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235 results for “orchards”
Data from: Using semidefinite programming to optimize unequal deployment of genotypes to a clonal seed orchard
Tree breeders must often consider the conservation of genetic diversity, while at the same time, maximizing response to selection. In the case of seed orchards, the buyer of seed wants maximum performance, while satisfying a restriction, sometimes legislated, on the diversity deployed to the forest. Optimal selection will not completely avoid kinship but rather maximize gain while imposing a constraint on average relatedness. Here, we present the application of semidefinite programming (SDP) as a flexible approach to optimize the deployment of genotypes to a clonal seed orchard. We formulate the selection problem as an SDP, where average breeding value is to be maximized, while imposing constraints on relatedness, as well as maximum and minimum contributions from each candidate. An open-source solver, SDPA, was embedded into a tool designed to make the optimization of seed orchards by SDP simple and flexible. Case studies optimizing seed orchards for Scots pine and loblolly pine illustrate how this flexibility can be used to impose additional constraints on the scion material available from some candidate genotypes and optimize selection even when related candidates have varying degrees of coancestry among them. Additional situations where SDP can be employed are discussed.
Data from: Genetic diversity and structure of Lolium perenne ssp. multiflorum in California vineyards and orchards indicates potential for spread of herbicide resistance via gene flow
Management of agroecosystems with herbicides imposes strong selection pressures on weedy plants leading to the evolution of resistance against those herbicides. Resistance to glyphosate in populations of Lolium perenne L. ssp. multiflorum is increasingly common in California, USA, causing economic losses and the loss of effective management tools. To gain insights into the recent evolution of glyphosate resistance in L. perenne in perennial cropping systems of northwest California and to inform management, we investigated the frequency of glyphosate resistance and the genetic diversity and structure of 14 populations. The sampled populations contained frequencies of resistant plants ranging from 10% to 89%. Analyses of neutral genetic variation using microsatellite markers indicated very high genetic diversity within all populations regardless of resistance frequency. Genetic variation was distributed predominantly among individuals within populations rather than among populations or sampled counties, as would be expected for a wide-ranging outcrossing weed species. Bayesian clustering analysis provided evidence of population structuring with extensive admixture between two genetic clusters or gene pools. High genetic diversity and admixture, and low differentiation between populations, strongly suggests the potential for spread of resistance through gene flow and the need for management that limits seed and pollen dispersal in L. perenne.
Data from: Divergence in calls but not songs in the orchard oriole complex: Icterus spurius and I. fuertesi
Birdsong has important functions in attracting and competing for mates, and song characteristics are thought to diverge rapidly during the process of speciation. In contrast, other avian vocalizations that may have non-reproductive functions, such as calls, are thought to be more evolutionarily conserved and may diverge more slowly among taxa. This study examines differences in both male song and an acoustically simpler vocalization, the 'jeet' call, between two closely related taxa, Icterus spurius and I. fuertesi. A previous study comparing song syllable type sharing within and between I. spurius and I. fuertesi indicated that their songs do not differ discernibly. Here we measured 18 acoustic characteristics of their songs and found strong evidence supporting this prior finding. In contrast, we measured 17 acoustic characteristics of jeet calls and found evidence of significant divergence between the two taxa in many of these characteristics. Calls in I. fuertesi have a longer duration, a larger frequency bandwidth, a lower minimum frequency, a lower beginning frequency, and greater levels of both frequency and amplitude modulation in comparison to the calls of I. spurius. In addition, I. fuertesi calls contain two distinct parts, while the calls of I. spurius have only one part. Thus, we find evidence of divergence in the calls of the two taxa but not their songs challenging the widespread assumption that complex bird song evolves more rapidly than other types of vocalizations. Understanding divergence in multiple vocalization types as well as other behavioral, morphological, and molecular traits is important to understanding the earliest stages of speciation.
FIGURES 1–12 in A new Neotropical sharpshooter genus Spinagonalia (Insecta, Hemiptera, Cicadellidae, Cicadellinae) with description of a new species from Citrus orchards and grapevines
FIGURES 1–12. Spinagonalia rubrovittata gen. nov. and sp. nov. (Paratypes). 1–6, male. 1—Head, pronotum and scutellum, dorsal view; 2—pygofer, lateral view; 3—valve and subgenital plate, ventral view; 4—style, connective and paraphysis, dorsal view; 5—aedeagus and anal tube, lateral view; 6—apex of aedeagus, posterior view; 7–12, female. 12 —pygofer and sternite VII, lateral view; 8—sternite VII, ventral view; 9—sternite VIII, dorsal view; 10—base of the first valvula, lateral view; 11—first valvula apex, lateral view; 12—second valvula, lateral view.
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.
FIGURE 2 in Survey Of Phytoseiid Mite Species (Acari: Phytoseiidae) In Citrus Orchards In Lattakia Governorate, Syria
FIGURE 2: Dorsal shield of the female of Typhlodromus (Anthoseius) thesbites.
FIGURE 1 in Survey Of Phytoseiid Mite Species (Acari: Phytoseiidae) In Citrus Orchards In Lattakia Governorate, Syria
FIGURE 1: Map of Syria and locations of study sites in Lattakia governorate.
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>
Dataset for canopy sensing in orchards and vineyards
<p>Data collected with the sensors:</p> <ul> <li> <p>OAK-D-POE Camera</p> </li> <li> <p>GP-808G GNSS receiver</p> </li> <li> <p>Hokuyo UST-10lx LiDAR</p> </li> </ul> <p>The dataset is composed of three different collections: two in orchards and one in vineyards.</p>
Supplementary material 1 from: Gray R, Strine CT (2017) Herpetofaunal assemblages of a lowland broadleaf forest, an overgrown orchard forest and a lime orchard in Stann Creek, Belize. ZooKeys 707: 131-165. https://doi.org/10.3897/zookeys.707.14029
Common captures during study : Explanation note: Photos of reptiles and amphibians most commonly captured during the study. Information is provided regarding the habitats each species was caught in during the study, their IUCN Redlist conservation status, and EVS scores according to Johnson et al. (2015).
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>
FIGURES 69–75 in An Identification key to the species of Auchenorrhyncha of Iranian fauna recorded as pests in orchards and a review on the pest status of the species
FIGURES 69–75. Male genitaliae of Cicadidae of Iran recorded as pests in orchards: 69. Chloropsalta ochreata, apical part of aedeagus, ventral view; 70. Chloropsalta smaragdula, aedeagus, lateral view; 71. Cicadatra alhageos, laeral view; 72. Cicadatra persica, apical part of aedeagus, lateral view; 73. Psalmocharias flava, apical part of aedeagus, lateral view; 74. Psalmocharias querula, apical part of aedeagus, lateral view; 75. Tibicen plebejus, Aedeagus, lateral view.
FIGURES 61–68 in An Identification key to the species of Auchenorrhyncha of Iranian fauna recorded as pests in orchards and a review on the pest status of the species
FIGURES 61–68. Habitus of Cicadidae of Iran recorded as pests in orchards: 61. Chloropsalta ochreata; 62. Chloropsalta smaragdula; 63. Cicadatra alhageos; 64. Cicadatra persica; 65. Pagiphora annulata; 66. Psalmocharias flava; 67. Psalmocharias querula; 68. Tibicen plebejus (already published in: Mozaffarian & Sanborn 2016).
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.