General chemical and amino acid compositions of the most widespread oil crops of Brassicáceae family (review)

Cultivation of oil crops of Brassicaceae family is an important part of agricultural production in many countries. Currently, interest to Brassicaceae crops is caused with their high productivity, diverse fatty-acid composition of oil of the modern cultivars, and a possibility to use them by various ways. Vegetable oils produced from Brassicaceae crops are, on the one hand, a basis of a rational human nutrition, on the other hand, this is a necessary raw material for the different industries. A balance between general chemical and amino acid compositions of protein allows using it in production of compound animal feeds and foods based on vegetable protein, having high nutritional value and useful technological characteristics (oil, protein, and essential amino acids contents). This paper presents a comparative description and principal features of the general chemical and amino acid composition of some oil crops of the Brassicaceae family. Analysis of the Russian and foreign literary sources proves the importance of further development and studying in this direction with the aim of breeding new cultivars with desired properties and providing domestic food industry with quality and safe products.

Cooked sausage enriched with essential nutrients for the gastrointestinal diet

Introduction. People with gastrointestinal disorders should have a sparing diet with a balanced chemical and amino acid composition including all essential components. Based on formulations of meat products, we identified a number of essential nutritional components that could improve the diet for gastrointestinal pathologies. In this study, we aimed to develop a formulation for cooked sausage enriched with deficient essential nutrients. Study objects and methods. Our study object was cooked sausage. First, we analyzed the diet for people with gastrointestinal disorders. Then, we formulated a meat-based product (cooked sausage), determined its chemical and amino acid compositions, as well as vitamin and mineral contents, and assessed the balance of amino acids. Finally, we evaluated the biological value and safety of the formulated sausage on laboratory mice. Results and discussion. The chemical and amino acid compositions of a daily gastrointestinal diet in medical institutions revealed a deficiency of some water-soluble vitamins, vitamin A, calcium, magnesium, and iron, as well as an imbalance of amino acids. To replenish the deficiency, we formulated a meat-based product composed of trimmed beef and pork, beef liver, egg mix, food gelatin, chitosan succinate, rice flour, and soy fortifier. The product was classified as a meat and cereal cooked sausage of grade B, in which most amino acids were used for anabolic purposes. Its daily portion of 100 g eliminated the deficiency of potassium and iron, almost completely replenished magnesium, calcium, and vitamin A, as well as reduced the deficiency of dietary fiber by 4.8 g. The cytological studies of the blood of laboratory animals, whose basic diet contained the formulated sausage, proved its high biological value and safety. Conclusion. We found that the formulated meat and cereal sausage can be included in the diet for patients with gastrointestinal diseases and used in medical institutions to eliminate the deficiency of essential nutrients.

Nutritional evaluation of the peels from Citrullus lanatus and Manihot esculenta, an insight into the conversion of waste to food

Background: Huge quantity of cassava and watermelon wastes are daily discharged to the environment with unwholesome consequences. Therefore, research into the effective utilization of these agricultural by-products is of global interest. Methods: The present study evaluated the proximate, minerals, and amino acid compositions of cassava and watermelon peels using standard procedures. Results: The results revealed that carbohydrate is the most abundant proximate contents of both the cassava (82.14±0.42%) and watermelon (62.58±0.78%) peel, followed by crude fiber (5.51±0.06% and 18.90±0.04%), moisture (8.31±0.04% and 5.20±0.07%), crude ash (1.25±0.03% and 7.25±0.04%) for cassava and watermelon peels respectively, while crude fat (0.98±0.03% and 3.92±0.06%) is the least abundant proximate in both samples. Magnesium is the most abundant mineral contents of both the cassava (79.50±4.45Mg/100g) and watermelon (75.53±3.70Mg/100g) peel, followed by sodium (62.35±0.79 Mg/100g and 52.24±3.24 Mg/100g), potassium (22.12±1.34 and 32.65±2.01 mg/100g) for cassava and watermelon peels respectively while copper (0.73±0.05 Mg/100g and 0.67±0.64 Mg/100g) was the least abundant minerals in both samples. The total amino acid compositions of 66.31±4.56 g/100g and 41.80±2.68 g/100g were recorded for cassava and watermelon peel. Glutamic acid (9.96±0.06g/100g) and leucine (4.03±0.05 mg/100g) the most abundant amino acid in cassava and watermelon seed respectively. Conclusion: In conclusion, the peels of cassava and water melon examined, have appreciable levels of nutrients compositions that can be incorporated into human and animal feed formulation.

