Matthias Corion , Miguel Portillo-Estrada , Simão Monteiro Belo dos Santos , Nadia Everaert , Jeroen Lammertyn , Maarten Hertog , Bart De Ketelaere
{"title":"鸡体内性别鉴定:评估挥发性有机化合物分析技术和从孵化开始的每日预测性能","authors":"Matthias Corion , Miguel Portillo-Estrada , Simão Monteiro Belo dos Santos , Nadia Everaert , Jeroen Lammertyn , Maarten Hertog , Bart De Ketelaere","doi":"10.1016/j.biosystemseng.2024.08.013","DOIUrl":null,"url":null,"abstract":"<div><p>In ovo sexing identifies chicken embryo sex before or during incubation to avoid euthanising male chicks after hatching, enhancing animal welfare in the laying hen industry. Recently, researchers demonstrated the potential for non-invasive and early in ovo sexing through the analysis of volatile organic compounds (VOCs) emitted by eggs. However, a knowledge gap remains in understanding prediction model robustness, the efficacy of faster acquisition techniques, and day-to-day performance. In this study, two experiments were performed to fill these gaps. In Experiment 1, passive VOC extractions were performed on 110 eggs on incubation day 10 using sampling bags employing headspace sorptive extraction-gas chromatography-mass spectrometry (HSSE-GC-MS), proton transfer reaction-time-of-flight-mass spectrometry (PTR-TOF-MS), and selected ion flow tube-mass spectrometry (SIFT-MS). Prediction models were built using partial least squares-discriminant analysis (PLS-DA) and variable selection methods. As a result, prediction accuracies ranged from 57.6 % to 61.4 %, indicating no significant difference between the devices and highlighting the need for further optimisations. In Experiment 2, passive VOC samplings were performed on 42 eggs in glass jars during the initial 12 days of incubation using HSSE-GC-MS. Consequently, the optimised setup yielded higher accuracies ranging from 63.1 % (on day 0) to 71.4 % (on days 4, 6, and 12), revealing VOCs consistently elevated in relative abundance for a specific sex, and overall VOC abundance was higher in male embryos. Suggestions for future experiments to increase the accuracy of VOC in ovo sexing include active sampling with inert materials, expanding sample sets, and targeting consistent compounds.</p></div>","PeriodicalId":9173,"journal":{"name":"Biosystems Engineering","volume":"247 ","pages":"Pages 109-118"},"PeriodicalIF":4.4000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"In ovo sexing of chickens: Evaluating volatile organic compounds analysis techniques and daily prediction performance from the onset of incubation\",\"authors\":\"Matthias Corion , Miguel Portillo-Estrada , Simão Monteiro Belo dos Santos , Nadia Everaert , Jeroen Lammertyn , Maarten Hertog , Bart De Ketelaere\",\"doi\":\"10.1016/j.biosystemseng.2024.08.013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In ovo sexing identifies chicken embryo sex before or during incubation to avoid euthanising male chicks after hatching, enhancing animal welfare in the laying hen industry. Recently, researchers demonstrated the potential for non-invasive and early in ovo sexing through the analysis of volatile organic compounds (VOCs) emitted by eggs. However, a knowledge gap remains in understanding prediction model robustness, the efficacy of faster acquisition techniques, and day-to-day performance. In this study, two experiments were performed to fill these gaps. In Experiment 1, passive VOC extractions were performed on 110 eggs on incubation day 10 using sampling bags employing headspace sorptive extraction-gas chromatography-mass spectrometry (HSSE-GC-MS), proton transfer reaction-time-of-flight-mass spectrometry (PTR-TOF-MS), and selected ion flow tube-mass spectrometry (SIFT-MS). Prediction models were built using partial least squares-discriminant analysis (PLS-DA) and variable selection methods. As a result, prediction accuracies ranged from 57.6 % to 61.4 %, indicating no significant difference between the devices and highlighting the need for further optimisations. In Experiment 2, passive VOC samplings were performed on 42 eggs in glass jars during the initial 12 days of incubation using HSSE-GC-MS. Consequently, the optimised setup yielded higher accuracies ranging from 63.1 % (on day 0) to 71.4 % (on days 4, 6, and 12), revealing VOCs consistently elevated in relative abundance for a specific sex, and overall VOC abundance was higher in male embryos. Suggestions for future experiments to increase the accuracy of VOC in ovo sexing include active sampling with inert materials, expanding sample sets, and targeting consistent compounds.</p></div>\",\"PeriodicalId\":9173,\"journal\":{\"name\":\"Biosystems Engineering\",\"volume\":\"247 \",\"pages\":\"Pages 109-118\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2024-09-13\",\"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/S1537511024001910\",\"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/S1537511024001910","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}
In ovo sexing of chickens: Evaluating volatile organic compounds analysis techniques and daily prediction performance from the onset of incubation
In ovo sexing identifies chicken embryo sex before or during incubation to avoid euthanising male chicks after hatching, enhancing animal welfare in the laying hen industry. Recently, researchers demonstrated the potential for non-invasive and early in ovo sexing through the analysis of volatile organic compounds (VOCs) emitted by eggs. However, a knowledge gap remains in understanding prediction model robustness, the efficacy of faster acquisition techniques, and day-to-day performance. In this study, two experiments were performed to fill these gaps. In Experiment 1, passive VOC extractions were performed on 110 eggs on incubation day 10 using sampling bags employing headspace sorptive extraction-gas chromatography-mass spectrometry (HSSE-GC-MS), proton transfer reaction-time-of-flight-mass spectrometry (PTR-TOF-MS), and selected ion flow tube-mass spectrometry (SIFT-MS). Prediction models were built using partial least squares-discriminant analysis (PLS-DA) and variable selection methods. As a result, prediction accuracies ranged from 57.6 % to 61.4 %, indicating no significant difference between the devices and highlighting the need for further optimisations. In Experiment 2, passive VOC samplings were performed on 42 eggs in glass jars during the initial 12 days of incubation using HSSE-GC-MS. Consequently, the optimised setup yielded higher accuracies ranging from 63.1 % (on day 0) to 71.4 % (on days 4, 6, and 12), revealing VOCs consistently elevated in relative abundance for a specific sex, and overall VOC abundance was higher in male embryos. Suggestions for future experiments to increase the accuracy of VOC in ovo sexing include active sampling with inert materials, expanding sample sets, and targeting consistent compounds.
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.