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7,101 to 7,110 of 13,542 Results
Replication Data for: Integrated weed management in transplanted rice: Options for addressing labor constraints and improving farmers’ income in Bangladesh
Jul 31, 2021 - Cereal Systems Initiative for South Asia (CSISA) Research Data
Ahmed,Sharif; Kumar,Virender; Alam,Murshedul; Dewan,Mahbubur Rahman; Bhuiya,Khairul Alam; Saha,Abhijit; Miajy,Abu Abdullah; Singh,Sudhanshu; Timsina,Jagadish; Krupnik,Timothy J., 2021, "Replication Data for: Integrated weed management in transplanted rice: Options for addressing labor constraints and improving farmers’ income in Bangladesh", https://hdl.handle.net/11529/10548600, CIMMYT Research Data & Software Repository Network, V1, UNF:6:HmO/JVvcmNC7pPO6MNVZJQ== [fileUNF]
The database contains data about on-farm trials with transplanted rice were conducted during monsoon (‘Aman’) season in 2016 and 2017 and winter (‘Boro’) season in 2016 to 2017 in agroecological zones (AEZs) 11 and 12 of south-west Bangladesh with ten treatments - seven herbicide...
Aman_weed_data.tab
Jul 31, 2021 - Replication Data for: Integrated weed management in transplanted rice: Options for addressing labor constraints and improving farmers’ income in Bangladesh
Tabular Data - 22.5 KB - 16 Variables, 320 Observations - UNF:6:RVmnv+CfSfqqK1FbPsXZbg==
Aman_Yield_and_economics.tab
Jul 31, 2021 - Replication Data for: Integrated weed management in transplanted rice: Options for addressing labor constraints and improving farmers’ income in Bangladesh
Tabular Data - 13.8 KB - 8 Variables, 320 Observations - UNF:6:WhoswlkTNTGWDmKuIzdgog==
Boro_weed_data.tab
Jul 31, 2021 - Replication Data for: Integrated weed management in transplanted rice: Options for addressing labor constraints and improving farmers’ income in Bangladesh
Tabular Data - 9.3 KB - 16 Variables, 120 Observations - UNF:6:FYOtIM11+UxMNkccQqU2SQ==
Boro_yield_and_economics-1.tab
Jul 31, 2021 - Replication Data for: Integrated weed management in transplanted rice: Options for addressing labor constraints and improving farmers’ income in Bangladesh
Tabular Data - 5.8 KB - 8 Variables, 120 Observations - UNF:6:kpZvSppsWkhXi+geJY7L6g==
Metadata_IWM_TPR.tab
Jul 31, 2021 - Replication Data for: Integrated weed management in transplanted rice: Options for addressing labor constraints and improving farmers’ income in Bangladesh
Tabular Data - 5.3 KB - 2 Variables, 46 Observations - UNF:6:DYkr+Tu+F0gQG00MlPbR3Q==
Metadata
Replication Data for: Genomic prediction of resistance to Tar Spot Complex of maize in multiple populations using genotyping-by-sequencing SNPs
Jul 20, 2021 - CIMMYT Research Data
Cao, Shiliang; Song, Junqiao; Yuan, Yibing; Zhang, Ao; Ren, Jiaojiao; Liu, Yubo; Qu, Jingtao; Hu, Guanghui; Zhang, Jianguo; Wang, Chunping; Cao, Jingsheng; Olsen, Michael; Prasanna, Boddupalli M.; San Vicente, Felix; Zhang, Xuecai, 2021, "Replication Data for: Genomic prediction of resistance to Tar Spot Complex of maize in multiple populations using genotyping-by-sequencing SNPs", https://hdl.handle.net/11529/10548579, CIMMYT Research Data & Software Repository Network, V1
Tar spot complex (TSC) is an important foliar disease for tropical maize. The data provided in this dataset were used to estimate the effectiveness of genomic selection for improving TSC resistance. The results of the analysis are reported in the accompanying journal article
DTMA+3Pop-noparent(728).hmp.txt.gz
Jul 20, 2021 - Replication Data for: Genomic prediction of resistance to Tar Spot Complex of maize in multiple populations using genotyping-by-sequencing SNPs
Gzip Archive - 83.2 MB - MD5: 94676a69aea9d484ce94a84e36402a17
Genotypic_data
DTMA+3Pop-noparent(728)pheno.txt
Jul 20, 2021 - Replication Data for: Genomic prediction of resistance to Tar Spot Complex of maize in multiple populations using genotyping-by-sequencing SNPs
Plain Text - 9.1 KB - MD5: 8bfc0a9ec7dcf3e4434af2ae0a14f22f
Phenotypic_data
phenotype_and_taxa_of_four_populations.xlsx.gz
Jul 20, 2021 - Replication Data for: Genomic prediction of resistance to Tar Spot Complex of maize in multiple populations using genotyping-by-sequencing SNPs
Gzip Archive - 27.1 KB - MD5: 6ee0663dfb5b7a035d7e10e1f4fa21db
Phenotypic_data
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