Journal of Analytical Methods in Chemistry

Journal of Analytical Methods in Chemistry / 2020 / Article

Research Article | Open Access

Volume 2020 |Article ID 8865849 |

Thiago L. Marques, Milton K. Sasaki, Lidiane C. Nunes, Fábio R. P. Rocha, "Flow-Batch Sample Preparation for Fractionation of the Stress Signaling Phytohormone Salicylic Acid in Fresh Leaves", Journal of Analytical Methods in Chemistry, vol. 2020, Article ID 8865849, 8 pages, 2020.

Flow-Batch Sample Preparation for Fractionation of the Stress Signaling Phytohormone Salicylic Acid in Fresh Leaves

Academic Editor: Pablo Richter
Received28 Apr 2020
Accepted01 Jul 2020
Published17 Jul 2020


Salicylic acid (SA) is an important stress signaling phytohormone and plays an essential role in physiological processes in plants. SA fractionation has been carried out batchwise, which is not compatible with the high analytical demand in agronomical studies and increases susceptibility to analytical errors. In this context, a novel flow-batch sample preparation system for SA fractionation on fresh plant leaves was developed. It was based on microwave-assisted extraction with water and conversion of the conjugated species to free SA by alkaline hydrolysis. Free and total SA were quantified by fluorimetry after separation by sequential injection chromatography in a C18 monolithic column. The proposed procedure is directly applicable to plant leaves containing up 16 mg kg−1 SA, with a limit of detection of 0.1 mg kg−1 of SA, coefficient of variation of 3.0% (n = 10), and sampling rate of 4 samples h−1. The flow-batch sample preparation system was successfully applied to SA fractionation in sugarcane, corn, and soybean leaves without clogging or increasing in backpressure. The proposed approach is simple, less time-consuming, and more environmentally friendly in comparison to batchwise procedures.

1. Introduction

Salicylic acid (SA) is an important phytohormone in plants, which acts as stress signaling, as well as on seed germination, seedling formation, plant respiration, legumes nodulation, fruits production, and defense against pathogens [13]. Although free SA is the active form involved in physiological processes, it is stored in cellular vacuoles either as inactive glycosylated or methylated species [3]. Thus, fractionation of SA is relevant to understand plant response under stressing conditions and to evaluate the activation of the mechanism of the plant defense [4].

Determination of SA and its derivatives in plants demands selective and sensitive procedures because the species are usually found in low contents (mg kg−1) in a relatively complex matrix [5, 6]. Chromatographic techniques are usually applied for this task, including high performance liquid chromatography (HPLC) with detection by mass spectrometry (MS) [6], tandem mass spectrometry (MS/MS) [7], fluorimetry [8] or spectrophotometry [9], ultra high performance liquid chromatography coupled to MS/MS [4], or gas chromatography (GC) coupled to MS [1, 10]. These alternatives are relatively expensive and sample preparation involves several steps, which increase sample handling and susceptibility to analytical errors [4, 6, 7]. In addition, these procedures typically consume large amounts of solvents and generate large quantity of residues, which is not in accordance to the principles of Green Analytical Chemistry [11].

Sequential injection chromatography (SIC) combines sequential injection analysis (SIA) with monolithic or fused-core particles columns operating at relatively low pressures to promote fast and cost-effective chromatographic separations, minimizing eluent volumes and waste amounts [12, 13]. Despite the lower chromatographic efficiency compared to HPLC, successful separations have been achieved for a diversity of applications, including determination of pharmaceutical compounds in medicines [12] and body fluids [14], contaminants in food [13], and pesticides in natural waters [15]. Barrientos et al. [16] successfully applied SIC with fluorimetric detection for determination of free SA on plant leaves after batchwise microwave-assisted extraction. It was demonstrated that fluorimetry based on the intrinsic fluorescence of salicylate is a cost-effective alternative to the MS detectors. Other studies have demonstrated that the conjugated species can be quantified after conversion to salicylate either by acid [8] or alkaline [17] hydrolysis, which allows fractionation of SA. A systematic evaluation of the batchwise experimental conditions for SA fractionation in plant leaves was recently presented [18].

