Crop and Pasture Science Crop and Pasture Science Society
Plant sciences, sustainable farming systems and food quality
RESEARCH ARTICLE (Open Access)

In-field methods for rapid detection of frost damage in Australian dryland wheat during the reproductive and grain-filling phase

Eileen M. Perry A C , James G. Nuttall B , Ashley J. Wallace B and Glenn J. Fitzgerald B
+ Author Affiliations
- Author Affiliations

A Department of Economic Development Jobs, Transport and Resources, Cnr Midland Highway and Taylors Street, Epsom, Vic. 3551, Australia.

B Grains Innovation Park, Department of Economic Development Jobs, Transport and Resources, 110 Natimuk Road, Horsham, Vic. 3400, Australia.

C Corresponding author. Email: eileen.perry@ecodev.vic.gov.au

Crop and Pasture Science 68(6) 516-526 https://doi.org/10.1071/CP17135
Submitted: 1 April 2017  Accepted: 10 June 2017   Published: 11 July 2017

Abstract

Frost damage causes significant production losses and costs to Australian dryland wheat, and frost impacts are not expected to decline in the near future, despite global warming. Rapid estimation of frost damage to crops on a spatial basis would allow for timely management decisions to reduce the economic impact of frost events. In this paper, we take a first step in evaluating the utility of hyperspectral reflectance and active light fluorescence for detecting frost damage to wheat during its reproductive phase. Two experiments were conducted immediately after the first observation of frost damage, (i) in 2006, five plots in an existing trial were opportunistically subdivided to take spectral reflectance measurements on frost damaged plants along with yield measurements, and (ii) in 2015, a transect across 31 rows within a commercial paddock was established to evaluate spectral reflectance, fluorometer measurements, and yield along a gradient from non-frosted to frost damaged plants. The results of the hyperspectral reflectance data appeared variable in response across the two experimental sites where frost was observed in-crop. In 2006, hyperspectral-derived indices showed significant differences (P < 0.05) between measurements of frosted and non-frosted canopies, but this was not the case for observations taken in 2015, where the mean response was reversed between experimental sites for several of the indices. In contrast, fluorometer measurements in the 2015 trial resulted in higher correlations with yield and observed frost damage compared with the reflectance measurements. Seven of the nine fluorometer indices evaluated were correlated with yield (used as an indicator of frost damage) at P < 0.01. An index of compounds which absorbs at 375 nm, FLAV, had the best correlation coefficients of 0.91 and 0.90 for the two dates in 2015. The fluorescence index FLAV was selected to evaluate whether it could be used to classify the canopy as frost affected or not, using discriminant analysis for the 2015 transect data. The overall classification accuracy, defined as the number of correctly classified measurements (57) divided by the total number (62) was 92%. The present study was not able to provide insight into how rapidly the sensors could detect frost damage before detection with the naked eye, as the survey data constituted a transect based on early visual symptoms, however this study does provide important insight into what sensors and/or indices may be sensitive to ‘seeing’ early frost damage in-crop. The next steps, which build on this work and need to be resolved are (i) what is the nominal scale of measurements required, and for which portions of the plant canopy? (ii) How robust (over space and time) are any relationships between frost damage and index response? (iii) Can frost damage be detected before the onset of visual damage?

Additional keywords: fluorometer, proximal sensing, spectral reflectance.


References

Agati G, Foschi L, Grossi N, Guglielminetti L, Cerovic ZG, Volterrani M (2013) Fluorescence-based versus reflectance proximal sensing of nitrogen content in Paspalum vaginatum and Zoysia matrella turfgrasses. European Journal of Agronomy 45, 39–51.

Al-Issawi M, Rihan HZ, El-Sarkassy N, Fuller MP (2013) Frost hardiness expression and characterisation in wheat at ear emergence. Journal of Agronomy & Crop Science 199, 66–74.
Frost hardiness expression and characterisation in wheat at ear emergence.CrossRef | 1:CAS:528:DC%2BC3sXktVGktbY%3D&md5=e7882f33fd965ad61b1416036208dd3fCAS |

Bürling K, Hunsche M, Noga G (2011) Use of blue-green and chlorophyll fluorescence measurements for differentiation between nitrogen deficiency and pathogen infection in winter wheat. Journal of Plant Physiology 168, 1641–1648.
Use of blue-green and chlorophyll fluorescence measurements for differentiation between nitrogen deficiency and pathogen infection in winter wheat.CrossRef |

Bürling K, Cerovic ZG, Cornic G, Ducruet J-M, Noga G, Hunsche M (2013) Fluorescence-based sensing of drought-induced stress in the vegetative phase of four contrasting wheat genotypes. Environmental and Experimental Botany 89, 51–59.
Fluorescence-based sensing of drought-induced stress in the vegetative phase of four contrasting wheat genotypes.CrossRef |

