## 1 Introduction  
Hyperspectral imaging technique is capable of acquiring both spatial and spectral information from a target by combining traditional imaging and spectroscopy methods, making it a powerful tool for many food and agricultural applications. Hyperspectral images are three-dimensional (3-D) in nature, with two spatial dimensions and one spectral dimension. The 3-D hyperspectral image data can be collected by three major image acquisition methods: point-scan, line-scan, and area-scan methods [1]. Since food commodities usually move along processing and production lines, the line-scan hyperspectral acquisition method naturally fits to inspect the individual moving food items. The hyperspectral imaging concept was brought to the food and agricultural field by scientists of the U.S. Department of Agriculture (USDA) in the late 1990s [2]. The practical implementation of line-scan hyperspectral imaging (particularly for reflectance and fluorescence techniques) for inspecting food and agricultural products was fulfilled in the early 2000s [3]. Since then, line-scan hyperspectral imaging techniques have drawn tremendous interest from both academic and industrial areas, and have been intensively researched and developed for food and agricultural applications during the past 15 years [1; 4]. With the introduction of new measurement concepts and instruments, line-scan hyperspectral techniques are continuously evolving to expand the scope of their applications. For example, by using a newly available high-power narrow-linewidth line laser and dispersive Raman imaging spectrograph, macro-scale line-scan hyperspectral Raman imaging was recently realized [5], which opens a new avenue for rapid and high-throughput evaluation of food safety and quality.  
This paper reviews line-scan hyperspectral imaging techniques in the food and agricultural area, with an emphasis on food safety and quality applications under indoor controlled lighting conditions. There is an introduction for the spectroscopy techniques (i.e., reflectance, transmittance, fluorescence, and Raman) and line-scan hyperspectral measurement methods (i.e., imaging and spatially resolved spectroscopy) in Section 2, giving basic concepts and ground rules for the rest of the paper. The focus of the paper is put on the introduction, demonstration, and summarization of existing and emerging line-scan hyperspectral imaging techniques for practical food and agricultural applications, including major hardware components (i.e., light sources, imaging spectrographs, and image sensors) working in different wavelength ranges (e.g., visible (VIS), near infrared (NIR), and short-wavelength infrared (SWIR)) in Section 3.1, representative imaging systems and spectral and spatial calibrations in Section 3.2, and techniques for analyzing hyperspectral images (i.e., typical hyperspectral image data, image preprocessing, band selection, and target identification) in Section 4. Applications for food and agricultural products are reviewed in Section 5 to reflect current practices and future trends. Conclusions in Section 6 present a summary and address future development of line-scan hyperspectral imaging techniques for food and agriculture.