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An unnatural flavor in a food or drink product caused by the presence of undesirable compounds due to contamination or deterioration is called off-flavor. This study determined the characteristics of cattle by-products off-flavor (heart, liver, lung, rumen, and intestine). We identified 25, 34, 26, 22, and 26 volatile compounds from the heart, liver, lung, rumen, and intestine, respectively, in the bovine via headspace solid-phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS). Based on the relative odor activity value (ROAV ≥ 1), 16 volatile compounds were labeled as characteristic off-flavor by principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The compounds involved in the characteristic off-flavor in bovine heart were E,E-2,4-nonadienal, E,E-2,4-decadien-1-al, hexanal, (E)-2-octenal, and decyl aldehyde. In the bovine liver, the off-flavor compounds were 1-nonanol, ethyl hexanoate, 2-octanone, and dodecyl aldehyde and in bovine lung 3-heptylacrolein was the off-flavor compound. In bovine rumen, heptaldehyde, octanal, p-cresol, and 1-nonanal were off-flavor compounds, and lastly, 1-octen-3-ol and E-2-nonenal were off-flavor compounds with bovine intestine. The cattle by-products were deodorized by shallot-ginger extract masking, baker's yeast fermentation, active dry yeast + β-cyclodextrin (β-CD) composite, and ultrasound + chitosan composite. The above 16 labeled characteristic compounds decreased in concentration. The ultrasound + chitosan composite method showed a significantly better effect than the other methods (p .05). The aim of this study was to determine the characteristic flavor information of cattle by-products and provide idea on how to improve the flavor by various deodorization methods. PRACTICAL APPLICATIONS: This study investigated the volatile flavor compounds of cattle by-products from five organs (heart, liver, lung, rumen, and intestine) by headspace solid-phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS). The 16 volatile compounds were labeled as the major characteristic off-flavor compounds by relative odor activity values and principal component analysis. Four different deodorization methods were adopted, and among them, ultrasound + chitosan composite method showed best results. This study has provided useful information about the characteristic off-flavor compounds and suggests how to improve the flavor of cattle by-products through various deodorization methods.

Rail corrugation often occurs on the high-speed railway, which will affect ride comfort and even the train operation safety in severe condition. Detection of rail corrugation wavelength and depth is absolutely essential for maintenance and safety. A novel method using wheel vibration acceleration is proposed in this paper, in which ensemble empirical mode decomposition (EEMD) is employed to estimate the wavelength, and bispectrum features are extracted to recognize the depth with support vector machine (SVM). Firstly, a vehicle-track coupling model considering the rail corrugation of high-speed railway is established to calculate the wheel vibration acceleration. Secondly, the estimation algorithm of wavelength is studied by analyzing the main frequency with EEMD. The optimal parameters of EEMD are selected according to the orthogonal coefficient of decomposition results and the distribution of the extreme points of signal. The depth detection is transformed to a classification problem with SVM. Bispectrum features, which are extracted from the reconstructed signal using the high-frequency components of wheel vibration acceleration, combining with train speed and corrugation wavelength are input into SVM to recognize the rail corrugation depth. Finally, numerical simulation is carried out to verify the accuracy of the proposed estimation method. The simulation results show that the proposed detection algorithm can accurately identify rail corrugation, the estimation error of rail corrugation wavelength is less than 0.25%, and the classification accuracy of rail corrugation depth is more than 99%.