Analyte extraction from solid samples has been predominantly performed on the batch mode, which is typically time-consuming and increases susceptibility to analytical errors. Alternatively, some flow systems have been successfully applied for this task [19], including bioavailability studies [20]. Applications involving treatment of plant tissues prior to chromatographic determination have also been reported [2123]. As an example, Wu et al. [23] developed a microwave-assisted extraction flow system for pesticide determination on vegetables by GC-MS. Samples were mixed with sand and packed into a glass column, which was put inside a domestic microwave oven. After extraction with a NaCl solution and online single drop microextraction with toluene, the pesticides were quantified into the organic phase by GC-MS [23]. The need for packing each sample into the glass column, the risks of clogging, and increase of backpressure are drawbacks that can be overcome by flow-batch extraction systems [24]. This approach combines advantages of flow-based (e.g., high sample throughput, low reagent consumption, and continuous system washing) and batchwise (e.g., better sample to reagent interaction and long sample residence times) procedures [25]. The potentiality of flow-batch extraction systems is increased by exploiting flow programming inherent to SIA, which allow independent handling of reagents, flow rates, and timing.

In this work, a flow-batch approach was combined to SIA for SA fractionation on plant tissues. The proposed system allows microwave-assisted extraction from the solid samples followed by either the direct determination of free SA or online alkaline hydrolysis aiming at the determination of total SA. The analytical determinations were carried out by fluorimetric detection of the salicylate ion after separation of the sample matrix by sequential injection chromatography.

2. Experimental

2.1. Apparatus

Extraction of the analytes from the plant tissues and hydrolysis of the conjugated forms of SA were performed with a SIA system (FIAlab® 3500, FIAlab Instruments Inc.®, Bellevue, USA) equipped with a 10 mL syringe pump, a bidirectional peristaltic pump, and an eight-port low-pressure PPS selection valve (Valco Instrument Co., Houston, USA). Analyte separation was performed with a SIChrom™ system (FIAlab Instruments®, Bellevue, USA) with an eight-port high-pressure stainless-steel selection C5H valve (Valco Instrument Co., Houston, USA) and an S17 PDP syringe pump (Sapphire™ Engineering, MA, USA) with a 4.0 mL reservoir. Flow systems were controlled by a microcomputer equipped with FIAlab® 5.9 software (FIAlab Instruments®). PTFE (0.8 mm i.d.) and PEEK (0.25 mm i.d.) tubing were used in SIA and SIC systems, respectively. Chromatographic separations were performed on a monolithic column (Phenomenex® Onyx™, C18, 50 mm long and 4.6 mm i.d.) with a 5 mm long guard column. Measurements were carried out with a spectrofluorimeter (Varian, Eclipse, Mulgrave, VIC, Australia) equipped with a 40 μL quartz flow cell. The excitation and emission slits were both adjusted to yield a 20 nm resolution and the software provided by the manufacturer was used for data acquisition.

A domestic microwave oven (2450 MHz, 700 W, NN-ST254W, Panasonic, Manaus, Brazil) was used for the flow-batch microwave-assisted extractions of SA and its derivatives, and a water bath with a 1 mL glass chamber was used for hydrolysis of the conjugated forms to free SA. A magnetic stirrer (Mod 753A, Fisatom, Brazil) with temperature control was used to heat the water bath and stir solutions inside the glass chamber. A cryogenic mill (Spex Model 6870, USA) with a self-container liquid nitrogen bath was used for sample grinding.

2.2. Reagents and Solutions

All solutions were prepared with deionized water (resistivity > 18 MΩ cm), analytical grade reagents, and HPLC grade solvents (Merck, Germany). Working solutions from 0.05 to 2.00 mg L−1 salicylic acid were prepared by dilution of a 1.000 g L−1 stock solution in water.

Alkaline and acid solutions used for hydrolysis and extract neutralization were prepared from NaOH and HCl (both from Merck, Germany). A 0.8 mol L−1 acetate buffer solution (pH 5.0) was prepared from sodium acetate (Sigma-Aldrich, USA) with pH adjusted to 5.0 with 1.0 mol L−1 HCl solution. The mobile phase for the chromatographic separation was a 7% v/v acetonitrile in 0.2 mol L−1 acetate buffer solution (pH 5.0) [16].

