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Photochemical Characterization of Greenhouse-grown Lettuce (Lactuca sativa L. ‘Green Towers’) with Applications for Supplemental Lighting Control

Authors:
Geoffrey WeaverDepartment of Horticulture, University of Georgia, 1111 Miller Plant Sciences Building, Athens, GA 30602

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Marc W. van IerselDepartment of Horticulture, University of Georgia, 1111 Miller Plant Sciences Building, Athens, GA 30602

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Abstract

Plant light use efficiency decreases as light intensity is increased, and a better understanding of crop-specific light responses can contribute to the development of more energy-efficient supplemental lighting control strategies for greenhouses. In this study, diurnal chlorophyll fluorescence monitoring was used to characterize the photochemical responses of ‘Green Towers’ lettuce (Lactuca sativa L.) to photosynthetic photon flux density (PPFD) and daily light integral (DLI) in a greenhouse during a production cycle. Plants were monitored continuously for 35 days, with chlorophyll fluorescence measurements collected once every 15 minutes. Quantum yield of photosystem II (ΦPSII) decreased exponentially with PPFD, whereas electron transport rate (ETR) increased asymptotically to 121 µmol·m–2·s–1. Daily photochemical integral (DPI) is defined as the integral of ETR over a 24-hour period; DPI increased asymptotically to 3.29 mol·m–2·d–1 with increasing DLI. No effects of plant age or prior day’s DLI and a negligible effect of PPFDs 15 or 30 minutes before measurements within days were observed. Simulations were conducted using the regression equation of ETR as a function of PPFD {ETR = 121[1 – exp(–0.00277PPFD)]} to illustrate methods of increasing photochemical light use efficiency for improved supplemental lighting control strategies. For a given DLI, DPI can be increased by providing light at lower PPFDs for a longer period of time, and can be maximized by providing light with a uniform PPFD throughout the entire photoperiod. Similarly, the DLI required to achieve a given DPI is reduced using these same methods.

Supplemental lighting can improve the profitability of greenhouse crop production, and a better quantitative understanding of plant responses to PPFD can facilitate the development of more efficient crop-specific control strategies for greenhouse supplemental lighting (van Iersel, 2017). Chlorophyll fluorescence measurements are a rapid and reliable means of probing the light reactions of photosynthesis directly (Baker, 2008). During the light reactions, some of the light energy absorbed by chlorophylls and accessory pigments migrates to photosystem II (PSII) reaction centers, resulting in the splitting of water molecules, liberating electrons and protons. The freed electrons are used to regenerate nicotinamide adenine dinucleotide phosphate hydrogen (NADPH) via the electron transport chain, and a proton gradient across the thylakoid membrane drives adenosine triphosphate (ATP) synthase, regenerating ATP. These energy-rich molecules—NADPH and ATP—provide the reducing power and chemical energy for carbohydrate production in the Calvin-Benson-Bassham cycle. However, not all light absorbed by photosynthetic pigments is used to drive the light reactions; a significant amount is dissipated as heat, and a small fraction is reemitted as fluorescence. By measuring the fluorescence emitted by chlorophyll a molecules before and during short exposure to a beam of light with sufficient intensity to saturate the PSII reaction centers completely (a “saturating pulse”), ΦPSII can be quantified directly. ΦPSII is a unitless measure of the efficiency with which absorbed light is used to drive photochemistry in the light-adapted state of PSII. The dark-adapted value of the quantum efficiency of PSII (Fv/Fm) is an indicator of maximum potential photochemical efficiency. Combined with PPFD, ΦPSII is used to calculate the rate of linear electron transport through PSII (the ETR), an estimate of the overall rate of the light reactions of photosynthesis (Baker and Rosenqvist, 2004; Genty et al., 1989; Maxwell and Johnson, 2000). To distinguish measurements based on chlorophyll fluorescence from other measures of photosynthesis such as gas exchange or oxygen evolution, data related to ΦPSII and ETR are referred to as photochemical rather than photosynthetic herein.

Chlorophyll fluorescence is an ideal tool for understanding crop-specific photochemical responses to PPFD. Chlorophyll fluorometers are generally small and portable, with simple operation that requires no recalibration. Measurements can be collected quickly in situ, and are noninvasive and accurate (Baker and Rosenqvist, 2004; Maxwell and Johnson, 2000). An exact correlation between ETR and CO2 fixation rates may be difficult to establish because the products of the light reactions can be used to drive processes other than the Calvin-Benson-Bassham cycle. Photorespiration is a major sink for NADPH and ATP in C3 plants (Krall and Edwards, 1992), and NADPH may be used as an electron donor for nitrate reduction (Tischner, 2000). Freed electrons may reduce O2 at photosystem I (Mehler reaction, or water–water cycle) rather than be used to produce NAPDH (Polle, 1996), and ATP can be used for chloroplast functions such as protein repair and nucleotide metabolism (Murata and Nishiyama, 2018; Spetea et al., 2004). Thus, the relationship between ETR and CO2 fixation depends on many factors, including temperature, relative humidity, CO2 concentration, and water and nutrient availability. However, ETR can be taken as a relative indicator of overall photosynthetic rates, and hence plant growth. Furthermore, compared with gas exchange, ETR of C3 plants is relatively insensitive to changes in environmental variables other than light (Murchie and Lawson, 2013). Thus, chlorophyll fluorescence measurements provide a convenient, rapid, accurate, and robust means of evaluating photochemical responses to PPFD.

Light response curves collected using chlorophyll fluorescence measurements are typically performed over a relatively brief period (often just a few minutes) with a highly focused light source and may not represent photochemical responses accurately under variable ambient light conditions (Rascher et al., 2000). Photoprotective processes affect photochemical light use efficiency by reducing the amount of absorbed light energy transferred to PSII reaction centers, and may operate over longer timescales. Because the accumulation of excess light energy in the light-harvesting complexes can lead to light-induced damage of PSII reaction centers (photoinhibition), plants have evolved a variety of interrelated photoprotective mechanisms by which excess absorbed light energy can be dissipated safely as heat, including molecular reorganization of PSII and the xanthophyll cycle (Demmig-Adams et al., 2012; Horton, 2012; Rochaix, 2014; Ruban, 2015). As PPFD increases, a larger fraction of absorbed light is dissipated as heat, resulting in a decrease in ΦPSII (Baker, 2008; Maxwell and Johnson, 2000). Fluctuations in PPFD throughout the course of a day can lead to variations in ΦPSII as a result of the up- or downregulation of the xanthophyll cycle. The xanthophyll cycle is the process by which the accumulation of protons leads to acidification of the thylakoid lumen, activating violaxanthin de-epoxidase, which catalyzes the de-epoxidation of violaxanthin to form antheraxanthin and zeaxanthin. This chemical conversion of the xanthophyll pigments facilitates the dissipation of excess light energy as heat. It reverses relatively slowly, over a scale of several minutes, through epoxidation catalyzed by zeaxanthin epoxidase. Because of this slow relaxation, transient exposure to high light levels may lead to decreases in photochemical efficiency (relative decreases in ΦPSII and ETR) for several minutes even if PPFDs subsequently decrease to much lower levels (Demmig-Adams et al., 2012; Kaiser et al., 2018; Ruban, 2015). Photochemistry-induced acidification of the thylakoid lumen can further affect rates of electron transport by inhibiting plastohydroquinone oxidation by the cytochrome b6f complex, thereby decreasing the rate of linear electron transport through PSII, in a process known as photosynthetic control (Foyer et al., 2012).

