Allelochemicals from Moso Bamboo: Identification and Their Effects on Neighbor Species

Abstract

Moso bamboo, which is essential to China’s economy, is currently facing significant threats due to declining profits. Inadequate management of moso bamboo can negatively impact the surrounding ecosystems. This study investigated allelopathy in moso bamboo forests by identifying potential allelochemicals and their effects on coexisting plants. Fresh leaves and litter from moso bamboo were collected to examine allelochemicals released through natural processes such as rainwater leaching and litter decomposition. Seven substances with potential allelopathic effects were identified using liquid chromatography–mass spectrometry (LC–MS). Four of these substances—DBP, PHBA, citric acid, and CGA—were selected for a detailed analysis of their effects on the photosynthetic and antioxidant systems of two naturally coexisting plants, Phoebe chekiangensis and Castanopsis sclerophylla. The results indicated that the four chemicals influenced P. chekiangensis and C. sclerophylla through different patterns of interference. DBP, PHBA, and citric acid negatively impacted the transfer of electrons during photosynthesis in both plants but had a lesser effect on the antioxidant system-related indicators in P. chekiangensis. In C. sclerophylla, these four chemicals led to a significant accumulation of reactive oxygen species (ROS) and increased malondialdehyde (MDA) content and catalase (CAT) activity to varying degrees. Furthermore, the relative abundance of fungi and bacteria in the soil was also affected by the DBP treatment. The identification of allelochemicals from moso bamboo, along with the investigation of their mechanisms, provides valuable insights into competitive interactions among plant species, particularly between moso bamboo and other species, along with the expansion of moso bamboo forests.

1. Introduction

Phyllostachys edulis (moso bamboo) is an extensively used commercial species that existed in southern China. Decreasing demand for bamboo timber and rising labor costs have led farmers to ignore bamboo forest management. Inadequate management of moso bamboo has caused substantial ecosystem change [1,2]. Local governments encourage people to add commercial trees, such as precious wood or medicinal tree species, to bamboo forests to improve their economic value. Promoting the economic value of bamboo-dominated forests has motivated farmers to maintain them effectively and sustainably [3]. However, it is unclear whether these immigrant species can adapt to new environments and withstand competition with bamboo. Understanding the effects of moso bamboo on neighboring plant communities is crucial for ecosystem health and sustainability.

Studies have shown that sapling survival and growth rates appear to be restrained by bamboo [4] and that species richness in bamboo-dominated stands decreases [5]. Moso bamboo interference is distinct from resource competition, which is regulated by factors such as light, water, mineral nutrients, and living space [6]. However, the superior growth of bamboo in forests is not solely due to effective light utilization. Bamboo root competition and mechanical crushing can cause root and stem damage in nearby saplings and seedlings [7], which affects the growth of surrounding plants. Nevertheless, competition for resources and physical damage may not completely explain the decrease in species richness and forest structure changes, suggesting that other strategies involving plant–plant interactions could be present. Giving further support to this hypothesis, some investigations have demonstrated that secondary metabolites, allelopathic compounds produced by bamboo, and chemicals from bamboo litters inhibit seed germination and tree growth [8].

Allelopathy is a complex process that includes both stimulating and inhibiting effects caused by the release of particular chemical molecules called allelochemicals [9]. Allelochemicals are substances that plants use to protect themselves from environmental hazards and can enter the environment through root exudation, volatilization, leaching, and litter decomposition [10]. Moreover, allelochemicals have concentration-dependent effects and are released into the environment along with numerous other secondary metabolites. These effects disrupt growth, reproduction, germination, and distribution.

Allelopathy in agriculture has been studied for several decades. Technological advancements have led to extensive research on the identification, mechanisms, and applications of allelochemicals [11]. Hussain [12] identified a variety of allelochemicals from the root exudates of sorghum (Sorghum Moench), a common allopathic crop, such as p-hydroxybenzoic acid, ferulic acid, chlorogenic acid, gallic acid, and caffeic acid. Shi [13] identified the allelochemicals of velvetleaf (Abutilon theophrasti), which contains protocatechuic acid, gallic acid, chlorogenic acid, and vanillic acid, and its aqueous extract inhibits the germination and growth of soybean. Qiao [14] demonstrated that triterpenes and anthraquinone, the allelochemicals of Panax notoginseng, hinder continuous cropping and affect other plants and rhizosphere microorganisms.

Many trees also exhibit allelochemical activity and can affect the growth of other plants [15]. Allelochemicals from Juglans nigra and Acer platanoides strongly affect the growth of Acer saccharinum and Betula papyrifera saplings [16]. The primary allelochemicals of Cinnamomum septentrionale, including alkanes, terpenoids, steroids, and ketones, significantly inhibit the growth of Eucalyptus grandis [17]. Kong et al. [18] confirmed a novel cyclic dipeptide from Chinese Fir (Cunninghamia lanceolata (Lamb.) Hook), 6-hydroxy-1,3-dimethyl-8-nonadecyl-[1,4]-diazocane-2,5-diketone can damage purple nutsedge (Cyperus rotundus), yellow nutsedge (Cyperus esculentus), field bindweed (Convolvulus arvensis), and horse nettle (Solanum carolinense).

Additionally, allelopathy promotes plant invasion, intensifies grassland degradation, and plays a role in the regeneration of natural forests [19]. Additionally, it influences the biodiversity, productivity, and sustainability of grasslands and forests [20]. However, current research on the allelopathic effects of bamboo is limited. Rawat [21] showed that depending on its concentration, leaf leachates from solid bamboo (Dendrocalamus stocksii) could prevent finger millet (Eleusine coracana) from sprouting and growing. Ogita and Sasamoto [22] assayed dried leaves of four bamboo species (Bambusa multiplex cv. Houraichiku, Phyllostachys bambusoides cv. Madake, Phyllostachys nigra cv. Hachiku, and Sasa kurilensis cv. Chishimazasa) exhibited moderate allelopathic effects on lettuce (Lactuca sativa) seedlings with minimal differences between them. Sasa kurilensis showed the strongest inhibitory effect, particularly the inhibition of yellow color accumulation in lettuce protoplasts. However, they did not identify the effective chemical compounds. Jose [23] evaluated the phytotoxic effects of Merostachys riedeliana (a Brazilian bamboo) and found that its leaf extract had the highest inhibitory effects on seed germination and seedling growth. 2(3H)-Benzoxazolinone, p-hydroxybenzoic acid, vanillic acid, and trans-ferulic acid may be putative allelochemicals. These studies suggest that bamboo is likely to compete with surrounding plants by releasing allelochemicals. This is considered to be a key mechanism for characterizing interspecific interactions, community structures, and vegetation dynamics. Although allelopathy has been studied in other bamboo species, it has not yet been studied in moso bamboo. Furthermore, no study has investigated the allelopathic chemicals of moso bamboo or their impact on economically important trees that can coexist with it.

In the present study, we focused on identifying allelochemicals in moso bamboo leaves and their effects on two economically important trees, Phoebe chekiangensis and Castanopsis sclerophylla. This is particularly evident in the context of photosynthesis and antioxidant systems. This study aimed to provide a theoretical foundation for research on allelochemical competition in moso bamboo forest environments where moso bamboo predominates. It also aims to contribute to a broader understanding of bamboo ecology and to facilitate the development of sustainable management strategies in bamboo-dominated regions.

