Comparative performance of spectral and thermographic properties of plants and physiological traits for phenotyping salinity tolerance of wheat cultivars under simulated field conditions
Yuncai Hu A B , Harald Hackl A and Urs Schmidhalter A
+ Author Affiliations
- Author Affiliations
A Department of Plant Sciences, Technical University of Munich, Emil-Ramann-Str. 2, 85354 Freising, Germany.
B Corresponding author. Email: hu@wzw.tum.de
Functional Plant Biology 44(1) 134-142 https://doi.org/10.1071/FP16217
Submitted: 18 June 2016 Accepted: 23 August 2016 Published: 10 October 2016
Abstract
Successful plant breeding in saline environments requires high-throughput phenotyping techniques to differentiate genotypes for salinity tolerance. This study employed advanced, non-destructive sensing technologies to identify traits contributing to salinity tolerance in wheat (Triticum aestivum L.). Plants were grown in large containers to simulate field conditions for control, salinity stress alone, and combined salinity and drought stress treatments. The comparative performance of spectral reflectance sensing, thermography, digital imaging, and the assessment of physiological traits of two wheat cultivars were tested at booting, anthesis and grain filling. Variation in grain yield between the two cultivars was significant for all treatments (controls, P < 0.01; others, P < 0.001), whereas there were no significant differences in straw DW regardless of treatment. Among the spectral and thermographic assessments, spectral indices were sufficiently sensitive to detect genotypic differences in salinity tolerance among the wheat cultivars after anthesis for the salinity alone and combined treatments. In contrast, physiological traits such as leaf water status and photosynthetic properties demonstrated no differences between the wheat cultivars for either the salinity alone or the combined treatments. These results suggest that spectral sensing has the potential for high-throughput screening of phenotypic traits associated with salinity tolerance of wheat cultivars.
Additional keywords: digital imaging, phenomics, phenotyping, physiological traits, reflectance sensing, salt tolerance, spectral indices, thermography.
References
Babar MA, Reynolds MP, Van Ginkel M, Klatt AR, Raun WR, Stone ML (2006) Spectral reflectance to estimate genetic variation for in-season biomass, leaf chlorophyll, and canopy temperature in wheat. Crop Science 46, 1046–1057.| Spectral reflectance to estimate genetic variation for in-season biomass, leaf chlorophyll, and canopy temperature in wheat.Crossref | GoogleScholarGoogle Scholar |
Babar MA, Van Ginkel M, Reynolds MP, Prasad B, Klatt AR (2007) Heritability, correlated response, and indirect selection involving spectral reflectance indices and grain yield in wheat. Australian Journal of Agricultural Research 58, 432–442.
| Heritability, correlated response, and indirect selection involving spectral reflectance indices and grain yield in wheat.Crossref | GoogleScholarGoogle Scholar |
Blum A, Mayer J, Gozlan G (1982) Infrared thermal sensing of plant canopies as a screening technique for dehydration avoidance in wheat. Field Crops Research 5, 137–146.
| Infrared thermal sensing of plant canopies as a screening technique for dehydration avoidance in wheat.Crossref | GoogleScholarGoogle Scholar |
Bowman BC, Chen J, Zhang J, Wheeler J, Wang Y, Zhao W, Nayak S, Heslot N, Bockelman H, Bonman JM (2015) Evaluating grain yield in spring wheat with canopy spectral reflectance. Crop Science 55, 1881–1890.
| Evaluating grain yield in spring wheat with canopy spectral reflectance.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC28XhsVWgtrvE&md5=bbfa0f5d14b539c4bd557ea30ea25a75CAS |
El-Hendawy SE, Hu YC, Yakout GM, Awad AM, Hafiz SE, Schmidhalter U (2005a) Evaluating salt tolerance of wheat genotypes using multiple parameters. European Journal of Agronomy 22, 243–253.
| Evaluating salt tolerance of wheat genotypes using multiple parameters.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXhtlSkurc%3D&md5=3f2de4ea1f3da018b8cf84a8d8f1c35bCAS |
El-Hendawy SE, Hu YC, Schmidhalter U (2005b) Growth, ion content, gas exchange, and water relations of wheat genotypes differing in salt tolerances. Australian Journal of Agricultural Research 56, 123–134.
| Growth, ion content, gas exchange, and water relations of wheat genotypes differing in salt tolerances.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXhvFykurk%3D&md5=816ad2843f6adc9cf84e10cf7ec839c0CAS |
El-Sayed 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 (2013) Spectral high-throughput assessments of phenotypic differences in biomass and nitrogen partitioning during grain filling of wheat under high yielding Western European conditions. Field Crops Research 141, 16–26.
