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United States Department of Agriculture

Agricultural Research Service

Title: Use of Hyperspectral Radiometry in Prediction of Lamb Growth on Bermuda Grass Pastures.

Authors
item Phillips, Amina - RCC, EL RENO, OK
item Brown, Michael
item Starks, Patrick
item Dawkins, David - RCC, EL RENO, OI
item Biles, Charles - EAST CENTRAL U, ADA, OK

Submitted to: Research Day Abstracts: Regional Universities Research Day
Publication Type: Abstract Only
Publication Acceptance Date: September 1, 2003
Publication Date: November 14, 2003
Citation: Phillips, A.P., Brown, M.A., Starks, P.J., Dawkins, D., Biles, C. 2003. Use of hyperspectral radiometry in prediction of lamb growth on bermuda grass pastures. Research Day Abstracts: Regional Universities Research Day. Abstract No. S-319. p. 99.

Interpretive Summary: Abstract Only.

Technical Abstract: In a two-year research project at the Grazinglands Research Laboratory, lambs (n=135) were used to evaluate the potential for predicting lamb growth from hyperspectral radiometer data taken in bermudagrass pastures grazed by lambs. Lambs were randomized to four, 1.6-hectare pastures so each pasture was stocked with approximately 12 (2002) or 22 (2003) lambs. When initial lamb weights were taken in early June, spectral reflectance was measured in each pasture using a mobile hyperspectral radiometer at 252 wavebands in the visible through near infrared portion of the electromagnetic spectrum (368.4 to 1113.7 nm). Spectral reflectance for each field was measured eight to ten times along a transect with three subsamples per sample. Lambs were weighed again on approximately two-week intervals and animal growth data estimated for four periods of two weeks per period. At the time of each weight, spectral reflectance from the pastures was measured as described above. Reflectance data were converted to absorbance by taking the logarithm to the base 10 of the reciprocal of reflectance. Relationships of animal gain to 252 spectral absorbance estimates were investigated by pairing averages for gain and spectral absorbance for each pasture at the beginning of each week or period in each year. Stepwise regression was performed to identify best multiple linear regression models based on coefficients of determination. A linear combination of 15 independent spectral absorbance variables ranging from absorbance in the lower visible spectrum (384 to 541.9 nm) to absorbance in the near-infrared spectrum of 896.4 to 1113.7 nm accounted for over 90% of the total variance in animal gains. Results suggest that prediction of animal growth from field level hyperspectral radiometry may be feasible.

Last Modified: 4/18/2014
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