Spectral Reflectance Evaluates the Nutritional Value of Forage

Even if you're not raising lambs, an innovative use of spectral reflectance technology now under development might hold out promise for some other project you are considering. Right now it's directed at determining the amount of nutrition an animal is getting from its forage and how much weight it's likely to gain from that grazing.

The Agricultural Research Service lab and two companies in Oklahoma have entered into a cooperative agreement to design and develop a small, handheld, inexpensive optical remote sensor for field use in calculating, storing, and displaying data on the nutrient quality of particular forage plants.

ARS soil scientist Patrick Starks observes that "a critical shortcoming in grazingland management is an inability to measure—in real time—the nutritional value of live, standing forages on pastures. This information is needed to make informed land- and livestock-management decisions about stocking rates, beginning and ending dates for grazing, and feeding of supplements. Spectral reflectance shows great potential for eliminating this problem."

Starks, animal scientists Michael Brown and William Phillips, and Samuel Coleman in the Subtropical Agricultural Research Station, have thus far demonstrated that spectral reflectance data can indicate the quality of forage grasses with an accuracy comparable to conventional lab analysis. The difference, though, is time. Spectral reflectance data can be processed in seconds, Starks says, whereas conventional methods "entail clipping, NIR spectroscopy, and chemical procedures that, while accurate and site-specific, are laborious and take days to complete." In addition to eliminating manual sampling, the advantages include nutritional landscape mapping and more efficient pasture management and an evaluation of the need for supplement feeding.

The researchers collected 0.6 ft.2 swaths of field samples with a commercial handheld hyperspectral radiometer. The data were used to estimate the scanned plants' digestibility through analysis of 252 wavebands of the electromagnetic spectrum. The study focused on Bermuda grass alone, and with a scattering of senescent downy brome and yellow bristlegrass, and compared the ways conventional and real-time data-collecting methods detected concentrations of nitrogen and other components. But they found more: The technology can help predict weight gains and growth of foraging animals.

Twelve spring-born lambs were randomly assigned to each of four, 4-acre, predomininantly Bermuda grass pastures and monitored for three years to see if their weight gains could be predicted by using the spectral reflectance data captured in each pasture. Birth weights were recorded, as were eight subsequent weights. The results suggest, according to Brown, that weight gains based on specific forages "can be predicted—using 15 wavelengths of light—with reasonable accuracy." But if those lambs fail to make their expected gains, supplements are in order. Now if someone could just find a way to scan our dinner tables and make the same intelligent suggestions!

Contact Patrick J. Starks, USDA-ARS Grazinglands Research Laboratory, El Reno, OK; patrick.starks@ars.usda.gov 405-262-5291. www.ars.usda.gov.