A. Manickavasagan

Non-Uniformity of Surface Temperatures of Grain after Microwave Treatment in an Industrial Microwave Dryer

In this study, temperature rise and non-uniformity of heating of grain with different moisture contents after microwave treatment were investigated. The temperature anomalies after microwave treatment were measured for barley and wheat at four moisture levels (12, 15, 18, and 21% wet basis) and for canola at five moisture levels (8, 12, 15, 18, and 21% wet basis). Fifty grams of grain samples were heated in a laboratory scale, continuous-type, industrial microwave dryer (2450 MHz) at five power levels (100, 200, 300, 400, and 500 W) and two exposure times (28 and 56 s). Grain samples were thermally imaged using an infrared thermal camera as soon as they came out from the microwave chamber. Average, maximum, and minimum temperatures were extracted from each thermal image and the difference between maximum and minimum temperatures (ΔT) was calculated. The grain type had significant effect on the surface temperatures after microwave treatment. The surface temperatures increased with microwave powers and exposure times but decreased with moisture content. The average surface temperatures after microwave treatment were between 72.5 and 117.5°C, 65.9 and 97.5°C, and 73.4 and 108.8°C for barley, canola and wheat, respectively, when the applied microwave power was 500 W. At the same power level, the maximum surface temperature was between 100.3 and 140.0°C, 77.8 and 117.7°C, and 98.3 and 130.9°C for barley, canola, and wheat, respectively. Non-uniform heating patterns were observed for all three grain types at all moisture contents, power levels, and exposure times. The ΔT was in the range of 7.2 to 78.9°C, 3.4 to 59.2°C, and 9.7 to 72.8°C for barley, canola, and wheat, respectively. The location of hot and cold spots may vary in different dryers based on the position of magnetron and other components, but almost similar non-uniform heating pattern is expected in all microwave dryers. Therefore, this non-uniformity must be taken into consideration while developing microwave processing systems for grains.

Thermal Imaging of a Stored Grain Silo to Detect a Hot Spot

A hot spot is a localized high temperature zone in a grain bulk and normally spoilage begins in this location. Many sensors need to be installed throughout the bin to detect hot spots by measuring grain temperature. A non-contact method to detect a hot spot in a stored grain silo would be beneficial. The capability of thermal imaging to detect a hot spot in an experimental silo (galvanized steel, 1.5-m diameter and 1.5-m height) filled with barley was studied. An artificial heat source was placed at nine locations inside the grain bulk and set at four temperature levels (30°C, 40°C, 50°C, and 60°C) in each location. The outer surface of the silo wall and the top surface of the grain bulk were thermally imaged up to 48 h at each treatment (n = 3). The temperature of the top surface of the grain bulk was significantly (a = 0.05) higher (0.4°C to 2.6°C) than the atmospheric temperature after 48 h of hot spot establishment. The hot spot was detected from the thermal images of the silo wall and grain bulk (as a high temperature region) when it was located 0.3 m from the silo wall and 0.3 m below the grain surface, respectively. The hot spot was not detected on the thermal images of the silo wall when the wind velocities were 1.0, 1.5 and 2.0 m/s, and immediately after wind (n = 3). Similarly, thermal imaging did not detect the hot spot on the grain bulk when the ambient temperature was 1°C (hot spot = 30°C), and on silo wall when the ambient temperature was -8°C (hot spot = 60°C) (n = 3). The surface temperature of the grain bulk decreased with increasing moisture content. It was 25.8°C, 24.3°C, 23.4°C, 22.8°C, and 22.4°C for the grains with 8%, 12%, 16%, 20%, and 24% moisture content, respectively, when the room temperature was 26°C (n = 20). Thermal imaging can not be used as an independent method to monitor the grain temperature in a silo.

Segmentation of Wheat Grains in Thermal Images Based on Pulse Coupled Neural Networks

Canada is one of the major exporters of wheat in the world. The quality of these exports is well known and factors such as lack of insect infestation are very important. The use of thermal images for subsequent analysis of temperatures profiles for grain classification and insect detection is a method under investigation. This paper presents an approach for automatic image segmentation of the wheat kernels based on the combined use of wavelet analysis and pulse coupled neural networks. It is shown that using wavelets as a preprocessing technique yields a consistent accurate segmentation in terms of the iteration number in which the network yields reliable edges of the wheat kernels. Subsequent analysis of these segmentations can determine internal qualities such as infestations.

Thermal Imaging to Identify Western Canadian Wheat Classes

Varietal purity is one of the important factors in grain grading. In the laboratory, wheat classes and varieties are determined by trained professionals. For online classification of wheat classes and varieties, several approaches have been made with image processing technology, but the classification efficiency was poor and inconsistent. The capability of thermal imaging system for the identification of wheat classes was investigated. In this study, eight classes of western Canadian wheat were subjected to heating and cooling treatments. During treatment, the sample was heated or cooled one kernel at a time and then surface temperatures were imaged with the thermal camera. In both treatments, the temperature profiles were dissimilar for all classes. The rate of heating and cooling of the germ end was slower than that of other parts of the kernel for all classes. The average temperature of the kernel was in the range of 37.1 (CPSW) to 45.6oC (CWRS) during heating and 18.9 (CWRW) to 22.3oC (CWAD) during cooling treatments. The temperature difference between kernel average and germ average was 1.7 to 4.1oC in heating and 0.8 to 1.6oC in cooling treatments. The performance of this system must be studied for bulk grain to evaluate the suitability for online application in grain handling facilities.