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Monitoring Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) Infestation in Soybean by Proximal Sensing.
Barros, Pedro P S; Schutze, Inana X; Iost Filho, Fernando H; Yamamoto, Pedro T; Fiorio, Peterson R; Demattê, José A M.
Afiliação
  • Barros PPS; Civil Engineering College, University Federal of Uberlândia, Monte Carmelo Campus, Monte Carmelo, Minas Gerais 38500-000, Brazil.
  • Schutze IX; Department of Entomology and Acarology, University of São Paulo, Piracicaba, São Paulo 13418-900, Brazil.
  • Iost Filho FH; Department of Entomology and Acarology, University of São Paulo, Piracicaba, São Paulo 13418-900, Brazil.
  • Yamamoto PT; Department of Entomology and Acarology, University of São Paulo, Piracicaba, São Paulo 13418-900, Brazil.
  • Fiorio PR; Department of Biosystems Engineering, University of São Paulo, Piracicaba, São Paulo 13418-900, Brazil.
  • Demattê JAM; Department of Soil Science, University of São Paulo, Piracicaba, São Paulo 13418-900, Brazil.
Insects ; 12(1)2021 Jan 09.
Article em En | MEDLINE | ID: mdl-33435312
Although monitoring insect pest populations in the fields is essential in crop management, it is still a laborious and sometimes ineffective process. Imprecise decision-making in an integrated pest management program may lead to ineffective control in infested areas or the excessive use of insecticides. In addition, high infestation levels may diminish the photosynthetic activity of soybean, reducing their development and yield. Therefore, we proposed that levels of infested soybean areas could be identified and classified in a field using hyperspectral proximal sensing. Thus, the goals of this study were to investigate and discriminate the reflectance characteristics of soybean non-infested and infested with Bemisia tabaci using hyperspectral sensing data. Therefore, cages were placed over soybean plants in a commercial field and artificial whitefly infestations were created. Later, samples of infested and non-infested soybean leaves were collected and transported to the laboratory to obtain the hyperspectral curves. The results allowed us to discriminate the different levels of infestation and to separate healthy from whitefly infested soybean leaves based on their reflectance. In conclusion, these results show that hyperspectral sensing can potentially be used to monitor whitefly populations in soybean fields.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Insects Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Insects Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Brasil País de publicação: Suíça