We explored the rapid qualitative analysis of wheat cultivars with good lodging resistances by Fourier transform infrared resonance (FTIR) spectroscopy and multivariate statistical analysis. FTIR imaging showing that wheat stem cell walls were mainly composed of cellulose, pectin, protein, and lignin. Principal components analysis (PCA) was used to eliminate multicollinearity among multiple peak absorptions. PCA revealed the developmental internodes of wheat stems could be distributed from low to high along the load of the second principal component, which was consistent with the corresponding bands of cellulose in the FTIR spectra of the cell walls. Furthermore, four distinct stem populations could also be identified by spectral features related to their corresponding mechanical properties via PCA and cluster analysis. Histochemical staining of four types of wheat stems with various abilities to resist lodging revealed that cellulose contributed more than lignin to the ability to resist lodging. These results strongly suggested that the main cell wall component responsible for these differences was cellulose. Therefore, the combination of multivariate analysis and FTIR could rapidly screen wheat cultivars with good lodging resistance. Furthermore, the application of these methods to a much wider range of cultivars of unknown mechanical properties promises to be of interest.Wheat (Triticum aestivum L.) flattening, known as lodging, can reduce the yield, production quality, and mechanical harvesting efficiency of a crop.

The random amplified polymorphic DNA (RAPD) technique was used to evaluate the genetic diversity and population structure of 91 genets from four wild populations of Betula luminifera at different elevations in the National Nature Reserve of the Wuyi Mountain, Fujian Province, China. Eighteen random primers (from 139 primers) produced a total of 199 scorable amplified fragments, of which 174 (87.44%) were polymorphic across all individuals. The genetic diversities of B. luminifera at the population level and species level were PPL = 60.05%, h = 0.2242, I = 0.3181 and PPL = 87.44%, h = 0.3442, I = 0.4899, respectively. The value of differentiation (G st = 0.3486) and analysis of molecular variance (AMOVA) indicated that there was a relatively high genetic differentiation among populations, and about one-third of the genetic variation occurred among populations. Pearson correlation analysis further revealed that the genetic diversity within populations had significant or very significant correlation with the elevation, climatic factors (annual average temperature and annual precipitation) and soil nutrient factors (total nitrogen, C/N ratio and organic matter). Mantel tests show that there was a significant correlation between the genetic distances among populations and the distance of elevation, and the divergence of soil nutrient factors. The results of the present study suggested that the relatively high genetic differentiation among populations of B. luminifera at different elevations might be caused by ecological factors and gene flow.