PREDICTION OF AFLATOXIN CONTAMINATION ON DRIED FIG (FICUS CARICA) SAMPLES BY SPECTRAL IMAGE ANALYSIS IN COMPARISON WITH LABORATORY RESULTS

WOS: 000427344600006Aflatoxins are toxic metabolites produced by some fungus (Aspergillus flavus and Aspergillus parasiticus) that can grow on a wide variety of foodstuffs. The most important factors that play a role in the growth of fungi in foodstuffs and in the formation of aflatoxin are relative to the humidity of the air and the storage temperature. It is also pointed out that aflatoxin, which is passed to humans through food, causes mostly liver cancer, increases the effect of hepatitis (B) and (C) viruses, and breaks the immune system. Traditionally, dried figs have been examined for the evidence of bright greenish-yellow fluorescence (BGYF), which can indicate the possible presence of Aspergillus flavus, when illuminated with ultra-violet (UV) light. The BGYF test is typically the first step that leads to a chemical analysis for possible aflatoxin contamination. Naturally, the chemical methods that detect aflatoxins are quite accurate but expensive and destructive. Nowadays, hyperspectral and multispectral imaging are becoming increasingly important for rapid and nondestructive testing for the presence of such contaminants. In this study, a compact machine vision system is being proposed for the detection of aflatoxin contaminated dried figs. An image-processing method is defined for a pixel-based prediction of an aflatoxin contaminated surface area on selected dried figs that is scanned by a Charge Coupled Device (CCD) color camera and under UV lighting in this system. Additionally, naturally contaminated fig test samples are sent to an authorized laboratory in order to determine the amount of aflatoxin B-1 and the total aflatoxins for comparing the actual aflatoxin amounts of dried figs and the pixel values of contaminated samples. The results of this study have shown that there is not a linear correlation between total surface area of aflatoxin contamination on dried figs in pixels and the actual aflatoxin amounts analyzed under laboratory conditions

COLOR CHANGE ANALYSIS OF DRIED ORANGE SLICES DURING HOT AIR DRYING

WOS: 000446644900034In this work, the hot air drying of orange slices was investigated in details, such as drying time, moisture ratio, dried products' colors and some macro- and micro-elements. The study aimed to apply a computer vision system to study the color changes due to drying. The orange slices were dried at hot air drying at temperatures of 70 degrees C and 80 degrees C and explored in detail such as drying time and mass degradations. Dried products of orange slices were subjected to color analysis by image analysis system in RGB color model. Three hundred color photographs of orange fruit slices taken before and after drying were analyzed

A REVIEW OF PHYSICAL AND MECHANICAL PROPERTIES OF CASSAVA RELATED TO HARVESTING MACHINES

For many years now, harvesting of cassava is difficult because there has not been a well-designed machine to harvest, separate, and convey the crop in a one-time operation. In all the unit operations in cassava production, several machines and types of equipment have been mechanized successfully. However, cassava harvesting and peeling have remained a global challenge to engineers involved in machine design. In light of this, some pieces of literature on the physicomechanical properties of cassava were qualitatively reviewed. The study presents harvesting methods for cassava around the globe, considering its merits and limitations for future development. We found out that cutting shear stress and force increased with increasing cassava tuber age because of an increase in density and starch content. Additionally, the ratio of the peel of cassava tuber ranges from 0.106 to 0.215. The frictional properties of cassava are essential to design and develop machines for post-harvest operations of cassava roots. Whereas, the angle of repose for the unpeeled cassava is required for the design of the hopper and that of the peeled is required for the design of the chute. The manual, semi-manual and fully mechanized harvesting methods require the capacity of about 22-51 man h/ha, 16-45 man h/ha, and 1-4 man h/ha respectively. The fully mechanized method is very efficient, and the field is plowed alongside harvesting which saves time, fuel, and cost of operation. Even though less research is carried out on cassava harvesting mechanization compared to other crops, the current development is a harvesting machine hitched to a tractor with a conveyor unit powered by the PTO system. The knowledge of this review would be a blueprint for engineers in designing cassava mechanical harvesters