Photosynthetica, 2020 (vol. 58), SPECIAL ISSUE
Photosynthetica 2020, 58(2):622-637 | DOI: 10.32615/ps.2020.016
Special issue in honour of Prof. Reto J. Strasser – Phenotyping with fast fluorescence sensors approximates yield component measurements in pepper (Capsicum annuum L.)
- 1 Department of Atomic Physics, Budapest University of Technology and Economics, Budafoki út 8, H-1111 Budapest, Hungary
- 2 Wageningen University & Research, Business Unit Greenhouse Horticulture, PO Box 644, 6700 AP Wageningen, The Netherlands
- 3 INRAE, UR 1052 GAFL Genetics and Breeding of Fruit and Vegetables, F-84143 Montfavet Cedex, France
- 5 Wageningen University & Research, Horticulture and Product Physiology Group, Wageningen, The Netherlands
- 6 Experimental Station of Cajamar Foundation, Paraje Las Palmerillas - El Ejido, Almería, Spain
- 7 Wageningen University and Research, Biometris Applied Statistics, P.O. Box 100, 6700 AA Wageningen, The Netherlands
Molecular breeding, a powerful technique to increase crop yield, tries to predict yield by crop growth models with genotype specific, environment-independent yield components and environmental indices as inputs. A fluorescence-trait-based approach is presented to approximate some costly and time-consuming measurements of yield components. Temporal monitoring of chlorophyll a fluorescence resulted in fluorescence traits with high heritability (0.60-0.82) that could act as proxies for model inputs. Medium-sized Pearson's correlations were calculated between fluorescence traits, light-use efficiency (LUE), and fruit related parameters up to 0.53. Multi-trait quantitative trait locus (QTL) analyses identified genomic regions of pepper (Capsicum annuum L.) involved in the phenotypic variation of the fluorescence traits. Fluorescence QTLs found on linkage groups P6, P7, and P11 corresponded to QTLs for number of fruits, partitioning into fruits, and LUE. Fluorescence parameters within 1 min of the fluorescence response curve can thus be useful to approximate yield component traits.
Keywords: complex trait; genotypic heritability; intelligent fluorosensor; plant phenotyping.
Received: August 30, 2019; Revised: February 4, 2020; Accepted: February 13, 2020; Prepublished online: April 4, 2020; Published: April 7, 2020Show citation
ACS | AIP | APA | ASA | Harvard | Chicago | IEEE | ISO690 | MLA | NLM | Turabian | Vancouver |
References
- Alimi N.A., Bink M.C.A.M., Dieleman J.A. et al.: Genetic and QTL analyses of yield and a set of physiological traits in pepper. -Euphytica 190: 181-201, 2013a. Go to original source...
- Alimi N.A. Bink M.C.A.M., Dieleman J.A. et al.: Multi-trait and multi-environment QTL analyses of yield and a set of physiological traits in pepper. - Theor. Appl. Genet. 126: 2597-2625, 2013b. Go to original source...
- Bąba W., Kompała-Bąba A., Zabochnicka-Świątek M. et al.: Discovering trends in photosynthesis using modern analytical tools: More than 100 reasons to use chlorophyll fluorescence. -Photosynthetica 57: 668-679, 2019. Go to original source...
- Baker N.R.: Chlorophyll fluorescence: a probe of photosynthesis in vivo. - Annu. Rev. Plant Biol. 59: 89-113, 2008. Go to original source...
- Baker N.R., Rosenquist E.: Applications of chlorophyll fluores-cence can improve crop production strategies: an examination of future possibilities. - J. Exp. Bot. 55: 1607-1621, 2004. Go to original source...
- Barbagallo R.P., Oxborough K., Pallett K.E., Baker N.R.: Rapid noninvasive screening for perturbations of metabolism and plant growth using chlorophyll fluorescence imaging. - Plant Physiol. 132: 485-493, 2003. Go to original source...
- Barchi L., Bonnet J., Boudet C. et al.: A high-resolution, intraspecific linkage map of pepper (Capsicum annuum L.) and selection of reduced recombinant inbred line subsets for fast mapping. - Genome 50: 51-60, 2007. Go to original source...