2. Materials and Methods

2.1. Plant Materials

Moso bamboo samples, fresh leaves, and litter were collected from two routinely managed moso bamboo forests in Zhejiang Province (place 1: P1, in Changxing, Huzhou, and place 2: P2, in Panan, Jihua). Changxing and Panan in Zhejiang Province experienced a humid subtropical climate without a dry season. The annual average temperature is 18 °C, the annual humidity level is 75%, and the annual precipitation is 109–130 mm. Two-year-old potted seedlings of Phoebe chekiangensis and Castanopsis sclerophylla, with a plant height of approximately 60 cm, pot body diameter of 15 cm, and soil layer height of 13 cm, were cultivated in the Jiande Forest Farm (Hangzhou, Zhejiang). The soil was collected meticulously from the surrounding woods and was classified as yellow loam. The soil was mixed prior to planting to ensure consistency in the soil conditions. The saplings were then routinely managed in a shade house.

2.2. Extraction of Allelochemicals of Phyllostachys edulis Leaves

Four quadrats were selected from each location (P1 and P2). Each quadrat measures 20 m × 20 m squares and has five points distributed in an x-shape, one at the center and four at the corners. Fresh leaves and litter (mostly withered and yellow leaves) of moso bamboo were immediately placed in an ice box and stored at 4 °C after being picked from the quadrats. The samples were mixed in equal proportions at the same locations within two nearby quadrats. Eight samples were used for follow-up testing. Clean scissors were used to shred 500 g of fresh leaves and litter separately in a beaker containing 300 mL of distilled water for 24 h at 25 °C, with ultrasonic-assisted vibration for the first 20 min. The extract was collected by filtration through glass microfiber filters (Whatman GF/F 0.7 $\mu$m CAT No. 1825). The samples were then placed in a freezer dryer (Labconco FreeZone^®, Kansas, MI, USA) and dried. The dried samples were placed on ice, and metabolites were extracted using 50% methanol buffer (mass-to-volume ratio of 1:6). The supernatants were transferred to 96-well plates after centrifugation. The samples were stored at −80 °C before liquid chromatography–mass spectrometry (LC–MS) analysis.

2.3. Identification of Potential Allelochemicals

Chromatographic separations were performed using an ultra-performance liquid chromatography (UPLC) machine from SCIEX in the UK by LC-Bio Technology Co., Ltd., Hangzhou, China. Reversed-phase separation was conducted using an ACQUITY UPLC T3 column (10 0 mm × 2.1 mm, 1.8 µm, Waters, UK). The column oven temperature was maintained at 35 °C. The flow rate was 0.4 mL/min with the mobile phase comprising solvent A (water with 0.1% formic acid) and solvent B (acetonitrile with 0.1% formic acid). The gradient elution conditions were programmed as follows: from 0 to 0.5 min, 5% B; from 0.5 to 7 min, 5% to 100% B; at 7 to 8 min, 100% B; from 8 to 8.1 min, 100% to 5% B; and from 8.1 to 10 min, 5% B. Each sample was injected at a volume of 4 µL.

The mass spectrometric data collected from UHPLC-MS-MS were analyzed using XCMS online in pair-wise job mode. The metabolites were annotated by comparing the exact molecular mass data (m/z) of the samples with information in the online KEGG and HMDB databases.

2.4. Chemical Treatment of P. chekiangensis and C. sclerophylla

We chose four chemicals, dibutyl phthalate (DBP), citric acid, p-hydroxybenzoic acid (PHBA), and chlorogenic acid (CGA), based on existing research [24,25,26,27,28,29,30,31] as potential allelochemicals, and confirmed their allelopathic properties. DBP, citric acid, PHBA, and CGA were dissolved in water to create solutions at concentrations of 1 mM, 10 mM, and 20 mM, labeled as solutions 1–12. Each treatment and control group consisted of five pots for both P. chekiangensis and C. erophylla, and all the pots were randomly positioned. Five pots (for one treatment) were watered with a 100 mL solution every three days, and the blanks (CK) were irrigated with an equal amount of water (100 mL). After 7 weeks of continuous treatment, photosynthesis, enzyme activity, and other subsequent tests were assessed on the 7th day following the final application.

2.5. The Fluorescence of Chlorophyll (Chl) A and Physiological and Biochemical Parameters

Six leaves were selected from each pot, two each from the upper, middle, and lower parts of the plant. After 30 min of dark adaptation, the leaves were measured using an OPYI-SCIENCES OS30p (Opti-Sciences Ltd., Hudson, NH, USA) equipment to assess fluorescence parameters and the Chl a fluorescence induction kinetics curve. The parameter settings and operations were strictly in accordance with the instrument manual. The same leaves were then harvested on ice and returned to the laboratory for storage at 4 °C while waiting for subsequent tests. Two leaves from the same position (upper, middle, and lower parts) were ground as one test sample in this experiment. The levels of chlorophyll, Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), peroxidase (POD), catalase (CAT), reactive oxygen species (ROS), and malondialdehyde (MDA) were analyzed using an ELISA (enzyme-linked immunosorbent assay) kit (Mlbio Ltd., Shanghai, China). Each protocol was performed in accordance with the manufacturer’s instructions.

2.6. Soil DNA Extraction, Amplification, and Sequencing

The abundance of soil microorganisms was also investigated using the combination of DBP × P. chekiangensis. Following the other tests mentioned above, soil was collected from each pot treated with DBP. After removal of the plants, the roots and nuggets from each soil sample were sieved (less than 2 mm), and an aliquot was kept at −20 °C until soil DNA was extracted. Soil DNA from different samples was extracted using CTAB according to the manufacturer’s instructions. The total DNA was eluted in 50 $\mu$L of Elution buffer and stored at −80 °C until PCR was performed by LC-Bio Technology Co., Ltd., Hangzhou, China.

Bacterial 16S rRNA genes and fungal ITS regions were PCR-amplified with primer pairs targeting V3–V4 [32] (341F: 5′-CCTACGGGNGGCWGCAG-3′ and 805R: 5′-GACTACH VGGGTATCTAATCC-3′) and ITS2 [33] (ITS1FI2: 5′-GTGARTCATCGAATCTTTG-3′ and ITS2: 5′-TCCTCCGC TTATTGATATGC-3′), respectively. PCR amplification was performed in a total volume of 25 $\mu$L reaction mixture containing 25 ng of template DNA, 12.5 $\mu$L PCR Premix, 2.5 $\mu$L of each primer, and PCR-grade water to adjust the volume. The PCR conditions used to amplify the prokaryotic 16S and ITS fragments consisted of an initial denaturation at 98 °C for 30 s; 32 cycles of denaturation at 98 °C for 10 s; annealing at 54 °C for 30 s; and extension at 72 °C for 45 s; and a final extension at 72 °C for 10 min. Electrophoresis on a 2% agarose gel was used to validate the PCR results. Ultrapure water was utilized throughout the DNA extraction procedure instead of the sample solution as a negative control to eliminate the potential for false-positive PCR results. Qubit (Invitrogen, Waltham, MA, USA) was used to quantify the PCR products after purification using AMPure XT beads (Beckman Coulter Genomics, Danvers, MA, USA). The amplicon pools were ready for sequencing, and an Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA) and Library Quantification Kit for Illumina (Kapa Biosciences, Woburn, MA, USA) were used to measure the size and quantity of the amplicon library. The NovaSeq PE250 platform was used to sequence libraries.

