A survey was carried out to detect aflatoxins and isolate aflatoxigenic moulds contaminating fresh and processed meat products. The fungal contamination was examined in 215 samples of fresh and processed meat products and 130 samples of spices used in the meat industry collected from different local companies in Cairo, Egypt. Processed meat products such as beefburger, hot-dog, kubeba, sausage, luncheon meat had the highest count of moulds as compared with fresh and canned meat. Out of 150 samples of meat products and 100 samples of spices, aflatoxin B1 was detected in five samples of beefburger, (8 micrograms/kg), four samples of black pepper (35 micrograms/kg), and four samples of white pepper (22 micrograms/kg). Aflatoxins B1 and B2 were detected in one sample of kubeba (150 micrograms B1/kg and 25 micrograms B2/kg); hot-dog (5 micrograms B1/kg and 2 micrograms B2/kg) sausage (7 micrograms B1/kg and 3 micrograms B2/kg) and luncheon meat (4 micrograms B1/kg and 2 micrograms B2/kg). Also, aflatoxins B1 and G1 were detected in two samples of turmeric (12 micrograms B1/kg and 8 micrograms G1/kg) and coriander (8 micrograms B1/kg and 2 micrograms G1/kg). Aspergillus flavus (24 isolates), and Aspergillus parasiticus (16 isolates) were the predominant aflatoxin-producing moulds isolated from both processed meat products and spices. Aflatoxins were absent in fresh meat, canned meat, salami, beefsteak and minced meat. The contamination of processed meat with aflatoxin was shown to correlate with the addition of spices to fresh meat.

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Investigates the effects of the most influential cutting parameters (cutting speed, feed rate, depth of cut, tool nose radius, tool length and work piece length) on surface roughness quality and on the formation of built‐up edge in a lathe dry turning process of mild carbon steel samples. A full factorial design (384 experiments), taking into account the three‐level interactions between the independent variables has been conducted. The results show that the following three‐level interactions: feed rate × cutting speed × depth of cut, feed rate × cutting speed × tool nose radius and tool nose radius × depth of cut × tool length have significant effects on surface roughness in this type of machining operation. Shows that the analysis of main effects alone and even two‐level interactions could lead to a false interpretation of the results. The analysis of variance revealed that the best surface roughness is achieved with a low feed rate, a large tool nose radius and a high cutting speed. The results also show that the depth of cut has no significant effect on surface roughness when operating at cutting speeds higher than 160m/min. Furthermore, it is shown that built‐up edge formation deteriorates surface roughness when machining mild carbon steel at specific feed rate, tool nose radius and cutting speed levels. Proposes a new model for evaluating the limiting cutting speed to avoid the built‐up edge formation. Finally, shows through experimentation that an increase in depth of cut would lead to improved surface roughness when tool vibration is increased.

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