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Article

Alleviating Continuous Cropping Obstacles in Celery Using Engineered Biochar: Insights into Chemical and Microbiological Aspects

by
Chia-Chia Lin
1,
Ya-Hui Chuang
1,
Fo-Ting Shen
1,
Wen-Hsin Chung
2,3,
Chi-Yu Chen
2,
Yu-Ting Liu
1,3,
Yi-Cheng Hsieh
4,
Yu-Min Tzou
1,3,* and
Shih-Hao Jien
1,*
1
Department of Soil and Environmental Sciences, National Chung Hsing University, 145 Xingda Rd., Taichung 402204, Taiwan
2
Department of Plant Pathology, National Chung Hsing University, 145 Xingda Rd., Taichung 402204, Taiwan
3
Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, 145 Xingda Rd., Taichung 402204, Taiwan
4
Office of the Texas State Chemist, Texas A&M AgriLife Research, Texas A&M University System, College Station, TX 77843, USA
*
Authors to whom correspondence should be addressed.
Agronomy 2024, 14(11), 2685; https://doi.org/10.3390/agronomy14112685
Submission received: 23 October 2024 / Revised: 9 November 2024 / Accepted: 11 November 2024 / Published: 14 November 2024
(This article belongs to the Section Soil and Plant Nutrition)
Browse Figures
Figure 1
<p>Changes in soil phenolic acid concentrations following the addition of 0% (N), 0.2% (BS2), 0.4% (BS4), or 0.8% (BS8) (<span class="html-italic">w</span>/<span class="html-italic">w</span>) WP400 biochar. * Indicates significant differences in the LSD test (<span class="html-italic">p</span> &lt; 0.05) between treatments of the first crop. ☆: &lt;limit of quantification. HYD: 4-hydroxybenzoic acid; VAN: vanillic acid; COU: p-coumaric acid; FER: ferulic acid.</p> "> Figure 2
<p>Changes in average well color development (AWCD) for the (<b>a</b>) first crop and (<b>b</b>) second crop over a 24 to 120 h period following the addition of 0% (N), 0.2% (BS2), 0.4% (BS4), or 0.8% (BS8) (<span class="html-italic">w</span>/<span class="html-italic">w</span>) WP400 biochar. Means with the same letter for a given factor do not significantly differ at <span class="html-italic">p</span> &lt; 0.05 (LSD test). The inserted figures represent the AWCD at 120 h reaction times.</p> "> Figure 3
<p>Utilization of different carbon source categories (C: carbohydrates; C&amp;K: carboxylic and ketonic acids; P: polymers; A: amino acids; AA: amines/amides) by soil bacteria during the (<b>a</b>) first crop and (<b>b</b>) second crop following the addition of 0% (N), 0.2% (BS2), 0.4% (BS4), or 0.8% (BS8) (<span class="html-italic">w</span>/<span class="html-italic">w</span>) WP400 biochar. * Indicates a significant difference in the LSD test (<span class="html-italic">p</span> &lt; 0.05).</p> ">
Versions Notes

Abstract

:
In the pursuit of environmental sustainability and food security, biochar has emerged as a promising soil conditioner to mitigate continuous cropping obstacles (CCOs). This study explored the use of engineered biochar (WP400) with high adsorption capacity for phenolic acids in celery cultivation. Using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) for both target and suspect analyses, along with Biolog EcoPlate™ to track the functional diversity of soil bacteria, the study examined chemical and microbiological interactions at varying WP400 application rates. WP400 enhanced celery growth, reduced disease severity, and adsorbed p-coumaric acid (COU), a potential autotoxin. Additionally, other potential allelochemicals, predominantly fatty acid-related, were identified, suggesting a broader role for fatty acids in allelopathy. WP400 also influenced soil bacterial carbon utilization and altered microbial communities. However, higher WP400 doses (0.8% w/w) may not be beneficial for celery growth and reduced bacterial metabolic potential, indicating limitations to its effectiveness. Proper application of WP400 provides a sustainable solution for alleviating continuous cropping issues, promoting both environmental sustainability and agricultural development.

