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β-Glucan is a component of barley grains with functional properties that make it useful for human consumption. Cultivars with high grain β-glucan are required for industrial processing. Breeding for barley genotypes with higher β-glucan content requires a high-throughput method to assess β-glucan quickly and cheaply. Wet-chemistry laboratory procedures are low-throughput and expensive, but indirect measurement methods such as near-infrared reflectance spectroscopy (NIRS) match the breeding requirements (once the NIR spectrometer is available). A predictive model for the indirect measurement of β-glucan content in ground barley grains with NIRS was therefore developed using 248 samples with a wide range of β-glucan contents (3.4%–17.6%). To develop such calibration, 198 unique samples were used for training and 50 for validation. The predictive model had R² = 0.990, bias = 0.013% and RMSEP = 0.327% for validation. NIRS was confirmed to be a very useful technique for indirect measurement of β-glucan content and evaluation of high-β-glucan barleys.