cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19929280.v1
title: Fruit flies (Diptera: Tephritidae) and their parasitoids associated with acerola, mango, and guava in the municipality of Brasil Novo, Pará

description: ABSTRACT Fruit flies are phytophagous insects that are important because of the damages caused to fruits, mainly by larvae that feed on the pulp. Surveys of the diversity of these tefritids are still scarce in Brazil, especially in the Amazon region, the objective of this study was to establish the tritrophic relationship existing between species of Anastrepha, their parasitoids, and the fruits acerola (Malpighia emarginata DC.), mango (Mangifera indica L.), and guava (Psidium guajava L.) in the municipality of Brasil Novo, Pará. Freshly fallen fruits were collected weekly from January to December 2018, in three farms. Throughout the survey, 4,324 puparium were collected in guavas, 2,682 in mangoes, and 644 in acerolas. The species Anastrepha obliqua (Macquart, 1835) were identified in mango (90.3%), acerola (7.7%) and guava (2.1%), and Anastrepha striata Schiner, 1868 were identified in guava (98.8%) and acerola (1.2%). Five species of parasitoids were identified in association with A. obliqua and six species of parasitoids were identified in association with A. striata. The specie Doryctobracon areolatus (Szépligeti, 1911) was the most frequent among the species of parasitoids recorded.
DOI: 10.6084/m9.figshare.19929280
title: Fruit flies (Diptera: Tephritidae) and their parasitoids associated with acerola, mango, and guava in the municipality of Brasil Novo, Pará

description: ABSTRACT Fruit flies are phytophagous insects that are important because of the damages caused to fruits, mainly by larvae that feed on the pulp. Surveys of the diversity of these tefritids are still scarce in Brazil, especially in the Amazon region, the objective of this study was to establish the tritrophic relationship existing between species of Anastrepha, their parasitoids, and the fruits acerola (Malpighia emarginata DC.), mango (Mangifera indica L.), and guava (Psidium guajava L.) in the municipality of Brasil Novo, Pará. Freshly fallen fruits were collected weekly from January to December 2018, in three farms. Throughout the survey, 4,324 puparium were collected in guavas, 2,682 in mangoes, and 644 in acerolas. The species Anastrepha obliqua (Macquart, 1835) were identified in mango (90.3%), acerola (7.7%) and guava (2.1%), and Anastrepha striata Schiner, 1868 were identified in guava (98.8%) and acerola (1.2%). Five species of parasitoids were identified in association with A. obliqua and six species of parasitoids were identified in association with A. striata. The specie Doryctobracon areolatus (Szépligeti, 1911) was the most frequent among the species of parasitoids recorded.
DOI: 10.5281/zenodo.6578915
title: SuperDARN data in netCDF format (2009-Mar)

description: 2009-Mar SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6573568
title: SuperDARN data in netCDF format (2010-Jul)

description: 2010-Jul SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6578537
title: SuperDARN data in netCDF format (2009-Aug)

description: 2009-Aug SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6578269
title: SuperDARN data in netCDF format (2009-Sep)

description: 2009-Sep SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6574943
title: SuperDARN data in netCDF format (2010-May)

description: 2010-May SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6576854
title: SuperDARN data in netCDF format (2009-Oct)

description: 2009-Oct SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6574868
title: SuperDARN data in netCDF format (2010-Jun)

description: 2010-Jun SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6575063
title: SuperDARN data in netCDF format (2010-Mar)

description: 2010-Mar SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6575165
title: SuperDARN data in netCDF format (2010-Jan)

description: 2010-Jan SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6575216
title: SuperDARN data in netCDF format (2009-Dec)

description: 2009-Dec SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.6084/m9.figshare.19929281
title: Biochar and swine wastewater: Effects on soil fertility of different textures and corn nutrition

description: ABSTRACT The use of organic waste in agriculture has stimulated the search for technologies that reduce environmental pollution. Among the residues are the biochar and swine wastewater (SW), which incorrectly disposed cause negative impacts, however, when combined, they can enhance agricultural production, due to the synergism between both. In this sense, the objective was to evaluate the influence of doses of biochar, from conilon coffee straw, combined or not with swine wastewater diluted to 50% (SW50%), on the nutrient content in medium and clayey texture soils and in the corn plant tissue. The experiment was carried out in a greenhouse, with five doses of biochar, two irrigation waters and two soils, with three repetitions. The pH, P, K+, Ca+2, Mg+2, Zn+2 and Na+ in the soil and N, P, K, Ca, Mg, Zn and Na in plant were evaluated. The addition of biochar in doses linearly increased the levels of P and K+ in both soil textures, with synergy when irrigated with SW50%. The SW50% provided a nutrients increase in the corn plant tissue. The agricultural use of biochar from conilon coffee straw was important to increase the content of P and, mainly, K in the aerial part of corn.
DOI: 10.6084/m9.figshare.19929281.v1
title: Biochar and swine wastewater: Effects on soil fertility of different textures and corn nutrition

description: ABSTRACT The use of organic waste in agriculture has stimulated the search for technologies that reduce environmental pollution. Among the residues are the biochar and swine wastewater (SW), which incorrectly disposed cause negative impacts, however, when combined, they can enhance agricultural production, due to the synergism between both. In this sense, the objective was to evaluate the influence of doses of biochar, from conilon coffee straw, combined or not with swine wastewater diluted to 50% (SW50%), on the nutrient content in medium and clayey texture soils and in the corn plant tissue. The experiment was carried out in a greenhouse, with five doses of biochar, two irrigation waters and two soils, with three repetitions. The pH, P, K+, Ca+2, Mg+2, Zn+2 and Na+ in the soil and N, P, K, Ca, Mg, Zn and Na in plant were evaluated. The addition of biochar in doses linearly increased the levels of P and K+ in both soil textures, with synergy when irrigated with SW50%. The SW50% provided a nutrients increase in the corn plant tissue. The agricultural use of biochar from conilon coffee straw was important to increase the content of P and, mainly, K in the aerial part of corn.
DOI: 10.5281/zenodo.6570689
title: SuperDARN data in netCDF format (2010-Sep)

description: 2010-Sep SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6570743
title: SuperDARN data in netCDF format (2010-Aug)

description: 2010-Aug SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6575029
title: SuperDARN data in netCDF format (2010-Apr)

description: 2010-Apr SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'