Detecting Frost Stress in Wheat: A Controlled Environment Hyperspectral Study on Wheat Plant Components and Implications for Multispectral Field Sensing

Radiant frost during the reproductive stage of plant growth can result in considerable wheat (Triticum aestivum L.) yield loss. Much effort has been spent to prevent and manage these losses, including post-frost remote sensing of damage. This study was done under controlled conditions to examine the effect of imposed frost stress on the spectral response of wheat plant components (heads and flag leaves). The approach used hyperspectral profiling to determine whether changes in wheat components were evident immediately after a frost (up to 5 days after frosting (DAF)). Significant differences were found between frost treatments, irrespective of DAF, in the Blue/Green (419–512 nanometers (nm)), Red (610–675 nm) and Near Infrared (NIR; 749–889 nm) regions of the electromagnetic spectrum (EMS) in head spectra, and in the Blue (415–494 nm), Red (670–687 nm) and NIR (727–889 nm) regions in the leaf spectra. Significant differences were found for an interaction between time and frost treatment in the Green (544–575 nm) and NIR (756–889 nm) in head spectra, and in the UV (394–396 nm) and Green/Red (564–641 nm) in leaf spectra. These findings were compared with spectral and temporal resolutions of commonly used field agricultural multispectral sensors to examine their potential suitability for frost damage studies at the canopy scale, based on the correspondence of their multispectral bands to the results from this laboratory-based hyperspectral study.

[1]  K. Kersting,et al.  Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis. , 2012, Functional plant biology : FPB.

[2]  Bappa Das,et al.  Hyperspectral Remote Sensing: Use in Detecting Abiotic Stresses in Agriculture , 2018 .

[3]  J. Sutka Genetic control of frost tolerance in wheat (Triticum aestivum L.) , 1994, Euphytica.

[4]  H. Marcellos,et al.  Studies on frost injury to wheat. IV.* Freezing of ears after emergence from the leaf sheath , 1974 .

[5]  J. H. Spink,et al.  Frost damage to winter wheat in the UK: the effect of plant population density , 2004 .

[6]  A. Huete,et al.  A review of vegetation indices , 1995 .

[7]  Glenn J. Fitzgerald,et al.  Frost Damage Assessment in Wheat Using Spectral Mixture Analysis , 2019, Remote. Sens..

[8]  Simon D. Jones,et al.  Remote sensing of nitrogen and water stress in wheat , 2007 .

[9]  G. A. Blackburn,et al.  Hyperspectral remote sensing of plant pigments. , 2006, Journal of experimental botany.

[10]  Manu Kumar Crop Plants and Abiotic Stresses , 2013 .

[11]  Shahryar F. Kianian,et al.  A Novel Approach to Assess Salt Stress Tolerance in Wheat Using Hyperspectral Imaging , 2018, Front. Plant Sci..

[12]  Bruno Basso,et al.  REMOTELY SENSED VEGETATION INDICES: THEORY AND APPLICATIONS FOR CROP MANAGEMENT INDICI DI VEGETAZIONE TELERILEVATI: TEORIA ED APPLICAZIONI PER LA GESTIONE AGRONOMICA DELLE COLTURE , 2004 .

[13]  B. Datt Remote Sensing of Chlorophyll a, Chlorophyll b, Chlorophyll a+b, and Total Carotenoid Content in Eucalyptus Leaves , 1998 .

[14]  G. Fitzgerald,et al.  Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI) , 2010 .

[15]  H. D. Patterson,et al.  Recovery of inter-block information when block sizes are unequal , 1971 .

[16]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[17]  A. Borrell,et al.  Current and emerging screening methods to identify post-head-emergence frost adaptation in wheat and barley. , 2012, Journal of experimental botany.

[18]  G. Wang,et al.  Hyperspectral data mining to identify relevant canopy spectral features for estimating durum wheat growth, nitrogen status, and grain yield , 2017, Comput. Electron. Agric..

