We present foliar biogenic volatile organic compound (BVOC) emission data from 24-h heat-stressed tomato (Solanum lycopersicum) seedlings including speciated monoterpenes and sesquiterpenes and high time-resolution measurements of methyl salicylate and total monoterpenes. The median total monoterpene and total sesquiterpene emission rates at 30°C were 18.5 and 0.172 pmol m–2 s–1, respectively, which falls within the negligible emission category of previous studies. However, initial heat exposure (39°C or 42°C) increased the emissions of approximately half of the targeted compounds beyond what was predicted by current BVOC emission temperature response algorithms. The enhanced emissions were not always sustained for the entire duration of the heat stress and some plants exhibited a delayed monoterpene response, where emissions peaked toward the end of the heat treatment. Methyl salicylate, a known stress marker, responded differently to the heat stress than most of the other compounds. Heat stress increased methyl salicylate emissions in some plants (at least initially), but in others, emissions declined or did not change significantly. There was no significant correlation between the magnitude of gene expression and emission induction of monoterpenes or methyl salicylate. Furthermore, the emitted monoterpenes did not exhibit any apparent light-dependent behavior, which suggests that these monoterpene stress emissions mostly originated from light-independent foliar storage pools and not from increased de novo production. In contrast, methyl salicylate emissions appear to have contributions from both de novo synthesis and stored pools, as they showed both enzyme-controlled (i.e., light-dependent) and light-independent behaviors. Analyses of the foliar essential oils demonstrate that most of the emitted BVOCs were also present in stored pools. The pool sizes were generally large enough to sustain unstressed emission levels for days to months, and even years for some compounds. However, heat-induced emission enhancement can diminish the pool sizes of some BVOCs, which could decrease subsequent emissions.

Plants emit a diverse range of biogenic volatile organic compounds (BVOCs) into the atmosphere, including terpenes, alkanes, alkenes, aldehydes, ketones, alcohols, and esters (Penuelas and Llusia, 2003; Seco et al., 2007), and these emissions are the dominant source of atmospheric VOCs (Guenther et al., 1995). The global mean annual total BVOC flux is estimated to be between 760 and 1000 Tg C yr–1 based on the simulation runs of the Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1), with isoprene constituting the bulk of the emissions (70%), followed by monoterpenes (MTs; 11%), methanol (6%), acetone (3%), sesquiterpenes (SQTs; 2.5%), and other BVOCs (<2% each; Guenther et al., 2012; Sindelarova et al., 2014). Many BVOCs have high chemical reactivities and some have high secondary organic aerosol (SOA) yields and contribute to ozone and SOA production, which can influence climate and radiative forcing on a regional to global scale (Penuelas and Staudt, 2010). Therefore, accurate estimations of BVOC emissions are needed to advance predictions of current and future climate scenarios. The magnitude of BVOC emissions is modulated by environmental conditions, principally light and temperature, and by external stresses (e.g., heat, drought, ozone; Loreto and Schnitzler, 2010). Both temperature and light-dependency effects for isoprene and MTs have been integrated into current emission models, for example, MEGANv2.1 (Guenther et al., 2012; Oderbolz et al., 2013). These models perform well in characterizing the emission behavior of constitutive terpenoids at unstressed temperatures (less than approximately 35°C; Guenther et al., 1993), but tend to underestimate the emission response of stored MTs from heat-stressed plants, as they do not account for the elicitation of some stress-induced emissions, for example, from ruptured resin ducts in conifers (Kleist et al., 2012). In contrast, the emission of de novo MTs from heat-stressed plants can be lower than that predicted by these models (Kleist et al., 2012). Furthermore, the temporal variability in the stress response adds another layer of complexity in modeling the emission behavior, for example, heat stress may increase emissions in the short term, but then induce a reduction in the longer term (Pazouki et al., 2016). It is evident that we still have an inadequate understanding of the emission behavior of plants under heat stress. The increasing prevalence of heat wave events (Perkins et al., 2012; Perkins-Kirkpatrick and Lewis, 2020) and the projected increase in global temperatures (Tollefson, 2020) underscore the importance of improving the accuracy of model estimates of emissions from heat-stressed vegetation.

The bulk of the effort to quantify BVOC emissions for atmospheric chemistry modeling has been focused on woody plants (e.g., coniferous, broadleaf, evergreen, and deciduous trees). Relatively fewer studies have been conducted on crop plants, as they generally produce lower emissions (Gentner et al., 2014; Okereke et al., 2021), and are therefore expected to have a smaller impact on atmospheric chemistry. We sought to investigate if a low-emitting crop could transform into a high emitter under heat stress. Tomato (Solanum lycopersicum) was chosen as a representative crop species, since previous studies had indicated that it is a low BVOC emitter in ambient conditions (Table 1; Section 3.1.1). Furthermore, tomato plants have a wide global distribution due to their economic value (Costa and Heuvelink, 2018). Two previous studies have explored the effects of heat stress on tomato foliar BVOC emissions: Copolovici et al. (2012) and Pazouki et al. (2016). In both studies, a transient (5 min) heat shock was applied by temporarily immersing the leaves in a temperature-controlled water bath. The BVOC emission response was subsequently measured at regular intervals after allowing for a short equilibration period. In our study, the whole plant was placed in a walk-in, temperature-controlled environmental chamber to simulate a more realistic heat wave event over a longer period (24 h). The plants were heat-stressed at temperatures, 39°C or 42°C, that occur in heat wave events in some regions. Rivero et al. (2001) grew tomato plants at different temperatures (15°C, 25°C, and 35°C) for 30 days and showed that the physiological effects of heat stress began to manifest at 35°C as indicated by reduced shoot biomass at the end of the growing period and accumulation of phenolics in the plant tissue. Accordingly, exposure to 39°C or 42°C for 24 h is likely above the temperature threshold for heat stress in tomato plants.

Table 1.

Range of reported tomato foliar BVOC emission rates based on direct enclosure measurements from 8 different studies. DOI: https://doi.org/10.1525/elementa.2021.00096.t1

Emission Rates (pmol m–2 s–1)a
Major BVOCsΣ MTΣ SQTSample SizeTemperature (°C)bStudy
β-Phellandrene 868–1560 1290–2200 1.84–6.12 1–3 35–38 Arey et al. (1991)
2-Carene 386–573
α-Pinene 33.8–52.1
β-Phellandrene NR 6.97–73.0 NR 18 18 Jansen et al. (2009)
2-Carene
Limonene
α-Phellandrene
α-Pinene
β-Phellandrene NR 5.00–100 <1.00 30 Copolovici et al. (2012)
2-Carene
β-Phellandrene 43.8–91.3 58.4–122 3.57–6.00 7 (MT) 27 Gentner et al. (2014)
2-Carene 8.18–17.0   3 (SQT)
α-Phellandrene 4.09–8.52
β-Phellandrene 3.21–21.6 17.5–74.7 0.070–1.01 ≥ 3 25 Pazouki et al. (2016)
β-Phellandrene NR 49.5–330 NR 25 Tomescu et al. (2017)
2-Carene
β-Phellandrene BDL–55.8 32.5–108 3.28–11.5 32–48 30 Dehimeche et al. (2021)
2-Carene BDL–19.3
α-Pinene 1.47–25.1
Linalool BDL–22.4
β-Phellandrene BDL–14.8 0.287–57.0 BDL–19.6 10 30 This studyc
2-Carene BDL–17.7
Limonene BDL–5.89
α-Phellandrene BDL–18.3
α-Pinene 0.252–4.98
TMTT BDL–118
Emission Rates (pmol m–2 s–1)a
Major BVOCsΣ MTΣ SQTSample SizeTemperature (°C)bStudy
β-Phellandrene 868–1560 1290–2200 1.84–6.12 1–3 35–38 Arey et al. (1991)
2-Carene 386–573
α-Pinene 33.8–52.1
β-Phellandrene NR 6.97–73.0 NR 18 18 Jansen et al. (2009)
2-Carene
Limonene
α-Phellandrene
α-Pinene
β-Phellandrene NR 5.00–100 <1.00 30 Copolovici et al. (2012)
2-Carene
β-Phellandrene 43.8–91.3 58.4–122 3.57–6.00 7 (MT) 27 Gentner et al. (2014)
2-Carene 8.18–17.0   3 (SQT)
α-Phellandrene 4.09–8.52
β-Phellandrene 3.21–21.6 17.5–74.7 0.070–1.01 ≥ 3 25 Pazouki et al. (2016)
β-Phellandrene NR 49.5–330 NR 25 Tomescu et al. (2017)
2-Carene
β-Phellandrene BDL–55.8 32.5–108 3.28–11.5 32–48 30 Dehimeche et al. (2021)
2-Carene BDL–19.3
α-Pinene 1.47–25.1
Linalool BDL–22.4
β-Phellandrene BDL–14.8 0.287–57.0 BDL–19.6 10 30 This studyc
2-Carene BDL–17.7
Limonene BDL–5.89
α-Phellandrene BDL–18.3
α-Pinene 0.252–4.98
TMTT BDL–118

NR = not reported; BDL = below detection limit; BVOC = biogenic volatile organic compound; MT = monoterpene; SQT = sesquiterpene; TMTT = trimethyltridecatetraene.

a Emission rates were normalized to 30°C (if they were not already) for comparability.

b The enclosure temperatures during measurements are reported.

c This study: Only emission data from the plants sampled at 30°C is included in the reported emission range. Emission values from Husky Cherry 1 and Early Girl 1 are omitted, as explained in the text.

The overall objective of our study was to investigate the emission response of tomato foliar BVOCs to heat stress and to determine whether the changes in emissions with temperature followed current model predictions. When the observed emissions differed from model estimates, we attempted to determine the source(s) of the stress-induced emissions, that is, either from foliar storage pools or from increased de novo production or both. We used a proton transfer reaction-mass spectrometer (PTR-MS) to acquire high time-resolution methyl salicylate (MeSA) and total MT measurements to deduce the temporal pattern in the emission response to heat stress. We also utilized an offline gas chromatograph (GC) to obtain periodic speciated terpenoid measurements; a total of 31 compounds were targeted for emission quantification. To our knowledge, high time-resolution BVOC emission data from tomato foliage has not previously been reported. To investigate possible changes in de novo BVOC production rates, a subset of the sampled plants was selected for gene expression measurements. Additionally, we used the observed changes in daytime and nighttime emission rates (ERs) to estimate the fractions of light-dependent (i.e., de novo-synthesized) and light-independent (i.e., storage-derived) BVOC emissions. Finally, we analyzed the BVOC content in the essential oils of a separate set of tomato plants to determine their foliar BVOC storage pool sizes. The measured pool sizes indicated the potential contribution of storage-derived emissions and informed if the pool capacity was sufficient to sustain the observed rates of heat stress-enhanced emissions.

### 2.1. Plant material

The BVOC emission rates from 18 individual tomato (Solanum lycopersicum) seedlings were measured in this study. These potted seedlings were from 9 different cultivated varieties (cultivars): Roma, Tami-G grape, Cherokee Purple, Red Beefsteak, Juliet (Roma Grape Hybrid), Summer Set, Early Girl, Husky Cherry Red, and Black Cherry. The seedlings were purchased from a commercial source (Bonnie Plants, Pala, CA, USA) and were 9–10 weeks old. They were moved into an environmental chamber (see Section 2.2) at least 2 weeks prior to the start of measurements. Two hundred milliliters of water was added daily to each plant prior to and during the measurement period. A different set of 8 tomato plants consisting of 4 Roma and 4 Beefsteak plants were grown from seeds (Ohio Heirloom Seeds, Columbus, OH, USA) for essential oil extraction and analysis (see Section 2.7). The seeds were germinated and grown in an environmental chamber with a temperature of 25°C, relative humidity of 45%, and a 12-h photocycle. The essential oil extraction was conducted when the 8 seedlings were 8–10 weeks old. The height of the seedlings from both sets was in the range of 25–35 cm. All the seedlings used in the VOC emissions study appeared to be in a similar developmental stage and none of the seedlings were flowering or bearing fruit at the time of the experiment.

