Next Article in Journal
Herbaceous Peony Polyphenols Extend the Vase Life of Cut Flowers
Previous Article in Journal
Response of Winter Wheat (Triticum aestivum L.) to Selected Biostimulants under Drought Conditions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 13
Issue 1
10.3390/agriculture13010119
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Blue-Light-Dependent Stomatal Density and Specific Leaf Weight Coordinate to Promote Gas Exchange of Soybean Leaves

by
Jiyu Chen
1,2,3,†,
Jing Gao
1,2,3,†,
Qi Wang
1,2,3,
Xianming Tan
1,2,3,
Shenglan Li
1,2,3,
Ping Chen
1,2,3,
Taiwen Yong
1,2,3,
Xiaochun Wang
1,2,3,
Yushan Wu
1,2,3,
Feng Yang
1,2,3,* and
Wenyu Yang
1,2,3
1
College of Agronomy, Sichuan Agricultural University, Chengdu 611130, China
2
Sichuan Engineering Research Center for Crop Strip Intercropping System, Chengdu 611130, China
3
Key Laboratory of Crop Ecophysiology and Farming System in Southwest, Ministry of Agriculture, Chengdu 611130, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2023, 13(1), 119; https://doi.org/10.3390/agriculture13010119
Submission received: 28 November 2022 / Revised: 27 December 2022 / Accepted: 27 December 2022 / Published: 31 December 2022
(This article belongs to the Section Crop Production)
Browse Figures
Versions Notes

Abstract

:
Blue and red light are essential light signals used to regulate stomatal development and leaf structure. In the present study, stomatal and leaf traits that respond to blue and red light were studied at two light intensities (400 and 100 µmol m−2 s−1) in soybeans. The stomatal traits and leaf characteristics were determined. Furthermore, their contribution to the operational maximum stomatal conductance (gopmax) was evaluated using the rdacca.hp R package. With the light intensity significantly reduced, the stomatal size (SZ) under blue light did not change. Similarly, the decrease in light intensity did not influence the stomatal density (SD), specific leaf weight (SLW) or gopmax under red light. These results implied that the regulation of SD and SLW depended on blue light and that SZ was highly sensitive to red light. In addition, SLW was strongly correlated with SD. The SLW and SD had the highest contribution rates (19.43% and 19.5%, respectively) to gopmax, as compared with the other parameters. In conclusion, these results suggested that in long-term exposure to blue light, the enhancements in gopmax were primarily due to the synergistic promotion of SLW and SD.

Graphical Abstract

1. Introduction

Stomata play an essential role in regulating gas exchange. Although stomata only account for 0.3 to 5% of the total leaf area, the stomata complete 95% of the gas exchange (CO2 diffusion) [1]. Gaseous CO2 diffuses through leaf tissue and mesophyll cells and eventually reaches the carboxylation site (rubisco enzyme in chloroplasts). The leaf structure exerts resistance to the diffusion of CO2. Thus, the CO2 concentration in the chloroplast (Cc) is relatively low, affecting the supply of CO2 to the carboxylation site [2]. Some studies have shown that maximizing stomatal conductance can increase the CO2 concentration at intercellular and chloroplast levels [3,4]. As a C3 crop, the unsaturated Cc generally limits the photosynthesis of soybean plants [2,5]. The net photosynthetic rate is closely related to stomatal conductance. The canopy-averaged stomatal conductance of rice increased with increasing photosynthetic rate [6]. In ferns, gymnosperms and angiosperms, stomatal conductance was significantly positively correlated with the net photosynthetic rate [7]. Therefore, improving stomatal conductance is beneficial for soybeans to obtain a high net photosynthetic rate.
The stomatal density (SD) and stomatal size (SZ) determine the theoretical capacity of gas exchange. In principle, an infinite combination of either of these parameters achieves the potential maximum stomatal conductance (gsmax). The SD and SZ can be calculated assuming all pores are open [2,7,8]. Although this principle is anatomically possible, the operational stomatal conductance (gop) is not near gsmax. Instead, it is maintained at approximately 20% of gsmax because it allows guard cells to most effectively regulate stomatal enlargement [9,10]. Previous studies proved that gsmax positively correlates with gop [9,11,12]. Moreover, stomatal characteristics (i.e., SD and SZ) are significantly related to gop in angiosperms; other unknown traits may be involved in regulating gop [12,13].
Many traits work in coordination instead of alone during the growth and development of plants. The SD and SZ are also affected by regulatory factors during stomatal development. They mutually coordinate with leaf tissue development to establish an efficient and robust network that facilitates gas exchange for photosynthesis [14]. Previous studies have shown that stomatal development is coupled with the underlying mesophyll tissues. It is beneficial to achieve high leaf photosynthetic potential (Vmax) and gsmax [15]. Tanaka et al. [16] reported that Arabidopsis epidermal pattern factor (EPF) mutants, with 75% more stomata than their wild-type counterparts, demonstrated significantly higher rates of the net photosynthetic rate under high light intensities. The authors attributed the net photosynthetic rate and stomatal conductance enhancement to the improvement in the Ci of the leaf and, thus, lateral diffusion of CO2. Therefore, variations in stomatal development and leaf anatomical structure are considered adaptive strategies that help plants respond to long-term environmental fluctuations and are essential to plant evolution and adaptation to new environmental conditions [17].
Light is an essential environmental signal that affects leaf structure and function through light quality and intensity. According to previous studies, plant leaves’ area decreases and leaf thickness becomes thinner under low light. The SD, SZ, net photosynthetic rate, transpiration, and stomatal conductance also decrease when light intensity is reduced [18,19,20,21,22,23]. Among the various light qualities, blue and red light are the two most efficient bands of photosynthesis in plants [24]. The two lights affect photosynthesis by altering the palisade and spongy mesophyll [25]. Nevertheless, the regulation of leaf structure by blue and red light is different. The blue light inhibited leaf extension, promoted leaf tissue structure and chloroplast development, and improved stomatal conductance and photosynthetic efficiency. The prolonged red light produced thinner grana lamellae and smaller starch grains, led to loosely organized leaf palisade tissues, and inhibited net photosynthesis [26,27]. In stomatal movement, the red-light-driven opening response of stomata relies on photosynthesis, and blue light induces stomatal opening by activating blue light photoreceptors [28,29,30,31,32,33,34,35]. However, whether blue and red light also has differential adjustments for stomatal characteristics, such as SD and SZ, still need to be researched.
Therefore, we measured soybean leaf characteristics, such as stomatal traits, gas exchange capacity, and photosynthetic capacity under different light treatments. This study aims to address the different responses of leaf characteristics and stomatal traits to blue and red light and reveal how these differences affect the actual gas exchange and photosynthetic capacity under blue and red light. The results will provide a theoretical basis for the rational application of different wavelength spectra in facility agriculture and intercropping systems.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

