Does natural vegetation from olive groves benefit the olive moth, Prays oleae ?

2021 ◽  
Author(s):  
Anabela Nave ◽  
Fátima Gonçalves ◽  
Irene Oliveira ◽  
Mercedes Campos ◽  
Laura Torres
Keyword(s):  
Natural Vegetation ◽  
Prays Oleae ◽  
Olive Groves

scholarly journals Land-Use Effect on Olive Groves Pest Prays oleae and on Its Potential Biocontrol Agent Chrysoperla carnea

Insects ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 46
Author(s):  
João Frederico Alves ◽  
Sara Mendes ◽  
António Alves da Silva ◽  
José Paulo Sousa ◽  
Daniel Paredes
Keyword(s):  
Biological Control ◽  
Land Use ◽  
Biological Control Agent ◽  
Control Agent ◽  
Agricultural Landscapes ◽  
Chrysoperla Carnea ◽  
Land Uses ◽  
Prays Oleae ◽  
Potential Biocontrol Agent ◽  
Olive Groves

Olive growing has been intensified through the simplification of agricultural landscapes. In order to rethink the environmental drawbacks of these practices, conservation biological control techniques have been examined. In this work, Prays oleae and its natural enemy Chrysoperla carnea were monitored to account for the effects of the amount and diversity of different land-uses. We found that C. carnea showed an attraction to areas with high abundances of P. oleae but this predator did not display any affection by the different land-uses. Inversely, P. oleae abundance was lower in diverse landscapes and higher in simplified ones. Importantly, higher abundances of C. carnea were related to lower infestation levels of P. oleae in the late part of the season. These results corroborate the attraction of C. carnea to the olive moth, highlighting the potential of C. carnea as a biological control agent of this pest, assert that the promotion of land-use diversity can reduce P. oleae and confirm that landscapes dominated by olive groves can promote this pest. The present study aims at contributing to the discussion about the management of agricultural ecosystems by providing farmers with sustainable alternatives that do not have harmful effects on the environment and public health.

scholarly journals Landscape composition and configuration affect the abundance of the olive moth (Prays oleae, Bernard) in olive groves

2020 ◽  
Vol 294 ◽  
pp. 106854
Author(s):  
María Villa ◽  
Sónia A.P. Santos ◽  
José Paulo Sousa ◽  
Alberto Ferreira ◽  
Pedro Martins da Silva ◽  
...  
Keyword(s):  
Landscape Composition ◽  
Prays Oleae ◽  
Olive Groves ◽  
Landscape Composition And Configuration

scholarly journals Hidden Genetic Variability, Can the Olive Moth Prays oleae (Lepidoptera: Yponomeutidae or Praydidae?) be a Species’ Complex?

Insects ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 204
Author(s):  
Marlon Pazian ◽  
Tânia Nobre ◽  
Imen Blibech ◽  
Fernando T Rei
Keyword(s):  
Cytochrome C ◽  
Cytochrome C Oxidase ◽  
Nadh Dehydrogenase ◽  
Environmental Changes ◽  
Haplotype Network ◽  
Nadh Dehydrogenase Subunit ◽  
Prays Oleae ◽  
Oxidase Subunit ◽  
Important Pest ◽  
Olive Groves

Prays oleae is the second most important pest in Mediterranean olive groves, causing substantial damage on olive production. We used mitochondrial [cytochrome c oxidase subunit I (COI), and NADH dehydrogenase subunit 5 (nad5)] and nuclear [ribosomal protein S5 (RpS5)] amplicons to assess the population variability in five main olive producing regions from Tunisia, to support or dismiss the existence of two non-monophyletic groups within the species, as found within Portugal. Our phylogenetic analysis with cytochrome c oxidase subunit I (COI) indeed displayed two distinct and well-supported clades of P. oleae, which were corroborated by the haplotype network reconstructed with both mitochondrial and nuclear amplicons. We were also able to dismiss the hypothesis that one of the clades would not develop on olive fruits. No correlation was observed between clades differentiation and geographic distribution. The existence of cryptic species can impact on the management of agroecosystems and on the perception of how these moths responds to environmental changes.

scholarly journals Mating Disruption of the Olive Moth Prays oleae (Bernard) in Olive Groves Using Aerosol Dispensers

Insects ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1113
Author(s):  
Antonio Ortiz ◽  
Andrés Porras ◽  
Jordi Marti ◽  
Antonio Tudela ◽  
Álvaro Rodríguez-González ◽  
...  
Keyword(s):  
Mating Disruption ◽  
Pheromone Trap ◽  
Field Trials ◽  
Prays Oleae ◽  
The Third ◽  
Olive Groves ◽  
The Mean ◽  
Fruit Damage ◽  
Trap Catches ◽  
Number Of Males

