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

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 intended to explore 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.

[1]  Ye Sun,et al.  Hyperspectral characteristics of bruised tomatoes as affected by drop height and fruit size , 2021 .

[2]  Wei Luo,et al.  Determination of soluble solids content in oranges using visible and near infrared full transmittance hyperspectral imaging with comparative analysis of models , 2020, Postharvest Biology and Technology.

[3]  Lav R. Khot,et al.  Optical sensing for early spring freeze related blueberry bud damage detection: Hyperspectral imaging for salient spectral wavelengths identification , 2019, Comput. Electron. Agric..

[4]  Paul Scheunders,et al.  Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform , 2019, Comput. Electron. Agric..

[5]  D. Hincha,et al.  Deacclimation after cold acclimation—a crucial, but widely neglected part of plant winter survival , 2019, Journal of experimental botany.

[6]  Xuechao Song,et al.  Rapid classification of virgin and recycled EPS containers by Fourier transform infrared spectroscopy and chemometrics , 2018, Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment.

[7]  Stefan Thomas,et al.  Quantitative assessment of disease severity and rating of barley cultivars based on hyperspectral imaging in a non-invasive, automated phenotyping platform , 2018, Plant Methods.

[8]  A. Siedliska,et al.  Detection of fungal infections in strawberry fruit by VNIR/SWIR hyperspectral imaging , 2018 .

[9]  Qian Zhou,et al.  The effect of ethylene absorbent treatment on the softening of blueberry fruit. , 2018, Food chemistry.

[10]  Guangtao Zhai,et al.  Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data , 2018, Sensors.

[11]  Yong He,et al.  Selection of Spectral Resolution and Scanning Speed for Detecting Green Jujubes Chilling Injury Based on Hyperspectral Reflectance Imaging , 2018 .

[12]  Jay Gao,et al.  Hyperspectral sensing of heavy metals in soil and vegetation: Feasibility and challenges , 2018 .

[13]  Jong Hae Kim,et al.  Statistical data preparation: management of missing values and outliers , 2017, Korean journal of anesthesiology.

[14]  Fei Liu,et al.  Mid-infrared spectroscopy combined with chemometrics to detect Sclerotinia stem rot on oilseed rape (Brassica napus L.) leaves , 2017, Plant Methods.

[15]  Yong He,et al.  Hyperspectral imaging for classification of healthy and gray mold diseased tomato leaves with different infection severities , 2017, Comput. Electron. Agric..

[16]  Hongbo Shao,et al.  Applying hyperspectral imaging to explore natural plant diversity towards improving salt stress tolerance. , 2017, The Science of the total environment.

[17]  C. Huck,et al.  A Review of Mid-Infrared and Near-Infrared Imaging: Principles, Concepts and Applications in Plant Tissue Analysis , 2017, Molecules.

[18]  Chunjiang Zhao,et al.  Fast detection and visualization of early decay in citrus using Vis-NIR hyperspectral imaging , 2016, Comput. Electron. Agric..

[19]  K. Kersting,et al.  Hyperspectral phenotyping on the microscopic scale: towards automated characterization of plant-pathogen interactions , 2015, Plant Methods.

[20]  Christian Bauckhage,et al.  Metro Maps of Plant Disease Dynamics—Automated Mining of Differences Using Hyperspectral Images , 2015, PloS one.

[21]  Stephen R. Delwiche,et al.  Hyperspectral near-infrared imaging for the detection of physical damages of pear , 2014 .

[22]  B. Iooss,et al.  A Review on Global Sensitivity Analysis Methods , 2014, 1404.2405.

[23]  Gang Wu,et al.  Plant Species Identification Based on Independent Component Analysis for Hyperspectral Data , 2014, J. Softw..

[24]  Ubirajara Contro Malavasi,et al.  Quantifying abiotic stress of plants - advantages and disadvantages of chlorophyll fluorescence Quantificação do estresse abiótico em plantas - vantagens e desvantagens da fluorescência da clorofila , 2013 .

[25]  Joe Mari Maja,et al.  Visible-near infrared spectroscopy for detection of Huanglongbing in citrus orchards , 2011 .

[26]  Ben Somers,et al.  Hyperspectral Reflectance and Fluorescence Imaging to Detect Scab Induced Stress in Apple Leaves , 2009, Remote. Sens..

[27]  Noel D.G. White,et al.  Detection of insect-damaged wheat kernels using near-infrared hyperspectral imaging , 2009 .

[28]  B. Matthews,et al.  Major differences observed in transcript profiles of blueberry during cold acclimation under field and cold room conditions , 2007, Planta.

[29]  Lisa J. Rowland,et al.  Cold Hardiness, Deacclimation Kinetics, and Bud Development among 12 Diverse Blueberry Genotypes under Field Conditions , 2005 .

[30]  Vijaya Gopal Kakani,et al.  Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum , 2005 .

[31]  J. Slovin,et al.  Analysis of gene expression associated with cold acclimation in blueberry floral buds using expressed sequence tags , 2004 .

[32]  J Rodrigo,et al.  Spring frosts in deciduous fruit trees — morphological damage and flower hardiness , 2000 .

[33]  E. Ashworth,et al.  Blueberry Flower-bud Hardiness Is Not Estimated by Differential Thermal Analysis , 1994 .

[34]  S. Sawilowsky.  Nonparametric Tests of Interaction in Experimental Design , 1990 .

[35]  Roberto Kawakami Harrop Galvão,et al.  Cross-validation for the selection of spectral variables using the successive projections algorithm , 2007 .

[36]  Steven Walfish,et al.  A review of statistical outlier methods , 2006 .