InTechOpen uses cookies to offer you the best online experience. By continuing to use our site, you agree to our Privacy Policy.

Agricultural and Biological Sciences » "Applied Photosynthesis - New Progress", book edited by Mohammad Mahdi Najafpour, ISBN 978-953-51-2267-8, Published: March 30, 2016 under CC BY 3.0 license. © The Author(s).

Chapter 1

Monitoring Photosynthesis by In Vivo Chlorophyll Fluorescence: Application to High-Throughput Plant Phenotyping

By Jorge Marques da Silva
DOI: 10.5772/62391

Article top

Monitoring Photosynthesis by In Vivo Chlorophyll Fluorescence: Application to High-Throughput Plant Phenotyping

Jorge Marques da Silva
Show details


In spite of the decrease in the rate of population growth, world population is expected to rise from the current figure (slightly above to 7.2 billion) to reach 9.6 billion in 2050. There is therefore a pressing need to increase food production. Since most of the best arable lands are already under production, expanding the agricultural areas would have negative impacts on important natural areas. Thereby, increasing the productivity of the current agricultural areas is the chief objective of agronomical planners, and planting more productive and better adapted plant varieties is crucial to achieve it. In fact, plant breeding is at the forefront of concern of both agronomists and plant biologists. Plant breeding is a millenary activity that deeply changed our world. However, the use of molecular biology techniques jointly with informatics capabilities—giving rise to the omics techniques—deeply accelerated plant breeding, providing new and better plant varieties at an increased pace. The advances in genomics, though, far by-passed the advances in phenomics, and so there is a rising consensus among plant breeders that plant phenotyping is a bottleneck to advancing plant breeding. Therefore, a range of international initiatives in high-throughput plant phenotyping (HTPP) are at course, and new automated equipment is being developed. Phenotyping plants, however, is not a simple matter. To begin with, it has to be decided which parameters to measure in order to extrapolate to the desired goals, plant resistance and plant productivity. For this, as well as for plant breeding, an in-depth knowledge of plant physiology is required. Photosynthesis has been considered as a good indicator of overall plant performance. It is the only energy input in plants and thereby impacts all aspects of plant metabolism and physiology. The cumulative rate of photosynthesis over the growing season is the primary determinant of crop biomass. It largely determines the redox state of plant cells, and therefore, it is at the core of regulatory networks. Therefore, assessing photosynthesis and the photosynthetic apparatus plays a core role on plant phenotyping. Nevertheless, high-throughput phenotyping demands very rapid measurements, and consequently the most common method of photosynthesis measurement—the infra-red gas analysis—is not well suited for this purpose. On the contrary, the techniques based on in vivo chlorophyll (Chl) a fluorescence measurements are perfectly fit. In this chapter, an historical perspective on the development of in vivo Chl a measurement is briefly addressed. Then, the state of the art of the fluorescence-based techniques of photosynthesis assessment is presented, and their potential use in HTPP is evaluated. Finally, the current use of these techniques in the main systems of phenotyping is surveyed.

Keywords: photosynthesis, photochemistry, chlorophyll fluorescence, optical techniques, plant phenomics, high-throughput plant phenotyping

1. Introduction: Food security, plant breeding, and high-throughput plant phenotyping

Albeit the rate on population rise is slowing down, world population is still increasing; from the current figure slightly above 7.2 billion, it is expected to reach 9.6 billion by 2050 [1]. Therefore, there is a pressing need to increase the global food production ([2] and references therein). Mostly, the population increase is expected to occur in developing countries ([3] and references therein), where the current productivity of farms is far below the one in the developed world. For instance, in India, where the population is expected to surpass China’s, the current productivity of wheat farming is only one third than that of France, while rice productivity accounts for less than half of China’s [4]. Increasing food production and ensuring availability of safe and nutritious food at affordable prices to the population of developing countries are, therefore, a pressing urgency. As most of the best arable lands are already under production, expanding the agricultural areas would have negative impacts on important natural areas. Thereby, increasing the productivity of the current agricultural areas is the chief objective [5], which requires more productive and better adapted plant varieties [6]. There is a long tradition of conventional plant breeding that deeply changed our world [7]. Moreover, being a cost-effective tool for increasing nutritional value of forage and crops, plant breeding still can contribute to global food security [4]. Therefore, it is at the forefront of concern of both agronomists and plant biologists. The use of molecular biology techniques jointly with informatics capabilities—giving rise to the omics techniques—deeply accelerated plant breeding, providing better plant varieties at an increased pace [8]. In fact, during the past 20 years, molecular profiling and classical sequencing technologies enabled significant advances toward the large-scale characterization of plant genomes [9], yielding valuable tools for plant breeding such as marker-assisted selection [10]. However, integrating approaches across all scales, from molecular to field applications, are necessary to develop sustainable plant production with higher yield. Regrettably, the advances in genomics far by-passed the advances in phenomics, and therefore, there is a rising consensus among plant biologists that plant phenotyping is a bottleneck to advancing both fundamental research and plant breeding [11]. Therefore, a range of international initiatives in high-throughput plant phenotyping (HTPP) are at course, and new automated equipment is being developed [12]. Plant phenotyping is “the application of a set of methodologies and protocols used to measure plant growth, architecture, and composition with a certain accuracy and precision at different scales of organization, from organs to canopies” [11]. Phenotyping, being a paradigm of the interdisciplinary character of modern plant physiology [13], is not a simple matter. To begin with, it has to be decided which parameters to measure to extrapolate to the desired plant traits (resistance and productivity). That is, researchers need sound and robust knowledge about the traits that are indicative of the intended performance. Here, mechanistic understanding of plant physiology plays a role in identifying useful parameters and proxies to measure [11]. In any case, it seems plausible that effective HTPP platforms will involve the measurement of multiple parameters. Two classes of parameters are of major importance: structural parameters and photosynthetic parameters. The structure of both the shoots [14] and the roots has been primarily phenotyped using a broad range of cameras sensitive in the visible spectral range. Conversely, photosynthetic activity has been phenotyped mainly by using in vivo chlorophyll (Chl) fluorescence techniques.

