Technology is becoming even better. It is developing itself or being developed by the genius minds in our industry to further make our lives easier. Aside from this, technology is instrumental in providing answers with the myriad of questions that we have in mind. From our appliances that we can’t live without everyday to the complicated laboratory equipment that many companies are now using.
One of these equipment is the Near Infrared Reflectance Spectroscopy. This device is used to determine the concentrations of the major classes of chemical compounds in organic materials, such as plant foliage. It claims to produce rapid, accurate and precise results that could work in lieu of the conventional wet chemistry procedures.
Using reflectance signals that is derived from bending and stretching vibrations in the molecular bonds of carbon, nitrogen, hydrogen and oxygen, it could correlate the spectral response of each specimen at an individual wavelength to known chemical concentrations from laboratory analyses.
Newman and his colleagues, in 1994, formulated the procedure for nitrogen, lignin and cellulose concentration for woody plant foliage using green leaf, leaf litter and decomposing lead litter. The specimen are dried and grinded to a uniform particle size before it would undergo NIRS.
Accordingly, diffuse reflectance spectral data were acquired using a NIRSystems 6500 monochromator with a spinning cup module, scanning at wavelengths from 400 to 2498 nm with a bandwidth of 10 nm. Reflectance data is converted to absorbance, A = log (1/R). Calibration equations were developed using partial least squares regression on first difference transformation of the absorbance data for the entire spectral range (Bolster et al., in press). A total of 18 deciduous and 10 conifer species are represented in the green leaf calibration equation; 13 deciduous and 4 conifer species in the leaf litter calibration equation; 4 deciduous species in the litter decomposition calibration equation.
Such equations are used for prediction of nitrogen, lignin, and cellulose concentrations in unknown samples. Equation should be precise in order to facilitate the prediction of unknown samples depends on whether the range of variation affecting the chemical and physical properties of the unknown samples is represented in the calibration samples. For convenience, universal equations are developed. They are made for broad, or infinite populations may be used for a wide range of samples. Universal equations increase the value of NIRS for the study of large-scale ecosystem processes and change through remote sensing.