2.3. Samples

Corn, sugarcane, and soybean leaves were collected from farmers at Piracicaba and Santa Cruz do Rio Pardo, SP, Brazil. Fresh leaves were washed with deionized water, dried at room temperature between paper sheets, grinded in a cryogenic mill for 15 min, and stored in polyethylene flasks in a domestic freezer at −20°C. Just before analyses, samples were stabilized to ambient temperature.

2.4. Flow Diagram and Procedure

The SIA system for online solid sample preparation (Figure 1(a)) was operated as described in Table 1. The grinded sample (500 mg) was introduced into a 50 mL Falcon® tube, which was placed in the center of the microwave oven and used as the flow-batch chamber (extraction reactor). This reactor was connected to the SIA system through two 70 cm long PTFE tubes trespassing the oven wall, for addition of the extractor (deionized water) and aspiration of the extract. A 100 μL micropipette tip with filter was adapted to the aspiration tube for filtration of the extract, as previously proposed [25].

StepValve of syringe pumpSelection valve portTime (s)Volume (μL)Flow rate (μL s−1)

Microwave-assisted extraction
Extractor insertion into reactor30200067
Microwave irradiation390

Washing of the extraction channel
Carrier aspirationIn51000200
Extract aspirationOut21260050
Discard to wasteOut181600200

Crude extract preparation
Carrier aspirationIn51000200
Air aspirationOut81010010
Extract aspirationOut21010010
Buffer aspirationOut455010
HCl aspirationOut52.52510
NaOH aspirationOut32.52510
Extract collectionOut73737010
Channel washingOut74.65930200
Air aspirationOut81020020
Channel emptyOut71020020

Hydrolyzed extract preparation
Carrier aspirationIn51000200
Air aspirationOut81010010
NaOH aspirationOut32.52510
Extract aspirationOut21010010
Transport towards hydrolysis chamberOut62828010
Hydrolysis time300
Hydrolyzed extract aspirationOut62828010
HCl aspirationOut52.52510
Buffer aspirationOut455010
Hydrolyzed extract collectionOut73737010
Channel washingOut74.65930200
Air aspirationOut81020020
Channel emptyOut71020020

Extractor insertion with peristaltic pump.

Microwave-assisted flow-batch extraction was carried out with 2 mL of deionized water introduced in the tube by the peristaltic pump of the SIA system (30 s, 4 mL min−1). The tube was heated during 6.5 min at 140 W, which corresponds to 20% of the maximum microwave power, achieving a final temperature of (54.5 ± 0.5)°C. An aliquot of the extract was used for channel washing prior to collecting and preparing crude and hydrolyzed extracts. Air was used as carrier to minimize cross contaminations and to avoid sample dispersion. For determination of free SA, 100 μL of the extract was aspirated to the holding coil (HC1) together with 50 μL of 0.8 mol L−1 acetate buffer (pH 5.0), 25 μL of 0.5 mol L−1 NaOH, and 25 μL of 0.5 mol L−1 HCl for adjustment of pH and ionic strength. Then, the sample zone was transferred to an Eppendorf® tube for posterior determination by SIC. Subsequently, HC1 was washed with water to prepare the hydrolyzed extract for determination of total SA. Then, 100 μL of the extract and 25 μL of 0.5 mol L−1 NaOH were aspirated to HC1 and transferred to the hydrolyzer reactor placed inside a water bath at (80 ± 2)°C. The solution was stirred for 5 min and the hydrolyzed extract was aspirated to HC1, followed by 25 μL of 0.5 mol L−1 HCl and 50 μL of 0.8 mol L−1 acetate buffer (pH 5.0). Further, the sample zone was transferred to an Eppendorf® tube for total SA determination by SIC.

Crude and hydrolyzed extracts were analyzed with the SIC system (Figure 1(b)) as described by Barrientos et al. [16]. Initially, 3.9 mL of the mobile phase was aspirated to HC2 at 50 μL s−1 followed by 10 μL of the extract. The sample zone was pumped at 10 μL s−1 through the chromatographic column and spectrofluorimetric detection was performed with excitation and emission at 298 and 406 nm, respectively. Measurements were based on peak areas and carried out in duplicate (system optimization) and triplicate (SA fractionation).