| Spectral high-throughput assessments of phenotypic differences in biomass and nitrogen partitioning during grain filling of wheat under high yielding Western European conditions.Crossref | GoogleScholarGoogle Scholar |
Fiorani F, Rascher U, Jahnke S, Schurr U (2012) Imaging plants dynamics in heterogenic environments. Current Opinion in Biotechnology 23, 227–235.
| Imaging plants dynamics in heterogenic environments.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XltVKnt7Y%3D&md5=3dd2abc95da7992e1285d3f802677039CAS | 22257752PubMed |
Furbank RT, Tester M (2011) Phenomics – technologies to relieve the phenotyping bottleneck. Trends in Plant Science 16, 635–644.
| Phenomics – technologies to relieve the phenotyping bottleneck.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXhsFOhu7%2FJ&md5=b61a1e3f534159863d82ad6b44ce19fdCAS | 22074787PubMed |
Graeff S, Claupein W (2007) Identification and discrimination of water stress in wheat leaves (Triticum aestivum L.) by means of reflectance measurements. Irrigation Science 26, 61–70.
| Identification and discrimination of water stress in wheat leaves (Triticum aestivum L.) by means of reflectance measurements.Crossref | GoogleScholarGoogle Scholar |
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 | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXptVymsL4%3D&md5=347bc65bbce17c642e0adbdc136e007bCAS | 20639342PubMed |
Hackl H, Baresel JP, Mistele B, Hu Y, Schmidhalter U (2012) A comparison of plant temperatures as measured by thermal imaging and infrared thermometry. Journal Agronomy & Crop Science 198, 415–429.
| A comparison of plant temperatures as measured by thermal imaging and infrared thermometry.Crossref | GoogleScholarGoogle Scholar |
Hackl H, Mistele B, Hu Y, Schmidhalter U (2013) Spectral assessments of wheat plants grown in pots and containers under saline conditions. Functional Plant Biology 40, 409–424.
| Spectral assessments of wheat plants grown in pots and containers under saline conditions.Crossref | GoogleScholarGoogle Scholar |
Hackl H, Hu Y, Schmidhalter U (2014) Establishing reliable growth platforms and stress scenarios to assess the salt tolerance of wheat plants in arid and semi-arid environments. Functional Plant Biology 41, 860–873.
| Establishing reliable growth platforms and stress scenarios to assess the salt tolerance of wheat plants in arid and semi-arid environments.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXhtFyntrzK&md5=1e0350003340769ce53704e374940ab0CAS |
Jackson RD, Huete AR (1991) Interpreting vegetation indexes. Preventive Veterinary Medicine 11, 185–200.
| Interpreting vegetation indexes.Crossref | GoogleScholarGoogle Scholar |
Jones HG (1999) Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces. Plant, Cell & Environment 22, 1043–1055.
| Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces.Crossref | GoogleScholarGoogle Scholar |
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 | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXisF2rs7g%3D&md5=4e9a0f450ad52374d346776af8389adeCAS |
Kipp S, Mistele B, Baresel P, Schmidhalter U (2014b) High-throughput phenotyping early plant vigour of winter wheat. European Journal of Agronomy 52, 271–278.
| High-throughput phenotyping early plant vigour of winter wheat.Crossref | GoogleScholarGoogle Scholar |
Leone AP, Menenti M, Buondonno A, Letizia A, Maffei C, Sorrentino G (2007) A field experiment on spectrometry of crop response to soil salinity. Agricultural Water Management 89, 39–48.
| A field experiment on spectrometry of crop response to soil salinity.Crossref | GoogleScholarGoogle Scholar |
Lopes MS, Reynolds MP (2012) Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology. Journal of Experimental Botany 63, 3789–3798.
| Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XhtVSht7jI&md5=ea34738739d3c02b42ce214fcd56cc43CAS | 22412185PubMed |
Mistele B, Schmidhalter U (2010) Tractor-based quadrilated spectral reflectance measurements to detect biomass and total aerial nitrogen in winter wheat. Agronomy Journal 102, 499–506.
| Tractor-based quadrilated spectral reflectance measurements to detect biomass and total aerial nitrogen in winter wheat.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXltVWquro%3D&md5=d796588443a9d3022543a12d1c5512efCAS |
Munns R, James RA (2003) Screening methods for salinity tolerance: a case study with tetraploid wheat. Plant and Soil 253, 201–218.
| Screening methods for salinity tolerance: a case study with tetraploid wheat.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXltVemsbc%3D&md5=7e726238b806bda9e38e996ba14ece64CAS |
Munns R, Tester M (2008) Mechanisms of salinity tolerance. Annual Review of Plant Biology 59, 651–681.
| Mechanisms of salinity tolerance.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXntFaqtrw%3D&md5=dd68a82a6d2c6414e1266213f98edac3CAS | 18444910PubMed |
Peleman JD, van der Voort JR (2003) Breeding by design. Trends in Plant Science 8, 330–334.