The samples were sequenced on an Illumina NovaSeq platform, according to the manufacturer’s instructions. Paired-end reads were assigned to samples based on their unique barcodes and shortened by cutting off the barcodes and primer sequences. Paired-end reads were merged using Pear software. According to fqtrim (v0.94), quality filtering of the raw reads was performed under specific conditions to produce high-quality clean tags. The Vsearch software (v2.3.4) was used to filter chimeric sequences. Following DADA2 dereplication, we acquired the feature table and feature sequence. The same number of sequences was randomly extracted by reducing the number of sequences to the lowest of some samples, and the relative abundance (X fungal count/total count) was employed in fungal taxonomy. Sequence alignment of species annotations was performed using the QIIME2 plugin feature classifier, and the alignment database was RDP and unite.

2.7. Statistical Analysis

The fluorescence data of chlorophyll a, physiological and biochemical parameters, and relative abundance of fungi and bacteria were statistically analyzed using SPSS 26. A one-way analysis of variance (ANOVA) was conducted to compare the results with those of the control group. All trials were performed using a randomized complete block design, with each treatment consisting of five replicates (five pots). Comparisons among means were evaluated using the Scheffé test at a significance level of p = 0.05.

3. Results

3.1. The Potential Allelochemicals of Moso Bamboo Leaves

After matching the MS 2 data with the online database, hundreds of chemicals were identified. Most of these compounds include amino acids, cholesterol, phosphatidylcholine, lipids, and organic acids. According to the published literature, we surmised that seven chemicals might be potential allelochemicals. Their relative contents in fresh leaves and litter at the two locations are shown in Figure 1. Detailed information regarding the MS2 of the seven chemicals shown in

Table A1. MS2 spectrometry data of moso bamboo leaves.

Metabolite	RT	MZ	Library MZ	HMDB No.	Formula	MS2 Spectrum
Quinic acid	0.95	191.05	191.05	0003072	C7H12O6	40.99946:37 41.00308:441 43.01778:334 44.99833:629 55.01411:72 55.01621:180 57.03528:642 59.00934:74 59.01694:487 66.79628:73 67.0204:480 69.03326:261 71.01401:1962 73.0288:179 79.86205:36 81.03254:357 83.01643:214 83.04732:214 85.02432:257 85.03083:4830 85.91743:73 87.01008:882 89.02543:250 92.72235:75 93.03541:1325 97.03492:185 99.00651:981 101.02489:179 108.02123:107 109.02908:361 111.04692:327 127.03934:583 129.01773:143 137.02631:107 153.0182:107 171.03391:214 173.04942:417 174.96277:79 191.05605:3588
Citric acid	1.60	191.02	191.02	0000094	C6H8O7	67.01717:72 87.00646:143 100.93161:36 110.99974:72
CGA	2.79	353.08	355.10	0003164	C16H18O9	61.00891:36 75.04426:36 77.04044:109 85.02658:74 89.03801:679 95.04737:72 107.04317:72 107.05048:179 111.04681:109 117.03191:913 119.05106:72 121.02843:72 133.02127:75 133.10762:74 135.04533:1445 137.00038:39 139.03938:115 144.5719:195 145.02902:3215 146.12634:47 162.5148:107 162.54901:133 163.0265:309 163.03912:35359 163.4469:172 163.7341:72 165.10852:72 169.07706:72 181.05067:251 193.04715:72 267.00098:72 355.17688:72
Caffeic acid	3.29	179.03	179.03	0001964	C9H8O4	65.03854:36 77.04755:36 79.05643:289 81.63769:36 89.04289:214 89.90189:36 91.05725:107 106.04301:143 107.04892:404 109.02779:217 112.39214:36 117.0374:326 123.76258:36 133.03691:146 134.03902:2391 134.62177:135 135.04488:12136 135.6627:83 136.50627:71 179.03864:107
Sinapic acid	3.86	223.06	223.06	0032616	C11H12O5	41.00102:107 65.00404:107 75.02504:36 89.04119:77 92.02576:75 93.03519:2444 105.03133:72 117.00034:79 121.02782:4162 123.58313:44 126.51756:36 134.03699:252 135.04285:1136 139.62241:36 148.01752:215 148.02438:86 149.01236:142 149.02271:5303 150.40866:87 152.67061:76 156.12781:75 160.99889:36 163.03751:966 164.0363:126 164.04715:3315 165.01819:1438 179.06845:179 182.74611:36 193.0014:145 193.01318:8430 207.03339:179 208.04054:1548 223.05495:72
PHBA	4.41	137.02	137.02	0000500	C7H6O3	41.00315:72 56.64464:76 65.03863:2151 67.02058:72 75.02061:215 75.02551:251 91.01833:72 92.74442:161 92.92404:201 93.03436:44951 93.45304:83 93.51313:125 93.55547:82 93.85078:72 95.14271:107 95.73878:72 97.11039:72 123.47231:36 137.02518:362
DBP	6.75	279.16	279.16	0033244	C16H22O4	38.01254:36 39.02306:143 39.37939:37 41.03774:354 41.71175:42 55.05587:18 57.07119:2732 64.83581:36 65.03609:366 77.04112:18 81.07014:36 86.06173:18 90.22057:37 93.0322:653 95.0866:36 109.7506:37 121.02752:2016 148.55592:509 148.60413:130 148.93484:117 149.02275:74692 149.24178:159 149.40399:36 149.65784:54 149.67857:54 149.77361:36 149.91017:54 149.97934:54 150.09178:54 150.2285:54 150.35487:54 150.48997:54 150.53676:54 150.63553:54 150.98932:54 151.07089:36 151.23758:54 151.27579:72 151.48254:54 151.72598:36 152.25525:36 167.03267:125 173.04865:36 201.04401:235 205.07475:36 223.09502:54 233.22247:18 262.13608:18 279.09756:345

and

Table A2. MS2 Spectrometry Data of Moso Bamboo Litter.

Metabolite	RT	MZ	Library MZ	HMDB No.	Formula	MS2 Spectrum
Quinic acid	0.96	191.05	191.05	0003072	C7H12O6	44.99367:72 44.99936:143 57.03325:72 59.00944:107 59.0127:179 65.04426:36 67.01704:72 69.03337:107 71.01174:251 73.02771:107 81.03648:143 83.05002:109 85.02705:1769 87.0089:325 87.04842:36 93.03555:625 94.53048:36 99.00806:72 99.04179:107 104.30777:36 109.02776:215 111.04559:179 127.03633:215 131.04393:36 145.0584:36 171.02304:72 173.04779:111 191.05823:1471
Citric acid	1.15	191.02	191.02	0000094	C6H8O7	31.99152:36 39.02368:107 41.00331:322 41.0395:251 41.99502:36 43.01988:183 57.03458:970 59.01406:107 59.01949:74 67.01738:1122 69.70777:75 75.005:36 85.03013:3065 86.48846:161 87.00806:7091 87.41035:52 93.03336:36 102.94829:72 103.03859:143 111.00906:8423 125.02664:36 129.02032:251 191.01074:72
Caffeic acid	3.30	179.03	179.03	0001964	C9H8O4	47.00843:36 89.03958:107 107.05118:216 134.04324:439 135.04585:1885
PHBA	4.42	137.02	137.02	0000500	C7H6O3	31.99063:73 41.01134:36 49.00727:76 60.25399:73 65.03873:1443 65.45056:40 67.01837:72 75.02439:143 92.74048:107 92.74864:143 92.8466:166 93.0345:37523 93.75381:72 94.12752:72 95.0079:72 95.40617:72 97.20938:72 137.02376:215
DBP	6.74	279.16	279.16	0033244	C16H22O4	38.01545:36 39.01984:72 39.02337:179 41.03806:418 56.89462:85 57.06944:4119 62.47806:18 65.03765:402 69.07075:54 81.06935:72 93.03272:965 107.08677:55 111.04358:37 113.01662:18 120.64935:56 121.02969:2255 147.78308:36 148.55147:368 149.02345:67704 149.19244:99 149.35982:67 149.6499:54 149.71384:54 149.74149:90 149.78642:54 149.86938:54 149.92645:54 149.93855:72 149.96796:54 150.01984:36 150.08557:54 150.1219:54 150.15825:54 150.1946:72 150.23785:54 150.30019:90 150.41966:72 150.50455:54 150.66225:54 150.71078:54 150.76106:54 150.85645:54 151.01607:54 151.06813:54 151.28171:54 151.30777:36 151.48152:36 152.20892:54 167.0316:215 195.07079:18 201.04688:304 205.08372:90 279.08923:234 279.24258:36

. Five chemicals (dibutyl phthalate, citric acid, 4-hydroxybenzoic acid, jasmonic acid, quinic acid, and caffeic acid) were detected in both fresh leaves and moso bamboo litter, while two (sinapic acid and chlorogenic acid) were detected only in fresh leaves.

