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Lee Y, Lee KG. Effects of pan- and air fryer-roasting on volatile and umami compounds and antioxidant activity of dried laver (Porphyra dentata). Food Chem 2024; 458:140289. [PMID: 38959799 DOI: 10.1016/j.foodchem.2024.140289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/03/2024] [Accepted: 06/29/2024] [Indexed: 07/05/2024]
Abstract
This study aimed to investigate the impact of pan- and air fryer-roasting on the volatiles, umami compounds, antioxidant activity, and sensory attributes of dried laver (Porphyra dentata). To assess the influence of time and temperature, pan-roasting was conducted at temperatures of 250, 300, and 350 °C for 5, 10, and 15 s, respectively. For air fryer-roasting, dried laver was roasted at 160, 170, and 180 °C for 2, 4, and 6 min, respectively. In both roasting methods, the levels of 1,5-octadien-3-ol and 1-octen-3-ol significantly decreased (p < 0.05) with increased time and temperature. The Equivalent Umami Concentration ranged from 94.89 to 518.09 g MSG/100 g. The antioxidant activity significantly increased (p < 0.05) with higher roasting temperatures and longer durations, whereas pigment content significantly decreased. The browning index increased by 64% and 43% for the pan and air frying methods, respectively. The samples pan-roasted at 300 °C for 15 s obtained the highest sensory scores.
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Affiliation(s)
- Yoojeong Lee
- Department of Food Science and Biotechnology, Dongguk University-Seoul, 32, Dongguk-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do, 10326, Republic of Korea
| | - Kwang-Geun Lee
- Department of Food Science and Biotechnology, Dongguk University-Seoul, 32, Dongguk-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do, 10326, Republic of Korea.
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Lee YJ, Uh YR, Kim YM, Kim CM, Jang CS. Characterization and comparative analysis of the complete organelle genomes of three red macroalgae species (Neoporphyra dentata, Neoporphyra seriata, and Neopyropia yezoensis) and development of molecular makers for their identification. Genes Genomics 2024; 46:355-365. [PMID: 37995039 DOI: 10.1007/s13258-023-01472-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 10/22/2023] [Indexed: 11/24/2023]
Abstract
BACKGROUND Many species of red algae belonging to the phylum Rhodophyta are consumed by humans as raw materials for nutrition and medicine. As the seaweed market grows, the importance of the laver species has increased. The classification of red algal species has changed significantly, and the accuracy of this classification has improved significantly in recent years. Here, we report the complete circular genomes of the chloroplasts (cp) and mitochondria (mt) of three laver species (Neoporphyra dentata, Neoporphyra seriata, and Neopyropia yezoensis). OBJECTIVE This study aims to assemble, annotate, and characterize the organization of the organelle genomes of three laver species, conduct comparative genomic studies, and develop molecular markers based on SNPs. METHODS We analyzed organelle genome structures, repeat sequences, sequence divergence, gene rearrangements, and phylogenetic relationships of three laver species. RESULTS The chloroplast genomes of the three species contained an average of 212 protein-coding genes (PCGs), while the mitochondrial genomes contained an average of 25 PCGs. We reconstructed the phylogenetic trees based on both chloroplast and mitochondrial genomes using 201 and 23 PCGs (in cp and mt genomes, respectively) shared in the class Bangiophyceae (and five species of Florideophyceae class used as an outgroup). In addition, 12 species-specific molecular markers were developed for qRT-PCR analysis. CONCLUSIONS This is the first report of Neoporphyra seriata complete organellar genomes. With the results, this study provides useful genetic information regarding taxonomic discrepancies, the reconstruction of phylogenetic trees, and the evolution of red algae. Moreover, the species-specific markers can be used as fast and easy methods to identify a target species.
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Affiliation(s)
- Yong Jin Lee
- Agriculture and Life Sciences Research Institute, Kangwon National University, Chuncheon, Republic of Korea
- Plant Genomics Laboratory, Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon, Republic of Korea
| | - Yo Ram Uh
- Plant Genomics Laboratory, Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon, Republic of Korea
| | - Yeon Mi Kim
- Plant Genomics Laboratory, Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon, Republic of Korea
| | - Cheol Min Kim
- Plant Genomics Laboratory, Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon, Republic of Korea
| | - Cheol Seong Jang
- Agriculture and Life Sciences Research Institute, Kangwon National University, Chuncheon, Republic of Korea.
- Plant Genomics Laboratory, Interdisciplinary Program in Smart Agriculture, Kangwon National University, Chuncheon, Republic of Korea.
