Abstract: The present disclosure provides a machine learning-based hyperspectral detection and visualization method of a nitrogen content in a soil profile. The method includes the following steps: collecting a plurality of soil profile samples; obtaining hyperspectral image data of a soil profile; selecting a plurality of rectangular ranges on a hyperspectral image as region of interest (ROIs), calculating an average spectral curve of all pixels in the ROIs, and analyzing and measuring standard contents of nitrogen in the soil samples corresponding to the ROIs; constructing hyperspectral prediction models of five types of soil nitrogen in the soil profile with reference to different learning algorithms respectively with an average spectrum of ROIs after preprocessing as a predictive variable and a standard soil nitrogen content as a response variable; selecting an optimal prediction model based on evaluation indexes to predict and visualize contents of different forms of nitrogen in the entire soil profile.

Abstract: A microfluidic chip (100) for capturing cells (200) and preparing method thereof. The chip (100) comprises an upper rigid material (10) and a lower rigid material (20), a channel (30) provided between the upper rigid material (10) and the lower rigid material (20). The channel has an inlet (32) and an outlet (34). At least one of the upper rigid material (10) and the lower rigid material (20) is made of transparent material. The channel (30) has a height decreasing gradually from the inlet (32) to the outlet (34), thus a wedge shape is formed, or a portion of the channel has the wedge shape. The lowest portion of the channel (30) has a dimension approximate to or less than that of at least one of target cells. The chip (100) could quickly, effectively separate and enrich cells with various sizes and specific molecular expressions.