### 2.2. Gas exchange and environmental control system

The heat stress-VOC emissions experiments were conducted in a walk-in (length: 2.5 m, width: 2.5 m, height: 2.5 m, volume: 15.625 m3) environmental chamber (Model MAT-G1HD-9X9; Darwin Chambers Co., Saint Louis, MO, USA) located in the basement of Croul Hall at the University of California, Irvine. The chamber is a semi-isolated system with minimal mixing between the air inside the chamber and the laboratory air outside. An integrated environmental control system allows for stable control of the temperature and relative humidity within the chamber. The VOC emissions from 3 individual tomato plants were measured concurrently during each experiment. The plants were enclosed in flexible, transparent, 5-gallon (approximately 18.9 L) Teflon PFA bag enclosures (Part number: P-00126; Welch Fluorocarbon, Inc., Dover, NH, USA) with a wall thickness of 0.002 inches (approximately 0.05 mm). A fourth empty Teflon enclosure served as a “blank” to provide background VOC, CO2, and H2O measurements. Each plant in the environmental chamber was illuminated artificially using LED growth lamps (Model Pro 325; LumiGrow, Inc., Emeryville, CA, USA). The lamps are composed of red, blue, and white LEDs, and their irradiance pattern closely approximates the photosynthetically active radiation spectrum of natural sunlight. The photosynthetic photon flux density incident upon the plants was approximately 500 µmol m–2 s–1, as measured inside the enclosures. We simulated a simple 12-h photocycle by programming the LED lamps to activate at 8 AM and to switch off at 8 PM daily. A type “K” thermocouple sensor (OMEGA Engineering, Inc., Norwalk, CT, USA) was inserted into each enclosure (including the blank) to measure the air temperature inside. The thermocouple wires were insulated with PFA to ensure inertness.

An ultra-high purity (UHP) zero air generator (Model 747-30; Aadco Instruments, Cleves, OH, USA) was used to deliver the influent VOC-free air into the enclosures. Since the zero air generator removes most of the CO2 from the input air, CO2 was readded into the air stream from a pure CO2 cylinder (99.999%; Part number: CD RP200; Airgas Specialty Gases, Chicago, IL, USA). The flow rate of the pure CO2 was controlled using a digital mass flow controller (MFC; Model GE50A; MKS Instruments, Inc., Andover, MA, USA) to obtain a diluted CO2 mole fraction of approximately 400 µmol mol–1 in the mixed air. An inline static tube mixer (Part number: Stratos 1/4-34; Koflo Corporation, Cary, IL, USA) was used to aid in the mixing of the CO2 and the zero air before the mixed air was split onto 4 separate 1/4 inch outer diameter PFA inlet lines that were each connected to one of the four Teflon enclosures. Stainless steel restriction orifices (O’Keefe Controls Co., Trumbull, CT, USA) were placed upstream of each of the 4 inlet lines to provide flow control. The flow rate into each enclosure was slightly different due to variations in the lengths of the inlet lines connecting the restriction orifices to the enclosures. Mass airflow sensors (Model AWM5102VN; Honeywell, Inc., Golden Valley, MN, USA) were installed in-line and upstream of each enclosure to continually measure the actual flow rate into the individual enclosures. The sensors were calibrated using a primary gas flow calibrator (Model Defender 510-H; Mesa Laboratories, Inc., Lakewood, CO, USA). The typical flow rate into each enclosure was approximately between 3.5 and 3.9 L/min.

The outlet line from each of the 4 enclosures runs out of the environmental chamber and into a vacuum pump (Model DOA-P704; Gast Manufacturing, Inc., Benton Harbor, MI, USA); the 4 outlet lines were bundled together inside several contiguous lengths of Buna-N/PVC closed-cell foam insulation tubing and were heated to a temperature of 43°C–44°C using a self-regulating heating cable (Model W51; Pentair Thermal Management, Houston, TX, USA) to inhibit the condensation of water vapor and to prevent higher boiling point VOCs from sticking to the inner walls of the flow lines. The vacuum pump ensured that the outlet flow lines were continuously flushed. Part of the airflow from each outlet line was diverted into a PEEK sample manifold (Model P-151; IDEX Health & Science, Oak Harbor, WA, USA). A 2-way, normally closed solenoid valve (Model EW-01540-02; Cole-Parmer Instrument Co., Vernon Hills, IL, USA) was installed between each outlet line and the sample manifold. These 4 solenoid valves are constructed of inert PTFE, have low dead volumes, and short response times (20 ms). The manifold–valve assembly was encased in a heated (43°C–44°C), thermally insulated enclosure. Each solenoid valve was independently actuated by a 167 mA at 24 VDC electrical signal that was supplied through a power switching board (Model PS12DC; LabJack Corporation, Lakewood, CO, USA) coupled to an external 24 VDC power supply and mounted on a LabJack data acquisition and automation module (Model T7-Pro; LabJack Corporation). The outlet port of the sample manifold was connected to a CO2/H2O infrared gas analyzer (IRGA; see Section 2.5) and to a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS; see Section 2.4.2). The LabJack module was programmed to sequentially actuate each solenoid valve to allow consecutive sampling of the blank enclosure and the 3 plant enclosures by the IRGA and the PTR-TOF-MS. Besides controlling valve actuation, the LabJack module continually logged sensor data (at a frequency of 1 Hz) from the enclosure thermocouples and mass airflow sensors. A portion of the airflow from each outlet line was also periodically diverted to a small, portable pump for sampling onto sorbent cartridges (see Section 2.4).

### 2.3. Experimental protocols

The tomato heat stress experiments presented in this study were conducted between July 20, 2020, and September 22, 2020, and were performed on 3 plants at a time. An initial survey-type study was conducted on 12 tomato plants from 9 different cultivars. In the survey study, the control (i.e., preheat treatment) temperature was set to 30°C, and the heat treatment was performed at 42°C for 24 h, typically starting at approximately 12 PM. The plants were enclosed and the BVOC emission measurements were started 1–2 days prior to the commencement of the heat stress and were continued throughout the duration of the heat stress. For some of these seedlings, BVOC ERs were also measured during the post-stress recovery period (at 30°C) for approximately 24 h following the end of the heat treatment.

Six more Roma tomato seedlings were selected for a second heat stress study. Three of the Roma seedlings were designated as control plants (Roma C1, C2, and C3), while the other 3 were exposed to heat stress (Roma HS1, HS2, and HS3). The duration of the heat treatment was the same as for the survey study (24 h). However, the heat stress temperature was lowered to 39°C, while the control temperature was set to 25°C. The leaves from the 6 Roma seedlings were harvested at the end of the experiment for gene expression analysis via the quantitative real time polymerase chain reaction (qRT-PCR) method (see Section 2.6).

### 2.4. VOC sampling and analysis

A portable sampling pump (Model Gilian GilAir Plus STP; Sensidyne LP, St. Petersburg, FL, USA) was used to pull a known volume of air from the outlet line of each plant enclosure and onto multibed stainless steel cartridges packed with Tenax TA and Carbograph 5TD, with quartz wool separating the 2 adsorbents (Part number: C3-AXXX-5304; Markes International Ltd, Llantrisant, UK). The sorbent cartridge was positioned in between the enclosure outlet and the pump. This configuration ensures that the VOCs in the sample air do not pass through (and therefore do not interact with) the pump, thereby preserving sample integrity. Blank (i.e., background) samples were collected from the blank Teflon enclosure for each sampling day to characterize the background level of BVOCs in the sampling system. This background BVOC level was subtracted from the BVOC amount fractions measured in the effluent air from each plant enclosure, as illustrated in Equation 1. The background BVOC amount fractions typically ranged between 0% and 4% of the amount fractions from the plant enclosures.

A 1-L sample volume was pulled from each enclosure at a flow rate of 100 mL/min. Prior to sampling, the sorbent cartridges were first conditioned to remove any trace amounts of VOCs that may have carried over from previous samples. Cartridge conditioning was carried out by flowing UHP nitrogen gas through each cartridge and heating it at 330°C for 30 min. Once the conditioning process was completed, the cartridges were capped with brass storage caps to restrict the passive diffusion of contaminants from the laboratory air into the cartridges. After sampling, the cartridges were promptly analyzed on our thermal desorption–gas chromatography with mass spectrometry and flame ionization detector (TD-GC-MS/FID) system (see Section 2.4.1), otherwise they were kept under refrigeration (2°C–3°C) until the GC-MS system was ready for cartridge analysis. BVOC ERs, normalized to leaf surface area (E, pmol m–2 s–1) were then calculated based on Equation 1 (Niinemets et al., 2011; Harley et al., 2014):

$E=(Cout−Cin)ALF,$
1

where Cout and Cin (pmol/m3) are the concentrations of the BVOC of interest in the air leaving and entering the plant enclosure, respectively. In our gas exchange system, the value of Cin is characterized by the concentration of the relevant BVOC measured in the air exiting the blank enclosure (i.e., background BVOC level). F (m3/s) is the airflow rate into the plant enclosure and AL (m2) is the total enclosed, one-sided leaf surface area, which was determined according to the following protocols. All the leaves enclosed within each plant enclosure were harvested at the conclusion of each stress experiment. The leaves were photographed together with a 2 cm by 2 cm, red-colored reference square that was placed in the same plane as the leaves. The reference square acted as a scale to calibrate the area of the leaves. The batch of digital images was then uploaded onto a computer and an open-source digital image analysis program (Easy Leaf Area; University of California at Davis, CA, USA) was used to batch-process the images and rapidly calculate the leaf areas. The methodology and digital protocols employed by the processing software is further detailed in Easlon and Bloom (2014). Afterward, the leaves were oven-dried at 70°C for 72 h and were subsequently weighed using an electronic mass balance (Model Practum513-1S; Sartorius GmbH, Goettingen, Germany) to obtain their dry weight. Dry weight values were not obtained for the leaves from the 6 Roma seedlings (Roma C1, C2, C3, HS1, HS2, and HS3) since these leaves were used for gene expression analysis (see Section 2.6).

The overall combined uncertainty in the reported ERs is estimated to be approximately 11%–16% and approximately 18% for GC-MS and PTR-MS-measured values, respectively, which are comparable to those reported in other BVOC studies (Harley et al., 2014; Kajos et al., 2015; McKinney et al., 2019); Equation S1 in the Supplemental Material describes the calculation of the overall uncertainty. The individual contributions to the overall uncertainty include uncertainties in leaf area measurements (2%), airflow rate into the plant enclosure (3%), sample volume (2%; for GC-MS measurements only), and BVOC amount fractions (10%–15% depending on compound for GC-MS measurements and 18% for MT measurements via PTR-MS).

