مقالات رزومه دکتر مجتبی نادری بلداجی

Sugarcane, an important crop in sugar production in the country, is widely produced in Khuzestan province. After harvesting the sugarcane and when delivered to the sugar factory, the cane is shredded. In this study, for measurement of sucrose concentration in shredded cane, the dielectric spectroscopy technique in the frequency range of 0-100 MHz was evaluated using a cylindrical parallel-plate sensor with compaction of the shredded cane. 55 samples of shredded cane were taken from the sugar production line of Salman Farsi factory during the harvesting season of 2021-2022 and their reference properties including sugar concentration with three indicators of Brix using refractometry method, Pol using simple polarimetry method and the sucrose measured using double polarimetry were measured. The samples were subjected to dielectric spectroscopy using the capacitance sensor and the dielectric spectra were analyzed for sugar concentration prediction. Multivariate regression analyses of partial least-sugare regresseion (PLSR), principal component regression (PCR) and support vector regression (SVR) were applied for development of prediction models of sugar concentration variables. Validation of the prediction model of PLSR showed a stronger prediction of sucrose (R2= 0.79, RMSE= 0.89, RPD= 2.22) measured using the double-polarimetry as compared to Pol (R2= 0.76, RMSE= 0.8, RPD= 2.07) and Brix (R2= 0.77, RMSE= 0.89, RPD= 2). This result was explained with higher number of OH groups of sucrose molecule as compared to the other sugars existing in the sugarcane juice and the dominant effect of sucrose on the dielectric characteristics of the juice. With optimization and improvement of the accuracy of this method, a simple and cost-effective instrument can be developed for use in sugar industries.

Determination of sugar concentration of sugar beet in sugar factories is of great importance and is a basis for valuation of the sugar beet as well as assessment of the sugar production process in the factory. In this study with the aim of development of a non-destructive method for measurement of the sugar concentration of sugar beet in terms of Brix, a proximal dielectric sensor was developed and evaluated. This sensor is an open-end coaxial probe consisting of two metallic concentric ring electrodes which is connected to function generator and spectrum analyzer through coaxial cables. One hundred random samples of sugar beet were selected and measured by the dielectric sensor. Dielectric spectra i.e. amplitude as a function of frequency were obtained in the frequency range of 0-150 MHz. The reference Brix was measured with extracting juice from the points of dielectric measurement using a refractometer. The results showed that in the ranges of 30-50 and 120-140 MHz, the dielectric spectra varied noticeably in relation with variations in sugar beet Brix so that the amplitude decreased with increasing the Brix. The partial least square regression (PLSR) method could model the Brix as a function of the dielectric spectra variables with R2= 0.81 and RMSE of 0.72 Brix. The results of the study indicated that the dielectric sensor and measurement method was a simple and reliable method for non-destructive measuring of sugar beet Brix.

The photoacoustic method is a sensing technique resulting from combination of optical and ultrasonic methods. The photoacoustic effect is the product of local heating with absorption of light energy, instantaneous expansion of matter and generation of pressure and sound propagation in the matter. In this study, in order to develop a photoacoustic spectroscopy system with LED light sources, in the first step, the photoacoustic interaction with a cuvette filled with liquid was simulated using Comsol Multiphysics 5.5. In the second step, a photo-acoustic spectroscopy system with light sources at eight wavelengths from 395-940 nm was designed and constructed. Finally, in order to evaluate the photoacoustic system, three samples i.e. milk, water and olive oil were subjected to photoacoustic spectroscopy and the measurement results were compared with the simulation results for the same samples. The results showed that the intensity of the acoustic response of the samples at different wavelengths varied significantly with the light absorption coefficient, so that the maximum amplitude of the acoustic signal was obtained for milk, water and olive oil at the wavelengths of 450, 395 and 450 nm with values of 0.34, 0.22 and 0.74 Pa, respectively. This was in agreement with the simulation results in terms of relative differences. Moreover, the adulteration of adding water to milk at volume ratios of 5, 10, 15 and 20% was evaluated with the system and analyzed with principal component analysis (PCA) which showed a satisfactory discrimination of adulterated samples from pure milk. The system developed in this study can be used to assess the quality of food liquids.

Cone penetration test is one of the methods widely used for measuring the soil mechanical strength. It can also be used as a simple method to calibrate soil parameters in the discrete element method (DEM) simulations. In this study, a DEM model for the interaction of a cone penetrometer with a clay loam soil was developed and the possibility of finding relationships between the cone index and the parameters of the model for different levels of moisture and soil density was investigated. A hybrid contact model, hysterical spring - linear cohesion was used to simulate the soil. Sensitivity analysis of the model parameters showed cohesion, coefficient of internal friction and particle yield strength are the most important parameters affecting the cone index. Laboratory cone penetration tests using a tension-compression loading frame were performed in remolded soil at two moisture contents of 11 and 16% each at two bulk densities of 1000 and 1150 kg m-3. By fitting the measured and simulated cone index- depth profiles, values ​​for particle yield strength were obtained which showed a strong correlation (R2 = 0.97) with the maximum cone index in the tested soils. The results were validated using plate sinkage test. As a general conclusion, the cone penetration test can be used to calibrate the yield strength of soil particles in the discrete element simulations.