Soybean (Glycine max L. Merr.) seeds ‘Rongxian Dongdou’ were used to assess growth conditions under different light environments. A light chamber was used at the Sichuan Agricultural University of China (30°71′20″ N, 103°86′87″ E). Soybean seeds were decontaminated with 75% ethanol and deionized water for 5 min and germinated on a wet sterile gauze for 48 h in the dark at 25 °C. After germination, we sowed two seeds in 400 mL pots filled with a mixed matrix of PINDSTRUP organic soil (Pindstrup Mosebrug A/S, Ryomgaard, Denmark) and vermiculite (v:v, 3:1) in a light chamber. The temperature was maintained at 25 °C during the 12 h daytime and 20 °C during 12 h of nighttime. Soybean seedlings were watered every 2 days with 0.2% Hoagland’s solution [36]. When the soybean seedlings had grown to the VC stage (cotyledon leaves unrolled sufficiently and the leaf edges are not touching), the pots were transferred to different light treatments under the abovementioned environmental conditions [37]. The fully unfolded penultimate compound leaves were used to measure morphological and physiological parameters during the V3 (three nodes on the main stem with fully developed leaves beginning with the unifoliolate nodes) [37].
The experiment used two light intensities (400 and 100 µmol m−2 s−1) at different light qualities (blue and red). The specific light quality and intensity (Figure 1) were as follows: blue light of 400 µmol m−2 s−1 (400 B); blue light of 100 µmol m−2 s−1 (100 B); red light of 400 µmol m−2 s−1 (400 R); and red light of 100 µmol m−2 s−1 (100 R). The position of the pots was adjusted daily to maintain the same light intensity during growth under one treatment. HR-450 (Hipoint Inc., Gaoxiong, Taiwan, China) was used to measure spectral irradiance and light intensity.

2.2. Measurement of Morphological Characteristics

Four soybean seedlings of penultimate compound leaves (fully expanded) were used. Samples were overdried at 105 °C for 0.5 h and then dried at 80 °C for 72 h to constant weight. The dry mass per unit leaf area of the penultimate compound leaf indicates the specific leaf weight (SLW, mg/cm2). The average value is considered the final result.

2.3. Leaf Anatomical Feature Measurements

Leaf pieces (4 mm2), from approximately four replications for each treatment without midribs, were fixed in formalin–acetic acid–alcohol solution (FAA; 90% ethanol; 5% formaldehyde; 5% glacial acetic acid, v/v/v) at 4 °C for 3 days. The leaf samples were dehydrated in a gradient series of ethanol solutions (95%, 75%, 50%, 25% and 10% ethanol) and embedded in paraffin. Tissue sections of 4 µm thickness were cut with a rotary microtome (RM2235, Leica Microsystems Ltd., Karlsruhe, Germany). The tissue sections were stained with toluidine blue, observed with a light microscope (ECLIPSE Ts2, Nikon Instruments Inc., Tokyo, Japan), and captured by a digital camera (Digital Sight DS-U3, Nikon Instruments Inc., Tokyo, Japan). ImageJ was used to measure the thickness of the leaf, spongy tissue, palisade tissue, and epidermal cells on the upper and lower sides. The parameters of the leaf tissue compactness (LC), leaf tissue looseness (LL), and the ratio of palisade tissue to spongy tissue (P/C) were calculated based on the following formula [38]:
LC = PT/LT,
LL = ST/LT,
P/C = PT/ST,
where LC is leaf tissue compactness, PT and LT are the thickness of the palisade tissue and leaf, respectively, LL is the leaf tissue looseness, ST is the thickness of spongy tissue, and P/C is the ratio of palisade tissue to spongy tissue.

2.4. Determination of Stomatal Structure Characteristics

From the base 1/3 of the fully unfolded penultimate compound leaf near the central vein, a small piece of 1 cm × 1 cm was cut. The samples were immediately placed into FAA fixative solution and fixed in a refrigerator at 4 °C for more than 48 h. Ethanol was used to perform step-by-step dehydration as follows: 50% ethanol soaked for 1 h, 70% ethanol soaked for 1 h, 85% ethanol soaked for 1 h, 95% ethanol soaked for 40 min twice, and 100% ethanol soaked for 40 min twice. The dehydrated samples were soaked in 5% sodium hydroxide solution for 42 h or more until the leaves turned white. The deionized water was used to clean the samples twice. Then, the samples were transferred to a saturated trichloroacetaldehyde solution. After completely transparent samples were obtained, deionized water was utilized to clean the trichloroacetaldehyde. Finally, each sample was stained with 1% toluidine blue aqueous solution and observed with an optical microscope (Nikon Eclipse 50I, Tokyo, Japan). A digital camera (Sight DS-U3, Nikon Instruments Inc., Tokyo, Japan) was used [39]. The SZ (stomatal long axis length) and SD (mm−2) on the upper and lower epidermis were measured using ImageJ in five visual fields for four replicates of each treatment.

2.5. Photosynthesis Measurements

Under each treatment, the fully unfolded penultimate compound leaves of five plants were used. The acquisition of photosynthetic parameters was conducted in a 6 cm2 leaf chamber with a CO2 concentration of 400 µmol mol−1 using a portable infrared gas analyzer (Li-6400, LI-COR Inc., Lincoln, USA). The spectral composition of LICOR 6400 was a combination of red and blue light with a ratio of 3:2, which was different from the growth light environment of the plants in the experiment. Fourteen light intensity levels (0, 20, 50, 100, 150, 200, 400, 600, 800, 1000, 1200, 1500, 2000 and 2300 µmol m−2 s−1) were imposed at increments of 2 min. The net photosynthetic rate and operational stomatal conductance (gop) response curve to light under different treatments were fitted with a smooth curve.

2.6. Statistical Analysis

In this experiment, SPSS statistics 25 was used to compare the differences between treatments via a one-way analysis of variance. Mean ± standard error values are presented for all statistical analyses, and at least three biological replicates were analyzed for significant differences at the 5% level in all parameters. Microsoft Excel 2016 was utilized for data wrangling, and the figures were drawn using Origin 2021b.

3. Results

3.1. Leaf Structure Response to Blue and Red Light

The response of soybean leaf structures to blue and red light at different light intensities is shown in Table 1. The SLW, leaf thickness, palisade tissue thickness, and spongy tissue thickness under 100 B treatment was significantly decreased compared with those under 400 B treatment. The LL and P/C of spongy tissue under 400 B were not significantly different from that under 100 B. However, the LC significantly increased by 9% under 100 B, as compared with 400 B. The thicknesses of the leaf, palisade tissue, spongy tissue, upper epidermal cells, and lower epidermal cells of soybean leaves under the 100 R treatment were significantly lower than those under 400 R. Nevertheless, the LC and SLW under 400 R were not significantly different from those under 100 R. Regardless of blue or red light, low light intensity inhibited the development of leaf structure, but the regulation of SLW was highly dependent on blue light.

