RESUMEN
Digestate is a nutrient-rich by-product from organic waste anaerobic digestion but can contribute to nutrient pollution without comprehensive management strategies. Some nutrient pollution impacts include harmful algal blooms, hypoxia, and eutrophication. This contribution explores current productive uses of digestate by analyzing its feedstocks, processing technologies, economics, product quality, impurities, incentive policies, and regulations. The analyzed studies found that feedstock, processing technology, and process operating conditions highly influence the digestate product characteristics. Also, incentive policies and regulations for managing organic waste by anaerobic digestion and producing digestate as a valuable product promote economic benefits. However, there are not many governmental and industry-led quality assurance certification systems for supporting commercializing digestate products. The sustainable and safe use of digestate in different applications needs further development of technologies and processes. Also, incentives for digestate use, quality regulation, and social awareness are essential to promote digestate product commercialization as part of the organic waste circular economy paradigm. Therefore, future studies about circular business models and standardized international regulations for digestate products are needed.
Asunto(s)
Ambiente , Eutrofización , AnaerobiosisRESUMEN
Increasing interest in constituents and dietary supplements has created the need for more efficient use of this information in nutrition-related fields. The present work aims to obtain optimal models to predict the total antioxidant properties of food matrices, using available information on the amount and class of flavonoids present in vegetables. A new dataset using databases that collect the flavonoid content of selected foods has been created. Structural information was obtained using a structural-topological approach called TOPological Sub-Structural Molecular (TOPSMODE). Different artificial intelligence algorithms were applied, including Machine Learning (ML) methods. The study allowed us to demonstrate the effectiveness of the models using structural-topological characteristics of dietary flavonoids. The proposed models can be considered, without overfitting, effective in predicting new values of Oxygen Radical Absorption capacity (ORAC), except in the Multi-Layer Perceptron (MLP) algorithm. The best optimal model was obtained by the Random Forest (RF) algorithm. The in silico methodology we developed allows us to confirm the effectiveness of the obtained models, by introducing the new structural-topological attributes, as well as selecting those that most influence the class variable.
RESUMEN
La fenilcetonuria (PKU) es causada por una actividad deficiente de la enzima fenilalanina hidroxilasa. En los pacientes con esta deficiencia la fenilalanina (Phe) no puede ser convertida en tirosina, aumentando sus niveles en sangre y de otros metabolitos neurotóxicos, provocando un retraso mental irreversible. El tratamiento fundamentalmente se basa en una dieta controlada de Phe. Sin embargo, los alimentos libres o bajos en Phe son escasos. El objetivo de esta investigación es obtener hidrolizados proteicos con bajo contenido de Phe a partir del suero dulce de leche en polvo y harina de E. edulis Triana. El aislado proteico (96,01% proteína cruda) se obtuvo por solubilización y precipitación de las proteínas de la harina, mientras que las proteínas del suero (15,69% proteína cruda) fueron tratadas en su matriz original. Las proteínas del suero y el asilado fueron hidrolizadas enzimáticamente con pepsina y proteasa de Streptomyces griseus. La concentración de Phe se determinó por fluorometría y por HPLC, de lo cual la Phe de las proteínas del suero es liberada una hora antes que las del chachafruto, debido a que las proteínas del suero en parte fueron hidrolizadas en la elaboración del queso. Además, los resultados de la utilización del carbón activados como captor de Phe indican la reducción total del contenido de este aminoácido en los hidrolizados y la reducción de la concentración de otros aminoácidos(AU)
henylketonuria (PKU) is caused by a low activity of the enzyme phenylalanine hydroxylase. In patients with this deficiency, phenylalanine (Phe) cannot be converted to tyrosine, increasing blood levels and other neurotoxic metabolites, causing irreversible mental retardation. The treatment is fundamentally based on a controlled diet of Phe. However, free or low-Phe foods are scarce. The objective of this research is to obtain protein hydrolysates with low Phe content from sweet milk powder and E. edulis Triana flour. The protein isolate (96.01% crude protein) was obtained by solubilization and precipitation of the flour proteins, while the whey proteins (15.69% crude protein) were treated in their original matrix. Serum and asylated proteins were enzymatically hydrolyzed with pepsin and Streptomyces griseus protease. The concentration of Phe was determined by fluorometry and by HPLC, from which the Phe of whey proteins is released one hour earlier than those of chachafruto, due to the fact that the whey proteins were partially hydrolyzed in the elaboration of the cheese. In addition, the results of the use of charcoal activated as Phe captor indicate the total reduction of the content of this amino acid in the hydrolysates and the reduction of the concentration of other amino acids(AU)