Data/hora: 01/06/2024 08:28:20

Biblioteca(s): 	Embrapa Florestas; Embrapa Trigo.	
Data corrente: 	28/01/2020	
Data da última atualização: 	17/09/2020	
Autoria: 	LINS, E. A.; RODRIGUEZ, J. P. M.; SCOLOSKI, S. I.; PIVATO, J.; LIMA, M. B.; FERNANDES, J. M. C.; PEREIRA, P. R. V. da S.; LAU, D.; RIEDER, R.	
Afiliação: 	ELISON ALFEU LINS, University of Passo Fundo (UPF), Passo Fundo, Rio Grande do Sul, Brazil1; JOÃO PEDRO MAZUCO RODRIGUEZ, University of Passo Fundo (UPF), Passo Fundo, Rio Grande do Sul, Brazil; SANDY ISMAEL SCOLOSKI, University of Passo Fundo (UPF), Passo Fundo, Rio Grande do Sul, Brazil1; JULIANA PIVATO, The Brazilian Agricultural Research Corporation (Embrapa Wheat), Passo Fundo, Rio Grande do Sul, Brazil2; MARÍLIA BALOTIN LIMA, The Brazilian Agricultural Research Corporation (Embrapa Wheat), Passo Fundo, Rio Grande do Sul, Brazil2; JOSE MAURICIO CUNHA FERNANDES, CNPT; PAULO ROBERTO VALLE DA S PEREIRA, CNPF; DOUGLAS LAU, CNPT; RAFAEL RIEDER, University of Passo Fundo (UPF), Passo Fundo, Rio Grande do Sul, Brazil1.	
Título: 	A method for counting and classifying aphids using computer vision.	
Ano de publicação: 	2020	
Fonte/Imprenta: 	Computers and Electronics in Agriculture, n. 169, 2020.	
DOI: 	https://doi.org/10.1016/j.compag.2019.105200	
Idioma: 	Inglês	
Conteúdo: 	Aphids are insects that attack crops and cause damage directly, by consuming the sap of plants, and indirectly,by vectoring microorganisms that can cause diseases. Cereal crops are hosts for many aphid species, includingRhopalosiphumpadi(an economically important aphid species). Recording and classifying aphids are necessaryfor evaluating and predicting crop damage. Thus, serving as a basis for decision making on the utilization ofcontrolmeasures.Itcanalsobeusefultoevaluateplantresistancetoaphids.Traditionally,therecordingprocessis manual and depends on magnification and well-trained staff. The manual counting is also a time-consumingprocess and susceptible to errors. With this in mind, this paper presents a method and software to automate thecounting and classification ofRhopalosiphum padiusing image processing, computer vision, and machinelearningmethods.Thetextalsopresentsacomparisonofmanuallycountsfromexpertsandvaluesobtainedwiththe software, considering 40 samples. The results showed strong positive correlation in counting and classifi-cation(rs=0.92579)and measurement (r=0.9799).Concluding, thesoftware provedtobe reliableandusefulto aphid population monitoring studies.	
Palavras-Chave: 	Aphids; Counting.	
Thesaurus Nal: 	Classification; Computer vision; Measurement.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/209811/1/1-s2.0-S0168169919306039-main.pdf	
Registro original: 	Embrapa Trigo (CNPT)	
Exemplares: 	CNPT - (44850-1) - UPC - AP - DD -  -  -  - DIS
CNPF - (57403-1) - UPC - AP - DD -  -  -  - DIS