Hyperspectral and genome-wide association analyses of leaf phosphorus status in local Thai indica rice

Phosphorus (P) is an essential mineral nutrient and one of the key factors determining crop productivity. P-deficient plants exhibit visual leaf symptoms, including chlorosis, and alter spectral reflectance properties. In this study, we evaluated leaf inorganic phosphate (Pi) contents, plant growth and reflectance spectra (420-790 nm) of 172 Thai rice landrace varieties grown hydroponically under three different P supplies (overly sufficient, mildly deficient and severely deficient conditions). We reported correlations between Pi contents and reflectance ratios computed from two wavebands in the range of near infrared (720-790 nm) and visible energy (green-yellow and red edge) (r > 0.69) in Pi-deficient leaves. Artificial neural network models were also developed which could classify P deficiency levels with 85.60% accuracy and predict Pi content with R-2 of 0.53, as well as highlight important waveband sections. Using 217 reflectance ratio indices to perform genome-wide association study (GWAS) with 113,114 SNPs, we identified 11 loci associated with the spectral reflectance traits, some of which were also associated with the leaf Pi content trait. Hyperspectral measurement offers a promising non-destructive approach to predict plant P status and screen large germplasm for varieties with high P use efficiency.

Automated summary

In this study, the leaf phosphate content, plant growth, and reflectance spectra of Thai rice landrace varieties were evaluated under different phosphorus supply conditions. The results showed a high correlation between phosphate content and reflectance ratios in Pi-deficient leaves. Artificial neural network models were developed to classify P deficiency levels and predict Pi content. Genome-wide association study identified loci associated with spectral reflectance traits and leaf Pi content. Hyperspectral measurement offers a promising non-destructive approach for predicting plant P status and screening for high P use efficiency varieties.