| Breeding by design.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXls1CjtLo%3D&md5=18367e0c7153cf8de68268a1583589bcCAS | 12878017PubMed |
Peñuelas J, Filella I, Biel C, Serrano L, Savé R (1993) The reflectance at the 950–970 nm region as an indicator of plant water status. International Journal of Remote Sensing 14, 1887–1905.
| The reflectance at the 950–970 nm region as an indicator of plant water status.Crossref | GoogleScholarGoogle Scholar |
Peñuelas J, Filella I, Gamon JA (1995) Assessment of photosynthetic radiation-use efficiency with spectral reflectance. New Phytologist 131, 291–296.
| Assessment of photosynthetic radiation-use efficiency with spectral reflectance.Crossref | GoogleScholarGoogle Scholar |
Peñuelas J, Isla R, Filella I, Araus JL (1997) Visible and near-infrared reflectance assessment of salinity effects on barley. Crop Science 37, 198–202.
| Visible and near-infrared reflectance assessment of salinity effects on barley.Crossref | GoogleScholarGoogle Scholar |
Poss JA, Russell WB, Grieve CM (2006) Estimating yields of salt- and water-stressed forages with remote sensing in the visible and near infrared. Journal of Environmental Quality 35, 1060–1071.
| Estimating yields of salt- and water-stressed forages with remote sensing in the visible and near infrared.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28Xns1Cksbc%3D&md5=49a1f99c69685a10e22c5e7c945bed2fCAS | 16738391PubMed |
Powell N, Ji X, Ravash R, Edlington J, Dolferus R (2012) Yield stability for cereals in a changing climate. Functional Plant Biology 39, 539–552.
| Yield stability for cereals in a changing climate.Crossref | GoogleScholarGoogle Scholar |
Prasad B, Carver BF, Stone ML, Babar MA, Raun WR, Klatt AR (2007) Genetic analysis of indirect selection for winter wheat grain yield using spectral reflectance indices. Crop Science 47, 1416–1425.
| Genetic analysis of indirect selection for winter wheat grain yield using spectral reflectance indices.Crossref | GoogleScholarGoogle Scholar |
Rajendran K, Tester M, Roy SJ (2009) Quantifying the three main components of salinity tolerance in cereals. Plant, Cell & Environment 32, 237–249.
| Quantifying the three main components of salinity tolerance in cereals.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXjsVKlsL4%3D&md5=bf1f1a37c3894cfc3b461d309c4b40d4CAS |
Reynolds M, Manes Y, Izanloo A, Langridge P (2009) Phenotyping approaches for physiological breeding and gene discovery in wheat. Annals of Applied Biology 155, 309–320.
| Phenotyping approaches for physiological breeding and gene discovery in wheat.Crossref | GoogleScholarGoogle Scholar |
Rischbeck P, Baresel JP, El-Sayed S, Mistele B, Schmidhalter U (2014) Development of a diurnal dehydration index for spring barley phenotyping. Functional Plant Biology 41, 1249–1260.
| Development of a diurnal dehydration index for spring barley phenotyping.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXhvFKltrbK&md5=c819202fb816a013a2182ed7ac28e2a9CAS |
Rud R, Shoshany M, Alchanatis V (2011) Spectral indicators for salinity effects in crops: a comparison of a new green indigo ratio with existing indices. Remote Sensing Letters 2, 289–298.
| Spectral indicators for salinity effects in crops: a comparison of a new green indigo ratio with existing indices.Crossref | GoogleScholarGoogle Scholar |
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 | GoogleScholarGoogle Scholar |
Sirault XRR, James RA, Furbank RT (2009) A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography. Functional Plant Biology 36, 970–977.
| A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtlOgs7rI&md5=e1ddc0bd079fca8d9a056b6b41c68b74CAS |
Tilman D, Balzer C, Hill J, Befort BL (2011) Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences of the United States of America 108, 20260–20264.
| Global food demand and the sustainable intensification of agriculture.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXhs1yqsbnM&md5=cb16304f14cb2df9b11230252f1e0616CAS | 22106295PubMed |
Walter A, Liebisch F, Hund A (2015) Plant phenotyping: from bean weighing to image analysis. Plant Methods 11, 14
| Plant phenotyping: from bean weighing to image analysis.Crossref | GoogleScholarGoogle Scholar | 25767559PubMed |
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 | GoogleScholarGoogle Scholar |
Yeo AR, Yeo ME, Flowers SA, Flowers TJ (1990) Screening of rice (Oryza sativa L.) genotypes for physiological characters contributing to salinity resistance, and their relationship to overall performance. Theoretical and Applied Genetics 79, 377–384.
| Screening of rice (Oryza sativa L.) genotypes for physiological characters contributing to salinity resistance, and their relationship to overall performance.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC2c7mt1Whug%3D%3D&md5=b55fd772da32967952e08ec886c37ee9CAS | 24226357PubMed |
