NIR Spectroscopy Applications for Internal and External Quality Analysis of Citrus Fruit—A Review

The global citrus industry is continually confronted by new technological challenges to meet the ever-increasing consumer awareness and demand for quality-assured fruit. To face these challenges, recent trend in agribusiness is declining reliance on subjective assessment of quality and increasing adoption of objective, quantitative and non-destructive techniques of quality assessment. Non-destructive instrument-based methods are preferred to destructive techniques because they allow the measurement and analysis of individual fruit, reduce waste and permit repeated measures on the same item over time. A wide range of objective instruments for sensing and measuring the quality attributes of fresh produce have been reported. Among non-destructive quality assessment techniques, near-infrared (NIR) spectroscopy (NIRS) is arguably the most advanced with regard to instrumentation, applications, accessories and chemometric software packages. This paper reviews research progress on NIRS applications in internal and external quality measurement of citrus fruit, including the selection of NIR characteristics for spectra capture, analysis and interpretation. A brief overview on the fundamental theory, history, chemometrics of NIRS including spectral pre-processing methods, model calibration, validation and robustness is included. Finally, future prospects for NIRS-based imaging systems such as multispectral and hyperspectral imaging as well as optical coherence tomography as potential non-destructive techniques for citrus quality assessment are explored.

[1]  Thomas H. Spreen,et al.  Projections of world production and consumption of citrus to 2010 , 2001 .

[2]  Robert L. Shewfelt,et al.  Postharvest handling: a systems approach. , 1993 .

[3]  G. P Krivoshiev,et al.  A Possibility for Elimination of the Interference from the Peel in Nondestructive Determination of the Internal Quality of Fruit and Vegetables by VIS/NIR Spectroscopy , 2000 .

[4]  J. Guthrie,et al.  Assessment of internal quality attributes of mandarin fruit. 2. NIR calibration model robustness , 2005 .

[5]  José Antonio Cayuela,et al.  Intact orange quality prediction with two portable NIR spectrometers , 2010 .

[6]  Bart Nicolai,et al.  Non-destructive measurement of bitter pit in apple fruit using NIR hyperspectral imaging , 2006 .

[7]  B. Nicolai,et al.  Postharvest quality of apple predicted by NIR-spectroscopy: Study of the effect of biological variability on spectra and model performance , 2010 .

[8]  Nuria Aleixos,et al.  Erratum to: Advances in Machine Vision Applications for Automatic Inspection and Quality Evaluation of Fruits and Vegetables , 2011 .

[9]  R. L. Perrine Principles and Methods of Measuring Moisture in Liquids and Solids: edited by Arnold Wexler and Paul N. Winn, Jr. 333 pages, diagrams, illustrations, 7 × 10 in. New York, Reinhold Publishing Corp., 1965. Price, $20.00 , 1965 .

[10]  R. Edelman,et al.  Magnetic resonance imaging (2) , 1993, The New England journal of medicine.

[11]  Marcelo Blanco,et al.  NIR spectroscopy: a rapid-response analytical tool , 2002 .

[12]  K. Peiris,et al.  Spatial variability of soluble solids or dry-matter content within individual fruits, bulbs, or tubers : Implications for the development and use of NIR spectrometric techniques , 1999 .

[13]  Qian Ma,et al.  Application of Wavelet Transform in the Prediction of Navel Orange Vitamin C Content by Near-Infrared Spectroscopy , 2007 .

[14]  P. Carlini,et al.  Vis-NIR measurement of soluble solids in cherry and apricot by PLS regression and wavelength selection. , 2000, Journal of agricultural and food chemistry.

[15]  V. A. McGlone,et al.  Prediction of storage disorders of kiwifruit (Actinidia chinensis) based on visible-NIR spectral characteristics at harvest , 2004 .

[16]  S. Engelsen,et al.  Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .

[17]  José Blasco,et al.  Multispectral inspection of citrus in real-time using machine vision and digital signal processors , 2002 .

