| 杨水艳
彭涛
杨瑾
陈国艳
郭颖
陶银
刘付英
邵志凌.近红外光谱法快速检测美藤果主要品质指标的定量模型研究[J].中国油脂,2020,45(3):38~43.[GUO Ying
TAO Yin
LIU Fuying
SHAO Zhiling.Quantitative model for rapid detection of main quality index of Sacha Inchi (Plukenetia volubilis L.) seed by near infrared spectrometry[J].China Oils and Fats,2020,45(3):38~43.] |
| 近红外光谱法快速检测美藤果主要品质指标的定量模型研究 |
| Quantitative model for rapid detection of main quality index of Sacha Inchi (Plukenetia volubilis L.) seed by near infrared spectrometry |
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| DOI：10.12166/j.zgyz.1003-7969/2020.03.009 |
| 中文关键词: 美藤果 近红外光谱法 水分含量 含油量 蛋白质含量 |
| 英文关键词:Sacha Inchi (Plukenetia volubilis L.) seed near infrared spectrometry moisture content oil content protein content |
| 基金项目:云南省科技厅青年项目（2017FD026） |
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| 摘要点击次数: 1597 |
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| 中文摘要: |
| 美藤果含有丰富的油脂、蛋白质等营养物质，具有重要的营养价值。为了快速检测美藤果品质，采用传统国标方法获得美藤果水分含量、含油量（湿基）和蛋白质含量（湿基）的化学值，之后对美藤果颗粒及美藤果粉的近红外光谱全谱及不同波段光谱进行预处理，通过偏最小二乘法分别建立了美藤果颗粒及美藤果粉的校正模型。结果显示，美藤果颗粒和美藤果粉建立的校正模型的相关系数（Rc）均大于0.94，校正均方根误差（RMSEC）小于0.45%，交叉验证相关系数（Rcv）大于091，验证均方根误差（RMSECV）小于0.53%。用建立的美藤果颗粒和美藤果粉校正曲线对未参与建模的20个样品进行了近红外检测，结果显示，用两种方法建立的校正模型都能较好地实现对美藤果水分、含油量（湿基）和蛋白质含量（湿基）的预测，但是使用美藤果颗粒建立的校正模型进行美藤果品质检测更简便，且对样品没有破坏性。 |
| 英文摘要: |
| Sacha Inchi seed is rich in nutrients, such as fat and protein, and has important nutritional value. In order to rapidly detect the quality of Sacha Inchi seed, the chemical values of moisture content, oil content (wet basis) and protein content (wet basis) in Sacha Inchi seed were obtained by traditional national standard methods. The full and part near infrared spectrum of Sacha Inchi seed and its powder were treated with differment method, and then the calibration models of Sacha Inchi seed and its powder were established by partial least squares regression. The results showed that the correlation coefficients(Rc) of the calibration models were all high than 0.94, the corrected root mean square error (RMSEC) was less than 0.45%, the correlation coefficients of the cross validation models (Rcv) were high than 091, and the root mean square error of cross validation (RMSECV) was less than 0.53%. Near infrared (NIR) measurements were carried out on 20 samples which were not involved in the established models, and the results showed that the calibration models could predict moisture content, oil content (wet basis) and protein content (wet basis) of Sacha Inchi seed and its powder. However, the calibration model established by Sacha Inchi seed was more convenient and non-destructive to the samples. |
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