Xiaoyan Xu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Xiaoyan Xu has a total of 42 co-authors. Here are the top co-authors by number of shared publications:
- Xingguo Tian
College of Food Science, South China Agricultural University, Guangzhou 510642, China
14 shared publications Qian You
Guangdong Provincial Key Laboratory of Food Quality and Safety, Nation-Local Joint Engineering Research Center for Machining and Safety of Livestock and Poultry Products, South China Agricultural University, Guangzhou 510642, China
4 shared publicationsRunxiang Mao
Guangdong Provincial Key Laboratory of Food Quality and Safety, College of Food Science, South China Agricultural University, Guangzhou 510642, China
3 shared publicationsYukun Yuan
Guangdong Provincial Key Laboratory of Food Quality and Safety, College of Food Science, South China Agricultural University, Guangzhou 510642, China
3 shared publicationsLing Zhang
College of Biological and Food Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China
2 shared publicationsTianyao Wang
Guangdong Provincial Key Laboratory of Food Quality and Safety, College of Food Science, South China Agricultural University, Guangzhou 510642, China
2 shared publications
Latest Publications
- Open Access
Development of a Composite Pork Quality Index from Instrumental Traits and Its Hyperspectral Prediction
Pork quality is multidimensional, but conventional evaluation methods are usually destructive, time-consuming, and unsuitable for rapid grading. In this study, longissimus dorsi samples from pigs weighing 30–150 kg were used to construct a composite quality index (CQI) from instrumental traits. Traits related to color, water-holding capacity, antioxidant capacity, and texture were measured, and 13 traits were retained after principal component analysis. The resulting CQI represents a dataset-dependent summary of instrumental quality traits rather than a validated measure of sensory eating quality. Hyperspectral images were collected from pork slices, and CQI was predicted using interval combination optimization (ICO) combined with extreme gradient boosting (XGBoost). In the fixed spectral-level comparison, the SNV–ICO–XGBoost model achieved an Rp2 of 0.8670, an RMSEp of 1.7319, and an RPDp of 2.7423. Animal-level mean-spectrum validation over 50 random splits showed that PLSR achieved the highest mean prediction performance, with an Rp2 of 0.807 ± 0.058, an RMSEp of 1.857 ± 0.345, and an RPDp of 2.374 ± 0.345, providing a more conservative assessment of model performance. The predicted CQI values were further visualized qualitatively on the pork surface, supporting further evaluation of HSI for rapid and non-destructive assessment of instrumentally derived pork quality.
Open AccessDevelopment of a Composite Pork Quality Index from Instrumental Traits and Its Hyperspectral Prediction
Pork quality is multidimensional, but conventional evaluation methods are usually destructive, time-consuming, and unsuitable for rapid grading. In this study, longissimus dorsi samples from pigs weighing 30–150 kg were used to construct a composite quality index (CQI) from instrumental traits. Traits related to color, water-holding capacity, antioxidant capacity, and texture were measured, and 13 traits were retained after principal component analysis. The resulting CQI represents a dataset-dependent summary of instrumental quality traits rather than a validated measure of sensory eating quality. Hyperspectral images were collected from pork slices, and CQI was predicted using interval combination optimization (ICO) combined with extreme gradient boosting (XGBoost). In the fixed spectral-level comparison, the SNV–ICO–XGBoost model achieved an Rp2 of 0.8670, an RMSEp of 1.7319, and an RPDp of 2.7423. Animal-level mean-spectrum validation over 50 random splits showed that PLSR achieved the highest mean prediction performance, with an Rp2 of 0.807 ± 0.058, an RMSEp of 1.857 ± 0.345, and an RPDp of 2.374 ± 0.345, providing a more conservative assessment of model performance. The predicted CQI values were further visualized qualitatively on the pork surface, supporting further evaluation of HSI for rapid and non-destructive assessment of instrumentally derived pork quality.