1. Introduction

Continuous cropping challenges are prevalent across various agricultural ecosystems. As noted by Cesarano et al. (2017) [1], approximately 111 crop species from 41 families are impacted by these issues. Key crops like rice, corn, sugarcane, and soybean experience problems associated with continuous cropping [2]. For example, soybean yields in China’s Heilongjiang region have decreased by 15–25% due to monoculture practices [3]. Horticultural crops such as strawberries, tomatoes, cucumbers, lettuce, and asparagus also encounter difficulties related to continuous cropping [4,5]. Furthermore, certain fruit trees, including pears and peaches, face these challenges globally, resulting in significant economic losses. Reports indicated that continuous cropping has led to fruit tree production losses of around $100,000 per hectare over ten years in Washington State, USA [6].
Current theories regarding the causes of continuous cropping problems include nutrient imbalances due to plant–soil feedback, increases in pathogen or pest populations, and the release of phytotoxic or autotoxic compounds by plants [1]. Other contributing factors may include soil degradation, reduced biodiversity, and declines in beneficial microorganisms. After examining evidence from agricultural and natural ecosystems, Cesarano et al. (2017) [1] proposed that nutrient imbalances are unlikely to be the sole cause of crop rotation obstacles, and neither pathogenic nor autotoxicity alone can fully explain the problems related to continuous cropping.
Plant metabolites are mainly released through root exudates or the decomposition of plant residues in the soil [5]. These chemicals can directly or indirectly influence other plants or soil microorganisms, either positively or negatively, a process known as allelopathy. The chemicals involved, called allelochemicals [7], can significantly impact the growth of subsequent plant generation. Autotoxicity occurs when allelochemicals produced by a plant negatively affect the growth of the same species; these chemicals are known as autotoxins [8]. A variety of substances can cause autotoxicity, with phenolic acids being the most commonly recognized allelochemicals and often identified as phytotoxic [7,9]. Other compounds, including water-soluble organic acids, linear alcohols, aliphatic aldehydes, phenols, coumarins, flavonoids, tannins, alkaloids, steroids, long-chain fatty acids, purines, and nucleosides, have also been reported as autotoxic substances [5,10].
In addition to autotoxins, many studies have documented changes in microbial populations under continuous cropping. These include decreases in microbial biomass [11], reductions in beneficial microorganisms [12,13,14], and increases in pathogenic microorganisms [15]. Research suggests that pathogenic microbial populations can become established soon after planting [16]. In cucumber crop rotation, Zhou and Wu (2012) [17] found that the population size of Fusarium was more closely linked to continuous cropping obstacles than overall fungal diversity. In peanut crop rotation, Chen et al. (2012) [18] observed that while fungal diversity increased, pathogen populations also rose, and beneficial microorganisms were selectively reduced. This reduction in beneficial diversity could impair plant resistance to pathogens [19]. Researchers believe that the release of allelopathic substances by plants significantly alters the microbial communities in the rhizosphere, contributing to continuous cropping issues [20,21]. For instance, phenolic acids are believed to affect microbial community structures due to their allelopathic effects. Bao et al. (2022) [20] observed an increase in fungal diversity when p-hydroxybenzoic, ferulic, syringic, and vanillic acid were added to the soil for Panax notoginseng cultivation. Bai et al. (2019) [22] suggested that the accumulation of phenolic acids could alter the soil bacterial community structure in tobacco cropping systems. Additionally, Chen et al. (2018) [23] found that vanillic acid increased the relative abundances of fungal genera in cucumber rhizosphere soil, including potential plant pathogens.
The causes of continuous cropping obstacles vary by crop type, the release of allelochemicals, shifts in microbiological communities, and overall soil health, which includes maintaining strong physiochemical and biological functions. Fusarium yellows, commonly seen in continuous celery cropping systems [24], may be caused by the release of phenolic acids such as gallic acid, p-coumaric acid, and ferulic acid into the soil. These acids can induce autotoxicity and/or promote the spore production and germination of the pathogen Fusarium oxysporum f. sp. Apii [25]. In previous research [26], engineered biochar, known for its high phenolic acid adsorption capacity, was used to amend the soil and mitigate continuous cropping challenges in celery. However, this study did not clearly establish changes in phenolic acids concentrations in the soil, biochar’s specific adsorption capacities for different phenolic acids, or whether reducing phenolic acid levels via biochar application affected soil microbial communities. Furthermore, it remains necessary to determine whether higher biochar doses could more effectively mitigate continuous cropping issues in celery. Therefore, this study hypothesizes that biochar will adsorb phenolic compounds released by celery, alter microbial community characteristics, and thereby improve celery’s continuous cropping obstacles. This study also tested different ratios of biochar as soil conditioners for potted celery plants, evaluating their effectiveness in alleviating these challenges. In addition, the content of phenolic compounds and identification of suspect compounds in soils were examined using a targeted and suspect analytical approach, respectively, via liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF/MS), as high-resolution mass spectrometry (HRMS) is commonly used in allelochemical analysis [27,28,29,30]. The metabolic potential and functional diversity of soil bacteria were also monitored using Biolog EcoPlate™. These results could enhance our understanding of the roles of phenolic compounds and microorganisms play in continuous celery cropping. Additionally, the findings may point to other potential allelochemicals for future research aimed at mitigating the allelopathic effects of continuous celery cropping.

