Legume hyperspectral and in-situ biophysical/biochemical dataset collected in the Southern Plains
A field experiment focused on three legumes (soybeans [Glycine max], mothbeans [Vigna aconitifolia], and tepary bean [Phaseolus acutifolius]) was conducted in El Reno, OK over a two year period (2018, 2019). The split-split plot design for the legumes were subject to various row spacing (38cm and 76cm) and irrigation regimes (irrigated and rainfed). Sampling of the plots took place a total of seven times over the two year period. Each of the samplings included an initial triplicate (averaged) hyperspectral readings using a spectroradiometer (350nm to 2500nm; FieldSpec Pro FR: Malvern Panalytical, Westborough, MA, USA), in-situ measurements (canopy cover [collected with the “Canopeo” app where a ratio of plant to ground pixels were calculated], chlorophyll content [collected with Chlorophyll Content Meter-300, Opti-Sciences, Hudson, NH, USA]), and biomass clipping for various laboratory analytics (dry weight, nitrogen/carbon content, crude protein, neutral detergent fiber, acid detergent fiber, in vitro true digestibility). Locations for sampling (n=334) within the 4m x 3m plots were chosen at random.
Funding
USDA-ARS
History
Data contact name
Flynn, K. ColtonData contact email
colton.flynn@usda.govPublisher
Ag Data CommonsIntended use
The original use was to determine the biophysical and biochemical in-situ measures of the three legumes using the hyperspectral data.Temporal Extent Start Date
2018-07-27Temporal Extent End Date
2019-09-03Theme
- Non-geospatial
Geographic location - description
These data collection efforts took place at the El Reno, Oklahoma USDA-ARS research station.ISO Topic Category
- farming
- health
- environment
Ag Data Commons Group
- Southern Plains
- Long-Term Agroecosystem Research
National Agricultural Library Thesaurus terms
data collection; field experimentation; soybeans; Glycine max; Vigna aconitifolia; Phaseolus acutifolius var. acutifolius; Oklahoma; experimental design; row spacing; irrigation management; reading; spectroradiometers; canopy; chlorophyll; biomass; nitrogen; carbon; crude protein; neutral detergent fiber; acid detergent fiber; digestibility; artificial intelligenceOMB Bureau Code
- 005:18 - Agricultural Research Service
OMB Program Code
- 005:040 - National Research
ARS National Program Number
- 211
ARIS Log Number
421280Pending citation
- Yes
Related material without URL
Moorthy, C., K.C. Flynn, G.S. Baath, P. Gowda, B. Northup, and A. Ashworth. (In Review). Monitoring legume nutrition with machine learning: The impact of splits in training and testing data. Moorthy, C., K.C. Flynn, G.S. Baath, T.O. Lee, P. Gowda, B. Northup, and A. Ashworth. (In Review). Hyperspectral reflectance and machine learning for monitoring forage quality in legumes.Public Access Level
- Public