Dibutyl phthalate (DBP), regarded as an allelochemical, was found by Geng [24] in hot peppers (Capsicum frutescens). It is considered an autotoxic substance that has a significant inhibitory effect on seed germination and seedling growth in Lanzhou lily (Lilium davidii var. unicolor) [25]. Among the seven chemicals, DBP had the highest average content, except for chlorogenic acid, which showed little difference between the four samples.

Citric acid is a common root secretion [26] that Syed [27] conjectured was an allelochemical from Tamarindus indica but had less effect on lettuce seedling growth. Fresh leaves contained less citric acid than litter, and P1 samples contained more citric acid than P2. These findings indicate that the production of citric acid may be influenced by the conditions of the location, particularly the soil environment [34].

4-hydroxybenzoic acid (PHBA) is a phenolic compound recognized as an allelochemical in various studies [28,29,30]. The relative concentration of PHBA was higher in the samples (fresh leaves and litter) collected from P1 than in P2. There was a minimal difference between the fresh leaves and litter in samples taken from the same location. This indicated that the production of p-hydroxybenzoic acid may also be related to the environment.

Quinic acid (QA), a major component of organic acids found in plants [35], has been studied for its possible allelopathic effects. However, its efficacy has not been established [36]. They also exhibit antimicrobial properties [37]. The quinic acid content was higher in Fresh P1 than in the other three samples.

Caffeic acid and sinapic acid are both trans-cinnamic acid derivatives [38]. It has been found to be highly phytotoxic, particularly to weeds [39,40], because it causes ROS production, MDA accumulation, and interference with the activities of several enzymes (POD, SOD, and CAT) [41]. Fresh P1 had the highest concentration of caffeic acid, followed by Litter P1 and Litter P2, while Fresh P2 had the lowest concentration.

Sinapic acid, a phenolic component, is the main allelochemical of dwarf lilyturf (Ophiopogon japonicus) and has inhibitory effects on the germination and growth of barnyardgrass (Echinochloa crus-galli var. oryzicola) [42,43]. In the present study, it was only detected in samples from location P1 and was found mainly in fresh leaves, with minimal amounts in the litter.

Chlorogenic acid (CGA), a type of phenolic acid, is abundant in potato peels [31] and can inhibit the growth of lettuce seedlings at high concentrations and stimulate the ROS accumulation in lettuce [44]. CGA was unique among the four compounds because it was absent from samples P2, including fresh leaves and litter, and showed a high level in Fresh P1 and an inadequate level in Litter P1.

3.2. Effects of Four Chemicals on Photosystem II (PS II) Chl a Fluorescence of P. chekiangensis and C. sclerophylla

We used P. chekiangensis and C. sclerophylla, two prevalent mixed trees in moso bamboo forests in Zhejiang Province (China), to confirm the effects on Chl a fluorescence of DBP, citric acid, PHBA (average relative content of the top three), and CGA (highest individual content).

3.2.1. OJIP Polyphasic Chl a Fluorescence Rise Kinetics

Figure 2 shows the OJIP transients of P. chekiangensis and C. sclerophylla leaves under DBP, citric acid, PHBA, and CGA stress. Typical fluorescence rise curves of the control (CK) were used to illustrate the changes in the kinetics of the OJIP rise.

DBP stress. Under DBP treatment at various concentrations, the Chl a fluorescence intensity in the K-P phase decreased, and the degree of reduction was proportional to the concentration, except for C. sclerophylla under 1 mM and 10 mM DBP stress (these two curves almost overlapped, Figure 2a,c). In addition, both P. chekiangensis and C. sclerophylla under 20 mM DBP stress of PS II were characterized by flattened fluorescence curves without visible characteristic steps: K, J, and I.

PHBA stress. The OJIP transient curves of P. chekiangensis and C. sclerophylla leaves were completely different under PHBA treatments. In P. chekiangensis, all the curves, including CK, had close start ${\mathrm{F}}_0$, 1 mM, and 10 mM PHBA dropped after K (0.3 ms), and they had almost the same trace between O and I (30 ms), and the Chl a fluorescence intensity of 10 mM was lower than 1 mM after I (Figure 2a). The OJIP curve of 20 mM PHBA dropped significantly before K when compared with the others. In contrast, for C. sclerophylla leaves, PHBA treatments increased the Chl a fluorescence intensity for the entire three seconds but was out of proportion to the concentration (Figure 2c). Fluorescence intensities from high to low were as follows: 20 mM PHBA, 1 mM PHBA, and 10 mM PHBA.

Citric acid stress. When P. chekiangensis was subjected to citric acid stress, the Chl a fluorescence intensity decreased in three seconds (Figure 2b), whereas the lowest concentration of 1 mM citric acid showed the largest decrease in fluorescence intensity, and the 10 mM and 20 mM citric acid treatments were close to each other. For C. sclerophylla (Figure 2d), the fluorescence intensity of 1 mM and 10 mM citric acid was lower than CK, and 20 mM citric acid was similar to CK. The curves of 1 mM and 10 mM citric acid were similar, but 1 mM decreased after J (2 ms) compared with 10 mM. Although the 20 mM citric acid treatment was similar to CK, it slightly increased the fluorescence intensity from steps O to I and decreased from 100 ms.

CGA stress. After P. chekiangensis was treated with 1 mM and 20 mM CGA, the fluorescence intensity increased (Figure 2b), and 1 mM CGA was higher than 20 mM. However, with 10 mM CGA, the fluorescence intensity decreased after 1 ms compared with CK. The influence of CGA on Chl a fluorescence intensity in C. sclerophylla might be the smallest among all the results. The fluorescence kinetic curves of CGA and CK almost overlapped before J but dropped slightly between J and I and strongly after I.

3.2.2. Chl a Fluorescence Parameters

The Chl a fluorescence parameters of P. chekiangensis and C. sclerophylla leaves under DBP, PHBA, citric acid, and CGA stress are shown in Figure 3.