- Barócsi A.: Intelligent, net or wireless enabled fluorosensors for mass monitoring of assorted crops. - Meas. Sci. Technol. 24: 025701, 2013. Go to original source...
- Barócsi A., Csintalan Z., Kocsányi L. et al.: Optimizing phyto-remediation of heavy metal-contaminated soil by exploiting plants' stress adaptation. - Int. J. Phytoremediat. 5: 13-23, 2003.
- Barócsi A., Kocsányi L., Várkonyi S. et al.: Two-wavelength, multipurpose, truly portable chlorophyll fluorometer and its application in field monitoring of phytoremediation. - Meas. Sci. Technol. 11: 717-729, 2000. Go to original source...
- Bertin N., Martre P., Génard M. et al.: Under what circumstances can process-based simulation models link genotype to phenotype for complex traits? Case study of fruit and grain quality traits. - J. Exp. Bot. 614: 955-967, 2010. Go to original source...
- Boer M.P., Wright D., Feng L. et al.: A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize. - Genetics 177: 1801-1813, 2007.
- Bonnet J., Danan S., Boudet C. et al.: Are the polygenic architectures of resistance to Phytophthora capsici and P. parasitica independent in pepper? - Theor. Appl. Genet. 115: 253-264, 2007. Go to original source...
- Boote K.J., Kropff M.J., Bindraban P.S.: Physiology and modelling of traits in crop plants: implications for genetic improvement. - Agr. Syst. 70: 395-420, 2001. Go to original source...
- Boureima S., Oukarroum A., Diouf M. et al.: Screening for drought tolerance in mutant germplasm of sesame (Sesamum indicum) probing by chlorophyll a fluorescence. - Environ. Exp. Bot. 81: 37-43, 2012. Go to original source...
- Bürling K., Cerovic Z.G., Cornic G. et al.: Fluorescence-based sensing of drought-induced stress in the vegetative phase of four contrasting wheat genotypes. - Environ. Exp. Bot. 89: 51-59, 2013. Go to original source...
- Buschmann C.: Variability and application of the chlorophyll fluorescence emission ratio red/far-red of leaves. - Photosynth. Res. 92: 261-271, 2007. Go to original source...
- Bustos-Korts D., Malosetti M., Chapman S., van Eeuwijk F.: Modelling of genotype by environment interaction and prediction of complex traits across multiple environments as a synthesis of crop growth modelling, genetics and statistics. -In: Yin X., Struik P.C. (ed.): Crop Systems Biology. Pp. 55-82. Springer, Cham 2016. Go to original source...
- Cerovic Z.G., Masdoumier G., Ghozlen N.B., Latouche G.: A new optical leaf-clip meter for simultaneous non-destructive assessment of leaf chlorophyll and epidermal flavonoids. - Physiol. Plantarum 146: 251-260, 2012. Go to original source...
- Chaerle L., Lenk S., Hagenbeek D. et al.: Multicolor fluorescence imaging for early detection of the hypersensitive reaction to tobacco mosaic virus. - Plant Physiol. 164: 253-262, 2007. Go to original source...
- Chenu K., Chapman S.C., Tardieu F. et al.: Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach. - Genetics 183: 1507-1523, 2009. Go to original source...
- Cottee N.S., Bange M.P., Wilson I.W., Tan D.K.Y.: Developing controlled environment screening for high-temperature tolerance in cotton that accurately reflects performance in the field. - Funct. Plant Biol. 39: 670-678, 2012. Go to original source...
- Czyczyło-Mysza I., Tyrka M., Marcińska I. et al.: Quantitative trait loci for leaf chlorophyll fluorescence parameters, chlorophyll and carotenoid contents in relation to biomass and yield in bread wheat and their chromosome deletion bin assignments. - Mol. Breeding 32: 189-210, 2013. Go to original source...
- Flood P.J., Kruijer W., Schnabel S.K. et al.: Phenomics for photosynthesis, growth and reflectance in Arabidopsis thaliana reveals circadian and long-term fluctuations in heritability. - Plant Methods 12: 14, 2016. Go to original source...
- Furbank R.T.: Plant phenomics: from gene to form and function. -Funct. Plant Biol. 36: V-VI, 2009.
