The objective of this paper was to determine the influence of three culture media with different water activities, times of incubation and temperatures on the growth of A. ochraceus, A. carbonarius and A. niger. Spores of A. ochraceus, A. carbonarius and A. niger were inoculated onto three culture media: Czapeck Yeast extract Agar (CYA), Dichloran 18% Glycerol Agar (DG18) and Malt Yeast extract 40% Glucose Agar (MY40G). The plates were incubated at five different temperatures (8, 25, 30, 35 and 41ºC). The growth of fungi was evaluated every 24h, measuring the colony diameter (mm). None of the species grew at 8°C in any culture media. For A. carbonarius, 30ºC was the best temperature for growth while for A. niger temperatures above 30ºC were better in all culture media. A. ochraceus presented good growth at 25 and 30ºC in all culture media, while at 35ºC, growth was slower, especially on CYA. At 41ºC, A. ochraceus did not grow in any culture media and A. carbonarius was significantly inhibited. A. niger grew at 41ºC and was shown to be the most xerophilic fungi when compared to A. carbonarius and A. ochraceus.

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Changes in temperature, relative humidity, and moisture content of green coffee beans were monitored during transportation of coffee from Brazil to Italy. Six containers (three conventional and three prototype) were stowed in three different places (hold, first floor, and deck) on the ship. Each prototype was located next to a conventional container. The moisture content of the coffee in the container located on the first floor was less affected by environmental variations (0.7%) than that in the hold and on the deck. Coffee located in the hold showed the highest variation in moisture content (3%); in addition, the container showed visible condensation. Coffee transported on the deck showed an intermediary variation in moisture (2%), and there was no visible condensation. The variation in coffee moisture content of the prototype containers was similar to that of the conventional ones, especially in the top layers of coffee bags (2 to 3%), while the increase in water activity was 0.70. This suggests that diffusion of moisture occurs very slowly inside the cargo and that there are thus sufficient time and conditions for fungal growth. The regions of the container near the wall and ceiling are susceptible to condensation since they are close to the headspace with its high relative humidity. Ochratoxin A production occurred in coffee located at the top of the container on the deck and in the wet bags from the hold (those found to be wet on opening the containers at the final destination).

Rice grain production is important for the world economy. Determining the moisture content of the grains, at several stages of production, is crucial for controlling the quality, safety, and storage of the grain. This work inspects how well rice images from global and local descriptors work for determining the moisture content of the grains using artificial vision and intelligence techniques. Three sets of images of rice grains from the INIAP 12 variety (National Institute of Agricultural Research of Ecuador) were captured with a mobile camera. The first one with natural light and the other ones with a truncated pyramid-shaped structure. Then, a set of global descriptors (color, texture) and a set of local descriptors (AZAKE, BRISK, ORB, and SIFT) in conjunction with the dominate technique bag of visual words (BoVW) were used to analyze the content of the image with classification and regression algorithms. The results show that detecting humidity through images with classification and regression algorithms is possible. Finally, f1-score values of at least 0.9 were accomplished for global color descriptors and of 0.8 for texture descriptors, in contrast to the local descriptors (AKAZE, BRISK, and SIFT) that reached up to an f1-score of 0.96.