In vitro and in situ procedures performed to estimate indigestible neutral detergent fiber (iNDF) in forage or fecal samples are time consuming, costly, and limited by intrinsic factors. In contrast, near infrared reflectance spectroscopy (NIRS) has become widely recognized as a valuable tool for accurately determining chemical composition and digestibility parameters of forages. The aim of this study was to build NIRS calibrations and equations for fecal iNDF. In total, 1,281 fecal samples were collected to build a calibration data set, but only 301 were used to develop equations. Once dried, samples were ground and chemically analyzed for crude protein, ash, amylase and sodium sulfite–treated NDF corrected for ash residue (aNDFom), acid detergent fiber, acid detergent lignin, and in vitro digestion at 240 h to estimate iNDF (uNDF240). Each fecal sample was scanned using a NIRSystem 6500 instrument (Perstorp Analytical Inc., Silver Spring, MD). Spectra selection was performed, resulting in 301 sample spectra used to develop regression equations with good accuracy and low standard error of prediction. The standard error of calibration (SEC), cross validation (SECV), and coefficients of determination for calibration (R²) and for cross validation (1 − VR, where VR = variance ratio) were used to evaluate calibration and validation results. Moreover, the ratio performance deviation (RPD) and ratio of the range of the original data to SECV (range/SECV; range error ratio, RER) were also used to evaluate calibration and equation performance. Calibration data obtained on fiber fractions aNDFom (R² = 0.92, 1 − VR = 0.87, SEC = 1.48, SECV = 1.89, RPD = 2.80, and RER = 20.19), uNDF240 (R² = 0.92, 1 − VR = 0.86, SEC = 1.65, SECV = 2.24, RPD = 2.57, and RER = 14.30), and in vitro rumen aNDFom digestibility at 240 h (R² = 0.90, 1 − VR = 0.85, SEC = 2.68, SECV = 3.43, RPD = 2.53, and RER = 14.0) indicated the predictive equations had good predictive value.

用于估算草料或粪便样品中难消化的中性洗涤剂纤维（iNDF）的体外和原位程序耗时，昂贵且受内在因素限制。相反，近红外反射光谱法（NIRS）已被广泛认为是准确确定草料化学成分和消化率参数的有价值的工具。这项研究的目的是为粪便iNDF建立NIRS校准和方程式。总共收集了1,281个粪便样本以建立校准数据集，但是仅使用301个粪便样本来建立方程式。干燥后，将样品研磨并化学分析粗蛋白，灰分，淀粉酶和亚硫酸钠处理的NDF，校正后的灰渣（aNDFom），酸性去污剂纤维，酸性去污剂木质素，并在240 h体外消化以评估iNDF（uNDF240 ）。使用NIRSystem 6500仪器（Perstorp Analytical Inc.，Silver Spring，MD）扫描每个粪便样品。进行了光谱选择，生成了301个样品光谱，这些样品光谱用于开发具有良好准确性和较低标准预测误差的回归方程式。校准的标准误差（SEC），交叉验证（SECV）和校准的确定系数（R²）和交叉验证（1- VR，其中VR =方差比）用于评估校准和验证结果。此外，还使用比率性能偏差（RPD）和原始数据的范围与SECV的比率（范围/ SECV；范围误差比，RER）来评估校准和方程式的性能。uNDF240（n ² = 0.92，1 − VR = 0.87，SEC = 1.48，SECV = 1.89，RPD = 2.80，RER = 20.19），uNDF240（R ² = 0.92，1 − VR = 0.86， SEC = 1.65，SECV = 2.24，RPD = 2.57，RER = 14.30），以及240 h时的体外瘤胃aNDFom消化率（R ² = 0.90，1 -VR = 0.85，SEC = 2.68，SECV = 3.43，RPD = 2.53 ，且RER = 14.0）表示预测方程具有良好的预测价值。