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Recently, there has been a need by dairy farmers for a method to assess milk quality in real time during milking. We have constructed an on-line near-infrared (NIR) spectroscopic sensing system on an experimental basis. The NIR system can be used for real-time monitoring of milk quality items such as fat, protein, lactose, somatic cell count, and milk urea nitrogen during milking with sufficient precision and accuracy. We tried to improve the robustness of calibration (CAL) models for measurement of milk quality items using NIR spectrum data obtained from two dairy herds. When CAL models developed from data obtained from one herd were used for validation of data obtained from the same herd, the milk quality items could be measured with high levels of accuracy. On the other hand, when the CAL models were used for validation of data obtained from the other herd, the levels of accuracy in measurements of all milk quality items except fat were low. The low levels of accuracy may be caused by factors such as differences in cow individuality, lactation stage, calving times, feeding stage and experimental period (temperatures in the dairy barn). To develop robust calibration models for measurement of milk quality items, therefore, data acquisition from various milk spectra caused by these factors is necessary.