Light response curves collected over a short period of time may also be inadequate to describe photochemical responses for an entire growing period because photosynthetic rates can vary with leaf or plant age (Locke and Ort, 2014; Salmon et al., 2011) and can be affected by slow acclimation to light intensities. Acclimation to light intensities over the course of hours or days can lead to changes in the overall light response through mechanisms such as chlorophyll antennae rearrangement or changes in cellular metabolism and translation, and nuclear transcription, induced by chloroplast signaling (Dietz, 2015; Ruban, 2015). If factors such as ontogeny or acclimation impact the overall photochemical light response significantly, light response curves collected over only a few minutes may not describe realistic photochemical responses for a crop sufficiently, and longer term monitoring would be needed to characterize the photochemical response during a production cycle. Diurnal chlorophyll fluorescence monitoring can be used to gain a more detailed understanding of the photochemical light response under greenhouse lighting conditions (Weaver and van Iersel, 2016). This method consists of measuring chlorophyll fluorescence and PPFD over the course of several days, with measurements taken at regular intervals. In general, a 15-min interval between chlorophyll fluorescence measurements is sufficiently long to avoid measurement-induced photoinhibition resulting from the repeated application of saturating light pulses (van Iersel et al., 2016).

Although supplemental lighting can improve the growth, quality, and profitability of greenhouse-grown crops, the electricity requirement of supplemental lights can account for as much as 30% of the operating cost of a greenhouse (van Iersel and Gianino, 2017; Watson et al., 2018). The advent of light-emitting diode (LED) technology for horticultural lighting has facilitated the development of innovative approaches to providing and controlling greenhouse supplemental lighting (Morrow, 2008; Pinho et al., 2012; Singh et al., 2015). LED fixtures have several distinct advantages over the high-intensity discharge (HID) lamps traditionally used for greenhouse lighting, including their relatively high efficacy, low radiant heat load, and variable spectra. Another unique feature of LEDs is that the intensity of their light output can be controlled precisely and rapidly in a manner that is not possible with HID lamps. Lighting control systems that use this dimmability have the potential to reduce the electricity costs associated with providing supplemental light, and to increase the efficiency with which supplemental light is used for promoting plant growth. These adaptive, or dynamic, supplemental LED lighting control systems operate by keeping the LED lights off when ambient PPFD exceeds a predefined threshold PPFD. When ambient PPFD falls below this level, supplemental light is provided so that the combined PPFD of the LED lights and sunlight reaches, but does not exceed, the threshold. This ensures that supplemental light is provided only when the overall PPFD is relatively low, and the supplemental light can be used more efficiently by plants, because plant light use efficiency invariably decreases at greater PPFDs (Pinho et al., 2013; van Iersel and Gianino, 2017).

Providing supplemental light in a manner that allows it to be used most efficiently by a crop has the potential to decrease the amount of supplemental light, and thus the total amount of electricity required, for crop growth. For example, using simulations based on historical weather data and cultivar-specific light responses, Weaver and van Iersel (2018) estimated that the amount of supplemental light required for early season production can be reduced by 24% for Petunia ×hybrida ‘Daddy Blue’ and 37% for Impatiens walleriana ‘Super Elfin XP Violet’ using an adaptive lighting control approach that accounts for crop light use efficiency. Thus, understanding species- or cultivar-specific photosynthetic or photochemical responses to PPFD can facilitate the implementation of lighting control strategies that use the dimmability of LEDs fully and reduce electricity costs by providing supplemental light according to a specific crop’s ability to use that light efficiently.

Lettuce is an important greenhouse crop because there is a continuous demand for a supply of fresh leafy greens, production cycles are relatively short, and lettuce can be produced year-round in greenhouses if appropriate environmental conditions (e.g., light, temperature) are provided. Supplemental lighting for hydroponic greenhouse lettuce production has been the subject of a great deal of research, and some of the most advanced supplemental lighting strategies developed to date have focused on lettuce production (Albright et al., 2000; Bumgarner and Buck, 2016; Seginer et al., 2006). In our study, in situ diurnal chlorophyll fluorescence monitoring was used to evaluate the photochemical performance of a greenhouse-grown crop of a romaine-type lettuce cultivar (Lactuca sativa L. ‘Green Towers’) under growing conditions comparable to a commercial production environment. Specific hypotheses tested were whether the current ETR is affected by previous PPFDs during a day, and whether photochemical efficiency is affected by plant age or previous day’s DLI. In addition to quantifying instantaneous photochemical responses to PPFD, the integral of ETR over individual measurement days was calculated and defined as the DPI (mol·m−2·d−1), the integral of ETR over a 24-h period. Last, we conducted simulations to demonstrate how these data can be used to develop energy-efficient supplemental lighting strategies, and outline general methods for using adaptive lighting control to improve crop light use efficiency by decreasing the DLI required to achieve a given DPI, or increasing the resulting DPI for a fixed DLI.

Materials and Methods

The study was conducted in a glass-covered greenhouse in Athens, GA, during Mar. and Apr. 2015. The mean relative humidity (±σ) was 66.3 ± 16.3%, the mean temperature was 21.4 ± 1.7 °C, and the mean DLI was 13.9 ± 6.8 mol·m–2·d–1 (Fig. 1). Seeds of ‘Green Towers’ lettuce were sown in 10-cm square pots filled with a peat–perlite substrate (Fafard 2P; Sun Gro Horticulture, Agawam, MA). Fifteen plants were grown on ebb-and-flow benches and fertigated daily with a 100 mg·L−1 N liquid fertilizer (15N–2.2P–12.45K; 15–5–15 Cal-Mag; Everris, Marysville, OH). The plants were grown without shading to ensure that measurements could be taken under the widest range of DLIs and PPFDs possible.

Fig. 1.
Fig. 1.

Daily light integral (DLI) over the course of the study.

Citation: HortScience horts 54, 2; 10.21273/HORTSCI13553-18

Chlorophyll fluorescence monitoring was initiated 2 weeks after germination and was performed using a chlorophyll fluorometer and attached leaf clip with quantum sensor (JUNIOR-PAM; Heinz Walz, Effeltrich, Germany). The most recently fully expanded leaf was measured until the onset of head formation, after which the youngest fully expanded leaf exterior to the head was measured. Leaves were placed in the leaf clip and positioned such that the quantum sensor was exposed fully to the south side of the greenhouse and not shaded by other leaves. Chlorophyll fluorescence measurements were taken once every 15 min to determine ΦPSII, and PPFD was measured using the built-in quantum sensor on the leaf clip. ETR, an estimate of the rate of the light reactions of photosynthesis, was calculated from ΦPSII and PPFD as ETR = ΦPSII × PPFD × 0.84 × 0.5. This equation assumes that excitation energy is distributed evenly between PSII and photosystem I, and that 84% of incident light is absorbed by a leaf (Björkman and Demmig, 1987; Genty et al., 1989). After 48 h, a different plant was selected randomly for measurement, and measurements using the new plant commenced at least 1 h after sunset to verify that the Fv/Fm of the new leaf section was within an acceptable range: at least 0.78, with a theoretical maximum of around 0.85. Observations of Fv/Fm less than 0.78 indicate that the leaf is experiencing some type of stress and may be senescing. Values exceeding 0.85 are usually the result of measurement error, especially improper positioning of the fluorometer sensor head. This initial value was recorded and used as the value of Fv/Fm for subsequent analysis. Chlorophyll fluorescence monitoring continued in this fashion for 35 d and ended when the plants had formed a head and reached a salable size. Only one plant was measured at any given time because no treatments were applied or compared, and replications were not needed for a statistical analysis of the data.

