Applications of Non-destructive Technologies for Agricultural and Food Products Quality Inspection.

The quality and safety of food is an increasing concern for worldwide business. Non-destructive methods (NDM), as a means of assessment and instrumentation have created an esteemed value in sciences, especially in food industries. Currently, NDM are useful because they allow the simultaneous measurement of chemical and physical data from food without destruction of the substance. Additionally, NDM can obtain both quantitative and qualitative data at the same time without separate analyses. Recently, many studies on non-destructive detection measurements of agro-food products and final quality assessment of foods were reported. As a general statement, the future of using NDM for assessing the quality of food and agricultural products is bright; and it is possible to come up with interesting findings through development of more efficient and precise imaging systems like the machine vision technique. The present review aims to discuss the application of different non-destructive methods (NDM) for food quality and safety evaluation.

Rapid detection of rice disease using microscopy image identification based on the synergistic judgment of texture and shape features and decision tree-confusion matrix method.

BACKGROUND: Rice smut and rice blast are listed as two of the three major diseases of rice. Owing to the small size and similar structure of rice blast and rice smut spores, traditional microscopic methods are troublesome to detect them. Therefore, this paper uses microscopy image identification based on the synergistic judgment of texture and shape features and the decision tree-confusion matrix method. RESULTS: The distance transformation-Gaussian filtering-watershed algorithm method was proposed to separate the adherent rice blast spores, and the accuracy was increased by about 10%. Four shape features (area, perimeter, ellipticity, complexity) and three texture features (entropy, homogeneity, contrast) were selected for decision-tree model classification. The confusion-matrix algorithm was used to calculate the classification accuracy, in which global accuracy is 82% and the Kappa coefficient is 0.81. At the same time, the detection accuracy is as high as 94%. CONCLUSIONS: The synergistic judgment of texture and shape features and the decision tree-confusion matrix method can be used to detect rice disease quickly and precisely. The proposed method can be combined with a spore trap, which is vital to devise strategies early and to control rice disease effectively. © 2019 Society of Chemical Industry.

Performance of a convective, infrared and combined infrared- convective heated conveyor-belt dryer.

A conveyor-belt dryer was developed using a combined infrared and hot air heating system that can be used in the drying of fruits and vegetables. The drying system having two chambers was fitted with infrared radiation heaters and through-flow hot air was provided from a convective heating system. The system was designed to operate under either infrared radiation and cold air (IR-CA) settings of 2000 W/m(2) with forced ambient air at 30 °C and air flow of 0.6 m/s or combined infrared and hot air convection (IR-HA) dryer setting with infrared intensity set at 2000 W/m(2) and hot at 60 °C being blown through the dryer at a velocity of 0.6 m/s or hot air convection (HA) at an air temperature of 60 °C and air flow velocity 0.6 m/s but without infrared heating. Apple slices dried under the different dryer settings were evaluated for quality and energy requirements. It was found that drying of apple (Golden Delicious) slices took place in the falling rate drying period and no constant rate period of drying was observed under any of the test conditions. The IR-HA setting was 57.5 and 39.1 % faster than IR-CA and HA setting, respectively. Specific energy consumption was lower and thermal efficiency was higher for the IR-HA setting when compared to both IR-CA and HA settings. The rehydration ratio, shrinkage and colour properties of apples dried under IR-HA conditions were better than for either IR-CA or HA.

A study into how thickness, infrared intensity, and airflow affect drying kinetics, modeling, activation energy, and quality attributes of apple slices using infrared dryer.

