requiring direct observation or capture, using minimally processed biological samples.\"},{\"question\":\"What does “mode-cloning” enable in this study?\",\"answer\":\"Mode-cloning transfers a master model from laboratory conditions (dry and ground samples) to satellite modes representing field conditions (wet or dry but unground), using spectral correction methods to support analysis in situ.\"}]","Remote physiological monitoring of the giant panda and red panda using near infrared spectroscopy and machine learning | 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