Clarke TR, Moran MS, Barnes EM, Pinter PJ, Qi J (2001) Planar domain indices: A method for measuring a quality of a single component in two-component pixels. In ‘IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings IEEE International Geoscience and Remote Sensing Symposium’. Sydney, NSW, 9–13 July 2001. Vol. 3, pp. 1279–1281. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=976818&isnumber=21047

Cromey M, Wright D, Boddington H (1998) Effects of frost during grain filling on wheat yield and grain structure. New Zealand Journal of Crop and Horticultural Science 26, 279–290.
Effects of frost during grain filling on wheat yield and grain structure.CrossRef |

Daughtry CST (2001) Discriminating crop residues from soil by shortwave infrared reflectance. Agronomy Journal 93, 125–131.
Discriminating crop residues from soil by shortwave infrared reflectance.CrossRef |

Daughtry CST, Walthall CL, Kim MS, de Colstoun EB, McMurtrey JE (2000) Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sensing of Environment 74, 229–239.
Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance.CrossRef |

de Leeuw J, Vrieling A, Shee A, Atzberger C, Hadgu K, Biradar C, Keah H, Turvey C (2014) The potential and uptake of remote sensing in insurance: A review. Remote Sensing 6, 10888–10912.
The potential and uptake of remote sensing in insurance: A review.CrossRef |

Fernandez-Jaramillo AA, Duarte-Galvan C, Contreras-Medina LM, Torres-Pacheco I, Romero-Troncoso RdJ, Guevara-Gonzalez RG, Millan-Almaraz JR (2012) Instrumentation in developing chlorophyll fluorescence biosensing: A review. Sensors 12, 11853–11869.
Instrumentation in developing chlorophyll fluorescence biosensing: A review.CrossRef | 1:CAS:528:DC%2BC38XhtlSjsrjO&md5=e1e75eeec1f8d91dea643cc291727179CAS |

Fitzgerald G, Rodriguez D, O’Leary G (2010) Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index – the canopy chlorophyll content index (CCCI). Field Crops Research 116, 318–324.
Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index – the canopy chlorophyll content index (CCCI).CrossRef |

Flower K, Boruss B, Nansen C, Jones H, Thompson S, Lacoste C, Murphy M (2014) Proof of concept: remote sensing frosted-induced stress in wheat paddocks. Grains Research and Development Corporation, Canberra.

Gamon JA, Peñuelas J, Field CB (1992) A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sensing of Environment 41, 35–44.
A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency.CrossRef |

Ghozlen NB, Cerovic ZG, Germain C, Toutain S, Latouche G (2010) Non-destructive optical monitoring of grape maturation by proximal sensing. Sensors 10, 10040–10068.
Non-destructive optical monitoring of grape maturation by proximal sensing.CrossRef |

Gitelson AA, Keydan GP, Merzlyak MN (2006) Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves. Geophysical Research Letters 33, L11402

Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment 83, 195–213.
Overview of the radiometric and biophysical performance of the MODIS vegetation indices.CrossRef |

Jones HG (2014) ‘Plants and microclimate: a quantitative approach to environmental plant physiology.’ (Cambridge University Press: Cambridge, UK)

Juttner J (2014) Focus on Frost. GRDC Ground Cover. Grains Research and Development Corporation, Canberra.

Kokaly RF, Clark RN (1999) Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression. Remote Sensing of Environment 67, 267–287.
Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression.CrossRef |

Macedo-Cruz A, Pajares G, Santos M, Villegas-Romero I (2011) Digital image sensor-based assessment of the status of oat (Avena sativa L.) crops after frost damage. Sensors 11, 6015–6036.
Digital image sensor-based assessment of the status of oat (Avena sativa L.) crops after frost damage.CrossRef |

Marcellos H, Single W (1984) Frost injury in wheat ears after ear emergence. Functional Plant Biology 11, 7–15.
Frost injury in wheat ears after ear emergence.CrossRef |

Merton RN (1998) Monitoring community hysteresis using spectral shift analysis and the red-edge vegetation stress index. In ‘Seventh Annual JPL Airborne Earth Science Workshop’. NASA Jet Propulsion Laboratory, Pasadena, California, USA, 12–16 January 1998.