[18]  J. Qin,et al.  Detection of citrus canker using hyperspectral reflectance imaging with spectral information divergence , 2009 .

[19]  Colm P. O'Donnell,et al.  Hyperspectral imaging – an emerging process analytical tool for food quality and safety control , 2007 .

[20]  Byoung-Kwan Cho,et al.  Determination of origin and sugars of citrus fruits using genetic algorithm, correspondence analysis and partial least square combined with fiber optic NIR spectroscopy. , 2008, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[21]  J. Guthrie,et al.  NIR model development and robustness in prediction of melon fruit total soluble solids , 2006 .

[22]  Kerry B. Walsh,et al.  Non-invasive assessment of pineapple and mango fruit quality using near infra-red spectroscopy , 1997 .

[23]  N. Kasabov,et al.  Linear and non-linear pattern recognition models for classification of fruit from visible–near infrared spectra , 2000 .

[24]  D. Burns,et al.  Quantitative Multiwavelength Constituent Measurements Using Single-Wavelength Photon Time-of-Flight Correction , 1999 .

[25]  J. Fujimoto,et al.  Optical Coherence Tomography , 1991, LEOS '92 Conference Proceedings.

[26]  A. Fercher,et al.  Optical coherence tomography - principles and applications , 2003 .

[27]  Rainer Künnemeyer,et al.  A Low-Cost System for the Grading of Kiwifruit , 1999 .

[28]  Richard G. Leffler,et al.  Near Infrared Analysis of Soluble Solids in Intact Cantaloupe , 1989 .

[29]  A. Peirs,et al.  Temperature compensation for near infrared reflectance measurement of apple fruit soluble solids contents , 2003 .

[30]  P. Schaare,et al.  Comparison of reflectance, interactance and transmission modes of visible-near infrared spectroscopy for measuring internal properties of kiwifruit (Actinidia chinensis) , 2000 .

[31]  Fernando López-García,et al.  Automatic detection of skin defects in citrus fruits using a multivariate image analysis approach , 2010 .

[32]  G. Ripandelli,et al.  Optical coherence tomography. , 1998, Seminars in ophthalmology.

[33]  Manuela Zude,et al.  NIRS as a tool for precision horticulture in the citrus industry , 2008 .

[34]  B. Nicolai,et al.  Time-resolved and continuous wave NIR reflectance spectroscopy to predict soluble solids content and firmness of pear , 2008 .

[35]  K. H. Norris,et al.  Qualitative applications of near-infrared reflectance spectroscopy , 1987 .

[36]  V. Mcglone,et al.  Light distribution inside mandarin fruit during internal quality assessment by NIR spectroscopy , 2003 .

[37]  B. Nicolai,et al.  Analysis of the time course of core breakdown in 'Conference' pears by means of MRI and X-ray CT , 2003 .

[38]  Jitendra Paliwal,et al.  Near-infrared spectroscopy and imaging in food quality and safety , 2007 .

[39]  S. Kawano,et al.  Nondestructive Determination of Sugar Content in Satsuma Mandarin using Near Infrared (NIR) Transmittance , 1993 .

[40]  Ruikang K. Wang,et al.  Theory, developments and applications of optical coherence tomography , 2005 .

[41]  F. Intrigliolo,et al.  Estimation of plant nutritional status by Vis-NIR spectrophotometric analysis on orange leaves (Citrus sinensis (L) Osbeck cv Tarocco) , 2010 .

[42]  G. Camps-Valls,et al.  Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins , 2008 .

[43]  Victor Alchanatis,et al.  A Multispectral Imaging Analysis for Enhancing Citrus Fruit Detection , 2010 .

[44]  Zhiqin Zhou,et al.  Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy , 2010 .

[45]  K. Walsh,et al.  Robustness of calibration models based on near infrared spectroscopy for the in-line grading of stonefruit for total soluble solids content , 2006 .

