基于高光譜技術(shù)的羊肉含水率測定方法研究
[Abstract]:According to the hygienic standard of mutton, moisture content is an important reference index to evaluate mutton quality. In this study, 108 mutton samples were collected in 400nm-1000mn band and 1000nm-2500mn band by hyperspectral imaging system, and moisture content of mutton was determined by drying method. By collecting sample hyperspectral, spectral pretreatment, extracting sensitive bands, screening moisture content to detect spectral characteristic parameters, a prediction model of moisture content based on hyperspectral was constructed, and the model was analyzed and evaluated. The main contents and results are as follows: 1. The light source angle adjusting device was designed, and the force condition of the device was checked by Solidworks. The 3D simulation of the motion track was carried out to verify that the device could adjust the illumination angle of the spectrometer light source. The sample hyperspectral information was collected and the original spectrum was pretreated by multiple scattering correction. The 400nm-1 OOOnm and 1000nm-2500nm spectral pretreatment algorithms were selected according to the PLSR model. The results show that the optimal preprocessing algorithms for 400nm-1000nm band and 1000nm-2500nm band are standard normal combination de-trend method and de-trend algorithm .3respectively. PLS regression weight method was used to analyze the data of spectral pretreatment. It was found that the sensitive wavelengths of 400nm-1000nm band and 1000nm-2500nm band were 405.6 nm ~ 516.5nm ~ (-1) ~ 563.7nm ~ (-1) ~ (615.9) mm ~ (-1) ~ (?) ~ 864.4nm ~ (-1) ~ (964.4) nm ~ (-1) ~ 1346nm ~ 1535nm ~ (1635nm) ~ (1635nm) ~ (1786) nmm ~ (-1) ~ (-1) nm ~ (-1) ~ (-1) nm. The partial least square method and stepwise multivariate linear regression method were used to establish the prediction models of mutton moisture content in the whole band and the characteristic band, respectively. The results show that the prediction effect of stepwise multivariate linear regression model is better than that of partial least square model. The correlation coefficient (Rp) of predictive set model is 0.8184 and 0.7984, the standard deviation SEP is 0.0581 and 0.0603, the correlation coefficient of verification set model is 0.8301 and 0.8231, and the standard deviation SEC is 0.0549 and 0.0587 respectively. Based on the hyperspectral technology, the method of moisture content measurement of mutton is studied in this paper, which avoids the shortcoming of the traditional method to destroy the sample, and provides a theoretical basis for the design and development of the portable mutton moisture content detector in the future.
【學(xué)位授予單位】:內(nèi)蒙古農(nóng)業(yè)大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:O657.3;TS251.53
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