2. Materials and Methods

2.1. Chemicals and Materials

For the analysis, standard phenolic acids were used: 4-hydroxybenzoic acid (HYD), p-coumaric acid (COU) and ferulic acid (FER) from Sigma-Aldrich (St. Louis, MO, USA), and vanillic acid (VAN) from ChromaDex (Los Angeles, CA, USA). These phenolic acids have been previously identified in celery extracts by Yao et al. (2010) [31], Sorour et al. (2015) [32], and Priecina et al. (2018) [33]. LC-MS grade acetonitrile and methanol were supplied by Merck KGaA (Darmstadt, Germany), and acetic acid by Honeywell. Oasis HLB SPE cartridges for solid phase extraction were from Waters Corporation (Milford, MA, USA). The biochar (WP400) was prepared by soaking wood meal in H3PO4 (1:1.5, w/w) and pyrolyzing at 400 °C.

2.2. Pot Experiment

The soils for the pot experiments were sourced from the experimental farm of National Chung Hsing University. The soil type was classified as Entisols with loam texture, pH 6.2, 2.3% organic matter (Corg × 1.724), 0.12% total nitrogen, 98 mg kg−1 available phosphorus, and 62 mg kg−1 potassium. Detailed information on the contents of other soil nutrients can be found in Table S1. Each pot, containing 300 g of soil, was planted with one celery seedling (2–3 leaves). To evaluate the effects of WP400 biochar (in powder form), the dosages (w/w) included: (1) no biochar (N), (2) 0.2% biochar (BS2), (3) 0.4% biochar (BS4), and (4) 0.8% biochar (BS8). Each treatment had 8 replicates in a completely randomized design, and plants were grown in a greenhouse.
The first celery crop was harvested 91 days after planting, with shoots and roots removed and weighed. After harvest, soil samples were air-dried, ground, and sieved (10-mesh) for the next planting cycle, with 250 g of soil per pot. The second crop was harvested 63 days after planting. During this period, celery plants were monitored for pathogens and disease severity, and soil samples were analyzed for phenolic acid content. Community-level physiological profiles were assessed using EcoPlates™. Before each transplanting, soils were treated with ammonium sulfate, potassium dihydrogen phosphate, and potassium chloride (N-P2O5-K2O: 50-60-50 mg/kg soil), with topdressing applied one month after planting (N-P2O5-K2O: 50-0-50 kg/ha).

2.3. Celery Pathogen Identification and Disease Severity

In some cases, celery grown under continuous cropping conditions exhibits symptoms of yellowing and wilting. After harvesting the second crop, stem base and leaf tissue samples were collected from all plants (8 replicates for each treatment) for pathogen isolation and identification [34], with further details provided in Supplementary Information (SI) Section S1.1. Disease severity in this experiment was measured using the method outlined by Nutter Forrest et al. (1991) [35], which quantifies the proportions of chlorotic leaf area on infected plants (Equation (1)). The mortality rate was determined by dividing the number of dead plants by the total number of plants, while disease incidence was calculated by dividing the number of infected plants by the total number of plants.
D i s e a s e   s e v e r i t y = c h l o r o t i c   l e a f   a r e a t o t a l   l e a f   a r e a × 100 %

