Browsing by Author "Sabat, Mousumi"
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ThesisItem Open Access Digital Image Processing based System for Real-Time Monitoring of Potato Slices in Hot Air Dryer(ICAR-INDIAN AGRICULTURAL RESEARCH INSTITUTE NEW DELHI, 2021) Sabat, Mousumi; Kotwaliwale, NachiketDrying, is one of the most common primary shelf-life enhancing technique. However, the process causes many sensorial, physical and mechanical changes in the food products, presently being evaluated by human observers or offline chemical methods for quality detection. However, these measurements are tedious, time consuming and subjective in nature. Assessment of the qualitative changes taking place during drying using computer vision system provides better alternative for process monitoring and control since it is rapid, inexpensive, non-destructive, sensitive, and precise. The computer vision system (CVS) includes five primary steps viz., image acquisition, image processing, feature extraction, pattern recognition and decision making. Previously, researchers were using different software for image acquisition and offline image processing. Whereas with online monitoring of the drying phenomena, changes in its size, shape, colour, texture, etc. can be studied and monitored as they are complexly dependent on each other as well as on the drying parameters. A laboratory scale dryer was developed and enable with sensors, controls and air distribution systems to ensure uniform distribution of temperature and air flow throughout the chamber. To visualize the colour, texture and morphological changes during drying progression, the dryer was equipped with an image acquiring system. In the current study experiments were conducted on drying of potato slices. Drying was monitored on real-time basis during at 4 levels of the drying air temperature (T) i.e., 45, 50, 55 and 60 °C, 3 levels of potato slice thickness (L) i.e., 1, 2 and 3 mm and 1.5 m/s of air velocity. The sample weight data was recorded till constant weight was achieved. An image acquisition system consisted of four principal components viz., camera, illumination, hardware and software. The images were processed using the algorithms written in MATLAB® platform. Image features were extracted to obtain the various quality related parameters (colour, image texture and product morphology) about the object of interest. Broadly image features can be classified into two main categories viz., external and internal. The internal image features include the chromatic and image textural features whereas the external features include the morphology of the product. 93 For studying the time series data of the image properties at different temperatures and slice thicknesses; recurrent neural network (RNN) was used that predicts the future while using the past data. Since three categories of image properties, viz., morphological, chromatic and textural properties, were studied; initially the attributes from each property were used as an input to the network to observe the predictability of the output (moisture content) and later the combinations of two and all three properties were used. Additionally, different number of nodes, number of hidden layers, transformation function and training algorithm used were determined, on hit and trial basis, since it depended on the complexity of the problem to be investigated. Using the best RNN (that has highest R2 value and lowest MSE as well as MAPE value) the algorithm was developed with the intent of creating a graphical user interface (GUI). The developed GUI helped in simplifying communication of information between the system and operator, being user friendly. To check the efficiency of the developed algorithm, the moisture content of the product displayed during drying was compared with the moisture content obtained from the sample weight (manually recorded). All morphological parameters considered in this study, except eccentricity and roundness, decreased smoothly till normalised moisture content (NMC) is equal to 0.25 and then declined rapidly. The roundness and eccentricity values increased after NMC0.97). In RNN 3, the network consisting of three hidden layers with 15-5-10 number of nodes in first, second and third hidden layers, respectively was selected as optimal topology to predict the moisture content of the potato slices during drying. In order to evaluate the performance of the developed algorithm on real time basis, the drying data were taken manually and compared with the moisture content predicted by the developed algorithm at 47, 54 and 58 °C for slices of thickness 2, 1 and 3 mm, respectively. The statistical parameters R2 (0.9981, 0.9991 and 0.9957), MSE (2.77 × 10-4, 1.62 × 10-4 and 8.88 × 10-4) and MAPE (0.0708, 0.3668 and 0.2242) indicated that the developed network as well as the algorithm perform efficiently.ThesisItem Open Access DRYING CHARACTERISTRICS OF ALOE VERA AND ITS MATHEMATICAL MODELLING(Indira Gandhi Krishi Vishwavidhyalaya, Raipur, 2017) Sabat, Mousumi; Patel, S.; Mishra, N. K.; Varma, Ajay; Saxena, R. R.; Pisalkar, P. S.Aloe vera (Aloe barbadensis Miller), is a short-stemmed juicy plant with green pointed and fleshy leaves entrapping a clear viscous gel. It can achieve a stature of 10-20 m with a girth up to 3 m. The annually produced flowers are orange in colour with the spikes reaching up to 90 cm tall. In India, the major areas under aloe vera cultivation are Alwar in Rajasthan, Satnapalli in Andhra Pradesh and Rajpipla in Gujarat. It is also found in the dry areas of states of Maharashtra and Tamil Nadu. The annual consumption of aloe vera extract by the Indian pharmaceutical industries is 200 tonnes which is met from the wild sources from the states of Maharashtra and Tamil Nadu. Ayurvedic pharmacies are using only 1% of the total production from India. The use of aloe vera in the pharmaceutical industry is significant as far as the manufacturing of tropical ointments, gel preparation, tablets and capsules are concerned. The challenge of aloe vera drying is to maximize the retention of nutrients while minimizing the moisture content of product to a level where microbiological growth should not occur. The physical characteristics of the aloe vera namely, length, width, thickness, apparent volume, leaf weight, gel weight and gel recovery were determined. The mean values of the length, width and thickness were found to be 551.18, 87.75 and 23.20 mm respectively, the average apparent volume and average weight of aloe vera leaf was found to be 291.88 cc and 344.18 g respectively. It was observed during the experiment that the aloe vera leaves having higher weight, had recorded better gel recovery. The chemical properties of the dried aloe vera sample were determined namely, yield, pH, total carbohydrate, total starch, crude fat, crude fibre, total ash and protein. The rehydration characteristic of aloe vera gel was predicted from two parameters viz. rehydration ratio (RR) and water holding capacity (WHC). It was found that the sample dried at 70oC temperature exhibited better chemical and rehydration characteristics. The fresh aloe vera samples were convectively dried at air temperature of 50, 60, 70 and 80oC and their drying behavior were investigated. The initial moisture content of the aloe vera samples was calculated to be 7042.85 per cent (db). After drying till constant weight was achieved, the moisture content was reduced to the range of 12.06 to 15.20% (db) for temperatures 80-50 oC. It was observed that, the moisture content of aloe vera samples decreased exponentially with drying time under all drying temperatures and for all experiments. The drying time required for higher temperature drying was less than that of low temperature drying. The coefficient of determination was more than 0.95 showing good correlation between the data collected. The convective drying of aloe vera samples followed a typical trend. As the drying air temperature increased, the drying curves exhibited steeper slope indicating that the drying rate increased with increase in drying air temperature. The equilibrium moisture content of aloe vera sample at different temperatures used in the drying experiments was obtained using dynamic method. The influence of moisture content on effective moisture diffusivity and to estimate the activation energy for different drying air temperatures, further analysis of the falling rate drying period was carried out to estimate effective moisture diffusivity (Deff). It is observed that moisture diffusivity values increased with drying air temperature. The Deff increased with decrease in moisture content for all drying temperatures. The Deff started decreasing as the moisture content decreased further below at the end of drying.The activation energy and Arrhenius factor was found to be 19.83 kJ/mol and 1.98 x 10-07 respectively. It is implied from the figure that moisture diffusivity of aloe vera sample decreased linearly with increase in 1/T.