Jie Zhao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Jie Zhao has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Ailiang Chen
State Key Laboratory for Quality and Safety of Agro-Products, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Beijing 100081, China
1 shared publication - Chuan Liu
State Key Laboratory for Quality and Safety of Agro-Products, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Beijing 100081, China
1 shared publication - Fengmei Sun
College of Agriculture, Forestry and Technology, Hebei North University, Zhangjiakou 075000, China
1 shared publication - Hui Li
College of Agriculture, Forestry and Technology, Hebei North University, Zhangjiakou 075000, China
1 shared publication - Jing Liu
State Key Laboratory for Quality and Safety of Agro-Products, Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Beijing 100081, China
1 shared publication - Jing Yuan
College of Agriculture, Forestry and Technology, Hebei North University, Zhangjiakou 075000, China
1 shared publication
Latest Publications
- Open Access
Preparation and Identification of Antioxidant Peptides in Quinoa
This study used locally sourced black, red, and white quinoa from Zhangjiakou as experimental materials to optimize the preparation process of quinoa antioxidant peptides and identify their sequence characteristics. Protein was extracted using the alkali-soluble acid precipitation method. The optimal hydrolytic enzyme was selected by comparing the hydrolysis effects of eight proteases. Enzymatic hydrolysis conditions were optimized using single-factor experiments and response surface methodology. After purification by Sephadex G-15 gel filtration chromatography, peptide sequences were identified by liquid chromatography–tandem mass spectrometry (LC-MS/MS) combined with De novo sequencing technology. The results showed that black quinoa and alcalase were identified as the optimal raw material and hydrolytic enzyme, respectively. The optimal enzymatic hydrolysis conditions were an enzyme dosage of 4000 U·g−1, hydrolysis time of 3.5 h, temperature of 42 °C, and pH 7.6, under which the average DPPH radical scavenging rate reached 86.61%. The purified G-1 fraction exhibited the highest antioxidant activity. A total of 1549 peptide sequences with confidence ≥90% were identified, among which peptides containing two or more hydrophobic amino acids accounted for 60.62%. This compositional feature is consistent with structural characteristics commonly associated with antioxidant peptides. This study provides a reference for the processing of quinoa-based functional ingredients.
Open AccessPreparation and Identification of Antioxidant Peptides in Quinoa
This study used locally sourced black, red, and white quinoa from Zhangjiakou as experimental materials to optimize the preparation process of quinoa antioxidant peptides and identify their sequence characteristics. Protein was extracted using the alkali-soluble acid precipitation method. The optimal hydrolytic enzyme was selected by comparing the hydrolysis effects of eight proteases. Enzymatic hydrolysis conditions were optimized using single-factor experiments and response surface methodology. After purification by Sephadex G-15 gel filtration chromatography, peptide sequences were identified by liquid chromatography–tandem mass spectrometry (LC-MS/MS) combined with De novo sequencing technology. The results showed that black quinoa and alcalase were identified as the optimal raw material and hydrolytic enzyme, respectively. The optimal enzymatic hydrolysis conditions were an enzyme dosage of 4000 U·g−1, hydrolysis time of 3.5 h, temperature of 42 °C, and pH 7.6, under which the average DPPH radical scavenging rate reached 86.61%. The purified G-1 fraction exhibited the highest antioxidant activity. A total of 1549 peptide sequences with confidence ≥90% were identified, among which peptides containing two or more hydrophobic amino acids accounted for 60.62%. This compositional feature is consistent with structural characteristics commonly associated with antioxidant peptides. This study provides a reference for the processing of quinoa-based functional ingredients.
- Open Access
Multi-Omics Mining of Characteristic Quality Factors Boosts the Brand Enhancement of the Geographical Indication Product—Pingliang Red Cattle
Pingliang Red Cattle, a renowned geographical indication product in China, is distinguished by its superior meat quality, yet the scientific basis for its unique attributes remains underexplored. This study integrated metabolomic and transcriptomic analyses to elucidate the biochemical and physiological factors underlying the enhanced flavor, color stability, and tenderness of Pingliang Red Cattle beef compared to Qinchuan and Simmental cattle. Metabolomic profiling revealed significantly elevated levels of inosine monophosphate (IMP, 2.86–3.96× higher) and glutathione (GSH, 2.42–5.43× higher) in Pingliang Red Cattle, contributing to intense umami flavor and prolonged meat color retention. Notably, ergothioneine (EGT), a potent antioxidant, was identified for the first time in Pingliang Red Cattle beef, with concentrations 2.55× and 4.25× higher than in Qinchuan and Simmental, respectively. Transcriptomic analysis highlighted the upregulation of 21 tenderness-related genes (e.g., FABP3, PRDX6, CAST) and key enzymes in purine and glutathione metabolism pathways (e.g., PDE4D, ADSL, GGT1), correlating with meat tenderness and the improved meat quality. Additionally, Pingliang Red Cattle’s natural forage-rich diet and low-density rearing practices were critical in enhancing these traits. These findings provide a scientific foundation for Pingliang Red Cattle’s premium quality, offering actionable insights for GI product branding, quality optimization, and market competitiveness. The multi-omics approach established here serves as a paradigm for quality assessment and improvement of other GI agricultural products, bridging traditional reputation with molecular evidence.
Open AccessMulti-Omics Mining of Characteristic Quality Factors Boosts the Brand Enhancement of the Geographical Indication Product—Pingliang Red Cattle
Pingliang Red Cattle, a renowned geographical indication product in China, is distinguished by its superior meat quality, yet the scientific basis for its unique attributes remains underexplored. This study integrated metabolomic and transcriptomic analyses to elucidate the biochemical and physiological factors underlying the enhanced flavor, color stability, and tenderness of Pingliang Red Cattle beef compared to Qinchuan and Simmental cattle. Metabolomic profiling revealed significantly elevated levels of inosine monophosphate (IMP, 2.86–3.96× higher) and glutathione (GSH, 2.42–5.43× higher) in Pingliang Red Cattle, contributing to intense umami flavor and prolonged meat color retention. Notably, ergothioneine (EGT), a potent antioxidant, was identified for the first time in Pingliang Red Cattle beef, with concentrations 2.55× and 4.25× higher than in Qinchuan and Simmental, respectively. Transcriptomic analysis highlighted the upregulation of 21 tenderness-related genes (e.g., FABP3, PRDX6, CAST) and key enzymes in purine and glutathione metabolism pathways (e.g., PDE4D, ADSL, GGT1), correlating with meat tenderness and the improved meat quality. Additionally, Pingliang Red Cattle’s natural forage-rich diet and low-density rearing practices were critical in enhancing these traits. These findings provide a scientific foundation for Pingliang Red Cattle’s premium quality, offering actionable insights for GI product branding, quality optimization, and market competitiveness. The multi-omics approach established here serves as a paradigm for quality assessment and improvement of other GI agricultural products, bridging traditional reputation with molecular evidence.