Ontology type: schema:ScholarlyArticle Open Access: True
2020-06-16
AUTHORSMichael-Thomas Ramsey, Martin Bencsik, Michael Ian Newton, Maritza Reyes, Maryline Pioz, Didier Crauser, Noa Simon Delso, Yves Le Conte
ABSTRACTIn this work, we disclose a non-invasive method for the monitoring and predicting of the swarming process within honeybee colonies, using vibro-acoustic information. Two machine learning algorithms are presented for the prediction of swarming, based on vibration data recorded using accelerometers placed in the heart of honeybee hives. Both algorithms successfully discriminate between colonies intending and not intending to swarm with a high degree of accuracy, over 90% for each method, with successful swarming prediction up to 30 days prior to the event. We show that instantaneous vibrational spectra predict the swarming within the swarming season only, and that this limitation can be lifted provided that the history of the evolution of the spectra is accounted for. We also disclose queen toots and quacks, showing statistics of the occurrence of queen pipes over the entire swarming season. From this we were able to determine that (1) tooting always precedes quacking, (2) under natural conditions there is a 4 to 7 day period without queen tooting following the exit of the primary swarm, and (3) human intervention, such as queen clipping and the opening of a hive, causes strong interferences with important mechanisms for the prevention of simultaneous rival queen emergence. More... »
PAGES9798
http://scigraph.springernature.com/pub.10.1038/s41598-020-66115-5
DOIhttp://dx.doi.org/10.1038/s41598-020-66115-5
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1128494140
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/32546693
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Information and Computing Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Artificial Intelligence and Image Processing",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Animals",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Bees",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Behavior, Animal",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Seasons",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Spectrum Analysis",
"type": "DefinedTerm"
},
{
"inDefinedTermSet": "https://www.nlm.nih.gov/mesh/",
"name": "Vibration",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Nottingham Trent University, School of Science and Technology, Clifton Lane, NG11 8NS, Nottingham, United Kingdom",
"id": "http://www.grid.ac/institutes/grid.12361.37",
"name": [
"Nottingham Trent University, School of Science and Technology, Clifton Lane, NG11 8NS, Nottingham, United Kingdom"
],
"type": "Organization"
},
"familyName": "Ramsey",
"givenName": "Michael-Thomas",
"id": "sg:person.013776426507.13",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013776426507.13"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Nottingham Trent University, School of Science and Technology, Clifton Lane, NG11 8NS, Nottingham, United Kingdom",
"id": "http://www.grid.ac/institutes/grid.12361.37",
"name": [
"Nottingham Trent University, School of Science and Technology, Clifton Lane, NG11 8NS, Nottingham, United Kingdom"
],
"type": "Organization"
},
"familyName": "Bencsik",
"givenName": "Martin",
"id": "sg:person.01234044621.07",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01234044621.07"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Nottingham Trent University, School of Science and Technology, Clifton Lane, NG11 8NS, Nottingham, United Kingdom",
"id": "http://www.grid.ac/institutes/grid.12361.37",
"name": [
"Nottingham Trent University, School of Science and Technology, Clifton Lane, NG11 8NS, Nottingham, United Kingdom"
],
"type": "Organization"
},
"familyName": "Newton",
"givenName": "Michael Ian",
"id": "sg:person.0624702152.65",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624702152.65"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "l\u2019Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE), UR 406 Abeilles et Environnement, Domaine Saint-Paul, 84914, Avignon, France",
"id": "http://www.grid.ac/institutes/None",
"name": [
"l\u2019Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE), UR 406 Abeilles et Environnement, Domaine Saint-Paul, 84914, Avignon, France"
],
"type": "Organization"
},
"familyName": "Reyes",
"givenName": "Maritza",
"id": "sg:person.012351722045.18",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012351722045.18"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "l\u2019Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE), UR 406 Abeilles et Environnement, Domaine Saint-Paul, 84914, Avignon, France",
"id": "http://www.grid.ac/institutes/None",
"name": [
"l\u2019Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE), UR 406 Abeilles et Environnement, Domaine Saint-Paul, 84914, Avignon, France"
],
"type": "Organization"
},
"familyName": "Pioz",
"givenName": "Maryline",
"id": "sg:person.01260656727.83",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01260656727.83"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "l\u2019Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE), UR 406 Abeilles et Environnement, Domaine Saint-Paul, 84914, Avignon, France",
"id": "http://www.grid.ac/institutes/None",
"name": [
"l\u2019Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE), UR 406 Abeilles et Environnement, Domaine Saint-Paul, 84914, Avignon, France"
],
"type": "Organization"
},
"familyName": "Crauser",
"givenName": "Didier",
"id": "sg:person.0637174341.97",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0637174341.97"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Centre Apicole de Recherche et d\u2019Information, CARI, 4, Place Croix du Sud, B-1348, Louvain-La-Neuve, Belgium",