2.4. Analysis of Adsorbed Phenolic Acids in Soil

Soils with four replicates from different treatments were randomly sampled for target phenolic acid analysis. After soil pore water removal (as described in Section 2.5), soils were freeze-dried and extracted using a modified QuEChERS method [36]. Briefly, 0.25 g of freeze-dried soil was placed in a centrifuge tube with ceramic homogenizers, followed by the addition of 1 mL Na2EDTA and shaking for 1 min. Then, 5 mL of ACN/MeOH (65/35, v/v) was added, shaken for 2 min, and salts (Na2SO4 and NaCl) were added to enhance extraction. After sonication and centrifugation, the supernatant was treated with C18 and Na2SO4, centrifuged again, filtered, and stored at −20 °C for LC-QTOF/MS analysis. The extraction method was validated through the standard addition of 400 ng g−1 phenolic acids, with recoveries and stability provided in Table 1.
For quantifying target phenolic acids in soils, an Agilent 1200 series liquid chromatography (LC) system coupled with an Agilent 6530 QTOF/MS (LC-QTOF/MS) (Agilent Technologies, Santa Clara, CA, USA) was utilized in all ion fragmentation (AIF) acquisition mode with collision energies of 0, 20, and 40 eV (i.e., negative ionization). In the LC system, details of the separation column, binary mobile phase, gradient program, flow rate, and injection volume are in Table S2, while Table S3 provides settings for the 6530 QTOF/MS system, including the Agilent Jet Stream ion source. The qualification of four target phenolic acids followed a “Target/Suspect Screening” workflow, comparing MS spectra to a personal compound database and library using authentic reference standards via Agilent MassHunter Qualitative Analysis software (v10.0). Compounds were qualified by retention time and mass difference criteria (<5 ppm) [37], then quantified using Agilent MassHunter Quantitative Analysis software (v10.1) with a matrix-matched calibration curve [38].

2.5. Suspected Allelochemicals Exploration

Soil pore water and soil samples from the first and second crops under the N treatment (N1 and N2, respectively) were analyzed using LC-QTOF/MS through a suspect analytical approach. Each treatment had four replicates as same as in target phenolic acid analysis. Soil pore water was collected on the harvest day following Carter et al. (2014) [39], where soil samples (~27% water content) were centrifuged at 13,000× g for 30 min to separate pore water. The water was then concentrated using a solid-phase extraction (SPE) method modified by Chuang et al. (2019) [36]. HLB SPE cartridges were activated with methanol and DI water (pH 3), loaded with 14 mL of pore water, washed with DI water, and eluted with methanol. The elutes were stored at −20 °C for LC-QTOF/MS analysis of phenolic acids. Soil extraction followed the procedure described in Section 2.4.
In the suspect analytical approach using LC-QTOF/MS, all extracts (from soil pore water and soils) were initially analyzed in the AIF acquisition mode with 0 eV collision energy under both positive and negative ionization to capture potential precursors. Data were processed using the “Compound discovery” workflow and “Find by Molecular Feature” with Agilent MassHunter Qualitative Analysis (v10.0). Compounds from control (N1) and experiment (N2) were compared using Agilent Mass Profiler (v10.0), selecting those with signal values in N2 at least 4 times higher than N1 (occurrence ≥ 50% in one group). Pooled N2 samples were then analyzed in AutoMSMS mode with collision energies of 10, 20, and 40 eV to obtain MS/MS spectra. Selected compounds were matched to the Metlin PCDL for potential celery allelochemicals, with qualification based on accurate mass (<5 ppm), isotope abundance, and spacing [38]. Matched compounds were tentatively identified with level 2 confidence [37,40].

2.6. Community-Level Physiological Profiles (CLPP) Analysis

Post-harvest, a portion of the soil sampled was stored at 4 °C and analyzed within two days. Four replicates were randomly selected for each treatment. To assess bacteria potential and functional diversity, a slightly modified version of the method by Garland and Mills (1991) [41] was used, with further details provided in Section S1.2 of the SI. The Biolog EcoPlateTM contains 31 carbon sources, categorized into carbohydrates (C), polymers (P), carboxylic and ketonic acids (C&K), amino acids (A), and amines/amides (AA) [38], as outlined in Table S4. The following metrics were calculated after a 120 h EcoPlateTM incubation: average well color development (AWCD), Shannon diversity index (H), richness (S), and Shannon evenness (E), using the method proposed by Gryta et al. (2014) [42].

