Suppr超能文献

使用拉曼光谱预测牛胸腰段最长肌的嫩度

Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy.

作者信息

Coria Maria Sumampa, Castaño Ledesma María Sofía, Gómez Rojas Jorge Raúl, Grigioni Gabriela, Palma Gustavo Adolfo, Borsarelli Claudio Darío

机构信息

Instituto de Bionanotecnología del NOA (INBIONATEC), CONICET, Universidad Nacional de Santiago del Estero, G4206XCP, Santiago del Estero, Argentina.

Universidad Nacional de Santiago del Estero. Facultad de Agronomía y Agroindustrias. Instituto para el desarrollo agropecuario del semiárido (INDEAS), G4200ABT, Santiago del Estero, Argentina.

出版信息

Anim Biosci. 2023 Sep;36(9):1435-1444. doi: 10.5713/ab.22.0451. Epub 2023 Feb 26.

Abstract

OBJECTIVE

This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle.

METHODS

Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups.

RESULTS

Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R2 = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm-1, suggests that the content of this amino acid could explain the differences between samples.

CONCLUSION

Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.

摘要

目的

本研究旨在评估拉曼光谱技术作为一种非侵入性工具预测布拉福德牛胸腰段最长肌肉质性状的能力。

方法

采用经典肉质分析技术和785 nm激光激发的拉曼光谱技术对30份布拉福德阉牛肉样进行分析。测定了持水力(WHC)、肌内脂肪含量(IMF)、蒸煮损失(CL)以及通过质地剖面分析记录的硬度、内聚性和咀嚼性,同时通过扫描电子显微镜测定了纤维直径和肌节长度。采用沃纳-布拉茨勒剪切力(WBSF)分析区分嫩肉组和老肉组。

结果

与老肉相比,嫩肉样品的内聚性和CL值较高,而WHC、IMF值较低,肌节较短。拉曼光谱分析能够区分嫩肉和老肉样品。拉曼预测的品质属性与物理测量值之间的相关性导致硬度的R2值为0.69,WBSF的R2值为0.58。硬度(r = 0.84)和WBSF(r = 0.79)参数与1003 cm-1处苯丙氨酸拉曼信号的皮尔逊相关系数表明,该氨基酸的含量可以解释样品之间的差异。

结论

785 nm激光激发的拉曼光谱是一种适用于识别具有不同品质属性牛肉的准确技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6574/10472156/0b66bf6f0d6d/ab-22-0451f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验