[46]  K. Norris,et al.  4. Direct Spectrophotometric Determination of Moisture Content of Grain and Seeds , 1996 .

[47]  José Blasco,et al.  Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features , 2009 .

[48]  K. Walsh,et al.  Short-Wavelength Near-Infrared Spectra of Sucrose, Glucose, and Fructose with Respect to Sugar Concentration and Temperature , 2003, Applied spectroscopy.

[49]  José Blasco,et al.  Computer vision detection of peel defects in citrus by means of a region oriented segmentation algorithm , 2007 .

[50]  Yidan Bao,et al.  Visible and near infrared spectroscopy for rapid detection of citric and tartaric acids in orange juice , 2007 .

[51]  W. Fred McClure,et al.  204 Years of near Infrared Technology: 1800–2003 , 2003 .

[52]  D. J. Reid,et al.  Assessment of internal quality attributes of mandarin fruit. 1. NIR calibration model development , 2005 .

[53]  K. Peiris,et al.  Near-infrared Spectrometric Method for Nondestructive Determination of Soluble Solids Content of Peaches , 1998 .

[54]  Rainer Künnemeyer,et al.  Method of Wavelength Selection for Partial Least Squares , 1997 .

[55]  D. Massart,et al.  Elimination of uninformative variables for multivariate calibration. , 1996, Analytical chemistry.

[56]  Stanley J. Kays,et al.  Near-infrared (NIR) Spectrometric Technique for Nondestructive Determination of Soluble Solids Content in Processing Tomatoes , 1998 .

[57]  Qingming Luo,et al.  Monte Carlo modeling of optical coherence tomography imaging through turbid media. , 2004, Applied optics.

[58]  P. Williams,et al.  Near-Infrared Technology in the Agricultural and Food Industries , 1987 .

[59]  B. Nicolai,et al.  MRI and x-ray CT study of spatial distribution of core breakdown in 'Conference' pears. , 2003, Magnetic resonance imaging.

[60]  A. Peirs,et al.  Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review , 2007 .

[61]  Josse De Baerdemaeker,et al.  Effects of bruise type on discrimination of bruised and non-bruised ‘Golden Delicious’ apples by VIS/NIR spectroscopy , 2003 .

[62]  J. J. Gaffney,et al.  Reflectance Properties of Citrus Fruits , 1973 .

[63]  Rainer Künnemeyer,et al.  Internal Quality Assessment of Mandarin Fruit by vis/NIR Spectroscopy , 2003 .

[64]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .

[65]  C. Camps,et al.  Non-destructive assessment of apricot fruit quality by portable visible-near infrared spectroscopy , 2009 .

[66]  Aiguo Ouyang,et al.  Nondestructive measurement of soluble solid content of navel orange fruit by visible-NIR spectrometric technique with PLSR and PCA-BPNN. , 2010 .

[67]  Min Huang,et al.  Measurement of soluble solids contents and pH in orange juice using chemometrics and vis-NIRS. , 2006, Journal of agricultural and food chemistry.

[68]  Bart Nicolai,et al.  Kernel PLS regression on wavelet transformed NIR spectra for prediction of sugar content of apple , 2007 .

[69]  J. Guthrie,et al.  Application of commercially available, low-cost, miniaturised NIR spectrometers to the assessment of the sugar content of intact fruit , 2000 .

[70]  Josse De Baerdemaeker,et al.  Detecting Bruises on ‘Golden Delicious’ Apples using Hyperspectral Imaging with Multiple Wavebands , 2005 .

[71]  Akademii︠a︡ medit︠s︡inskikh nauk Sssr Journal of physics , 1939 .

[72]  T. Fearn,et al.  Near infrared spectroscopy in food analysis , 1986 .

[73]  J. Guthrie,et al.  Robustness of NIR Calibrations for Soluble Solids in Intact Melon and Pineapple , 1998 .