DLI was calculated by integrating PPFD over each 24-h period, with PPFD assumed to be constant for each 15-min increment of the 24-h period. DPI was calculated by integrating ETR over each 24-h period, with ETR assumed to be constant for each 15-min increment of the 24-h period. The 24-h period was defined as beginning and ending at midnight. The apparent saturating PPFD for ETR was calculated as the PPFD at which 90% of the asymptote of ETR was reached. The apparent saturating DLI for DPI was calculated as the DLI at which 90% of the asymptote of DPI was reached.

Regression analyses were performed using SigmaPlot (version 13; Systat Software, Inc., San Jose, CA). Regression analysis was used to evaluate ETR and ΦPSII as functions of PPFD for all days pooled and for individual days, and to evaluate Fv/Fm as a function of measurement day and preceding day’s DLI. ETR was fit as a function of PPFD using the equation ETR = a[1 – e–b(PPFD)], ΦPSII was fit as a function of PPFD using the equation ΦPSII = c + a[e–b(PPFD)], and DPI was fit as a function of DLI using the equation DPI = a[1 – e–b(DLI)], where a, b, and c are regression coefficients. To test the hypothesis that plant age affected photochemical capacity, daily asymptotes of ETR were analyzed as a function of plant age for all measurement days with at least two observations of PPFD greater than 831 µmol·m–2·s–1, the apparent saturating PPFD for the pooled ETR response. The analysis was restricted to days on which saturating PPFDs were observed to ensure that an accurate approximation of the asymptote could be obtained. These asymptotes were also analyzed as a function of the previous day’s DLI to test whether acclimation to the previous day’s DLI affected the current day’s photochemical capacity. To test the hypothesis that previous PPFDs affected current photochemistry within days, ΦPSII was analyzed as a quadratic function of current PPFD and the observed PPFDs 15 and 30 min prior (PPFD15 and PPFD30, respectively) for all days, using polynomial regression with a general linear model (Proc GLM, SAS version 9.2; SAS Institute, Cary, NC) according to the model: ΦPSII = a0 + a1 × PPFD + a2 × PPFD2 + a3 × PPFD15 + a4 × PPFD30, where a0, . . . , a4 are regression coefficients. Significance was tested at P = 0.05. To test further the effect of within-day variations in PPFD on ETR and ΦPSII, observations of ETR and ΦPSII occurring before and after solar noon for nonzero PPFDs were compared and tested for significant differences at P = 0.05 using a mixed-model analysis of covariance, where day of experiment was treated as a random effect, time of day (before/after solar noon) was a fixed effect, and PPFD was a covariate. Analysis was performed using the general linear model in SAS (Proc GLM). The covariate effect was approximated using a ninth-order polynomial for ETR and a sixth-order polynomial for ΦPSII, according to the model y = a0 + a1 × PPFD + . . . + an × PPFDn, where y is the dependent variable, n is the highest order of the polynomial, and a0, . . . , an are regression coefficients. Polynomial order for each dependent variable was selected by using Taylor’s theorem to determine the lowest order polynomial needed to replicate accurately the function values of the exponential equations fitted via regression analysis over at least 90% of the range of the PPFD data. Polynomial fit was verified using regression analysis in SAS, with model significance tested at P = 0.001.

Data from five measurement days were excluded from the analyses and graphs because observations of Fv/Fm recorded more than 1 h after sunset following the first photoperiod of diurnal measurement fell outside the acceptable range (0.78–0.85)—the same criteria used for the initial measurement of Fv/Fm at the onset of diurnal monitoring. In addition, observations were missing from 3 measurement days, and thus DPI and DLI were not calculated for these days.

Simulations were conducted based on the relationship between ETR and PPFD. A set of simulations was conducted in which the objective was to reach a DLI of 17 mol·m–2·d–1 with nine photoperiods (8–24 h, 2-h intervals) with a constant PPFD. The required constant PPFD for each photoperiod was determined by dividing 17 mol·m–2 by the photoperiod. ETRs corresponding to these PPFDs were calculated using the regression equation of ETR as a function of PPFD. Calculated ETRs were integrated over the photoperiod to obtain the DPI. Further simulations were conducted in which the objective was to reach a DLI of 17 mol·m–2·d–1 with a 12-h photoperiod using two PPFDs, each for half of the photoperiod, with a range of differences (0–700 µmol·m–2·s–1) between the two PPFDs (ΔPPFD). The constant PPFD for the 0-µmol·m–2·s–1 difference scenario was calculated as described earlier to be 394 µmol·m–2·s–1. For the remaining scenarios, the required PPFD for each half of the photoperiod was calculated by increasing or decreasing 394 µmol·m–2·s–1 by one-half the required difference in PPFD. For each half of the photoperiod, ETR was calculated using the regression equation of ETR vs. PPFD, and DPI was obtained by integrating these values over the whole photoperiod. A third set of simulations was conducted in which the objective was to reach a DPI of 2.89 mol·m–2·d–1 with nine photoperiods (8–24 h, 2-h intervals) with a constant ETR (which corresponds to a constant PPFD). The required constant ETR was calculated for each photoperiod by dividing 2.89 mol·m–2 by the photoperiod. The corresponding PPFD was calculated using the inverse function of the regression equation of ETR as a function of PPFD: PPFD = ln(a/a – ETR)/b, where a and b are regression coefficients. DLI was obtained by integrating this PPFD over the photoperiod.

Results and Discussion

Quantum yield of PSII decreased exponentially (R2 = 0.89, P < 0.0001) as PPFD increased from 0 to ≈1500 µmol·m–2·s–1, the greatest PPFD observed during this study (Fig. 2, top). This decrease in ΦPSII was observed because, as PPFD increases, a greater proportion of absorbed light energy is dissipated as heat as a result of the operation of the xanthophyll cycle and other photoprotective processes, leaving a smaller fraction of the light to drive photochemistry (Demmig-Adams et al., 2012; Horton, 2012; Rochaix, 2014; Ruban, 2015). The response of ETR to PPFD was an exponential rise to a maximum (Fig. 2, bottom) with an asymptote of 121 µmol·m–2·s–1 and an initial slope of 0.335 mol of electrons per mole of incident photons (R2 = 0.95, P < 0.0001). The apparent saturating PPFD (reached at 90% of the asymptote of ETR) was 831 µmol·m–2·s–1.

Fig. 2.
Fig. 2.

