Applications and Developments on the Use of Vibrational Spectroscopy Imaging for the Analysis, Monitoring and Characterisation of Crops and Plants

The adaptation and use of advanced technologies is an effective and encouraging way to efficiently and reliably characterise crops and plants. Additionally advances in these technologies will improve the information available for agronomists, breeders and plant physiologists in order to develop best management practices in the process and commercialization of agricultural products and commodities. Methods based on vibrational spectroscopy such as near infrared (NIR) spectroscopy using either single spot or hyperspectral measurements are now more available and ready to use than ever before. The main characteristics of these methodologies (high-throughput, non-destructive) have determined a growth in basic and applied research using NIR spectroscopy in many disciplines related with crop and plant sciences. A wide range of studies have demonstrated the ability of NIR spectroscopy to analyse different parameters in crops. Recently the use of hyperspectral imaging techniques have expanded the range of applications in crop and plant sciences. This article provides an overview of applications and developments of NIR hyperspectral image for the analysis, monitoring and characterisation of crops and plants.

[1]  B. Osborne,et al.  Classification of Sound and Stained Wheat Grains Using Visible and near Infrared Hyperspectral Image Analysis , 2007 .

[2]  Fang Cheng,et al.  Spectral and Image Integrated Analysis of Hyperspectral Data for Waxy Corn Seed Variety Classification , 2015, Sensors.

[3]  J. Hernández-Hierro,et al.  Feasibility study on the use of near-infrared hyperspectral imaging for the screening of anthocyanins in intact grapes during ripening. , 2013, Journal of agricultural and food chemistry.

[4]  P. Dardenne,et al.  Near-infrared, mid-infrared, and Raman spectroscopy , 2020, Chemical Analysis of Food.

[5]  Sidney Cox,et al.  Information technology: the global key to precision agriculture and sustainability , 2002 .

[6]  David K. Weaver,et al.  Use of spatial structure analysis of hyperspectral data cubes for detection of insect‐induced stress in wheat plants , 2009 .

[7]  José Crossa,et al.  High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge. , 2012, Journal of integrative plant biology.

[8]  Wenjiang Huang,et al.  [Using canopy hyperspectral ratio index to retrieve relative water content of wheat under yellow rust stress]. , 2010, Guang pu xue yu guang pu fen xi = Guang pu.

[9]  William R. Raun,et al.  Improving Nitrogen Use Efficiency for Cereal Production , 1999 .

[10]  D. Cozzolino Applications of Molecular Spectroscopy in Environmental and Agricultural Omics , 2013 .

[11]  Y. R. Chen,et al.  HYPERSPECTRAL REFLECTANCE AND FLUORESCENCE IMAGING SYSTEM FOR FOOD QUALITY AND SAFETY , 2001 .

[12]  Yud-Ren Chen,et al.  Hyperspectral imaging for safety inspection of food and agricultural products , 1999, Other Conferences.

[13]  Pedro Melo-Pinto,et al.  Identification of grapevine varieties using leaf spectroscopy and partial least squares , 2013 .

[14]  Shaokun Li,et al.  [Study on hyperspectral estimation of pigment contents in leaves of cotton under disease stress]. , 2010, Guang pu xue yu guang pu fen xi = Guang pu.

[15]  Reza Ehsani,et al.  Review: A review of advanced techniques for detecting plant diseases , 2010 .

[16]  D. Cozzolino,et al.  Instrumental Techniques and Methods: Their Role in Plant Omics , 2015 .

[17]  Norman C. Elliott,et al.  High spectral and spatial resolution hyperspectral imagery for quantifying Russian wheat aphid infestation in wheat using the constrained energy minimization classifier , 2014 .

[18]  Noel D.G. White,et al.  Identification of wheat classes at different moisture levels using near-infrared hyperspectral images of bulk samples , 2011 .

[19]  Jeffrey W. White,et al.  Field-based phenomics for plant genetics research , 2012 .

[20]  Paul J. Williams,et al.  Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis. , 2009, Analytica chimica acta.

[21]  Noel D.G. White,et al.  Identification of insect-damaged wheat kernels using short-wave near-infrared hyperspectral and digital colour imaging , 2010 .

[22]  Douglas Fernandes Barbin,et al.  Grape seed characterization by NIR hyperspectral imaging , 2013 .

[23]  Tony E Grift The farm of the future , 2011 .

[24]  Babangida Lawal Yusuf,et al.  Application of hyperspectral imaging sensor to differentiate between the moisture and reflectance of healthy and infected tobacco leaves , 2011 .

[25]  I. M. Scotford,et al.  Applications of Spectral Reflectance Techniques in Northern European Cereal Production: A Review , 2005 .

[26]  Colm P. O'Donnell,et al.  Applications of thermal imaging in food quality and safety assessment , 2010 .

[27]  V. Bellon-Maurel,et al.  Determining Vitreousness of Durum Wheat Kernels Using near Infrared Hyperspectral Imaging , 2006 .

[28]  Gonzalo Pajares Advances in Sensors Applied to Agriculture and Forestry , 2011, Sensors.

[29]  Daniel Cozzolino,et al.  Recent Trends on the Use of Infrared Spectroscopy to Trace and Authenticate Natural and Agricultural Food Products , 2012 .

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

[31]  Margarita Ruiz-Altisent,et al.  Review: Sensors for product characterization and quality of specialty crops-A review , 2010 .

[32]  Julio Nogales-Bueno,et al.  Determination of technological maturity of grapes and total phenolic compounds of grape skins in red and white cultivars during ripening by near infrared hyperspectral image: a preliminary approach. , 2014, Food chemistry.

[33]  D. Jayas,et al.  Identification of wheat classes using wavelet features from near infrared hyperspectral images of bulk samples. , 2009 .

[34]  Noel D.G. White,et al.  Feasibility of near-infrared hyperspectral imaging to differentiate Canadian wheat classes , 2008 .

[35]  Moon S. Kim,et al.  Limitations of single kernel near-infrared hyperspectral imaging of soft wheat for milling quality ☆ , 2013 .

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

[37]  Chu Zhang,et al.  Rice Seed Cultivar Identification Using Near-Infrared Hyperspectral Imaging and Multivariate Data Analysis , 2013, Sensors.

[38]  Lena Åberg,et al.  Near infrared spectroscopy for determination of mycotoxins in cereals , 2003 .