Determination of Basic Density and Moisture Content of Loblolly Pine Wood Disks Using a near Infrared Hyperspectral Imaging System

Hyperspectral imaging is a powerful technique that can rapidly, accurately, and non-destructively determine the quality of agricultural products. In this study, a hyperspectral imaging system has been developed to evaluate and visualize the Brix values and moisture contents in sugarcane stalks to be used as a tool for breeding programmes. After extracting the spectral data via ENVI coding, data in the wavelength range of 450–950 nm were used to generate prediction models for Brix and moisture content via partial least squares regression. The coefficients of determination of the predictive models for Brix and moisture content were found to be 0.70 and 0.68, respectively. The root mean square errors of cross-validation were 1.28° for Brix and 1.49% for moisture content, and the performance to deviation ratios were 1.71 and 1.61, respectively. The models were applied to each pixel of the hypercube data in order to determine the distributions of Brix and moisture content within the sugarcane stalks. Both distribution mappings indicated that the Brix and the moisture content level were lower in the internode regions. The results demonstrated the feasibility of using hyperspectral imaging to visualize Brix and moisture content in sugarcane stalks. The developed method has potential applications in farming management and also in breeding programs.

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Nondestructive and rapid determination of lignocellulose components of biofuel pellet using online hyperspectral imaging system

Biotechnology for Biofuels ◽

10.1186/s13068-018-1090-3 ◽

2018 ◽

Vol 11 (1) ◽

Cited By ~ 8

Author(s):

Xuping Feng ◽

Chenliang Yu ◽

Xiaodan Liu ◽

Yunfeng Chen ◽

Hong Zhen ◽

...

Keyword(s):

Hyperspectral Imaging ◽

Imaging System ◽

Rapid Determination

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Rapid ripening stage classification and dry matter prediction of durian pulp using a pushbroom near infrared hyperspectral imaging system

Measurement ◽

10.1016/j.measurement.2021.110464 ◽

2021 ◽

pp. 110464

Author(s):

Sneha Sharma ◽

K.C. Sumesh ◽

Panmanas Sirisomboon

Keyword(s):

Hyperspectral Imaging ◽

Dry Matter ◽

Near Infrared ◽

Imaging System ◽

Ripening Stage ◽

Stage Classification

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Prediction of Douglas-Fir Lumber Properties: Comparison between a Benchtop Near-Infrared Spectrometer and Hyperspectral Imaging System

Applied Sciences ◽

10.3390/app8122602 ◽

2018 ◽

Vol 8 (12) ◽

pp. 2602 ◽

Cited By ~ 4

Author(s):

Laurence Schimleck ◽

Joseph Dahlen ◽

Seung-Chul Yoon ◽

Kurt Lawrence ◽

Paul Jones

Keyword(s):

Hyperspectral Imaging ◽

Near Infrared ◽

Imaging System ◽

Nir Spectroscopy ◽

Physical And Mechanical Properties ◽

Douglas Fir ◽

Modulus Of Rupture ◽

Visual Grade ◽

Fit Statistics ◽

Infrared Spectrometer

Near-infrared (NIR) spectroscopy and NIR hyperspectral imaging (NIR-HSI) were compared for the rapid estimation of physical and mechanical properties of No. 2 visual grade 2 × 4 (38.1 mm by 88.9 mm) Douglas-fir structural lumber. In total, 390 lumber samples were acquired from four mills in North America and destructively tested through bending. From each piece of lumber, a 25-mm length block was cut to collect diffuse reflectance NIR spectra and hyperspectral images. Calibrations for the specific gravity (SG) of both the lumber (SGlumber) and 25-mm block (SGblock) and the lumber modulus of elasticity (MOE) and modulus of rupture (MOR) were created using partial least squares (PLS) regression and their performance checked with a prediction set. The strongest calibrations were based on NIR spectra; however, the NIR-HSI data provided stronger predictions for all properties. In terms of fit statistics, SGblock gave the best results, followed by SGlumber, MOE, and MOR. The NIR-HSI SGlumber, MOE, and MOR calibrations were used to predict these properties for each pixel across the transverse surface of the scanned samples, allowing SG, MOE, and MOR variation within and among rings to be observed.

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Chemometric Tools for NIRS and NIR Hyperspectral Imaging

Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca Agriculture ◽

10.15835/buasvmcn-agr:8658 ◽

2012 ◽

Vol 69 (1) ◽

Author(s):

Laura M. DALE ◽

André THEWIS ◽

Ioan ROTAR ◽

Juan A. FERNANDEZ PIERNA ◽

Christelle BOUDRY ◽

...

Keyword(s):

Hyperspectral Imaging ◽

Near Infrared ◽

Agricultural Sector ◽

Spatial Information ◽

Imaging System ◽

Agricultural Products ◽

Chemical Information ◽

Special Focus ◽

Large Area ◽

Analytical Tools

Nowadays in agriculture, new analytical tools based on spectroscopic technologies are developed. Near Infrared Spectroscopy (NIRS) is a well known technology in the agricultural sector allowing the acquisition of chemical information from the samples with a large number of advantages, such as: easy to use tool, fast and simultaneous analysis of several components, non-polluting, noninvasive and non destructive technology, and possibility of online or field implementation. Recently, NIRS system was combined with imaging technologies creating the Near Infrared Hyperspectral Imaging system (NIR-HSI). This technology provides simultaneously spectral and spatial information from an object. The main differences between NIR-HSI and NIRS is that many spectra can be recorded simultaneously from a large area of an object with the former while with NIRS only one spectrum was recorded for analysis on a small area. In this work, both technologies are presented with special focus on the main spectrum and images analysis methods. Several qualitative and quantitative applications of NIRS and NIR-HSI in agricultural products are listed. Developments of NIRS and NIR-HSI will enhance progress in the field of agriculture by providing high quality and safe agricultural products, better plant and grain selection techniques orÂ compound feed industryâ€™s productivity among others.

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