Quantum yield of photosystem II (ΦPSII) of ‘Green Towers’ lettuce as a function of photosynthetic photon flux density (PPFD) based on 35 d of constant diurnal monitoring. Closed symbols represent measurements taken before solar noon; open symbols represent measurements taken after solar noon. The regression line represents the equation ΦPSII = 0.171 + 0.643e–0.00178PPFD, with R2 = 0.89 and P < 0.0001 (top). Electron transport rate (ETR) of ‘Green Towers’ lettuce as a function of PPFD based on 35 d of constant diurnal monitoring. Closed symbols represent measurements taken before solar noon; open symbols represent measurements taken after solar noon. The regression line represents the equation ETR = 121(1 – e–0.00277PPFD), with R2 = 0.95 and P < 0.0001 (bottom).

Citation: HortScience horts 54, 2; 10.21273/HORTSCI13553-18

There was no significant change in the daily asymptotes of ETR throughout the course of the study (data not shown). This suggests that, for this cultivar, plant age has little impact on maximum photochemical capacity. Some of the variability in these data may have been the result of leaf (rather than plant) age, which was not documented. Similarly, Fv/Fm did not change significantly with plant age (data not shown), which could be the result of the short duration of the study or the relative insensitivity of Fv/Fm to leaf ontogeny. Although some chlorophyll fluorescence parameters may change with plant age, Fv/Fm is known to vary little with leaf age, except during senescence (Mauromicale et al., 2006; Šesták, 1999). Because plant age did not affect photochemical characteristics, it is likely that diurnal chlorophyll fluorescence monitoring conducted over a much shorter period of time than the 35 d used in our study would be adequate to describe the photochemical light response of this cultivar over a production cycle. However, because only a small part of one leaf was measured at any given time, these results may not be indicative of entire canopies or the effect of aging on whole-canopy photochemistry.

Fluctuating light levels can affect overall daily rates of photochemistry because photoprotective processes such as the xanthophyll cycle (Demmig-Adams et al., 2012), as well as photosynthetic control (Foyer et al., 2012), can inhibit photochemical light use for several minutes after transient exposure to high light intensities (Kaiser et al., 2018; Slattery et al., 2018). To test the hypothesis that previous light levels affect current photochemistry, ΦPSII was analyzed as a quadratic function of current PPFD and linear effects of the PPFDs observed 15 and 30 min prior. Overall, the model fit well (R2 = 0.86, P < 0.0001) and both PPFD15 and PPFD30 were highly significant (P < 0.0001), but contributed little to the overall model R2 (partial R2 = 0.008 and 0.005, respectively). Thus, PPFDs from the previous 15 and 30 min had a negligible effect on ΦPSII (and hence ETR). Furthermore, there was no significant difference in observations of either ΦPSII or ETR taken before vs. after solar noon (Fig. 2). These results are likely the result of the time resolution of our measurements; the 15-min interval needed to avoid measurement-induced photoinhibition is likely a sufficient span of time for xanthophyll cycle activity to relax almost completely after transient high light exposure. Zeaxanthin is converted back to the nonphotoprotective violaxanthin by zeaxanthin epoxidase on a scale of several minutes (Demmig-Adams et al., 2012; Kaiser et al., 2018). DLIs of individual measurement days also had no significant effect on Fv/Fm measured during the subsequent dark period or on the following day’s asymptote of ETR (data not shown), and the study was conducted under a wide range of DLIs (Fig. 1). Thus, photochemical acclimation over a timescale of days was not observed in this study.

DPI, the integral of ETR over a 24-h period, was evaluated as a function of DLI. Like the response of ETR to PPFD, DPI increased exponentially to a maximum with DLI (Fig. 3; R2 = 0.82, P < 0.0001), with an asymptote of 3.30 mol·m–2·d–1; 90% of this asymptote was reached at a DLI of 18.9 mol·m–2·d–1 (apparent saturating DLI). Previous research showed that the ideal DLI for hydroponic greenhouse production of the bibb lettuce cultivar ‘Ostinata’ is 17 mol·m–2·d–1. At this DLI, growth rates were sufficiently high to guarantee rapid production without causing excessive leaf tip burn (Albright et al., 2000; Both et al., 1997). Interestingly, although a different cultivar was used, the saturating DLI found in our study deviates by only 11% from the recommended DLI based on growth trials (Both et al., 1997). This points to the potential utility of chlorophyll fluorescence monitoring for developing crop-specific DPI or DLI recommendations. However, it is important to recognize that DPI is not a direct function of DLI, but rather of the integral of ETR over a day. ETR in turn is a nonlinear function of PPFD, and hence DPI not only depends on DLI, but also on how observations of PPFD are distributed throughout the course of a day. Because of this, seasonal variation in daily distributions of PPFD would be expected to influence the observed response of DPI to DLI.

Fig. 3.
Fig. 3.

Daily photochemical integral (DPI) of ‘Green Towers’ lettuce as a function of daily light integral (DLI) based on 35 d of diurnal chlorophyll fluorescence monitoring. The regression line represents the equation DPI = 3.30(1 – e–0.122DLI), with R2 = 0.82 and P < 0.0001.

Citation: HortScience horts 54, 2; 10.21273/HORTSCI13553-18

Lighting recommendations for greenhouse crops are currently made based on estimates of the range of DLIs required for ideal production of specific crops (e.g., Torres and Lopez, n.d.). However, with the same DLI, different DPIs can result from providing the same quantity of light with different distributions of PPFD, resulting from the nonlinearity of the ETR response. Although a clear correlation between DPI and crop growth has not yet been established, quantifying DPI provides a means of assessing the effectiveness of greenhouse supplemental lighting control strategies, assuming that an increase in DPI will result in greater growth rates. One means of increasing DPI for a given DLI is to extend the photoperiod, allowing supplemental light to be provided at lower PPFDs, thereby increasing the efficiency of photochemical light use and leading to greater DPIs. Figure 4 shows the PPFD required to reach a DLI of 17 mol·m–2·d–1 using a constant PPFD at a range of photoperiods (8–24 h), with the corresponding calculated ETR and resulting DPI based on the regression equation of ETR as a function of PPFD. As the photoperiod is increased and the constant PPFD decreased, DPI increases from 2.81 mol·m–2·d–1 with an 8-h photoperiod to 4.39 mol·m–2·d–1 with a 24-h photoperiod (Fig. 4). This occurs because the rate of increase in ETR decreases exponentially as PPFD increases, because ETR as a function of PPFD is an exponential rise to a maximum. Evidence from previous research indicates that these simulated increases in DPI do indeed correspond to improved plant growth. Koontz and Prince (1986) showed that providing the same DLI with a 24-h photoperiod increased lettuce weight by 30% to 50% compared with a 16-h photoperiod. Soffe et al. (1977) demonstrated that extending the photoperiod from 12 to 16 h, while holding DLI constant at 5 MJ·m–2, increased growth rates of seven vegetables: lettuce, celery (Apium graveolens), beetroot (Beta vulgaris), spinach beet (Beta vulgaris), radish (Raphanus raphanistrum ssp. sativus), cabbage (Brassica oleracea), and oilseed rape (Brassica napus). Because altering the photoperiod may have unintended consequences for flowering of many daylength-sensitive crops, extending the photoperiod may not always be an option. Another means of increasing DPI for a fixed DLI is to provide supplemental light with a more uniform (less variable) distribution throughout the photoperiod. Figure 5 illustrates this principle. If light is provided to reach a DLI of 17 mol·m–2·d–1 with a 12-h photoperiod, a constant PPFD of 394 µmol·m–2·s–1 would be required, resulting in a DPI of 3.47 mol·m–2·d–1. If the distribution of PPFD is altered such that light is provided to reach a DLI of 17 mol·m–2·d–1 in 12 h, with a greater PPFD for half the photoperiod and a lesser PPFD for the other half (with the difference between these denoted as ΔPPFD), DPI will decrease with increasing ΔPPFD; and, at a ΔPPFD of 700 µmol·m–2·s–1, DPI is reduced to 2.58 mol·m–2·d–1 (Fig. 5). Uniform distributions of PPFD are associated with greater DPIs than more variable distributions as a result of the nonlinearity of the ETR response; as PPFD is decreased or increased by the same amount from some initial value, the decrease in ETR at the lower PPFD will be greater than the increase in ETR at the higher PPFD, and the magnitude of this difference increases as the change in PPFD increases. The hypothesis that an increase in DPI resulting from improved uniformity of PPFD will improve crop growth is supported by past research. Aikman (1989) demonstrated the effect of lighting uniformity on tomato growth. Tomatoes were grown in growth chambers at a constant DLI with a consistent light level of 58 W·m–2 and with two variable light distributions, where the light was provided at 103 W·m–2 for the first half of the day and 13 W·m–2 for the second, or vice versa. Dry weight of plants grown under the uniform light intensity was, on average, 33% greater than in the other treatments. Although the simulations presented herein do not account for the interactions of supplemental LED lights and sunlight, adaptive lighting control can be used to improve the uniformity of PPFDs from LED lights and sunlight combined, and to minimize the PPFD provided by LED lights, thereby achieving equivalent increases in DPI (van Iersel and Gianino, 2017).

