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Dietary fiber is an important quality parameter of barley (Hordeum vulgare L.) but is extremely laborious to measure. Near-infrared (NIR) transmission and reflectance spectroscopy were investigated as rapid screening tools to evaluate the total dietary fiber content of barley cultivars. The Foss Grainspec Rice Analyzer and NIR Systems 6500 spectrometer were used to obtain transmission and reflectance spectra, respectively, of polished grains and ground barley. Total dietary fiber was determined for each cultivar by AOAC Method 991.43. Modified PLS models developed for predicting total dietary fiber, using transmission spectra (850-1048 nm) of polished grains, had a standard error of cross validation (SECV) of 10.4 (range 58-197) g [kg.sup.-1] and [R.sup.2] of 0.82 indicating sufficient accuracy for selecting or rejecting high dietary fiber cultivars. NIR reflectance spectroscopy (1104-2494 nm) of ground barley samples resulted in a model with SECV of 5.2 (range 58-197) g [kg.sup.-1] and [R.sup.2] 0.96, indicating a high degree of precision in the prediction of total dietary fiber. The increased accuracy of the reflectance model may be due in part to more information available in the wavelength region used. The precision, low cost per sample and speed of measurement of the technique allow making dietary fiber selection decisions for large numbers of progeny in barley breeding programs. Abbreviations: NIR, near-infrared; PLS, partial least squares; [R.sup.2], coefficient of determination; [r.sup.2], multiple coefficient of determination; SD, standard deviation; SEC, standard error of calibration; SECV, standard error of cross validation; TDF, total dietary fiber., DIETARY FIBER is an important quality parameter for barley cultivars. High fiber content is undesirable in cultivars used for brewing and animal feed and desirable in barley cultivars used for [...]

Flax fibers may be blended with cotton to provide an aesthetic property, improve performance and tailor fabric properties. The quality and cost of the woven fabric blends are affected by the amount of linen in the blend. Microscopic and chemical analyses are currently used to determine linen content in fabrics. This study describes a method to predict the linen percentage in linen/cotton blends using Fourier transform near-infrared (FT-NIR) spectroscopy, rapidly and non-invasively. A calibration model using partial least squares regression analysis was developed with gray]metrically measured ground flax-cotton fiber mixtures as reference samples versus NIR spectra. The best model occurred with a combination of multiplicative scatter correction and first derivative processing of the spectral data gave a standard error of validation of 2.20%, and only one factor was used for the model performance. Using this model, flax content was predicted in specific mixtures of flax and cotton fibers, blended flax-cotton yams, and various non-scoured flax-cotton fabrics, giving standard errors of prediction less than 3%. Application of the calibration model to the scoured fabric, however, resulted in a higher error value. This result seemed to be due to loss in wax components and substantial changes in the NIR absorbance values of the fabric resulting from the scouring process. An alternative calibration model for scoured and dyed fabrics was developed, and using the model it was possible to predict flax contents in dyed fabrics with an error of 4-6%. [ABSTRACT FROM AUTHOR]