Functional Plant Biology Functional Plant Biology Society
Plant function and evolutionary biology
RESEARCH ARTICLE

Development of a diurnal dehydration index for spring barley phenotyping

Pablo Rischbeck A C , Peter Baresel A , Salah Elsayed A B , Bodo Mistele A and Urs Schmidhalter A
+ Author Affiliations
- Author Affiliations

A Deparment of Plant Sciences, Technische Universität München, Emil-Ramann-Str. 2, D-85350 Freising-Weihenstephan, Germany.

B Evaluation of Natural Resources Department, Environmental Studies and Research Institute, Minufiya University, Sadat City, Egypt.

C Corresponding author. Email: pablo.rischbeck@wzw.tum.de

Functional Plant Biology 41(12) 1249-1260 https://doi.org/10.1071/FP14069
Submitted: 28 February 2014  Accepted: 28 May 2014   Published: 31 July 2014

Abstract

Spectral and thermal assessments may enable the precise, high-throughput and low-cost characterisation of traits linked to drought tolerance. However, spectral and thermal measurements of the canopy water status are influenced by the crops’ soil coverage, the size of the biomass and other properties such as the leaf angle distribution. The aim of this study was to develop a referenced spectral method that would be minimally influenced by potentially perturbing factors for retrieving the water status of differing cultivars. Sixteen spring barley cultivars were grown in field trials under imposed drought stress, natural drought stress and irrigated conditions. The relative leaf water content of barley plants declines diurnally from pre-dawn until the afternoon, and other plant traits such as the biomass change little throughout the day. As an indicator of the current drought stress, pre-dawn and afternoon values of the relative leaf water content were assessed spectrally. Diurnal changes in reflectance are only slightly influenced by other perturbing factors. A new spectral index (diurnal dehydration index) was developed by using the wavelengths 730 and 457 nm collected from an active spectrometer. This index allowed the differentiation of the drought tolerance of barley plants. The diurnal dehydration index was significantly related to final biomass, grain yield and harvest index and significantly different between cultivars. Compared with other indices, the diurnal dehydration index offered a higher stability in retrieving the water status of barley plants. Due to its diurnal assessment, the index was barely influenced by the differences in cultivars biomass at the time of measurement. It may represent a valuable tool for assessing the water status or drought tolerance in breeding nurseries.

Additional keywords: abiotic stress, drought tolerance, phenomics, high throughput, precision phenotyping, spectroscopy.


References

Bastiaanssen WGM, Noordman EJM, Pelgrum H, Davids G, Thoreson BP, Allen RG (2005) SEBAL model with remotely sensed data to improve water-resources management under actual field conditions. Journal of Irrigation and Drainage Engineering 131, 85–93.
SEBAL model with remotely sensed data to improve water-resources management under actual field conditions.CrossRef |

Bowman WD (1989) The relationship between leaf water status, gas exchange, and spectral reflectance in cotton leaves. Remote Sensing of Environment 30, 249–255.
The relationship between leaf water status, gas exchange, and spectral reflectance in cotton leaves.CrossRef |

Carter GA (1991) Primary and secondary effects of water content on the spectral reflectance of leaves. American Journal of Botany 78, 916–924.
Primary and secondary effects of water content on the spectral reflectance of leaves.CrossRef |

Ceccato P, Flasse S, Tarantola S, Jacquemoud S, Grégoire JM (2001) Detecting vegetation leaf water content using reflectance in the optical domain. Remote Sensing of Environment 77, 22–33.
Detecting vegetation leaf water content using reflectance in the optical domain.CrossRef |

Ceccato P, Flasse S, Grégoire JM (2002a) Designing a spectral index to estimate vegetation water content from remote sensing data – Part 2. Validation and applications. Remote Sensing of Environment 82, 198–207.
Designing a spectral index to estimate vegetation water content from remote sensing data – Part 2. Validation and applications.CrossRef |

Ceccato P, Gobron N, Flasse S, Pinty B, Tarantola S (2002b) Designing a spectral index to estimate vegetation water content from remote sensing data. Part 1: Theoretical approach. Remote Sensing of Environment 82, 188–197.
Designing a spectral index to estimate vegetation water content from remote sensing data. Part 1: Theoretical approach.CrossRef |

Elsayed S, Mistele B, Schmidhalter U (2011) Can changes in leaf water potential be assessed spectrally? Functional Plant Biology 38, 523–533.