2. Photosynthesis: a proxy of plant performance

An in-depth knowledge of plant physiology is required for successful plant breeding [15], as most of plant stresses are under the control of complex traits [16]. In particular, as accumulating data did not fit into conventional theories, it becomes clear that metabolic engineering is in need of a better understanding of metabolic regulation and plasticity [8]. Photosynthesis has been considered as a good indicator of overall plant performance. It is the only significant energy input in plants and thereby impacts all aspects of plant metabolism and physiology. The cumulative rate of photosynthesis over the growing season is the primary determinant of crop biomass [17]. Photosynthesis largely determines the redox state of plant cells and therefore is at the core of regulatory networks [18]. Therefore, assessing photosynthesis and the photosynthetic apparatus plays a core role on plant phenotyping. Nevertheless, high-throughput phenotyping demands very rapid measurements, and consequently, the most common methods of photosynthesis measurement—the infra-red gas analysis and the polarographic measurement of oxygen evolution—are not well suited for this purpose. On the contrary, optical methods present considerable advantages for in vivo and in vitro assessment of the physiological condition of live tissues, as compared to chemical and physicochemical methods, because they are much faster, non-invasive, and non-destructive (e.g. [19, 20]). Among these, in vivo Chl fluorescence measurements are best suited for this purpose. Albeit the use of optical methods in plant phenotyping has been recently reviewed [21], to our knowledge, a review specifically addressing the use of Chl fluorescence techniques in HTPP is missing in the literature. In the following sections, an historical perspective on the development of in vivo Chl fluorescence measurement, from the seminal work of Kautsky and Hirsch [22] to the ground-breaking invention of pulse amplitude modulation (PAM) [23], is briefly addressed. Then, the current state of the art of the Chl fluorescence measurement techniques is presented, and their potential use in HTPP is evaluated.

3. Chlorophyll fluorescence

The emission of photons from excited molecules was named fluorescence by the Irish physicist George Gabriel Stokes [24], after fluorspar or fluoride, the mineral from calcium fluorite where he studied the phenomenon. When a molecule of Chl a from the antenna complex of a photosynthetic organism is hit by a photon, it absorbs its energy and an electron is raised to a higher energy level S1 (singlet 1, corresponding to the absorption of one red photon) or S3 (singlet 3, corresponding to the absorption of one blue photon; Figure 1).

media/Figure 1.png

Figure 1.

Simplified diagram of the energy levels of the singlet excitation states of chlorophyll a molecules. Source: Adapted from Ref. [25].

The excited molecule is very unstable, and its excess energy is promptly released. There are three different competing ways of de-excitation: (1) heat dissipation; (2) photochemical utilization of energy; and (3) fluorescence emission. The relative contribution of each process is dependent on the physiological status of the photosynthetic systems [25]. In the last few decades, the measurement of Chl fluorescence has become a universal technique in the study of virtually all types of photosynthetic entities, including fruits [2628], corals [29], seagrasses [30], macroalgae [31], microphytobenthos [3234], and many types of higher plants, such as tobacco [35], maize [36], and tomato [37]. The use of Chl fluorescence has been recently proposed for detecting early responses to abiotic and biotic stresses, before a decline in growth can be observed [3840]. Likewise, there are numerous applications of Chl fluorescence in the horticultural sectors (reviewed in [41]). With the advent of different instrumental techniques, Chl fluorometry developed into various types, with different timescales of signal capturing [42]. It is useful, however, to divide the currently available techniques for in vivo Chl fluorescence measurements into passive and active [43]. While passive techniques measure fluorescence emission under actinic light, active techniques stimulate fluorescence emission using dedicated light sources.

3.1. Passive fluorescence

Albeit it has been known for a long time that Chl, like many other molecules, emits fluorescence after excitation, it was not until 1931 that Kautsky and Hirsch observed that the in vivo emission of fluorescence during a dark–light transition showed a typical variation [22], usually known as the Kautsky induction curve or simply Kautsky effect. Even though these authors have speculated on a possible relation between the observed fluorescence emission and carbon fixation, the molecular basis of photosynthesis was, at the time, poorly understood,1 and therefore, their observations did not significantly impact photosynthesis research. As the understanding of the molecular mechanisms progressed, however, prototypes of continuous fluorescence recording fluorometers were built and used in photosynthesis research [45]. These simple devices had limited use in stress physiology, but Lichtenthaler and Rinderle [46] developed the Vitality Index (Rfd = Fv′/(FmFv′)) and successfully used it to detect low temperature stress in higher plants. However, continuous fluorescence recording fluorometers acquired increase potential in photosynthesis research only when equipped with high-time resolution capacities. This allowed to explore the kinetics of the fast phase of fluorescence signal rise in a dark–light transition. Although the exploration of these signals begun earlier with experimental prototypes, it was the commercial availability of the Plant Efficiency Analyzer by the UK-based manufacturer Hansatech that made this technique widely available to plant physiologists and plant breeders. In Switzerland, Reto Strasser provided the theoretical basis for the interpretation of these signals [47]. His group at the University of Genève have developed the JIP test (termed after the main inflections in the fast fluorescence rise, called J, I, and P) to analyze the photosystem II (PS II) behavior [48] (Figure 2).

media/Figure 2.png

Figure 2.

Chlorophyll fluorescence induction curve (OJIP transient).

Based on the Chl a fast fluorescence transient measurement [49], numerous indexes and parameters quantifying the energy flow related to the different phases in the PS II photochemical reactions can be calculated. The JIP transient rise reflects the successive but overlapping reduction of the electron acceptor pool of PS II [50] and can be used to obtain information on the redox state of the photosynthetic electron transport chain, on the stoichiometry of its components and on the relative PS II antenna size [51]. This transient has been found to be very sensitive to stress caused by changes in different biotic and abiotic conditions, presenting alterations even before visible symptoms could be detected on the plants [5257]. Albeit some information may be obtained from the application of the JIP test to pre-illuminated leaves, the most used protocols require a dark-adaptation period [58]. This may be achieved for many leaves simultaneously by using the leaf clips provided by the manufacturer Hansatech. Individual measurements are rapid as usually a 1-second light (saturating) pulse is applied, and the kinetics of fluorescence rise is immediately recorded. Therefore, the main hindrance to the use of the JIP test on high-throughput automated plant phenotyping is the need to previously dark-adapt the samples (Table 1). Albeit this technique has been proved useful in manual low-throughput plant phenotyping [57, 59], none of the commercial phenotyping platforms makes use of it. It is possible to envisage, however, a system where whole plants would be pre-adapted for dark conditions, and non-contact measurements of the fluorescence induction curve would be made. In fact, imaging of the JIP parameters is already possible and has been used to screen wild barley genotypes under heat stress [60]. Passive fluorescence spectra of leaves may also be obtained and provide information on the status of the photosynthetic apparatus [61]. However, fluorescence emission spectra have been studied mainly with active fluorescence techniques, mostly with laser-induced fluorescence (LIF) [62] which is discussed in the next section.