- Furbank R.T., Tester M.: Phenomics - technologies to relieve the phenotyping bottleneck. - Trends Plant Sci. 16: 635-644, 2011. Go to original source...
- Georgieva K., Lenk S., Buschmann C.: Responses of the resurrection plant Haberlea rhodopensis to high irradiance. - Photosynthetica 46: 208-215, 2008. Go to original source...
- Harbinson J., Prinzenberg A.E., Kruijer W., Aarts M.G.M.: High throughput screening with chlorophyll fluorescence imaging and its use in crop improvement. - Curr. Opin. Biotech. 23: 221-226, 2012. Go to original source...
- Huot Y., Babin M.: Overview of fluorescence protocols: theory, basic concepts and practice. - In: Suggett D., Prášil O., Borowitzka M. (ed.): Chlorophyll a Fluorescence in Aquatic Sciences: Methods and Applications. Developments in Applied Phycology. Pp. 31-74. Springer, Dordrecht 2010. Go to original source...
- Kalaji H.M., Rastogi A., Živčák M. et al.: Prompt chlorophyll fluorescence as a tool for crop phenotyping: an example of barley landraces exposed to various abiotic stress factors. - Photosynthetica 56: 953-961, 2018. Go to original source...
- Kautz B., Noga G., Hunsche M.: Sensing drought- and salinity-imposed stresses on tomato leaves by means of fluorescence techniques. - Plant Growth Regul. 73: 279-288, 2014. Go to original source...
- Keränen M., Aro E.-M., Tyystjärvi E., Nevalainen O.: Auto-matic plant identification with chlorophyll fluorescence fingerprinting. - Precis. Agric. 4: 53-67, 2003. Go to original source...
- Kim K.-S., Giacomelii G.A., Sase S. et al.: Optimization of growth environment in a plant production facility using a chlorophyll fluorescence method. - JARQ-Jpn. Agr. Res. Q. 40: 149-156, 2006. Go to original source...
- Kolukisaoglu Ü., Thurow K.: Future and frontiers of automated screening in plant sciences. - Plant Sci. 178: 476-484, 2010. Go to original source...
- Kuijken R.C.P, van Eeuwijk F.A., Marcelis L.F.M., Bouwmeester H.J.: Root phenotyping: from component trait in the lab to breeding. - J. Exp. Bot. 66: 5389-5401, 2015. Go to original source...
- Mahlein A.-K., Steiner U., Hillnhütter C. et al.: Hyperspectral imaging for small-scale analysis of symptoms caused by different sugar beet diseases. - Plant Methods 8: 3, 2012. Go to original source...
- Marcelis L.F.M., Elings A., Bakker M.J. et al.: Modelling dry matter production and partitioning in sweet pepper. - Acta Hortic. 718: 121-128, 2006. Go to original source...
- Marcelis L.F.M., Heuvelink E., Goudriaan J.: Modelling biomass production and yield of horticultural crops: a review - Sci. Hortic.-Amsterdam 74: 83-111, 1998.
- Marcial L., Sarrafi A.: Genetic analysis of some chlorophyll fluorescence and productivity parameters in barley Hordeum vulgare. - Plant Breeding 115: 339-342, 1996. Go to original source...
- Maxwell K., Johnson G.N.: Chlorophyll fluorescence - a practical guide. - J. Exp. Bot. 51: 659-668, 2000. Go to original source...
- McAusland L., Atkinson J.A., Lawson T., Murchie E.H.: High throughput procedure utilising chlorophyll fluorescence imaging to phenotype dynamic photosynthesis and photo-protection in leaves under controlled gaseous conditions. - Plant Methods 15: 109, 2019. Go to original source...
- Miloslavina Y., Wehner A., Lambrev P.H. et al.: Far-red fluores-cence: A direct spectroscopic marker for LHCII oligomer formation in non-photochemical quenching. - FEBS Lett. 582: 3625-3631, 2008. Go to original source...
- Mishra A., Matouš K., Mishra K.B., Nedbal L.: Towards discrimi-nation of plant species by machine vision: Advanced statistical analysis of chlorophyll fluorescence transients. - J. Fluoresc. 19: 905-913, 2009. Go to original source...
