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31 to 40 of 161 Results
Nov 19, 2025 - CIMMYT Research Data
Dreisigacker, Susanne, 2025, "58IBWSN and 43SAWSN - Gene-based marker data for marker-assisted selection", https://doi.org/10.71682/10549362, CIMMYT Research Data & Software Repository Network, V1
Gene-based marker data from international screening nurseries for marker-assisted selection .
MS Excel Spreadsheet - 212.4 KB - MD5: 179a9fb3242c491e1bfac1cbdda3dc8a
DataGenotypic data
Nov 19, 2025 - CIMMYT Research Data
Dreisigacker, Susanne, 2025, "57IBWSN, 42SAWSN, and 35HRWSN - Gene-based marker data for marker-assisted selection", https://doi.org/10.71682/10549361, CIMMYT Research Data & Software Repository Network, V1
Gene-based marker data from international screening nurseries for marker-assisted selection .
MS Excel Spreadsheet - 279.9 KB - MD5: 23bfd6c14b644ef3ee255bc4a6207ff7
DataGenotypic data
Sep 10, 2025 - CIMMYT Research Data
Krupnik, Timothy; Harun-Or-Rashid, Md; Pandit, Dinabandhu; Islam, Rabiul; Hossain, Md. Khaled; Cunha Fernandes, José Mauricio; Roy, Krishna Kanta; Kabir, Muhammad Rezaul; Stuerz, Sabine; Singh, Pawan Kumar; Faruq, Golam, 2025, "Replication Data for: Mix and manage: Cultivar mixtures can maintain yield under high wheat blast disease pressure", https://hdl.handle.net/11529/10549179, CIMMYT Research Data & Software Repository Network, V1
Wheat blast disease, which began in South America, has now spread to Asia and Africa, posing a serious threat to food security. The first outbreak in Bangladesh occurred in 2016, leading to the release of the blast-resistant wheat variety BARI Gom 33. Although seeds for this vari...
Sep 10, 2025 - CIMMYT Research Data
Blasch, Gerald; Alemayehu, Yoseph; Lesne, Louise; Wolter, Jolan; Taymans, Matthieu; Tesfaye, Tsegaab; Negash, Tamirat; Andulalem, Mequanint; Gutu, Kitessa; Debela, Megersa; Eshetu, Zerihun; Tesfaye, Kindie; Mottaleb, Khondoker; Defourny, Pierre; Hodson, David, 2025, "Ethiopian crop type 2020 (EthCT2020) dataset", https://hdl.handle.net/11529/10549285, CIMMYT Research Data & Software Repository Network, V1
The observation of crop types is paramount for a myriad of agricultural and environmental remote sensing applications, including land use mapping, crop growth monitoring, and yield forecasting. Accurate georeferenced and quality-controlled crop type data is integral to the calibr...
dBASE Table for ESRI Shapefile - 2.6 MB - MD5: ec5eeb471aa3b882aacf783f8e9d5f53
ESRI Shapefile - 401 B - MD5: 0234e8c390933195e1d0c82a13d16869
Shape - 5.3 MB - MD5: 80d04d71aa0bf735563f415f48c7fce7
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