3.2. Active fluorescence

3.2.1. Laser-induced fluorescence

Since LIF measurements can be carried out remotely, allowing, for example, to inspect difficult-to-access canopies, this technique is particularly interesting for HTPP in the field. In fact, large crop areas can be efficiently surveyed by scanning an instrument placed at a high viewpoint or by mounting it in an airplane or a drone [63]. LIF was applied for estimating the overall metabolic activity of plants during a defined period of time [64, 65]; differentiating plant species [6668]; assessing potassium deficiency [69]; estimating the maturity of lettuce [70]; detecting mildew and rust fungal [71] and bacterial [72] infections; and studying the influence of water stress [73, 74], ambient light [68], UV radiation [75], atmospheric [76], and soil pollutants [76, 77] and excess of ammonium nitrate [78] and nickel [79] on plant physiology. In addition, LIF has been used to assess the productive biomass of benthic diatoms [62, 80] and to differentiate between groups of macroalgae [81]. LIF spectra of plant leaves present a local Chl emission maximum in the red region of the spectrum at 685 nm (F685) and an absolute maximum at the far-red region, circa 740 nm (F740) [65, 75]. The relative intensity, shape, and wavelength of these peaks are dependent on the physiological status of the photosynthetic apparatus. Changes in the Fr/Ffr ratio were suggested to be well correlated to Chl a concentration [69, 82, 83], which is altered, in most plant species by stress [84]. In addition to changes in the Chl concentration, other factors, related to membrane lipid composition and protein environment [85] as well as leaf ultrastructure and the accumulation of specific light absorbing metabolites, such as anthocyanins, are likely to affect Fr/Ffr ratios. It is known that water stress significantly impacts leaf lipid composition of thylakoid membranes, causing a decrease in the contents of polar lipids, namely chloroplast-specific glycolipids as well as changes in their fatty acid composition, likely to affect membrane fluidity [86]. In forest species subjected to severe drought, Lavrov and coworkers [73] showed that the red/far-red emission fluorescence ratio (Fr/Ffr) is very well correlated with the maximum potential photochemical efficiency of PS II estimated with a Plant Efficiency Analyzer (Hansatech, U.K.). Also, simultaneous measurement of Chl fluorescence in maize (Zea mays), sugar beet (Beta vulgaris), and kalanchoë (Kalanchoë sp.) by LIF and PAM indicated that the steady state of fluorescence is useful for water stress detection [87]. Albeit LIF has been extensively used in applied research, its possibilities have not been thoroughly explored in fundamental research. In fact, even though Arabidopsis thaliana had become the main model organism in plant biology, applications of LIF to this species are almost absent, the exceptions being a study on npq mutants, altered in the expression of the PS II PsbS protein [88] and, more recently, a study on the water stress effect on photosynthesis [74]. Advanced variations of this technique as is the case of laser-induced fluorescence transients (LIFT) allow the calculation of quantum efficiency [89], leading values in line with the ones obtained by the more established technique of PAM fluorometry (see below).

3.2.2. Conventional pulse amplitude modulated fluorescence

Active fluorescence protocols exploiting PAM [23] can measure the potential and effective quantum efficiency of photosystem II, the electron transport rate, and the extent of non-photochemical quenching. Based on the concepts used in the light-doubling technique [90], PAM fluorometry enables to distinguish between the photochemical (qP) and non-photochemical (i.e., dissipative; qN and NPQ) use of light energy. Notably, the quantum efficiency of photosystem II can be measured much more easily than the other parameters [91]. Kitajima and Butler [92] showed that the maximum potential quantum yield of PS II is characterized by the dimensionless parameter Fv/Fm (the ratio of variable and maximum fluorescence measured after saturating light pulses). A very constant value of 0.832 ± 0.004 was found for healthy leaves of a very wide variety of species [93] while stress due to disease or environmental conditions is indicated by lower values. The basal fluorescence (Fo) is dependent on the tissues’ Chl concentration [33], which, in turn, depends on the physiological condition of the photosynthetic system. However, severe stress may change the basal fluorescence yield, affecting the relation between Fo and Chl concentration. In fact, a significant increase of Fo due to heat stress, independent of the Chl concentration was reported by Havaux and Strasser [94]. The heat-induced increase of the basal fluorescence intensity probably reflects a disturbance on the organization of thylakoid membranes [95]. The Fv/Fm parameter appears to be relatively insensitive to severe water limitation but could be used to differentiate between responses during cold. On the basis of the calculation of the fluorescence index ΔF/Fm′ (where ΔF is the difference between the maximal fluorescence [Fm′] and the steady-state fluorescence [F] of light-adapted samples), which measures the effective quantum yield of PS II [96], PAM fluorometry allows the construction of rapid light curves (RLCs) relating the rate of photosynthetic electron transport and incident photon irradiance [97, 98]. PAM was successfully applied to a wide range of plants, such as the olive tree, rosemary, and lavender [99]; Paspalum dilatatum [100], Phillyrea angustifolia [101], and other Mediterranean shrubs [102]; the tropical grass Setaria sphacelata [84] and several C4 turfgrasses [103]; maize [36, 104]; and Arabidopsis thaliana [105], among others.

3.2.3. Imaging pulse amplitude modulated fluorescence

The development of Chl fluorescence imaging systems by numerous research groups [106108] together with the emergence of commercially available models by PSI (Brno, Czech Republic), Walz Systems (Effeltrich, Germany), and Technologica Ltd. (Colchester, UK) has greatly increased the versatility of Chl fluorometry techniques (reviewed in [109]). Systems that image at the microscopic level allow to measure PS II photochemical efficiencies from chloroplasts within intact leaves and from individual cells within mixed populations [107, 110]. On the other hand, lower resolution imaging systems allow the mapping of fluorescence parameters over large areas, making it a unique technique to study the spatial heterogeneity of the photosynthetic activity across an autotrophic surface [111113]. Conventional and imaging techniques use different technologies, namely in the detection processes of the fluorescence signal: a photodiode or phototube in conventional PAM fluorometry and a charge-coupled device (CCD) camera in imaging-PAM fluorometry. Consequently, caution is needed when comparing results from conventional and imaging fluorescence techniques [114]. Nevertheless, imaging-PAM fluorometry has proven to be a powerful technique and new technological developments, as the use of semi-automated systems equipped with fluorescence cameras continuously assessing the photochemical activity of leaves [115] are in course.

