Blueberry bud freeze damage detection using optical sensors: Identification of spectral features through hyperspectral imagery

Abstract

BACKGROUND:

Highbush blueberry (Vaccinium corymbosum), the species primarily grown in the state of Washington, U.S., is relatively cold hardy. However, low temperatures in winter and early spring can still cause freeze damage to the buds.

OBJECTIVE:

This study explored hyperspectral imaging (HSI) for detecting freeze induced bud damage. Blueberry buds (c.v. Duke) were collected over two seasons and tested in the laboratory to detect damage at four typical phenological stages.

METHODS:

The HSI data was acquired via line scan HSI system with spectral wavelength ranging from 517 to 1729 nm for buds grouped into either normal or injured mortalities. The successive projection algorithm was employed for pertinent feature wavelength selection. Analysis of variance and linear regression were then applied for evaluating sensitivity of feature wavelengths.

RESULTS:

Overall, five salient wavelengths (706, 723, 872, 1384, and 1591 nm) were selected to detect bud freeze injury. A quadratic discriminant analysis method-based analysis verified reliability of these five wavelengths in bud damage detection with overall accuracy in the ranges of 64 to 82%for the test datasets of each stage in two seasons.

CONCLUSIONS:

This study indicated potential of optical sensing to identify the injured buds using five salient wavelengths.