2.5. System Optimization

Multivariate optimization was carried out to maximize free and total SA peak areas, which are indicative of the efficiency of analyte extraction and hydrolysis. A sample of sugarcane leaves with a total SA content of 0.4 mg kg−1 previously determined by a reference procedure [18] was used in the optimization step. Maximum and minimum levels of each variable were chosen based on the conditions set for batchwise extraction of SA and hydrolysis of the conjugated forms [18]. The experimental data were processed using the STATISTICA 8.0 software.

A two-level full factorial design (23) was performed to evaluate the effect of the parameters involved in the flow-batch alkaline hydrolysis, that is, hydrolysis time, NaOH concentrations, and temperature (Table S1). Experiments were carried out using 100 μL of the sugarcane leaves extract, prepared from 2.0 g of sample and 8 mL of water according to a batchwise procedure [16]. The peak areas of total SA were taken as indicative of the hydrolysis efficiency. A Doehlert matrix design [26] was used for optimization of the flow-batch microwave-assisted extraction. The extraction time (X1) was evaluated in five levels (2.0, 3.5, 5.0, 6.5, and 8.0 min) and microwave power (X2) was evaluated in three levels (20, 40, and 60%), Table S2. The replicates at the central point were exploited to estimate the experimental, pure, and lack of fit errors. The robustness of the flow-batch procedure under the optimized conditions was evaluated by a 23 full factorial design (hydrolysis step) and by the univariate method (extraction step).

3. Results and Discussion

3.1. General Aspects

The fractionation method exploited in this work is based on the measurement of the intrinsic fluorescence of salicylate ion. Free SA can be directly measured in plant extracts, whereas the total amount is measured after conversion of the conjugated forms to free SA by alkaline hydrolysis [17, 18]. Salicylic acid O-β-glucoside (SAG) and salicyloyl glucose ester (SGE) are examples of SA derivatives [3] that are converted into SA after alkaline hydrolysis and solution acidification as shown in Figure 2.

The conjugated species are then quantified by subtracting the concentration of free SA from the total SA content. Chromatographic separation is required to avoid interferences on determination of salicylate, caused by either other fluorescent species or quenchers in the sample extracts. SA was efficiently separated from the sample matrix of extracts of sugarcane, corn, and soybean fresh leaves by SIC (resolution >1.6 for adjacent peaks) and quantified in retention time of 5 min (Figure 3).

The literature reports different solvents such as water [16], methanol plus ethyl acetate [1], chloroform [10], methanol [1, 4] or ethanol [9], and temperatures (from −20°C to 80°C) [5, 8, 9, 16] for extraction of SA from plant materials. Although convective heating [8] has been exploited, microwave-assisted heating proved to be a reliable and fast approach for extraction of SA and its derivatives using greener solvents, such as water [16] and ethanol/water solutions [6, 18]. In fact, extraction efficiencies were up to 20 and 40% higher for free and total SA, respectively, by comparing microwave-assisted process to convective heating [18].

Alkaline hydrolysis is slower in ethanolic medium than in water, demanding 60 and 5 min to achieve the steady-state, respectively [18]. This is a critical aspect for online hydrolysis of the conjugated forms because of the compromise between the residence time and sample throughput. Based on these aspects and aiming at a more environmentally friendly procedure, water was preferred as extractor in the flow-batch system.