#### 2.4.1. Thermal desorption–Gas chromatography with mass spectrometry and flame ionization detector

Sampled sorbent cartridges were thermally desorbed using a TD autosampler (Model ULTRA-xr; Markes International Ltd) at 285°C for 6 min. Prior to desorption, the cartridges were first prepurged with helium gas for 3 min to remove oxygen and any trace amounts of water that may be present. The analytes from the desorbed cartridges were preconcentrated at 10°C on a focusing trap (Part number: U-T12ME-2S, material emissions, C4–C32; Markes International Ltd). The focusing trap was subsequently flash-heated from 10°C to 290°C in 2–3s; the trap was held at 290°C for 3 min to ensure that all VOCs were desorbed from the trap. A portion of the desorbed sample (50%) was injected into a GC (Model 7890B; Agilent Technologies Inc., Santa Clara, CA, USA) through a 1 m heated transfer line; the remainder of the sample was vented through a split vent. A 60 m Rxi-624Sil MS (mid-polar stationary phase) chromatographic column (Restek Corporation, Bellefonte, PA, USA) with an internal diameter of 0.32 mm and a film thickness (df) of 1.80 µm was used for compound separation in conjunction with helium as the carrier gas. The GC oven temperature program used in our analyses can be summarized as follows: initial temperature, 35°C; 5 min hold; Ramp 9°C/min to 280°C; and 5 min hold (total GC runtime was 37.22 min). The GC was operated in a “constant flow” mode with the column flow rate set to 5 mL/min. A built-in electronic pneumatic control unit regulated the column head pressure as the oven temperature was ramped to hold the column flow rate constant throughout the GC run. The eluate from the outlet of the GC column was split equally onto a flame ionization detector (FID) and an electron impact ionization TOF-MS (Model BenchTOF-Select; Markes International Ltd). The TOF-MS was operated at an ionization energy of –70 eV and was used for compound identification and quantitation. Blank cartridges were run periodically to characterize the background level of VOCs in the system. To account for variations in TOF-MS sensitivity, we routinely calibrated the system by analyzing sorbent cartridges loaded with a known amount of an α-pinene gas-phase calibration standard (Apel-Riemer Environmental, Inc., Miami, FL, USA; cylinder no.: D479201; α-pinene mole fraction: 931 nmol mol–1; analysis date: October 24, 2017). The gas stream from the calibration cylinder was passed through a gas mixing station consisting of two digital MFCs (Model GE50A), where it was diluted using VOC-free air (i.e., zero air) from an UHP zero air generator (Model 747-30) to a final mole fraction of 0.93 nmol mol–1. The MS peak areas obtained from these calibration runs were then used to calculate the response factor of α-pinene. To quantify the other compounds of interest, we calculated empirically derived response factors based on FID quantitation using the protocols described in Harley et al. (2014). The MS peak areas of the major ion fragment for each compound of interest were integrated using the TERN integration software (TERN ver. 2.16; see Isaacman-VanWertz et al., 2017 for a detailed description); a list of the major ion fragments is provided in the Supplemental Material (Table S1).

#### 2.4.2. Proton transfer reaction time-of-flight mass spectrometry

A PTR-TOF-MS (Model PTR-TOF 1000 ultra; IONICON Analytik GmbH, Innsbruck, Austria) was used to acquire high-time-resolution BVOC emission data from the tomato plants. The PTR-TOF-MS was sequentially switched between the 4 enclosures (i.e., the 3 plant enclosures and the blank) every 4 min. The instrument was equipped with an ion funnel and was operated in H3O+ mode with a drift tube pressure of 2.8 mbar and a drift tube voltage of 530 V. We routinely calibrated the instrument using the same gas standard that was used to calibrate our GC-MS system. The data output from the instrument was processed using PTR-MS Viewer ver. 3.2.13 (IONICON Analytik GmbH). The different target VOCs were quantitated using their respective protonated parent ions: total MTs at m/z 137.132 and MeSA at m/z 153.055 (Karl et al., 2008; Peron et al., 2021; Yanez-Serrano et al., 2021).

### 2.5. Photosynthesis measurements

A CO2/H2O IRGA (Model LI-840A; LI-COR Biosciences, Lincoln, NE, USA) was used to measure the difference in the CO2 and H2O amount fractions between the influent and effluent air from each plant enclosure. The IRGA was cycled between the outlet line of the blank enclosure (which is representative of the influent air) and the outlet line of the plant enclosure every 20s via a fast-switching 3-way solenoid valve (Model EW-01540-12; Cole-Parmer Instrument Co.) to capture any fluctuations in the background (i.e., influent) CO2/H2O amount fractions. The airflow rate to the IRGA was approximately 270 mL/min. The common port of the 3-way valve was coupled to the IRGA inlet, while the normally closed port was connected to the outlet line of the blank enclosure and the normally open port was connected to the sample manifold (see Section 2.2), which in turn was cycled between the 3 plant enclosures and the blank every 4 min. This cycling between enclosures was achieved through preprogrammed, automated valve switching as described in Section 2.2. CO2/H2O readings from the first and last few seconds were discarded during data processing to eliminate transient effects that arise from the switching between enclosures. In some cases, plant transpiration rates were very high (especially during the heat treatment period) and the IRGA flow cell became saturated with water vapor from the plant enclosure and consequently, the 20-s blank-plant switching time was insufficient to completely purge the flow cell of residual water vapor. Therefore, the fast-switching background H2O data was unusable. In these scenarios, the fast-switching background CO2/H2O data were discarded during data processing and the background CO2/H2O amount fractions were determined (at the expense of reduced temporal resolution) from the 4-min periods when both the PTR-TOF-MS and the IRGA were sampling from the blank enclosure. Net photosynthetic rates were subsequently calculated using the equations detailed in von Caemmerer and Farquhar (1981) and after correcting for water vapor dilution effects arising from plant transpiration. We then used the observed reduction in net photosynthetic activity (i.e., net carbon assimilation) following heat exposure as a quantitative indicator of plant physiological stress.

### 2.6. Gene expression measurements

At the conclusion of the respective control and heat stress experiments, the leaves from each of the 6 Roma seedlings (Roma C1, C2, C3, HS1, HS2, and HS3) were harvested and snap-frozen in liquid nitrogen. The leaf samples were then placed in resealable polyethylene storage bags, packed in dry ice, and transported to the Basu Lab (Citrus Hall, California State University, Northridge), where they were stored at –80°C until analyzed. RNA extraction and purification was performed on 100 mg of leaf tissue from each plant sample using a modified TRIzol method described in Ramadoss and Basu (2018). Reverse transcription PCR was carried out using iScript cDNA Synthesis Kit (Bio-Rad; Hercules, CA, USA) with 1 µg of extracted and purified RNA per sample, followed by a 1:10 dilution for optimal complementary DNA (cDNA) concentration. Gene expression quantification was carried out using quantitative real-time PCR (qRT-PCR) performed on a CFX96 thermocycler (Bio-Rad) using iTaq Universal SYBR Green Supermix (Bio-Rad). Primers and qRT-PCR protocol were consistent with Schilmiller et al. (2009). There were at least 3 technical replicates for each biological sample and target gene combination, calibrated with EF-1α housekeeping gene (GenBank accession number: X14449). Reaction volumes of 10 µL were used, with 1 µL of cDNA, 1 µL of each primer, 3 µL of UltraPure water (Invitrogen; Carlsbad, CA, USA), and 5 µL of 2X iTaq Universal SYBR Green Supermix (Bio-Rad). All computations were performed using CFX Manager software ver. 3.0.1224.1015 (Bio-Rad), including in Gene Study mode for final expression calculations.

### 2.7. Essential oil analyses

Several leaves and some stem material were harvested from each of the 4 Roma (referred to herein as Roma EO1, EO2, EO3, and EO4) and the 4 Beefsteak tomato plants (referred to herein as Beefsteak EO1, EO2, EO3, and EO4). These 8 plants had not been subjected to heat stress. The harvested plant material was photographed for leaf area analysis (see Section 2.4) and was then weighed using an electronic mass balance to determine its fresh weight (FW; typically in the range of 2000 mg). Next, the plant material was briefly immersed in liquid nitrogen and was then ground into a fine powder using a porcelain mortar and pestle. Afterward, the finely powdered material was transferred into a glass vial with a screw-top cap. An extraction solvent (20 mL of methanol) was added to the vial, the vial was then capped, and the mixture was stirred overnight at room temperature using a magnetic stirring plate (Model PC-420D; Corning Inc., NY, USA). Later, 5 µL of the extract from each plant was injected into a sorbent cartridge and was subsequently analyzed by TD-GC-MS/FID (see Section 2.4.1) to identify the VOC species present in the storage pool of each plant and to measure their respective pool sizes. Two to 4 replicate cartridges were prepared and analyzed for each extract.

### 3.1. BVOC emission

#### 3.1.1. Preheat stress BVOC ERs

A total of 31 compounds were targeted for analysis and quantification via GC-MS and the results are illustrated in 2-dimensional heat maps (Figures 1 and S1A–B). The values shown in the heat maps are based on ERs measured during the daylight phase of the 12-h photocycle. The first ER measurement from each tomato plant (usually measured 1–2 h after the plant was enclosed) was not used in the median ER calculations. This was done because the emission of BVOCs from most of the sampled plants was temporarily (circa 1–2 h) elevated after the plant was enclosed (data not shown), likely due to mechanical disturbance.

Figure 1.

Preheat stress BVOC emissions. Median values of the preheat stress, daytime emission rates (in pmol m–2 s–1) for 31 compounds (quantified via GC-MS) from 18 individual tomato plants. The values are expressed on a log2 scale. BDL = below detection limit; MT = monoterpene; SQT = sesquiterpene; MeSA = methyl salicylate; TMTT = trimethyltridecatetraene; GC-MS = gas chromatography with mass spectrometry. The compound class, molecular formula, and CAS number (if known) of each of the 31 compounds are listed in the Supplemental Material (Table S1). DOI: https://doi.org/10.1525/elementa.2021.00096.f1

Figure 1.

Preheat stress BVOC emissions. Median values of the preheat stress, daytime emission rates (in pmol m–2 s–1) for 31 compounds (quantified via GC-MS) from 18 individual tomato plants. The values are expressed on a log2 scale. BDL = below detection limit; MT = monoterpene; SQT = sesquiterpene; MeSA = methyl salicylate; TMTT = trimethyltridecatetraene; GC-MS = gas chromatography with mass spectrometry. The compound class, molecular formula, and CAS number (if known) of each of the 31 compounds are listed in the Supplemental Material (Table S1). DOI: https://doi.org/10.1525/elementa.2021.00096.f1

Close modal

Of the 31 targeted compounds, 29 of them were emitted by the tomato plants at detectable levels at either ambient temperatures, heat stress temperatures, or both, including 16 MTs and 9 SQTs. Not all of the 29 compounds were emitted by all 18 tomato plants. There was significant variability in the composition and ERs of BVOCs from the different plants at both ambient and heat stress temperatures (Figures 1 and S1A–B). However, a few compounds including 2-carene, α-pinene, β-phellandrene, limonene, o-cymene, p-menthatriene, and trimethyltridecatetraene (TMTT) were universally emitted in some amount by at least 16 of the 18 plants. TMTT has been shown to be a plant stress marker and could indicate possible pathogen infection (Richter et al., 2016). It is important to note that the absolute value of the preheat stress ERs of most compounds (especially SQTs) at 25°C/30°C were relatively low (mostly in the sub-pmol to sub-nmol m–2 s–1 range), or were below the detection limit (BDL) of our GC-MS. These emission measurements indicate that these tomato plants would be considered as “negligible” terpene emitters in unstressed conditions based on the terpene emission categories established by Guenther et al. (1994). In general, the preheat stress ERs were higher for MTs than for SQTs. The median value of the preheat stress total MT ER (measured via GC-MS) among the 12 tomato plants sampled at 30°C was 23.1 pmol m–2 s–1 (with a range of 0.287–2480 pmol m–2 s–1), while the corresponding value for total SQTs was 0.778 pmol m–2 s–1 (with a range of BDL–83.3 pmol m–2 s–1; note the significant range in ERs between individual plants). Husky Cherry 1 and Early Girl 1 showed significantly higher emissions across a wide range of compounds in comparison to the other tomato plants at ambient temperatures (Figure 1). The much higher preheat stress ERs observed for these 2 seedlings could be due to physiological stress or mechanical disturbance although there was no visible indication of this. When the emission measurements from these 2 plants are omitted, then the median unstressed total MT ER at 30°C from the remaining 10 plants is 18.5 pmol m–2 s–1 (with a range of 0.287–57.0 pmol m–2 s–1), and the total SQT ER is 0.172 pmol m–2 s–1 (with a range of BDL–19.6 pmol m–2 s–1). The preheat stress emissions from the 18 plants were dominated by 8 compounds, 2-carene, α-phellandrene, α-pinene, β-phellandrene, limonene, o-cymene, p-menthatriene, and TMTT, which together accounted for 72% to 100% of the total measured BVOC emissions from each plant, except for Black Cherry 1, for which the 8 compounds only contributed to 59% of total emissions. The lower relative contribution of these compounds from Black Cherry 1 was due to the significant contribution of hexenol emissions (Figure 1).

