scispace - formally typeset
Search or ask a question
Journal Article•DOI•

Preliminary study on the use of near infrared hyperspectral imaging for quantitation and localisation of total glucosinolates in freeze-dried broccoli

José Miguel Hernández-Hierro1, Carlos Esquerre2, Juan Valverde3, Salvador Villacreces3, Kim Reilly3, Michael Gaffney3, M. Lourdes González-Miret1, Francisco J. Heredia1, Colm P. O'Donnell2, Gerard Downey3 •
University of Seville1, University College Dublin2, Teagasc3
01 Apr 2014-Journal of Food Engineering (Elsevier)-Vol. 126, pp 107-112
TL;DR: In this article, the use of hyperspectral imaging to quantify and localise total glucosinolates in florets of a single broccoli species has been examined Two different spectral regions (vis-NIR and NIR), a number of spectral pre-treatments and different mask development strategies were studied to develop the quantitative models.
About: This article is published in Journal of Food Engineering.The article was published on 2014-04-01 and is currently open access. It has received 28 citations till now. The article focuses on the topics: Hyperspectral imaging.

Summary (2 min read)

Jump to: [1. Introduction] – [2.2. Hyperspectral imaging analysis] – [2.3. Data processing and analysis] – [2.4 Prediction map] – [3.2. Prediction map] and [4. Conclusion]

1. Introduction

  • The aim of this study was to evaluate the potential of hyperspectral imaging technology for the quantitative screening and localisation of total glucosinolates in freeze-dried broccoli.
  • Since predictive models developed on freeze-dried powders by conventional NIR spectrometers may not be transferred directly to hyperspectral imaging datasets, a new predictive model must be generated using an actual hyperspectral imaging system on homogeneous, freeze-dried broccoli powders after which it may be applied to hyperspectral images of intact broccoli for localisation and quantitation of total glucosinolates.
  • To their knowledge, this is the first time that this analytical tool has been applied to broccoli for these purposes.

2.2. Hyperspectral imaging analysis

  • Data were recorded in units of reflectance and saved in ENVI header format using the instrument acquisition software (Spectral Scanner; DV Optics, Padua, Italy).
  • When using System 1, only spectral data in the 450 -900 nm regions were used in data analysis due to reduced efficiency of the light source and CCD in wavelength regions outside this range.
  • In the case of System 2, the spectral range was attenuated to 950 -1650 nm for similar operational reasons.

2.3. Data processing and analysis

  • Data treatment and quantitative model development was carried out using Matlab (R2010b; The Math Works, Inc. USA).
  • For each hyperspectral image, regions of interest (ROIs) of approx.
  • 3 cm diameter were selected using an interactive selection tool available in the acquisition software ('ROI tool') and 500 pixels were randomly-selected within each ROI.
  • Spectral data were pre-treated using the standard normal variate (SNV) transform to diminish the effects of light scatter.
  • Finally, quantitative calibrations were developed by partial least squares (PLS) regression using total glucosinolates as the dependent (Y) variable and pixel spectra as the independent (X) variables.

2.4 Prediction map

  • Slices of whole freeze-dried broccoli were scanned in the NIR zone (950-1650 nm) to apply the previously constructed model and identify the glucosinolate allocation.
  • Prior to the quantitative analysis, a thresholding rule method was applied to the broccoli images to isolate the broccoli from other parts of image.
  • An image was generated using the maximum reflectance value of each pixel spectrum in a raw image.
  • A threshold of 0.45 reflectance units was set analysing the corresponding histogram and drawing a tentative mask image in an iterative process.
  • SNV was applied to minimise the effects of scattering in the mask created and then the PLS model was applied.

3.2. Prediction map

  • Their potent odour and pronounced taste suggests a role in herbivore and microbial defence.
  • Deposition in external plant parts, confirmed spectroscopically in this work, would be the optimal location for these purposes.

4. Conclusion

  • Two different spectral regions (vis-NIR and NIR) were studied to develop the quantitative models.
  • Better results were obtained using the 950-1650 nm wavelength range and subsequent analyses were therefore carried out using this spectral zone.
  • The procedure demonstrates potential for the quantitative screening and location of total glucosinolates in broccoli using the 950-1650 nm wavelength range.
  • Nevertheless, a comprehensive study should be made in order to evaluate all other relevant sources of variability in the complete development of these models.
  • Such a study would entail several years work but the results reported herein suggest the viability of obtaining useful results from such an undertaking.

