Impact of Eucalyptus gall wasp,Leptocybe invasainfestation on growth and biomass production ofEucalyptus grandisandE. salignaseedlings in Tanzania

Petro, Revocatus; Madoffe, S. S.; Iddi, S.; Mugasha, Wilson Ancelm

doi:10.1080/09670874.2015.1039096

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…Tipping et al [8] observed that the damage caused by Lophodiplosis trifida Gagné (Diptera: cecidomyidae) reduced the height of Melaleuca seedlings by 10.1%, the LVV of leaves by 42%, the LVV of wood by 42.7%, and the LVV of roots by 30.3%. Petro et al [9] analyzed the effects of Tanzanian Leptocybe invasa infection on the growth and LVV of Eucalyptus grandis and eucalyptus. They discovered that the degree of the LVV loss in infected seedlings on the stems and leaves was significantly higher than that on the seedling roots, and the impact on the LVV of Eucalyptus grandis was higher than that of eucalyptus.…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing Detecting of Yellow Leaf Disease of Arecanut Based on UAV Multisource Sensors

et al. 2021

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Unmanned aerial vehicle (UAV) remote sensing technology can be used for fast and efficient monitoring of plant diseases and pests, but these techniques are qualitative expressions of plant diseases. However, the yellow leaf disease of arecanut in Hainan Province is similar to a plague, with an incidence rate of up to 90% in severely affected areas, and a qualitative expression is not conducive to the assessment of its severity and yield. Additionally, there exists a clear correlation between the damage caused by plant diseases and pests and the change in the living vegetation volume (LVV). However, the correlation between the severity of the yellow leaf disease of arecanut and LVV must be demonstrated through research. Therefore, this study aims to apply the multispectral data obtained by the UAV along with the high-resolution UAV remote sensing images to obtain five vegetation indexes such as the normalized difference vegetation index (NDVI), optimized soil adjusted vegetation index (OSAVI), leaf chlorophyll index (LCI), green normalized difference vegetation index (GNDVI), and normalized difference red edge (NDRE) index, and establish five algorithm models such as the back-propagation neural network (BPNN), decision tree, naïve Bayes, support vector machine (SVM), and k-nearest-neighbor classification to determine the severity of the yellow leaf disease of arecanut, which is expressed by the proportion of the yellowing area of a single areca crown (in percentage). The traditional qualitative expression of this disease is transformed into the quantitative expression of the yellow leaf disease of arecanut per plant. The results demonstrate that the classification accuracy of the test set of the BPNN algorithm and SVM algorithm is the highest, at 86.57% and 86.30%, respectively. Additionally, the UAV structure from motion technology is used to measure the LVV of a single areca tree and establish a model of the correlation between the LVV and the severity of the yellow leaf disease of arecanut. The results show that the relative root mean square error is between 34.763% and 39.324%. This study presents the novel quantitative expression of the severity of the yellow leaf disease of arecanut, along with the correlation between the LVV of areca and the severity of the yellow leaf disease of arecanut. Significant development is expected in the degree of integration of multispectral software and hardware, observation accuracy, and ease of use of UAVs owing to the rapid progress of spectral sensing technology and the image processing and analysis algorithms.

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Section: Introductionmentioning

confidence: 99%

Remote Sensing Detecting of Yellow Leaf Disease of Arecanut Based on UAV Multisource Sensors

et al. 2021

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“…It was recorded for the first time in Brazil in 2008, in the northeast of Bahia State. The wasp oviposition in leaves, young branches and petioles causing the formation of gall of several Eucalyptus species (MENDEL et al 2004;THU et al 2009;PETRO et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Oviposition of the Gall Wasp Leptocybe Invasa (Hymenoptera: Eulophidae) and Morphological Changes in Eucalyptus Spp. Genotypes Susceptible

Dantas

Aragão

Lisi

et al. 2021

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Oviposição de Leptocybe invasa (hymenoptera: eulophidae) e alterações morfológicas em eucalyptus spp. genótipos sensíveis. O eucalipto é cultivado em todo o mundo para diversos fins, como para a produção de madeira, lenha, celulose e óleos essenciais. O eucalipto foi introduzido no Brasil em 1904, e seu cultivo vem crescendo desde então, com cerca de 5,57 milhões de hectares de plantações em 2014. Esse aumento nas plantações favoreceu as populações de insetos nativos, alguns insetos se tornaram pragas, enquanto outras pragas de insetos exóticos foram introduzidos, como a vespa (Leptocybe invasa), que se deposita na nervura central das folhas, pecíolos e brotações jovens, causando a formação de galhas que comprometem o crescimento normal das plantas. Com o objetivo de avaliar as alterações morfológicas nos genótipos de Eucalyptus spp., causados pela formação de galhas, foi estudada a anatomia, qualitativa e quantitativamente dos feixes vasculares. Os resultados mostraram que a oviposição ocorreu nos 4 genótipos estudados, porém a formação de galhas não ocorreu no genótipo 1404, classificado como resistente, enquanto a suscetibilidade foi baixa no genótipo 1277, media no genótipo 1724 e muito alta no genótipo 1262. Os feixes vasculares e as células do parênquima nas folhas e pecíolos foram desorganizados. O surgimento de insetos adultos causou rupturas nas células vasculares, parênquima e epiderme, resultando em necrose e seca foliar.

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Assessment performance of Eucalyptus clones attacked by the recent invasion of Leptocybe invasa (Hymenoptera: Eulophidae): Implications to invasion pest management

Carvalho

Pinto

Sarmento

et al. 2022

Journal of Asia-Pacific Entomology

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Impact of Eucalyptus gall wasp,Leptocybe invasainfestation on growth and biomass production ofEucalyptus grandisandE. salignaseedlings in Tanzania

Cited by 4 publications

References 19 publications

Remote Sensing Detecting of Yellow Leaf Disease of Arecanut Based on UAV Multisource Sensors

Remote Sensing Detecting of Yellow Leaf Disease of Arecanut Based on UAV Multisource Sensors

Oviposition of the Gall Wasp Leptocybe Invasa (Hymenoptera: Eulophidae) and Morphological Changes in Eucalyptus Spp. Genotypes Susceptible

Assessment performance of Eucalyptus clones attacked by the recent invasion of Leptocybe invasa (Hymenoptera: Eulophidae): Implications to invasion pest management

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