The aim of this educational review is to provide practical information on the hardware, methodology, and the hands on application of chlorophyll (Chl) a fluorescence technology. We present the paper in a question and answer format like frequently asked questions. Although nearly all information on the application of Chl a fluorescence can be found in the literature, it is not always easily accessible. This paper is primarily aimed at scientists who have some experience with the application of Chl a fluorescence but are still in the process of discovering what it all means and how it can be used. Topics discussed are (among other things) the kind of information that can be obtained using different fluorescence techniques, the interpretation of Chl a fluorescence signals, specific applications of these techniques, and practical advice on different subjects, such as on the length of dark adaptation before measurement of the Chl a fluorescence transient. The paper also provides the physiological background for some of the applied procedures. It also serves as a source of reference for experienced scientists.

Using chlorophyll (Chl) a fluorescence many aspects of the photosynthetic apparatus can be studied, both in vitro and, noninvasively, in vivo. Complementary techniques can help to interpret changes in the Chl a fluorescence kinetics. Kalaji et al. (Photosynth Res 122:121–158, 2014a) addressed several questions about instruments, methods and applications based on Chl a fluorescence. Here, additional Chl a fluorescence-related topics are discussed again in a question and answer format. Examples are the effect of connectivity on photochemical quenching, the correction of F V/F M values for PSI fluorescence, the energy partitioning concept, the interpretation of the complementary area, probing the donor side of PSII, the assignment of bands of 77 K fluorescence emission spectra to fluorescence emitters, the relationship between prompt and delayed fluorescence, potential problems when sampling tree canopies, the use of fluorescence parameters in QTL studies, the use of Chl a fluorescence in biosensor applications and the application of neural network approaches for the analysis of fluorescence measurements. The answers draw on knowledge from different Chl a fluorescence analysis domains, yielding in several cases new insights.

Non-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g(-1) for soluble sugars, 6-533 (mean = 94) mg g(-1) for starch and 53-649 (mean = 153) mg g(-1) for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R(2) = 0.05-0.12 for soluble sugars, 0.10-0.33 for starch and 0.01-0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g(-1) for total NSC, compared with the range of laboratory estimates of 596 mg g(-1). Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41-0.91), but less so for total NSC (r = 0.45-0.84) and soluble sugars (r = 0.11-0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods.

DNA binding with One Finger (DOF) transcription factors are involved in multiple aspects of plant growth and development but their precise roles in abiotic stress tolerance are largely unknown. Here we report a group of five tomato DOF genes, homologous to Arabidopsis Cycling DOF Factors (CDFs), that function as transcriptional regulators involved in responses to drought and salt stress and flowering-time control in a gene-specific manner. SlCDF1-5 are nuclear proteins that display specific binding with different affinities to canonical DNA target sequences and present diverse transcriptional activation capacities in vivo. SlCDF1-5 genes exhibited distinct diurnal expression patterns and were differentially induced in response to osmotic, salt, heat, and low-temperature stresses. Arabidopsis plants overexpressing SlCDF1 or SlCDF3 showed increased drought and salt tolerance. In addition, the expression of various stress-responsive genes, such as COR15, RD29A, and RD10, were differentially activated in the overexpressing lines. Interestingly, overexpression in Arabidopsis of SlCDF3 but not SlCDF1 promotes late flowering through modulation of the expression of flowering control genes such as CO and FT. Overall, our data connect SlCDFs to undescribed functions related to abiotic stress tolerance and flowering time through the regulation of specific target genes and an increase in particular metabolites.

DNA-binding with one finger (DOF)-type transcription factors are involved in many fundamental processes in higher plants, from responses to light and phytohormones to flowering time and seed maturation, but their relation with abiotic stress tolerance is largely unknown. Here, we identify the roles of CDF3, an Arabidopsis DOF gene in abiotic stress responses and developmental processes like flowering time. CDF3 is highly induced by drought, extreme temperatures and abscisic acid treatment. The CDF3 T-DNA insertion mutant cdf3-1 is much more sensitive to drought and low temperature stress, whereas CDF3 overexpression enhances the tolerance of transgenic plants to drought, cold and osmotic stress and promotes late flowering. Transcriptome analysis revealed that CDF3 regulates a set of genes involved in cellular osmoprotection and oxidative stress, including the stress tolerance transcription factors CBFs, DREB2A and ZAT12, which involve both gigantea-dependent and independent pathways. Consistently, metabolite profiling disclosed that the total amount of some protective metabolites including γ-aminobutyric acid, proline, glutamine and sucrose were higher in CDF3-overexpressing plants. Taken together, these results indicate that CDF3 plays a multifaceted role acting on both flowering time and abiotic stress tolerance, in part by controlling the CBF/DREB2A-CRT/DRE and ZAT10/12 modules.