The literature-reported tomato foliar BVOC ERs based on direct enclosure measurements from 8 different studies (including this one) are summarized in Table 1. Emission rates that were reported on a leaf dry weight basis were converted into leaf area-based values for comparison. This conversion was done using a specific leaf area value of 0.019 m2/g DW (SD: 0.0038 m2/g DW) that was calculated based on our dry weight and area measurements of tomato leaves (see Section 2.4). All reported ERs were also normalized to 30°C (if they were not already) using the Guenther et al. (1993) BVOC emission temperature response algorithm (Equation 2; see Section 3.1.2). In all of the reported studies, total MT ERs were higher than total SQT ERs in agreement with our experimental results, most of the reported emission values were low (in the low pmol to sub-nmol m–2 s–1 range), and both β-phellandrene and 2-carene were consistently reported as dominant BVOCs in 7 out of the 8 studies (Table 1). However, MT ERs reported by Arey et al. (1991) were significantly higher than the values from the other studies. It is important to note that these emission measurements were conducted during summertime in Riverside, California, where the enclosure temperatures were considerably higher (35°C–38°C) than the temperatures reported by the other studies (Table 1). These plants were likely heat-stressed, which could explain the relatively high MT ERs, even after temperature normalization to 30°C. The relatively high emissions could also be due to the small sample size (1–3 plants) or disturbance of terpene storage structures. Tomato plants have been shown to possess terpene-storing glandular trichomes on their leaf and stem surfaces (Li et al., 2004; van Schie et al., 2007; Schilmiller et al., 2009), which when disturbed could emit terpenoids at enhanced rates. It is possible that the tomato plants sampled by Arey et al. (1991) were of a cultivar that has a higher concentration of these trichomes.

#### 3.1.2. Emission maximum response to heat stress

The Guenther et al. (1993) BVOC emission temperature response algorithms include a simple exponential increase for emissions from storage pools (Equation 2) and an algorithm based on enzyme activity behavior for emissions of non-stored (i.e., de novo-synthesized), light-dependent terpenoids (Equation 3):

$ET2ET1=exp[β×(T2−T1)],$
2
$ET2ET1=expcT1(T2−T1)RT1T21+expcT2(T2−TM)RT1T2,$
3

where $ET1$ and $ET2$ are the BVOC ERs at temperatures T1 and T2, respectively, β is an empirical coefficient (typically derived from emission measurements performed at unstressed leaf temperatures of less than approximately 35°C), R is the universal gas constant (8.314 J K–1 mol–1), and cT1, cT2, and TM are empirical coefficients. Equation 2 is generally used for modeling MT emissions although it is widely recognized that the MT emission behavior from some plants follow Equation 3 (Ciccioli et al., 1997; Dindorf et al., 2006; Ghirardo et al., 2010). It is also well established that the MT emissions from some conifer species, for example, Norway spruce (Picea abies) and Scots pine (Pinus sylvestris) can be described by a combination of Equations 2 and 3 (Lindfors et al., 2000; Oderbolz et al., 2013). The model-predicted increase in ERs from 25°C to 39°C (E39°C/E25°C), from 30°C to 42°C (E42°C/E30°C), and the predicted average per-degree emission change (ΔE/ΔT) for 4 MEGAN compound classes were calculated using Equation 2 with the unstressed β emission coefficients used in the MEGANv2.1 model (βmodel; Guenther et al., 2012) and are summarized in Table 2. Guenther et al. (1993) noted that the value of βmodel varies by about ±20%, so this was used to establish a range for the expected temperature response. We also calculated β coefficients based purely on temperature–vapor pressure relations (βvp) by generating temperature–vapor pressure curves for different BVOCs using the Antoine coefficients for pure compounds reported by Yaws and Satyro (2015). βvp is defined as the slope of the log-linear temperature–vapor pressure curve (loge P = βvp × T), where P is the terpene vapor pressure at temperature T (and T is set to be in the range between 20°C and 32°C). Hence, the calculated βvp parameter represents the rate at which terpene vapor pressure increases with temperature. However, βmodel values for each of the 4 MEGAN compound classes are higher than the corresponding βvp values (Table 2), which indicates that the increase in leaf BVOC emissions with temperature is greater than that predicted by temperature–vapor pressure relations alone, as was also shown by Tingey et al. (1991) for α-pinene emissions from conifers.

Table 2.

Model-predicted increase in emission rates with temperature (E39°C/E25°C, E42°C/E30°C, and average ΔET) for 4 different MEGAN compound classes. DOI: https://doi.org/10.1525/elementa.2021.00096.t2

MEGAN Compound Classβvp (°C–1)aβmodel (°C–1)bE39°C/E25°CE42°C/E30°CAverage ΔET (%/°C)
Monoterpenes 0.056–0.067 0.080–0.120 3.06–5.37 2.61–4.22 14–29
Sesquiterpenes 0.093 0.136–0.204 6.71–17.39 5.11–11.57 38–103
C10 aromatics 0.064–0.073c 0.080–0.120 3.06–5.37 2.61–4.22 14–29
Stress compounds 0.062–0.083c 0.080–0.120 3.06–5.37 2.61–4.22 14–29
MEGAN Compound Classβvp (°C–1)aβmodel (°C–1)bE39°C/E25°CE42°C/E30°CAverage ΔET (%/°C)
Monoterpenes 0.056–0.067 0.080–0.120 3.06–5.37 2.61–4.22 14–29
Sesquiterpenes 0.093 0.136–0.204 6.71–17.39 5.11–11.57 38–103
C10 aromatics 0.064–0.073c 0.080–0.120 3.06–5.37 2.61–4.22 14–29
Stress compounds 0.062–0.083c 0.080–0.120 3.06–5.37 2.61–4.22 14–29

E39°C/E25°C and E42°C/E30°C are the expected ratios of emission rates at 39°C to 25°C and at 42°C to 30°C, respectively, as predicted by the MEGANv2.1 model, while ΔET is the predicted average per-degree emission change. GC-MS = gas chromatography with mass spectrometry.

a βvp values were calculated using the Antoine coefficients for pure compounds reported by Yaws and Satyro (2015). The range of βvp values for several different compounds in each MEGAN class is listed here. βvp values for individual compounds are provided in the Supplemental Material (Table S2). The βvp coefficient reported for sesquiterpenes is based on data from a single compound, cadinene, which is the sole sesquiterpene listed in Yaws and Satyro (2015).

b βmodel values were obtained from MEGANv2.1 (Guenther et al., 2012).

c O-cymene is the only C10 aromatic targeted in our GC-MS analysis, while hexenol, methyl salicylate (MeSA), and trimethyltridecatetraene (TMTT) are the only stress compounds. However, the reported βvp range for these 2 MEGAN classes includes values calculated from other compounds that were not targeted in our study.

β emission coefficients were calculated for the 29 compounds emitted by the 15 heat-stressed tomato plants using Equation 2. A box-whisker statistical analysis was then performed on the calculated β values (Figure 2). Two separate heat stress periods were designated in the calculations of β, that is, the initial (first 8 h of the heat treatment) and final (last 2 h) periods. We then used the maximum $ET2$ measured during each of the designated stress periods (initial and final) and the median value of $ET1$ measured during the prestress period to calculate β. Therefore, the reported β values represent the maximum observed BVOC emission response of each tomato plant. In cases where $ET1$ was zero or BDL, we divided $ET2$ by the minimum detectable ER (in pmol m–2 s–1) for each compound, which was calculated based on the detection limit of the GC-MS system. The BVOC response of the tomato plants can be classified into 5 categories based on their β values: no detectable emission, suppressed (β < 0; 0 < $ET2/ET1$ < 1), low increase (0 < β < lower limit of βmodel), expected increase (β within the ±20% range of βmodel), and elevated increase response (β > upper limit of βmodel). Heat maps illustrating the emission response of different BVOCs from each individual plant are included in the Supplemental Material (Figure S1A–B).

Figure 2.

β emission coefficients. Box-whisker plot of β emission coefficients for 29 compounds from 15 heat-stressed tomato plants during the initial (top plot) and final (bottom plot) periods of the heat treatment. The red circles represent the data points, the blue squares show the outliers (beyond 1.5 × interquartile range), and the blue triangles show the far outliers (beyond 3 × interquartile range). Absent data points indicate undetectable emissions during heat stress. β-elemene and δ-elemene were not emitted at detectable levels by any of the sampled plants and are thus excluded from the box-whisker plot. The cyan-shaded region denotes the expected range of β values for unstressed plants (βmodel) as listed in Table 2. The dashed line delineates β = 0; β values lower than 0 indicate suppressed emissions (i.e., $ET2$ < $ET1$, where T2 > T1), while β values greater than 0 denote increased emissions (i.e., $ET2$ > $ET1$). DOI: https://doi.org/10.1525/elementa.2021.00096.f2

Figure 2.

β emission coefficients. Box-whisker plot of β emission coefficients for 29 compounds from 15 heat-stressed tomato plants during the initial (top plot) and final (bottom plot) periods of the heat treatment. The red circles represent the data points, the blue squares show the outliers (beyond 1.5 × interquartile range), and the blue triangles show the far outliers (beyond 3 × interquartile range). Absent data points indicate undetectable emissions during heat stress. β-elemene and δ-elemene were not emitted at detectable levels by any of the sampled plants and are thus excluded from the box-whisker plot. The cyan-shaded region denotes the expected range of β values for unstressed plants (βmodel) as listed in Table 2. The dashed line delineates β = 0; β values lower than 0 indicate suppressed emissions (i.e., $ET2$ < $ET1$, where T2 > T1), while β values greater than 0 denote increased emissions (i.e., $ET2$ > $ET1$). DOI: https://doi.org/10.1525/elementa.2021.00096.f2

Close modal

The box-whisker statistical analysis demonstrates that the median β coefficients of most of the emitted compounds (25 out of 29 compounds during the initial stress period and 18 out of 29 during the final) were higher than the expected range for unstressed plants (βmodel). For 16 compounds, at least 75% of the β measurements (indicated by the interquartile ranges and upper whiskers in Figure 2) were higher than βmodel during the initial stress period, and the same was true for 8 compounds during the final stress period. This elevated increase response (β > 0.204 and ΔET greater than approximately 103%/°C for SQTs; β > 0.12 and ΔET greater than approximately 29%/°C for all other targeted compounds) exhibited by about half of the measured BVOC species during the initial stress period indicates the elicitation of “stress emission” (in addition to the existing constitutive emission) that causes total observed emissions to be higher than expected from the behavior of emissions at lower temperatures (Equation 2). This stressed emission behavior alludes to the existence of other emission mechanism(s) in these tomato plants in addition to the simple physical volatilization of BVOCs from existing pools. Possible mechanisms include the following: (1) Induced emissions resulting from physical damage to storage structures, (2) reduction in physical barriers, and (3) gene upregulation of production. A rupture or an increase in the wall permeability of specialized external BVOC storage structures could occur at elevated temperatures (Copolovici et al., 2012). Previous studies have established the presence of such structures (glandular trichomes) on the foliar and stem surfaces of tomato plants that contain various terpenoids including MTs and SQTs (Li et al., 2004; van Schie et al., 2007; Schilmiller et al., 2009). At higher temperatures, there could be reduced resistance in the diffusion pathway or a breakdown of physical barriers between the BVOC synthesis sites/internal storage pools and the leaf stomata, thereby facilitating BVOC diffusion and subsequent emission into the atmosphere (Tingey et al., 1991). Exposure to heat stress could also result in the upregulation of genes responsible for the synthesis of specific terpene molecules (Gupta et al., 2014), thereby resulting in increased de novo production of those terpenes and consequently increased emissions.

