Meat adulteration, mainly for the purpose of economic pursuit, is widespread and leads to serious public health risks, religious violations, and moral loss. Rapid, effective, accurate, and reliable detection technologies are keys to effectively supervising meat adulteration. Considering the importance and rapid advances in meat adulteration detection technologies, a comprehensive review to summarize the recent progress in this area and to suggest directions for future progress is beneficial. In this review, destructive meat adulteration technologies based on DNA, protein, and metabolite analyses and nondestructive technologies based on spectroscopy were comparatively analyzed. The advantages and disadvantages, application situations of these technologies were discussed. In the future, determining suitable indicators or markers is particularly important for destructive methods. To improve sensitivity and save time, new interdisciplinary technologies, such as biochips and biosensors, are promising for application in the future. For nondestructive techniques, convenient and effective chemometric models are crucial, and the development of portable devices based on these technologies for onsite monitoring is a future trend. Moreover, omics technologies, especially proteomics, are important methods in laboratory detection because they enable multispecies detection and unknown target screening by using mass spectrometry databases.

中文翻译：

---

肉制品掺假检测技术比较综述及最新进展

肉类掺假主要以经济为目的，普遍存在，并导致严重的公共卫生风险、宗教侵犯和道德损失。快速、有效、准确、可靠的检测技术是有效监督肉类掺假的关键。考虑到肉类掺假检测技术的重要性和快速发展，全面回顾总结该领域的最新进展并提出未来进展的方向是有益的。本综述对基于DNA、蛋白质和代谢物分析的破坏性肉类掺假技术和基于光谱的无损技术进行了比较分析。讨论了这些技术的优缺点、应用情况。在将来，确定合适的指标或标记对于破坏性方法尤其重要。为了提高灵敏度和节省时间，新的跨学科技术，如生物芯片和生物传感器，有望在未来得到应用。对于无损技术而言，方便有效的化学计量模型至关重要，基于这些技术的便携式设备的开发用于现场监测是未来的趋势。此外，组学技术，尤其是蛋白质组学，是实验室检测中的重要方法，因为它们可以利用质谱数据库实现多物种检测和未知目标筛选。对于无损技术而言，方便有效的化学计量模型至关重要，基于这些技术的便携式设备的开发用于现场监测是未来的趋势。此外，组学技术，尤其是蛋白质组学，是实验室检测中的重要方法，因为它们可以利用质谱数据库实现多物种检测和未知目标筛选。对于无损技术而言，方便有效的化学计量模型至关重要，基于这些技术的便携式设备的开发用于现场监测是未来的趋势。此外，组学技术，尤其是蛋白质组学，是实验室检测中的重要方法，因为它们可以利用质谱数据库实现多物种检测和未知目标筛选。