Title:	A method for counting and classifying aphids using computer vision.
Authors:	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.
Affiliation:	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.
Date Issued:	2020
Citation:	Computers and Electronics in Agriculture, n. 169, 2020.
Description:	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.
NAL Thesaurus:	Classification Computer vision Measurement
Keywords:	Aphids Counting
DOI:	https://doi.org/10.1016/j.compag.2019.105200
Type of Material:	Artigo de periódico
Access:	openAccess
Appears in Collections:	Artigo em periódico indexado (CNPT)