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首页> 外文期刊>Journal of near infrared spectroscopy >Predicting intramuscular fat content in pork and beef by near infrared spectroscopy
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Predicting intramuscular fat content in pork and beef by near infrared spectroscopy

机译:用近红外光谱法预测猪肉和牛肉中的肌内脂肪含量

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Prediction ability of near infrared (NIR) spectroscopy for intramuscular fat content (IMF) determination was studied. The material comprised 126 muscle samples; 46 pig longissimus dorsi and semitendinosus and 34 beef longissimus dorsi muscle samples. The IMF content was chemically determined in duplicate using two different chemical methods; fat extraction according to Folch et al. and Soxhlet extraction with hydrolysis according to SIST ISO 1443. Folch extraction underestimated IMF content compared to Soxhlet extraction with hydrolysis (-0.32%, P< 0.0001). Similar repeatability was obtained for Folch and Soxhlet extraction with hydrolysis (0.17% and 0.18%, respectively, P< 0.0001). Sample spectra were scanned from 400-2500 nm by the NIR Systems model 6500 spectrophotometer (Silver Spring, MD, USA) and analysed by WinlSI II on minced and intact (pork only) samples. Modified partial least squares regression was used to develop models and to obtain calibration statistics: coefficient of determination in calibration ((R{sup}2){sub}C) and cross-validation ((R{sup}2){sub}(CV)) and standard error in calibration (SEC) and cross-validation (SECV). We prepared different models (for a single muscle/common, by applying NIR spectrum or the whole spectrum, on intact and minced samples). Obtained models proved the remarkable prediction ability of NIR spectroscopy to determine IMF content (R2CV between 0.84 and 0.99; SECV between 0.14% and 0.53%) and confirms the potential of NIR spectroscopy to replace laborious chemical procedures. Regarding the factors studied, calibrations were less accurate for intact than for minced samples; the use of an NIR spectrum compared to the whole spectrum had no important effect on the prediction ability. According to calibration statistics, the prediction using a common equation for several muscles seems more reliable than the equations within the muscle, but the latter showed lower bias.
机译:研究了近红外(NIR)光谱法测定肌内脂肪含量(IMF)的预测能力。该材料包括126个肌肉样本。取46头猪背最长肌和半腱肌和34头牛肉背最长肌肌肉样本。使用两种不同的化学方法一式两份地确定IMF含量;根据Folch等人的脂肪提取。以及按照SIST ISO 1443进行水解的索氏提取。与水解索氏提取相比,化学提取低估了IMF含量(-0.32%,P <0.0001)。水解提取的Folch和Soxhlet提取具有相似的重复性(分别为0.17%和0.18%,P <0.0001)。用NIR Systems的6500型分光光度计(Silver Spring,MD,USA)在400-2500 nm范围内扫描样品光谱,并用WinlSI II对切碎和完整(仅猪肉)的样品进行分析。修正的偏最小二乘回归用于开发模型并获得校准统计数据:校准中的确定系数((R {sup} 2){sub} C)和交叉验证((R {sup} 2){sub}( CV))以及校准中的标准误差(SEC)和交叉验证(SECV)。我们准备了不同的模型(对于完整的和切碎的样品,通过应用NIR光谱或整个光谱,对于单个肌肉/普通样品)。获得的模型证明了NIR光谱测定IMF含量的显着预测能力(R2CV在0.84至0.99之间; SECV在0.14%至0.53%之间),并证实了NIR光谱法可替代费力的化学程序。关于所研究的因素,完整的标定比切碎的样品的标定准确度低。与整个光谱相比,使用NIR光谱对预测能力没有重要影响。根据校准统计数据,使用多条肌肉的通用方程进行的预测似乎比肌肉内的方程更可靠,但后者显示出较低的偏差。

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