NIR Reflectance Spectroscopy for Nondestructive Moisture Content Determination in Peanut Kernels

摘要

There are some commercial instruments available that use near-infrared (NIR) radiation measurements to determine the moisture content (MC) of a variety of grain products, such as wheat and corn, without the need of any sample grinding or preparation. However, to measure the MC of peanuts with these instruments, the peanut kernels have to be chopped into smaller pieces and filled into the measuring cell. This is cumbersome, time consuming, and destructive. An NIR reflectance method is presented here by which the average MC of about 100 g of whole kernels could be determined rapidly and nondestructively. The MC range of the peanut kernels tested was between 8% and 26%. Initially, NIR reflectance measurements were made at 1 nm intervals in the wavelength range of 1000 to 1800 nm, and the data were modeled using partial least squares regression (PLSR). The predicted values of the samples tested in the above range were compared with the values determined by the standard air-oven method. The predicted values agreed well with the air-oven values, with an R 2 value of 0.93 and a standard error of prediction (SEP) of 1.18. Using the PLSR beta coefficients, five key wavelengths were identified, and MC predictions were made using multiple linear regression (MLR). The R 2 and SEP values of the MLR model were 0.91 and 1.09, respectively. Both methods performed satisfactorily and, being rapid, nondestructive, and noncontact, may be suitable for continuous monitoring of MC of grain and peanuts as they move on conveyor belts during their processing