Drying is a widely recognized process that reduces the need for storage and shipping weight, keeps free water out of the product, and prolongs its shelf life. An infrared dryer was designed to dry apples under different drying conditions. Apple slices of 6-, 4-, and 2-mm thicknesses were dried at intensities 0.130, 0.225, and 0.341 W/cm2 and airflow 1.0, 0.5, and 1.5 m/s. The dehydrating period was prolonged with higher airflow and shortened with higher infrared intensity (IR). The shortest dehydrating period was verified by 190 min at 0.341 W/cm2, 0.5 m/s under 2 mm thickness. Increasing the sample thickness from 2 to 4 mm and then to 6 mm resulted in an 84% and 192% increase in drying time, respectively. Dehydrated apples had water activity values ranging from 0.30 to 0.40. The shrinkage ratio increased with an increase in infrared radiation intensity. However, it decreased with an increase in air velocity, while the rehydration ratio decreased with an increase in radiation intensity and increased with an increase in air velocity. Regarding total color change, apple slice thickness was a major factor. The effective diffusivities varied between 2.6 and 9.0 𝗑10-10 m2/s under different drying conditions. The dehydrating curves of apples were best described by the model developed by Midilli et al.

Mathematical modeling of thin-layer drying kinetics and moisture diffusivity study of apple slices using infrared conveyor-belt dryer.

The drying features of apples at different infrared drying settings were investigated. The drying time, moisture-effective diffusion, and activation energy of infrared dried apples were measured experimentally and statistically as a function of slice thicknesses, radiation intensity, and air velocity. The infrared intensity of 0.225, 0.130, and 0.341 W/cm2 , slice thicknesses of 6, 4, and 2 mm, and airflow of 0.5, 1.0, and 1.5 m/s were used to dry apple slices. The data shows that the drying time reduced as IR increased, but airflow and slice thickness increased. Eight statistical factors were used to compare 11 alternative mathematical drying models. The experimentally acquired drying curves were matched to the thin-layer drying equations. According to the calculations, the Midilli et al. equation had the greatest (efficiency and R2 ) and lowest (χ2 , sum of squared errors, standard error of estimate, standard error, standard deviation of difference) values. As a result, this equation is the best for modeling the drying curves of apple slices across all drying circumstances. The optimum moisture diffusivity value varied from 2.59 to 9.07 × 10-10  m2 /s. The mean activation energy was determined to be 19.02-29.83 kJ/mol under various experimental conditions.

Artificial intelligence as a tool for predicting the quality attributes of garlic (Allium sativum L.) slices during continuous infrared-assisted hot air drying.

Effective drying methods are a highly suitable solution for ensuring stable food supply chains, reducing postharvest agricultural losses, and preventing the spoilage of perishable fruits and vegetables. Moreover, machine learning techniques are innovative and dependable, especially in addressing food spoilage and optimizing drying processes. This study utilized a continuous infrared (IR) hot air dryer to dry garlic (Allium sativum L.) slices. The experiments were conducted at different levels of IR power, air velocities (V), and temperature (T). The relationships between the input process parameters (IR, T, and V) and response parameters, including effective moisture diffusivity (Deff), drying time, and physicochemical properties of the dried slices (rehydration ratio [RR], total color change, flavor strength, and allicin content in the garlic), were modeled using an artificial neural network (ANN). Our findings showed that the maximum Deff of 6.8 × 10-10 m2/s and minimum drying time of 225 min were achieved with an IR of 3000 W/m2, an air velocity of 0.7 m/s, and a temperature of 60°C. The total color change and RR values increased with IR and higher air temperature but declined with higher air velocity. Furthermore, the garlic's flavor strength and allicin content levels decreased as the IR and air temperature increased. The results demonstrated a significant influence of the independent parameters on the response parameters (p < 0.01). Interestingly, the ANN predictions closely matched the test data sets, providing valuable insights for understanding and controlling the factors affecting drying behaviors.

Bio-Optimization of Chemical Parameters and Earthworm Biomass for Efficient Vermicomposting of Different Palm Oil Mill Waste Mixtures.

The present study reports mathematical modelling of palm oil mill effluent and palm-pressed fiber mixtures (0% to 100%) during vermicomposting process. The effects of different mixtures with respect to pH, C:N ratio and earthworms have been optimized using the modelling parameters. The results of analysis of variance have established effect of different mixtures of palm oil mill effluent plus palm press fiber and time, under selected physicochemical responses (pH, C:N ratio and earthworm numbers). Among all mixtures, 60% mixture was achieved optimal growth at pH 7.1 using 16.29 C:N ratio in 15 days of vermicomposting. The relationship between responses, time and different palm oil mill waste mixtures have been summarized in terms of regression models. The obtained results of mathematical modeling suggest that these findings have potential to serve a platform for further studies in terms of kinetic behavior and degradation of the biowastes via vermicomposting.