3.2. Stomatal Size of the Two Sides

Figure 2 shows the SZ of the upper and lower epidermises response to different light environments. The SZ on the upper and lower epidermis under 100 B was significantly increased compared to those under 100 R. The SZ of the upper epidermis under 400 R was considerably higher than that under 400 B and no significant difference was observed in the lower epidermis (Figure 2B,D). As the light intensity decreased from 400 to 100 µmol m−2 s−1, it significantly reduced the SZ on the upper and lower epidermis by 17.5% and 11.7%, respectively, under red light. In contrast, the significant reduction in light intensity under blue light (400 and 100 B) did not affect the SZ of the upper and lower epidermis (Figure 2B,D). These results showed that SZ was susceptible to red light.

3.3. Stomatal Density of the Two Sides

The SD of the two sides in soybean leaves is shown in Figure 3. There was no significant difference between the SD under 400 R and 100 R on the upper and lower epidermis. The SDs of the upper and lower epidermises at 400 B were significantly higher than those at 400 R. Compared to 100 R, the 100 B treatment significantly improved the SD on the upper epidermis but had no significant impact on the SD of the lower epidermis. In addition, the 100 B treatment significantly reduced the SD of the upper and the lower epidermis by 33.2% and 29.5% compared with those under 400 B, respectively (Figure 3B,C). Although light intensity could significantly regulate the SD of the upper and lower epidermis, blue light was indispensable.

3.4. The Response Curves of Light Intensities

With the light intensity increasing, the net photosynthetic rate of soybean leaves under various treatments gradually rose and remained stable after reaching the maximum (Figure 4A). The statistical analysis for the maximum net photosynthetic rate indicated that low light and red light significantly decreased the maximum net photosynthetic rate (Figure 4B) compared with high light and blue light, respectively. Under the same light intensity, the gop of soybean leaves in the red light treatment was significantly lower than that under blue light. In addition, the high light intensity increased the gop compared with the low light intensity under the same light quality (Figure 4C). In terms of the operational maximum stomatal conductance (gopmax), the treatments were ordered from highest to lowest as follows: 400 B > 100 B> 400 R > 100 R treatments (Figure 4D). The gopmax under 100 B was significantly lower than that under 400 B. However, the gopmax between 400 R and 100 R showed no significant effects. The blue light was more critical in regulating the gas exchange capacity than red light.

3.5. Relationship between Net Photosynthetic Rate and Operational Stomatal Conductance

The dynamic gop positively correlated with the net photosynthetic rate under 400 B, 100 B, 400 R, and 100 R. The correlation coefficients were as high as 0.841, 0.992, 0.876 and 0.983, respectively (Figure 5). These results showed that net photosynthetic rate was highly correlated with gop under different light quality and intensity environments.

3.6. Contribution of Leaf Characteristics and Stomatal Traits to Maximum Operational Stomatal Conductance

Leaf characteristics and stomatal traits greatly affected the gopmax of soybean leaves. The contribution rates of leaf characteristics to gopmax reached 60.48%. The main leaf traits were SLW, leaf thickness, palisade tissue thickness, and spongy tissue thickness, whose contribution rates to gopmax were 19.43%, 15.65%, 13.39% and 12.01%, respectively (Figure 6A). Stomatal traits contributed to gopmax by 24.22%, mainly including SD on the upper (9.75%) and lower epidermis (9.7%). By contrast, gopmax was nearly unaffected by SZ. The correlation analysis also proved that leaf characteristics and stomatal traits had a highly significant positive correlation with gopmax (Figure 6B). The SD was positively correlated with leaf characteristics but not with the SZ of the upper and lower epidermis.

4. Discussion

Light quality can affect the arrangement of palisade and spongy cells and, thus, affect photosynthesis [25,40]. However, the response of leaves to various light qualities differed (Table 1). In many plant species, red and blue combined light and blue light affect the growth of palisade tissue when compared with red light and white light [25]. In the present study, when the light intensity was significantly reduced, the LC was unchanged under red light but increased under blue light. On the contrary, the LL did not significantly change under blue light and improved under red light. The results suggested that the blue light partially alleviated the reduced thickness of palisade tissue caused by the decreased light intensity but had no effect on the proportion of spongy tissue (Table 1), thereby increasing the proportion of palisade tissue in leaves. This may be because palisade histiocyte development depends on the activation of phototropin under blue light [41,42,43,44]. In addition, our results also showed that the decreased light intensity under red light increased the proportion of spongy tissue in the leaf. This may be because red light did not change the proportion of palisade tissue (Table 1) and simultaneously alleviated the reduction in spongy tissue thickness caused by declined light intensity.
In addition, the SZ under blue light was not significantly different from high to low light intensity but was decreased considerably under red light (Figure 2). These results suggested that SZ was highly dependent on the red light. Seif et al. [45] also found that red light reduces stomatal size but promotes gas exchange in the chrysanthemum. With light intensity significantly reduced in the current study, the SD and SLW under red light were unaffected but decreased observably under blue light. These results proved that SD and SLW were highly sensitive to blue light (Figure 3). This is consistent with the results of previous studies, where SLW is much less affected than the maximum net photosynthetic rate in the spectrum containing relatively little blue [24,46]. Increasing blue light under red light could increase SD [47,48]. Our results showed that blue and red lights specifically regulated SD and SZ. However, different light qualities usually regulate plant development in different ways. In stomatal movement, the stomatal blue light response is mediated by blue light photoreceptor protein kinases [30,33,35]. The red light required the involvement of a mesophyll signal to regulate stomatal opening [49]. Therefore, SD and SZ responding specifically to blue and red light may also be regulated by corresponding photoreceptors, but further study is needed.
A high correlation between leaf characteristics and stomatal traits (Figure 6B) indicated that they could influence and coordinate with each other. Some previous studies found that stomatal development of stomata-specific regulators could alter leaf structural changes to obtain a high gsmax [14,15]. In the present study, the SD was highly correlated with functional leaf characteristics, such as SLW and leaf thickness, among which the SD correlated most closely with leaf thickness. In contrast, no correlation was observed between SZ and leaf anatomical characteristics, regardless of the upper or lower epidermis. Previous studies have shown that the epidermal pattern factor increases the density of palisade mesophyll cells below the paraxial epidermis [15].
Manipulating transcription factor SPEECHLESS’s activity can change the degree of stomatal lineage proliferation, which increases leaf area and thickness [50,51]. Our results suggested that specific regulators of SD were more pivotal in influencing leaf development, especially for leaf tissue development, than SZ for the high gas exchange capacity obtained. For SZ, many studies have reported that small stomata usually accelerate the stomatal response because the membrane surface area is larger, relative to the volume ratio of guard cells. Thus, increasing the rate of ion flux is conducive to a rapid response to fluctuating light environments, which improves the photosynthetic rate [52,53,54]. However, the association of stomatal response speed with SZ varies across many species [55,56], and the molecular genetic mechanisms that control SZ remain unclear. Thus, further investigations are needed.
Previous studies have widely proven the intense influence of gas exchange capacity on photosynthesis [7,57,58,59]. We also demonstrated that the net photosynthetic rate was positively associated with stomatal conductance under blue and red light (Figure 4). Stomatal conductance is related to SZ and SD [53,60,61]. A study discovered that the structural differences between the leaves of angiosperms and ferns partly explain the decline in gas exchange capacity in ferns, according to the comparison of the leaf anatomical characteristics between ferns and angiosperms [62]. In particular, leaf thickness affects the transport of water and CO2, which influences stomatal conductance [63,64,65].
Moreover, SD and SZ have a significantly negative correlation, determining gsmax [53,64]. Nevertheless, there was nearly no connection between SZ and SD in the present study (Figure 6B). This finding is the same as previous research, where SD and SZ showed no coincident trend during the breeding process of japonica rice varieties [66]. Although increasing gop within species is possible, by decreasing SZ and increasing SD, this trend may only apply to some species due to variations in the natural habit of species [52,53]. In this study, we quantified the relative importance of individual structural variables in gopmax using rdacca.hp [67], which indicated that the leaf characteristics SLW and SD strongly affected gopmax (Figure 6). These results are consistent with previous studies, which proposed that SZ and gopmax had no significant correlation. High SD significantly promoted gopmax [12]. By practical consequence, leaf characteristics had a more substantial ability to regulate gopmax than SD. Especially in a red-light background, we found that gopmax was concordant with SD and SLW and unaffected by the light intensity change (Figure 6). This result indicated that SD and SLW regulation depended on blue light. Beyond that, the SLW and SD harmoniously improved gas exchange and photosynthetic capacity under blue light. Among them, the SLW appeared to be more critical in influencing gop. As a result, the amount of SD in plants is reduced by approximately half and has no adverse effects on plant growth and development [8,68,69]. However, broader studies and more profound research are needed to elucidate the specific mechanisms.