Parameters Under DBP: Phenomenological energy fluxes per excited cross section (CS) of leaves on P. chekiangensis and C. sclerophylla were strongly affected by DBP. The four parameters, namely, absorption flux (${\mathrm{ABS/CS}}_0$), trapped energy flux (${\mathrm{TR}}_0$/${\mathrm{CS}}_0$), electron transport flux (${\mathrm{ET}}_0$/${\mathrm{CS}}_0$), and active reaction center (${\mathrm{RC/CS}}_0$), of the leaves under DBP stress were all significantly lower than CK for P. chekiangensis. The values of ${\mathrm{TR}}_0$/${\mathrm{CS}}_0$, ${\mathrm{ET}}_0$/${\mathrm{CS}}_0$, and ${\mathrm{RC/CS}}_0$ decreased, and the dissipated energy flux (${\mathrm{DI}}_0$/${\mathrm{CS}}_0$) increased under 20 mM DBP in C. sclerophylla. DBP also significantly decreased the quantum yields of photosynthesis in the two kinds of plants, such as the maximum quantum yield of PSII photochemistry (${\mathrm{TR}}_0$/ABS), quantum yield of electron transport from QA– to the PQ pool (${\mathrm{ET}}_0$/ABS), and quantum yield of electron transport from QA– to the final electron acceptors of PSI (${\mathrm{RE}}_0$/ABS). Meanwhile, it also increased the quantum yield of energy dissipation in the PSII antenna (${\mathrm{DI}}_0$/ABS). The specific energy flux per active reaction center did not appear to be significantly affected by DBP; however, the values of absorption (ABS/RC), trapping (${\mathrm{TR}}_0$/RC), dissipation (${\mathrm{DI}}_0$/RC), and electron flux from QA– to the PSI acceptor side per RC (${\mathrm{RE}}_0$/RC) increased under 20 mM DBP stress of C. sclerophylla.

Parameters Under PHBA: Phenomenological energy fluxes per CS, quantum yields of photosynthesis, and specific energy fluxes per active reaction center of leaves of P. chekiangensis were not affected by 1 mM or 10 mM PHBA. However, 20 mM PHBA significantly decreased ${\mathrm{TR}}_0$/${\mathrm{CS}}_0$, ${\mathrm{ET}}_0$/${\mathrm{CS}}_0$, and ${\mathrm{RC/CS}}_0$ and increased ${\mathrm{DI}}_0$/${\mathrm{CS}}_0$. The quantum yields, including ${\mathrm{TR}}_0$/ABS, ${\mathrm{ET}}_0$/ABS, and ${\mathrm{RE}}_0$/ABS, also decreased, and ${\mathrm{DI}}_0$/ABS increased. The effects of three concentrations of PHBA on C. sclerophylla were not significantly different. They increased the dissipation (${\mathrm{DI}}_0$/${\mathrm{CS}}_0$), and the quantum yields ${\mathrm{ET}}_0$/ABS and ${\mathrm{RE}}_0$/ABS.

Parameters Under Citric Acid: The three concentrations of citric acid had similar values for all the parameters, and they only decreased the values of ${\mathrm{ET}}_0$/${\mathrm{CS}}_0$, ${\mathrm{RC/CS}}_0$, ${\mathrm{ET}}_0$/ABS, and ${\mathrm{RE}}_0$/ABS in P. chekiangensis. However, its effects on C. sclerophylla are complex. These parameters were more sensitive to 1 mM citric acid. ${\mathrm{TR}}_0$/${\mathrm{CS}}_0$, ${\mathrm{ET}}_0$/${\mathrm{CS}}_0$, ${\mathrm{RC/CS}}_0$, ${\mathrm{TR}}_0$/ABS, and ${\mathrm{RE}}_0$/ABS decreased significantly, and the ${\mathrm{DI}}_0$/ABS increased. Moreover, the absorption (${\mathrm{ABS/CS}}_0$) of 10 mM citric acid was significantly lower than that of the control.

Parameters Under CGA: CGA did not affect the fluorescence parameters of P. chekiangensis leaves. Only 1 mM CGA significantly increased ${\mathrm{ET}}_0$/${\mathrm{CS}}_0$ and ${\mathrm{DI}}_0$/${\mathrm{CS}}_0$, whereas 20 mM CGA significantly increased ${\mathrm{DI}}_0$/${\mathrm{CS}}_0$. Others did not show much difference from the CK. However, their effects on C. sclerophylla were different. The quantum yield and efficiency were significantly affected by CGA. ${\mathrm{TR}}_0$/ABS, ET0/ABS, and ${\mathrm{RE}}_0$/ABS were all reduced by the three concentrations of CGA, and 20 mM CGA significantly enhanced energy dissipation (${\mathrm{DI}}_0$/ABS). Meanwhile, the ${\mathrm{ET}}_0$/${\mathrm{CS}}_0$ of 10 mM and 20 mM CGA and ${\mathrm{RC/CS}}_0$ of 10 mM CGA were significantly reduced.

3.3. Physiological and Biochemical Parameters of Plant Leaves

The parameters (chlorophyll, Rubisco, POD, CAT, ROS, and MDA) reflect the biochemical status and activity of plants in terms of growth, development, and response to environmental stress. All these parameters were detected; however, only a limited amount of data exhibited significant differences from the control group (CK). In the present study, chlorophyll and Rubisco levels were not significantly different (

Table 1. Chlorophyll and Rubisco of P. chekiangensis and C. sclerophylla under four chemical stresses.

Stress Type	P. chekiangensis		C. sclerophylla
	Chlorophyll (pmol/g)	Rubisco (ng/g)	Chlorophyll (pmol/g)	Rubisco (ng/g)
CK	49.912 ± 4.671	43.290 ± 3.734	50.656 ± 3.584	46.202 ± 6.127
1 mM DBP	50.590 ± 4.744	46.044 ± 5.145	52.550 ± 4.992	48.506 ± 3.872
10 mM DBP	51.298 ± 4.941	46.202 ± 6.375	54.742 ± 5.912	48.134 ± 2.662
20 mM DBP	53.842 ± 6.269	48.034 ± 5.566	52.110 ± 5.879	50.232 ± 4.630
1 mM citric acid	54.516 ± 3.618	44.092 ± 2.027	53.138 ± 7.118	46.678 ± 5.560
10 mM citric acid	54.726 ± 5.312	46.034 ± 4.600	51.156 ± 6.019	47.876 ± 6.472
20 mM citric acid	51.778 ± 4.667	47.544 ± 5.928	52.124 ± 3.616	51.596 ± 3.717
1 mM PHBA	49.408 ± 4.124	45.162 ± 3.602	53.484 ± 7.746	49.036 ± 4.588
10 mM PHBA	47.118 ± 3.022	47.098 ± 5.227	50.220 ± 3.742	46.192 ± 6.794
20 mM PHBA	50.104 ± 4.489	47.586 ± 5.837	52.776 ± 4.624	46.332 ± 3.665
1 mM CGA	48.788 ± 4.229	45.262 ± 6.570	53.626 ± 6.093	46.852 ± 1.975
10 mM CGA	53.426 ± 5.969	45.598 ± 4.998	55.242 ± 4.528	50.486 ± 3.693
20 mM CGA	54.174 ± 7.092	46.602 ± 1.958	55.190 ± 3.053	44.964 ± 3.712

Means ± SE (n = 15).

).

The data showing the levels of MDA, ROS, CAT, and POD in the leaves of P. chekiangensis are presented in

Table 2. MDA, ROS, CAT, and POD of leaves on P. chekiangensis.