2.7. Statistical Analysis

Statistical analyses were conducted on the collected data to assess the significance of the results. A one-way analysis of variance (ANOVA) was performed, followed by multiple comparisons using the least significant difference (LSD) method. All statistical procedures were executed using SPSS version 20, with statistical significance set at a threshold of p < 0.05.

3. Results

3.1. The Impact of Different Biochar Application Rates on Celery Growth

None of the celery plants exhibited disease symptoms in the first crop cycle. Table 2 presents the plant characteristics at the time of harvest. Although plant height showed no significant differences among the treatments, the shoot dry weight in the BS2, BS4, and BS8 treatments was significantly greater than in the control (N) treatment. For root dry weight, the BS4 treatment had the highest values, considerably exceeding the control, while the BS8 treatment had the lowest values (Table 2). In the second crop cycle, some plants developed yellowing leaves, and instances of whole-plant wilting were observed in the N, BS4, and BS8 treatments before harvest. Fusarium oxysporum was identified as the pathogen causing chlorosis and wilting. Table 3 outlines the disease incidence, mortality rate, and disease severity for each treatment. The control group (N), without WP400 biochar, exhibited a 50% disease incidence and a 25% mortality rate. The 0.2% and 0.4% WP400 biochar treatments had lower disease incidences of 13% and 25%, respectively, with mortality rates of 0% and 13%. The BS8 treatment had the highest disease incidence at 63%, but its mortality rate was similar to that of the control, at 25%. Disease severity was most pronounced in the N and BS8 groups, with values of 33% and 37%, respectively.

3.2. Changes in Phenolic Acids in Soil Grown with Celery

To accurately quantify the concentration of target phenolic acids in soils from the different treatments, this study utilized a modified QuEChERS extraction method combined with LC-QTOF/MS analysis, which demonstrated both high accuracy and efficiency. By leveraging the accurate mass measurements provided by LC-QTOF/MS, the qualification criteria—accurate m/z for precursor ions and at least one product ion (as listed in Table 4)—ensured the reliable detection of target phenolic acids in complex soil matrices. As shown in Table 1, the recoveries for HYD, VAN, COU, and FER from soil samples ranged from 76% to 103%, with relative standard deviations (RSDs) between 5% and 20%. These recoveries and standard deviations meet the criteria set by the EU guidelines for multiple pesticide residue analyses in various foods and feeds, which require recovery rates between 70% and 120% and RSDs below 20% [37]. This confirms the suitability of the analytical methodology for detecting phenolic acids in soil samples.
Applying this method in the pot experiment revealed no accumulation trend for HYD and VAN in the soil (Figure 1). FER was detected only in the 0.8% WP400 biochar treatment group during the second crop cycle. Interestingly, COU was detected across all treatments and exhibited an accumulation trend under continuous cropping conditions. The average concentration of COU in the control group (N) increased from 40.7 μg kg−1 to 55.4 μg kg−1 between the first and second crops. Similarly, biochar-treated groups (BS2 to BS8) showed higher concentrations of COU during the second crop. Notably, the BS4 treatment demonstrated a significant increase in COU concentration, from 20.0 μg kg−1 to 41.9 μg kg−1. The difference in COU concentration between the first and second crops was more pronounced in the BS4 treatment compared to the control, suggesting that WP400 biochar may enhance the accumulation of COU in the soil.

3.3. Suspected Allelochemicals Exploration

Although the celery in the experiment exhibited continuous cropping obstacles (Table 2), the soil samples did not show a noticeable accumulation of target phenolic acids (Figure 1). As a result, further analysis of target phenolic acids was conducted in soil pore water, since mass flow is a key factor in introducing xenobiotics into plants [43,44]. It was hypothesized that phenolic acids might be more likely to distribute in soil pore water rather than accumulate in the soil itself. However, results revealed that only trace amounts of HYD, COU, VAN, and FER (less than 2.0 μg L−1) were detected in soil pore water under continuous cropping conditions. Given that plants release a wide variety of metabolites, beyond just the target phenolic acids [45], this study utilized LC-QTOF/MS for suspect analysis, paired with the Metlin database (https://metlin.scripps.edu/landing_page.php?pgcontent=mainPage, accessed on 25 December 2023), to explore the presence of other plant metabolites in both soil pore water and soil samples. Interestingly, a comparative analysis revealed a significant accumulation of several suspicious compounds in both soil pore water and soils. These compounds include ethyl 3-hydroxybutyrate, 2-octanoic acid, myristic acid ethyl ester, 9-HODE, 5-oxo-ETE, phytosphingosine, 2-linoleoyl glycerol, and 5′-deoxyadenosine (Table 5). These compounds were classified as level 2 of identification confidence based on the criteria outlined by Schymanski et al. (2014) [40] and Pihlström et al. (2017) [37].