Erdle K, Mistele B, Schmidhalter U (2011) Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars. Field Crops Research 124, 74–84.
Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars.CrossRef |

Federal Biological Research Center for Agriculture and Forestry (2001) Growth stages of mono- and dicotyledonous plants. In ‘BBCH Monograph’. (2nd edn) (Federal Biological Research Centre for Agriculture and Forestry: Berlin and Braunschweig, Germany)

Font L, Körösi F (2005) Optical measuring system for water stress indication of tomato plants. Acta Horticulturae 691, 781–788.

Gao BC (1996) A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment 58, 257–266.
A normalized difference water index for remote sensing of vegetation liquid water from space.CrossRef |

Girma FS, Krieg DR (1992) Osmotic adjustment in sorghum. I: Mechanisms of diurnal osmotic potential changes. Plant Physiology 99, 577–582.
Osmotic adjustment in sorghum. I: Mechanisms of diurnal osmotic potential changes.CrossRef | 1:CAS:528:DyaK38XkvVOjtro%3D&md5=d99e449643d3779b4802b7c258b8344aCAS | 16668925PubMed |

Gutierrez M, Reynolds MP, Klatt AR (2010) Association of water spectral indices with plant and soil water relations in contrasting wheat genotypes. Journal of Experimental Botany 61, 3291–3303.
Association of water spectral indices with plant and soil water relations in contrasting wheat genotypes.CrossRef | 1:CAS:528:DC%2BC3cXptVymsL4%3D&md5=fff3cec98c6b7bfed2113b870144ff2bCAS | 20639342PubMed |

Gutiérrez-Rodriguez M, Reynolds MP, Escalante-Estrada JA, Rodríguez-González MT (2004) Association between canopy reflectance indices and yield and physiological traits in bread wheat under drought and well-irrigated conditions. Australian Journal of Agricultural Research 55, 1139–1147.
Association between canopy reflectance indices and yield and physiological traits in bread wheat under drought and well-irrigated conditions.CrossRef |

Hackl H, Mistele B, Hu Y, Schmidhalter U (2013) Spectral assessment of wheat plants grown in pots and containers under saline conditions. Functional Plant Biology 40, 409–424.
Spectral assessment of wheat plants grown in pots and containers under saline conditions.CrossRef |

Kipp S, Mistele B, Schmidhalter U (2014a) Identification of stay-green and early-senescence phenotypes in high-yielding winter wheat and their relationship to grain yield and grain protein concentration using high-throughput phenotyping techniques. Functional Plant Biology 41, 227–235.
Identification of stay-green and early-senescence phenotypes in high-yielding winter wheat and their relationship to grain yield and grain protein concentration using high-throughput phenotyping techniques.CrossRef | 1:CAS:528:DC%2BC2cXisF2rs7g%3D&md5=3eba7b595080b86d7b2ba7fa149fc04bCAS |

Kipp S, Mistele B, Schmidhalter U (2014b) The performance of active spectral reflectance sensors as influenced by measuring distance, device temperature and light intensity. Computers and Electronics in Agriculture 100, 24–33.
The performance of active spectral reflectance sensors as influenced by measuring distance, device temperature and light intensity.CrossRef |

Liu L, Wang J, Huang W, Zhao C, Zhang B, Tong Q (2004) Estimating winter wheat plant water content using red edge parameters. International Journal of Remote Sensing 25, 3331–3342.
Estimating winter wheat plant water content using red edge parameters.CrossRef |

Millar AA, Jensen RE, Bauer A, Norum EB (1971) Influence of atmospheric and soil environmental parameters on the diurnal fluctuations of leaf water status of barley. Agricultural Meteorology 8, 93–105.
Influence of atmospheric and soil environmental parameters on the diurnal fluctuations of leaf water status of barley.CrossRef |

Mistele B, Elsayed S, Schmidhalter U (2012) Assessing water status in wheat under field conditions using laser-induced chlorophyll fluorescence and hyperspectral measurements. In ‘11th International Conference on Precision Agriculture’. (International Society of Precision Agriculture: Indianapolis, IN USA)