Stress Type	MDA (ng/g)	ROS (ng/g)	CAT (nmol/g)	POD (ng/g)
CK	1.524 ± 0.053	242.724 ± 26.456	22.094 ± 1.432	16.916 ± 1.117
1 mM DBP	1.410 ± 0.082 *	239.118 ± 27.993	20.546 ± 1.881	16.356 ± 0.810
10 mM DBP	1.468 ± 0.100	242.262 ± 18.080	21.182 ± 2.230	16.908 ± 2.097
20 mM DBP	1.494 ± 0.121	250.220 ± 13.685	21.668 ± 1.260	16.744 ± 1.298
1 mM citric acid	1.460 ± 0.155	243.928 ± 9.382	19.436 ± 1.038 *	16.332 ± 1.273
10 mM citric acid	1.604 ± 0.163	257.742 ± 23.693	22.212 ± 1.561	17.094 ± 0.839
20 mM citric acid	1.472 ± 0.127	248.862 ± 27.646	21.006 ± 2.213	16.300 ± 2.017
1 mM PHBA	1.448 ± 0.130	228.364 ± 12.940	19.812 ± 1.096 *	15.734 ± 1.910
10 mM PHBA	1.496 ± 0.151	239.698 ± 18.104	19.468 ± 1.796 *	15.668 ± 1.058
20 mM PHBA	1.506 ± 0.131	240.570 ± 29.859	19.716 ± 1.420 *	16.688 ± 0.684
1 mM CGA	1.386 ± 0.071 *	231.952 ± 19.996	20.274 ± 2.683	17.142 ± 1.181
10 mM CGA	1.492 ± 0.057	234.016 ± 20.644	20.772 ± 2.081	15.770 ± 1.133
20 mM CGA	1.510 ± 0.111	248.422 ± 29.578	20.478 ± 1.752	16.592 ± 1.991

Means ± SE (n = 15) in a column with * indicate significant differences from the control group (CK) were observed at a p-value of 0.05.

. With the exception of 10 mM citric acid, the data showed that MDA and CAT decreased under all four chemical stresses; only 1 mM DBP and 1 mM CGA showed a significant difference from CK for MDA, and 1 mM citric acid and PHBA showed significant differences in CAT activity. There was no significant variation in ROS content; however, ROS was reduced at low concentrations but increased at high concentrations of DBP and CGA. The amount of ROS in the leaves was increased by citric acid and decreased by PHBA within the experimental concentration range. The POD of the leaves did not vary noticeably after treatment with the four chemicals.

Data on the levels of MDA, ROS, CAT, and POD in C. sclerophylla leaves are presented in

Table 3. MDA, ROS, CAT, and POD of leaves on C. sclerophylla.

Stress Type	MDA (ng/g)	ROS (ng/g)	CAT (nmol/g)	POD (ng/g)
CK	1.388 ± 0.063	209.892 ± 10.144	19.110 ± 2.204	16.560 ± 1.251
1 mM DBP	1.478 ± 0.089	246.780 ± 17.433 *	21.434 ± 2.147	16.276 ± 0.912
10 mM DBP	1.556 ± 0.163	247.012 ± 28.245 *	20.796 ± 2.261	16.956 ± 1.423
20 mM DBP	1.456 ± 0.059	229.908 ± 24.519	20.016 ± 1.744	16.888 ± 0.945
1 mM citric acid	1.456 ± 0.132	247.768 ± 20.381 *	22.886 ± 1.812 *	17.634 ± 0.838
10 mM citric acid	1.502 ± 0.133	245.202 ± 29.219 *	20.954 ± 3.319	15.654 ± 2.126
20 mM citric acid	1.548 ± 0.067 *	242.654 ± 29.194 *	21.982 ± 2.546	16.008 ± 1.138
1 mM PHBA	1.466 ± 0.178	244.576 ± 21.448 *	22.406 ± 3.129	17.340 ± 1.086
10 mM PHBA	1.534 ± 0.103	240.260 ± 18.125 *	20.698 ± 2.146	16.794 ± 1.595
20 mM PHBA	1.506 ± 0.186	243.780 ± 19.293 *	21.472 ± 1.577	16.212 ± 1.226
1 mM CGA	1.534 ± 0.201 *	246.780 ± 17.433 *	20.576 ± 1.341	16.582 ± 1.764
10 mM CGA	1.564 ± 0.068 *	247.012 ± 28.245 *	23.156 ± 1.831 *	17.410 ± 1.822
20 mM CGA	1.516 ± 0.071 *	229.908 ± 24.519	20.638 ± 2.216	16.192 ± 2.392

Means ± SE (n = 15) in a column with * indicate significant differences from the control group (CK) were observed at a p-value of 0.05.

. POD levels did not change significantly in the leaves of C. sclerophylla under any of the stress scenarios at any concentration. Under DBP, citric acid, PHBA, and CGA conditions, MDA, the ROS, and CAT levels were increased. MDA was significantly increased by 20 mM DBP and CGA, whereas CAT was significantly increased by 1 mM citric acid and 10 mM CGA. ROS was highly sensitive to all four substances at different concentrations, with all values exceeding those of the control. However, no significant differences were observed between the 20 mM DBP and 20 mM CGA treatments.

3.4. Effects of DBP on P. chekiangensis Soil Microorganisms Including Bacteria and Fungi

Figure 4 shows the statistically analyzed phyla of fungi and bacteria with relative contents greater than 1%.

The results demonstrated that Ascomycota and Basidiomycota, two of the main phyla of fungi, accounted for more than 80% of the fungal species in soil samples. The relative abundance of Ascomycota increased significantly with increasing DBP concentration, which is well-known for its critical role in ecosystems as decomposers and symbionts [45]. The relative abundance of Basidiomycota decreased with increasing DBP concentrations; however, 1 mM DBP did not differ from CK. The relative abundances of the three phyla Zygomycota, Glomeromycota, and Chytridiomycota were much less abundant than Ascomycota and Basidiomycota. Following DBP treatment, the relative abundance of these three phyla significantly decreased.

The fungal genera that had an abundance greater than 1% during the experiment are depicted in Figure 5, where three genera (Hypocrea, Sistotrema, and Nectria) showed a substantial increase in abundance following the treatment, whereas the majority of the genera showed a significant decrease. Among these, Hypocrea, which had the highest average abundance, likely contributes significantly to nutrient cycling, plant health, and disease suppression.

The abundance of Proteobacteria (bacteria) significantly increased when the DBP concentration increased. In contrast, there was a decline in the abundance of several bacterial phyla, including Actinobacteria, Bacteroidetes, Chloroflexi, Planctomycetes, Acidobacteria, Verrucomicrobia, and Patescibacteria (Figure 4).

The relative abundances of bacterial genera that were greater than 1% and significantly different from CK are shown in Figure 6. Nine genera showed an increase in abundance following the treatment, whereas the majority showed a decrease in abundance. In contrast, the abundances of four genera (Burkholderia-Caballeronia-Paraburkholderia, Gluconacetobacter, Azotobacter, and Novosphingobium) increased.

4. Discussion

4.1. Characteristics of Potential Allelochemiclas Released from Moso Bamboo

We investigated the chemical composition of fresh leaves and litter, which correspond to the compounds released from moso bamboo by rain leaching and litter decomposition, respectively. We identified seven substances that may affect other plants via allelopathy. In moso bamboo, DBP may be the primary allelochemical that is less influenced by its surroundings. All the experimental samples had high concentrations and showed little variation in fresh leaves and litter. Previous studies have also mentioned DBP as an allelochemical found in leaves, stems [46], rhizospheric soil [25], and decomposed cotton stalks [47].