Table 3 summarizes the information presented in the box-whisker plot (Figure 2) and in the heat maps (Figure S1A–B) with the percentage of BVOC species out of a total of 465 (i.e., 31 compounds × 15 plants) that fall into each of the 5 emission response categories during both the initial and final periods of the heat stress. For many of the emitted compounds, the magnitude of the heat stress emission response (characterized by β) was generally lower during the final period of the heat treatment (last 2 h) compared to the initial period (first 8 h; Figures 2 and S1B). The number of compounds that exhibited an elevated increase response also decreased in the final period of the heat stress, while the number of compounds with no detectable emission increased during the same period (Table 3). A few compounds from some plants showed suppressed emissions (β < 0; 0 < $ET2/ET1$ < 1) after exposure to heat stress and their numbers increased during the final period of the heat treatment (Figure 2 and Table 3).

Table 3.

Percentage of BVOC species out of a total of 465 (i.e., 31 compounds × 15 plants) that fall into each of the 5 emission response categories during both the initial and final periods of the heat stress. DOI: https://doi.org/10.1525/elementa.2021.00096.t3

Emission Response CategoryPercentage of BVOC Species (%)
During Initial Heat Stress PeriodDuring Final Heat Stress Period
No detectable emission 34.6 40.0
Suppressed 3.4 8.4
Low increase 9.0 9.7
Expected increase 8.0 7.1
Elevated increase 44.9 34.8
Emission Response CategoryPercentage of BVOC Species (%)
During Initial Heat Stress PeriodDuring Final Heat Stress Period
No detectable emission 34.6 40.0
Suppressed 3.4 8.4
Low increase 9.0 9.7
Expected increase 8.0 7.1
Elevated increase 44.9 34.8

BVOC = biogenic volatile organic compound.

There are several possible explanations for the general decrease in stress emissions toward the end of the 24-h heat treatment including: (1) diminished BVOC storage pools, (2) reduced terpene synthase activity, and (3) reduced carbon substrate availability due to photosynthesis suppression. If heat stress-enhanced emissions are high relative to BVOC pool sizes, then the emissions could diminish or completely exhaust the storage pools of those BVOCs in a relatively short time (less than approximately 24 h) in the absence of additional de novo production (see Section 3.4 and Table S4B-C). Terpenoid production is controlled by substrate availability and enzymatic activity; the latter generally increases with temperature up to an optimum limit. Exposure to temperatures beyond this optimum leads to reduced terpene synthase activity and possibly synthase denaturation, which diminishes de novo-derived BVOC emissions (Loreto and Schnitzler, 2010). However, the optimal temperature for MT synthase activity is reported to be approximately 40°C (Fischbach et al., 2000; Niinemets et al., 2002), which was exceeded by only 2°C for most of the heat-stressed tomato plants (Tstress = 42°C) and may not have been exceeded for the plants that were treated at 39°C (Roma HS1, HS2, and HS3). High temperatures partially suppressed photosynthetic activity in some of the sampled plants, and the degree of suppression typically increased during the final period of the heat treatment (see Section 3.2; Table 4). It is conceivable that this time-cumulative photosynthetic suppression would have progressively limited the availability of new carbon for the synthesis of terpene molecules, thereby leading to decreased emissions. Interestingly, Tami-G 1 showed the highest degree of photosynthetic suppression among the heat-stressed tomato plants during the final period of the heat treatment (Table 4), but Tami-G 1 also had the highest MT emission response among the sampled plants during that same period. However, the MT emissions from Tami-G 1 peaked in the dark (Figure S2A), so most of the additional stress emissions presumably originated from stored pools and not from light-dependent de novo synthesis. Emissions from stored pools would likely be unaffected by reduced photosynthetic activity, at least in the short-term.

Table 4.

Time-averaged net photosynthetic rates before the heat treatment (Anet, prestress) and the percentage change in Anet relative to prestress levels during the initial (ΔAnet, HS-initial) and final (ΔAnet, HS-final) periods of the heat treatment for the 15 heat-stressed tomato plants. DOI: https://doi.org/10.1525/elementa.2021.00096.t4

PlantAnet, prestress (µmol CO2 m–2 s–1)ΔAnet, HS-initial (%)ΔAnet, HS-final (%)
Beefsteak 1 10.4 –9.0 –35.3
Beefsteak 2 7.5 –8.3 –14.3
Black Cherry 1 5.0 –1.0 –18.8
Cherokee 1 6.4 +0.1 –19.6
Early Girl 1 6.4 –20.3 –30.9
Husky Cherry 1 6.0 –6.2 –5.6
Juliet 1 9.2 –13.8 –7.8
Roma 1 7.2 –2.3 –18.7
Roma HS1 7.3 +0.3 –8.8
Roma HS2 6.5 +8.8 –5.2
Roma HS3 7.1 +17.0 –0.1
Summer Set 1 6.6 +13.5 –44.6
Tami-G 1 7.3 –10.8 –99.4
Tami-G 2 7.3 –17.4 –95.0
Tami-G 3 6.9 –8.2 –47.1
PlantAnet, prestress (µmol CO2 m–2 s–1)ΔAnet, HS-initial (%)ΔAnet, HS-final (%)
Beefsteak 1 10.4 –9.0 –35.3
Beefsteak 2 7.5 –8.3 –14.3
Black Cherry 1 5.0 –1.0 –18.8
Cherokee 1 6.4 +0.1 –19.6
Early Girl 1 6.4 –20.3 –30.9
Husky Cherry 1 6.0 –6.2 –5.6
Juliet 1 9.2 –13.8 –7.8
Roma 1 7.2 –2.3 –18.7
Roma HS1 7.3 +0.3 –8.8
Roma HS2 6.5 +8.8 –5.2
Roma HS3 7.1 +17.0 –0.1
Summer Set 1 6.6 +13.5 –44.6
Tami-G 1 7.3 –10.8 –99.4
Tami-G 2 7.3 –17.4 –95.0
Tami-G 3 6.9 –8.2 –47.1

#### 3.1.3. Temporal variability in MT emission response

Tomato foliar MT emissions were dominated by 6 compounds: α-pinene, α-phellandrene, α-terpinene, limonene, β-phellandrene, and 2-carene (Figures 3 and S2A–C). The sum of the individual MT ERs measured via GC-MS were generally lower than the corresponding PTR-MS-measured total MT ERs (Figures 3 and S2A–B), which implies the significant emission of MT species that were not detected by GC-MS. We observed a broad spectrum of time-varying emission behaviors across individual heat-stressed plants. Most (but not all) of the plants emitted a temporary burst of MTs following the initial heat exposure (Figure 3; top panel, Figure 4, and Figure S2B–C). Following the transient MT burst, MT emissions generally decreased (Figure 3; top panel), but in some plants, the emissions started to increase again in the latter period of the heat stress (Figures 4 and S2B–C). In Beefsteak 2 (Figure 3; bottom panel), the initial MT burst was not transient, but was instead sustained, and the emissions continued to increase throughout most of the heat treatment period. In contrast, Black Cherry 1 (Figure 3; middle panel) did not emit a transient pulse of MTs, but instead exhibited a delayed response to the ongoing heat stress, where MT emissions peaked circa 7 h after the start of the heat treatment. This delayed-type emission response was also observed in Tami-G 1, Tami-G 2, and Tami-G 3 (Figure S2A). There were some changes in the composition of the emitted MTs with time and with the imposition of heat stress; for example, the fractional contribution of α-phellandrene was marginally higher during the heat stress than before in some of the plants (Figure 3). However, we did not observe any notable changes in the MT composition that appeared consistently across the different plants. This may indicate emission from a common stored pool rather than new production. In summary, the time-dependent MT emission response of heat-stressed tomato plants may be classified into 2 broad categories: early burst response and delayed increase response; the early burst could be either temporary (Figure 3; top panel) or sustained (Figure 3; bottom panel). However, these 2 categories are not mutually exclusive, as some plants exhibited both behaviors with an early MT burst followed by a second, delayed increase in MT emissions (Figures 4 and S2B–C).

Figure 3.

Total and speciated monoterpene emissions. Time series of total monoterpene emissions measured via online PTR-MS and discontinuous GC-MS, and fractional contribution of speciated monoterpenes for 3 select heat-stressed tomato plants, Husky Cherry 1, Black Cherry 1, and Beefsteak 2. The gray-shaded areas represent nighttime (i.e., plant chamber lights were turned off), while the beige-shaded area delineates the transitionary period from 30°C to 42°C. Time series of monoterpene emissions for 9 other heat-stressed tomato plants are presented in the Supplemental Material (Figure S2A–C). P-menthatriene is excluded from the emission time series because its protonated mass (m/z 135.117) is different from that of the other monoterpenes (m/z 137.132), and its inclusion would cause disagreements between the GC-MS and PTR-MS-measured values. PTR-MS = proton transfer reaction-mass spectrometer; GC-MS = gas chromatography with mass spectrometry. DOI: https://doi.org/10.1525/elementa.2021.00096.f3

Figure 3.

Total and speciated monoterpene emissions. Time series of total monoterpene emissions measured via online PTR-MS and discontinuous GC-MS, and fractional contribution of speciated monoterpenes for 3 select heat-stressed tomato plants, Husky Cherry 1, Black Cherry 1, and Beefsteak 2. The gray-shaded areas represent nighttime (i.e., plant chamber lights were turned off), while the beige-shaded area delineates the transitionary period from 30°C to 42°C. Time series of monoterpene emissions for 9 other heat-stressed tomato plants are presented in the Supplemental Material (Figure S2A–C). P-menthatriene is excluded from the emission time series because its protonated mass (m/z 135.117) is different from that of the other monoterpenes (m/z 137.132), and its inclusion would cause disagreements between the GC-MS and PTR-MS-measured values. PTR-MS = proton transfer reaction-mass spectrometer; GC-MS = gas chromatography with mass spectrometry. DOI: https://doi.org/10.1525/elementa.2021.00096.f3

Close modal
Figure 4.

Methyl salicylate and total monoterpene emission time series. Time series of emissions of methyl salicylate (MeSA) and total monoterpenes (MT) from 3 heat-stressed Roma tomato plants (Roma HS1, HS2, and HS3) [left], and 3 control plants (Roma C1, C2, and C3) [right] measured via PTR-MS. The gray-shaded areas represent nighttime (i.e., plant chamber lights were turned off). The beige-shaded area delineates the transitionary period from 25°C to 39°C for the 3 heat-stressed plants. PTR-MS = proton transfer reaction-mass spectrometer. DOI: https://doi.org/10.1525/elementa.2021.00096.f4

Figure 4.

Methyl salicylate and total monoterpene emission time series. Time series of emissions of methyl salicylate (MeSA) and total monoterpenes (MT) from 3 heat-stressed Roma tomato plants (Roma HS1, HS2, and HS3) [left], and 3 control plants (Roma C1, C2, and C3) [right] measured via PTR-MS. The gray-shaded areas represent nighttime (i.e., plant chamber lights were turned off). The beige-shaded area delineates the transitionary period from 25°C to 39°C for the 3 heat-stressed plants. PTR-MS = proton transfer reaction-mass spectrometer. DOI: https://doi.org/10.1525/elementa.2021.00096.f4

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There were no notable differences in the total MT ERs between the light and dark hours for any of the sampled tomato plants (Figures 3, 4, and S2A–C). This apparent lack of light-dependent emission behavior indicates that the bulk of the observed tomato foliar MT emissions were derived from light-independent stored pools as opposed to light-dependent de novo synthesis. In fact, in two of the sampled plants (Tami-G 1 and Tami-G 3; Figure S2A), MT emissions peaked in the dark during the heat treatment period, which indicates that the source of the stress-induced MT emissions was primarily from existing MT pools and not from increased de novo MT synthesis (which would have been absent in the dark). One of these dark-peaking plants, Tami-G 1, exhibited the highest MT stress emission response among the 15 heat-stressed tomato plants with a peak ER of approximately 85 nmol m–2 s–1 (Figure S2A). However, the apparent absence of MT light dependency does not rule out the coemission of a minor fraction of light-dependent (i.e., de novo) MTs during daytime at rates that are too minute to cause an appreciable difference between the observed daytime and nighttime MT ERs.