- Montes J.M., Melchinger A.E., Reif J.C.: Novel throughput phenotyping platforms in plant genetic studies. - Trends Plant Sci. 12: 433-436, 2007. Go to original source...
- Murchie E.H., Lawson T.: Chlorophyll fluorescence analysis: a guide to good practice and understanding some new applications. - J. Exp. Bot. 64: 3983-3998, 2013. Go to original source...
- Noga A., Warchoł M., Czyczyło-Mysza I. et al.: Chlorophyll a fluorescence parameters in the evaluation of oat DH lines yield components. - Cereal Res. Commun. 45: 665-674, 2017. Go to original source...
- Oakey H., Verbyla A., Pitchford W. et al.: Joint modeling of additive and non-additive genetic line effects in single field trials. - Theor. Appl. Genet. 113: 809-819, 2006. Go to original source...
- Oxborough K., Baker N.R.: Resolving chlorophyll a fluorescence images of photosynthetic efficiency into photochemical and non-photochemical components - calculation of qP and Fv'/Fm' without measuring FO'. - Photosynth. Res. 54: 135-142, 1997. Go to original source...
- Palombi L., Cecchi G., Lognoli D. et al.: A retrieval algorithm to evaluate the Photosystem I and Photosystem II spectral contributions to leaf chlorophyll fluorescence at physiological temperatures. - Photosynth. Res. 108: 225-239, 2011. Go to original source...
- Pedrós R., Goulas Y., Jacquemond S. et al.: FluorMODleaf: A new leaf fluorescence emission model based on the PROSPECT model. - Remote Sens. Environ. 114: 155-167, 2010. Go to original source...
- Pfündel E.: Estimating the contribution of Photosystem I to total leaf chlorophyll fluorescence. - Photosynth. Res. 56: 185-195, 1998. Go to original source...
- Poormohammad Kiani S., Maury P., Sarrafi A., Grieu P.: QTL analysis of chlorophyll fluorescence parameters in sunflower (Helianthus annuus L.) under well-watered and water-stressed conditions. - Plant Sci. 175: 565-573, 2008. Go to original source...
- Prinzenberg A.E., Víquez-Zamora M., Harbinson J. et al.: Chlorophyll fluorescence imaging reveals genetic variation and loci for a photosynthetic trait in diploid potato. - Physiol. Plantarum 164: 163-175, 2018. Go to original source...
- Richards R.A., Rebetzke G.J., Condon A.G., van Herwaarden A.F.: Breeding opportunities for increasing the efficiency of water use and crop yield in temperate cereals. - Crop Sci. 42: 111-121, 2002. Go to original source...
- Rousseau C., Belin E., Bove E. et al.: High throughput quantitative phenotyping of plant resistance using chlorophyll fluorescence image analysis. - Plant Methods 9: 17, 2013. Go to original source...
- Ruts T., Matsubara S., Walter A.: Synchronous high-resolution phenotyping of leaf and root growth in Nicotiana tabacum over 24-h periods with GROWMAP-plant. - Plant Methods 9: 2, 2013. Go to original source...
- Schreiber U., Klughammer C., Kolbowski J.: Assessment of wavelength-dependent parameters of photosynthetic electron transport with a new type of multi-color PAM chlorophyll fluorometer. - Photosynth. Res. 113: 127-144, 2012. Go to original source...
- Sharma D.K., Andersen S.B., Ottosen C.-O., Rosenqvist E.: Phenotyping of wheat cultivars for heat tolerance using chlorophyll a fluorescence. - Funct. Plant Biol. 39: 936-947, 2012. Go to original source...
- Shibu M.E., Leffelaar P.A., van Keulen H., Aggarwal P.K.: LINTUL3, a simulation model for nitrogen-limited situations: Application to rice. - Eur. J. Agron. 32: 255-271, 2010. Go to original source...
- Solti Á., Lenk S., Mihailova G. et al.: Effects of habitat light conditions on the excitation quenching pathways in desiccating Haberlea rhodopensis leaves: An Intelligent FluoroSensor study. - J. Photoch. Photobio. B 130: 217-225, 2014. Go to original source...
- Song Y., Glasbey C.A., Horgan G.W. et al.: Automatic fruit recognition and counting from multiple images. - Biosyst. Eng. 118: 203-215, 2014. Go to original source...