Fig. 4.
Fig. 4.

Daily photochemical integral (DPI) resulting from reaching a daily light integral (DLI) of 17 mol·m–2·d–1 with a constant photosynthetic photon flux density (PPFD) over a range of photoperiods required (top); required PPFD, and corresponding electron transport rate (ETR; calculated from equation in Fig. 2, bottom).

Citation: HortScience horts 54, 2; 10.21273/HORTSCI13553-18

Fig. 5.
Fig. 5.

Daily photochemical integral (DPI) resulting from reaching a daily light integral (DLI) of 17 mol·m–2·d–1 with a 12-h photoperiod using two photosynthetic photon flux densities (PPFDs), each for half of the photoperiod, with a range of differences between the two PPFDs (ΔPPFD) (top). Required PPFDs (bottom), and corresponding electron transport rates (ETRs) (middle) are shown. For ΔPPFD = 0, only one PPFD is used.

Citation: HortScience horts 54, 2; 10.21273/HORTSCI13553-18

In a manner analogous to increasing DPI for a given DLI, the DLI required to reach a particular DPI can be reduced by providing supplemental light at lower PPFDs and/or with a more uniform PPFD distribution. Reducing the required DLI will decrease the total amount of supplemental light provided, which results in electricity savings. According to the regression equation of DPI vs. DLI (Fig. 3), a DPI of 2.89 mol·m–2·d–1 corresponds to the recommended DLI of 17 mol·m–2·d–1 for lettuce (Both et al., 1997). If light is provided to reach a DPI of 2.89 mol·m–2·d–1 with a continuous PPFD over a range of photoperiods (8–24 h), the required DLI decreases as the photoperiod is extended (Fig. 6). The greatest DLI requirement, 18.4 mol·m–2·d–1, occurs with an 8-h photoperiod, whereas the DLI required for a 24-h photoperiod is only 10.1 mol·m–2·d–1, a 45% decrease. Similarly, for a fixed photoperiod and DPI, DLI will be reduced if supplemental light is provided with a more uniform distribution of PPFD (Weaver and van Iersel, 2018).

Fig. 6.
Fig. 6.

Daily light integral (DLI) needed to reach a calculated daily photochemical integral (DPI) of 2.89 mol·m–2·d–1 with a constant photosynthetic photon flux density (PPFD) over a range of photoperiods (top); required electron transport rate (ETR) and corresponding PPFD (bottom) based on the regression equation in Fig. 2 (bottom).

Citation: HortScience horts 54, 2; 10.21273/HORTSCI13553-18

Control strategies for greenhouse supplemental lighting that account for daily requirements of photosynthesis or photochemistry have been developed with the goal of reducing electricity costs by decreasing the amount of supplemental lighting required, or providing supplemental lighting when electricity is less expensive (Clausen et al., 2015; Wang et al., 2018; Watson et al., 2018; Weaver and van Iersel, 2018). Kjaer et al. (2011) demonstrated that the electricity cost associated with supplemental lighting can be reduced by 25% without affecting the overall quality of two ornamental Campanula species when supplemental lights are controlled by the DynaLight system. This system accounts for electricity prices and photosynthetic rates to achieve a specified DPI with the lowest possible electricity cost, using a canopy photosynthesis model based on PPFD, temperature, and CO2 concentration (Aaslyng et al., 2003; Clausen et al., 2015; Kjaer et al., 2012). Implementing such strategies requires evaluating crop-specific light response and establishing recommendations for daily photosynthesis or photochemistry for individual crops. The results of our study demonstrate that the response of ETR to PPFD, as determined using diurnal chlorophyll fluorescence monitoring, is robust to plant age, within-day fluctuations in PPFD, and previous day’s DLI for the lettuce cultivar studied. Additional research, including greenhouse growth trials, is needed to evaluate the relationship between DPI and crop growth, and to establish methods for determining crop-specific DPI requirements.

Conclusions

The photochemical responses of ‘Green Towers’ lettuce were found to be consistent throughout the course of our study, and were unaffected by plant age, or previous PPFDs or DLIs within or across days. This suggests that, although diurnal chlorophyll fluorescence monitoring throughout a production cycle provides valuable insight, photochemical light response curves collected for a shorter period of time should be adequate for characterizing crop-specific photochemical responses to develop supplemental lighting control strategies. ETR is an asymptotically increasing function of PPFD, and therefore daily photochemical light use efficiency can be improved by providing supplemental light at relatively low PPFDs over an extended period of time, or by providing supplemental light in a uniform manner. For a given DLI, DPI can be increased by applying these principles. Similarly, the DLI required to achieve a given DPI can be reduced. Further research is needed to assess the effectiveness of supplemental lighting control strategies that account for these dynamics, and to determine whether greenhouse crop production can be improved by providing supplemental light in a photochemically efficient manner.