5. Conclusions

The stomatal traits and leaf characteristics of soybean leaves had different responses to blue and red light during their growth and development. Nevertheless, stomatal traits were usually coordinated with leaf traits to better adapt to environmental changes. Our results were as follows: (1) Light intensity and quality could significantly affect the development of leaf characteristics and stomatal traits. (2) The stomatal density and specific leaf weight were blue light-dependent, while the stomatal size was highly sensitive to red light. (3) Although the specific leaf weight had a more significant effect on stomatal conductance than stomatal density, the improvement in stomatal conductance under blue light was more due to the long-term synergistic promotion of stomatal density and specific leaf weight. These results emphasized that coordinated optimization among plant leaf traits may be a new direction for improving photosynthetic capacity.

Author Contributions

Data curation, J.C., Q.W., X.T. and S.L.; software, J.C. and P.C.; writing—original draft preparation, J.C. and J.G.; writing—review and editing, T.Y., X.W., Y.W. and F.Y.; funding acquisition, F.Y. and W.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (32071963), the International S & T Cooperation Projects of Sichuan Province (2020YFH0126), and the Program on Industrial Technology System of National Soybean (CARS-04-PS19).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

All data are fully available without restriction.

Conflicts of Interest

The authors declare that they have no competing interests.

References

  1. Lawson, T.; Matthews, J. Guard cell metabolism and stomatal function. Annu. Rev. Plant Biol. 2020, 71, 273–302. [Google Scholar] [CrossRef] [Green Version]
  2. Harrison, E.L.; Arce Cubas, L.; Gray, J.E.; Hepworth, C. The influence of stomatal morphology and distribution on photosynthetic gas exchange. Plant J. 2020, 101, 768–779. [Google Scholar] [CrossRef] [Green Version]
  3. von Caemmerer, S.; Evans, J. Determination of the average partial pressure of CO2 in chloroplasts from leaves of several C3 Plants. Funct. Plant Biol. 1991, 18, 287–305. [Google Scholar] [CrossRef]
  4. Lloyd, J.; Syvertsen, J.P.; Kriedemann, P.E.; Farquhar, G.D. Low conductances for CO2 diffusion from stomata to the sites of carboxylation in leaves of woody species. Plant Cell Environ. 1992, 15, 873–899. [Google Scholar] [CrossRef]
  5. Farquhar, G.D.; von Caemmerer, S.; Berry, J.A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 1980, 149, 78–90. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Ono, K.; Maruyama, A.; Kuwagata, T.; Mano, M.; Takimoto, T.; Hayashi, K.; Hasegawa, T.; Miyata, A. Canopy-scale relationships between stomatal conductance and photosynthesis in irrigated rice. Glob. Chang. Biol. 2013, 19, 2209–2220. [Google Scholar] [CrossRef]
  7. Xiong, D.; Flexas, J. From one side to two sides: The effects of stomatal distribution on photosynthesis. New Phytol. 2020, 228, 1754–1766. [Google Scholar] [CrossRef] [PubMed]
  8. Franks, P.J.; Doheny Adams, T.W.; Britton Harper, Z.J.; Gray, J.E. Increasing water-use efficiency directly through genetic manipulation of stomatal density. New Phytol. 2015, 207, 188–195. [Google Scholar] [CrossRef]
  9. Franks, P.J.; Leitch, I.J.; Ruszala, E.M.; Hetherington, A.M.; Beerling, D.J. Physiological framework for adaptation of stomata to CO2 from glacial to future concentrations. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 2012, 367, 537–546. [Google Scholar] [CrossRef] [Green Version]
  10. Dow, G.J.; Bergmann, D.C.; Berry, J.A. An integrated model of stomatal development and leaf physiology. New Phytol. 2014, 201, 1218–1226. [Google Scholar] [CrossRef] [PubMed]
  11. Farquhar, G.D.; Sharkey, T.D. Stomatal conductance and photosynthesis. Annu. Rev. Plant Physiol. 1982, 33, 317–345. [Google Scholar] [CrossRef]
  12. McElwain, J.C.; Yiotis, C.; Lawson, T. Using modern plant trait relationships between observed and theoretical maximum stomatal conductance and vein density to examine patterns of plant macroevolution. New Phytol. 2016, 209, 94–103. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Russo, S.E.; Cannon, W.L.; Elowsky, C.; Tan, S.; Davies, S.J. Variation in leaf stomatal traits of 28 tree species in relation to gas exchange along an edaphic gradient in a Bornean rain forest. Am. J. Bot. 2010, 97, 1109–1120. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Lundgren, M.R.; Mathers, A.; Baillie, A.L.; Dunn, J.; Wilson, M.J.; Hunt, L.; Pajor, R.; Fradera-Soler, M.; Rolfe, S.; Osborne, C.P.; et al. Mesophyll porosity is modulated by the presence of functional stomata. Nat. Commun. 2019, 10, 2825. [Google Scholar] [CrossRef] [Green Version]
  15. Dow, G.J.; Berry, J.A.; Bergmann, D.C. Disruption of stomatal lineage signaling or transcriptional regulators has differential effects on mesophyll development, but maintains coordination of gas exchange. New Phytol. 2017, 216, 69–75. [Google Scholar] [CrossRef] [Green Version]
  16. Tanaka, Y.; Sugano, S.S.; Shimada, T.; Hara-Nishimura, I. Enhancement of leaf photosynthetic capacity through increased stomatal density in Arabidopsis. New Phytol. 2013, 198, 757–764. [Google Scholar] [CrossRef]
  17. Franks, P.J.; Farquhar, G.D. The mechanical diversity of stomata and its significance in gas-exchange control. Plant Physiol. 2007, 143, 78–87. [Google Scholar] [CrossRef] [Green Version]
  18. Wild, A.; Wolf, G. The effect of different light intensities on the frequency and size of stomata, the size of cells, the number, size and chlorophyll content of chloroplasts in the mesophyll and the guard cells during the ontogeny of primary leaves of Sinapis alba. Z. Pflanzenphysiol. 1980, 97, 325–342. [Google Scholar] [CrossRef]
  19. Dongchen, N.A. Effect of water stress on the structure and chlorophyll content of Sedum tatarinowii Maxim leaves. J. Med. Plant 2011, 2, 40–42. [Google Scholar]
  20. Yang, F.; Huang, S.; Gao, R.; Liu, W.; Yong, T.; Wang, X.; Wu, X.; Yang, W. Growth of soybean seedlings in relay strip intercropping systems in relation to light quantity and red:far-red ratio. Field Crops Res. 2014, 155, 245–253. [Google Scholar] [CrossRef]
  21. Wu, Y.; Gong, W.; Yang, W. Shade inhibits leaf size by controlling cell proliferation and enlargement in soybean. Sci. Rep. 2017, 7, 9259. [Google Scholar] [CrossRef]
  22. Yang, F.; Liao, D.; Wu, X.; Gao, R.; Fan, Y.; Raza, M.A.; Wang, X.; Yong, T.; Liu, W.; Liu, J.; et al. Effect of aboveground and belowground interactions on the intercrop yields in maize-soybean relay intercropping systems. Field Crops Res. 2017, 203, 16–23. [Google Scholar] [CrossRef]
