An independent validation reveals the potential to predict Hagberg–Perten falling number using spectrometers

The Hagberg–Perten falling number (HFN) method is the international standard used to evaluate damage wheat (Triticum aestivum) grain quality due preharvest sprouting (PHS) and late maturity alpha-amylase (LMA). However, HFN test requires specialized laboratory facilities time consuming. Spectrometers were known as a potential tool for quick assessment, but none of studies have validated assessment results across different datasets. In this study, an independent validation was conducted using samples spectral instruments. calibration set had 462 92 varieties grown at 24 locations in 2019 examined near-infrared spectrometer. set, 19 collected from 10 2 years that experienced either PHS or LMA scanned with hyperspectral camera. association between spectra modeled by partial least square regression. As result, correlation accuracy r = 0.72 mean absolute error 56 s. Furthermore, study showed cost-effective alternative only bands predict HFN, it achieved better performance than full spectrum system. conclusion, first could be predicted on dataset measured instrument. result suggested spectrometers can potentially serve faster plant breeders develop resistant LMA, growers screen damaged grains transportation processes.