The chemical method for the determination of the resistant starch (RS) content in grains is time-consuming and labor intensive. Near-infrared (NIR) and attenuated total reflectance mid-infrared (ATR-MIR) spectroscopy are rapid and nondestructive analytical techniques for determining grain quality. This study was the first report to establish and compare these two spectroscopic techniques for determining the RS content in wheat grains. Calibration models with four preprocessing techniques based on the partial least squares (PLS) algorithm were built. In the NIR technique, the mean normalization + Savitzky–Golay smoothing (MN + SGS) preprocessing technique had a higher coefficient of determination ( = 0.672;  = 0.552) and a relative lower root mean square error value (RMSEC = 0.385; RMSEP = 0.459). In the ATR-MIR technique, the baseline preprocessing method exhibited a better performance regarding to the values of coefficient of determination ( = 0.927;  = 0.828) and mean square error value (RMSEC = 0.153; RMSEP = 0.284). The validation of the developed best NIR and ATR-MIR calibration models showed that the ATR-MIR best calibration model has a better RS prediction ability than the NIR best calibration model. Two high grain RS content wheat mutants were screened out by the ATR-MIR best calibration model from the wheat mutant library. There was no significant difference between the predicted values and chemical measured values in the two high RS content mutants. It proved that the ATR-MIR model can be a perfect substitute in RS measuring. All the results indicated that the ATR-MIR spectroscopy with improved screening efficiency can be used as a fast, rapid, and nondestructive method in high grain RS content wheat breeding.

中文翻译：

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开发用于测定小麦籽粒中抗性淀粉含量的衰减全反射中红外 (ATR-MIR) 和近红外 (NIR) 光谱

测定谷物中抗性淀粉 (RS) 含量的化学方法费时费力。近红外 (NIR) 和衰减全反射中红外 (ATR-MIR) 光谱是用于确定谷物质量的快速无损分析技术。本研究是第一份建立和比较这两种光谱技术以确定小麦籽粒中 RS 含量的报告。建立了基于偏最小二乘法(PLS)算法的四种预处理技术的校准模型。在 NIR 技术中，均值归一化 + Savitzky-Golay 平滑（MN + SGS）预处理技术具有更高的决定系数（ = 0.672； = 0.552）和相对较低的均方根误差值（RMSEC = 0.385；RMSEP = 0.459）。在 ATR-MIR 技术中，基线预处理方法在决定系数值方面表现出更好的性能（ = 0.927； = 0.828）和均方误差值（RMSEC = 0.153；RMSEP = 0.284）。对开发的最佳NIR和ATR-MIR校准模型的验证表明，ATR-MIR最佳校准模型比NIR最佳校准模型具有更好的RS预测能力。通过ATR-MIR最佳校准模型从小麦突变体库中筛选出两个高粒RS含量的小麦突变体。两个高 RS 含量突变体的预测值和化学测量值之间没有显着差异。证明ATR-MIR模型可以完美替代RS测量。所有结果表明，具有更高筛选效率的 ATR-MIR 光谱可作为一种快速、快速、无损的方法用于高粒 RS 含量小麦育种。