Wheat oligopeptides are a polypeptide mixture obtained from an enzymatic hydrolysate of wheat protein using specific small peptide separation techniques, which are rich in amino acids such as glutamic acid and proline, and can be easily digested and absorbed. Wheat oligopeptides have abundant bioactive functions, making them promising ingredients for functional products and conferring them potential value for processing and application. This article aims to review the primary preparation methods for wheat oligopeptides and analyze the in vivo and in vitro antioxidant, anti-inflammatory, immunoregulatory, antihypertensive, hypoglycemic and neuroprotective effects and mechanisms of wheat oligopeptides. Moreover, this article introduces the current status of the application of wheat oligopeptides in the fields of food, drug carriers and chemical products, and discusses the potential application value and future directions of wheat oligopeptides. It is expected to provide theoretical references for in-depth studies, processing and application of wheat oligopeptides.

Cereals, as the staple food for humans, are rich in a variety of nutrients such as moisture, proteins, fats and carbohydrates. However, the quality of cereals can be seriously affected by long-term storage, mold contamination and heterogeneous cereals, which jeopardize food security. Therefore, accurate and rapid detection of nutrients, physicochemical properties, and mold contamination in cereals is essential for food quality control and nutritional assessment. Near infrared spectroscopy has been widely used as a rapid and non-destructive detection method for cereal analysis in recent years. This paper aims to review the current status of the application of near infrared spectroscopy in the detection of cereals nutrients (starch, fat, protein and bioactive compounds), physicochemical properties (starch viscosity, hardness and farinograph parameters), mold contamination and other aspects (freshness, variety identification, heavy metals and pesticide residues), summarize and compare the advantages and disadvantages of common model algorithms, and propose some problems and future trends in the application of near infrared spectroscopy in cereal detection, in order to provide a reference for further improvement of near infrared spectroscopy in the detection of cereals.