Merzlyak MN, Gitelson AA, Chivkunova OB, Rakitin VYU (1999) Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening. Physiologia Plantarum 106, 135–141.
Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening.CrossRef | 1:CAS:528:DyaK1MXktFKks78%3D&md5=cb45fd5a3f4f20ae5f92a448d4db445fCAS |

Peel MC, Finlayson BL, McMahon TA (2007) Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Sciences 11, 1633–1644.
Updated world map of the Köppen-Geiger climate classification.CrossRef |

Penuelas J, Baret F, Filella I (1995) Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance. Photosynthetica 31, 221–230.

Penuelas J, Pinol J, Ogaya R, Filella I (1997) Estimation of plant water concentration by the reflectance water index WI (R900/R970). International Journal of Remote Sensing 18, 2869–2875.
Estimation of plant water concentration by the reflectance water index WI (R900/R970).CrossRef |

Peters AJ, Griffin SC, Vina A, Ji L (2000) Use of remotely sensed data for assessing crop hail damage. Photogrammetric Engineering and Remote Sensing 66, 1349–1355.

Rapacz M, Woźniczka A (2009) A selection tool for freezing tolerance in common wheat using the fast chlorophyll a fluorescence transient. Plant Breeding 128, 227–234.
A selection tool for freezing tolerance in common wheat using the fast chlorophyll a fluorescence transient.CrossRef |

Rapacz M, Sasal M, Gut M (2011) Chlorophyll fluorescence-based studies of frost damage and the tolerance for cold-induced photoinhibition in freezing tolerance analysis of triticale (×Triticosecale Wittmack). Journal of Agronomy & Crop Science 197, 378–389.
Chlorophyll fluorescence-based studies of frost damage and the tolerance for cold-induced photoinhibition in freezing tolerance analysis of triticale (×Triticosecale Wittmack).CrossRef | 1:CAS:528:DC%2BC3MXhtlCgurzL&md5=75128d27b7142e5ecae6cb80b3bef49bCAS |

Rizza F, Pagani D, Stanca AM, Cattivelli L (2001) Use of chlorophyll fluorescence to evaluate the cold acclimation and freezing tolerance of winter and spring oats. Plant Breeding 120, 389–396.
Use of chlorophyll fluorescence to evaluate the cold acclimation and freezing tolerance of winter and spring oats.CrossRef |

Rouse JW, Jr, Haas RH, Schell JA, Deering DW (1974) Monitoring vegetation systems in the Great Plains with ETRS. In ‘Third Earth Resources Technology Satellite-1 Symposium’. 10–14 Dec. 1973. Vol. 1, Technical Presentations, NASA SP-351. (Eds SC Freden, EP Mercanti, MA Becker) (NASA: Washington, DC)

Silleos N, Perakis K, Petsanis G (2002) Assessment of crop damage using space remote sensing and GIS. International Journal of Remote Sensing 23, 417–427.
Assessment of crop damage using space remote sensing and GIS.CrossRef |

VSN International (2011) ‘Genstat for Windows.’ 14th edn. (VSN International: Hemel Hempstead, UK)

Wahlquist A (2012) Researchers probe warming climate frost puzzle. GroundCover, Grains Research and Development Corporation, ACT, Australia.

Wang B, Liu DL, Asseng S, Macadam I, Yu Q (2015) Impact of climate change on wheat flowering time in eastern Australia. Agricultural and Forest Meteorology 209–210, 11–21.
Impact of climate change on wheat flowering time in eastern Australia.CrossRef |

White C, and GRDC and Agriculture Western Australia (2000) ‘Cereals – frost identification: the back pocket guide.’ (Agriculture Western Australia: Perth)

Wu Q, Zhu D, Wang C, Ma Z, Wang J (2012) Diagnosis of freezing stress in wheat seedlings using hyperspectral imaging. Biosystems Engineering 112, 253–260.
Diagnosis of freezing stress in wheat seedlings using hyperspectral imaging.CrossRef |

Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Research 14, 415–421.
A decimal code for the growth stages of cereals.CrossRef |

Zheng B, Chenu K, Fernanda Dreccer M, Chapman SC (2012) Breeding for the future: what are the potential impacts of future frost and heat events on sowing and flowering time requirements for Australian bread wheat (Triticum aestivium) varieties? Global Change Biology 18, 2899–2914.
Breeding for the future: what are the potential impacts of future frost and heat events on sowing and flowering time requirements for Australian bread wheat (Triticum aestivium) varieties?CrossRef |

Zheng B, Chapman SC, Christopher JT, Frederiks TM, Chenu K (2015) Frost trends and their estimated impact on yield in the Australian wheatbelt. Journal of Experimental Botany 66, 3611–3623.
Frost trends and their estimated impact on yield in the Australian wheatbelt.CrossRef | 1:CAS:528:DC%2BC2MXitVCqu7%2FF&md5=0c80b223e3217312600638d1683d1562CAS |


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