- Stirbet A., Lazár D., Kromdijk J., Govindjee: Chlorophyll a fluorescence induction: Can just a one-second measurement be used to quantify abiotic stress responses? - Photosynthetica 56: 86-104, 2018. Go to original source...
- Strasser R.J., Srivastava A., Govindjee: Polyphasic chlorophyll a fluorescence transient in plants and cyanobacteria. - Photochem. Photobiol. 61: 32-42, 1995. Go to original source...
- Strasser R.J., Srivastava A., Tsimilli-Michael M.: The fluores-cence transient as a tool to characterize and screen photosyn-thetic samples. - In: Yunus M., Pathre U., Mohanty P. (ed.): Probing Photosynthesis: Mechanisms, Regulation and Adaptation. Pp. 445-483. Taylor & Francis, London 2000.
- Strigens A., Freitag N.M., Gilbert X. et al.: Association mapping for chilling tolerance in elite flint and dent maize inbred lines evaluated in growth chamber and field experiments. - Plant Cell Environ. 36: 1871-1887, 2013.
- Thoren D., Schmidhalter U.: Nitrogen status and biomass determination of oilseed rape by laser-induced chlorophyll fluorescence. - Eur. J. Agron. 30: 238-242, 2009. Go to original source...
- Tyystjärvi E., Koski A., Keränen M., Nevalainen O.: The Kautsky curve is a built-in barcode. - Biophys. J. 77: 1159-1167, 1999. Go to original source...
- Tyystjärvi E., Nørremark M., Mattila H. et al.: Automatic identification of crop and weed species with chlorophyll fluorescence induction curves. - Precis. Agric.12: 546-563, 2011. Go to original source...
- van der Heijden G., Song Y., Horgan G. et al.: SPICY: towards automated phenotyping of large pepper plants in the greenhouse. - Funct. Plant Biol. 39: 870-877, 2012. Go to original source...
- van Eeuwijk F.A, Bink M.C.A.M., Chenu K., Chapman S.C.: Detection and use of QTL for complex traits in multiple environments. - Curr. Opin. Plant Biol. 13: 193-205, 2010. Go to original source...
- van Eeuwijk F.A., Bustos-Korts D.V., Malosetti M.: What should students in plant breeding know about the statistical aspects of genotype × environment interactions? - Crop Sci. 56: 2119-2140, 2016. Go to original source...
- van Ittersum M.K., Leffelaar P.A., van Keulen H. et al.: On approaches and applications of the Wageningen crop models. - Eur. J. Agron. 18: 201-234, 2003. Go to original source...
- van Rooijen R., Kruijer W., Boesten R. et al.: Natural variation of YELLOW SEEDLING1 affects photosynthetic acclimation of Arabidopsis thaliana. - Nat. Commun. 81: 1421, 2017. Go to original source...
- Voorrips R.E., Palloix A., Dieleman J.A. et al.: Crop growth models for the -omics era: the EU-SPICY project. - In: Prohens J., Rodríguez-Burruezo A. (ed.): Advances in Genetics and Breeding of Capsicum and Eggplant: Proceedings of the XIVth EUCARPIA Meeting on Genetics and Breeding of Capsicum and Eggplant. Pp. 315-321. Editorial Universidad Politécnica de Valencia, Valencia 2010.
- Yin X., Struik P.C., Kropff M.J.: Role of crop physiology in predicting gene-to-phenotype relationships. - Trends Plant Sci. 9: 426-432, 2004. Go to original source...
- Yin X., Struik P.C., van Eeuwijk F.A. et al.: QTL analysis and QTL-based prediction of flowering phenology in recombinant inbred lines of barley. - J. Exp. Bot. 56: 967-976, 2005. Go to original source...
- Zunzunegui M., Díaz Barradas M.C., Ain-Lhout F. et al.: To live or to survive in Doñana dunes: Adaptive responses of woody species under a Mediterranean climate. - Plant Soil 273: 77-89, 2005. Go to original source...
- Zunzunegui M., Díaz Barradas M.C., Ain-Lhout F. et al.: Seasonal physiological plasticity and recovery capacity after summer stress in Mediterranean scrub communities. - Plant Ecol. 212: 127-142, 2011. Go to original source...