عنوان مقاله [English]
Walnut is an important economic and commercial product all over the world. The reflected light spectrum can be one of the key factors in determining the ripening time of the fruit and it depends on the content of the chemical compounds of the fruit and its skin. Crunchyness and easy peeling are the main features that affect the level of satisfaction of walnut consumers. The complexity of the reflectance spectrum of food makes it difficult to analyze them with conventional analytical techniques such as gas chromatography. However, sensory analysis by experts is a costly process and requires trained people who can only work for a relatively short period of time. A near-infrared spectrometer can detect the spectrum of reflected light by estimating its concentration or determining some of its inherent properties.
The quality assessment of agricultural products includes two main methods, quality grading systems based on the external characteristics of agricultural products and quality grading systems based on internal quality assessment, which has gained outstanding points in recent years. In the meantime, several methods have been invented so far for the qualitative grading of agricultural products based on the assessment of their internal properties in a non-destructive way, and only some of them have been able to meet the above conditions and have been justified in terms of technical and industrial aspects. To be meanwhile, spectrometry can be highly efficient in determining the quality of cultivars. Spectroscopy is a type of system that has a different structure and approach from other methods (image processing, neural network, etc.) and can perform classification and determination of digit quality.
With increasing expectations for food products with high quality and safety standards, the need for accurate, fast and targeted determination of the characteristics of food products is now necessary. Because manual methods do not have automatic control, they are very tiring, difficult and expensive, and they are easily affected by environmental factors. Today, spectroscopic systems are non-destructive and cost-effective and are ideally used for routine inspections and quality assurance in the food industry and related products. This technology allows inspection works to be carried out using wavelength data analysis techniques and is a non-destructive method for measuring quality parameters. In this research, the ripening time of walnuts was investigated using spectrometry and chemometrics methods.
In each treatment period (in total 5 periods were considered and the intervals of periods were determined as one week), unripe walnut samples in addition to ripe samples (in the last period) were taken from one of the orchards around Ardabil (located in Shahrivar village) was prepared, tested and data collected.
A spectroradiometer model PS-100 (Apogee Instruments, INC., Logan, UT, USA) was used to acquire the spectrum of the samples. This spectroradiometer is very small, light, portable, has a single-wavelength sputtering type with a resolution of 1 nm and a linear silicon CCD array detector with 2048 pixels that covers the spectral range of 250-1150 nm (Vis/NIR) well. Also, there is the ability to connect the optical fibre to the PS-100 spectroradiometer and transfer the data to the computer with the purpose of displaying and storing the acquired spectra in the Spectra Wiz software through the USB port. With the aim of creating optimal light in contrast mode measurements, an OPTC (Halogen Light Source) model halogen-tungsten light source, which can be connected to an optical fibre, was used. This light source has three output powers of 10, 20, and 30 watts, which were used in this research. Also, a two-branch optical fibre probe model (Apogee Instruments, INC., Logan, Utah, USA), which includes 7 parallel optical fibres with a diameter of 400 micrometres, was used in counter-mode measurements. After providing the necessary equipment, the optimal spectroscopic arrangement was designed and implemented in order to facilitate the experiments and minimize the effect of environmental factors during the spectroscopic process, which is shown in Figure 1.
The average absorption spectra of Vis/NIR absorption spectra for different treatments in the range of 680-970 nm are presented in Figure 1.
Environmental factors (light and heat) as well as the spectrometer's expression quality cause disturbances in the initial and final wavelengths of the spectra, so some of these wavelengths are removed from the data set. And as it is clear in Figure 1, the samples had an almost similar trend; this may be affected by the colour of the samples. According to Figure 1, there are two distinct peaks for the spectra and it is that the peaks appeared around the wavelength of 680 and 970 nm. It can also be seen in Figure 1 that the amount of absorption of ripe walnuts is higher compared to other periods, which can be due to the difference in the content and texture of the product.
Based on the PCA analysis results presented in Figure 2, the first principal component (PC-1) describes 94% and the second principal component (PC-2) describes 5% of the variance of the tested samples. As a result, the first two principal components together express 99% of the data. Considering that it is possible that the degree of correlation between the properties of different samples during the tests, due to various reasons such as technical problems of the equipment, data collection, incorrect sampling, etc., in some samples, inappropriate or so-called outliers.
The values of R2 and RMSE for calibration and validation sets of different regression models (PLS) with raw and processed data are presented in Figure 3, which is equal to 0.98. The results show that the spectra are able to detect the ripening time of walnuts with high accuracy. Khodabakhshian et al investigated the potential of visible and infrared spectroscopy to classify the ripening stage and predict the quality traits of pomegranate varieties including SSC and TA. Among the methods of centring, Savitzky-Golay smoothing, median filter, standard normal variable, incremental spread correction (MSC) and differentiation with first derivative and second derivative, the use of incremental spread correction (MSC) has the highest accuracy in identifying pomegranate quality parameters. followed Zhang and colleagues (Zhang et al, 2018) in estimating the SSC of red Fuji apple using near-infrared spectroscopy to reduce noises using the functions of additive scatter correction (MSC) and standard normal distribution (SNV) and reported that the additive scatter correction method (MSC) compared to the standard normal distribution (SNV) will result in a more accurate estimate of the SSC value. Kim et al. estimated the SSC of oriental melon using near-infrared spectroscopy among different pre-processing methods including Savitzky-Golay smoothing, normalization with maximum and minimum, stable normalization, standardization, stable normal variable, distribution Standard normal (SNV) and incremental spread correction (MSC) reported that the best result was obtained with a standard normal distribution (SNV). Although considering the different nature of the samples, measurement methods and equipment, and other conditions affecting the spectral properties of the product, it is better not to compare the data obtained from different researches with each other.