3.2. System Optimization

A two-level full factorial design was carried out in an exploratory study to evaluate the effects of hydrolysis time (X1), NaOH concentration (X2), and temperature (X3), as well as their interactions, on flow-batch alkaline hydrolysis. Peak areas related to total SA were taken as the analytical response (y). From the Pareto chart (Figure 4), it can be concluded that, at 95% confidence level, all variables evaluated as well as the time-temperature and NaOH concentration-temperature interactions affected significantly the hydrolysis efficiency:

The effect of temperature was the most significant. Increasing hydrolysis efficiency with temperature was expected by considering the limited sample residence time and agreed with the results observed in batchwise hydrolysis [18]. The relatively slow hydrolysis of the conjugated species was also evidenced by the positive coefficient related to the reaction time (b1 = +1.03). Hydrolysis is also favored at higher NaOH concentration (b2 = +0.64). Moreover, effects of interactions between time and temperature (b13 = +0.63) and NaOH concentration and temperature (b23 = +0.38) indicate that hydrolysis is favored when all variables are in the highest levels, which correspond to experiment 8 (Table S1). This working condition (0.1 mol L−1 NaOH and hydrolysis at 80°C for 5 min) was selected for further experiments. Despite the full factorial design indicated that a higher response would be achieved, the variables were not evaluated at higher levels because increase of NaOH concentration, time, and temperature could damage the chromatographic column, hinder sample throughput, and promote losses of the solvent and volatile derivatives (e.g., methyl salicylate), respectively.

Preliminary experiments indicated that both microwave power and extraction time affected the extraction of the analytes [18]. Doehlert design was then used to optimize the microwave-assisted extraction of SA and its derivatives from sugarcane leaves (Table S2 shows the seven experiments required). Peak areas for free and total SA were both evaluated as the extraction conditions for the different species may differ significantly. Variation in peak areas for free SA was not significant at 95% confidence level, indicating that any region of the established experimental domain would yield similar results. On the other hand, the regression model for total SA was statistically significant, as evaluated by the analysis of variance (ANOVA), Table S3. In fact, by comparing the Mean Square of Regression (MSR) and Mean Square of Residual (MSr), the F value (Fcal = 53.2) was higher than the tabulated value (Ftab = 9.01) at the 95% confidence level. Moreover, comparing the ratio between Mean Square of lack of fit (MSlof) and Mean Square of pure error (MSpe), Fcal = 0.50, which is lower than Ftab = 18.5, indicating that the proposed model does not present lack of fit, at the 95% confidence level. The good adjust of the proposed model is also evidenced by the coefficient of determination (R > 0.99).

The regression model for the microwave-assisted extraction is described by (2) that presents six coefficients (b0 (constant), b1 (extraction time), b2 (microwave power), , , and b1 × b2) and their confidence intervals (95% confidence level) between parentheses:

In order to maximize peak areas for total SA, the extraction time and the microwave power should be at the highest and lowest levels, respectively. In addition, interaction between these variables was significant. The contour plot of the proposed model is shown in Figure 5, in which the arrow indicate the optimal condition for determination of total SA in plant leaves, that is, extraction with 20% microwave power for 6.5 min that corresponds to the experiment 5 (Table S2).

3.3. Analytical Features and Application

A linear response was achieved from 0.05 to 2.0 mg L−1 of SA, described by the equation peak area = (84 ± 3) (SA) − (0.86 ± 0.03), r = 0.999, in which (SA) refers to salicylic acid concentration in mg L−1. This linear response range corresponds to 0.4 to 16 mg kg−1 SA in the plant leaves under the set conditions. The limit of detection (LOD) was estimated as 0.01 mg L−1 (equivalent to 0.1 mg kg−1 of SA in fresh samples) according to IUPAC recommendations [27]. The coefficient of variation was 3.0% (n = 10) and variations of the analytical response between days were lower than 5.0%. The proposed procedure consumed only water for extraction of the analytes and as low as 1 mg NaOH, 2 μL of 37% m/v HCl, and 6.6 mg of sodium acetate per sample for SA fractionation. The waste volume for determination of both fractions is 2.2 mL and sample throughput was estimated as 4 h−1. For comparison, the batch procedure for SA fractionation [18] consumes 6 mL of ethanol, 2 mg NaOH, 4 μL of 37% m/v HCl, and 0.5 μL H3PO4 85% m/v per sample and generates 9.6 mL of waste per sample. It also demands 60 min to promote the alkaline hydrolysis, in comparison to 5 min in the flow-batch procedure. However, a set of extracts can be simultaneously hydrolyzed in the batch procedure. Consumption of acetonitrile per determination was 10-fold lower in SIC in comparison to HPLC [18].