"id": "http://www.grid.ac/institutes/None",
"name": [
"Centre Apicole de Recherche et d\u2019Information, CARI, 4, Place Croix du Sud, B-1348, Louvain-La-Neuve, Belgium"
],
"type": "Organization"
},
"familyName": "Delso",
"givenName": "Noa Simon",
"id": "sg:person.07700154247.27",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07700154247.27"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "l\u2019Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE), UR 406 Abeilles et Environnement, Domaine Saint-Paul, 84914, Avignon, France",
"id": "http://www.grid.ac/institutes/None",
"name": [
"l\u2019Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE), UR 406 Abeilles et Environnement, Domaine Saint-Paul, 84914, Avignon, France"
],
"type": "Organization"
},
"familyName": "Le Conte",
"givenName": "Yves",
"id": "sg:person.01223471277.66",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01223471277.66"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1038/s41598-018-32931-z",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1107245498",
"https://doi.org/10.1038/s41598-018-32931-z"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf02224083",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028555853",
"https://doi.org/10.1007/bf02224083"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf00603817",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007221798",
"https://doi.org/10.1007/bf00603817"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s002650050536",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053160430",
"https://doi.org/10.1007/s002650050536"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf00339456",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085725671",
"https://doi.org/10.1007/bf00339456"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf02226919",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1041221169",
"https://doi.org/10.1007/bf02226919"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/184842a0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042138953",
"https://doi.org/10.1038/184842a0"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1051/apido:19930309",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053217929",
"https://doi.org/10.1051/apido:19930309"
],
"type": "CreativeWork"
}
],
"datePublished": "2020-06-16",
"datePublishedReg": "2020-06-16",
"description": "In this work, we disclose a non-invasive method for the monitoring and predicting of the swarming process within honeybee colonies, using vibro-acoustic information. Two machine learning algorithms are presented for the prediction of swarming, based on vibration data recorded using accelerometers placed in the heart of honeybee hives. Both algorithms successfully discriminate between colonies intending and not intending to swarm with a high degree of accuracy, over 90% for each method, with successful swarming prediction up to 30 days prior to the event. We show that instantaneous vibrational spectra predict the swarming within the swarming season only, and that this limitation can be lifted provided that the history of the evolution of the spectra is accounted for. We also disclose queen toots and quacks, showing statistics of the occurrence of queen pipes over the entire swarming season. From this we were able to determine that (1) tooting always precedes quacking, (2) under natural conditions there is a 4 to 7 day period without queen tooting following the exit of the primary swarm, and (3) human intervention, such as queen clipping and the opening of a hive, causes strong interferences with important mechanisms for the prevention of simultaneous rival queen emergence.",
"genre": "article",
"id": "sg:pub.10.1038/s41598-020-66115-5",
"inLanguage": "en",
"isAccessibleForFree": true,
"isFundedItemOf": [
{
"id": "sg:grant.3793000",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1045337",
"issn": [
"2045-2322"
],
"name": "Scientific Reports",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "10"
}
],
"keywords": [
"human intervention",
"algorithm",
"vibration data",
"machine",
"primary swarm",
"hives",
"swarm",
"prediction",
"accuracy",
"strong interference",
"information",
"Predicting",
"swarming",
"method",
"toot",
"monitoring",
"accelerometer",
"work",
"high degree",
"limitations",
"data",
"interference",
"process",
"statistics",
"emergence",
"honeybee colonies",
"honeybee hives",
"evolution",
"events",
"mechanism",
"non-invasive method",
"degree",
"colonies",
"conditions",
"exit",
"spectra",
"heart",
"pipe",
"important mechanism",
"occurrence",
"queen emergence",
"history",
"natural conditions",
"intervention",
"prevention",
"days",
"season",
"period",
"queens",
"opening",
"quacks",
"quacking",
"day period",
"vibrational spectra"
],
"name": "The prediction of swarming in honeybee colonies using vibrational spectra",
"pagination": "9798",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1128494140"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1038/s41598-020-66115-5"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"32546693"
]
}
],
"sameAs": [
"https://doi.org/10.1038/s41598-020-66115-5",
"https://app.dimensions.ai/details/publication/pub.1128494140"
],
"sdDataset": "articles",
"sdDatePublished": "2022-06-01T22:20",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/article/article_863.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1038/s41598-020-66115-5"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-020-66115-5'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-020-66115-5'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-020-66115-5'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-020-66115-5'
This table displays all metadata directly associated to this object as RDF triples.
227 TRIPLES
22 PREDICATES
94 URIs
78 LITERALS
13 BLANK NODES