Nutrição e vigor de mudas de cafeeiro e infestação por bicho mineiro

Caixeta, Sérgio Luiz; Martínez, Herminia; Picanço, Marcelo Coutinho; Cecon, Paulo Roberto; Esposti, Marlon Dutra Degli; Amaral, José Francisco Teixeira do

doi:10.1590/s0103-84782004000500016

Cited by 4 publications

(2 citation statements)

References 10 publications

(8 reference statements)

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“…Coffee leaf damage caused by leaf miners reduces leaf area and causes leaf fall, thereby decreasing photosynthetic activity and productivity 50 . Larger leaf areas and greater numbers of leaves reduce leaf miner infestation 51 . In the present study, thiamethoxam was very effective in controlling leaf miner populations even at the lowest concentration tested, which prevented the establishment of significant infestations.…”

Section: Discussionsupporting

confidence: 43%

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The effects of thiamethoxam on coffee seedling morphophysiology and Neotropical leaf miner (Leucoptera coffeella) infestations

Leite

Guedes

Costa

et al. 2022

Pest Management Science

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BACKGROUND: Coffee (Coffea arabica L.) is one of the main commodities produced in Brazil. Insecticides like the (systemic) neonicotinoid thiamethoxam are widely used to suppress pest populations during coffee production, in particular the Neotropical leaf miner (Leucoptera coffeella Guérin-Mèneville & Perrottet, 1842) (Lepidoptera: Lyonetiidae). In addition to its efficacy against this pest species, thiamethoxam is also thought to be a bioactivator of plant metabolism, but has not yet been tested for such activity. Thus, the objectives of the present study were (1) to assess the concentration-response effects of thiamethoxam on the vegetative vigor of coffee seedlings (C. arabica 'Catuaí 144' cultivar) at different concentrations [2, 20, 40, 80 and 200 mg active ingredient (a.i.) kg −1 ] applied via soil drenching and (2) to evaluate if the plant response interferes with the effectiveness of thiamethoxam in controlling leaf miner populations. The morphophysiological traits of the coffee seedlings were evaluated 20, 40, 60 and 80 days after application, and leaf miner infestations were recorded starting 20 days after the insecticide application with the releasing of adults, and every 20 days afterwards. RESULTS:The results indicated that thiamethoxam has a deleterious effect on the morphophysiological traits of the plants compromising their development with increase in concentrations. However, leaf area exhibited a different pattern with a peak at 50 mg a.i. kg −1 consistent with thiamethoxam-induced hormesis (i.e. biphasic response with stimulatory effect at sublethal range of a toxic substance at the higher concentration). Nonetheless, such bioactivator effect did not affect thiamethoxan effectiveness against the leaf miner even at the lowest concentration tested. CONCLUSION: Thiamethoxan exhibited bioactivation effect on leaf at low concentration, but without compromising efficacy against leaf miner populations. Therefore, its proposed metabolism-boosting properties may encourage the unnecessary use of this insecticide, potentially leading to higher selection for insecticide resistance and an eventual decline in its effectiveness against the Neotropical leaf miner.

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Section: Discussionsupporting

confidence: 43%

“…50 Larger leaf areas and greater numbers of leaves reduce leaf miner infestation. 51 In the present study, thiamethoxam was very effective in controlling leaf miner populations even at the lowest concentration tested, which prevented the establishment of significant infestations.…”

Section: Discussionmentioning

confidence: 45%

The effects of thiamethoxam on coffee seedling morphophysiology and Neotropical leaf miner (Leucoptera coffeella) infestations

Leite

Guedes

Costa

et al. 2022

Pest Management Science

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Machine learning algorithms for forecasting the incidence of Coffea arabica pests and diseases

Aparecido¹,

Rolim

Moraes³

et al. 2020

Int J Biometeorol

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Geostatistical analysis of the spatial variation of the berry borer and leaf miner in a coffee agroecosystem

et al. 2009

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The advent of geostatistics and geographical information systems has made it possible to analyze complex spatial patterns of ecological phenomena over large areas in applied insect ecology and pest management. The objective of this study was to use geostatistics to characterize the spatial structure and map the spatial variation of damage caused by the berry borer (Hypothenemus hampei) and leaf miner (Leucoptera coffeella) in a coffee agroecosystem planted with the cultivar Catuai Vermelho IAC-99. Infestations of berry borer and leaf miner were evaluated in fruits and leaves, respectively. The pests were monitored at 67 georeferenced points in an area of 6.6 ha in 2005, 2006 and 2007. Variograms estimated by the method of moments (MoM) and residual maximum likelihood REML were compared. The latter were generally better in terms of the kriging error coefficients. Spherical variograms estimated by REML for berry borer infestation in fruits had ranges of spatial dependence of 34.62-118.4 m and for the leaf miner they were 53.93-133.7 m. For models fitted by weighted ordinary least squares (OLS) to the MoM experimental variogram, the ranges varied between 37.22 and 68.67 m for the berry borer and 100 and 155.4 m for leaf miner infestation. The variogram model parameters were used with the data for ordinary kriging to map the spatial variation of coffee pests for different monitoring periods. If there was no suitable variogram, inverse distance weighting was used to map the variation. The maps enabled visualization of the intensity of infestation of the insect pests for the different periods evaluated.

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Nutrição e vigor de mudas de cafeeiro e infestação por bicho mineiro

Cited by 4 publications

References 10 publications

The effects of thiamethoxam on coffee seedling morphophysiology and Neotropical leaf miner (Leucoptera coffeella) infestations

The effects of thiamethoxam on coffee seedling morphophysiology and Neotropical leaf miner (Leucoptera coffeella) infestations

Machine learning algorithms for forecasting the incidence of Coffea arabica pests and diseases

Geostatistical analysis of the spatial variation of the berry borer and leaf miner in a coffee agroecosystem

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