Literature Cited

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    • Search Google Scholar
    • Export Citation
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    • Search Google Scholar
    • Export Citation
  • Albright, L.D., Both, A.J. & Chiu, A.J. 2000 Controlling greenhouse light to a consistent daily integral Trans. ASABE 43 421 431

  • Baker, N.R. 2008 Chlorophyll fluorescence: A probe of photosynthesis in vivo Annu. Rev. Plant Biol. 59 89 113

  • Baker, N.R. & Rosenqvist, E. 2004 Applications of chlorophyll fluorescence can improve crop production strategies: An examination of future possibilities J. Expt. Bot. 55 1607 1621

    • Search Google Scholar
    • Export Citation
  • Both, A.J., Albright, L.D., Langhans, R.W., Reiser, R.A. & Vinzant, B.G. 1997 Hydroponic lettuce production influenced by integrated supplemental light levels in a controlled environment agriculture facility: Experimental results Acta Hort. 418 45 52

    • Search Google Scholar
    • Export Citation
  • Björkman, O. & Demmig, B. 1987 Photon yield of O2 evolution and chlorophyll fluorescence at 77k among vascular plants of diverse origins Planta 170 489 504

    • Search Google Scholar
    • Export Citation
  • Bumgarner, N. & Buck, J. 2016 Light emitting diode and metal halide supplemental lighting for greenhouse Bibb lettuce production in the Midwestern United States J. Appl. Hort. 18 128 134

    • Search Google Scholar
    • Export Citation
  • Clausen, A., Maersk-Moeller, H.M., Soerensen, J.C., Joergensen, B.N., Kjaer, K.H. & Ottosen, C.O. 2015 Integrating commercial greenhouses in the smart grid with demand response based control of supplemental lighting. Intl. Conf. Ind. Technol. Mgt. Sci. (ITMS 2015) 199–213.

  • Demmig-Adams, B., Cohu, C.M., Muller, O. & Adams, W.W. 2012 Modulation of photosynthetic energy conversion in nature: From seconds to seasons Photosynth. Res. 113 75 78

    • Search Google Scholar
    • Export Citation
  • Dietz, K.J. 2015 Efficient high light acclimation involves rapid processes at multiple mechanistic levels J. Expt. Bot. 66 2401 2414

  • Foyer, C.H., Neukermans, J., Queval, G., Noctor, G. & Harbinson, J. 2012 Photosynthetic control of electron transport and the regulation of gene expression J. Expt. Bot. 63 1637 1661

    • Search Google Scholar
    • Export Citation
  • Genty, B., Briantais, J. & Baker, N.R. 1989 The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence Biochim. Biophys. Acta 990 87 92

    • Search Google Scholar
    • Export Citation
  • Horton, P. 2012 Optimization of light harvesting and photoprotection: Molecular mechanisms and physiological consequences Philos. Trans. R. Soc. Lond. B Biol. Sci. 367 3455 3465

    • Search Google Scholar
    • Export Citation
  • Kaiser, E., Morales, A. & Harbinson, J. 2018 Fluctuating light takes crop photosynthesis on a rollercoaster ride Plant Physiol. 176 977 989

  • Kjaer, K.H., Ottosen, C.O. & Jørgensen, B.N. 2011 Cost-efficient light control for production of two Campanula species Scientia Hort. 129 825 831

  • Kjaer, K.H., Ottosen, C.O. & Jørgensen, B.N. 2012 Timing growth and development of Campanula by daily light integral and supplemental light level in a cost-efficient light control system Scientia Hort. 143 189 196

    • Search Google Scholar
    • Export Citation
  • Koontz, H.V. & Prince, R.P. 1986 Effect of 16 and 24 hours daily radiation (light) on lettuce growth HortScience 21 123 124

  • Krall, J.P. & Edwards, G.E. 1992 Relationship between photosystem II activity and CO2 fixation in leaves Physiol. Plant. 86 180 187

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    • Search Google Scholar
    • Export Citation
  • Mauromicale, G., Ierna, A. & Marchese, M. 2006 Chlorophyll fluorescence and chlorophyll content in field-grown potato as affected by nitrogen supply, genotype, and plant age Photosynthetica 44 76 82

    • Search Google Scholar
    • Export Citation
  • Maxwell, K. & Johnson, G.N. 2000 Chlorophyll fluorescence: A practical guide J. Expt. Bot. 51 659 668

  • Morrow, R.C. 2008 LED lighting in horticulture HortScience 43 1947 1950

  • Murata, N. & Nishiyama, Y. 2018 ATP is a driving force in the repair of photosystem II during photoinhibition Plant Cell Environ. 41 285 299

  • Murchie, E.H. & Lawson, T. 2013 Chlorophyll fluorescence analysis: A guide to good practice and understanding some new applications J. Expt. Bot. 64 3983 3998

    • Search Google Scholar
    • Export Citation
  • Pinho, P., Hytönen, T., Rantanen, M., Elomaa, P. & Halonen, L. 2013 Dynamic control of supplemental lighting intensity in a greenhouse environment Light. Res. Technol. 45 295 304

    • Search Google Scholar
    • Export Citation
  • Pinho, P., Jokinen, K. & Halonen, L. 2012 Horticultural lighting: Present and future challenges Light. Res. Technol. 44 427 437

  • Polle, A. 1996 Mehler reaction: Friend or foe in photosynthesis? Plant Biol. 109 84 89

  • Rascher, U., Liebig, M. & Lüttge, U. 2000 Evaluation of instant light-response curves of chlorophyll fluorescence parameters obtained with a portable chlorophyll fluorometer on site in the field Plant Cell Environ. 23 1397 1405

    • Search Google Scholar
    • Export Citation
  • Rochaix, J. 2014 Regulation and dynamics of the light-harvesting system Annu. Rev. Plant Biol. 65 287 309

  • Ruban, A.V. 2015 Evolution under the sun: Optimizing light harvesting in photosynthesis J. Expt. Bot. 66 7 23

  • Salmon, Y., Barnard, R.L. & Buchmann, N. 2011 Ontogeny and leaf gas exchange mediate the carbon isotopic signature of herbaceous plants Plant Cell Environ. 34 465 479

    • Search Google Scholar
    • Export Citation
  • Seginer, I., Albright, L.D. & Ioslovich, I. 2006 Improved strategy for a constant daily light integral in greenhouses Biosyst. Eng. 93 69 80

  • Šesták, Z. 1999 Chlorophyll fluorescence kinetic depends on age of leaves and plants, p. 291–296. In: J.H. Argyroudi-Akoyunoglou and H. Senger (eds.). The chloroplast: From molecular biology to biotechnology. Springer, Dordrecht, Netherlands

  • Singh, D., Basu, C., Meinhardt-Wollweber, M. & Roth, B. 2015 LEDs for energy efficient greenhouse lighting Renew. Sustain. Energy Rev. 49 139 147

  • Slattery, R.A., Walker, B.J., Weber, A.P. & Ort, D.R. 2018 The impacts of fluctuating light on crop performance Plant Physiol. 176 990 1003

  • Soffe, R.W., Lenton, J.R. & Milford, G.F.J. 1977 Effects of photoperiod on some vegetable species Ann. Appl. Biol. 85 411 415

  • Spetea, C., Hundal, T., Lundin, B., Heddad, M., Adamska, I. & Andersson, B. 2004 Multiple evidence for nucleotide metabolism in the chloroplast thylakoid lumen Proc. Natl. Acad. Sci. USA 101 1409 1414

    • Search Google Scholar
    • Export Citation
  • Tischner, R. 2000 Nitrate uptake and reduction in higher and lower plants Plant Cell Environ. 23 1005 1024

  • Torres, A.P. & Lopez, R.G. n.d Measuring daily light integral in a greenhouse. Dept. of Hort. and Landscape Architecture, Purdue Univ. Purdue Extension Bul. HO-238-W