[19]  Woodruff 'WHEATMAN' a decision support system for wheat management in subtropical Australia , 1992 .

[20]  Damon L. Smith,et al.  Introduction to Abiotic Disorders in Plants , 2012 .

[21]  A. Gitelson,et al.  Application of Spectral Remote Sensing for Agronomic Decisions , 2008 .

[22]  B. Rock,et al.  Comparison of in situ and airborne spectral measurements of the blue shift associated with forest decline , 1988 .

[23]  J. Sutka Genetic studies of frost resistance in wheat , 1981, Theoretical and Applied Genetics.

[24]  W. Single Studies on frost injury to wheat. II. Ice formation within the plant , 1964 .

[25]  Linzhang Yang,et al.  Deriving leaf chlorophyll content of green-leafy vegetables from hyperspectral reflectance , 2009 .

[26]  H. Marcellos Wheat frost injury — freezing stress and photosynthesis , 1977 .

[27]  R. Mittler,et al.  Abiotic stress, the field environment and stress combination. , 2006, Trends in plant science.

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

[29]  R. Chibbar,et al.  Identification of quantitative trait loci and associated candidate genes for low-temperature tolerance in cold-hardy winter wheat , 2006, Functional & Integrative Genomics.

[30]  James Barber,et al.  Red edge measurements for remotely sensing plant chlorophyll content , 1983 .

[31]  J. Snape,et al.  Mapping genes for flowering time and frost tolerance in cereals using precise genetic stocks , 2004, Euphytica.

[32]  E. Hoque,et al.  Spectral blue-shift of red edge minitors damage class of beech trees , 1992 .

[33]  Anthony King,et al.  Technology: The Future of Agriculture , 2017, Nature.

[34]  Y. Qian,et al.  Spectral Reflectance Response of Three Turfgrasses to Leaf Dehydration , 2011 .

[35]  Christopher B. Field,et al.  Reflectance indices associated with physiological changes in nitrogen- and water-limited sunflower leaves☆ , 1994 .

[36]  J. Peñuelas,et al.  The red edge position and shape as indicators of plant chlorophyll content, biomass and hydric status. , 1994 .

[37]  Jihua Wang,et al.  Diagnosis of freezing stress in wheat seedlings using hyperspectral imaging , 2012 .

[38]  R. Sahoo,et al.  Comparison of different uni- and multi-variate techniques for monitoring leaf water status as an indicator of water-deficit stress in wheat through spectroscopy , 2017 .

[39]  Gregory A. Carter,et al.  Responses of leaf spectral reflectance to plant stress. , 1993 .

[40]  D. Wright,et al.  Effects of frost during grain filling on wheat yield and grain structure , 1998 .

[41]  G. O'Leary,et al.  Simulating the impact of extreme heat and frost events on wheat crop production: a review , 2015 .

[42]  H. Jones,et al.  Remote Sensing of Vegetation: Principles, Techniques, and Applications , 2010 .

[43]  A. Gitelson,et al.  Detection of Red Edge Position and Chlorophyll Content by Reflectance Measurements Near 700 nm , 1996 .

[44]  R. Pearce Extracellular ice and cell shape in frost-stressed cereal leaves: A low-temperature scanning-electron-microscopy study , 1988, Planta.

[45]  S. Guessoum,et al.  Predicting the efficiency of using the RGB (Red, Green and Blue) reflectance for estimating leaf chlorophyll content of Durum wheat (Triticum durum Desf.) genotypes under semi arid conditions. , 2012 .

[46]  J. Sutka Genes for frost resistance in wheat , 2001, Euphytica.

[47]  Jadunandan Dash,et al.  Elucidating the impact of temperature variability and extremes on cereal croplands through remote sensing , 2015, Global change biology.

[48]  B. Trevaskis,et al.  Frost-tolerance genes Fr-A2 and Fr-B2 in Australian wheat and their effects on days to heading and grain yield in lower rainfall environments in southern Australia , 2016, Crop and Pasture Science.

