## 1 Introduction  
The assessment of quality traits in rice (_Oryza sativa_ L.) can be considered a very important issue, as these parameters play an important role for both consumers and industry. The assessment of these traits can be performed by the measurement of the physical parameters of the grain, its biochemical composition, its cooking properties, and its milling performance. The most interesting quality parameters are related to physical properties (weight, grain volume), appearance (color, size, shape, smoothness, and hardness), flow properties, biochemical composition (moisture, lipids, protein, ash, and amylose content), temperature of gelatinization, pasting viscosity, and gel consistency [1]. The pasting properties of rice are by far some of the most interesting rice quality traits, as they define the capacity of the rice for applications in food processing and other industries, and they are also used to explain rice aging [2]. The pasting profile displays the physicochemical changes in the aqueous suspension of starch at a certain temperature and time, allowing for an evaluation of the apparent viscosity [3]. In the food industry, the Rapid Visco Analyzer (RVA) is a suitable tool used to obtain information linked to the apparent viscosity, allowing for simulations of processing focusing on the structural properties and functionality [4]. The final viscosity (FV) is usually used to characterize the quality of samples and their capacity to develop into a viscous gel after cooking and cooling processes. The setback (ST) region is commonly defined as the pasting curve region between the trough (TR) and FV. The breakdown (BD) parameter, which represents the difference between the pasting viscosity (PV) and TR, evaluates the ease of upsetting swollen starch granules, showing the stability degree through cooking [5]. The peak time and PV, as integral parts of the pasting profile, have been linked with water absorption capacity--which is considered an important parameter for the development of rice-based products--as they may inform the future behavior of a paste during and after processing. Pasting properties are also related to other sensory qualities of rice besides texture, as rice with a higher taste evaluation tends to present a significant amylose content, which presents a correlation with PV, hold viscosity, FV, and BD, as well as the pasting temperature, peak time, and protein content [6]. The viscosity of a gel depends on the gelatinization stage of the starch and the extent of its molecular BD. Starch gelatinization and degradation can be related to a decrease in the PV and the FV, depending on the rice type. The end-use quality of food, such as the texture of cooked rice and noodles, has also been evaluated on the basis of its pasting properties [4]. Considering that the RVA procedure is a time-consuming process, rapid methodologies, such as near-infrared (NIR) spectroscopy, have been explored through routinary models for the evaluation of quality properties in cereals [7]. The infrared spectra methodology is considered a detailed analysis tool for quality control and represents excellent potential for use in the assessment of sample properties in breeding programs and industry based on reliable and fast techniques [8]. For agricultural product analysis, NIR spectroscopy has been broadly used due to its advantages related to sample preparation, including being faster and easier to manipulate, non-destructive, and accurate. This technology, based on a single spectrum, also allows for the evaluation of several properties relating to rice quality [9; 10]. Partial least squares (PLS) regression is an algorithm that estimates and quantifies the components in a particular sample [11]. By using suitable algorithms, it is possible to select the spectral region associated with a significant improvement in the performance of the full-spectrum calibration techniques, preventing non-modelled interference and creating an adjusted model [12].