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52 results for “apple orchards”
Data for: Direct and indirect effects of management and landscape on biological pest control and crop pest infestation in apple orchards
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Predatory arthropod community composition in apple orchards: Orchard management, landscape structure and sampling method
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Data from: Assessing flower-visiting arthropod diversity in apple orchards through metabarcoding of environmental DNA from flowers and visual census
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Data from: Temporal snapshot of parasitoid wasp communities on three flowering plant species and implications for the regulation of the rosy apple aphid (Dysaphis plantaginea) in apple orchards
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Data for: Wild bee communities benefit from temporal complementarity of hedges and flower strips in apple orchards
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Enhancing ecosystem services in apple orchards: Nest boxes increase pest control by insectivorous birds
<p>Ecological intensification in croplands aims to enhance biodiversity-based ecosystem services, helping to increase yield while reducing agricultural environmental impacts. Identifying ecological intensification tools of wide applicability and easily implemented by farmers is, therefore, an imperative. Here, we verify the efficiency of provisioning artificial nest boxes for insectivorous birds to reinforce pest biological control in apple orchards.</p> <p>The study was conducted in 24 cider-apple orchards in Asturias (NW Spain) over three years. We compared the effect of insectivorous birds between orchards with and without nest boxes occupied by different bird species, through insectivory estimates based on attack on a sentinel pest and measurements of arthropod abundance in apple trees. We also identified preys that birds of different species captured to feed nestlings.</p> <p>Bird occupancy of nest boxes was widespread, ranging 25.0-33.3% each year. Great tit was the dominant species, followed by blue tit and, occasionally, common redstart.</p> <p>Predation pressure on apple pests increased in orchards with nest boxes, as judged by the increased proportion of sentinel models attacked by birds (34.9% increase in 2018 and 41.1% in 2019), decreased biomass of tree-dwelling arthropods (-51.7%) and reduced probability of apple pest occurrence (from 57 to 40%), compared to orchards without nest boxes.</p> <p>Nesting species showed different predatory roles in apple orchards. Fewer attacks on sentinel pests but lower arthropod biomass was associated with blue tit rather than great tit. Besides, blue tit fed nestlings at a faster rate and included in their diet a higher proportion of apple pests than great tit, which preyed mostly on other herbivorous insects.</p> <p>Synthesis and applications. We demonstrated the usefulness of nest boxes for insectivorous birds in enhancing biological control of apple pests at a regional scale, identifying tit species as complementary predators of apple pests and herbivores. From the farmers' perspective, providing nest boxes in orchards may represent an efficient, easy to implement, cheap and attractive measure of ecological intensification, compatible with other actions fostering biodiversity in croplands.</p>
Data from: The challenge of accurately documenting bee species richness in agroecosystems: bee diversity in eastern apple orchards
Bees are important pollinators of agricultural crops, and bee diversity has been shown to be closely associated with pollination, a valuable ecosystem service. Higher functional diversity and species richness of bees have been shown to lead to higher crop yield. Bees simultaneously represent a mega-diverse taxon that is extremely challenging to sample thoroughly and an important group to understand because of pollination services. We sampled bees visiting apple blossoms in 28 orchards over 6 years. We used species rarefaction analyses to test for the completeness of sampling and the relationship between species richness and sampling effort, orchard size, and percent agriculture in the surrounding landscape. We performed more than 190 h of sampling, collecting 11,219 specimens representing 104 species. Despite the sampling intensity, we captured <75% of expected species richness at more than half of the sites. For most of these, the variation in bee community composition between years was greater than among sites. Species richness was influenced by percent agriculture, orchard size, and sampling effort, but we found no factors explaining the difference between observed and expected species richness. Competition between honeybees and wild bees did not appear to be a factor, as we found no correlation between honeybee and wild bee abundance. Our study shows that the pollinator fauna of agroecosystems can be diverse and challenging to thoroughly sample. We demonstrate that there is high temporal variation in community composition and that sites vary widely in the sampling effort required to fully describe their diversity. In order to maximize pollination services provided by wild bee species, we must first accurately estimate species richness. For researchers interested in providing this estimate, we recommend multiyear studies and rarefaction analyses to quantify the gap between observed and expected species richness.
