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Damage assessment and monitoring of the whitefly Bemisia tabaci MEAM1 (Hemiptera: Aleyrodidae) in soybean

Schutze, Inana Xavier

Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Escola Superior de Agricultura Luiz de Queiroz 2021-05-28

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  • Título:
    Damage assessment and monitoring of the whitefly Bemisia tabaci MEAM1 (Hemiptera: Aleyrodidae) in soybean
  • Autor: Schutze, Inana Xavier
  • Orientador: Yamamoto, Pedro Takao
  • Assuntos: Teor De Proteína; Glycine Max; Amostragem; Condições De Campo; Teor De Açúcares; Mosca-Branca; Sensoriamento Proximal; Sugar Content; Silverleaf Whitefly; Sampling; Protein Content; Hyperspectral Proximal Sensing; Field Conditions
  • Notas: Tese (Doutorado)
  • Descrição: In recent decades, Bemisia tabaci MEAM1 has become a serious pest for soybean in Brazil, causing direct and indirect damage, however, the population level that effectively causes productivity losses in soybean is not known. Bemisia tabaci reduced size and fast population growth make monitoring a challenge, and since whiteflies are sucking species, it is more difficult to measure the damage caused by this pest, so generally, the damage is indirectly inferred by yield losses. The goal here was to better understand how B. tabaci influences the soybean crop and to identify new approaches for improving the management of this pest. Temperature influences B. tabaci development affecting the lifecycle length, population size, and crop yield. An increase of 3° C in temperature affected the population density of B. tabaci. The higher temperature promoted a shorter lifecycle and, as consequence, more B. tabaci generations. Bemisia tabaci can cause yield losses of over a ton in a soybean field and, in temperatures around 25° C, it represented 30% of total production. A decrease of 33 g in the weight of thousand grains was also observed, and although no significant differences were observed among the grains\' vigor quality, estimated losses were up to 440 kg ha-1 in protein content. Monitoring insect pest populations in the fields is essential, but laborious and sometimes ineffective. The use of hyperspectral proximal sensing (PS) is a tool that allows the identification of arthropod-infested areas without contact with the plants. This optimizes the time spent on crop monitoring, important for large cultivation areas. The hyper-spectral PS was used to find differences in the responses obtained from B. tabaci soybean non-infested and infested leaves, with good accuracy by the responses of the bands related to photosynthesis and water content, which allowed us to discriminate the different levels of infestation and to separate healthy from whitefly infested soybean leaves based on their reflectance. Imprecise decision-making in an integrated pest management program may lead to ineffective control. Also, high infestation levels may diminish the photosynthetic activity of soybean, reducing their development and yield. An alternative to directly measuring the damage caused by B. tabaci is following how the insect feeding alters leaf chemical composition and photosynthesis of infested plants. Leaf chemical composition affects the performance of whiteflies. Plants with a higher level of sugars present better conditions for the development of B. tabaci, also reduction of the photosynthetic rate caused by whitefly infestation has been reported for many crops causing yield losses, associated with decreases in chlorophyll content. Correlation networks were created from data on sugar content, starch, and photosynthetic parameters connecting these factors to the number of nymphs. Bemisia tabaci feeding affected the plant\'s physiology and its interaction were reflected in part by the relationships among photosynthetic parameters as well as the levels of sugars and starch. The results found here are helpful for better understanding some conditions in which soybean is more vulnerable to B. tabaci, providing tools for improving the monitoring and control of this key pest.
  • DOI: 10.11606/T.11.2021.tde-05082021-113304
  • Editor: Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Escola Superior de Agricultura Luiz de Queiroz
  • Data de criação/publicação: 2021-05-28
  • Formato: Adobe PDF
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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