The soil environment is thought to influence the release of citric acid, as evidenced by the wide variations in the relative concentrations of the compounds in the samples from different places. Studies have shown that the application of citric acid can lead to significant increases in various phosphorus fractions in the soil, including inorganic phosphorus and phosphorus associated with iron and aluminum [48]. reported a correlation between soil phosphorus (P) levels and citric acid emissions. The mechanisms by which citric acid enhances phosphorus availability include the dissolution of sparingly soluble phosphorus minerals and the alteration of soil pH, which can influence the solubility of phosphorus compounds [49]. Furthermore, we discovered that the new leaves had higher concentrations of citric acid, indicating that once the leaves wither, citric acid is broken down or transformed into other materials in the environment.

It is frequently believed that PHBA, a common allelochemical, causes problems with continuous cropping obstacles [50,51], which are also typical in cultivated forests, particularly in litter and roots [52]. PHBA concentrations were directly associated with the sampling site, whereas samples from the same area had almost equal concentrations. Similarly, Huang [30] discovered that the three main phenolic compounds (p-hydroxybenzoic acid, p-hydroxybenzaldehyde, and ethyl p-hydroxybenzoate) varied and that each compound’s quality was dynamic at distinct developmental stages in his investigation of phenolic allelochemicals from Sorghum halepense. P-hydroxybenzoic acid was the only phenolic component found during the seedling stage.

QC and caffeic acid levels did not exhibit any specific patterns in this experiment. Sinapic acid and CGA are secondary metabolites stimulated and generated in fresh leaves under specific conditions. When the leaves turn brown, they are consumed. While some allelopathy is mentioned for each of these, none is a major contributing factor.

4.2. Mechanisms of Allelopathy of DBP

We confirmed that DBP had a significant effect on PSII Chl a fluorescence at three different doses. Specifically, the electron transport network of the test plants was the most affected by 20 mM DBP. DBP also caused closure of part of the reactive center, a decline in the energy trap, blocked electron transport, and increased heat dissipation. However, the effect of each RC on electron transit was negligible except for 20 mM DBP × C. sclerophylla. Meanwhile, DBP increased the contents of chlorophyll and Rubisco in the two plants.

We assumed that the increased chlorophyll and Rubisco production was a result of the energy block, which encouraged plants to enhance the absorption of light energy and use ${\mathrm{CO}}_2$ more efficiently. Studies [53] have shown a strong correlation between Chlorophyll and Rubisco content. Rubisco, a key enzyme in the Calvin cycle, plays a crucial role in fixing ${\mathrm{CO}}_2$ during photosynthesis, and its content is closely linked to the absorption of light energy by chlorophyll. The treatment of eggplant (Solanum melongena) seedlings with DBP revealed that chlorophyll content may be related to DBP concentration. 0.05 mM DBP significantly increased chlorophyll content, 0.1 and 0.5 mM DBP had no effect on chlorophyll, and 1.0 and 4.0 mM significantly decreased chlorophyll content [54].

Furthermore, DBP caused ROS accumulation in C. sclerophylla leaves; however, the ROS-scavenging enzyme POD did not respond to this, despite the increase in CAT and MDA levels. However, it did not affect P. chekiangensis. Some studies have reported that different species of Brassica parachinensis respond differently to DBP exposure [55,56]. DBP caused ROS accumulation, and the activities of all antioxidative enzymes had significant alterations in barley plants [57].

Photosynthesis and oxidation are only a part of the way DBP affects plant growth and development, and its mechanism of action in plants is complex. Through proteomic analysis, Zhao [58] proposed that DBP is involved in cell wall biosynthesis and modification, photosynthesis and energy balance, antioxidation and detoxification capacity, and signal transduction.

In addition to its effects on photosynthesis and leaf oxidative stress, DBP has a major impact on soil microorganisms. Ascomycota and Basidiomycota are crucial for soil health because of their roles in decomposition and nutrient cycling [59]. The increase in the relative abundance of Ascomycota and decrease in the relative abundance of Basidiomycota with increasing DBP concentrations suggests that DBP selectively influences fungal communities, possibly due to differences in tolerance or metabolic capacity to process or detoxify DBP among these phyla. This selective pressure can alter soil microbial dynamics, potentially affecting the soil structure and nutrient availability [60]. For instance, Ascomycota genera such as Hypocrea, known for their contribution to nutrient cycling and plant health [49] and roles in suppressing plant diseases [61], showed increased abundance following DBP treatment, which could influence soil health and productivity and affect plant growth and ecosystem services [62].

The influence of DBP on soil bacterial communities is complex and varies significantly across phyla. The observed increase in Proteobacteria abundance with increasing DBP concentration suggests that this phylum may possess members with metabolic capability to tolerate or even degrade DBP [63]. This phylum includes various beneficial bacteria that play crucial roles in nitrogen recycling and plant growth [64], suggesting that DBP might selectively favor certain microbial processes that are beneficial for plant growth under specific conditions. Conversely, a decline in the abundance of other phyla, including Actinobacteria, Bacteroidetes, Chloroflexi, Planctomycetes, Acidobacteria, Verrucomicrobia, and Patescibacteria, indicates a potential disruption in the microbial equilibrium essential for maintaining soil health and function [65].

The observed increase in the abundance of Burkholderia-Caballeronia-Paraburkholderia, Gluconacetobacter, Azotobacter, and Novosphingobium in response to DBP treatment was noteworthy. These genera are known for their roles in promoting plant growth, enhancing nutrient uptake, and suppressing pathogens, suggesting that they may be key players in mitigating the negative effects of DBP on soil and plant health [66,67,68,69]. This increase might indicate an adaptive response of the soil microbiome to mitigate DBP stress, potentially through the biodegradation of DBP to compensate for the altered microbial community structure. Similarly, Lin [70] indicated that Alsobacter, Lacibacter, Myceligenerans, Schrenkiella parvula, and Undibacterium were responsible for DBP dissipation. Wang [25] also confirmed that DBP, as an autotoxic allelochemical from Atractylodes lancea, affects biochemical properties, microbial communities, and overall soil health.

4.3. Mechanisms of Allelopathy of PHBA

P. chekiangensis and C. sclerophylla responded differently to PSII Chl a fluorescence under pressure from PHBA.

In P. chekiangensis, the fluorescence intensity dropped after 0.3 ms. This was associated with a significant decrease in trapped energy fluxes, electron transport fluxes, and reactive centers and increased heat dissipation, whereas the absorption fluxes per CS were unaffected. This reduces the maximum quantum yield, which corresponds to an increase in the quantum yield of energy dissipation (such as heat and fluorescence) and a decrease in the quantum yield of electron transport in the PSII antenna. Although Rubisco was greater, both chlorophyll and Rubisco did not differ substantially from that of the control. Liang [71] found that PHBA significantly inhibited the photosynthesis of poplar (Populus × euramericana), as shown by a clear decline in the net photosynthetic rate, indicating the limitation responsible for photosynthesis reduction.

In addition, ROS levels were marginally lower and CAT activity was dramatically reduced compared with those in CK, whereas MDA and POD remained the same. Similarly, Huang [50] reported that PHBA suppressed root growth in Cucumis sativus by reducing ROS accumulation in the root tips. However, the expression levels of several ROS scavenging-related genes, including POD and CAT, increased. These changes indicate that although plants adopt certain defense mechanisms to mitigate oxidative damage under stress conditions, their defense capacity is compromised, especially in terms of CAT activity, revealing the adaptive strategies and survival challenges faced by plants under environmental stress.

