“…The NIR technology has been applied to predict oil per se and its quality in rapeseed, safflower, and soybean (Tajuddin et al, 2002;Kim et al, 2007;Patil et al, 2010;Rudolphi et al, 2012;Wittkop et al, 2012); fiber fractions in rapeseed (Wittkop et al, 2012); starch, protein, oil, amino acid composition and weight of individual grains in maize (Spielbauer et al, 2009;Tallada et al, 2009;Rosales et al, 2011); stover quality in maize (Melchinger et al, 1986); amino acid composition in soybean (Kovalenko et al, 2006); protein, starch and seed weight in intact seed in common bean (Hacisalihoglu et al, 2010); and for sensing moisture content of in-shell peanut (Sundaram et al, 2012). Baianu et al (2012) developed a high-resolution nuclear magnetic resonance and NIR models that they validated by estimating amino acid profiles of proteins from a large number of single and bulked soybean seeds, without protein extraction from the seed. Using partial least squares regression technique to analyze the NIR spectral data, they found that single soybean seed NIR spectra are broadly similar to those of bulk whole soybeans, with the exception of minor peaks, 950-1000 nm, in single soybean NIR spectra.…”