Prabal K. Ghosh

MAGNETIC RESONANCE IMAGE ANALYSIS TO EXPLAIN MOISTURE MOVEMENT DURING WHEAT DRYING

Two-dimensional (2D) spin-echo magnetic resonance imaging (MRI) was used to explain the moisture movement in single wheat kernels prior to and during drying. Drying was performed at temperatures of 40°C and 50°C using heated N2 gas at a velocity of 0.23 m/s. Individual wheat kernels of 20% to 64% moisture content (wet mass basis) were dried to study the moisture movement inside the kernel during drying. MR images were recorded at equal time intervals during drying. Moisture distribution and transfer were analyzed from MR images of wheat kernels obtained before and during drying. Moisture distribution was non-uniform at an equilibrium state prior to drying. Further, moisture loss from the seed parts differed significantly during drying. The MR images were used to obtain the drying rates and patterns of water in wheat kernels during the drying process. Influence of grain parts on the moisture distribution was also studied using mechanically scarified kernels and germ-removed kernels.

Optimization of Fluidized Bed Drying Process of Green Peas Using Response Surface Methodology

The fluidized bed drying process of green peas was optimized using the response surface methodology for the process variables: drying air temperature (60–100°C), tempering time (0–60 min), pretreatment, and mass per unit area (6.3–9.5 g/cm2). The green peas were pretreated by pricking, hot water blanching, or chemical blanching. Product quality parameters such as rehydration ratio, color, texture, and appearance were determined and analyzed. Second-order polynomial equations, containing all the process variables, were used to model the measured process and product qualities. Rehydration ratio was influenced mostly by pretreatment followed by tempering time, temperature, and mass per unit area. Pretreatment and mass per unit area significantly affected color and texture. Higher levels of temperature and lower levels of tempering time and mass per unit area increased the rehydration ratio. The optimum process conditions were derived by using the contour plots on the rehydration ratio and sensory scores generated by the second-order polynomials. Optimum conditions of 79.4°C drying air temperature, 35.8-min tempering time, pretreatment of the once pricked peas with chemical blanching in a solution of 2.5% NaCl and 0.1% NaHCO3, and mass per unit area of 6.8 g/cm2 were recommended for the fluidized bed drying of green peas. At these conditions the rehydration ratio was 3.49.

Measurement of Water Diffusivities in Barley Components Using Diffusion Weighted Imaging and Validation with a Drying Model

Diffusion-weighted magnetic resonance imaging was used to determine water diffusion coefficients (D) in hull-less barley kernel components (endosperm and embryo) at 20.5±0.5°C. The D values in barley components were time-dependent and restricted in nature as indicated by the decrease in the apparent diffusion coefficient with increasing diffusion time (from 3 to 25 ms). A four-parameter Padé approximation model was used to estimate D and pore geometry (pore surface area–to-volume ratio, pore size, porosity, electrical conductivity and permeability of water) of the barley components after long diffusion time (t → ∞) using data obtained during a relatively short period of diffusion. The D of embryo and endosperm were 2.2±0.07 × 10−5 mm 2 /s and 1.0±0.10 × 10−5 mm 2 /s, respectively. These D values were used to simulate moisture and temperature patterns during the drying of a barley kernel using a two-dimensional simultaneous heat and moisture transfer model and compared with literature D values for validation purposes. Based on the comparison, the D values of barley components obtained from our study can be used to develop realistic models of water transport in barley during different postharvest processing operations (e.g., drying, kilning, steeping).

Enzymatic Hydrolysis of Oilseeds for Enhanced Oil Extraction: Current Status

Enzymatic hydrolysis is a bioconversion process that offers an option for pre-conditioning of oilseeds prior-to conventional oil extraction processes. This pre-treatment breaks down the seeds as it opens up the cell walls by converting the cellulose materials into glucose. It also converts the complex lipoprotein molecules into simple lipid and protein molecules. Therefore, this process helps in obtaining extra oil from various oilseeds (for example, soybean, sunflower, canola, rapeseed, mustard, sesame, peanut). Mathematical models are currently being developed for the kinetics of the enzymatic hydrolysis procedure. Research and development efforts are being carried out to find the proper methodology and optimum processing parameters (for example, solvent, pH, temperature, enzymatic concentration, hydrolysis period) that will enhance both the oil availability and extractability. Aqueous enzymatic extraction is another promising technique where hydrothermal pretreatment is given prior to oil extraction to activate the native enzymes present in the oilseeds and to loosen their structure for the extraction of extra oil with better quality. This paper focuses on the current status of the application of both enzymatic hydrolysis as well as aqueous enzymatic hydrolysis pre-treatments on the oilseeds in view of obtaining enhanced oil yield with high quality indices.

