不同品种冷鲜猪肉pH值高光谱检测模型的传递方法研究

doi:10.3964/j.issn.1000-0593(2015)07-1973-07

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Abstract Calibration transfer is an effective approach to solve model invalidation problems caused by the change of instruments or the prediction samples. However, most studies on calibration transfer were based on different instruments, and models were established by Near Infrared Spectroscopy. In this study, hyperspectral detecting model of pork pH value was established, and in order to enhance the applicability of model to different breeds of pork samples, a new transfer algorithm based on spectra Mahalanobis distance, sync correction of spectrum and prediction value (CSPV), has been proposed, and was compared with model updating method. Equations with correlation coefficient of prediction (r_p)≥0.837 and residual prediction deviation (RPD)≥1.9 were considered as applicable to predict pork quality. In this paper, three breeds, duchangda, maojia and linghao pork were researched, and a pH detecting model of duchangda (the primary breed) was established using partial least squares (PLS) regression method with r_c of 0.922, r_p of 0.904, root mean squared error of cross validation (RMSECV) of 0.045, root mean squared error of prediction (RMSEP) of 0.046 and RPD of 2.380. However, the prediction of the model to samples from maojia and linghao breeds (the secondary breeds) was very poor with r_p of 0.770 and 0.731 respectively, RMSEP of 0.111 and 0.209, RPD reached only 1.533 and 1.234 separately. Obviously, the PLS model of duchangda was unable to achieve the prediction to maojia and linghao samples. With the transformation of CSPV algorithm to duchangda model, only 9 and 10 standard samples from maojia and linghao breeds were used respectively, the prediction ability was improved with r_p of 0.889 and 0.900, RPD grew to 2.071 and 2.231, which met the requirement of r_p≥0.837 and RPD≥1.9. While with model updating method, when 11 and 9 representative samples from maojia and linghao breeds were added to calibration set of duchangda model, r_p increased to 0.869 and 0.845, but RPD only raised to 1.934 and 1.804 exclusively, even though tally r_p≥0.837, it didn’t meet that RPD≥1.9. The results demonstrate that CSPV transfer algorithm could realize the pH value prediction of duchangda model to maojia and linghao samples, while model updating method was only applicable for maojia samples instead of linghao samples, and the performance of CSPV transfer algorithm was better than model updating.

Key words：Pork;pH value;Hyperspectral;Model transfer;Model update

Received: 2014-04-02 Accepted: 2014-08-12

ZTFLH:

O433.4

Corresponding Authors: LI Xiao-yu E-mail: lixiaoyu@mail.hzau.edu.cn

Cite this article:

LIU Jiao,LI Xiao-yu,JIN Rui, et al. Extending Hyperspectral Detecting Model of pH in Fresh Pork to New Breeds [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(07): 1973-1979.

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https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2015)07-1973-07 OR https://www.gpxygpfx.com/EN/Y2015/V35/I07/1973