![]() ![]() PCA models showed two major groups-one with Sweet Bran and distillers grains, and the other with corn silage and corn stalk. Principal component analysis (PCA) and partial least squares (PLS) regression models were developed using mean-centered data that had been preprocessed using standard normal variate (SNV) or Savitzky-Golay first derivative (SG1) or second derivative (SG2) algorithm. For H1, only absorbances in the NIR region (780–2500 nm) were used in the multivariate analyses, while for H2, absorbances in the second and third overtone regions (940–1660 nm) were used. Spectral data of 147 forage and feed samples were collected by both handheld instruments and split into calibration ($n$ = 120) and validation ($n$ = 27) sets. Second was a smartphone spectrometer, which measured from 900–1700 nm with a spectral interval of 4 nm (H2). First was a transportable spectrometer, which measured in the visible and NIR ranges (320–2500 nm) with a spectral interval of 1 nm (H1). ![]() Two handheld near infrared (NIR) spectrometers were used to quantify crude protein ($CP$) content of mixed forage and feedstuff composed of Sweet Bran, distiller's grains, corn silage, and corn stalk. ![]()
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