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Evaluation of Chemical Parameters in Soft Mold-Ripened Cheese During Ripening by Mid-Infrared Spectroscopy

机译:中红外光谱法评估软质发霉干酪成熟过​​程中的化学参数

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摘要

The suitability of mid-infrared spectroscopy (MIR) to follow the evolution throughout ripening of specific physicochemical parameters in Camembert-type cheeses was evaluated. The infrared spectra were obtained directly from raw cheese samples deposited on an attenuated total reflectance crystal. Significant correlations were observed between physicochemical data, pH, acid-soluble nitrogen, nonprotein nitrogen, ammonia (NH_4~+), lactose, and lactic acid. Dry matter showed significant correlation only with lactose and nonprotein nitrogen. Principal components analysis factorial maps of physicochemical data showed a ripening evolution in 2 steps, from d 1 to d 7 and from d 8 to d 27, similar to that observed previously from infrared spectral data. Partial least squares regressions made it possible to obtain good prediction models for dry matter, acid-soluble nitrogen, nonprotein nitrogen, lactose, lactic acid, and NH_4~+ values from spectral data of raw cheese. The values of 3 statistical parameters (coefficient of determination, root mean square error of cross validation, and ratio prediction deviation) are satisfactory. Less precise models were obtained for pH.
机译:评估了中红外光谱(MIR)跟踪卡门培尔型干酪中特定理化参数整个成熟过程的演变过程。红外光谱直接从沉积在衰减的全反射率晶体上的生干酪样品中获得。在理化数据,pH,酸溶性氮,非蛋白氮,氨(NH_4〜+),乳糖和乳酸之间存在显着相关性。干物质仅与乳糖和非蛋白质氮显示显着相关。理化数据的主成分分析阶乘图显示了从d 1到d 7和从d 8到d 27分两个步骤的成熟演变,这与之前从红外光谱数据中观察到的相似。偏最小二乘回归可以从生奶酪的光谱数据中获得有关干物质,酸溶性氮,非蛋白质氮,乳糖,乳酸和NH_4〜+值的良好预测模型。 3个统计参数(确定系数,交叉验证的均方根误差和比率预测偏差)的值令人满意。 pH值的精确度较低。

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