A robustness test was performed using a 23 factorial design with variation of ±10% in relation to the optimum parameters defined on the hydrolysis step, that is, 0.1 mol L−1 NaOH and 5 min at 80°C. The ANOVA from the results in Table 2 indicated that the procedure is robust in relation to the hydrolysis step.

ExperimentNaOH (mol L−1)Hydrolysis time (min)Temperature (°C)Peak area of total SAa

1−1 (0.09)−1 (4.5)−1 (70)5.90
21 (0.11)−1 (4.5)−1 (70)5.66
3−1 (0.09)1 (5.5)−1 (70)7.06
41 (0.11)1 (5.5)−1 (70)5.70
5−1 (0.09)−1 (4.5)1 (90)7.07
61 (0.11)−1 (4.5)1 (90)6.31
7−1 (0.09)1 (5.5)1 (90)5.35
81 (0.11)1 (5.5)1 (90)5.90

aMean values of duplicate measurements.

The robustness test related to the extraction step was carried out in a univariate manner because it was not possible to range microwave power on 10% in a commercial oven in relation to optimum condition (i.e., 18 and 22%). Results obtained for microwave power of 10 and 20% and extraction time from 6.0 to 8.0 min did not differ significantly at 95% confidence level. Thus, the flow-batch system, under the optimized conditions, is also robust in relation to the extraction step.

For accuracy assessment, sugarcane, corn, and soybean leaves previously analyzed by batch procedures for free [16] and total SA [18] determination were assayed by the flow-batch sample preparation procedure (Table 3). The mean values agreed and the variances were not significantly different, according to statistical tests (F-test and paired t-test) both at the 95% confidence level. Acceptable precision was achieved for the sample extracts, with CV from 2.6 to 17% (Table 3). The high contents of free SA on soybean leaves were expected because these plants were on development, while sugarcane and corn were mature plants.

SamplesSpeciesContent (mg kg−1)F-values
ProposedReference [16]

Sugarcane leavesFree SA0.29 ± 0.050.30 ± 0.026.2
Total SA0.38 ± 0.010.31 ± 0.011.0
Corn leavesFree SA0.18 ± 0.030.16 ± 0.022.2
Total SA0.89 ± 0.040.9 ± 0.16.2
Soybean leavesFree SA11.4 ± 0.311 ± 111
Total SA12 ± 111.2 ± 0.311

Fcritical (95% confidence level): 19.

4. Conclusions

The proposed flow-batch sample preparation system is a reliable approach for online fractionation of SA on plant leaves. System was able to handle solid samples in a sequential injection analysis system without clogging and using ordinary laboratorial devices (flasks and a pipette tip with filter). All sample preparation steps were performed in a closed system, which avoids analytical errors due to sample contamination and analyte losses. The flow-batch approach was successfully exploited to improve interaction of the solid sample with the extractor as well as providing the required residence times needed to analyte extraction and hydrolysis. Extractions were carried out with deionized water and minimal reagent amounts were consumed in the hydrolysis of the conjugated species, which are in agreement with Green Analytical Chemistry principles. Fractionation of each sample takes about 15 min, which is in compliance with the high analytical demand for SA fractionation in agronomic studies. The developed procedure is a simple, environmentally friendly, and suitable alternative for routine analysis, which is potentially useful for other applications involving microwave-assisted extraction and analyte fractionation.

Data Availability

The data used to support this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.


The authors thank the fellowships and financial support from the Brazilian agencies São Paulo Research Foundation (FAPESP), (2016/25333-0), National Council of Technological and Scientific Development (CNPq), (424080/2016-8 and 309581/2017-6), and Coordination for the Improvement of Higher Education Personnel (CAPES) (Finance Code 001). This is a contribution of the National Institute of Advanced Analytical Sciences and Technology (INCTAA).