  23. Fan, Y.; Chen, J.; Wang, Z.; Tan, T.; Li, S.; Li, J.; Wang, B.; Zhang, J.; Cheng, Y.; Wu, X.; et al. Soybean (Glycine max L. Merr.) seedlings response to shading: Leaf structure, photosynthesis and proteomic analysis. BMC Plant Biol. 2019, 19, 34. [Google Scholar] [CrossRef] [Green Version]
  24. Hogewoning, S.W.; Trouwborst, G.; Maljaars, H.; Poorter, H.; van Ieperen, W.; Harbinson, J. Blue light dose-responses of leaf photosynthesis, morphology, and chemical composition of Cucumis sativus grown under different combinations of red and blue light. J. Exp. Bot. 2010, 61, 3107–3117. [Google Scholar] [CrossRef] [PubMed]
  25. Zheng, L.; Van Labeke, M.C. Long-term effects of red- and blue-light emitting diodes on leaf anatomy and photosynthetic efficiency of three ornamental pot plants. Front. Plant Sci. 2017, 8, 917. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Miao, Y.; Chen, Q.; Qu, M.; Gao, L.; Hou, L. Blue light alleviates ‘red light syndrome’ by regulating chloroplast ultrastructure, photosynthetic traits and nutrient accumulation in cucumber plants. Sci. Hortic. 2019, 257, 108680. [Google Scholar] [CrossRef]
  27. Li, Z.; Chen, Q.; Xin, Y.; Mei, Z.; Gao, A.; Liu, W.; Yu, L.; Chen, X.; Chen, Z.; Wang, N. Analyses of the photosynthetic characteristics, chloroplast ultrastructure, and transcriptome of apple (Malus domestica) grown under red and blue lights. BMC Plant Biol. 2021, 21, 483. [Google Scholar] [CrossRef]
  28. Kuiper, P.J. Dependence upon Wavelength of Stomatal Movement in Epidermal Tissue of Senecio odoris. Plant Physiol. 1964, 39, 952–955. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Sharkey, T.D.; Raschke, K. Separation and measurement of direct and indirect effects of light on stomata. Plant Physiol. 1981, 68, 33–40. [Google Scholar] [CrossRef] [Green Version]
  30. Kinoshita, T.; Shimazaki, K. Analysis of the phosphorylation level in guard-cell plasma membrane H+-ATPase in response to fusicoccin. Plant Cell Physiol. 2001, 42, 424–432. [Google Scholar] [CrossRef] [Green Version]
  31. Tominaga, M.; Kinoshita, T.; Shimazaki, K. Guard-cell chloroplasts provide ATP required for H(+) pumping in the plasma membrane and stomatal opening. Plant Cell Physiol. 2001, 42, 795–802. [Google Scholar] [CrossRef]
  32. Olsen, R.L.; Pratt, R.B.; Gump, P.; Kemper, A.; Tallman, G. Red light activates a chloroplast-dependent ion uptake mechanism for stomatal opening under reduced CO(2) concentrations in Vicia spp. New Phytol. 2002, 153, 497–508. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Doi, M.; Shigenaga, A.; Emi, T.; Kinoshita, T.; Shimazaki, K. A transgene encoding a blue-light receptor, phot1, restores blue-light responses in the Arabidopsis phot1 phot2 double mutant. J. Exp. Bot. 2004, 55, 517–523. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Messinger, S.M.; Buckley, T.N.; Mott, K.A. Evidence for involvement of photosynthetic processes in the stomatal response to CO2. Plant Physiol. 2006, 140, 771–778. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Christie, J.M. Phototropin blue-light receptors. Annu. Rev. Plant Biol. 2007, 58, 21–45. [Google Scholar] [CrossRef] [Green Version]
  36. Hoagland, D.R.; Arnon, D.I. The water-culture method for growing plants without soil. Calif. Agric. Exp. Stn. 1950, 347, 32. [Google Scholar]
  37. Fehr, W.R.; Caviness, C.E.; Burmood, D.T.; Pennington, J.S. Stage of development descriptions for soybeans, Glycine Max (L.) Merrill. Crop Sci. 1971, 11, 929–931. [Google Scholar] [CrossRef]
  38. Li, L.L.; Jiang, X.Q.; Liu, Q.C.; Liu, Q.H.; Sun, Y.K.; Wang, K.L. Adaptability of Camellia sasanqua leaf morphology during natural changes in temperature. J. Appl. Ecol. 2016, 27, 2815–2822. [Google Scholar]
  39. Xie, Z.S.; Du, H.R.; Li, J.B.; Bondada, B. Morphological and structural changes of stomata and leaf veins during growth of grape leaves using tissue clearing technique. Plant Physiol. J. 2018, 54, 237–246. [Google Scholar]
  40. Boardman, N.K. Comparative photosynthesis of sun and shade plants. Annu. Rev. Plant Physiol. 1977, 28, 355–377. [Google Scholar] [CrossRef]
  41. Schuerger, A.C.; Brown, C.S.; Stryjewski, E.C. Anatomical features of pepper plants (Capsicum annuum L.) grown under red light-emitting diodes supplemented with blue or far-red light. Ann. Bot. 1997, 79, 273–282. [Google Scholar] [CrossRef] [PubMed]
  42. López-Juez, E.; Bowyer, J.R.; Sakai, T. Distinct leaf developmental and gene expression responses to light quantity depend on blue-photoreceptor or plastid-derived signals, and can occur in the absence of phototropins. Planta 2007, 227, 113–123. [Google Scholar] [CrossRef] [PubMed]
  43. Fukuda, N.; Fujita, M.; Ohta, Y.; Sase, S.; Nishimura, S.; Ezura, H. Directional blue light irradiation triggers epidermal cell elongation of abaxial side resulting in inhibition of leaf epinasty in geranium under red light condition. Sci. Hortic. 2008, 115, 176–182. [Google Scholar] [CrossRef]
  44. Macedo, A.F.; Leal-Costa, M.V.; Tavares, E.S.; Lage, C.L.S.; Esquibel, M.A. The effect of light quality on leaf production and development of in vitro-cultured plants of Alternanthera brasiliana Kuntze. Environ. Exp. Bot. 2011, 70, 43–50. [Google Scholar] [CrossRef]
  45. Seif, M.; Aliniaeifard, S.; Arab, M.; Mehrjerdi, M.Z.; Shomali, A.; Fanourakis, D.; Li, T.; Woltering, E. Monochromatic red light during plant growth decreases the size and improves the functionality of stomata in chrysanthemum. Funct. Plant Biol. FPB 2021, 48, 515–528. [Google Scholar] [CrossRef]
  46. Hogewoning, S.W.; Douwstra, P.; Trouwborst, G.; van Ieperen, W.; Harbinson, J. An artificial solar spectrum substantially alters plant development compared with usual climate room irradiance spectra. J. Exp. Bot. 2010, 61, 1267–1276. [Google Scholar] [CrossRef] [Green Version]
  47. Savvides, A.; Fanourakis, D.; van Ieperen, W. Co-ordination of hydraulic and stomatal conductances across light qualities in cucumber leaves. J. Exp. Bot. 2012, 63, 1135–1143. [Google Scholar] [CrossRef] [Green Version]
  48. Wang, J.; Lu, W.; Tong, Y.; Yang, Q. Leaf morphology, photosynthetic performance, chlorophyll fluorescence, stomatal development of Lettuce (Lactuca sativa L.) exposed to different ratios of red light to blue light. Front. Plant Sci. 2016, 7, 250. [Google Scholar] [CrossRef] [Green Version]
  49. Ando, E.; Kinoshita, T. Red Light-Induced Phosphorylation of Plasma Membrane H(+)-ATPase in Stomatal Guard Cells. Plant Physiol. 2018, 178, 838–849. [Google Scholar] [CrossRef] [Green Version]