Current status and future perspectives of solid waste management in Iran: a critical overview of Iranian metropolitan cities.

By growing urban population, Iran faces numerous environmental issues and solid waste management is on the top of these problems. Studies showed that a daily average of 700-1000 g of wastes are produced per person in Iran, in which organic waste accounts for a significant amount. On the other hand, hospital waste represents a part of the wastes, which need careful consideration from the environmental point of view. In the present study, the amount, composition, and management of urban and hospital wastes were evaluated in 7 Iranian metropolises, which account for about 30% of the population and produce about 35% of the country wastes. Based on prior surveys, landfill method is the current main method for waste management in these cities, which is generally not completely sanitary and therefore causes many environmental problems. The other common methods for waste management in these cities are composting of organic wastes, and the use of waste conversion methods to energy. However, the latter is ongoing only in Tehran which also includes some limitations. Therefore, the study also evaluated the future perspectives and feasibility of waste-to-energy conversion as a promising economic route for waste disposal.

Effect of infrared drying with multifrequency ultrasound pretreatments on the stability of phytochemical properties, antioxidant potential, and textural quality of dried sweet potatoes.

The study aims to determine drying of sweet potatoes using multifrequency ultrasound (US) pretreatments (20, 40, and 60 kHz) at three different infrared (IR) drying temperatures (60, 70, and 80°C) and evaluate the phytochemical and textural quality of the dried product. Drying time was significantly decreased in moderate US frequency (40 kHz) at 70°C with the increasing drying temperature. Comparing to the fresh samples, the dried samples showed the highest amount of phytochemical contents. The antioxidant activity of the samples increased especially at 60 kHz and 80°C, while US-IR treatments shown a positive impact on total carotenoids contents and ß-carotene. For phenolic compounds, Ellagic acid and Rutin were quantified in higher amount while Quercetin-3-rhamnoside and Quercetin 3-ß-D-glucoside were two new compounds identified for the first time in sweet potatoes. FTIR spectra showed the successful synthesis of OH group and phenolics in samples treated with the US at 20 kHz. PRACTICAL APPLICATIONS: This study investigated the effects of multifrequency ultrasound with different infrared drying temperatures. The study provides evidence that infrared drying application in synergy with ultrasonic pretreatments can improve drying efficiency and food quality much better than using each method alone. Total phenolic contents and total flavonoid contents remained stable at US 40 kHz and 60°C conditions. The findings showed that moderate ultrasound frequency (40 kHz) at 60°C improved phytochemical properties while antioxidant activities showed better preservation response at 80°C with 60 kHz. In addition, the samples treated with the same US treatment at 40 kHz showed less cell breakage in SEM analysis.

Thin-layer drying characteristics, modeling and quality attributes of tomato slices dried with infrared radiation heating

An Infrared dryer was used to examine the drying of tomato slices. In this investigation, the influence of infrared radiation (IR) on the rate of drying, physical quality, energy combustion of tomato was estimated at three different levels of intensity at 0.15, 0.20, and 0.35 W/cm² under different air flows of 0.5, 1, and 1.5 m/s. Tomato slices were dried with an initial moisture content of 19.7 to 0.17 g water/g dry solids by infrared drying. The moisture content and drying rates are found to be dramatically affected by infrared density. An increase in the drying rate and a decrease in the drying period occurred with increasing infrared intensity. A decrease in energy consumption was detected with the increase of radiation intensity. The results clarified that the shrinkage ratio increased with increasing infrared intensity. The rehydration ratio raised with the increase in radiation intensity. The change in the colour difference of dried slices increased with an increase in radiation intensity. The models were in comparison using (R²) coefficient of determination, modelling efficiency (EF), and (χ²) reduced chi-square. Midilli model was fit for simulation of all drying conditions and could be used to estimate tomato moisture content at any time during the infrared drying process.