MT emission data from the post-stress recovery period were acquired using high-time-resolution PTR-MS for 3 plants (Figure S2B). Two out of the 3 plants (Cherokee 1 and Beefsteak 1) emitted a transient pulse of MTs almost immediately after temperatures were returned to 30°C. The appearance of these emission pulses was also verified via complementary GC-MS measurements (Figure S2B). The mechanism behind the post-heat stress MT pulse is unclear. However, we note that the transition from 42°C to 30°C was rather rapid (circa 6 min), and this abrupt change in temperature could have influenced the emission behavior. These two plants also emitted a second, longer lasting MT emission pulse during the recovery period as shown by the PTR-MS time series (Figure S2B). However, these emission peaks are not discernible in the corresponding GC-MS measurements, which could indicate substantial emission of MTs that were not detectable via GC-MS.

#### 3.1.4. Emission of stress compounds

Emissions of MeSA and TMTT were observed in the sampled tomato plants. Both compounds have been associated with plant physiological stress (Rose et al., 1996; Kant et al., 2004), although some plants, for example, wintergreen (Gaultheria procumbens L.) and sweet birch (Betula lenta L.) are known to store MeSA in their essential oils (Murphy et al., 2021). Sixteen out of the 18 sampled tomato plants (i.e., all except for Summer Set 1 and Black Cherry 1) were emitting detectable amounts of MeSA at ambient temperatures (25°C/30°C) prior to the heat treatment (Figures 4 and 5), while all but one of the plants were emitting some amount of TMTT (Figure 1). Of the 16 plants with detectable preheat stress MeSA emissions, only 3 (Tami-G 1, Husky Cherry 1, and Beefsteak 2) were emitting MeSA from the beginning of the measurement period, while the other 13 plants started emitting MeSA circa 11–24 h after being enclosed in the Teflon enclosures (Figures 4 and 5). MeSA and TMTT emissions are often associated with biotic stress (e.g., pathogen infection and insect grazing; Kant et al., 2004). However, MeSA emissions can also be induced by abiotic stress, for example, in walnut (Juglans californica × Juglans regia) plants exposed to chilling temperatures (Karl et al., 2008). We note that there were no visible indicators of physical damage or biotic stressors in any of our tomato plants prior to the heat treatment. Furthermore, in all plants, MeSA emissions were either low or undetectable at the beginning of the measurement period (Figures 4 and 5). The elevated preheat stress MeSA emissions that were observed in several plants only appeared after some period of enclosure. If the plants had been subjected to significant preexisting stress, then the MeSA emissions would likely have been elevated from the start of the measurements. The prolonged enclosure in an artificial enclosure may have imposed some degree of stress on the plants over time, and this could have manifested in the elevated preheat treatment MeSA and TMTT emissions in some of the plants. We note that the observed MeSA and TMTT emissions could also have been induced by an indiscernible biotic stress.

Figure 5.

Methyl salicylate emission time series. Time series of methyl salicylate (MeSA) emissions measured via online PTR-MS for 9 heat-stressed tomato plants. PTR-MS-measured emission data is unavailable for 3 other plants, Roma 1, Summer Set 1, and Early Girl 1 (second panel from the top); therefore, the GC-MS-measured emission rates are shown instead. Each panel in the figure displays a set of 3 plants that were heat-stressed concurrently. The gray-shaded areas represent nighttime (i.e., plant chamber lights were turned off), while the beige-shaded area delineates the transitionary period from 30°C to 42°C. For 6 plants (first and second panels from the top), emission rates were also measured during the post-heat stress recovery period; the cyan-shaded region delineates the brief transitionary period from 42°C back to 30°C. MeSA emission time series for Roma HS1, HS2, HS3, and Roma C1, C2, and C3 are shown in Figure 4. PTR-MS = proton transfer reaction-mass spectrometer; GC-MS = gas chromatography with mass spectrometry. DOI: https://doi.org/10.1525/elementa.2021.00096.f5

Figure 5.

Methyl salicylate emission time series. Time series of methyl salicylate (MeSA) emissions measured via online PTR-MS for 9 heat-stressed tomato plants. PTR-MS-measured emission data is unavailable for 3 other plants, Roma 1, Summer Set 1, and Early Girl 1 (second panel from the top); therefore, the GC-MS-measured emission rates are shown instead. Each panel in the figure displays a set of 3 plants that were heat-stressed concurrently. The gray-shaded areas represent nighttime (i.e., plant chamber lights were turned off), while the beige-shaded area delineates the transitionary period from 30°C to 42°C. For 6 plants (first and second panels from the top), emission rates were also measured during the post-heat stress recovery period; the cyan-shaded region delineates the brief transitionary period from 42°C back to 30°C. MeSA emission time series for Roma HS1, HS2, HS3, and Roma C1, C2, and C3 are shown in Figure 4. PTR-MS = proton transfer reaction-mass spectrometer; GC-MS = gas chromatography with mass spectrometry. DOI: https://doi.org/10.1525/elementa.2021.00096.f5

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There were no consistent differences in the observed MeSA ERs between the light and dark hours (Figures 4 and 5). This behavior suggests that most of the observed MeSA emissions were released from light-independent stored pools. An example of this light-independent emission behavior can be seen in Cherokee 1 and Juliet 1, where both plants first began to emit MeSA while it was dark (Figure 5; top panel), that is, in the absence of de novo MeSA synthesis. Furthermore, our analyses of the essential oils of Roma and Beefsteak tomato foliage detected significant quantities of MeSA in the stored pools. In contrast, TMTT was absent in the essential oils (see Section 3.4). However, post-illumination bursts (PIBs) of MeSA were observed during the heat treatment in 6 of the sampled plants, Roma HS1, HS2, and HS3 (Figure 4) and Cherokee 1, Beefsteak 1, and Juliet 1 (Figure 5; top panel). MeSA PIBs were not observed in any of the sampled plants during non-heat stressed periods. PIBs are transient emissions of plant volatiles that occur when illumination is abruptly terminated and have been associated with light-dependent emission behavior (Jud et al., 2016; Srikanta Dani et al., 2017). Plant volatiles that have been shown to exhibit PIBs include isoprene, methanol, ethanol, acetone, acetaldehyde, and green leaf volatiles such as 3-hexenal, 3-hexenol, and 3-hexenyl acetate (Brilli et al., 2011; Jardine et al., 2012; Jud et al., 2016). To our knowledge, the occurrence of MeSA PIBs has not previously been reported. The appearance of MeSA PIBs in some of the heat-stressed plants indicates that some fraction of tomato foliar MeSA emissions may be derived from light-dependent, de novo synthesis.

In contrast to MTs, whose emissions generally increased in response to heat stress, especially during the initial period of exposure (Figures 2 and 3), MeSA does not appear to have a consistent response to heat stress (Figures 4 and 5). In some plants, MeSA emissions increased initially following heat exposure before gradually decreasing (e.g., Beefsteak 1, Roma HS1, HS2, and HS3), while in others, emissions decreased almost immediately (e.g., Juliet 1 and Early Girl 1). Furthermore, several plants showed no significant changes in MeSA emissions following heat exposure (e.g., Roma 1, Summer Set 1, Tami-G 2, and Tami-G 3). A few of the tomato plants that were sampled concurrently (e.g., Roma HS1, HS2, and HS3) had similar MeSA temporal emission patterns (i.e., the emissions started to increase and decrease at similar times), although the magnitude of the emissions varied between the plants. Considering that part of the foliage was positioned outside the Teflon enclosure during sampling, this observed similarity in emission patterns could be a result of plant-to-plant signaling (Park et al., 2007; Chen et al., 2019).

The heat stress-induced rapid decrease in MeSA emissions observed in 3 of the plants (Juliet 1, Cherokee 1, and Early Girl 1) and the transient decrease shown by 4 plants (Beefsteak 1, Roma HS1, HS2, and HS3) may be attributed to a reduction in enzyme activity and production rates. In contrast, the rate of physical volatilization from stored pools always increases with temperature and would not contribute to a decline in emissions. Previous studies have shown that high temperatures (above the enzyme activity optimum) have an immediate inhibitory effect on the ERs of de novo-synthesized BVOCs (e.g., isoprene) that are not stored in long-term pools or in specialized storage structures (Loreto et al., 2006; Possell and Loreto, 2013). The rapid nature of the MeSA emission inhibition observed in some of the tomato plants therefore suggests that the emitted MeSA did not originate from long-term storage pools but rather was produced de novo and/or stored in small temporary pools with high turnover rates. If the MeSA were primarily emitted from long-term pools, then the observed decline in MeSA emissions should have been more gradual due to the buffering effect of the storage pools. Instead, the observed “rapid decrease” in emissions implies direct control by enzyme activity and production rates and contradicts the evident light-independent MeSA behavior and may suggest a dual source for the emitted MeSA, that is, from both (1) light-independent long-term storage pools and (2) light-dependent de novo production and/or temporary pools.

The temporary increase in MeSA emissions observed in some of the plants (Beefsteak 1, Beefsteak 2, Husky Cherry 1, Roma HS1, HS2, and HS3) was likely due to heat stress-enhanced volatilization from the MeSA pools. The subsequent gradual decrease in emissions may have been caused by diminishing MeSA pool sizes resulting from the enhanced volatilization, as well as reduced de novo production rates stemming from declining enzyme activity following heat stress. However, we note that the measured foliar MeSA pool sizes in Roma and Beefsteak tomato plants were generally large enough to sustain emissions, even at heat-enhanced rates, for days to months (see Section 3.4 and Table S4B–C). Heat stress also reduced photosynthetic activity in some of the sampled plants, especially during the latter period (see Section 3.2; Table 4), which would have limited substrate availability for de novo MeSA production.

