Edible oil is a necessity in daily diet, providing heat energy and fatty acid for the human body. It is an important organic matter that promotes the absorption of fat-soluble vitamins. With the improvement of people’s living standards, high-grade edible oil has entered the table of the public and is deeply welcomed. Due to the high selling price of high-grade edible oil in the market, some illegal manufacturers mix cheap edible oil into high-grade edible oil for sale to make huge profits. And this leads to the adulteration of edible oil from time to time, which has aroused widespread concern of the government and the public. In order to protect the legitimate interests of consumers and maintain the normal order of the edible oil market, it is urgent to detect the adulteration of edible oil quickly and effectively. Near-infrared spectroscopy(NIR)has the advantages of simple, rapid, nondestructive and no sample pretreatment, and it is widely used in the analysis of adulteration of edible oil. This paper summarizes the basic principle of NIR technology and reviews the research progress of NIR technology in adulteration detection of edible oils such as olive oil, camellia oil, sesame oil and walnut oil in recent ten years. Different test devices, test methods and data processing methods(pretreatment, wavelength selection and modeling methods) are mainly used to detect the binary, ternary and multivariant adulteration of edible oil to improve the accuracy and application range of edible oil adulteration detection and establish a more effective quantitative detection and qualitative identification model for edible oil adulteration. Then, it summarizes the existing problems in the detection of adulteration of edible oil by near-infrared spectroscopy, such as the detection mechanism of adulteration of edible oil is unclear. The prepared adulterated edible oil samples are difficult to meet the actual complex adulteration forms, the adulteration detection by sampling can only realize part of the spot sampling inspection, and the unified standard specification of adulteration detection of edible oil is not established. At last, it points out the development trend in future to integrate NIR with other rapid detection technologies to obtain more accurate and reliable detection models, and the construction of edible oil NIR database using the internet of things and big data technology to realize spectral data sharing and online upgrade and remote update of adulteration detection models. This paper aims to provide references and solutions for detecting adulteration of edible oil in China.