[49]  V. Cantore,et al.  Remote sensing based monitoring of durum wheat under water stress treatments , 2017 .

[50]  A. Borrell,et al.  Post-head-emergence frost in wheat and barley: defining the problem, assessing the damage, and identifying resistance. , 2015, Journal of experimental botany.

[51]  M. Fuller,et al.  A chamber for the simulation of radiation freezing of plants , 1998 .

[52]  D. Livingston,et al.  High-definition infrared thermography of ice nucleation and propagation in wheat under natural frost conditions and controlled freezing , 2017, Planta.

[53]  Jan G. P. W. Clevers,et al.  Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review , 2015 .

[54]  Linesh Raja,et al.  Agriculture drones: A modern breakthrough in precision agriculture , 2017 .

[55]  G. O'Leary,et al.  Frost response in wheat and early detection using proximal sensors , 2018, Journal of Agronomy and Crop Science.

[56]  K. Moffett,et al.  Remote Sens , 2015 .

[57]  D. M. Klaus,et al.  The assessment of leaf water content using leaf reflectance ratios in the visible, near‐, and short‐wave‐infrared , 2008 .

[58]  C. Tucker Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[59]  Daniel Rodriguez,et al.  Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop eco-physiological concepts , 2006 .

[60]  C. Field,et al.  A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency , 1992 .

[61]  H. Marcellos A plant freezing chamber with radiative and convective energy exchange , 1981 .

[62]  Nader Aryamanesh,et al.  Use of variogram analysis to classify field peas with and without internal defects caused by weevil infestation , 2014 .

[63]  E. Ashworth,et al.  Cell shape and localisation of ice in leaves of overwintering wheat during frost stress in the field , 1992, Planta.

[64]  H. Lichtenthaler Vegetation stress : an introduction to the stress concept in plants , 1996 .

[65]  Joe T. Ritchie,et al.  Low-Temperature Tolerance in Cereals: Model and Genetic Interpretation , 1999 .

[66]  Dimitrios Moshou,et al.  Water stress detection based on optical multisensor fusion with a least squares support vector machine classifier , 2014 .

[67]  X. Vanrobaeys,et al.  Early detection of nutrient and biotic stress in Phaseolus vulgaris , 2007 .

[68]  Moon S. Kim,et al.  Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .

[69]  J. Boyer Plant Productivity and Environment , 1982, Science.

[70]  M. Burke,et al.  Freezing and Injury in Plants , 1976 .

[71]  G. Fitzgerald,et al.  In-field methods for rapid detection of frost damage in Australian dryland wheat during the reproductive and grain-filling phase , 2017, Crop and Pasture Science.

[72]  P. Duce,et al.  Rischio climatico per l’agricoltura in ambiente mediterraneo , 2004 .

[73]  K. Chenu,et al.  Frost trends and their estimated impact on yield in the Australian wheatbelt , 2015, Journal of experimental botany.

[74]  A. Gitelson,et al.  Remote estimation of chlorophyll content in higher plant leaves , 1997 .

[75]  G. Menexes,et al.  Assessment of Vegetation Indices Derived by UAV Imagery for Durum Wheat Phenotyping under a Water Limited and Heat Stressed Mediterranean Environment , 2017, Front. Plant Sci..

[76]  Michael F. Thomashow,et al.  PLANT COLD ACCLIMATION: Freezing Tolerance Genes and Regulatory Mechanisms. , 1999, Annual review of plant physiology and plant molecular biology.

[77]  H. Poilvé,et al.  Hyperspectral Imaging and Stress Mapping in Agriculture , 1998 .

[78]  Li He,et al.  Canopy Vegetation Indices from In situ Hyperspectral Data to Assess Plant Water Status of Winter Wheat under Powdery Mildew Stress , 2017, Front. Plant Sci..

[79]  David B. Lobell,et al.  Impacts of Day Versus Night Temperatures on Spring Wheat Yields: A Comparison of Empirical and CERES Model Predictions in Three Locations , 2007 .