Peñuelas 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 |

Rascher U, Blossfeld S, Fiorani F, Jahnke S, Jansen M, Kuhn AJ, Matsubara S, Märtin LLA, Merchant A, Metzner R, Mueller-Linow M, Nagel KA, Pieruschka R, Pinto F, Schreiber CM, Temperton VM, Thorpe MR, van Dusschoten D, van Volkenburgh E, Windt CW, Schurr U (2011) Non-invasive approaches for phenotyping of enhanced performance traits in beans. Functional Plant Biology 38, 968–983.
Non-invasive approaches for phenotyping of enhanced performance traits in beans.CrossRef | 1:CAS:528:DC%2BC3MXhsFKktLvP&md5=9b7ac43357902700d4cefb01b676ec77CAS |

Römer C, Wahabzada M, Ballvora A, Pinto F, Rossini M, Panigada C, Behmann J, Leon J, Thurau C, Bauckhage C, Kersting K, Rascher U, Plümer L (2012) Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis. Functional Plant Biology 39, 878–890.
Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis.CrossRef |

Schmidhalter U, Burucs Z, Camp KH (1998) Sensitivity of root and leaf water status in maize (Zea mays) subjected to mild soil dryness. Australian Journal of Plant Physiology 25, 307–316.
Sensitivity of root and leaf water status in maize (Zea mays) subjected to mild soil dryness.CrossRef |

Seelig HD, Hoehn A, Stodieck LS, Klaus DM, Adams WW, Emery WJ (2008) The assessment of leaf water content using leaf reflectance ratios in the visible, near-, and short-wave infrared. International Journal of Remote Sensing 29, 3701–3713.
The assessment of leaf water content using leaf reflectance ratios in the visible, near-, and short-wave infrared.CrossRef |

Smart RE, Bingham GE (1974) Rapid estimates of relative water content. Plant Physiology 53, 258–260.
Rapid estimates of relative water content.CrossRef | 1:STN:280:DC%2BC3cnhtVylug%3D%3D&md5=91b0fdbc97e775968c4934d4144ae772CAS | 16658686PubMed |

Van Iersel MW, Oosterhuis DM (1995) Diurnal water relations of expanding and full sized cotton fruits and subtending leaves. Plant, Cell & Environment 18, 807–812.
Diurnal water relations of expanding and full sized cotton fruits and subtending leaves.CrossRef |

Weatherley PE (1950) Studies in the water relations of the cotton plant. New Phytologist 49, 81–97.
Studies in the water relations of the cotton plant.CrossRef |

Weber JA, Ustin SL (1991) Diurnal water relations of walnut trees: implications for remote sensing. IEEE Transactions on Geoscience and Remote Sensing 29, 864–874.
Diurnal water relations of walnut trees: implications for remote sensing.CrossRef |

Winterhalter L, Mistele B, Jampatong S, Schmidhalter U (2011) High throughput phenotyping of canopy water mass and canopy temperature in well-watered and drought stressed tropical maize hybrids in the vegetative stage. European Journal of Agronomy 35, 22–32.
High throughput phenotyping of canopy water mass and canopy temperature in well-watered and drought stressed tropical maize hybrids in the vegetative stage.CrossRef |

Zarco-Tejada PJ, Berni JAJ, Suárez L, Sepulcre-Cantó G, Morales F, Miller JR (2009) Imaging chlorophyll fluorescence with an airborne narrow-band multi-spectral camera for vegetation stress detection. Remote Sensing of Environment 113, 1262–1275.
Imaging chlorophyll fluorescence with an airborne narrow-band multi-spectral camera for vegetation stress detection.CrossRef |

Zimmermann D, Reuss R, Westhoff M, Geer P, Bauer W, Bamberg E, Bentrup FW, Zimmermann U (2008) A novel, non-invasive, online monitoring, versatile and easy plant-based probe for measuring leaf water status. Journal of Experimental Botany 59, 3157–3167.
A novel, non-invasive, online monitoring, versatile and easy plant-based probe for measuring leaf water status.CrossRef | 1:CAS:528:DC%2BD1cXpslalsLk%3D&md5=5be2f87087471cba921bf52131fffcabCAS | 18689442PubMed |



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