### 3.2. Photosynthetic activity

The time-averaged net photosynthetic (i.e., net carbon assimilation) rates (Anet) for the circa 3- to 4-h period preceding the heat treatment and the percentage change in Anet relative to preheat stress levels during both the initial and final periods of the heat treatment are summarized in Table 4 for the 15 heat-stressed tomato plants. The degree of change in Anet following heat exposure can be used as a quantitative indicator of plant physiological stress. The prestress Anet values for the 15 plants ranged from 5.0 to 10.4 µmol CO2 m–2 s–1, with typical diurnal variations (from 9.00 AM to 7.30 PM) between ±1.5% and ±8.3%. The range of diurnal variabilities was estimated using plants for which gas exchange data were available for a full unstressed day. Following initial exposure to mild heat stress (39°C), 2 of the 3 Roma HS seedlings (Roma HS2 and HS3) experienced a modest increase in Anet (+8.8% and +17.0%, respectively), while Roma HS1 showed no notable change (+0.3%). During the final period of the heat treatment, Roma HS1 experienced a small reduction in Anet (–8.8%), while Roma HS2 and HS3 showed no notable change (–5.2% and –0.1%, respectively). The measured ΔAnet values were generally within the expected diurnal variability range of the plants, which suggests that mild heat stress (39°C) has no substantial impact on the photosynthetic activity of tomato plants even after prolonged periods of exposure (24 h). The other 12 tomato plants were exposed to moderate heat stress (42°C), and following initial exposure, 5 of the plants exhibited modest reductions in Anet, with values ranging from –9.0% to –20.3%. However, one plant (Summer Set 1) experienced a small increase in Anet (+13.5%), while 6 others (Beefsteak 2, Black Cherry 1, Cherokee 1, Husky Cherry 1, Roma 1, and Tami-G 3) showed no notable change (–8.3%, –1.0%, +0.1%, –6.2%, –2.3%, and –8.2%, respectively) during the initial heat treatment period. For 10 out of the 12 plants exposed to 42°C, the magnitude of reduction in Anet was greater during the final period of the heat treatment compared to the initial period, which is expected, since the adverse physiological effects of heat stress are generally time-cumulative (Song et al., 2014). The photosynthetic activity of the 3 Tami-G seedlings was particularly impacted during the final period of the heat treatment. Two of the 3 Tami-G seedlings (Tami-G 1 and Tami-G 2) experienced an almost complete shutdown of photosynthetic activity (ΔAnet of –99.4% and –95.0%, respectively), while the net photosynthetic rate of Tami-G 3 decreased by 47.1% relative to prestress levels. We also observed physical signs of heat stress damage in Tami-G 1 and Tami-G 2 toward the end of the heat treatment; the leaves from both plants appeared wilted. The two plants were rewatered after the heat treatment and the leaves on both plants subsequently recovered some of their turgidity, suggesting that the physiological damage was not permanent. Measurements of stomatal conductance for water vapor indicate that both Tami-G 1 and Tami-G 2 were severely droughted during the final period of the heat treatment (Table S3). This suggests that the extreme reduction in photosynthetic activity observed in these 2 plants may be caused by water stress resulting in stomata closure and not solely due to heat stress. ΔAnet values for the other 9 tomato plants measured during the final period of the 42°C heat treatment ranged from –5.6% to –44.6%. It should be noted that heat stress-induced suppression of photosynthetic activity (carbon assimilation) can limit the availability of substrates required for de novo terpene synthesis, thereby leading to a decrease in some plant BVOC emissions.

### 3.3. Gene expression

Gene expression measurements were performed on the leaves from 3 heat-stressed Roma tomato plants (Roma HS1, HS2, and HS3) and 3 control plants (Roma C1, C2, and C3). The differential expression of 3 genes coding for the enzymes neryl diphosphate synthase 1 (NDPS1), β-phellandrene synthase 1 (PHS1), and salicylic acid methyl transferase (SISAMT) in each of the heat-stressed plants were quantified relative to the control plants (Figure 6). NDPS1 synthesizes neryl diphosphate and was identified in tomato leaf trichomes by Schilmiller et al. (2009). PHS1 is a terpene synthase that uses the substrate neryl diphosphate to synthesize β-phellandrene and other MTs, including 2-carene, α-terpinene, limonene, γ-terpinene, and α-phellandrene. PHS1 was also detected in tomato leaf trichomes by Schilmiller et al. (2009). Meanwhile, SISAMT is an enzyme that catalyzes methylation of salicylic acid to produce MeSA and has been observed in tomato plants (Tieman et al., 2010).

Figure 6.

Differential gene expression. Differential expression of 3 genes coding for the enzymes neryl diphosphate synthase 1 (NDPS1), β-phellandrene synthase 1 (PHS1), and salicylic acid methyl transferase (SISAMT) in 3 different heat-stressed Roma tomato plants (Roma HS1, HS2, and HS3). Y axis denotes normalized gene expression relative to control plants. The figure was generated using CFX Manager (Bio-Rad) software. The software used gene expression values in the control plants (Roma C1, C2, and C3) to generate this data normalized against EF-1α, a housekeeping gene (GenBank accession number: X14449). DOI: https://doi.org/10.1525/elementa.2021.00096.f6

Figure 6.

Differential gene expression. Differential expression of 3 genes coding for the enzymes neryl diphosphate synthase 1 (NDPS1), β-phellandrene synthase 1 (PHS1), and salicylic acid methyl transferase (SISAMT) in 3 different heat-stressed Roma tomato plants (Roma HS1, HS2, and HS3). Y axis denotes normalized gene expression relative to control plants. The figure was generated using CFX Manager (Bio-Rad) software. The software used gene expression values in the control plants (Roma C1, C2, and C3) to generate this data normalized against EF-1α, a housekeeping gene (GenBank accession number: X14449). DOI: https://doi.org/10.1525/elementa.2021.00096.f6

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Some amounts of β-phellandrene, 2-carene, and limonene were emitted constitutively by all 6 Roma tomato plants (Figure 1). None of the plants emitted detectable levels of α-terpinene or γ-terpinene prior to the heat treatment, while 4 out of the 6 plants emitted α-phellandrene (Figure 1). Following initial exposure to heat stress, emissions of β-phellandrene, 2-carene, α-terpinene, limonene, γ-terpinene, and α-phellandrene increased in all 3 heat-stressed plants (Figure S1A; top plot), and we also observed a corresponding increase in total MT emissions (Figure 4). Emissions of β-phellandrene, 2-carene, α-terpinene, limonene, α-phellandrene (Figure S1A; bottom plot), and total MTs (Figure 4) remained elevated relative to prestress levels at the end of the heat treatment for all 3 plants, while γ-terpinene emissions decreased to undetectable levels for 2 out of the 3 plants (Figure S1A; bottom plot). Even though all 3 heat-stressed plants exhibited sustained induction of most MTs, the gene expression data indicates downregulation of NDPS1 and PHS1 in Roma HS1 relative to the control plants (Figure 6). In contrast, both terpene synthases were upregulated in Roma HS2 and Roma HS3, and the degree of upregulation was comparable in both plants (Figure 6). There were no notable differences in the ERs of total MTs (Figure 4) and speciated MTs (Figure S3) between Roma HS1, HS2, and HS3 in the final period of the heat stress (i.e., shortly before the leaf samples were harvested and snap-frozen for gene analysis). For the control plants, the total MT ERs were higher in Roma C3 than in Roma C1 and C2, which both emitted at similar rates (Figure 4). The total MT ERs from all 3 control plants remained relatively stable over the measurement period, and the notable increase in MT emissions observed in the heat-stressed plants was beyond the intrinsic temporal emission variability of the control plants (Figure 4). The weak correlation between the magnitudes of NDPS1 and PHS1 expression and the ERs of MTs in the heat-stressed plants suggests that the bulk of the observed MT stress emissions were likely derived from existing foliar stored pools and not from increased de novo synthesis via gene upregulation. The apparent absence of light-dependent MT emissions from the sampled plants (Figure 4) also suggests emissions from stored pools.

Emission rates of MeSA were higher in the heat-stressed plants than in the control plants, with the exception of Roma HS3, in which the emissions were comparable to the control plants (Figure 4). MeSA emissions from all 3 heat-stressed plants peaked circa 4 h after the start of the heat treatment, and then decreased gradually with time (Figure 4). However, it should be noted that MeSA emissions from these 3 plants began to increase even before the heat treatment. There is very poor correlation between the magnitude of SISAMT expression and the observed MeSA ERs in the heat-stressed plants. SISAMT was downregulated in Roma HS1 relative to the control plants (Figure 6), but Roma HS1 had the highest MeSA emissions among the 3 heat-stressed plants (Figure 4). In contrast, Roma HS3 showed the highest degree of SISAMT upregulation among the 3 plants but had the lowest MeSA emissions. There are several possible explanations for the disparity in the SISAMT expression levels and observed MeSA emissions. Firstly, the emitted MeSA may have mostly originated from existing foliar stored pools and not from de novo synthesis. However, the appearance of MeSA PIBs during the heat treatment in all 3 plants (Figure 4) indicates at least some de novo contribution to the observed MeSA emissions (see Section 3.1.4). Secondly, significant de novo synthesis of MeSA may have occurred in Roma HS1 at the plant level, but the particular leaf that was sampled for gene expression could have been a low expressor of SISAMT, and vice versa for Roma HS3. Furthermore, Rong et al. (2016) and Maruri-Lopez et al. (2019) reported that MeSA and its salicylic acid precursor are readily interconvertible. It is conceivable that Roma HS3 was indeed synthesizing large amounts of new MeSA as evidenced by the significant upregulation of SISAMT (Figure 6), but the newly synthesized MeSA could have been demethylated back to salicylic acid, thereby resulting in relatively low MeSA emissions.

Moreover, it is possible that the expression levels of all 3 targeted genes corresponding to the enzymes NDPS1, PHS1, and SISAMT were changing with time. All 3 genes may have been upregulated in Roma HS1 during some period of the heat treatment, and the plant may have been synthesizing new MeSA and MTs at increased rates, but the gene expression levels could have decreased toward the end of the heat treatment, when the leaves were harvested for gene analysis. Pazouki et al. (2016) reported a circa 2-h time delay between the onset of gene expression and terpenoid emission response in 5-min heat-shocked tomato leaves. However, our data show an almost immediate induction of MT emissions following heat stress (Figure 4), which again indicates a physical pool volatilization origin for the bulk of the observed MT stress emissions. Further investigation into the role of genes in modulating heat stress-induced BVOC emissions would require gene expression measurements at higher temporal resolutions from more plant replicates with multiple leaf samples from each plant in conjunction with high time-resolution BVOC emission measurements.

### 3.4. Essential oil composition and pool size

The VOC content in the essential oils of 4 Beefsteak and 4 Roma tomato seedlings were quantified via GC-MS. It is important to note that the essential oil analyses were not conducted on the same plants used in the heat stress-VOC emission study (henceforth referred to as “chamber” plants to differentiate them from the plants selected for essential oil analyses). We found that there was some variability in the absolute amounts, but the composition (i.e., presence or absence) of individual VOC species in the stored pools was mostly consistent among the 8 sampled plants (Figures 7 and S4). The VOC species with the highest pool concentrations were MeSA (22.9–37.6 µg/g in Beefsteak and 27.9–47.9 µg/g in Roma), β-phellandrene (14.9–55.4 µg/g in Beefsteak and 9.1–16.4 µg/g in Roma), β-caryophyllene (4.3–28.3 µg/g in Beefsteak and 2.1–13.6 µg/g in Roma), 2-carene (6.1–30.3 µg/g in Beefsteak and 3.9–6.5 µg/g in Roma), and limonene (3.8–14.6 µg/g in Beefsteak and 2.2–4.0 µg/g in Roma). The sum of these 5 compounds accounted for 77% to 88% of all stored VOCs in the sampled plants. In general, the pool concentrations of most VOC species were higher in the sampled Beefsteak plants than in the Roma (Figure S4). In a recent study, Dehimeche et al. (2021) reported the major constituents of tomato foliar essential oil to be α-pinene, 2-carene, β-phellandrene, and β-caryophyllene, which together accounted for 70% to 95% of all stored VOCs in their sampled plants. The pool concentration values for most of the major compounds reported in our study are comparable with the values reported by Dehimeche et al. (2021). However, Dehimeche et al. (2021) did not report limonene as a stored VOC, and their reported MeSA pool concentrations were notably lower than our values. This disparity could be a result of the different cultivars used in the two studies. The high MeSA pool concentrations reported in our study could also be attributed to some undetected physiological stress.

Figure 7.

VOC storage pool sizes. VOC content (µg/g FW) in the stored pools of 4 Beefsteak and 4 Roma tomato plants (quantified via GC-MS). The values are expressed on a log2 scale. BDL = below detection limit; GC-MS = gas chromatography with mass spectrometry. DOI: https://doi.org/10.1525/elementa.2021.00096.f7

Figure 7.