4. High-throughput plant phenotyping platforms and chlorophyll fluorescence techniques

The advancement of plant phenotyping is a key factor for the success of modern plant breeding and basic plant research. Since the recognition of the phenotyping bottleneck to plant breeding [12], a global effort to provide HTPP platforms was set on. Currently, most platforms are user-built, but some commercial platforms are already available, as is the case of the German platform from the manufacturer LemnaTec and the Czech platform from the manufacturer Photon System Instruments (PSI). The Canadian-based firm Qubit Systems offers a modified version of the PSI platform. To provide high-throughput phenotyping capabilities to plant breeders, numerous user-built phenotyping facilities are organized in networks, the most prominent being the European Plant Phenotyping Network, which offers access to 23 different plant phenotyping facilities to the user community [116]. Some countries organized national networks, as is the case of the German Plant Phenotyping Network [117] and the UK Plant Phenomics Network [118]. The Jülich Plant Phenotyping Centre [119] is a leading EPPN member. Jülich’s platform makes use of LIFT to perform middle-range remote sensing of crops [119]. The commercial phenotyping platforms do not use LIF technologies. A simplified JIP test (restricted to the calculation of Fv/Fm) is used in the commercial platform from LemnaTech; a LemnaTech module with this feature is incorporated in the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) HTPP Platform [120]. PlantScreen, the commercial platform from PSI, uses conventional PAM fluorometry to perform quenching analysis. This platform has been used to phenotype cold-tolerant pea (Pisum sativum) plants [121]. Kjaer and Ottosen [122] used six independent PAM fluorometers in a HTPP experiment to assess daily growth of field-grown Brassica napus. In this case, however, the PAM system was exclusively used to show that the near infra-red laser beam of a 3D laser scanning, used for phenotyping, had not a deleterious effect over the photosynthetic metabolism of the plants. Bellasio and coworkers [123] have used an imaging-PAM system based on a FluorCam camera (PSI) inserted in a user-developed setting to phenotype common bean (Phaseolus vulgaris). The French platforms based at Montpellier [124] use an imaging-PAM system based on Walz’s devices. An important advantage of Chl fluorescence imaging is that it can be used to screen a large number of small plants simultaneously [125]. A recent advance introduced by Serôdio and coworkers [126] allows the rapid generation of light curves from non-sequential, temporally independent fluorescence measurements. This technique has the potential to bring the valuable information provided by fluorescence RLCs into the realm of HTPP. David Kramer’s group, at the Michigan State University, is currently developing a multi-instrument platform entitled Dynamic Environmental Photosynthetic Imaging (DEPI) [127], with the aim of reproducing in phytotrons the dynamics of field conditions, while continuously recording multiple parameters related with them photosynthetic performance.

TechniquePotentialLimitationsCurrent use
JIP testVery fast measurements; well-established technique; successfully used in low-throughput plant phenotyping, including in field conditionsNeed of a dark-adaptation
period; signal interpretation not always straight forward; plant contact required
IPK (LemnaTech module)LemnaTech (limited to Fv/Fm)
LIFMiddle-distance remote sensing; suitable for field phenotyping; LIFT allows the calculation of quantum efficiencyFluorescence spectra less informative than variable fluorescence
Very limited use in model plants
Conventional PAMVery informative, physiological interpretation well establishedMost protocols need a dark-adaptation period; measurements possible only at close rangeUnreportedPlantScreen (Photon System Instruments) [121]
Imaging PAMAllows mapping of the photosynthetic heterogeneity over an autotrophic surface; facilitates replication.Most protocols need a dark-adaptation period; measurements possible only at close range
Expensive and sensitive equipment
JPPC [123];
PlantScreen (Photon System Instruments)

Table 1.

Applications of chlorophyll a fluorescence techniques in high-throughput plant phenotyping.

Note: JPPC: Jülich Plant Phenotyping Centre [119]; IPK: Leibniz Institute of Plant Genetics and Crop Plant Research [120]; M3P: INRA—Montpellier Plant Phenotyping Platforms [124].

5. Prospective

Chl fluorescence techniques will continue to play a major role on HTPP. Among these, imaging-PAM techniques will play a pivotal role, although specific cases will require different technological solutions. Moreover, field HTPP, which is expected to be fostered in the forthcoming years, will require technologies not dependent on sample dark adaptations and able to operate at medium-range distance, where the family of techniques based on LIF may play a role. Finally, the development of low-cost HTPP platforms [128], required to improve plant breeding in developing countries, is expected to make use of the less expensive Chl measurement techniques, namely passive fluorescence. On the other hand, high-technology in-house HTPP platforms are expected to make simultaneously use of different Chl fluorescence techniques, integrated in a systems approach to plant phenomics.


