A Low-rank strategy for improving the prediction accuracy of partial least square models

•The ranks of infrared spectral matrix will increase with the undesired variations.•The undesired variations can be effectively removed by the low-rank constraint.•The singular value is a parameter to evaluate the low-rank performance.•The accuracy of the chemometric model can be improved by the low-rank strategy.