< p >< p >< p >One of the most important ingredients of most foods is sugar, so it is important to detect the type of sugar in foods. In this study, a cylindrical dielectric sensor using a function generator and a spectrum analyzer was used to measure dielectric spectra in the range of 0-150 MHz to detect different sugars in water-sugar solutions. Dielectric spectra were investigated by preparing a variety of water-sugar solutions including glucose, sucrose, fructose, invert, high fructose corn syrup and malt extract (dominantly maltose sugar) in four brix levels ranged within 3-12. Moreover, samples were tested with mixing the sugars in a solution. The statistical method of principal component analysis (PCA) was evaluated for detecting and discriminating different types of sugars from dielectric spectral data. PCA with two principal components PC1 and PC2, showed a distinct separation of sugars in three visual groups of sucrose and high fructose corn syrup, fructose and invert and glucose and malt. Irrespective of glucose, the mixed sugar solutions were discriminated from single sugar solutions in two groups. The results of this study showed a promising potential of dielectric method for detecting different sugars, however, the cumulative dielectric effect of the mixed sugars was not discriminable which is expected to be detected with greater range of frequency.

In this study, three harvesting methods of sugar beet, including semi-mechanized, multi-stage mechanized and single-stage mechanized (by combine) in Khorasan Razavi province (Jovein town) were compared from the view of some technical factors. The total losses of sugar beet, including the weight of cut crown beets, damaged beets and unharvested healthy beets were 1944 kg ha-1 (i.e. 3% of yield), for for multi-stage method; for  single-stage and semi-mechanized methods this figure reduced to 542 and 454 kg ha-1 respectively. The highest increase in soil compaction in terms of cone index was measured for the single-stage method followed by the multi-stage method. The fuel consumption in the single-stage and semi-mechanized methods were 25% and 33% of the fuel consumption in multi-stage mechanized method. Energy consumption in single-stage and semi-mechanized methods was  less than what had been consumed in  multi-stage method,  24% and 34% respectively. Results also showed that single-stage mechanized (combine) harvesting method, compareing with two other methods, had relative advantages, except in soil compaction, for which some technical optimizations would be needed.

One of the important concerns regarding the food safety is widespread adulteration in food production which necessitates the development of precise and rapid diagnostic instruments more than ever. In this study, a cylindrical resonator sensor, developed in previous studies and examined for quality detection of some food materials, was applied for detection of adulteration in sesame oil mixed with corn, canola and sunflower oils. To measure the dielectric response of oil in 0-150 MHz frequency range, a new sensor with 400 mm long cylinder was fabricated. Adulteration samples were prepared with mixing pure sesame oil with the above mentioned oils at 15, 30 and 45% by weight and each sample was measured with three replications using the dielectric sensor. Statistical methods of principal component analysis (PCA), linear discriminant analysis (LDA) and support vector machine (SVM) were evaluated for detection of adulteration type and level from the dielectric spectral data. The biplot of the first two principal components showed excellent discrimination of adulteration type and level with 96% of variation explanation. As the best result, LDA classifier showed 96.7% accuracy for adulteration detection.

To manage the traffic-induced soil compaction in a field, the applied stress on soil with machinery traffic needs to be controlled below the soil bearing capacity (i.e. precompression stress, σpc) to prevent increase in soil compaction. Precompresson stress is primarily a function of soil moisture and secondarily soil texture. This study aimed at developing an empirical -analytical algorithm for daily prediction of soil precompression stress in a selected field at Shahrekord University. Statistical analyses showed that using the meteorology variables of each year including the precipitation of the target day and its previous day, temperature, radiation and wind velocity, daily changes in soil moisture could be well predicted (R2 = 0.85, RMSE= 3.3%). To determine the relationship between the soil moisture and precompression stress, remolded soil samples were prepared at three bulk densities of 1.15, 1.22 and 1.3 Mg m-3 and four moisture levels of 10, 15, 20 and 25% and subjected to stepwise confined compressive stress. Precompression stress was estimated at the point of maximum curvature on the void ratio- log stress curves with fitting Gompertz function. In addition, the analytical model of Elbanna & Witney (1987) was tested for extending the results to different soil textures using an empirical relation between cone index and precompression stress. The results showed that the model predicts well the variations in precompression stress as affected by soil moisture. The algorithm developed in this study can be implemented in managing the machinery traffic and predicting the trafficable days of each year.