The olive moth (OM), Prays oleae (Bern.) (Lepidoptera: Yponomeutidae), is a major olive grove pest worldwide; however, until now, very few studies have investigated the effectiveness of mating disruption (MD) techniques against this pest. Experiments were carried out for two successive years (2019 and 2020) in three different olive groves in Andalucía (Southern Spain) to evaluate mating disruption’s efficacy in controlling the OM from the first to the third generation. The effectiveness of MD formulations against the three generations of OM was assessed by determining the percentage of infested olive fruits, the reduction of pheromone trap catches, and the number of affected inflorescences in both MD-treated and untreated control olive groves. The number of release points (one or two aerosol devices per ha) was also evaluated. In all years and trials, the mean number of males caught in traps placed in the MD-treated plots was significantly lower than untreated sites. Mating disruption registered a high suppression of male captures (>75%) in treated plots for two consecutive seasons. Concerning infested olive fruits, substantial reductions (about 80%) were observed in the MD plots of locations B and C, and a reduction of about 40% was detected in location A, compared to the control plot. Results showed that the installation of two aerosol devices/ha reduced fruit damage below 20% of infested olive fruits except for one site where a reduction of about 71% in the MD plot was recorded in 2019. Although few significant differences were associated with OM male catches and infested olive fruits between plots treated with one aerosol/ha and two aerosols/ha in most of the comparisons, significant differences in the number of olive inflorescences infested by P. oleae were found, suggesting a similar performance between the two tested aerosol densities. Results of two-year field trials in Andalucía demonstrated the potential of Mister P X841 aerosol devices as an effective tool for controlling the olive moth, P. oleae.

scholarly journals Do non-crop areas and landscape structure influence dispersal and population densities of male olive moth?

2020 ◽  
Vol 111 (1) ◽  
pp. 73-81
Author(s):  
María Villa ◽  
Sónia A. P. Santos ◽  
Susana Pascual ◽  
José Alberto Pereira
Keyword(s):  
Landscape Structure ◽  
Pollen Grains ◽  
Olive Grove ◽  
Population Densities ◽  
Prays Oleae ◽  
Three Generations ◽  
Olive Groves

AbstractThe permeability of the crop surroundings to pests and the landscape structure can influence pest dispersal between crop patches as well as its abundance within the crop. In this work, we analyzed the dispersal of the olive moth Prays oleae (Bernard) throughout the olive grove surroundings and their abundance within the crop following three approaches: (i) pollen grains settled on bodies of olive moths collected in olive groves were identified and compared with flora occurring on the surrounding patches; (ii) the capability of P. oleae males to penetrate non-crop patches was analyzed (iii) the effect of the landscape structure on the abundance of the three generations of the olive moth was studied. Pollen grains of scrubs and other trees occurring in the crop surroundings, such as Cistus sp., Quercus sp., Juniperus-type or Pinaceae were identified on P. oleae bodies suggesting that P. oleae penetrates into non-crop habitats. Additionally, woody and, to a lesser degree, herbaceous patches, did not constitute barriers for P. oleae. Finally, more complex and heterogeneous patches presented lower numbers of captures of P. oleae. These results give new insights into the movements of the olive moth in the olive grove surroundings and suggest that the management of non-crop areas could influence this pest abundance.

VEMAP 1: U.S. POTENTIAL NATURAL VEGETATION

1998 ◽  
Author(s):  
C. DALY ◽  
H. H. FISHER ◽  
A. GRIMSDELL ◽  
E. R. HUNT ◽  
T. G. F. KITTEL ◽  
...  
Keyword(s):  
Natural Vegetation ◽  
Potential Natural Vegetation

Organic farming promotes arthropod predators, but this depends on neighbouring patches of natural vegetation

2021 ◽  
Vol 310 ◽  
pp. 107295
Author(s):  
Alistair D. Galloway ◽  
Colleen L. Seymour ◽  
Rene Gaigher ◽  
James S. Pryke
Keyword(s):  
Organic Farming ◽  
Natural Vegetation ◽  
Arthropod Predators

scholarly journals Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

2020 ◽  
Vol 13 (1) ◽  
pp. 14
Author(s):  
Annamaria Castrignanò ◽  
Antonella Belmonte ◽  
Ilaria Antelmi ◽  
Ruggiero Quarto ◽  
Francesco Quarto ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Early Detection ◽  
Plant Pathogens ◽  
Early Stage ◽  
Xylella Fastidiosa ◽  
Mediterranean Countries ◽  
Parametric Classification ◽  
Aerial Vehicle ◽  
Olive Groves ◽  
Olive Trees

Xylella fastidiosa subsp. pauca (Xfp) is one of the most dangerous plant pathogens in the world. Identified in 2013 in olive trees in south–eastern Italy, it is spreading to the Mediterranean countries. The bacterium is transmitted by insects that feed on sap, and causes rapid wilting in olive trees. The paper explores the use of Unmanned Aerial Vehicle (UAV) in combination with a multispectral radiometer for early detection of infection. The study was carried out in three olive groves in the Apulia region (Italy) and involved four drone flights from 2017 to 2019. To classify Xfp severity level in olive trees at an early stage, a combined method of geostatistics and discriminant analysis was implemented. The results of cross-validation for the non-parametric classification method were of overall accuracy = 0.69, mean error rate = 0.31, and for the early detection class of accuracy 0.77 and misclassification probability 0.23. The results are promising and encourage the application of UAV technology for the early detection of Xfp infection.

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