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Mycotoxins are produced by fungi and are known to be toxic to humans and animals. Common mycotoxins include aflatoxins, ochratoxins, zearalenone, patulin, sterigmatocystin, citrinin, ergot alkaloids, deoxynivalenol, fumonisins, trichothecenes, Alternaria toxins, tremorgenic mycotoxins, fusarins, 3-nitropropionic acid, cyclochlorotine, sporidesmin, etc. These mycotoxins can pose several health risks to both animals and humans, including death. As several mycotoxins simultaneously occur in nature, especially in foods and feeds, the detoxification and/or total removal of mycotoxins remains challenging. Moreover, given that the volume of scientific literature regarding mycotoxins is steadily on the rise, there is need for continuous synthesis of the body of knowledge. To supplement existing information, knowledge of mycotoxins affecting animals, foods, humans, and plants, with more focus on types, toxicity, and prevention measures, including strategies employed in detoxification and removal, were revisited in this work. Our synthesis revealed that mycotoxin decontamination, control, and detoxification strategies cut across pre-and post-harvest preventive measures. In particular, pre-harvest measures can include good agricultural practices, fertilization/irrigation, crop rotation, using resistant varieties of crops, avoiding insect damage, early harvesting, maintaining adequate humidity, and removing debris from the preceding harvests. On the other hand, post-harvest measures can include processing, chemical, biological, and physical measures. Additionally, chemical-based methods and other emerging strategies for mycotoxin detoxification can involve the usage of chitosan, ozone, nanoparticles, and plant extracts.

New lifestyles, higher incomes and better consumer awareness are increasing the demand for a year-round supply of innovative food products. In past decades, important developments have been achieved in areas related to food and the food industry. This review shows that factors influencing performance in new product development (NPD) are dynamic and continuously guiding project development. The data obtained by direct involvement of consumers can impact positively successful product development and enhance the company’s financial performance. The study of consumer behaviour and attitudes towards new foods encompasses multiple aspects, such as preference, choice, desire to eat certain foods, buying intentions and frequency of consumption. Additionally, both the consumers’ willingness to purchase and the willingness to pay a premium are important in NPD, launching and success.

Bananas (cv. Musa nana and Musa cavendishii) fresh and dried by hot air at 50 and 70°C and lyophilisation were analysed for phenolic contents and antioxidant activity. All samples were subject to six extractions (three with methanol followed by three with acetone/water solution). The experimental data served to train a neural network adequate to describe the experimental observations for both output variables studied: total phenols and antioxidant activity. The results show that both bananas are similar and air drying decreased total phenols and antioxidant activity for both temperatures, whereas lyophilisation decreased the phenolic content in a lesser extent. Neural network experiments showed that antioxidant activity and phenolic compounds can be predicted accurately from the input variables: banana variety, dryness state and type and order of extract. Drying state and extract order were found to have larger impact in the values of antioxidant activity and phenolic compounds.

The convective drying of apples from two different cultivars, Golden Delicious and Granny Smith, in a range of temperatures from 30 to 60 • C is studied. Some chemical and physical properties were determined fresh after drying: moisture, acidity and sugar content, color, and textural attributes, in order to evaluate the effect of drying and drying temperature on these properties. Furthermore, the drying kinetics were studied in terms of thin layer models and also by means of the Fick's equation of diffusion, and some mass transfer properties were evaluated, such as effective moisture diffusivity and convective mass transfer coefficient. It was concluded that drying decreased both acidity and sugar content for both apple cultivars. Color was significantly affected by drying, resulting in high values of the total color difference, between 19.43 and 25.04. Drying turned the products less hard and less cohesive. Furthermore, it was found that mass diffusivity increased with temperature following an Arrhenius type function, where D e 0 was 5.4621 × 10 −4 and 1.8401 × 10 −4 m 2 /s, and E was 35.3 and 32.8 kJ/mol, respectively, for cultivars Golden Delicious and Granny Smith.

The aim of this work was to determine the mass transfer properties of pumpkin (Cucurbita moschata) exposed to air drying. The drying temperatures tested ranged between 30°C and 70°C, and the kinetic behavior was studied in this temperature band. The samples were analyzed in terms of moisture content, acidity, proteins, lipids, and crude fiber, both in the fresh state and after drying. From the chemical analyses made, it was possible to conclude that drying induces some reductions in acidity, lipids, fibers, and proteins. As to the influence of the drying temperature on the process, it was observed that a temperature rise from 30°C to 70°C led to a 70% saving in drying time. The results obtained by fitting the experimental data to the kinetic models tested allowed concluding that the best model for the present case is Henderson-Pabis, and the worst is Vega-Lemus. Furthermore, in this work, it was possible to determine the values of the diffusion coefficient at an infinite temperature, D e 0 , and activation energy for moisture diffusion, E d , which were, respectively, 0.0039 m 2 /s and 32.26 kJ/mol. Similarly, the values of the Arrhenius constant and the activation energy for convective mass transfer, respectively, h m 0 and E c , were also calculated, the first being 3.798×10 8 m/s and the latter 86.25 kJ/mol. These results indicate that the activation energy for convective mass transfer is higher than that for mass diffusion.