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Rapid and accurate determination of chemical composition of rice straw is crucial to predictions of its value and nutritive quality. In this work, calibration models using near-infrared reflectance spectroscopy (NIRS) for determination of rice straw analytical parameters such as total ash, insoluble ash, moisture, cellulose, hemicellulose and Klason lignin were studied using a diverse group of rice straws. The NIRS calibration models for chemical compositions of rice straw were derived by partial least-squares (PLS) regression and prediction of chemical composition of independent rice straw samples showed these models to be rapid and accurate, giving R-2 -values higher than 0.85. Such NIRS calibration models are appropriate for the determination of the quality of rice straw samples. (C) 2007 Elsevier B.V. All rights reserved.Rapid and accurate determination of chemical composition of rice straw is crucial to predictions of its value and nutritive quality. In this work, calibration models using near-infrared reflectance spectroscopy (NIRS) for determination of rice straw analytical parameters such as total ash, insoluble ash, moisture, cellulose, hemicellulose and Klason lignin were studied using a diverse group of rice straws. The NIRS calibration models for chemical compositions of rice straw were derived by partial least-squares (PLS) regression and prediction of chemical composition of independent rice straw samples showed these models to be rapid and accurate, giving R-2 -values higher than 0.85. Such NIRS calibration models are appropriate for the determination of the quality of rice straw samples. (C) 2007 Elsevier B.V. All rights reserved