- Open Access
Exploring Metabolite Changes in Crispy Tilapia During the Crisping Process via 1H-NMR Metabolomic Analysis
Faba bean-fed crispy tilapia represents a commercially valuable aquaculture product, renowned for its exceptional muscle firmness. However, the dynamic changes in muscle metabolite profiles during the tilapia crisping process remain largely unelucidated. In this study, proton nuclear magnetic resonance spectroscopy (1H-NMR) combined with multivariate statistical analysis was employed to characterize and compare the muscle metabolomes of tilapia subjected to different crispness grades (CD0, CD2, CD4). A total of 11 differential metabolites were successfully identified, among which glycine, threonine, and trans-4-hydroxy-L-proline were demonstrated to be potential crispness-related biomarkers. Specifically, as the crispness grade increased from 0 to 4, the muscle contents of these key metabolites exhibited a consistent downward trend: glycine decreased significantly from 19.86 mM to 7.15 mM, threonine from 1.21 mM to 0.58 mM, and trans-4-hydroxy-L-proline from 2.25 mM to 0.89 mM. Subsequent metabolic pathway enrichment analysis further revealed that the glycine-serine-threonine metabolic pathway represented the most significantly perturbed pathway associated with the crisping process. Collectively, our findings demonstrate that faba bean-based feeding regimens enhance tilapia muscle crispness by orchestrating metabolite signatures involved in collagen biosynthesis and lipid metabolism. These results not only provide novel insights into the intrinsic molecular mechanisms underlying tilapia crisping but also establish a solid theoretical framework for the precise quality control and standardized production of high-quality crispy tilapia.
Open AccessExploring Metabolite Changes in Crispy Tilapia During the Crisping Process via 1H-NMR Metabolomic Analysis
Faba bean-fed crispy tilapia represents a commercially valuable aquaculture product, renowned for its exceptional muscle firmness. However, the dynamic changes in muscle metabolite profiles during the tilapia crisping process remain largely unelucidated. In this study, proton nuclear magnetic resonance spectroscopy (1H-NMR) combined with multivariate statistical analysis was employed to characterize and compare the muscle metabolomes of tilapia subjected to different crispness grades (CD0, CD2, CD4). A total of 11 differential metabolites were successfully identified, among which glycine, threonine, and trans-4-hydroxy-L-proline were demonstrated to be potential crispness-related biomarkers. Specifically, as the crispness grade increased from 0 to 4, the muscle contents of these key metabolites exhibited a consistent downward trend: glycine decreased significantly from 19.86 mM to 7.15 mM, threonine from 1.21 mM to 0.58 mM, and trans-4-hydroxy-L-proline from 2.25 mM to 0.89 mM. Subsequent metabolic pathway enrichment analysis further revealed that the glycine-serine-threonine metabolic pathway represented the most significantly perturbed pathway associated with the crisping process. Collectively, our findings demonstrate that faba bean-based feeding regimens enhance tilapia muscle crispness by orchestrating metabolite signatures involved in collagen biosynthesis and lipid metabolism. These results not only provide novel insights into the intrinsic molecular mechanisms underlying tilapia crisping but also establish a solid theoretical framework for the precise quality control and standardized production of high-quality crispy tilapia.
- 15 February 2025
- Published by Elsevier in Journal of Chromatography A
- Vol. 1746, 465783
Analysis of volatile flavor and lipids in different breeds of pork using electronic noses, GC–MS and UPLC-MS/MS
- 15 February 2025
- Published by Elsevier in Journal of Chromatography A
- Vol. 1746, 465783
Analysis of volatile flavor and lipids in different breeds of pork using electronic noses, GC–MS and UPLC-MS/MS
- 10 November 2024
- Published by Elsevier in Meat Science
- Vol. 220, 109708
Simultaneous monitoring of two comprehensive quality evaluation indexes of frozen-thawed beef meatballs using hyperspectral imaging and multi-task convolutional neural network
- 10 November 2024
- Published by Elsevier in Meat Science
- Vol. 220, 109708
Simultaneous monitoring of two comprehensive quality evaluation indexes of frozen-thawed beef meatballs using hyperspectral imaging and multi-task convolutional neural network
- Open Access
- 10 September 2024
- Published by Wiley in Food Bioengineering
- Vol. 3 (3) , 301-313
Effect of sodium bicarbonate with ultrasound on reduced‐salt Chaozhou beef meatballs quality: Physicochemical and sensory properties
This study aimed to create a reduced‐salt version of Chaozhou beef meatballs (CBMs) by employing ultrasound treatment (0 and 30 min) combined with sodium bicarbonate (0%, 0.15%, and 0.3%). The ultrasound‐assisted sodium bicarbonate treatment significantly enhanced pH, salt‐soluble protein solubility (SSP), water‐holding capacity (WHC), and storage modulus (G′) of the CBMs (p < 0.05). Specifically, after treatment, the increase in pH value promoted the solubilization of SSP, with the content increasing from 28.23% to 56.53%. Moreover, the initial relaxation times (T21 and T22) were shortened, indicating a decrease in water mobility, as evidenced by an increase in WHC from 85% to 87%. Furthermore, the ultrasound treatment effectively facilitated protein unfolding, increased β‐sheet secondary structure content, augmented hydrogen and disulfide bond proportions, and resulted in a denser and more uniform gel structure. Consequently, the hardness of the CBMs was significantly improved (p < 0.05). Sensory evaluation revealed that the treated reduced‐salt CBMs were comparable to those produced by conventional methods. Therefore, combining sodium bicarbonate with ultrasound treatment is a viable approach to mitigate the negative effects of reduced salt content and produce high‐quality reduced‐salt CBMs.