1 - United Nations (2014) Concise Report on the World Population Situation in 2014. Department of Economic and Social Affairs, Population Division, United Nations, New York.
2 - Godfray HCJ, Beddington JR, Crute JI, Haddad L, Lawrence D, Muir JF, Pretty J, Robinson S, Thomas S, Toulmin C (2010) Food security: the challenge of feeding 9 billion people. Science 327: 812–818.
3 - Gore A (2013) The Future: Six Drivers of Global Change. Random House, New York.
4 - Neethu F, Namitha E (2015) Plant breeding as a means to achieve food security. International Journal of Applied Research 1 (8): 123–125.
5 - Phalan B, Balmford A, Green RE, Scharlemann JPW (2011) Minimising harm to biodiversity of producing more food globally. Food Policy 36: S62–S71.
6 - Husenov B, Makhkamov M, Garkava-Gustavsson L, Muminjanov H, Johansson E (2015) Breeding for wheat quality to assure food security of a staple crop: the case study of Tajikistan. Agriculture & Food Security 4: 9.
7 - Hallauer AR (2011) Evolution of plant breeding. Crop Breeding and Applied Biotechnology 11: 197–206.
8 - Morandini P, Salamini F (2003) Plant biotechnology and breeding: allied for years to come. Tends in Plant Science 8 (2): 70–75.
9 - Yano M, Tuberosa R (2009) Genome studies and molecular genetics—from sequence to crops: genomics comes of age. Current Opinion in Plant Biology 12: 103–106.
10 - Francia E, Tacconi G, Crosatti C, Barabaschi D, Bulgarelli D, Dall’Aglio E, Vale G (2005) Marker assisted selection in crop plants. Plant Cell, Tissue and Organ Culture 82: 317–342.
11 - Fiorani F, Schurr U (2013) Future scenarios for plant phenotyping. Annual Review of Plant Biology 64: 267–291.
12 - Furbank R, Tester M (2011) Phenomics – technologies to relieve the phenotyping bottleneck. Trends in Plant Science 16 (12): 635–644.
13 - Marques da Silva J, Casetta E (2015) The evolutionary stages of plant physiology and a plea for transdisciplinarity. Axiomathes 25: 205–215.
14 - Lièvre M, Wuyts N, Cookson SJ, Bresson J, Dapp M, Vasseur F, Massonnet C, Tisné Bettembourg M, Balsera C, Bédiée A, Bouvery F, Dauzat M, Rolland G, Vile D, Granier C (2013) Phenotyping the kinematics of leaf development in flowering plants: recommendations and pitfalls. WIREs Developmental Biology 2: 809–821.
15 - Jackson P, Robertson M, Cooper M, Hammer G (1996) The role of physiological understanding in plant breeding; from a breeding perspective. Field Crops Research 49: 1–37.
16 - Duque S, Almeida AM, Bernardes da Silva A, MarquesdaSilva J, Farinha AP, Santos D, Fevereiro P, Araújo SS (2013) Abiotic stress responses in plants: unravelling the complexity of genes and networks to survive. In: Abiotic Stress – Plant Responses and Applications in Agriculture, pp. 49–101 (Vahdati K, Leslie C eds.), InTech, Rijeka.
17 - Parry MA, Hawkesford MJ (2012) An integrated approach to crop genetic improvement. Journal of Integrative Plant Biology 54 (4): 250–259.
18 - Scheibe R, Backhausen JE, Emmerlich V, Holtgrefe S (2005) Strategies to maintain redox homeostasis during photosynthesis under changing conditions. Journal of Experimental Botany 56 (416): 1481–1489.
19 - Berberan-Santos MN, Bodunov EN, Valeur B (2005) Mathematical functions for the analysis of luminescence decays with underlying distributions 1. Kohlrausch decay function (stretched exponential). Chemical Physics 315: 171–182.
20 - Berberan-Santos MN, Bodunov EN, Valeur B (2008) Luminescence decays with underlying distributions of rate constants: general properties and selected cases. In: Fluorescence of Supermolecules, Polymers and Nano-systems, pp. 67–103 (Berberan-Santos MN ed.), Springer, Berlin.
21 - Li L, Zhang Q, Huang D (2014) A review of imaging techniques for plant phenotyping. Sensors 14: 20078–20111.
22 - Kautsky H, Hirsch A (1931) Neue Versuche zur Kohlensäureassimilation (New experiments on carbonic acid assimilation). Naturwissenschaften 19: 48.
23 - Schreiber U, Schliwa U, Bilger W (1986) Continuous recording of photochemical and non-photochemical chlorophyll fluorescence quenching with a new type of modulation fluorometer. Photosynthesis Research 10: 51–62.
24 - Stokes GG (1852) On the change of refrangibility of light. Philosophical Transactions of the Royal Society of London 142: 463–562.
25 - Marques da Silva J, Bernardes da Silva A, Pádua M (2007) Modulated chlorophyll a fluorescence: a tool for teaching photosynthesis. Journal of Biological Education 41: 178–183.
26 - Cavaco AM, Antunes MDC, Marques da Silva J, Antunes R, Guerra R (2009) Preliminary results on the non-invasive diagnosis of superficial scald in ‘Rocha’ pear by fluorescence imaging. In: Proceedings of the 1st International Workshop in Computer Image Analysis in Agriculture, pp. 121–127, Potsdam.
27 - Guerra R, Gardé I, Antunes M, Marques da Silva J, Antunes R, Cavaco AM (2012) A possibility for non-invasive diagnosis of superficial scald in ‘Rocha’ pear based on chlorophyll a fluorescence, colorimetry, and the relation between alpha-farnesene and conjugated trienols. Scientia Horticulturae 134: 127–138.
28 - Breia R, Vieira S, Marques da Silva J, Gerós H, Cunha A (2013) Mapping grape berry photosynthesis by chlorophyll fluorescence imaging: the effect of saturating pulse intensity in different tissues. Photochemistry & Photobiology 89: 579–585.
29 - Ralph PJ, Schreiber U, Gademann R, Kühl M, Larkum AWD (2005) Coral photobiology studied with a new imaging pulse amplitude modulated fluorometer. Journal of Phycology 41: 335–342.
30 - Ralph PJ, Gademann R, Dennison WC (1998) In situ seagrass photosynthesis measured using a submersible, pulse-amplitude modulated fluorometer. Marine Biology 132: 367–373.
31 - Beer S, Larsson C, Poryan O, Axelsson L (2000) Photosynthetic rates of Ulva (Chlorophyta) measured by pulse amplitude modulated (PAM) fluorometry. European Journal of Phycology 35: 69–74.
32 - Serôdio J, Marques da Silva J, Catarino F (1997) Nondestructive tracing of migratory rhythms of intertidal benthic microalgae using in vivo chlorophyll a fluorescence. Journal of Phycology 33: 542–553.
33 - Serôdio J, Marques da Silva J, Catarino F (2001) Use of in vivo chlorophyll a fluorescence to quantify short-term variations in the productive biomass of intertidal microphytobenthos. Marine Ecology Progress Series 218: 45–61.
34 - Cartaxana P, Vieira S, Ribeiro L, Rocha R, Cruz S, Calado R, Marques da Silva J (2015) Effects of elevated temperature and CO2 on intertidal microphytobenthos. BMC Ecology 15: 10.