Proximate, Minerals, and Amino Acid Compositions of Banana and Plantain Peels

The by-products of banana and plantain fruits, especially banana and plantain peels are usually thrown away by producers in plantations, and produce important quantities of post-harvest waste. The banana and plantain peels grown in Nigeria was assessed for their proximate, minerals and amino acid compositions. The proximate contents including moisture, ash, lipids, proteins, carbohydrates and crude fibres were determined using standard A.O.A.C methods. The amino acids by HPLC, and minerals by atomic absorption spectrophotometry. Results revealed that the total amino acid of 89.71±5.45 g/100g and 86.71±3.02 g/100g was recorded for plantain and banana peel. Glutamic acid 12.72±0.02 g/100g was the most abundant amino acid in plantain peel while glycine (3.02±0.82 mg/100g) was the most abundant amino acid in banana peel. Results revealed that sodium is the most abundant minerals contents of both the plantain (76.88±0.89 Mg/100g) and banana (58.16±2.73 Mg/100g) peel, while iron (7.89±0.79 Mg/100g and 5.06±0.07 Mg/100g) was the least minerals in the both samples. Carbohydrate is the most abundant proximate contents of both the plantain (74.12±0.565) and banana (63.82±0.32%) peel, followed by Crude fibre 8.36±0.04% and 12.67±0.08 %, crude ash (6.17±0.05% and 9.56±0.06%) for both plantain and banana peels respectively. While crude fat (3.01±0.06% and 0.89±0.04%) was the least proximate in the both samples. These peels could be considered good source of nutrients for production of human and animal feeds, and their utilization for this purpose should be encouraged, as this will also help in reducing the menace of nutrient deficiencies

iAmideV-Deep: Valine Amidation Site Prediction in Proteins Using Deep Learning and Pseudo Amino Acid Compositions

Amidation is an important post translational modification where a peptide ends with an amide group (–NH2) rather than carboxyl group (–COOH). These amidated peptides are less sensitive to proteolytic degradation with extended half-life in the bloodstream. Amides are used in different industries like pharmaceuticals, natural products, and biologically active compounds. The in-vivo, ex-vivo, and in-vitro identification of amidation sites is a costly and time-consuming but important task to study the physiochemical properties of amidated peptides. A less costly and efficient alternative is to supplement wet lab experiments with accurate computational models. Hence, an urgent need exists for efficient and accurate computational models to easily identify amidated sites in peptides. In this study, we present a new predictor, based on deep neural networks (DNN) and Pseudo Amino Acid Compositions (PseAAC), to learn efficient, task-specific, and effective representations for valine amidation site identification. Well-known DNN architectures are used in this contribution to learn peptide sequence representations and classify peptide chains. Of all the different DNN based predictors developed in this study, Convolutional neural network-based model showed the best performance surpassing all other DNN based models and reported literature contributions. The proposed model will supplement in-vivo methods and help scientists to determine valine amidation very efficiently and accurately, which in turn will enhance understanding of the valine amidation in different biological processes.

Interfacial and Emulsion Stabilizing Properties of Zein Nanoparticles: Differences Between the Zein Fractions (α-, β-, and γ-zein)

According to the solubility in the binary solvent of ethanol water, zein can be classified into α-, β-, γ-, and δ-zein, and the difference on amino acid compositions of these...