Supplementary Materials

Supplementary material includes further information on the optimization of the alkaline hydrolysis (full-factorial design, Table S1) and of SA extraction (Doehlert design, Table S2) and ANOVA parameters for the quadratic model (Table S3). (Supplementary Materials)


  1. Z. H. Huang, Z. L. Wang, B. L. Shi et al., “Simultaneous determination of salicylic acid, jasmonic acid, methyl salicylate, and methyl jasmonate from Ulmus pumila leaves by GC-MS,” International Journal of Analytical Chemistry, vol. 2015, Article ID 698630, 7 pages, 2015. View at: Publisher Site | Google Scholar
  2. A. Figueiredo, F. Monteiro, and M. Sebastiana, “First clues on a jasmonic acid role in grapevine resistance against the biotrophic fungus Plasmopara viticola,” European Journal of Plant Pathology, vol. 142, pp. 645–652, 2015. View at: Publisher Site | Google Scholar
  3. A. C. Vlot, D. A. Dempsey, and D. F. Klessig, “Salicylic acid, a multifaceted hormone to combat disease,” Annual Review of Phytopathology, vol. 47, no. 1, pp. 177–206, 2009. View at: Publisher Site | Google Scholar
  4. K. Floková, D. Tarkowská, O. Miersch, M. Strnad, C. Wasternack, and O. Novák, “UHPLC-MS/MS based target profiling of stress-induced phytohormones,” Phytochemistry, vol. 105, pp. 147–157, 2014. View at: Publisher Site | Google Scholar
  5. L.-J. Sun, Z.-Q. Pan, J. Xie et al., “Electrocatalytic activity of salicylic acid on Au@Fe3O4 nanocomposites modified electrode and its detection in tomato leaves infected with Botrytis cinerea,” Journal of Electroanalytical Chemistry, vol. 706, pp. 127–132, 2013. View at: Publisher Site | Google Scholar
  6. N. Uddin, C. Krieg, W. Stöggl et al., “Quantitative analysis of salicylic acid and its derivatives in primulae radix by high performance liquid chromatography-diode array detection-electrospray ionization mass spectrometry (HPLC-DAD-ESI-MS) and simultaneous determination of total polyphenol co,” Current Analytical Chemistry, vol. 10, pp. 271–279, 2014. View at: Publisher Site | Google Scholar
  7. M. de Sá, J. P. Ferreira, V. T. Queiroz et al., “A liquid chromatography/electrospray ionisation tandem mass spectrometry method for the simultaneous quantification of salicylic, jasmonic and abscisic acids in Coffea arabica leaves,” Journal of the Science of Food and Agriculture, vol. 94, pp. 529–536, 2014. View at: Publisher Site | Google Scholar
  8. A. Toiu, L. Vlase, I. Oniga, D. Benedec, and M. Tǎmaş, “HPLC analysis of salicylic derivatives from natural products,” Farmacia, vol. 59, pp. 106–112, 2011. View at: ǎmaş&publication_year=2011" target="_blank">Google Scholar
  9. V. Gupta, M. Kumar, H. Brahmbhatt, C. R. K. Reddy, A. Seth, and B. Jha, “Simultaneous determination of different endogenetic plant growth regulators in common green seaweeds using dispersive liquid-liquid microextraction method,” Plant Physiology and Biochemistry, vol. 49, no. 11, pp. 1259–1263, 2011. View at: Publisher Site | Google Scholar
  10. C. Deng and K. Words, “Rapid determination of salicylic acid in plant materials by gas chromatography–mass spectrometry,” Chromatographia, vol. 58, pp. 225–229, 2003. View at: Google Scholar
  11. W. R. Melchert, B. F. Reis, and F. R. P. Rocha, “Green chemistry and the evolution of flow analysis. A review,” Analytica Chimica Acta, vol. 714, pp. 8–19, 2012. View at: Publisher Site | Google Scholar
  12. P. Chocholouš, P. Solich, and D. Šatínský, “An overview of sequential injection chromatography,” Analytica Chimica Acta, vol. 600, no. 1-2, pp. 129–135, 2007. View at: Publisher Site | Google Scholar
  13. A. D. Batista, C. F. Nascimento, W. R. Melchert, and F. R. P. Rocha, “Expanding the separation capability of sequential injection chromatography: determination of melamine in milk exploiting micellar medium and on-line sample preparation,” Microchemical Journal, vol. 117, pp. 106–110, 2014. View at: Publisher Site | Google Scholar