[74]  Jianwei Qin,et al.  Citrus canker detection using hyperspectral reflectance imaging and PCA-based image classification method , 2008 .

[75]  D. L. Wetzel Near-Infrared Reflectance Analysis , 1983 .

[76]  U. M. Peiper,et al.  A Spectrophotometric Method for Detecting Surface Bruises on "Golden Delicious" Apples , 1994 .

[77]  W. E. Morf Time-dependent selectivity behavior and dynamic response of silver halide membrane electrodes to interfering ions , 1983 .

[78]  Roberto Kawakami Harrop Galvão,et al.  NIR spectrometric determination of quality parameters in vegetable oils using iPLS and variable selection , 2008 .

[79]  E. K. Kemsley,et al.  Feasibility study of NIR diffuse optical tomography on agricultural produce , 2008 .

[80]  V. A. Kamenskii,et al.  Visualization of Plant Tissues by Optical Coherence Tomography , 2003, Russian Journal of Plant Physiology.

[81]  P. Butz,et al.  Recent Developments in Noninvasive Techniques for Fresh Fruit and Vegetable Internal Quality Analysis , 2006 .

[82]  C. N. Thai,et al.  Nondestructive Detection of Section Drying, an Internal Disorder in Tangerine , 1998 .

[83]  Bart De Ketelaere,et al.  Chapter 15 – Non-destructive Evaluation: Detection of External and Internal Attributes Frequently Associated with Quality and Damage , 2009 .

[84]  Yibin Ying,et al.  Comparison of diffuse reflectance and transmission mode of visible-near infrared spectroscopy for detecting brown heart of pear , 2007 .

[85]  J. Fujimoto,et al.  Optical Coherence Tomography , 1991 .

[86]  P. Greenwood,et al.  Influences on the loin and cellular characteristics of the m. longissimus lumborum of Australian Poll Dorset-sired lambs , 2006 .

[87]  A. Peirs,et al.  Effect of biological variability on the robustness of NIR models for soluble solids content of apples , 2003 .

[88]  R. Kuranov,et al.  Study of the Morphological and Functional State of Higher Plant Tissues by Optical Coherence Microscopy and Optical Coherence Tomography , 2005, Russian Journal of Plant Physiology.

[89]  J. Gómez-Sanchís,et al.  Advances in Machine Vision Applications for Automatic Inspection and Quality Evaluation of Fruits and Vegetables , 2011 .

[90]  Xudong Sun,et al.  Nondestructive measurement of internal quality of Nanfeng mandarin fruit by charge coupled device near infrared spectroscopy , 2010 .

[91]  A. Peirs,et al.  Light penetration properties of NIR radiation in fruit with respect to non-destructive quality assessment , 2000 .

[92]  I. Meglinski,et al.  Plant photonics: application of optical coherence tomography to monitor defects and rots in onion , 2010 .

[93]  F. Mizutani,et al.  Relationship between Fruit Shape and Acid Content in Different Parts of Citrus Fruits , 2002 .

[94]  J. Burns,et al.  Postharvest peel pitting at non-chilling temperatures in grapefruit is promoted by changes from low to high relative humidity during storage , 2004 .

[95]  S. D. Jong PLS fits closer than PCR , 1993 .

[96]  R. Kuranov,et al.  In vivo visualization of Tradescantia leaf tissue and monitoring the physiological and morphological states under different water supply conditions using optical coherence tomography , 2004, Planta.

[97]  Federico Pallottino,et al.  Non-destructive Estimation of Mandarin Maturity Status Through Portable VIS-NIR Spectrophotometer , 2011 .

[98]  Sun Xudong,et al.  Nondestructive assessment of quality of Nanfeng mandarin fruit by a portable near infrared spectroscopy , 2009 .

[99]  T. Næs,et al.  Ensemble methods and data augmentation by noise addition applied to the analysis of spectroscopic data , 2005 .

