Data from: Single-kernel NIR spectroscopy for non-destructive rice bran color discrimination across diverse hull types and production environments
Uniformity of rice bran color is important in the whole grain rice market as well as in seed rice production. Normally, determining bran color requires the removal of the outer hull, which is a destructive process, time-consuming, and an obstacle to the production of nutritious pigmented bran varieties. In this study, single-kernel near-infrared (SKNIR) spectroscopy (905-1688 nm) and multivariate techniques were explored to discriminate rough rice based on bran color (brown, purple, red bran) in rice varieties with similar hull colors (Objective 1), different hull colors (Objective 2), and different growing environments in the US (Objective 3). Dataset includes raw SKNIR data and correlation coefficients of wavelengths used to differentiate between red, purple, and brown rice for objectives 1-3.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode |
[
"005:18"
]
|
| contactPoint |
{
"fn": "Mendoza, Princess Tiffany",
"hasEmail": "mailto:ptiffany@ksu.edu"
}
|
| description | <p dir="ltr">Uniformity of rice bran color is important in the whole grain rice market as well as in seed rice production. Normally, determining bran color requires the removal of the outer hull, which is a destructive process, time-consuming, and an obstacle to the production of nutritious pigmented bran varieties. In this study, single-kernel near-infrared (SKNIR) spectroscopy (905-1688 nm) and multivariate techniques were explored to discriminate rough rice based on bran color (brown, purple, red bran) in rice varieties with similar hull colors (Objective 1), different hull colors (Objective 2), and different growing environments in the US (Objective 3). Dataset includes raw SKNIR data and correlation coefficients of wavelengths used to differentiate between red, purple, and brown rice for objectives 1-3. </p> |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Rice SKNIR_rawdata.xlsx",
"format": "xlsx",
"mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
"downloadURL": "https://ndownloader.figshare.com/files/57285179"
},
{
"@type": "dcat:Distribution",
"title": "Rice SKNIR_regcoeff.xlsx",
"format": "xlsx",
"mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
"downloadURL": "https://ndownloader.figshare.com/files/57285182"
}
]
|
| identifier | 10.15482/USDA.ADC/29901707.v1 |
| keyword |
[
"Machine learning",
"Multivariate analysis",
"Near-infrared spectrscopy",
"Pigmented rice",
"Rice bran color"
]
|
| license | https://www.usa.gov/publicdomain/label/1.0/ |
| modified | 2025-09-30 |
| programCode |
[
"005:040"
]
|
| publisher |
{
"name": "Agricultural Research Service",
"@type": "org:Organization"
}
|
| temporal | 2023-05-01/2025-05-01 |
| title | Data from: Single-kernel NIR spectroscopy for non-destructive rice bran color discrimination across diverse hull types and production environments |