Data from: Effectiveness of vole control by owls in apple orchards
1. Biological pest control is gaining greater acceptance as an important part of integrated pest management for sustainable agriculture. However, knowledge regarding biological control of rodent pests is limited, and its effectiveness in temperate areas has not been quantified. In traditional Japanese apple orchards, the Ural owl Strix uralensis breeds in tree hollows and preys on the Japanese field vole Microtus montebelli, a native pest species that can harm fruit production. In this study, we hypothesized that the Ural owl, a generalist predator, can act as a biological control agent by reducing vole densities in temperate orchards. 2. To quantify the pest control effects of breeding Ural owls, we first analysed the diet of individual owls nesting in apple tree hollows. Second, we installed nest boxes in orchards to attract breeding owl pairs and collected data on vole population changes around owl nests to compare with control areas. The population changes were analysed using a generalised linear mixed model to assess the effect of breeding owls within their breeding territory. The model took into account seasonal fluctuations in vole population size as well as surrounding land-use. We also examined vole populations around the owl nests in April, and the distance between nests and forested areas, to determine if these variables influenced nest site selection. 3. The primary prey of Ural owls breeding in orchards was voles, and the owls reduced vole populations within their estimated breeding territories by 63% (± SE: 53%–70%) compared with the predicted density without owls. Owls preferred to nest in orchards with higher vole population densities in April. Our findings also indicate that higher occupancy rates are possible by distributing nest boxes based on Ural owl breeding territory size (306 m radius circle in our study). 4. Synthesis and applications. As breeding Ural owls provided significant pest control effects within their breeding territories, the re-introduction of breeding Ural owl pairs within orchards will contribute to rodent pest control. Promoting the reproduction of native raptors in agricultural areas can be an option for developing integrated pest management while simultaneously maintaining regional biodiversity.04-Oct-2018
FIGURES 36–41. Ologamasus spp., microphotographs. 36 in Two new species of the genus Ologamasus (Ologamasidae) from apple orchards in southern Brazil
FIGURES 36–41. Ologamasus spp., microphotographs. 36. Ologamasus margaridae, adult male, leg II, tibial spur and similar structure on tarsus; 37. Ologamasus tuberculatus, protonymph, dorsal pore gd4; 38. Ologamasus tuberculatus, deutonymph, podonotal shield and pore gd4; 39. Ologamasus tuberculatus, deutonymph, opisthonotal shield and pore gd9; 40. Ologamasus tuberculatus, adult female, dorsal pore gd4 pore; 41. Ologamasus tuberculatus, adult female, dorsal pore gd9.
FIGURES 32–35. Ologamasus tuberculatus n in Two new species of the genus Ologamasus (Ologamasidae) from apple orchards in southern Brazil
FIGURES 32–35. Ologamasus tuberculatus n. sp. Adult male. 32. Dorsal idiosoma; 33. Ventral idiosoma; 34. Lateral view of leg II; 35. Chelicera.
FIGURES 23–26. Ologamasus tuberculatus n in Two new species of the genus Ologamasus (Ologamasidae) from apple orchards in southern Brazil
FIGURES 23–26. Ologamasus tuberculatus n. sp. Deutonymph. 23. Dorsal idiosoma; 24. Ventral idiosoma; 25. Epistome; 26. Chelicera.
FIGURES 7–12. Ologamasus margaridae n in Two new species of the genus Ologamasus (Ologamasidae) from apple orchards in southern Brazil
FIGURES 7–12. Ologamasus margaridae n. sp. Adult female. 7. Dorsal idiosoma; 8. Ventral idiosoma; 9. Tritosternum; 10. Epistome; 11. Chelicera; 12. Palp.
FIGURES 13–17. Ologamasus margaridae n in Two new species of the genus Ologamasus (Ologamasidae) from apple orchards in southern Brazil
FIGURES 13–17. Ologamasus margaridae n. sp. Adult male. 13. Dorsal idiosoma; 14. Ventral idiosoma; 15. Leg II; 16. Chelicera; 17. Ventral view of palp.
FIGURES 27–31. Ologamasus tuberculatus n in Two new species of the genus Ologamasus (Ologamasidae) from apple orchards in southern Brazil
FIGURES 27–31. Ologamasus tuberculatus n. sp. Adult female. 27. Dorsal idiosoma; 28. Ventral idiosoma; 29. Epistome; 30. Chelicera; 31. Palp.
