Purity analysis of multi-grain rice seeds with non-destructive visible and near-infrared spectroscopy

Abstract

Seed purity is a crucial indicator of seed breeding, production and circulation. The traditional purity analysis methods are based on the authenticity identification of single-seed, which are complex, time consuming and lowly efficient. Using visible and near-infrared (Vis-NIR) spectroscopy, a novel purity analysis method of multi-grain rice seeds was developed. The samples were mixed samples that the target variety (Y Liangyou 900) was contaminated by the other four varieties. The standard normal variate method was used for spectral pretreatment. The equidistant combination-partial least squares (EC-PLS) was adopted for large-range wavelength screening. The wavelength step-by-step phase-out PLS (WSP-PLS) was further used to eliminate interference wavelengths and improve predicted effect. In vis-short NIR region, the selected WSP-PLS model included 19 non-equidistant wavelengths. The root mean square errors and correlation coefficients for prediction in modeling (RMSEPM, RP,M) reached 0.115, 0.920, respectively. In validation, the root mean square errors and correlation coefficients for prediction (RMSEPV, RP,V) were 0.152, 0.845, respectively. In the long NIR region, the selected model included 24 non-equidistant wavelengths, the RMSEPM, RP,M were 0.103, 0.930 and the RMSEPV, RP,V were 0.129, 0.894, respectively. Results showed that the predicted and actual purity values had high correlation, and the wavelength model complexity was low. The proposed Vis-NIR detection method has the feasibility to analyse the purity of multi-grain rice seeds, which is a rapid, non-destructive and promising analytical technique. As a simple and efficient wavelength selection method, WSP-PLS is expected to be used for more analysis objects.