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作者	单位
魏霞，陈功海，龙周锴，范小峰，张文英，徐延浩	(1.长江大学农学院涝渍灾害与湿地农业湖北省重点实验室/主要粮食作物产业化湖北省协同创新中心，湖北荆州 434100； 2.荆州市农业科学院，湖北荆州 434025)

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中文摘要:

为探索快速高效测定大麦籽粒中抗性淀粉含量的方法，利用衰减全反射中红外（attenuated total reflection mid-infrared spectroscopy,ATR-MIR）和近红外（near-infrared spectroscopy,NIR）光谱技术，分别用3种不同方法进行预处理，建立大麦样品的抗性淀粉含量快速测定红外模型，通过不同预处理预测模型的校正和内部交叉验证结果的比较，依据决定系数（r）和均方根误差（RMSE）筛选出基于ATR-MIR和NIR光谱的最佳预测模型，再对最佳预测模型进行外部验证。结果表明，经基线位移校正+范围归一化（BOC+RN）预处理后的PLS模型为最佳ATR-MIR预测模型；经标准正态变换+Savitzky-Golay法一阶求导（SNV+1thD）的预处理模型为最佳NIR预测模型。用验证集材料对BOC+RN和SNV+1thD最佳预测模型的预测效果进行外部验证，光谱预测值与化学测定值之间没有显著差异，说明两种方法均可以用于大麦籽粒抗性淀粉含量测定；ATR-MIR光谱比NIR光谱具有更好的预测能力。

英文摘要:

In order to determine resistant starch content of barley grains rapidly and efficiently,the attenuated total reflection mid-infrared spectroscopy(ATR-MIR) and near-infrared spectroscopy(NIR) techniques was applied in this paper. After the spectrum was collected,three different pretreatments were used to establish the rapid determination infrared models for resistant starch content in barley samples. The coefficient of determination(r) and root mean square error(RMSE) of calibration and the internal cross-validation results from different pretreatment models were used to evaluate for the best ATR-MIR and NIR prediction models. The externally verification was performed for the best ATR-MIR and NIR prediction models. The results showed that the baseline offset correction+range normalization(BOC+RN) pretreatment method was selected as the best ATR-MIR prediction model. Meanwhile,the best NIR prediction model was obtained by the standard normal variate+first derivative Savitzky-Golay(SNV+1thD) pretreatment method. No significant difference was detected between the values predicted by the ATR-MIR model of BOC+RN and the NIR model of SNV+1thD and chemical measured values for the validation set. These results indicated that both the best prediction models of ATR-MIR and NIR spectral can be used for the determination of resistant starch content in barley grains.The ATR-MIR spectroscopy performed a better predictive ability than the NIR spectroscopy.

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