VOC storage pool sizes. VOC content (µg/g FW) in the stored pools of 4 Beefsteak and 4 Roma tomato plants (quantified via GC-MS). The values are expressed on a log2 scale. BDL = below detection limit; GC-MS = gas chromatography with mass spectrometry. DOI: https://doi.org/10.1525/elementa.2021.00096.f7

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Both our study and Dehimeche et al. (2021) identified β-caryophyllene as the dominant stored SQT in the essential oil of tomato foliage. The measured storage pool concentrations of β-caryophyllene are comparable to those of β-phellandrene (Figure 7 in our study; table 1 in Dehimeche et al., 2021), which is typically the dominant compound in tomato foliar BVOC emissions (see Section 3.1.1; Table 1). However, the literature-reported ERs of β-caryophyllene from tomato foliage are consistently much lower than that of β-phellandrene. The average unstressed ERs (normalized to 30°C) of β-phellandrene and β-caryophyllene are 29.9 and 2.04 pmol m–2 s–1, respectively, based on values reported by Gentner et al. (2014), Pazouki et al. (2016), Dehimeche et al. (2021), and this study. Heat stress enhances β-caryophyllene emissions (Figure 2 in our study; figure 5B in Pazouki et al., 2016), but the stressed emission value is still much lower than that of β-phellandrene. Despite having similar storage pool sizes, the ER of β-caryophyllene is approximately 15 times lower than that of β-phellandrene. This disparity is likely a result of the difference in volatilities between the 2 compounds. β-phellandrene has a vapor pressure of 1.59 mmHg at 25°C, while the corresponding predicted value for β-caryophyllene is 0.0255 mmHg (EPA CompTox), which is 62 times lower. Assuming an average βvp value of 0.062°C–1 for MTs and 0.093°C–1 for SQTs (Table 2), the vapor pressure of β-caryophyllene at 42°C would be 0.124 mmHg, which is still 37 times lower than the corresponding value of 4.56 mmHg for β-phellandrene. Due to its significantly lower volatility, β-caryophyllene would have a greater tendency than β-phellandrene to remain inside its storage pool, rather than emit into the atmosphere, even at moderately elevated temperatures. Another possible explanation for the lower emissions is that some portion of the stored β-caryophyllene in tomato foliage might reside within internal pools that are not open to the atmosphere. Two other SQTs, β-elemene and δ-elemene were also consistently present in our stored pool measurements, but these were not emitted at detectable levels by any of the “chamber” tomato plants at either ambient or heat stress temperatures (Figures 1 and S1A–B), likely due to their lower pool concentrations (0.21–7.5 µg/g; Figure 7) and presumed low volatilities.

To deduce the impact of heat stress on BVOC storage pool sizes and long-term ERs, we estimated the pool depletion time of each BVOC species for the 2 Beefsteak and 4 Roma “chamber” tomato plants (Figure 8 and Table S4A–C) by dividing the BVOC pool size (expressed on a leaf area basis in units of pmol/m2) by the observed ER (quantified via GC-MS). This derived variable characterizes the time required to completely exhaust the BVOC of interest from its storage pool if emission to the atmosphere continues at the observed rate and there is no additional production. Three different pool depletion times were calculated for each BVOC from each of the 6 plants: (1) median value before heat stress, (2) median value during heat stress, and (3) minimum value. The median pool depletion times were calculated using the median ERs, while the minimum time was derived from the maximum ER observed during the experimental period. Both daytime and nighttime emission values were included in the calculations, except for the first emission measurement (i.e., 1–2 h after the plant was enclosed), which was typically artificially elevated.

Figure 8.

VOC storage pool depletion times. Median storage pool depletion times (in days) for 31 compounds. The values were calculated using the emission rates from the 2 Beefsteak and 4 Roma “chamber” plants measured both before and during the heat stress. Absent data points indicate either undetectable emissions, undetectable storage pools, or both. The pool depletion times for the individual plants (including both median and minimum values) are tabulated in the Supplemental Material (Table S4A–C). DOI: https://doi.org/10.1525/elementa.2021.00096.f8

Figure 8.

VOC storage pool depletion times. Median storage pool depletion times (in days) for 31 compounds. The values were calculated using the emission rates from the 2 Beefsteak and 4 Roma “chamber” plants measured both before and during the heat stress. Absent data points indicate either undetectable emissions, undetectable storage pools, or both. The pool depletion times for the individual plants (including both median and minimum values) are tabulated in the Supplemental Material (Table S4A–C). DOI: https://doi.org/10.1525/elementa.2021.00096.f8

Close modal

The storage pools of most of the emitted compounds were large enough to sustain unstressed emission levels for at least a few days, and for several months and even years for some compounds (Figure 8). Roma HS1, HS2, and HS3 generally had longer pool depletion times than the other 3 plants (Table S4A–C) due to their relatively lower emissions. Exposure to heat stress enhanced the emissions of most compounds, which in turn would have depleted the storage pools at a faster rate (Figure 8). The relatively short minimum pool depletion times of some BVOCs (Table S4C) indicate that high emissions, even if only temporary, could diminish the pool sizes of those BVOCs, thereby depressing subsequent emissions. Furthermore, the duration of emissions would presumably be shortened if there were no additional de novo production to replenish the exhausted pools. We note that our estimated pool depletion times did not always agree with the observed BVOC emission persistence. For example, γ-terpinene emissions from Roma HS2 and HS3 and MeSA emissions from Roma HS3 decreased to undetectable levels by the final period of the heat treatment (Figure S1A), even though the corresponding minimum pool depletion times were much longer than the experimental duration (11.6, 29.6, and 303 days, respectively; Table S4C). In contrast, α-terpinene, camphene, and o-cymene emissions from Beefsteak 2 remained at elevated levels during the final period of the heat stress (Figure S1A), even though the corresponding median pool depletion times were shorter than a day (0.312, 0.358, and 0.175 days, respectively; Table S4B). This suggests that de novo-synthesized BVOCs made a significant contribution, thereby sustaining emissions. Several compounds including MT 18.69, α-copaene, SQT 27.57, SQT 28.50, and TMTT were not detected in the foliar storage pools of Beefsteak or Roma but were present in the emission profiles of some of the plants (Table S4C). It is possible that the amount of these BVOCs in the storage pools was BDL, but this still indicates that the stored amount was small compared to the atmospheric emission, which suggests that the majority of these emissions originated from de novo synthesis. However, having the essential oil analyses conducted on plant individuals that were different than those used in the BVOC emission study adds to the uncertainties associated with these results.

Foliar BVOC emissions from 24-h heat-stressed tomato plants were investigated using real-time PTR-MS technique for continuous MeSA and total MT emission measurements and off-line GC-MS (via sorbent cartridge sampling) for speciated terpenoid measurements. Preheat stress BVOC ERs were generally low, for 16 out of the 18 sampled plants, with a median total MT ER at 30°C of 18.5 pmol m–2 s–1 and median total SQT ER of 0.172 pmol m–2 s–1, where both values were measured via GC-MS. We therefore conclude that tomato foliage is not a significant source of BVOC emissions at ambient temperatures and in unstressed conditions, as also shown by Jansen et al. (2009), Copolovici et al. (2012), Gentner et al. (2014), Pazouki et al. (2016), Tomescu et al. (2017), and Dehimeche et al. (2021). However, following initial exposure to heat stress, the ERs of approximately half of the targeted compounds from the sampled plants increased beyond what was expected based on current BVOC emission temperature response algorithms. These results demonstrate that the current algorithms do not perform well in modeling the emission behavior of heat-stressed plants (i.e., at temperatures greater than approximately 35°C), as they do not account for the elicitation of stress emissions in addition to the existing constitutive emissions. It is important to note that not all compounds responded to heat stress in the same manner. MT emissions, for the most part, exhibited an increase, especially in the initial period of the heat treatment. In contrast, MeSA, a known stress marker, had a variable response to heat stress, where in some plants, MeSA emissions increased initially after heat exposure, while in others, emissions declined or did not change significantly. The heat stress emission magnitude subsequently decreased for many of the emitted compounds during the final period of the heat treatment, likely due to diminishing terpene storage pools and/or reduced terpene synthase and photosynthetic activity. This heat-enhanced emission behavior underscores the importance of using temperature-controlled enclosure systems for emission factor measurements. Unintended physiological stress stemming from elevated enclosure temperatures can bias plant emission data toward higher than normal values even after temperature normalization and could therefore reduce the accuracy of emission models. Consequently, the atypically high tomato foliar BVOC ERs reported in some of the earlier studies (Arey et al., 1991; Winer et al., 1992) must be revised and should not be used in emission models. The tomato plants that were sampled in these studies were likely heat-stressed and/or mechanically disturbed, and their emission values would not be representative of unstressed tomato plants in ambient conditions.

The results from our gene expression measurements on select tomato plants were inconclusive. We found no significant correlation between the magnitude of gene expression and emission induction of MTs or MeSA among the sampled plants. Elucidating genetic-level controls on tomato stress emission response would require additional gene expression measurements at higher temporal resolutions from more plant samples. Our continuous BVOC measurements via PTR-MS indicate that the bulk of the observed MT stress emissions likely originated from existing foliar storage pools and not from increased de novo synthesis, as evidenced by the weak light-dependence of MT emissions. In contrast, MeSA emissions exhibited both enzyme-controlled (i.e., light-dependent) and light-independent behaviors and likely had contributions from both de novo synthesis and stored pools. Our analyses of the BVOC composition and content in the essential oils of tomato foliage demonstrate that most of the emitted compounds were also consistently present in the stored pools of the sampled plants, barring a few exceptions. The measured pool sizes of most compounds were sufficiently large to sustain unstressed emissions on the order of days to months and even years. However, heat stress-enhanced emissions would deplete these pools at a faster rate. Therefore, long-term heat exposure would presumably shorten the duration of emissions if there were no additional de novo production.

The data generated in this study are provided within the Supplemental Materials of this manuscript.

Table S1. Compound classes, molecular formula, CAS numbers, and major ion fragments of the 31 targeted BVOCs (docx).

Table S2. βvp values for various BVOCs (docx).

Table S3. Stomatal conductance for water vapor (docx).

Table S4A–C. Storage pool depletion times for select plants (docx).

Figure S1A–B. Heat stress BVOC emission response and corresponding β coefficients (docx).

Figure S2A–C. Total and speciated monoterpene emissions for 9 plants (docx).

Figure S3. Select speciated monoterpene emission time series (docx).

Figure S4. VOC storage pool sizes (docx).

Equation S1. Equation describing the overall uncertainty in the reported BVOC emission rates (docx).

Data File S1. Tomato VOC emission rates measured via GC-MS (xlsx).

Data File S2. Tomato VOC pool sizes measured via GC-MS (xlsx).

The research work presented in this paper was financially supported by the US National Science Foundation [award no: AGS-1643042], including salary support for SN, RS, CB, SK, and AG. RS acknowledges grants RYC2020-029216-I and CEX2018-000794-S funded by the Spanish Ministry of Science and Innovation and the State Research Agency (MCIN/AEI/ 10.13039/501100011033) and by the European Social Fund “ESF Investing in your future.”

AG and SK are associate editors at Elementa but played no role in the review or editorial process of this paper.

Designed, planned, and carried out the experiments and analyzed the data: SN.

Interpreted the results: SN and AG.

Designed and built the gas exchange system and wrote the code to process the output data: RS.

Conducted the gene expression measurements and analyzed and interpreted the resulting data: KM and CB.

Wrote the original draft of this manuscript: SN and AG.

Contributed to manuscript writing and revision and approved the submitted version: All authors.

Conceived and acquired the funding for the study: AG and SK.

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How to cite this article: Nagalingam, S, Seco, R, Musaev, K, Basu, C, Kim, S, Guenther, A. 2022. Impact of heat stress on foliar biogenic volatile organic compound emission and gene expression in tomato (Solanum lycopersicum) seedlings. Elementa: Science of the Anthropocene 10(1). DOI: https://doi.org/10.1525/elementa.2021.00096

Domain Editor-in-Chief: Detlev Helmig, Boulder AIR LLC, Boulder, CO, USA

Associate Editor: Ralf Koppmann, University of Wuppertal, Wuppertal, Germany

Knowledge Domain: Atmospheric Science

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