FIGURES 18–22. Ologamasus tuberculatus n in Two new species of the genus Ologamasus (Ologamasidae) from apple orchards in southern Brazil
FIGURES 18–22. Ologamasus tuberculatus n. sp. Protonymph. 18. Dorsal idiosoma; 19. Ventral idiosoma; 20. Epistome; 21. Palp genu; 22. Chelicera.
FIGURES 3–6. Ologamasus margaridae n in Two new species of the genus Ologamasus (Ologamasidae) from apple orchards in southern Brazil
FIGURES 3–6. Ologamasus margaridae n. sp. Deutonymph. 3. Dorsal idiosoma; 4. Ventral idiosoma; 5. Tritosternum; 6. Chelicera.
Combined effects of insecticide and IGP on native and invasive ladybeetles in apple orchard
<p>Raw data on the comparison of the combined effects of Rimon and IGP on two ladybeetle species</p>
Vineyard and Apple Orchard Suitability Maps for Mountainous Areas (Southern Pyrenees and Pre-Pyrenees)
<p>The manuscript related to this dataset can be consulted trought:</p> <p>The layers available in this dataset are in EPSG: WGS84.</p> <ul> <li><strong>Indicators</strong> <ul> <li><strong>BBL.tif </strong>- Hydrothermic index of Branas, Bernon, Levadoux (ºC*mm)</li> <li><strong>CDls.tif </strong>- Cold Days late spring (days)</li> <li><strong>FRea.tif </strong>- Frost Risk early autumn (days)</li> <li><strong>FRls_vineyard.tif </strong>- Frost Risk late spring vineyard (days)</li> <li><strong>FRls_apple.tif </strong>- Frost Risk late spring apple orchard (days)</li> <li><strong>GDD.tif</strong> - Growing Degree Days (ºC)</li> <li><strong>GSP.tif </strong>- Growing Season Precipitation (mm)</li> <li><strong>GST.tif </strong>- Growing Season Temperature (ºC)</li> <li><strong>Ha</strong><strong>.tif </strong>- Hail (days)</li> <li><strong>HI</strong><strong>.tif </strong>- Heliothermal Index of Huglin (ºC)</li> <li><strong>NCIr</strong><strong>.tif </strong>- Night Cool Index ripenning (ºC)</li> <li><strong>NHN.tif</strong> - Need Hydric Needs (mm/year)</li> <li><strong>SHDr.tif </strong>- Stressful Hot Days ripening (days)</li> <li><strong>WI.tif </strong>- Winkler Index (ºC)</li> <li><strong>CaCO3.tif </strong>- Calcium Carbonates (%)</li> <li><strong>CEC.tif </strong>- Cation Exchange Capacity (cmol/kg)</li> <li><strong>pH.tif </strong>- pH</li> <li><strong>SD.tif </strong>- Soil Depth (cm)</li> <li><strong>TAW.tif</strong> - Total Available Water (mm)</li> <li><strong>Te.tif</strong> - Texture</li> <li><strong>TOC.tif </strong>- Topsoil Organic Carbon (%)</li> <li><strong>As.tif </strong>- Aspect</li> <li><strong>GSR.tif </strong>- Growing season Solar Radiation (kWh/m2)</li> <li><strong>Sl.tif </strong>- Slope (%)</li> </ul> </li> </ul> <ul> <li><strong>Indicators_Suitability</strong> <ul> <li><strong>BBL_suitability.tif </strong>- Hydrothermic index of Branas, Bernon, Levadoux (ºC*mm)</li> <li><strong>CDls_suitability.tif </strong>- Cold Days late spring (days)</li> <li><strong>FRea_suitability.tif </strong>- Frost Risk early autumn (days)</li> <li><strong>FRls_vineyard_suitability.tif </strong>- Frost Risk late spring vineyard (days)</li> <li><strong>FRls_apple_suitability.tif </strong>- Frost Risk late spring apple orchard (days)</li> <li><strong>GDD_suitability.tif</strong> - Growing Degree Days (ºC)</li> <li><strong>GSP_suitability.tif </strong>- Growing Season Precipitation (mm)</li> <li><strong>GST_suitability.tif </strong>- Growing Season Temperature (ºC)</li> <li><strong>Ha_suitability</strong><strong>.tif </strong>- Hail (days)</li> <li><strong>HI_suitability</strong><strong>.tif </strong>- Heliothermal Index of Huglin (ºC)</li> <li><strong>NCIr_suitability</strong><strong>.tif </strong>- Night Cool Index ripenning (ºC)</li> <li><strong>NHN_suitability.tif</strong> - Need Hydric Needs (mm/year)</li> <li><strong>SHDr_suitability.tif </strong>- Stressful Hot Days ripening (days)</li> <li><strong>WI_suitabilitytif</strong> - Winkler Index (ºC)</li> <li><strong>CaCO3_suitability.tif </strong>- Calcium Carbonates (%)</li> <li><strong>CEC_suitability.tif </strong>- Cation Exchange Capacity (cmol/kg)</li> <li><strong>pH_suitability.tif </strong>- pH</li> <li><strong>SD_suitability.tif </strong>- Soil Depth (cm)</li> <li><strong>TAW_suitability.tif</strong> - Total Available Water (mm)</li> <li><strong>Te_suitability.tif</strong> - Texture</li> <li><strong>TOC_suitability.tif </strong>- Topsoil Organic Carbon (%)</li> <li><strong>As_suitability.tif </strong>- Aspect</li> <li><strong>GSR_suitability.tif </strong>- Growing season Solar Radiation (kWh/m2)</li> <li><strong>Sl_suitability.tif </strong>- Slope (%)</li> </ul> </li> </ul> <ul> <li><strong>Suitability</strong> <ul> <li><strong>Vineyard_suitability.tif </strong>- Vineyard Suitability map (Minumum Suitability 0 - 100 Maximum Suitability)</li> <li><strong>Apple_orchard_suitability.tif </strong>- Apple Orchard Suitability map (Minumum Suitability 0 - 100 Maximum Suitability) </li> </ul> </li> </ul>
Proximity to natural habitat and flower plantings increases insect populations and pollination services in South African apple orchards
<p><span><span><span><span><span><span><span><span><span><span><span>Introducing areas of wildflower vegetation within crop fields has been shown to enhance pollinator activity and pollination services to crops, and findings in Europe showed an interaction effect between floral treatments and landscape context. Natural fynbos patches in the South African Cape Floristic Region (CFR) are potential reservoirs for beneficial insects that could enhance pollinator populations and crop pollination in commercial apple orchards. However, the effect of proximity to natural habitat and floral enhancement treatments on crop pollinators and yield are yet to be fully tested in southern temperate regions.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>To elucidate the impact of enhanced floral resources to apple flower visitors and crop yield, we established small experimental patches of flowers in non-productive areas of commercial apple (<i>Malus domestica</i>) orchards in the CFR. Experimental orchards were embedded in landscapes with varying proportions of natural habitat within 1 km. We used pollinator exclusion experiments to determine the benefits of insect pollination on apple yield, quality and economic value. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>We found that the primary pollinators of apple flowers in the region is the endemic Cape honey bee<i>, Apis mellifera capensis</i>. Floral plantings enhanced overall pollinator abundance and honey bee flower visitation within the orchards, and positively affected apple size and economic value. Increased landscape complexity had a significantly positive effect on wild bees but not on honey bees. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><i>Synthesis and applications</i>. We demonstrate that presence of floral plantings within orchards enhances pollinator activity within apple orchards and apple quality. This sustainable management practice may represent a profitable choice for growers, which could increase pollination services while reducing reliance on renting hives. These practices can indirectly contribute to increased landscape-scale resilience and connectivity, while also benefiting pollinators within the remaining natural habitat.</span></span></span></span></span></span></span></span></span></span></span></p>
Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms - SensitivityAnalysis
<p>The dataset "Sensitivity Analysis" consists of image sequences (videos) for apple detection and tracking and its corresponding ground truth. The ground truth is presented in MOT format. This dataset is part of the paper:</p> <p>Villacrés, J., Viscaino, M., Delpiano, J., Vougioukas, S. & Cheein, F. A. (2022). Apple orchard production estimation using deep learning strategies: a comparison of tracking-by-detection algorithms. <em>Computers and Electronics in Agriculture</em>.</p> <p>The article is currently accepted. For a better reference format, please refer to the journal's official website.</p> <p>If you have used the material presented in this data set, please cite the previous article.</p> <p>For more information regarding the dataset, please refer to the paper mentioned below.</p>
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