  • van Iersel, M.W. 2017 Optimizing LED lighting in controlled environment agriculture, p. 59–80. In: S.D. Gupta (ed.). Light emitting diodes for agriculture: Smart lighting. Springer, Singapore

  • van Iersel, M.W. & Gianino, D. 2017 An adaptive control approach for light-emitting diode lights can reduce the energy costs of supplemental lighting in greenhouses HortScience 52 72 77

    • Search Google Scholar
    • Export Citation
  • van Iersel, M.W., Weaver, G., Martin, M.T., Ferrarezi, R.S., Mattos, E. & . Haidekker, M 2016 A chlorophyll fluorescence-based biofeedback system to control photosynthetic lighting in controlled environment agriculture J. Amer. Soc. Hort. Sci. 141 169 176

    • Search Google Scholar
    • Export Citation
  • Wang, Y., Wei, R. & Xu, L. 2018 Dynamic control of supplemental lighting for greenhouse Amer. Institute Phys. Conf. Proc. 1956 020050

  • Watson, R.T., Boudreau, M. & van Iersel, M.W. 2018 Simulation of greenhouse energy use: An application of energy informatics Energy Informatics 1 1

  • Weaver, G. & van Iersel, M.W. 2016 Screening photosynthetic performance of bedding plants using chlorophyll fluorescence Proc. SNA Res. Conf. 61 71 75

    • Search Google Scholar
    • Export Citation
  • Weaver, G.M. & van Iersel, M.W. 2018 Modeling energy-efficient lighting strategies for petunia and impatiens using electron transport rate and historical weather data Proc. SNA Res. Conf. 62 29 34

    • Search Google Scholar
    • Export Citation
  • View in gallery

    Daily light integral (DLI) over the course of the study.

  • View in gallery

    Quantum yield of photosystem II (ΦPSII) of ‘Green Towers’ lettuce as a function of photosynthetic photon flux density (PPFD) based on 35 d of constant diurnal monitoring. Closed symbols represent measurements taken before solar noon; open symbols represent measurements taken after solar noon. The regression line represents the equation ΦPSII = 0.171 + 0.643e–0.00178PPFD, with R2 = 0.89 and P < 0.0001 (top). Electron transport rate (ETR) of ‘Green Towers’ lettuce as a function of PPFD based on 35 d of constant diurnal monitoring. Closed symbols represent measurements taken before solar noon; open symbols represent measurements taken after solar noon. The regression line represents the equation ETR = 121(1 – e–0.00277PPFD), with R2 = 0.95 and P < 0.0001 (bottom).

  • View in gallery

    Daily photochemical integral (DPI) of ‘Green Towers’ lettuce as a function of daily light integral (DLI) based on 35 d of diurnal chlorophyll fluorescence monitoring. The regression line represents the equation DPI = 3.30(1 – e–0.122DLI), with R2 = 0.82 and P < 0.0001.

  • View in gallery

    Daily photochemical integral (DPI) resulting from reaching a daily light integral (DLI) of 17 mol·m–2·d–1 with a constant photosynthetic photon flux density (PPFD) over a range of photoperiods required (top); required PPFD, and corresponding electron transport rate (ETR; calculated from equation in Fig. 2, bottom).

  • View in gallery

    Daily photochemical integral (DPI) resulting from reaching a daily light integral (DLI) of 17 mol·m–2·d–1 with a 12-h photoperiod using two photosynthetic photon flux densities (PPFDs), each for half of the photoperiod, with a range of differences between the two PPFDs (ΔPPFD) (top). Required PPFDs (bottom), and corresponding electron transport rates (ETRs) (middle) are shown. For ΔPPFD = 0, only one PPFD is used.

  • View in gallery

    Daily light integral (DLI) needed to reach a calculated daily photochemical integral (DPI) of 2.89 mol·m–2·d–1 with a constant photosynthetic photon flux density (PPFD) over a range of photoperiods (top); required electron transport rate (ETR) and corresponding PPFD (bottom) based on the regression equation in Fig. 2 (bottom).

  • Aaslyng, J.M., Lund, J.B., Ehler, N. & Rosenqvist, E. 2003 IntelliGrow: A greenhouse component-based climate control system Environ. Model. Softw. 18 657 666

    • Search Google Scholar
    • Export Citation
  • Aikman, D.P. 1989 Potential increase in photosynthetic efficiency from the redistribution of solar radiation in a crop J. Expt. Bot. 40 855 864

    • Search Google Scholar
    • Export Citation
  • Albright, L.D., Both, A.J. & Chiu, A.J. 2000 Controlling greenhouse light to a consistent daily integral Trans. ASABE 43 421 431

  • Baker, N.R. 2008 Chlorophyll fluorescence: A probe of photosynthesis in vivo Annu. Rev. Plant Biol. 59 89 113

  • Baker, N.R. & Rosenqvist, E. 2004 Applications of chlorophyll fluorescence can improve crop production strategies: An examination of future possibilities J. Expt. Bot. 55 1607 1621

    • Search Google Scholar
    • Export Citation
  • Both, A.J., Albright, L.D., Langhans, R.W., Reiser, R.A. & Vinzant, B.G. 1997 Hydroponic lettuce production influenced by integrated supplemental light levels in a controlled environment agriculture facility: Experimental results Acta Hort. 418 45 52

    • Search Google Scholar
    • Export Citation
  • Björkman, O. & Demmig, B. 1987 Photon yield of O2 evolution and chlorophyll fluorescence at 77k among vascular plants of diverse origins Planta 170 489 504

    • Search Google Scholar
    • Export Citation
  • Bumgarner, N. & Buck, J. 2016 Light emitting diode and metal halide supplemental lighting for greenhouse Bibb lettuce production in the Midwestern United States J. Appl. Hort. 18 128 134

    • Search Google Scholar
    • Export Citation
  • Clausen, A., Maersk-Moeller, H.M., Soerensen, J.C., Joergensen, B.N., Kjaer, K.H. & Ottosen, C.O. 2015 Integrating commercial greenhouses in the smart grid with demand response based control of supplemental lighting. Intl. Conf. Ind. Technol. Mgt. Sci. (ITMS 2015) 199–213.

  • Demmig-Adams, B., Cohu, C.M., Muller, O. & Adams, W.W. 2012 Modulation of photosynthetic energy conversion in nature: From seconds to seasons Photosynth. Res. 113 75 78

    • Search Google Scholar
    • Export Citation
  • Dietz, K.J. 2015 Efficient high light acclimation involves rapid processes at multiple mechanistic levels J. Expt. Bot. 66 2401 2414

  • Foyer, C.H., Neukermans, J., Queval, G., Noctor, G. & Harbinson, J. 2012 Photosynthetic control of electron transport and the regulation of gene expression J. Expt. Bot. 63 1637 1661

    • Search Google Scholar
    • Export Citation
  • Genty, B., Briantais, J. & Baker, N.R. 1989 The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence Biochim. Biophys. Acta 990 87 92

    • Search Google Scholar
    • Export Citation
  • Horton, P. 2012 Optimization of light harvesting and photoprotection: Molecular mechanisms and physiological consequences Philos. Trans. R. Soc. Lond. B Biol. Sci. 367 3455 3465

    • Search Google Scholar
    • Export Citation
  • Kaiser, E., Morales, A. & Harbinson, J. 2018 Fluctuating light takes crop photosynthesis on a rollercoaster ride Plant Physiol. 176 977 989