Did you find this useful? Give us your feedback

Figures (5)
Citations
More filters
Journal Article•DOI•
A Review of Mid-Infrared and Near-Infrared Imaging: Principles, Concepts and Applications in Plant Tissue Analysis

[...]

Sevgi Türker-Kaya1, Christian W. Huck•
Kocaeli University1
20 Jan 2017-Molecules
TL;DR: This review aims to present a general perspective about near-infrared and mid- Infrared imaging/microspectroscopy in plant research to compare potentialities of these methodologies with their advantages and limitations.
Abstract: Plant cells, tissues and organs are composed of various biomolecules arranged as structurally diverse units, which represent heterogeneity at microscopic levels. Molecular knowledge about those constituents with their localization in such complexity is very crucial for both basic and applied plant sciences. In this context, infrared imaging techniques have advantages over conventional methods to investigate heterogeneous plant structures in providing quantitative and qualitative analyses with spatial distribution of the components. Thus, particularly, with the use of proper analytical approaches and sampling methods, these technologies offer significant information for the studies on plant classification, physiology, ecology, genetics, pathology and other related disciplines. This review aims to present a general perspective about near-infrared and mid-infrared imaging/microspectroscopy in plant research. It is addressed to compare potentialities of these methodologies with their advantages and limitations. With regard to the organization of the document, the first section will introduce the respective underlying principles followed by instrumentation, sampling techniques, sample preparations, measurement, and an overview of spectral pre-processing and multivariate analysis. The last section will review selected applications in the literature.

244 citations

Cites methods from "Preliminary study on the use of nea..."

  • ...Moreover, the quantification and localization of glucosinolates in florets of a single broccoli species were examined by hyperspectral imaging in the regions of 950–1650 nm [91]....

    [...]

Journal Article•DOI•
Hyperspectral imaging technique for evaluating food quality and safety during various processes: A review of recent applications

[...]

Yuwei Liu1, Yuwei Liu2, Hongbin Pu2, Hongbin Pu1, Da-Wen Sun •
Guangzhou Higher Education Mega Center1, South China University of Technology2
01 Nov 2017-Trends in Food Science and Technology
TL;DR: In this paper, detailed applications of hyperspectral imaging (HSI) system in various food processes are outlined, including cooking, drying, chilling, freezing and storage, and salt curing.
Abstract: Background The quality of products depends on their processing. Effective way of monitoring and controlling these processes will ensure the quality and safety of products. Since traditional measurement methods cannot achieve on-line monitoring, imaging spectroscopy, as a fast, accurate and non-destructive detection tool, has been widely used to evaluate quality and safety attributes of foods undergoing various processes. Scope and Approach In the current review, detailed applications of hyperspectral imaging (HSI) system in various food processes are outlined, including cooking, drying, chilling, freezing and storage, and salt curing. The study emphasized the ability of HSI technique to detect internal and external quality parameters in different food processes. Also, the advantages and disadvantages of HSI applications on these food processes are discussed. Key Findings and Conclusions The literature presented in this review clearly demonstrate that HSI has the ability to inspect and monitor different food manufacturing processes and has the potential to control the quality and safety of the processed foods. Although still with some barriers, it can be expected the HSI systems will find more useful and valuable applications in the future evaluation of food processes.

228 citations

Journal Article•DOI•
Recent Progress of Hyperspectral Imaging on Quality and Safety Inspection of Fruits and Vegetables: A Review

[...]

Yuan-Yuan Pu1, Yao-Ze Feng1, Da-Wen Sun1•
University College Dublin1
01 Mar 2015-Comprehensive Reviews in Food Science and Food Safety
TL;DR: Recent advances and applications of Hyperspectral imaging in detecting, classifying, and visualizing quality and safety attributes of fruits and vegetables and the basic principles and major instrumental components are presented.
Abstract: Objective quality assessment and efficacious safety surveillance for agricultural and food products are inseparable from innovative techniques. Hyperspectral imaging (HSI), a rapid, nondestructive, and chemical-free method, is now emerging as a powerful analytical tool for product inspection by simultaneously offering spatial information and spectral signals from one object. This paper focuses on recent advances and applications of HSI in detecting, classifying, and visualizing quality and safety attributes of fruits and vegetables. First, the basic principles and major instrumental components of HSI are presented. Commonly used methods for image processing, spectral pretreatment, and modeling are summarized. More importantly, morphological calibrations that are essential for nonflat objects as well as feature wavebands extraction for model simplification are provided. Second, in spite of the physical and visual attributes (size, shape, weight, color, and surface defects), applications from the last decade are reviewed specifically categorized into textural characteristics inspection, biochemical components detection, and safety features assessment. Finally, technical challenges and future trends of HSI are discussed.