[100]  Huirong Xu,et al.  Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: A review , 2008 .

[101]  L. Smith Pineapple specific gravity as an index of eating quality , 1984 .

[102]  John Weiner,et al.  Letter to the Editor , 1992, SIGIR Forum.

[103]  Hai-yan Yu,et al.  Application Fourier transform near infrared spectrometer in rapid estimation of soluble solids content of intact citrus fruits , 2006, Journal of Zhejiang University SCIENCE B.

[104]  K. Miyamoto,et al.  Classification of High Acid Satsuma Mandarins by Near Infrared Transmittance Spectroscopy , 1998 .

[105]  S. Kawano,et al.  Firmness, dry-matter and soluble-solids assessment of postharvest kiwifruit by NIR spectroscopy , 1998 .

[106]  Annia García Pereira,et al.  Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using Vis/NIR-spectroscopy techniques , 2006 .

[107]  José Antonio Cayuela,et al.  Vis/NIR soluble solids prediction in intact oranges (Citrus sinensis L.) cv. Valencia Late by reflectance , 2008 .

[108]  K. Miyamoto,et al.  Non-Destructive Determination of Sugar Content in Satsuma Mandarin Fruit by near Infrared Transmittance Spectroscopy , 1995 .

[109]  Adel A. Kader,et al.  Opportunities in using biotechnology to maintain postharvest quality and safety of fresh produce , 2000 .

[110]  M. J. Delwiche,et al.  Spectral analysis of peach surface defects. , 1990 .

[111]  Moon S. Kim,et al.  Development of hyperspectral imaging technique for the detection of apple surface defects and contaminations , 2004 .

[112]  D. Bulanon,et al.  Spectral reflectance characteristics of citrus canker and other peel conditions of grapefruit. , 2009 .

[113]  K. Miyamoto,et al.  Application of Time-of-flight Near-infrared Spectroscopy to Detect Sugar and Acid Content in Satsuma Mandarin , 2003 .

[114]  K. Walsh,et al.  Calibration Transfer between Miniature Photodiode Array-Based Spectrometers in the near Infrared Assessment of Mandarin Soluble Solids Content , 2002 .

[115]  D A Hutchins,et al.  A near-infrared (NIR) technique for imaging food materials. , 2009, Journal of food science.

[116]  Dudley A. Williams,et al.  Optical properties of water in the near infrared. , 1974 .

[117]  V. Mcglone,et al.  Vis/NIR estimation at harvest of pre- and post-storage quality indices for 'Royal Gala' apple , 2002 .

[118]  T. Lovász,et al.  Application of near Infrared Transmission Spectroscopy for the Determination of Some Quality Parameters of Apples , 1994 .

[119]  Xuhui Zhao,et al.  Effect of fruit harvest time on citrus canker detection using hyperspectral reflectance imaging , 2010 .

[120]  M. Agustí,et al.  Postharvest rind staining in Navel oranges is aggravated by changes in storage relative humidity: effect on respiration, ethylene production and water potential , 2003 .

[121]  K. Miyamoto,et al.  Classification of High Acid Fruits by Partial Least Squares Using the near Infrared Transmittance Spectra of Intact Satsuma Mandarins , 1998 .

[122]  G. Dull,et al.  Use of near infrared analysis for the nondestructive measurement of dry matter in potatoes , 1989, American Potato Journal.

[123]  S. Arridge,et al.  INSTITUTE OF PHYSICS PUBLISHING PHYSICS IN MEDICINE AND BIOLOGY , 2003 .

[124]  H. Schulz,et al.  Classification and analysis of citrus oils by NIR spectroscopy , 2001 .

[125]  Karen I. Theron,et al.  Robust prediction models for quality parameters in Japanese plums (Prunus salicina L.) using NIR spectroscopy. , 2010 .

[126]  José Blasco,et al.  Citrus sorting by identification of the most common defects using multispectral computer vision , 2007 .