  • Kjaer, K.H., Ottosen, C.O. & Jørgensen, B.N. 2011 Cost-efficient light control for production of two Campanula species Scientia Hort. 129 825 831

  • Kjaer, K.H., Ottosen, C.O. & Jørgensen, B.N. 2012 Timing growth and development of Campanula by daily light integral and supplemental light level in a cost-efficient light control system Scientia Hort. 143 189 196

    • Search Google Scholar
    • Export Citation
  • Koontz, H.V. & Prince, R.P. 1986 Effect of 16 and 24 hours daily radiation (light) on lettuce growth HortScience 21 123 124

  • Krall, J.P. & Edwards, G.E. 1992 Relationship between photosystem II activity and CO2 fixation in leaves Physiol. Plant. 86 180 187

  • Locke, A.M. & Ort, D.R. 2014 Leaf hydraulic conductance declines in coordination with photosynthesis, transpiration and leaf water status as soybean leaves age regardless of soil moisture J. Expt. Bot. 65 6617 6627

    • Search Google Scholar
    • Export Citation
  • Mauromicale, G., Ierna, A. & Marchese, M. 2006 Chlorophyll fluorescence and chlorophyll content in field-grown potato as affected by nitrogen supply, genotype, and plant age Photosynthetica 44 76 82

    • Search Google Scholar
    • Export Citation
  • Maxwell, K. & Johnson, G.N. 2000 Chlorophyll fluorescence: A practical guide J. Expt. Bot. 51 659 668

  • Morrow, R.C. 2008 LED lighting in horticulture HortScience 43 1947 1950

  • Murata, N. & Nishiyama, Y. 2018 ATP is a driving force in the repair of photosystem II during photoinhibition Plant Cell Environ. 41 285 299

  • Murchie, E.H. & Lawson, T. 2013 Chlorophyll fluorescence analysis: A guide to good practice and understanding some new applications J. Expt. Bot. 64 3983 3998

    • Search Google Scholar
    • Export Citation
  • Pinho, P., Hytönen, T., Rantanen, M., Elomaa, P. & Halonen, L. 2013 Dynamic control of supplemental lighting intensity in a greenhouse environment Light. Res. Technol. 45 295 304

    • Search Google Scholar
    • Export Citation
  • Pinho, P., Jokinen, K. & Halonen, L. 2012 Horticultural lighting: Present and future challenges Light. Res. Technol. 44 427 437

  • Polle, A. 1996 Mehler reaction: Friend or foe in photosynthesis? Plant Biol. 109 84 89

  • Rascher, U., Liebig, M. & Lüttge, U. 2000 Evaluation of instant light-response curves of chlorophyll fluorescence parameters obtained with a portable chlorophyll fluorometer on site in the field Plant Cell Environ. 23 1397 1405

    • Search Google Scholar
    • Export Citation
  • Rochaix, J. 2014 Regulation and dynamics of the light-harvesting system Annu. Rev. Plant Biol. 65 287 309

  • Ruban, A.V. 2015 Evolution under the sun: Optimizing light harvesting in photosynthesis J. Expt. Bot. 66 7 23

  • Salmon, Y., Barnard, R.L. & Buchmann, N. 2011 Ontogeny and leaf gas exchange mediate the carbon isotopic signature of herbaceous plants Plant Cell Environ. 34 465 479

    • Search Google Scholar
    • Export Citation
  • Seginer, I., Albright, L.D. & Ioslovich, I. 2006 Improved strategy for a constant daily light integral in greenhouses Biosyst. Eng. 93 69 80

  • Šesták, Z. 1999 Chlorophyll fluorescence kinetic depends on age of leaves and plants, p. 291–296. In: J.H. Argyroudi-Akoyunoglou and H. Senger (eds.). The chloroplast: From molecular biology to biotechnology. Springer, Dordrecht, Netherlands

  • Singh, D., Basu, C., Meinhardt-Wollweber, M. & Roth, B. 2015 LEDs for energy efficient greenhouse lighting Renew. Sustain. Energy Rev. 49 139 147

  • Slattery, R.A., Walker, B.J., Weber, A.P. & Ort, D.R. 2018 The impacts of fluctuating light on crop performance Plant Physiol. 176 990 1003

  • Soffe, R.W., Lenton, J.R. & Milford, G.F.J. 1977 Effects of photoperiod on some vegetable species Ann. Appl. Biol. 85 411 415

  • Spetea, C., Hundal, T., Lundin, B., Heddad, M., Adamska, I. & Andersson, B. 2004 Multiple evidence for nucleotide metabolism in the chloroplast thylakoid lumen Proc. Natl. Acad. Sci. USA 101 1409 1414

    • Search Google Scholar
    • Export Citation
  • Tischner, R. 2000 Nitrate uptake and reduction in higher and lower plants Plant Cell Environ. 23 1005 1024

  • Torres, A.P. & Lopez, R.G. n.d Measuring daily light integral in a greenhouse. Dept. of Hort. and Landscape Architecture, Purdue Univ. Purdue Extension Bul. HO-238-W

  • van Iersel, M.W. 2017 Optimizing LED lighting in controlled environment agriculture, p. 59–80. In: S.D. Gupta (ed.). Light emitting diodes for agriculture: Smart lighting. Springer, Singapore

  • van Iersel, M.W. & Gianino, D. 2017 An adaptive control approach for light-emitting diode lights can reduce the energy costs of supplemental lighting in greenhouses HortScience 52 72 77

    • Search Google Scholar
    • Export Citation
  • van Iersel, M.W., Weaver, G., Martin, M.T., Ferrarezi, R.S., Mattos, E. & . Haidekker, M 2016 A chlorophyll fluorescence-based biofeedback system to control photosynthetic lighting in controlled environment agriculture J. Amer. Soc. Hort. Sci. 141 169 176

    • Search Google Scholar
    • Export Citation
  • Wang, Y., Wei, R. & Xu, L. 2018 Dynamic control of supplemental lighting for greenhouse Amer. Institute Phys. Conf. Proc. 1956 020050

  • Watson, R.T., Boudreau, M. & van Iersel, M.W. 2018 Simulation of greenhouse energy use: An application of energy informatics Energy Informatics 1 1

  • Weaver, G. & van Iersel, M.W. 2016 Screening photosynthetic performance of bedding plants using chlorophyll fluorescence Proc. SNA Res. Conf. 61 71 75

    • Search Google Scholar
    • Export Citation
  • Weaver, G.M. & van Iersel, M.W. 2018 Modeling energy-efficient lighting strategies for petunia and impatiens using electron transport rate and historical weather data Proc. SNA Res. Conf. 62 29 34

    • Search Google Scholar
    • Export Citation
Geoffrey WeaverDepartment of Horticulture, University of Georgia, 1111 Miller Plant Sciences Building, Athens, GA 30602

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Marc W. van IerselDepartment of Horticulture, University of Georgia, 1111 Miller Plant Sciences Building, Athens, GA 30602

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Contributor Notes

This research was funded in part by a U.S. Department of Agriculture, National Institute of Food and Agriculture, Small Business Innovation Research grant to Candidus, Inc.

Corresponding author. E-mail: gmweaver@uga.edu.

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