Optical sensing for early spring freeze related blueberry bud damage detection: Hyperspectral imaging for salient spectral wavelengths identification

Abstract The floral tissue of blueberry buds is very sensitive to the freezing and can be damaged during early spring freeze events. Such damage results in loss of yield to the commercial blueberry producers. Therefore, this study investigated the feasibility of injured blueberry buds damage detection during early spring freeze using hyperspectral imaging (HSI) technique. Imaged were the buds from bud swell and early pink stage for two growing seasons. Prior to imaging, buds in 2017 were subjected to freezing temperatures of −7 to −16 °C and −2 to −11 °C at respective growth stages. In 2018 season, buds were frozen at −11 to −20 °C and −4 to −13 °C at two respective sampling date for bud swell stage and at −2 to −11 °C for early pink growth stage. The HSI data was obtained using a push broom type system in the spectral wavelength ranges of 517–1729 nm. For the imaged buds, each of the indivisual buds on sampled shoot was considered as one sample, and the average spectra of such bud within 540 to 1599 nm was extracted for further analysis. Principal component analysis and successive projection algorithms were applied to select key wavelengths related to bud damage symptoms. Common wavelengths of 615, 673, 690, 756, 979 and 1467 nm were identified for both the growth stages. Partial least squares discriminant analysis was performed to identify normal and injured bud samples with the selected common wavelengths. Performance of the models manifested good results with better sensitivity (>0.80), specificity (>0.75), the area under the receiver operating characteristic curve (>0.84) and accuracy (>0.75) attributes for 2017, 2018 seasons and two seasons combined test dataset.