Mass transfer kinetics model of osmotic dehydration of carrots

A model based on mass balance was developed and validated to predict the mass transfer kinetics during osmotic dehydration of carrot slices. Carrot slices, 5 mm thick, were dipped in solutions of salt (three different concentrations: 5%, 10%, and 15%) along with 50°B sugar and 0.1% sodium metabisulphite at 30°C temperature for 10, 20, 30, 40, 50, 60, 90, 120, 150, and 180 min. A sample to solution ratio of 1:5 and a constant agitation of 150 rpm were used. The moisture loss from and solids gain by carrots increased non-linearly with the duration of osmosis at all salt concentrations, and both were higher in the initial period of osmosis than the later period. Further, both increased with increasing salt concentration. The proposed model was able to predict osmosis mass transfer data up to the equilibrium point using data for relatively short period of osmosis.

Magnetic Resonance Image Analysis to explain Moisture Movement in Wheat Drying

Three-dimensional Spin-Echo magnetic resonance imaging (MRI) was used to explain the moisture profile of single wheat kernels prior-to and during drying. Drying was performed at temperatures of 40 and 50oC using heated N2 gas with a velocity of 0.23 m/s. Individual wheat kernels of 20% wet basis moisture content were dried to study the moisture movement inside the kernel during drying. MR images were recorded at equal time intervals during drying. Moisture distribution and transfer were analyzed from spin-echo pulse sequence MR images of wheat kernels obtained before and during drying. Analysis of the images revealed that the moisture distribution was non-uniform at an equilibrium state prior-to drying. Further, moisture losses from the seed parts differed significantly during drying. The images were also used to obtain the drying rates and patterns of water in wheat kernels during the drying process. Keywords. Magnetic resonance imaging, wheat, drying, moisture movement.

Wheat Quality Evaluation

Wheat is the main cereal grain consumed around the world. There are many classes of wheat grown around the world. Each class of wheat is used for specific processed products such as pasta, noodles, bread, and confectionary items. Wheat quality can deteriorate during the growing period, as well postharvest, due to improper handling and storage conditions. Deterioration could be minor with minimal changes for human consumption to severe when wheat becomes unfit for human consumption. The mixing of classes of wheat causes issues in the processing industry and reduces the quality of the processed products. Poor quality wheat also cannot produce high quality finished products. Therefore tools are needed to assess the quality of wheat, as well as to identify interclass contamination or contamination by foreign objects. This chapter describes different imaging techniques which can be used to assess classes of wheat, as well as quality of wheat at any stage from harvest to processing.

Use of Spectroscopic Data for Automation in Food Processing Industry

Advances in spectroscopy now enable researchers to obtain information about chemical and physical components in the food/biological materials at the molecular level. Various spectroscopic techniques (e.g., atomic absorption spectroscopy, Raman and FTIR spectroscopy, NIR spectroscopy, NMR spectroscopy, mass spectroscopy, X-ray fluorescence spectroscopy, UV spectroscopy) have been used to study structure-function relationships in foods (both liquid and solid) to improve overall food quality, safety and sensory characteristics; to investigate fungal infections in plant materials (fruits, seeds etc.); or to study mobility of different chemical components in food materials. Processing, analyzing, and displaying these data can often be difficult, time-consuming, and problem-specific. Chemometrics is well established for calibrating the spectral data to predict concentrations of constituents of interest. Similarly, proteomics deals with the structure-function relationship of protein molecules. Since most of the food processing industries are becoming increasingly automated, there is a need to understand how the spectroscopic data can be used for automation. In this paper, we have provided basic working principles of the above mentioned spectroscopic techniques, examples of the use of spectral data in food processing, methods of analysis of spectral data and their integration in the automation process.

Magnetic Resonance Imaging Study of Moisture Movement during Pigeon Pea (Cajanus cajan L.) Cooking

Magnetic resonance imaging (MRI) has been used to non-invasively study the moisture movement inside the pigeon peas during cooking to quantify the cooking process and to investigate the intrinsic factors responsible for cooking. Both pre-soaked (in water for 20 min) and non-soaked pigeon peas were cooked in boiling water for 25 min for MR image analysis. Cooked pigeon peas were imaged at 5 min intervals to study the water distribution and transfer pattern during cooking. Results showed a homogenous distribution of water inside the pigeon peas with a high moisture region generated at the surface at the onset of cooking and a moisture-front that moved inward with increasing cooking time. Variations in the water distribution implied different mechanisms for water influx.

Non-Destructive Measurement of Moisture Pattern Using MRI in A Wheat Kernel during Drying

Three-dimensional (3D) spin-echo magnetic resonance imaging (MRI) was used to study the moisture pattern in single wheat kernels during drying. Drying was performed at temperatures of 40 and 50oC using heated N2 gas with a velocity of 0.23 m/s. Individual wheat kernels of 20-64% wet mass basis moisture content were dried to study the moisture movement inside the kernel during drying. MR images were recorded at equal time intervals and moisture patterns were analyzed from the MR images of wheat kernels. Analysis of the images revealed that moisture loss from the seed parts differed significantly during drying. Influence of grain parts on the moisture distribution was also studied using mechanically scarified kernels and germ-cut kernels.