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Lu ZB, Li YD, Jiang SG, Yang QB, Jiang S, Huang JH, Yang LS, Chen X, Zhou FL. Transcriptome analysis of hepatopancreas in penaeus monodon under acute low pH stress. FISH & SHELLFISH IMMUNOLOGY 2022; 131:1166-1172. [PMID: 36410647 DOI: 10.1016/j.fsi.2022.11.031] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 11/12/2022] [Accepted: 11/17/2022] [Indexed: 06/16/2023]
Abstract
The decrease of seawater pH can affect the metabolism, acid-base balance, immune response and immunoprotease activity of aquatic animals, leading to aquatic animal stress, impairing the immune system of aquatic animals and weakening disease resistance, etc. In this study, we performed high-throughput sequencing analysis of the hepatopancreas transcriptome library of low pH stress penaeus monodon, and after sequencing quality control, a total of 43488612-56271828 Clean Reads were obtained, and GO annotation and KEGG pathway enrichment analysis were performed on the obtained Clean Reads, and a total of 395 DEGs were identified. we mined 10 differentially expressed and found that they were significantly enriched in the Metabolic pathways (ko01100), Biosynthesis of secondary metabolites (ko01110), Nitrogen metabolism (ko00910) pathways, such as PIGA, DGAT1, DGAT2, UBE2E on Metabolic pathways; UGT, GLT1, TIM genes on Biosynthesis of secondary metabolites; CA, CA2, CA4 genes on Nitrogen metabolism, are involved in lipid metabolism, induction of oxidative stress and inflammation in the muscular body of spot prawns. These genes play an important role in lipid metabolism, induction of oxidative stress and inflammatory response in the muscle of the shrimp. In summary, these genes provide valuable reference information for future breeding of low pH-tolerant shrimp.
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Affiliation(s)
- Zhi-Bin Lu
- South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, Guangzhou, 510300, China; College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, 201306, China
| | - Yun-Dong Li
- South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, Guangzhou, 510300, China; Hainan Yazhou Bay Seed Laboratory, Sanya, 572025, China
| | - Shi-Gui Jiang
- South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, Guangzhou, 510300, China; College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, 201306, China; Key Laboratory of Efficient Utilization and Processing of Marine Fishery Resources of Hainan Province, Sanya Tropical Fisheries Research Institute, Sanya, 572018, China
| | - Qi-Bin Yang
- South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, Guangzhou, 510300, China
| | - Song Jiang
- South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, Guangzhou, 510300, China
| | - Jian-Hua Huang
- South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, Guangzhou, 510300, China
| | - Li-Shi Yang
- South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, Guangzhou, 510300, China
| | - Xu Chen
- Key Laboratory of Efficient Utilization and Processing of Marine Fishery Resources of Hainan Province, Sanya Tropical Fisheries Research Institute, Sanya, 572018, China
| | - Fa-Lin Zhou
- South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory of South China Sea Fishery Resources Exploitation and Utilization, Ministry of Agriculture and Rural Affairs, Guangzhou, 510300, China; College of Fisheries and Life Science, Shanghai Ocean University, Shanghai, 201306, China; Key Laboratory of Efficient Utilization and Processing of Marine Fishery Resources of Hainan Province, Sanya Tropical Fisheries Research Institute, Sanya, 572018, China.
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Yang M, Ma L, Yang X, Li L, Chen S, Qi B, Wang Y, Li C, Yang S, Zhao Y. Bioinformatic Prediction and Characterization of Proteins in Porphyra dentata by Shotgun Proteomics. Front Nutr 2022; 9:924524. [PMID: 35873412 PMCID: PMC9301277 DOI: 10.3389/fnut.2022.924524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 05/30/2022] [Indexed: 11/13/2022] Open
Abstract
Porphyra dentata is an edible red seaweed with high nutritional value. It is widely cultivated and consumed in East Asia and has vast economic benefits. Studies have found that P. dentata is rich in bioactive substances and is a potential natural resource. In this study, label-free shotgun proteomics was first applied to identify and characterize different harvest proteins in P. dentata. A total of 13,046 different peptides were identified and 419 co-expression target proteins were characterized. Bioinformatics was used to study protein characteristics, functional expression, and interaction of two important functional annotations, amino acid, and carbohydrate metabolism. Potential bioactive peptides, protein structure, and potential ligand conformations were predicted, and the results suggest that bioactive peptides may be utilized as high-quality active fermentation substances and potential targets for drug production. Our research integrated the global protein database, the first time bioinformatic analysis of the P. dentata proteome during different harvest periods, improves the information database construction and provides a framework for future research based on a comprehensive understanding.
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Affiliation(s)
- Mingchang Yang
- Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- College of Food Science and Bioengineering, Tianjin Agricultural University, Tianjin, China
- Co-innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang, China
| | - Lizhen Ma
- College of Food Science and Bioengineering, Tianjin Agricultural University, Tianjin, China
| | - Xianqing Yang
- Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- Co-innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang, China
- Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian, China
| | - Laihao Li
- Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- Co-innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang, China
- Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian, China
| | - Shengjun Chen
- Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- Co-innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang, China
| | - Bo Qi
- Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- Co-innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang, China
| | - Yueqi Wang
- Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- Co-innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang, China
| | - Chunsheng Li
- Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian, China
| | - Shaoling Yang
- Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- Co-innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang, China
| | - Yongqiang Zhao
- Key Laboratory of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs, National R&D Center for Aquatic Product Processing, South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- Co-innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang, China
- Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian, China
- *Correspondence: Yongqiang Zhao,
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