Publications by authors named "Kunli Xu"

The flavor of dairy products crucially affects consumer purchase preference. Although the flavor and sensory perception of milk can be influenced by heat treatment during processing, the exact mechanism remains unclear. Therefore, this study analyzed the whey protein content and structural changes of milk heated at different time and temperature combinations and evaluated the flavor compounds and sensory characteristics of milk.

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Understanding consumers' sensory preferences for dairy products is essential. This study employed sensory analysis and instrumental techniques to analyze the flavor of pasteurized milk and UHT milk. There were 6 milk samples with similar fat content (4.

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Chestnuts are known for their unique flavor and nutritional value. However, the flavor changes in chestnuts after processing remain unclear. Multi-intelligent sensory technologies and headspace solid-phase microextraction-arrow gas chromatography-mass spectrometry (HS-SPME-Arrow-GC-MS) combined with multivariate statistical analysis were applied to evaluate the effect of packaging and heat sterilization procedures on the sensory quality of chestnuts.

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Excessive pesticide residues are a serious problem faced by food regulatory authorities, suppliers, and consumers. To assist with this challenge, this work aimed to develop a method of detecting and classifying pesticide residue on fruit samples using an electronic nose, through the application of three different data-recognition algorithms. The apple samples carried various concentrations of two known pesticides, namely cypermethrin and chlorpyrifos.

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A comparison study on the freshness of rainbow trout () fillets in the course of their sale was performed using near-infrared spectroscopy (NIRS), solid-phase microextraction combined with gas chromatography-mass spectrometry (SPME-GC-MS), and the electronic nose (E-nose) technique. Quantitative analysis of the volatile salt nitrogen (TVB-N) of rainbow trout fillets with different freshness using NIR combined with the partial least squares (PLS) method revealed that the predicted values of TVB-N of the samples were significantly correlated with the true values ( < 0.01).

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