近红外光谱及成像检测凭借其高效、无损、非接触等优点近年来被广泛应用于农林产品、食品检测等方面。该技术可快速获取样品光谱和图像信息，进而结合化学计量学、机器学习建模等对样品进行品质安全、掺杂掺假、理化指标和产地溯源等方面检测，深受各行各业的认可。但光学仪器使用环境以及被测样品性质具有局限性，光学检测结果易受到各种因素干扰，从而影响检测精度，应当予以消除或削弱。简述了近红外光谱和高光谱成像的检测基本原理，并对国内外近红外光谱及成像技术在检测时受到的影响因素进行总结与归纳，结合国内外研究学者在相关方面的研究内容，重点在温度、光照、水分、曲率变化和湿度等5个方面及相关校正方法的应用进行阐述，对当前存在的部分问题提出总结与建议，以期为相关方向的研究人员提供参考及借鉴。

Near infrared spectroscopy and hyperspectral imaging techniques have been widely used in agricultural and forestry products as well as food detection in recent years due to their advantages of high efficiency, nondestructive, and noncontact. These two techniques are applied to obtain spectral and imaging information of samples, and then chemometrics and machine learning modeling methods are combined to detect their quality and safety traits, adulteration issues, physical and chemical indicators, and origin traceability. Currently, they are both well recognized by people worldwide. However, the operating environment of optical instruments and the properties of the tested samples have their own limitations. The optical detection results are susceptible to various factors, which significantly affect the detection accuracy and should be eliminated or weakened. In this manuscript, the basic principles of near infrared spectroscopy and hyperspectral imaging are briefly described, and the influencing factors of these techniques at home and abroad are summarized. Considering the works of domestic and foreign researchers in related areas, the application of related correction methods regarding five aspects including temperature, illumination, moisture, curvature change and humidity is elaborated. Suggestions are finally presented for several existing problems to provide reference for researchers in this field.