35 - Almeida AM, Bernardes da Silva A, Araújo S, Cardoso L, Santos D, Tomé J, Marques da Silva J, Paul M, Fevereiro P (2007) Responses to water withdrawal of tobacco plants genetically engineered with the AtTPS1 gene: a special reference to photosynthetic parameters. Euphytica 154: 113–126.
36 - Cruz de Carvalho R, Cunha A, Marques da Silva J (2011) Photosynthesis by six Portuguese maize cultivars during drought stress and recovery. Acta Physiologiae Plantarum 33: 359–374.
37 - Willits DH, Peet MM (2001) Measurement of chlorophyll fluorescence as a heat stress indicator in tomato: laboratory and greenhouse comparisons. Journal of the American Society of Horticultural Sciences 126 (2): 188–194.
38 - Chaerle L, Lenk S, Leinonen I, Jones HG, Van Der Straeten D, Buschmann C (2009) Multi-sensor plant imaging: towards the development of a stress-catalogue. Biotechnology Journal 4: 1152–1156.
39 - Jansen M, Gilmer F, Biskup B, Nagel KA, Rascher U, Fischbach A, Briem S, Dreissen G, Tittmann S, Braun S, De Jaeger I, Metzlaff M, Schurr U, Scharr H, Walter A (2009) Simultaneous phenotyping of leaf growth and chlorophyll fluorescence via GROWSCREEN FLUORO allows detection of stress tolerance in Arabidopsis thaliana and other rosette plants. Functional Plant Biology 36 (11): 902–914.
40 - Munns R, James RA, Sirault XRR, Furbank RT, Jones HG (2010) New phenotyping methods for screening wheat and barley for beneficial responses to water deficit. Journal of Experimental Botany 61 (13): 3499–3507.
41 - Gorbe E, Calatayud A (2012) Applications of chlorophyll fluorescence imaging technique in horticultural research: a review. Scientia Horticulturae 138: 24–35.
42 - Misra AN, Misra M, Singh R (2012) Chlorophyll fluorescence in plant biology. In: Biophysics, pp. 171–192 (Misra AN ed.), InTech, Rijeka.
43 - Cendrero-Mateo MP, Moran MS, Papuga SA, Thorp KR, Alonso L, Moreno J, Ponce-Campos G, Rascher U, Wang G (2015) Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments. Journal of Experimental Botany 67 (1): 275–286.
44 - Hill R (1937) Oxygen evolved by isolated chloroplasts. Nature 139: 881–882.
45 - Malkin S, Kok B (1966) Fluorescence induction studies in isolated chloroplasts. I. Number of components involved in the reaction and quantum yields. Biochimica Biophysica Acta 126: 413–432.
46 - Lichtenthaler H, Rinderle U (1988) The role of chlorophyll fluorescence in the detection of stress conditions in plants. Critical Reviews in Analytical Chemistry 19: 29–85.
47 - Strasser RJ (1986) Mono- bi- tri- and polypartite models in photosynthesis. Photosynthesis Research 10: 255–276.
48 - Strasser BJ, Strasser RJ (1995) Measuring fast fluorescence transients to address environmental questions: the JIP‐test. In: Photosynthesis: From Light to Biosphere, pp. 977–980 (Mathis P ed.), Kluwer Academic Publishers, Dordrecht.
49 - Strasser BJ (1997) Donor side capacity of photosystem II probed by chlorophyll a fluorescence transients. Photosynthesis Research 52: 147–155.
50 - Govindjee (1995) Sixty-three years since Kautsky: chlorophyll a fluorescence. Australian Journal of Plant Physiology 22: 131–160.
51 - Kalaji HM, Schansker G, Ladle RJ, Goltsev V, Bosa K, Allakhverdiev SI, Brestic M, Bussotti F, Calatayud A, Dabrowski P, Elsheery NI, Ferroni L, Guidi L, Hogewoning SW, Jajoo A, Misra AN, Nebauer SG, Pancaldi S, Penella C, Poli D, Pollastrini M, Romanowska-Duda ZB, Rutkowska B, Serôdio J, Suresh K, Szulc W, Tambussi E, Yanniccari M, Zivcak M (2014) Frequently asked questions about in vivo chlorophyll fluorescence: practical issues. Photosynthesis Research 122: 121–158.
52 - Srivastava A, Guissé B, Greppin H, Strasser RJ (1997) Regulation of antenna structure and electron transport in photosystem II of Pisum sativum under elevated temperature probed by the fast polyphasic chlorophyll a fluorescence transient: OKJIP. Biochimica et Biophysica Acta 1320: 95–106.
53 - Tsimilli‐Michael M, Eggenberg P, Biro B, Köves‐Pechy K, Vörös I, Strasser RJ (2000) Synergistic and antagonistic effects of arbuscular mycorrhizal fungi and Azospirillum and Rizhobium nitrogen‐fixers on the photosynthetic activity of alfalfa probed by the polyphasic chlorophyll a fluorescence transient O‐J‐I‐P. Applied Soil Ecology 15: 169–182.
54 - Demetriou G, Neonaki C, Navakoudis E, Kotzabasis K (2007) Salt stress impact on the molecular structure and function of the photosynthetic apparatus—the protective role of polyamines. Biochimica et Biophysica Acta 1767: 272–280.
55 - Zivcák M, Brestic M, Olsovská K, Slamka P (2008) Performance index as a sensitive indicator of water stress in Triticum aestivum L. Plant, Soil and Environment 54: 133–139.
56 - Mathur S, Mehta P, Jajoo A (2013) Effects of dual stress (high salt and high temperature) on the photochemical efficiency of wheat leaves (Triticum aestivum). Physiology and Molecular Biology of Plants 19 (2): 179–188.
57 - Silvestre S, Araújo SS, Vaz Patto MC, Marques da Silva J (2014) Performance index: an expeditious tool to screen for improved drought resistance in the Lathyrus genus. Journal of Integrative Plant Biology 56 (7): 610–621.
58 - Zivcák M, Brestic M, Kalaji HM, Govindjee (2014) Photosynthetic responses of sun- and shade-grown barley leaves to high light: is the lower PSII connectivity in shade leaves associated with protection against excess of light? Photosynthesis Research 119: 339–354.
59 - Öz MT, Turan Ö, Kayihan C, Eyidoğan F, Ekmekçi Y, Yücel M, Öktem HA (2014) Evaluation of photosynthetic performance of wheat cultivars exposed to boron toxicity by the JIP fluorescence test. Photosynthetica 52 (4): 555–563.
60 - Jedmowski C, Brüggemann W (2015) Imaging of fast chlorophyll fluorescence induction curve (OJIP) parameters, applied in a screening study with wild barley (Hordeum spontaneum) genotypes under heat stress. Journal of Photochemistry and Photobiology B: Biology 151: 153–160.
61 - Van Wittenberghe S, Alonso L, Verrelst J, Hermans I, Delegido J, Veroustraete F, Valcke R, Moreno J, Samson R (2013) Upward and downward solar-induced chlorophyll fluorescence yield indices of four tree species as indicators of traffic pollution in Valencia. Environmental Pollution 173: 29–37.
62 - Vieira S, Lavrov A, Utkin A, Santos A, Vilar R, Marques da Silva J, Cartaxana P (2011) Effects of migration on intertidal microphytobenthos biomass measured by laser-induced fluorescence (LIF). Marine Ecology Progress Series 432: 45–52.