- 10 September 2024
- Published by Wiley in Food Bioengineering
- Vol. 3 (3) , 301-313
Open AccessEffect of sodium bicarbonate with ultrasound on reduced‐salt Chaozhou beef meatballs quality: Physicochemical and sensory properties
This study aimed to create a reduced‐salt version of Chaozhou beef meatballs (CBMs) by employing ultrasound treatment (0 and 30 min) combined with sodium bicarbonate (0%, 0.15%, and 0.3%). The ultrasound‐assisted sodium bicarbonate treatment significantly enhanced pH, salt‐soluble protein solubility (SSP), water‐holding capacity (WHC), and storage modulus (G′) of the CBMs (p < 0.05). Specifically, after treatment, the increase in pH value promoted the solubilization of SSP, with the content increasing from 28.23% to 56.53%. Moreover, the initial relaxation times (T21 and T22) were shortened, indicating a decrease in water mobility, as evidenced by an increase in WHC from 85% to 87%. Furthermore, the ultrasound treatment effectively facilitated protein unfolding, increased β‐sheet secondary structure content, augmented hydrogen and disulfide bond proportions, and resulted in a denser and more uniform gel structure. Consequently, the hardness of the CBMs was significantly improved (p < 0.05). Sensory evaluation revealed that the treated reduced‐salt CBMs were comparable to those produced by conventional methods. Therefore, combining sodium bicarbonate with ultrasound treatment is a viable approach to mitigate the negative effects of reduced salt content and produce high‐quality reduced‐salt CBMs.
- 18 July 2024
- Published by Elsevier in Food Chemistry
- Vol. 460 (Pt 1) , 140519
A molecular imprinted ratiometric fluorescence sensor based on blue/orange MXene quantum dots for visual detection of histamine
- 18 July 2024
- Published by Elsevier in Food Chemistry
- Vol. 460 (Pt 1) , 140519
A molecular imprinted ratiometric fluorescence sensor based on blue/orange MXene quantum dots for visual detection of histamine
- 30 May 2023
- Published by Elsevier in Food Chemistry
- Vol. 425, 136469
A multi-block data approach to assessing beef quality: ComDim analysis of hyperspectral imaging, 1H NMR, electronic nose and quality parameters data
- 30 May 2023
- Published by Elsevier in Food Chemistry
- Vol. 425, 136469
A multi-block data approach to assessing beef quality: ComDim analysis of hyperspectral imaging, 1H NMR, electronic nose and quality parameters data
- 27 May 2023
- Published by Elsevier in Food Chemistry
- Vol. 424, 136479
Qualitative and quantitative analysis of four benzimidazole residues in food by surface-enhanced Raman spectroscopy combined with chemometrics
- 27 May 2023
- Published by Elsevier in Food Chemistry
- Vol. 424, 136479
Qualitative and quantitative analysis of four benzimidazole residues in food by surface-enhanced Raman spectroscopy combined with chemometrics