  50. Lampard, G.R.; Macalister, C.A.; Bergmann, D.C. Arabidopsis stomatal initiation is controlled by MAPK-mediated regulation of the bHLH SPEECHLESS. Science 2008, 322, 1113–1116. [Google Scholar] [CrossRef] [Green Version]
  51. Gonzalez, N.; Vanhaeren, H.; Inzé, D. Leaf size control: Complex coordination of cell division and expansion. Trends Plant Sci. 2012, 17, 332–340. [Google Scholar] [CrossRef]
  52. Hetherington, A.M.; Woodward, F.I. The role of stomata in sensing and driving environmental change. Nature 2003, 424, 901–908. [Google Scholar] [CrossRef] [PubMed]
  53. Franks, P.J.; Beerling, D.J. Maximum leaf conductance driven by CO2 effects on stomatal size and density over geologic time. Proc. Natl. Acad. Sci. USA 2009, 106, 10343–10347. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Drake, P.L.; Froend, R.H.; Franks, P.J. Smaller, faster stomata: Scaling of stomatal size, rate of response, and stomatal conductance. J. Exp. Bot. 2013, 64, 495–505. [Google Scholar] [CrossRef] [PubMed]
  55. Elliott-Kingston, C.; Haworth, M.; Yearsley, J.M.; Batke, S.P.; Lawson, T.; McElwain, J.C. Does size matter? atmospheric CO2 may be a stronger driver of stomatal closing rate than stomatal size in taxa that diversified under low CO2. Front. Plant Sci. 2016, 7, 1253. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Haworth, M.; Scutt, C.P.; Douthe, C.; Marino, G.; Gomes, M.T.G.; Loreto, F.; Flexas, J.; Centritto, M. Allocation of the epidermis to stomata relates to stomatal physiological control: Stomatal factors involved in the evolutionary diversification of the angiosperms and development of amphistomaty. Environ. Exp. Bot. 2018, 151, 55–63. [Google Scholar] [CrossRef]
  57. Scoffoni, C.; Chatelet, D.S.; Pasquet-Kok, J.; Rawls, M.; Donoghue, M.J.; Edwards, E.J.; Sack, L. Hydraulic basis for the evolution of photosynthetic productivity. Nat. Plants 2016, 2, 16072. [Google Scholar] [CrossRef] [PubMed]
  58. Tosens, T.; Nishida, K.; Gago, J.; Coopman, R.E.; Cabrera, H.M.; Carriquí, M.; Laanisto, L.; Morales, L.; Nadal, M.; Rojas, R.; et al. The photosynthetic capacity in 35 ferns and fern allies: Mesophyll CO2 diffusion as a key trait. New Phytol. 2016, 209, 1576–1590. [Google Scholar] [CrossRef]
  59. Xiong, D.; Douthe, C.; Flexas, J. Differential coordination of stomatal conductance, mesophyll conductance, and leaf hydraulic conductance in response to changing light across species. Plant Cell Environ. 2018, 41, 436–450. [Google Scholar] [CrossRef]
  60. Jordan, G.J.; Carpenter, R.J.; Koutoulis, A.; Price, A.; Brodribb, T.J. Environmental adaptation in stomatal size independent of the effects of genome size. New Phytol. 2015, 205, 608–617. [Google Scholar] [CrossRef] [Green Version]
  61. de Boer, H.J.; Price, C.A.; Wagner-Cremer, F.; Dekker, S.C.; Franks, P.J.; Veneklaas, E.J. Optimal allocation of leaf epidermal area for gas exchange. New Phytol. 2016, 210, 1219–1228. [Google Scholar] [CrossRef] [Green Version]
  62. Carriquí, M.; Cabrera, H.M.; Conesa, M.; Coopman, R.E.; Douthe, C.; Gago, J.; Gallé, A.; Galmés, J.; Ribas-Carbo, M.; Tomás, M.; et al. Diffusional limitations explain the lower photosynthetic capacity of ferns as compared with angiosperms in a common garden study. Plant Cell Environ. 2015, 38, 448–460. [Google Scholar] [CrossRef] [PubMed]
  63. Brodribb, T.J.; Feild, T.S.; Jordan, G.J. Leaf maximum photosynthetic rate and venation are linked by hydraulics. Plant Physiol. 2007, 144, 1890–1898. [Google Scholar] [CrossRef] [Green Version]
  64. de Boer, H.J.; Eppinga, M.B.; Wassen, M.J.; Dekker, S.C. A critical transition in leaf evolution facilitated the Cretaceous angiosperm revolution. Nat. Commun. 2012, 3, 1221. [Google Scholar] [CrossRef] [PubMed]
  65. de Boer, H.J.; Drake, P.L.; Wendt, E.; Price, C.A.; Schulze, E.D.; Turner, N.C.; Nicolle, D.; Veneklaas, E.J. Apparent overinvestment in leaf venation relaxes leaf morphological constraints on photosynthesis in Arid Habitats. Plant Physiol. 2016, 172, 2286–2299. [Google Scholar] [CrossRef] [Green Version]
  66. Wu, L.; de Boer, H.J.; Zixiao, Z.; Chen, X.; Shi, Y.; Peng, S.; Wang, F. The coordinated increase in stomatal density and vein dimensions during genetic improvement in rice. Agron. J. 2020, 112, 2791–2804. [Google Scholar] [CrossRef]
  67. Lai, J.; Zou, Y.; Zhang, J.; Peres-Neto, P.R. Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package. Methods Ecol. Evol. 2022, 13, 782–788. [Google Scholar] [CrossRef]
  68. Hughes, J.; Hepworth, C.; Dutton, C.; Dunn, J.A.; Hunt, L.; Stephens, J.; Waugh, R.; Cameron, D.D.; Gray, J.E. Reducing stomatal density in barley improves drought tolerance without impacting on yield. Plant Physiol. 2017, 174, 776–787. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  69. Caine, R.S.; Yin, X.; Sloan, J.; Harrison, E.L.; Mohammed, U.; Fulton, T.; Biswal, A.K.; Dionora, J.; Chater, C.C.; Coe, R.A.; et al. Rice with reduced stomatal density conserves water and has improved drought tolerance under future climate conditions. New Phytol. 2019, 221, 371–384. [Google Scholar] [CrossRef]
Agriculture 13 00119 g001 550
Figure 1. The light environment of different treatments. (A) Light quality; (B) Light intensity. 400 B, 100 B, 400 R, and 100 R denote 400 µmol m−2 s−1 under blue light, 100 µmol m−2 s−1 under blue light, 400 µmol m−2 s−1 under red light, and 100 µmol m−2 s−1 under red light, respectively. The mean ± SE is expressed by each value. Different lowercase letters indicate significant differences between treatments (p ≤ 0.05).
Figure 1. The light environment of different treatments. (A) Light quality; (B) Light intensity. 400 B, 100 B, 400 R, and 100 R denote 400 µmol m−2 s−1 under blue light, 100 µmol m−2 s−1 under blue light, 400 µmol m−2 s−1 under red light, and 100 µmol m−2 s−1 under red light, respectively. The mean ± SE is expressed by each value. Different lowercase letters indicate significant differences between treatments (p ≤ 0.05).
Agriculture 13 00119 g001
Agriculture 13 00119 g002 550
Figure 2. The response of stomatal size to various light treatments. (A,B) Stomatal size on the upper epidermis. (C,D) Stomatal size on the lower epidermis. 400 B and 100 B denote the blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. The mean ± SE is expressed by each value. Different lowercase letters indicate significant differences between treatments (p ≤ 0.05).
