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Downloads and views - Time Series

Number of downloads and views in the period.

Period:
Total Year Month Day

Item Handle
(eg. 1822/417)
 

Item
Title : Machine learning and statistics to qualify environments through multi-traits in Coffea arabica.
Entry Date : 19-08-2021
Downloads and viewsExport
Year Downloads Views
2021 7.0 69
2022 9.0 81
2023 18.0 131
2024 71.0 271
2025 40.0 62
145.0 614
Downloads and views per year
Downloads by country (top 10)
Views by country (top 10)
Downloads by countryExport
Origin Downloads Perc.(%)
United States United States 126.0 67.74
Brazil Brazil 11.0 5.91
China China 11.0 5.91
Czech Republic Czech Republic 6.0 3.23
Netherlands Netherlands 6.0 3.23
Russian Federation Russian Federation 5.0 2.69
Embrapa Embrapa 5.0 2.69
France France 4.0 2.15
Germany Germany 3.0 1.61
N/A N/A 2.0 1.08
Japan Japan 2.0 1.08
Latvia Latvia 2.0 1.08
United Kingdom United Kingdom 1.0 0.54
Italy Italy 1.0 0.54
Australia Australia 1.0 0.54
186.0 100.00
Views by countryExport
Origin Views Perc.(%)
United States United States 366 51.19
United Kingdom United Kingdom 69 9.65
Germany Germany 54 7.55
Moldova, Republic of Moldova, Republic of 51 7.13
N/A N/A 30 4.20
China China 25 3.50
Embrapa Embrapa 23 3.22
Russian Federation Russian Federation 20 2.80
Brazil Brazil 19 2.66
Canada Canada 15 2.10
Japan Japan 10 1.40
Australia Australia 8 1.12
France France 6 0.84
Sweden Sweden 6 0.84
Latvia Latvia 5 0.70
Netherlands Netherlands 2 0.28
Mongolia Mongolia 1 0.14
Romania Romania 1 0.14
Argentina Argentina 1 0.14
Ireland Ireland 1 0.14
Venezuela Venezuela 1 0.14
Ukraine Ukraine 1 0.14
715 100.00
Indexed by
Portal Brasileiro de Publicações e Dados Científicos em Acesso Aberto        BR1– FAO AGRIS data provider 2025
Supported by


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Brazilian Agricultural Research Corporation - Embrapa SAC: https://www.embrapa.br/fale-conosco

The repository content is licensed under the Creative Commons License Attribution-NonCommercial-NoDerivs 4.0 International.
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