  14. A. M. Idris and A. O. Alnajjar, “Native fluorescent detection with sequential injection chromatography for doping control analysis,” Chemistry Central Journal, vol. 7, no. 1, p. 144, 2013. View at: Publisher Site | Google Scholar
  15. L. B. O. Santos, C. M. C. Infante, and J. C. Masini, “Determination of picloram in waters by sequential injection chromatography with UV detection,” Journal of the Brazilian Chemical Society, vol. 21, no. 8, pp. 1557–1562, 2010. View at: Publisher Site | Google Scholar
  16. M. O. Barrientos, A. D. Batista, and F. R. P. Rocha, “Fast and environmentally friendly determination of salicylic acid in plant materials by sequential injection chromatography,” Anal. Methods, vol. 8, pp. 6398–6403, 2016. View at: Publisher Site | Google Scholar
  17. M. N. Irakli, V. F. Samanidou, C. G. Biliaderis, and I. N. Papadoyannis, “Development and validation of an HPLC-method for determination of free and bound phenolic acids in cereals after solid-phase extraction,” Food Chemistry, vol. 134, no. 3, pp. 1624–1632, 2012. View at: Publisher Site | Google Scholar
  18. T. L. Marques, L. M. B. Moraes, and F. R. P. Rocha, “Systematic evaluation of sample preparation for fractionation of phytohormone salicylic acid in fresh leaves,” Talanta, vol. 208, p. 120352, 2020. View at: Publisher Site | Google Scholar
  19. T. L. Marques, J. A. Nóbrega, and F. R. P. Rocha, “Flow-based solid sample preparation: advantages, limitations, and challenges,” TrAC Trends in Analytical Chemistry, vol. 118, pp. 677–685, 2019. View at: Publisher Site | Google Scholar
  20. M. Rosende and M. Miró, “Recent trends in automatic dynamic leaching tests for assessing bioaccessible forms of trace elements in solid substrates,” TrAC Trends in Analytical Chemistry, vol. 45, pp. 67–78, 2013. View at: Publisher Site | Google Scholar
  21. J. Liu, M. Sandahl, P. J. R. Sjöberg, and C. Turner, “Pressurised hot water extraction in continuous flow mode for thermolabile compounds: extraction of polyphenols in red onions,” Analytical and Bioanalytical Chemistry, vol. 406, no. 1, pp. 441–445, 2014. View at: Publisher Site | Google Scholar
  22. J. You, S. Gao, H. Jin, W. Li, H. Zhang, and A. Yu, “On-line continuous flow ultrasonic extraction coupled with high performance liquid chromatographic separation for determination of the flavonoids from root of Scutellaria baicalensis Georgi,” Journal of Chromatography A, vol. 1217, pp. 1875–1881, 2010. View at: Publisher Site | Google Scholar
  23. L. Wu, M. Hu, Z. Li et al., “Dynamic microwave-assisted extraction combined with continuous-flow microextraction for determination of pesticides in vegetables,” Food Chemistry, vol. 192, pp. 596–602, 2016. View at: Publisher Site | Google Scholar
  24. P. H. G. D. Diniz, L. F. Almeida, D. P. Harding, and M. C. U. Araújo, “Flow-batch analysis,” TrAC Trends in Analytical Chemistry, vol. 35, pp. 39–49, 2012. View at: Publisher Site | Google Scholar
  25. T. L. Marques and J. A. Nóbrega, “Fast and simple flow-batch extraction procedure for screening of macro and micronutrients in dried plant leaves by ICP OES,” Microchemical Journal, vol. 134, pp. 27–34, 2017. View at: Publisher Site | Google Scholar
  26. D. H. Doehlert, “Uniform shell designs,” Applied Statistics, vol. 19, pp. 231–239, 1970. View at: Publisher Site | Google Scholar
  27. L. A. Currie, “Nomenclature in evaluation of analytical methods including detection and quantification capabilities1 (IUPAC recommendations 1995),” Analytica Chimica Acta, vol. 391, pp. 105–126, 1999. View at: Publisher Site | Google Scholar

Copyright © 2020 Thiago L. Marques et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.