The objective of this work was to evaluate the antioxidant and antimicrobial capacity of Kale leaves, as well as to quantify the levels of phenolic compounds and flavonoids present in its aqueous extract, and the viability when added to a fermented milk drink. The leaves were subjected to four treatments: fresh crushed in a blender, fresh sprayed with liquid nitrogen, dried in an oven at 45°C for 72 hours and frozen. Antioxidant activity, concentration of total phenolic compounds, flavonoids and antimicrobial activity were determined. To prepare the dairy drink, the amounts of 5%, 10% and 15% of the dry extract of Kale leaves were added, as well as 15% of the dry extract with sorbate and the control treatment. Furthermore, it determined the antioxidant activity and the number of lactic acid bacteria in the drink. The dried and frozen leaves showed better antioxidant activity and, when compared to fresh powdered leaves, they did not differ in phenolic compounds, presenting the best contents. Fresh powdered leaves showed the highest flavonoid yield. The aqueous extracts of kale leaves did not show antibacterial activity against the studied microorganisms. The abstract did not show antioxidant capacity contents of total phenolic compounds and flavonoids in kale subjected to different treatments.

The selection of kale genotypes more resistant to dehydration is important, since this product is marketed fresh and characterized as perishable. For the post-harvest study, the adjustment of regression models is useful. However, when there are many treatments, it is difficult to identify the superior one through the graphical representation of the curves. In this sense, the model identity test groups the curves establishing genotypes that have statistically similar behavior. Thus, we aimed to select kale accesses for post-harvest dehydration using the model identity test. The accumulated loss of fresh matter of 22 kale genotypaes was evaluated, being 19 of the germplasm bank of the UFVJM and three commercial cultivars (COM). The model identity test was used for the statistical grouping of the regression curves. The UFVJM-19 and UFVJM-32 accessions had lower rates of dehydration as a function of time. The test facilitated the interpretation of the results, with a reduction of 22 to six regression curves, helping to select the best genotypes. The UFVJM-19 and UFVJM-32 accessions are the most indicated because they present lower post-harvest dehydration, being the most recommended for commercialization.

The demand for the consumption of milk and dairy products by the consumer market is very high. This makes it difficult to analyze the large number of milk samples for quality. In addition to the requirement to consider many quality attributes, there are usually large number of producers, who need daily milk evaluations. The aim of the study was to evaluate the efficiency of fuzzy logic in decision making for the classification of milk. In the fuzzification stage, physical and chemical characteristics of the milk were considered as input linguistic variables. For each linguistic variable, pertinence functions were created, and these were made considering the trapezoidal forms. In the inference stage, rules were established for the association of linguistic variables and output variables (adulterated, inadequate and adequate). To verify the efficiency of the modeled system, 1,000 adulterated, inadequate and adequate milk samples were computationally simulated. Precision was verified when automating decision making in the classification of milk by the fuzzy logic, totaling 100% of correctness. Therefore, the fuzzy system is an efficient tool for the classification of milk and can be used advantageously by professionals in the field in order to reduce human and financial resources.