These effects appear to differ among C. sclerophylla. Compared with CK, Chl a fluorescence intensity increased over three seconds. In C. sclerophylla leaves, PHBA significantly increased the dissipated energy flux per CS and reduced the quantum yield of electron transport from QA to the PQ pool and PSI final electron acceptor. Notably, 1 mM PHBA resulted in an increase in chlorophyll and Rubisco content, but this increase was not statistically significant. Same as Ahrabi’s results [29], the chlorophyll content of canola (Talaieh cultivar) was not affected at low concentrations (0.05 and 0.5 mM PHBA), but significantly decreased with an increase in PHBA concentration. However, PHBA caused a significant decrease in chlorophyll a in Microcystis aeruginosa [72].

In our study, PHBA stress significantly increased ROS content in C. sclerophylla leaves, resulting in increased MDA and CAT levels. In Microcystis aeruginosa, PHBA increases the amount of superoxide anion radical (${\mathrm{O}}_2$) and the electrical conductivity [72]. The findings of Liang [51] lend credence to this conclusion. When Solanum lycopersicum was treated with PHBA, there was a noticeable difference in the expression of genes linked to POD, SOD, and CAT. This suggests that this treatment alters the ROS metabolism. Guan [73] proposed that both NO and ${\mathrm{H}}_2$${\mathrm{O}}_2$ are important signals that mediate Arabidopsis response to the PHBA, where during this process ${\mathrm{H}}_2$${\mathrm{O}}_2$ may work upstream of the NO signal.

4.4. Mechanisms of Allelopathy of Citric Acid

Citric acid can affect cellular metabolism when applied externally as a tricarboxylic acid cycle intermediary. This might influence the pH and ionic balance within the chloroplast stroma or cytosol, affecting the enzyme activities crucial for photosynthesis [74]. Research [75] indicates that citric acid as an allelochemical can negatively affect the germination of species such as Medicago sativa. In addition, a study by Zhu et al. [76] evaluated citric acid in melon (Cucumis melo) seeds and seedlings, confirming that citric acid adversely affects seed germination and early growth stages. In our study, citric acid on P. chekiangensis caused the OJIP curve to decrease from J to P, and the significant decrease in ${\mathrm{RE}}_0$/ABS, ${\mathrm{ET}}_0$/ABS, ${\mathrm{TR}}_0$/${\mathrm{CS}}_0$, ${\mathrm{ET}}_0$/${\mathrm{CS}}_0$, and ${\mathrm{RC/CS}}_0$ indicated that the electron flow within PSII or from PSII to PSI was hindered and some reaction centers were closed. In C. sclerophylla, Chl a fluorescence intensity decreased for three seconds in 1mM and 10 mM citric acid. In addition, 1 mM citric acid significantly affected the fluorescence parameters of ${\mathrm{CS}}_0$ involved. The effect of citric acid on C. sclerophylla appeared to be closely related to its concentration.

Presumably, citric acid alters the redox state of the plastoquinone pool or affects the stability and function of the cytochrome ${\mathrm{b}}_6$f complex, resulting in reduced electron transport and energy conversion efficiencies [77]. The slight increase in chlorophyll and Rubisco content under citric acid treatment could be a compensatory response to stress, and plants might upregulate the synthesis of these molecules to increase their capacity for ${\mathrm{CO}}_2$ fixation and light absorption, attempting to offset the reduced photosynthetic efficiency.

In our study, CAT activity was significantly decreased in P. chekiangensis but significantly increased in C. sclerophylla after exposure to 1 mM citric acid. The ROS levels in C. sclerophylla increased significantly.

Several studies have suggested that citric acid plays a significant role in alleviating plant stress by enhancing antioxidant enzyme activity, increasing the chlorophyll content, and potentially facilitating plant growth under stressful conditions. Jin et al. [78] reported that organic acids, including citric acid, stimulated the antioxidant system and promoted quinoa (Chenopodium quinoa) photosynthesis, further promoting quinoa growth. Sunflowers (Helianthus annuus) can potentially remediate Cr contamination in soil and water through chelation with citric acid, enhancing plant growth, biomass, photosynthesis, and reducing oxidative stress [79]. Citric acid application improves crop growth and yield under various abiotic stress conditions, particularly by promoting heavy metal stress relief through increasing photosynthetic rates, reducing reactive oxygen species, and improving osmoregulation [80]. Exogenous citric acid application improves heat stress tolerance in tall fescue (Lolium arundinaceum) by decreasing electrolyte leakage and MDA content and promoting plant growth, chlorophyll content, and antioxidant enzyme activities [81].

4.5. Mechanisms of Allelopathy of CGA

Compared with the other treatments, CGA had a smaller effect on chlorophyll fluorescence. Especially for P. chekiangensis, 1 mM CGA showed a promoting effect, such as increasing the electron transport flux per CS and reducing the accumulation of ROS, MDA, and CAT. The above results indicate that CGA did not produce stress on P. chekiangensis but rather helped the growth of the plant. Furthermore, in C. sclerophylla, CGA reduced the maximum quantum yield and quantum yield of electron transport from QA– to the PQ pool and PSI final electron acceptor. MDA was significantly increased by CGA; correspondingly, ROS and CAT levels in the leaves also increased to varying degrees. Within the experimental concentration range, CGA burdened the C. sclerophylla. In particular, MDA, an indicator of lipid peroxidation and cellular damage, significantly increased, accompanied by a large accumulation of ROS after treatment. This may be because CGA has the potential to enhance the permeability of the outer membranes [82,83].

The contrasting outcomes observed in the two plants provide evidence for the distinct allelopathic effects of CGA on plants. Wang [44] suggested that this may be related to the CGA concentration used. Low concentrations of CGA promoted the growth of lettuce root tip cells, whereas high concentrations killed the root tip cells. D’Orso [84] indicated that CGA is the predominant phenolic component found in olanaceous plants and exhibits notable protective characteristics, including antibacterial and antioxidant capabilities. These traits hold special significance in situations in which plants are subjected to unfavorable conditions such as pathogen invasion, excessive light exposure, or harsh temperatures that induce oxidative stress. Furthermore, the release of CGA may function as a chemical defense mechanism against insect herbivores in plants. This is supported by evidence demonstrating that CGA is an effective defensive compound against a wide array of insect herbivores [85].

5. Conclusions

We investigated the chemical composition of fresh leaves and litter, which corresponded to the compounds released from moso bamboo by rain leaching and litter decomposition, respectively. Seven substances that might affect other plants through allelopathy were identified. Of these, four were selected for functional validation.

In moso bamboo, DBP may be the primary allelochemical, which is less influenced by its environment. PHBA was associated with the sampling site and had similar contents in the fresh leaves and litter. Citric acid content may be correlated with soil phosphorus content. CGA is stimulated and generated in fresh leaves under specific conditions.

Most of the four chemicals had significant negative effects but exhibited different modes of interference on P. chekiangensis and C. sclerophylla. DBP and citric acid negatively affected PSII Chl a fluorescence in both plants; however, PHBA and CGA had negative effects only on P. chekiangensis and C. sclerophylla, respectively. DBP, PHBA, and citric acid are typically thought to cause closure of part of the reactive center per CS, increased heat dissipation, decreased trapped energy, and blocked energy transmission. CGA had similar effects on C. sclerophylla. The major difference between P. chekiangensis and C. sclerophylla is that the four chemicals contributed to a significant accumulation of ROS in the leaves of C. sclerophylla, resulting in increased MDA content and CAT activity to varying degrees, but no changes were observed in P. chekiangensis. Furthermore, DBP can significantly alter the abundance of various microorganisms, including fungi and bacteria, in soil associated with P. chekiangensis.

These results indicate that the allelochemicals of moso bamboo assist in competing with the surrounding plants. This information is valuable for studying both the invasion of moso bamboo and the renovation of moso bamboo forests.