Nondestructive Testing for Wheat Quality with Sensor Technology Based on Big Data

Table 3

Hyperspectral test of wheat.

No.	Data	Conclusion	References
1	600	The correct classification of 85–100% of healthy wheat and wheat with pests and diseases is carried out.	[45]
2	230	96.4% of healthy wheat and 91.0–100.0% of pest-infested wheat kernels are identified.	[46]
3	48	A fluorescence wavelength of 531 nm was chosen for image processing and classification analysis, and the classification accuracy can be as high as 95%.	[47]
4	121	In the classification methods of different types of wheat head blight, only 4 optimal wavelengths (1104, 1384, 1454, and 1650 nm) were selected among 121 wavelengths, and good classification results were obtained.	[48]
5	79	Determining the distribution of whole wheat protein content.	[50]
6	190	Taking the determination of protein content of about 190 wheat flour as an example, the hyperspectral line scan system works like a classic near-infrared spectrometer, but the time required to analyze the sample is reduced by at least half.	[52]