63 - Zarco-Tejada PJ, Gonzalez-Dugo V, Berni JAJ (2012) Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera. Remote Sensing of Environment 117: 322–337.
64 - Astafurova TP, Grishin AI, Zotikova AP, Klimkin VM, Matvienko GG, Romanovskii OA, Sokovikov VG, Timofeev VI, Kharchenko OV (2001) Remote probing of plant photosynthetic apparatus by measuring laser-induced fluorescence. Russian Journal of Plant Physiology 48: 518–522.
65 - Zuev VV, Zueva NE, Grishaev MV (2009) Seasonal variations of fluorescence of Scotch pine according to data of measurements at Siberian Lidar Station. Atmospheric and Oceanic Optics 22 (1): 42–48.
66 - Saito Y, Saito R, Kawahara TD, Nomura A, Takeda S (2000) Development and performance characteristics of laser-induced fluorescence imaging lidar for forestry applications. Forest Ecology and Management 128: 129–137.
67 - Saito Y, Kurihara K, Takahashi H, Kobayashi F, Kawahara T, Nomura A, Takeda S (2002) Remote estimation of the chlorophyll concentration of living trees using laser-induced fluorescence imaging lidar. Optical Review 9 (2): 37–39.
68 - Richards TJ, Schuerger AC, Capelle G, Guikema JA (2003) Laser-induced fluorescence spectroscopy of dark- and light-adapted bean (Phaseolus vulgaris L.) and wheat (Triticum aestivum L.) plants grown under three irradiance levels and subjected to fluctuating lighting conditions. Remote Sensing of Environment 84: 323–341.
69 - Chappelle EW, Wood Jr. FM, McMurtrey III JE, Newcomb W (1984) Laser-induced fluorescence of green plants. 1: A technique for the remote detection of plant stress and species identification. Applied Optics 23 (1): 134.
70 - Brach EJ, Molnar JM, Jasmin JJ (1977) Detection of lettuce maturity and variety by remote sensing techniques. Journal of Agricultural Engineering Research 22: 45–54.
71 - Lüdeker W Dahn H-G, Günther HP (1996) Detection of fungal infection of plants by laser-induced fluorescence: an attempt to use remote sensing. Journal of Plant Physiology 148: 579–585.
72 - Pereira FMV, Milori DMBP, Pereira-Filho ER, Venâncio AL, Russo MST, Cardinali MCB, Martins PK, Freitas-Astúa J (2011) Laser-induced fluorescence imaging method to monitor citrus greening disease. Computers and Electronics in Agriculture 79: 90–93.
73 - Lavrov A, Utkin AB, Marques da Silva J, Vilar R, Santos NM, Alves B (2012) Water stress assessment of cork oak leaves and maritime pine needles based on LIF spectra. Optics and Spectroscopy 112: 271–279.
74 - Gameiro C, Utkin AB, Cartaxana P, Marques da Silva J, Matos AR (2015) The use of laser induced chlorophyll fluorescence (LIF) as a fast and non-destructive method to investigate water deficit in Arabidopsis. Agricultural Water Management 164 (1): 127–136.
75 - Edner H, Johansson J, Svanberg S, Wallinder E (1994) Fluorescence lidar multicolor imaging of vegetation. Applied Optics 33: 2471–2479.
76 - Grishin AI, Krekov GM, Krekova MM, Matvienko GG, Sukhanov AY, Timofeev VI, Fateyeva NL, Lisenko AA (2007) Investigation of organic aerosol of plants with fluorescence lidar. Atmospheric and Ocean Optics 20: 328–337.
77 - Fateyeva NL, Matvienko GG (2004) Application of the method of laser-induced fluorescence. In: SPIE Proceedings 5232 “Remote Sensing for Agriculture, Ecosystems, and Hydrology V”, pp. 652–657 (Owe M, D’Urso G, Moreno JF, Calera A eds.), SPIE Press, Bellingham.
78 - Fateyeva NL, Klimkin AV, Bender OV, Zotikova AP, Yamburov MS (2006) Analysis of laser-induced fluorescence in wood plants under nitrogen soil pollution. Atmospheric and Oceanic Optics 19: 189–192.
79 - Gopal R, Mishra KB, Zeeshan M, Prasad SM, Joshi MM (2002) Laser-induced chlorophyll fluorescence spectra of mug plants growing under nickel stress. Current Science 83 (7): 880–884.
80 - Utkin AB, Vieira S, Marques da Silva J, Lavrov A, Leite E, Cartaxana P (2013) Compact low-cost detector for in vivo assessment of microphytobenthos using laser induced fluorescence. Optics and Spectroscopy 114: 471–474.
81 - Gameiro C, Utkin AB, Cartaxana P (2015) Characterisation of estuarine intertidal macroalgae by laser-induced fluorescence. Estuarine, Coastal and Shelf Science 167: 119–124.
82 - Hák R, Lichtenthaler HK, Rinderle U (1990) Decrease of the chlorophyll fluorescence ratio F690/F730 during greening and development of leaves. Radiation and Environmental Biophysics 29: 329–336.
83 - Lichtenthaler HK, Hák R, Rinderle U (1990) The chlorophyll fluorescence ratio F690/F730 in leaves of different chlorophyll contents. Photosynthesis Research 25: 295–298.
84 - Marques da Silva J, Arrabaça MC (2004) Photosynthesis in the water stressed C4 grass Setaria sphacelata is mainly limited by stomata with both rapidly and slowly imposed water deficits. Physiologia Plantarum 121: 409–420.
85 - Buschmann C (2007) Variability and application of the chlorophyll fluorescence emission ratio red/far red of leaves. Photosynthesis Research 92: 261–271.
86 - Gigon A, Matos AR, Laffray D, Zuily-Fodil Y, Pham-Thi AT (2004) Effect of drought stress on lipid metabolism in the leaves of Arabidopsis thaliana (ecotype Columbia). Annals of Botany 94: 345–351.
87 - Cerovic ZG, Goulas Y, Gorbunov M, Briantais J-M, Camenen L, Moya I (1996) Fluorosensing of water stress in plants: diurnal changes of the mean lifetime and yield of chlorophyll fluorescence, measured simultaneously and at distance with a τ-LIDAR and a modified PAM-fluorimeter, in maize, sugar beet, and kalanchoë. Remote Sensing of Environment 58 (3): 311–321.
88 - Kolber Z, Klimov D, Ananyev G, Rascher U, Berry J, Osmond B (2005) Measuring photosynthetic parameters at a distance: laser induced fluorescence transient (LIFT) method for remote measurements of photosynthesis in terrestrial vegetation. Photosynthesis Research 84: 121–129.
89 - Raesch AR, Muller O, Pieruschka R, Rascher U (2014) Field observations with laser-induced fluorescence transient (LIFT) method in barley and sugar beet. Agriculture 4: 159–169.
90 - Baker N, Bradbury M (1981) Possible applications of chlorophyll fluorescence techniques for studying photosynthesis in vivo. In: Plants and the Daylight Spectrum, pp. 355–372 (Smith H ed.), Academic Press, London.
91 - Maxwell K, Johnson GN (2000) Chlorophyll fluorescence—a practical guide. Journal of Experimental Botany 51: 659–668.
92 - Kitajima M, Butler WL (1975) Quenching of chlorophyll fluorescence and primary photochemistry in chloroplasts by dibromothymoquinone. Biochimica et Biophysica Acta 376: 105–115.
93 - Björkman O, Demmig B (1987) Photon yield of O2 evolution and chlorophyll fluorescence characteristics at 77 K among vascular plants of diverse origins. Planta 170: 489–504.
