Spectra of walnut kernel for moisture content measurement

The rapid and accurate detection of moisture content is of great significance to the quality evaluation and oil extraction process of walnut kernel. Near-infrared (NIR) spectroscopy is an ideal method for measuring moisture content in walnut kernel. In this paper, an analysis model for the moisture content in walnut kernel was developed based on NIR diffuse reflectance spectroscopy using chemometric methods. The different spectral pretreatment methods were adopted to pre-process the original spectral data. The whole spectra band was divided into 5 subbands, 10 subbands, 15 subbands and 20 subbands to screen specific wavelengths relevant to the walnut kernel moisture content and different pretreatment spectral data. The PLS, MLR, PCR and SVR were used to establish the relationship model between the spectral data and measurement values of moisture content. In comparison, the optimized modeling conditions were determined as follows: detection wavelength range from 1349 to 1490nm, SNV+1st preprocessing, and PLS modeling. Under these conditions, the square correlation coefficient(R2) and root mean square error of prediction(RMSEP) of the prediction model were 0.9865 and 0.0017, respectively. The results of this study provided a feasible method for the rapid detection of moisture content in walnut kernel. In addition, in order to improve the the performance and applicability of the model, it was necessary to continuously expand the size of the sample set.

Methods
The walnut kernel samples used in the experiment were collected from Aksu, Xinjiang province in China. In order to make the walnut kernel samples more representative, the method of moisture absorption in a closed container was adopted. The walnut kernels were crushed by a high-speed universal pulverizer and passed through a 10-mesh fine sieve after removing the shell. The filtered samples were used in the experiment. A certain amount of walnut kernels were placed in a closed container with water at the bottom, and then the container was stored in a constant temperature incubator at 20°C to make the water absorbed evenly. The NIR spectra were collected at 780-2500nm with DS2500 near-infrared diffuse reflectance spectrometer, which was equipped with a tungsten halogen lamp light source and a lead sulfide (1100-2500nm) detector. The operating conditions were listed as follows: the operating temperature 35°C, resolution ±2nm and scanning times 32 times. All data were obtained in triplicate and the mean value was used in subsequent calculations. At last, the spectra of 136 walnut kernel samples with different moisture contents were collected.