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dc.date.available
2024-03-22T10:04:35Z  
dc.identifier.citation
Martinez Von Ellrichshausen, Andres Santiago; Masciocchi, Maité; (2024): Wasp entry and exit from the nest recorded by automatic detection. Consejo Nacional de Investigaciones Científicas y Técnicas. (dataset). http://hdl.handle.net/11336/231233  
dc.identifier.uri
http://hdl.handle.net/11336/231233  
dc.description.abstract
1.We describe the development and validation of an autonomous monitoring station that identifies and records the movement of social insects into and out of the colony. 2.The hardware consists of an illuminated channel and a fixed camera to capture the wasps' activities. An ad-hoc post-processing software was developed to identify the direction of movement and caste of the recorded individuals. 3.Validation results indicate that the model can recognize the direction of movement of wasps and identifying workers and drones with higher accuracy than gynes. Further development of the software and hardware should enable higher levels of accuracy. 4.This innovative tool holds immense potential for advancing ecological and behavioural research by providing researchers with rapid and easily accessible data. 5.Understanding the activity patterns of individual wasps within the colony can yield valuable insights into factors influencing their growth, foraging patterns, and the behaviour of reproductive individuals. Ultimately, this information can be incorporated into effective management plans for controlling harmful social insect populations in both ecological and productive systems.  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.title
Wasp entry and exit from the nest recorded by automatic detection  
dc.type
dataset  
dc.date.updated
2024-03-21T14:30:26Z  
dc.description.fil
Fil: Martinez Von Ellrichshausen, Andres Santiago. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina  
dc.description.fil
Fil: Masciocchi, Maité. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina  
dc.datacite.PublicationYear
2024  
dc.datacite.Creator
Martinez Von Ellrichshausen, Andres Santiago  
dc.datacite.Creator
Masciocchi, Maité  
dc.datacite.affiliation
Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche  
dc.datacite.affiliation
Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche  
dc.datacite.publisher
Consejo Nacional de Investigaciones Científicas y Técnicas  
dc.datacite.subject
Ecología  
dc.datacite.subject
Ciencias Biológicas  
dc.datacite.subject
CIENCIAS NATURALES Y EXACTAS  
dc.datacite.date
17/03/2023-10/06/2023  
dc.datacite.DateType
Creado  
dc.datacite.language
eng  
dc.datacite.version
1.0  
dc.datacite.description
1.We describe the development and validation of an autonomous monitoring station that identifies and records the movement of social insects into and out of the colony. 2.The hardware consists of an illuminated channel and a fixed camera to capture the wasps' activities. An ad-hoc post-processing software was developed to identify the direction of movement and caste of the recorded individuals. 3.Validation results indicate that the model can recognize the direction of movement of wasps and identifying workers and drones with higher accuracy than gynes. Further development of the software and hardware should enable higher levels of accuracy. 4.This innovative tool holds immense potential for advancing ecological and behavioural research by providing researchers with rapid and easily accessible data. 5.Understanding the activity patterns of individual wasps within the colony can yield valuable insights into factors influencing their growth, foraging patterns, and the behaviour of reproductive individuals. Ultimately, this information can be incorporated into effective management plans for controlling harmful social insect populations in both ecological and productive systems.  
dc.datacite.DescriptionType
Métodos  
dc.datacite.FundingReference
PICT 2018-657  
dc.datacite.FunderName
Ministerio de Ciencia. Tecnología e Innovación Productiva. Agencia Nacional de Promoción Científica y Tecnológica  
dc.subject.keyword
monitoreo  
dc.subject.keyword
avispa social  
dc.subject.keyword
plaga  
dc.subject.keyword
machine learning  
dc.datacite.resourceTypeGeneral
dataset  
dc.conicet.datoinvestigacionid
14778  
dc.datacite.awardTitle
PICT 2018-657  
dc.datacite.geolocation
San Carlos de Bariloche  
dc.datacite.formatedDate
2023