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211 to 220 of 10,510 Results
CBBW (EYT_CBBW) Y 21-22 Antaris(QData+NIR).csv
Apr 16, 2025 - T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy
Comma Separated Values - 2.8 MB - MD5: 95376828ab420b09e2774adb19ff7d25
DataQuality data
CBBW Pipelines 1-3 Y.csv
Apr 16, 2025 - T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy
Comma Separated Values - 3.7 MB - MD5: f8a404470aafacee450e24c5b9dc5ccc
DataQuality data
CBBW Pipelines 2-4 Y.csv
Apr 16, 2025 - T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy
Comma Separated Values - 3.1 MB - MD5: af40628a7de748d168317a809771defa
DataQuality data
CBBW(C56IBWSN) Y.csv
Apr 16, 2025 - T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy
Comma Separated Values - 2.3 MB - MD5: 77a98142e8b7f88c5ad9bc9a9c934c6c
DataQuality data
CBBW(EYTBWB2IR) Y 21-22 Antaris(QData+NIR).csv
Apr 16, 2025 - T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy
Comma Separated Values - 2.8 MB - MD5: 60d49f11dc734d9d08f2f60d043a8abe
DataQuality data
CBBW(EYTBWB5IR) Y 20-21 Antaris(QData+NIR).csv
Apr 16, 2025 - T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy
Comma Separated Values - 2.3 MB - MD5: 4c671d63749aa081240fc08c2eb3912e
DataQuality data
CBBW(EYTBWLHT) Y 21-22 Antaris(NIR Data).csv
Apr 16, 2025 - T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy
Comma Separated Values - 2.8 MB - MD5: 88003e0a9c7e28bb8d530bd4bb563c15
DataQuality data
CBBW5IR (C57IBWSN) Y 21-22 Antaris(QData+NIR).csv
Apr 16, 2025 - T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy
Comma Separated Values - 951.7 KB - MD5: 35fcda3f2f6ab86b5e1286b5b1230303
EYTBWLHT Y 20-21 (Antaris)(QData+NIR).csv
Apr 16, 2025 - T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy
Comma Separated Values - 2.3 MB - MD5: 588dfe5bc35f4932f9f0cab3aeddc142
Using a Video-based Product Ranking Tool (VPRT) as a basis for maize market segmentation in Kenya and Uganda in 2022
Mar 25, 2025
Rutsaert, Pieter; Mawia, Harriet, 2025, "Using a Video-based Product Ranking Tool (VPRT) as a basis for maize market segmentation in Kenya and Uganda in 2022", https://doi.org/10.71682/10549312, CIMMYT Research Data & Software Repository Network, V1
The maize data was collected in 2022 from small-scale farmers in the districts of Mubende and Mityana in Uganda, and the counties of Kakamega and Bungoma in Kenya. The sample size consists of 2,422 small-scale farmers. Farmer profiling questions cover various topics, including: S...
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