Figure 2. The response of stomatal size to various light treatments. (A,B) Stomatal size on the upper epidermis. (C,D) Stomatal size on the lower epidermis. 400 B and 100 B denote the blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. The mean ± SE is expressed by each value. Different lowercase letters indicate significant differences between treatments (p ≤ 0.05).
Agriculture 13 00119 g002
Agriculture 13 00119 g003 550
Figure 3. Stomatal density under different light intensities of blue and red light. (A) Photos; (B) the stomatal density of the upper epidermis; (C) the stomatal density of the lower epidermis. 400 B and 100 B denote the blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. Black spots indicate stomata. The stomatal density is higher when the number of black spots is higher. The mean ± SE is expressed in each value. Different lowercase letters indicate significant differences between treatments (p ≤ 0.05).
Figure 3. Stomatal density under different light intensities of blue and red light. (A) Photos; (B) the stomatal density of the upper epidermis; (C) the stomatal density of the lower epidermis. 400 B and 100 B denote the blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. Black spots indicate stomata. The stomatal density is higher when the number of black spots is higher. The mean ± SE is expressed in each value. Different lowercase letters indicate significant differences between treatments (p ≤ 0.05).
Agriculture 13 00119 g003
Agriculture 13 00119 g004 550
Figure 4. Effects of different light treatments on photosynthetic parameters. (A,C) The response curves of net photosynthetic rate and operational stomatal conductance (gop). (B,D) The maximum net photosynthetic rate and operational maximum stomatal conductance (gopmax). 400 B and 100 B denote blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. The mean ± SE is expressed in each value. Different lowercase letters indicate significant differences between treatments (p ≤ 0.05).
Figure 4. Effects of different light treatments on photosynthetic parameters. (A,C) The response curves of net photosynthetic rate and operational stomatal conductance (gop). (B,D) The maximum net photosynthetic rate and operational maximum stomatal conductance (gopmax). 400 B and 100 B denote blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. The mean ± SE is expressed in each value. Different lowercase letters indicate significant differences between treatments (p ≤ 0.05).
Agriculture 13 00119 g004
Agriculture 13 00119 g005 550
Figure 5. The correlation of net photosynthetic rate and operational stomatal conductance (gop). (A) 400 B; (B) 400 R; (C) 100 B; (D) 100 R. 400 B and 100 B denote the blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. Values represent the mean of three replicates. The bars represent the standard error.
Figure 5. The correlation of net photosynthetic rate and operational stomatal conductance (gop). (A) 400 B; (B) 400 R; (C) 100 B; (D) 100 R. 400 B and 100 B denote the blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. Values represent the mean of three replicates. The bars represent the standard error.
Agriculture 13 00119 g005
Agriculture 13 00119 g006 550
Figure 6. The relative importance of individual variables on gopmax and the correlation between gopmax and influence variables. (A) The contribution value analysis; (B) the correlation analysis. Blue indicates a passive correlation, and red shows a positive correlation. The darker color indicates a more robust correlation. Note: gopmax—maximum operational stomatal conductance; LC—leaf tissue compactness; LET—lower epidermal cell thickness; LT—leaf thickness; LL—leaf tissue looseness; LSD—stomatal density of the lower epidermis; LSZ—stomatal size of the lower epidermis; P/C—ratio of palisade tissue to the spongy tissue; PT—palisade tissue thickness; SLW—specific leaf weight; ST—spongy tissue thickness; UET—upper epidermal cell thickness; USD—stomatal density of the upper epidermis; USZ—stomatal size of the upper epidermis.
Figure 6. The relative importance of individual variables on gopmax and the correlation between gopmax and influence variables. (A) The contribution value analysis; (B) the correlation analysis. Blue indicates a passive correlation, and red shows a positive correlation. The darker color indicates a more robust correlation. Note: gopmax—maximum operational stomatal conductance; LC—leaf tissue compactness; LET—lower epidermal cell thickness; LT—leaf thickness; LL—leaf tissue looseness; LSD—stomatal density of the lower epidermis; LSZ—stomatal size of the lower epidermis; P/C—ratio of palisade tissue to the spongy tissue; PT—palisade tissue thickness; SLW—specific leaf weight; ST—spongy tissue thickness; UET—upper epidermal cell thickness; USD—stomatal density of the upper epidermis; USZ—stomatal size of the upper epidermis.
Agriculture 13 00119 g006
Table
Table 1. Soybean leaf structure under different light intensities of blue and red light: 400 B and 100 B denote the blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively.
Table 1. Soybean leaf structure under different light intensities of blue and red light: 400 B and 100 B denote the blue light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively. 400 R and 100 R denote the red light with 400 µmol m−2 s−1 and 100 µmol m−2 s−1, respectively.
Treatments400 B100 B400 R100 R
SLW (mg/cm2)0.223 ± 0.04 a0.185 ± 0.0 b0.14 ± 0.01 c0.125 ± 0.01 c
LT (µm)115.678 ± 4.4 a63.252 ± 4.5 c80.334 ± 6.2 b55.401 ± 2.9 d
UET (µm)12.346 ± 1.7 a5.813 ± 0.9 b12.976 ± 2.1 a6.581 ± 1.1 b
LET (µm)7.161 ± 1.2 a4.081 ± 1 b6.979 ± 1.2 a4.453 ± 0.7 b
PT (µm)68.541 ± 4.4 a40.826 ± 3.3 b49.209 ± 5.3 c24.386 ± 2.2 d
ST (µm)33.485 ± 3.8 a19.014 ± 2.8 b17.873 ± 2.1 b14.923 ± 1.5 c
LC0.593 ± 0.04 b0.649 ± 0.08 a0.614 ± 0.07 ab0.622 ± 0.04 ab
LL0.289 ± 0.03 ab0.298 ± 0.04 a0.221 ± 0.02 c0.268 ± 0.03 b
P/C2.07 ± 0.25 c2.19 b ± 0.35 bc2.805 ± 0.3 a2.35 ± 0.25 b
Notes: SLW—specific leaf weight; LT—leaf thickness; UET—upper epidermal cell thickness; LET—lower epidermal cell thickness; PT—palisade tissue thickness; ST—spongy tissue thickness; LC—leaf tissue compactness; LL—leaf tissue looseness; P/C—ratio of palisade tissue to spongy tissue. The mean ± SE is expressed by each value. Different lowercase letters indicate significant differences between treatments (p ≤ 0.05).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chen, J.; Gao, J.; Wang, Q.; Tan, X.; Li, S.; Chen, P.; Yong, T.; Wang, X.; Wu, Y.; Yang, F.; et al. Blue-Light-Dependent Stomatal Density and Specific Leaf Weight Coordinate to Promote Gas Exchange of Soybean Leaves. Agriculture 2023, 13, 119. https://doi.org/10.3390/agriculture13010119