94 - Havaux M, Strasser R (1992) Plasticity of the stress tolerance of the photosystem II in vivo. In: Research in Photosynthesis, vol. IV, pp. 149–152 (Murata N ed.), Kluwer Academic Publishers, Dordrecht.
95 - Kovács L, Damkjaer J, Kereiche S, Ilioaia C, Ruban AV, Boekema EJ, Jansson S, Horton P (2006) Lack of the light-harvesting complex CP24 affects the structure and function of the grana membranes of higher plant chloroplasts. The Plant Cell 18 (11): 3106–3120.
96 - Genty B, Briantais JM, Baker NR (1989) The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence. Biochimica et Biophysica Acta 990: 87–92.
97 - Serôdio J, Vieira S, Cruz S, Barroso F (2005) Short-term variability in the photosynthetic activity of microphytobenthos as detected by measuring rapid light curves using variable fluorescence. Marine Biology 146: 903–914.
98 - Perkins RG, Mouget JL, Lefebvre S, Lavaud J (2006) Light response curve methodology and possible implications in the application of chlorophyll fluorescence to benthic diatoms. Marine Biology 149: 703–712.
99 - Nogués S, Baker NR (2000) Effects of drought on photosynthesis in Mediterranean plants grown under enhanced UV‐B radiation. Journal of Experimental Botany 51: 1309–1317.
100 - Marques da Silva J, Arrabaça MC (l992). Characteristics of fluorescence emission by leaves of nitrogen starved Paspalum dilatatum POIR. Photosynthetica 26 (2): 253–256.
101 - Munne-Bosch S, Penuelas J (2003) Photo- and antioxidative protection, and a role for salicylic acid during drought and recovery in field-grown Phillyrea angustifolia plants. Planta 217: 758–766.
102 - Marques da Silva J (2007) Chlorophyll fluorescence parameters of three Mediterranean shrubs in a summer-autumn period in central Portugal. Biologia Plantarum 51: 741–745.
103 - Carmo-Silva A, Soares A, Marques da Silva J, Bernardes da Silva A, Keys A, Arrabaça MC (2007) Photosynthetic responses of three C4 grasses of different metabolic sub-types to water deficit. Functional Plant Biology 34: 204–213.
104 - Xu ZZ, Zhou GS, Wang YL, Han GX, Li YJ (2008) Changes in chlorophyll fluorescence in maize plants with imposed rapid dehydration at different leaf ages. Journal of Plant Growth Regulation 27: 83–92.
105 - Woo NS, Badger MR, Pogson BJ (2008) A rapid, non-invasive procedure for quantitative assessment of drought survival using chlorophyll fluorescence. Plant Methods 4: 27.
106 - Omasa K, Shimazaki KL, Aiga I, Larcher W, Onoe M (1987) Image analysis of chlorophyll fluorescence transients for diagnosing the photosynthetic system of attached leaves. Plant Physiology 84: 748–752.
107 - Oxborough K, Baker NR (1997) An instrument capable of imaging chlorophyll a fluorescence from intact leaves at very low irradiance and at cellular and subcellular levels of organization. Plant, Cell and Environment 20: 1473–1483.
108 - Nedbal L, Soukupova J, Kaftan D, Whitmarsh J, Trilek M (2000) Kinetic imaging of chlorophyll fluorescence using modulated light. Photosynthesis Research 66: 25–34.
109 - Oxborough K (2004) Imaging of chlorophyll a fluorescence: theoretical and practical aspects of an emerging technique for the monitoring of photosynthetic performance. Journal of Experimental Botany 55: 1195–1205.
110 - Oxborough K, Hanlon ARM, Underwood GJC, Baker NR (2000) In vivo estimation of the Photosystem II photochemical efficiency of individual microphytobenthic cells using high-resolution imaging of chlorophyll a fluorescence. Limnology and Oceanography 45: 1420–1425.
111 - Scholes JD, Rolfe SA (1996) Photosynthesis in localized regions of oat leaves infected with crown rust (Puccinia coronata): quantitative imaging of chlorophyll fluorescence. Planta 199: 573–582.
112 - Meng Q, Siebke K, Lippert P, Baur B, Mukherjee U, Weis E (2001) Sink-source transition in tobacco leaves visualized using chlorophyll fluorescence imaging. New Phytologist 151: 585–596.
113 - Hill R, Schreiber U, Gademann R, Larkum AWD, Kühl M, Ralph PJ (2004) Spatial heterogeneity of photosynthesis and the effect of temperature-induced bleaching conditions in three species of corals. Marine Biology 144: 633–640.
114 - Vieira S, Ribeiro L, Jesus B, Cartaxana P, Marques da Silva J (2013) Photosynthesis assessment in microphytobenthos with conventional and imaging pulse amplitude modulation fluorometry. Photochemistry and Photobiology 89: 97–102.
115 - Chaerle L, Hulsen K, Hermans C, Strasser RJ, Valcke R, Höfte M, Van Der Straeten D (2003) Robotized time-lapse imaging to assess in-planta uptake of phenylurea herbicides and their microbial degradation. Physiologia Plantarum 118: 613–619.
116 - EPPN (2016), downloaded January 14, 2016.
117 - DPPN (2016);jsessionid=EEB 2F474C83047B82BA1B1DF745BCCCE, downloaded January 14, 2016.
118 - UKPPN (2016), downloaded January 14, 2016.
119 - JPPC (2016), downloaded January 14, 2016.
120 - IPK (2016), downloaded January 14, 2016.
121 - Humplík JF, Lazár D, Fürst T, Husičková A, Hýbl M, Spíchal L (2015) Automated integrative high-throughput phenotyping of plant shoots: a case study of the cold-tolerance of pea (Pisum sativum L.). Plant Methods 11: 20.
122 - Kjaer KH, Ottosen C-O (2015) 3D laser triangulation for plant phenotyping in challenging environments. Sensors 15: 13533–13547.
123 - Bellasio C, Olejníčková J, Tesař R, Šebela D, Nedbal L (2012) 3D computer reconstruction of plant growth and chlorophyll fluorescence emission in three spatial dimension. Sensors 12: 1052–1071.
124 - M3P (2016)
125 - Brestic M, Zivcak M (2013) PSII fluorescence techniques for measurement of drought and high temperature stress signal in crop plants: protocols and applications. In: Molecular Stress Physiology of Plants, pp. 87–131 (Rout GR, Das AB eds.), Springer, Dordrecht.
126 - Serôdio J, Ezequiel J, Frommlet J, Laviale M, Lavaud J (2013) A method for the rapid generation of nonsequential light-response curves of chlorophyll fluorescence. Plant Physiology 163: 1089–1102.
127 - Xu L, Cruz JA, Savage LJ, Kramer DM, Chen J (2015) Plant photosynthesis phenomics data quality control. Bioinformatics 31 (11): 1796–1804.
128 - Cessna S, Demmig-Adams B, Adams III WW (2010) Exploring photosynthesis and plant stress using inexpensive chlorophyll fluorometers. Journal of Natural Resources and Life Sciences Education 39: 22–30.


1 Please note that the very concept of photosynthesis as being a redox process was only to be demonstrated 6 years later [44].