Utilizing vegetation indices with optimal wavelengths to predict nitrogen uptake at the flowering stage and wheat yield

Techniques for determining the amount of nitrogen topdressing based on remote sensing during the flowering stage of wheat require highly accurate yield predictions. Optimal wavelength combinations for accurately predicting nitrogen uptake and wheat yield using remote sensing methods remain inconsistent. This study aimed to estimate the wheat yield and nitrogen uptake using a portable spectrometer capable of capturing a wide range of wavelengths from 340 to 850 nm. Spectral data were collected at the flowering stage in 2022 and 2023 for the ‘Ayahikari,’ ‘Satonosora,’ and ‘Yumekaori’ varieties. The ratio spectral indices (RSIN and RSIY, identified as vegetation indices with strong correlations to nitrogen uptake at the flowering stage and wheat yield, respectively) were analyzed from the dataset for 2023. Both indices exhibiting the highest coefficient of determination (R2) were derived from the combinations of two wavelengths within the 730–810 nm range. The yield prediction model using the RSIN or RSIY, based on the 2023 dataset, showed goodness-of-fit for the 2022 dataset, achieving an R2 of 0.61 and an RMSE of 1.4 g m− 2 for nitrogen uptake alongside an R2 of 0.50 and an RMSE of 61 g m− 2 for wheat yield. The RSIN and RSIY vegetation indices outperformed the well-known NDVI, GNDVI, RENDVI, and plant height × SPAD value × spike number index in explaining the variation in wheat yield and nitrogen uptake. These findings present important implications for enhancing agricultural practices by providing more accurate and efficient methods for predicting nitrogen uptake and wheat yield.