151 citations

Journal Article•DOI•
Investigation on water status and distribution in broccoli and the effects of drying on water status using NMR and MRI methods

[...]

Fangfang Xu1, Xin Jin1, Lu Zhang1, Xiao Dong Chen1•
Soochow University (Suzhou)1
01 Jun 2017-Food Research International
TL;DR: The results of this study show that the low-field NMR and MRI methods can precisely provide the quantitative information of water status inside food materials, and can be used to investigate the effects of food processing on product quality.

149 citations

Journal Article•DOI•
Facilitated wavelength selection and model development for rapid determination of the purity of organic spelt (Triticum spelta L.) flour using spectral imaging.

[...]

Wen-Hao Su1, Da-Wen Sun1•
National University of Ireland1
01 Aug 2016-Talanta
TL;DR: Results reveal that spectral imaging integrated with multivariate analysis has good potential for rapidly evaluating the purity of organic spelt flour.

50 citations

References
More filters
Journal Article•DOI•
Wavelength selection for development of a near infrared imaging system for early detection of bruise damage in mushrooms ( Agaricus bisporus )

[...]

Carlos Esquerre1, Aoife Gowen1, Gerard Downey2, Colm P. O'Donnell1•
University College Dublin1, Teagasc2
01 Jan 2012-Journal of Near Infrared Spectroscopy
TL;DR: In this article, the potential use of near infrared hyperspectral imaging for non-destructive monitoring of mushroom quality has been demonstrated for the first time, and the results showed that NIR NIR images can be used for a variety of applications.
Abstract: Previous research has demonstrated the potential use of near infrared (NIR) hyperspectral imaging for non-destructive monitoring of mushroom quality. The mushroom industry demands economical and hi...

29 citations

"Preliminary study on the use of nea..." refers methods in this paper

  • ...Prior to131 quantitative model development, principal component analysis (PCA) was applied to132 the data (32000 spectra = 64 samples x 500 pixels) in order to identify and, if necessary,133 eliminate spectral outliers using the T2 Hotelling value (Esquerre et al., 2012; Hotelling,134 1931)....

    [...]

Related Papers (5)
Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry

[...]

01 Jul 2007-Journal of Food Engineering
Gamal ElMasry, Gamal ElMasry, Ning Wang, Adel ElSayed, Michael Ngadi 
Prediction of color and moisture content for vegetable soybean during drying using hyperspectral imaging technology

[...]

01 May 2014-Journal of Food Engineering
Min Huang, Qingguo Wang, Min Zhang, Qibing Zhu 
Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review — Part II: Applications

[...]

01 Jul 2013-Innovative Food Science and Emerging Technologies
Di Wu, Da-Wen Sun
Hyperspectral imaging – an emerging process analytical tool for food quality and safety control

[...]

01 Dec 2007-Trends in Food Science and Technology
Aoife Gowen, Colm P. O'Donnell, Patrick J. Cullen, Gerard Downey, Jesus M. Frias 
Studies on banana fruit quality and maturity stages using hyperspectral imaging

[...]

01 Jan 2012-Journal of Food Engineering
P. Rajkumar, Ning Wang, G. EImasry, G.S.V. Raghavan, Yvan Gariepy 
Frequently Asked Questions (1)
Q1. What are the contributions mentioned in the paper "Preliminary study on the use of near infrared hyperspectral imaging for quantitation and localisation of total glucosinolates in freeze-dried broccoli" ?

1 The use of hyperspectral imaging to ( a ) quantify and ( b ) localise total glucosinolates in 2 florets of a single broccoli species has been examined. Two different spectral regions 3 ( vis-NIR and NIR ), a number of spectral pre-treatments and different mask development 4 strategies were studied to develop the quantitative models. The procedure demonstrates potential for the 7 quantitative screening and localisation of total glucosinolates in broccoli using the 9508 1650 nm wavelength range.