红外光谱在牛奶生产和检测方面的研究进展

Research advances in milk production and detection by infrared spectroscopy

红外光谱不仅可以反应物质的结构组成,还能够随着成分含量变化形成不同响应值,红外技术也被广泛应用于畜产品的化学成分含量检测和质量评估。牛奶是人类膳食结构中的重要组成部分,对其营养成分和质量的准确评估有着非常重要的生产意义。该文介绍了红外光谱技术牛奶生产中各个环节中的应用,通过测定牛奶成分的含量,红外技术被用于产品定价和品质评价;掺假物质在牛奶中会引起光谱的变化,定性和定量模型的建立为牛奶质量快速鉴别诊断提供了便捷途径;牧场生产中,光谱被用于诊断奶牛酮病、机体能量状态。该文对近年来国外利用红外光谱技术在牛奶成分和凝集性能预测、掺假和质量检测、奶牛健康养殖等方面文献进行综述,重点介绍乳蛋白成分、脂肪酸、凝集性能等牛奶性状红外光谱模型以及牛奶光谱特征,对不同研究中模型性能进行比较,以较为全面的评估光谱技术在牛奶性状、质量和奶牛养殖等方面的应用,并为今后的检测和研究发展提供参考。

Infrared spectrum（IR） reflects the molecular structure of unknown material, and responds with varied chemical bonds. So it is used to determine chemical composition contents and evaluate product quality in livestock products extensively. Milk is a key part in human nutrition intake. And the exact determination of nutrients and the proper evaluation of quality have important significance for milk production. This paper introduced the application of IR in each link of milk production. Fat and protein contents in milk vary in different dairy farms, and many factors affect milk quality, which contribute to the final price of raw milk in acquisition. Milk composition determination using IR is likely to give a quick and comprehensive evaluation for milk quality. Unknown and undeclared adulterants of milk threaten consumers＇ health seriously. Qualitative and quantitative analysis models provide a convenient identification method for milk adulteration based on spectrum variation of adulterants. Milk trait related to cow health and robustness is very important for dairy farm management. Diagnosis of ketoacidosis and body energy status using IR instruments is helpful for accurate breeding in dairy farm. This paper reviewed recent literatures in order to evaluate the general trends of infrared spectroscopy application on milk production. On the basis of introducing the data processing and model building, this paper presented a review of the overseas and domestic researches on milk composition and milk coagulation properties using IR, especially for milk protein fraction and fatty acids composition. We compared the model performance of optical spectroscopy from different research reports. The effects of reference method, sample size and unit on model parameters were discussed in particular. Moreover, IR was efficient for phenotypes assessment and genetic selection based on these models. The variances of absorption on IR caused by adulterants spiked in milk not only indicated the appearance of milk adulteration, but also displayed the difference between cow milk and soy milk. Milk spectrum was proved to be heritable in specified wavelength, while some other bands varied with different enviromental factors. And many literatures confirmed the correlation between cow＇s feed and milk optical characteristic. Although nonnegligible random error and data variability existed in sampling, IR reflected energy status of dairy cows with moderate accuracy. Mid-IR has been also studied as a potential tool to predict several milk traits related to cow health, such as ketone bodies, which were closely related to cow fertility and production. IR was also used to predict methane emissions from cow digestive tract. The advantages of infrared spectroscopy analysis were emphasized, and we also listed potential challenges existing in instrument setting, data collection and model building. The objective of this paper was to highlight the application of infrared spectroscopy on milk traits, which was related to milk composition and quality, and dairy farm management. Considering the overall trends, we proposed some future research directions of this methodology on milk production, including prediction of trace nutrients, uniformity of references methods and units, possibility of spectrum assessment, and diagnosis of disorder and fertility. With the future developments in these areas, infrared methods would be more popular in milk composition determination, quality control, and dairy farm managements, with higher accuracy, efficiency and convenience.