AMA Style

Chen J, Gao J, Wang Q, Tan X, Li S, Chen P, Yong T, Wang X, Wu Y, Yang F, et al. Blue-Light-Dependent Stomatal Density and Specific Leaf Weight Coordinate to Promote Gas Exchange of Soybean Leaves. Agriculture. 2023; 13(1):119. https://doi.org/10.3390/agriculture13010119

Chicago/Turabian Style

Chen, Jiyu, Jing Gao, Qi Wang, Xianming Tan, Shenglan Li, Ping Chen, Taiwen Yong, Xiaochun Wang, Yushan Wu, Feng Yang, and et al. 2023. "Blue-Light-Dependent Stomatal Density and Specific Leaf Weight Coordinate to Promote Gas Exchange of Soybean Leaves" Agriculture 13, no. 1: 119. https://doi.org/10.3390/agriculture13010119

APA Style

Chen, J., Gao, J., Wang, Q., Tan, X., Li, S., Chen, P., Yong, T., Wang, X., Wu, Y., Yang, F., & Yang, W. (2023). Blue-Light-Dependent Stomatal Density and Specific Leaf Weight Coordinate to Promote Gas Exchange of Soybean Leaves. Agriculture, 13(1), 119. https://doi.org/10.3390/agriculture13010119

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop