• Journal of Animal Environmental Science
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• v.13 no.2
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• pp.113-120
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• 2007

This study was conducted to measure Nitrogen(N), Phosphate($P_2O_5$), Potassium ($K_2O$), Organic matter(OM) and Moisture content of liquid pig manure by Near Infrared Spectroscopy(NIRS) and to develop an alternative and analytical instrument which are used for measurement of N, $P_2O_5$, $K_2O$, OM, and Moisture contents for liquid pig manure. The liquid pig manure sample's transmittance spectra were measured with a NIRS in the wavelength range of 400 to 2,500 nm. Multiple linear regression and partial least square regression were used for calibrations. The correlation coefficient(RSQ) and standard error of calibration(SEC) obtained for nitrogen were 0.9190 and 2.1649, respectively. The RSQ for phosphate, potassium, organic matter and moisture contents were 0.9749, 0.5046, 0.9883 and 0.9777, and the SEC were 0.5019, 1.9252, 0.1180 and 0.0789, respectively. These results are indications of the rapid determination of components of liquid pig manure through the NIR analysis. The simple analytical instrument for liquid pig manure consisted of a tungsten halogen lamp for light source, a sample holder, a quartz cell, a SM 301 spectrometer for spectrum analyzer, a power supply, an electronics, a computer and a software. Results showed that the simple analytical instrument that was developed can approximately predict the phosphate, organic matter and moisture content of the liquid pig manure when compared to the analysis taken by NIRS. The low predictability value of potassium however, needs further investigation. Generally, the experiment proved that the simple analytical instrument was reliable, feasible and practical for analyzing liquid pig manure.

• Food Engineering Progress
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• v.15 no.1
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• pp.48-55
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• 2011

In this research, the near-infrared absorption from 1,100-2,300 nm was used to measure the content of capsaicinoids in the red-pepper powder by using the Acousto-optic tunable filters (AOTF) spectrometer with sample plate and sample rotating unit. Non-spicy red-pepper samples from one location (Younggwang-gun. Korea) were mixed with spicy one (var. Chungyang) to make samples separated by particle size (below 0.425 mm, 0.425-0.71 mm, and 0.71- 1.4 mm). The Partial Least Squares Regression (PLSR) model to predict the capsaicinoid content on particle sizes was developed with measured spectra by AOTF spectrometer and used to analyze the amount of capsaicinoids by HPLC. The PLSR Model of red-pepper powder of below 0.425 mm, 0.425-0.71 mm, and 0.71-1.4 mm with cross validation had ${R_V}^2$ = 0.948-0.979 and Standard Error of Prediction (SEP) = 6.56-7.94 mg%. The prediction error of smaller particle size of red-pepper powder was low. The best PLSR model was found in pretreatment of Range Normalization, Standard Normal Variate, and 1st Derivatives of red-pepper powder of below 1.4 mm with cross validation, having ${R_V}^2$ = 0.959 and SEP = 8.82 mg%.