3.4. CLPP Analysis

The metabolic potential of bacteria was quantified using average well-color development (AWCD), with microbial growth trends assessed by monitoring daily changes in AWCD. In the first crop cycle, bacterial metabolic potential was generally similar across the different treatments, as indicated by AWCD results (Figure 2a). However, the BS8 treatment exhibited a significantly lower AWCD at 120 h compared to the BS2 treatment. Figure 2b shows the AWCD changes for the second crop cycle, indicating comparable bacterial metabolic potential across all treatments. At 120 h, no significant differences in AWCD were observed between treatments. In the first crop cycle, no significant differences were found in the Shannon indices for diversity (H), evenness (E), and richness (S) across the treatments (Table S5). However, in the second crop, the BS8 treatment showed higher evenness (E) in carbon source utilization compared to the BS2 and BS4 treatments, although there were no significant differences in diversity (H) and richness (S) among the treatments.
Regarding the utilization of different carbon sources, results from the first crop cycle showed that the application of WP400 biochar significantly reduced the bacterial community’s potential to utilize amines/amides (AA) (Figure 3a). No significant differences were observed in the utilization of other carbon source categories. In the second crop, results indicated that there were no significant differences in carbon source utilization among treatments, regardless of biochar application. However, lower AA utilization was still observed in the BS2 and BS4 treatments (Figure 3b).

4. Discussion

4.1. The Impact of Different Biochar Application Rates on Celery Growth

The results from the first crop demonstrate that the application of WP400 biochar did not significantly affect celery plant height, but it did result in a notable increase in aboveground dry weight. Among the different application rates (BS2 to BS8), the BS4 treatment proved to be the most effective. Similarly, for root dry weight, the BS4 treatment yielded the highest values, followed by BS2. However, at the highest application rate of 0.8% (BS8), the average root dry weight was lower than BS4, suggesting that excessive biochar application may not be beneficial for celery root growth. In the second crop, both the N and BS8 treatments showed relatively higher disease incidence, mortality rates, and disease severity, with the BS8 treatment exhibiting the highest values (Table 3). This suggests that higher WP400 biochar application rates are not favorable for consecutive celery cropping, as they may contribute to increased disease susceptibility and reduced plant performance.

4.2. Phenolic Acids Accumulation in Celery-Planted Soil

Substances such as ferulic acid (FER), p-coumaric acid (COU), vanillic acid (VAN), 4-hydroxybenzoic acid (HYD), caffeic acid, protocatechuic acid, and syringic acid have been identified as potential phytotoxic agents. These compounds can impair plant growth by reducing water transport and nutrient absorption by roots, decreasing photosynthesis, increasing levels of abscisic acid (ABA), and reducing leaf expansion rates [7,9,46,47,48,49]. Among the phenolic acids measured in this study, COU was the only one that showed an accumulation trend under continuous cropping, suggesting that COU may be the primary allelochemical secreted by celery, contributing to autotoxicity.
From the different treatment groups, the WP400-treated group showed a significantly higher accumulation of COU compared to the control group (N), indicating that WP400 influenced the adsorption and retention of COU in the soil. FER was only detected during the second crop at the highest application rate (0.8%), suggesting that a larger amount of WP400 is required to accumulate FER to a detectable level. Both COU and FER, identified as phenolic acids with the highest adsorption capacity in the WP400 adsorption test (described in SI Section S1.3 and Figure S1), are also major phenolic compounds in celery [34,50,51,52].
Dalton (1989) [53] proposed that phenolic acids, when reversibly adsorbed by soils, might accumulate to concentrations that could cause allelopathy, as they are protected from microbial decomposition. However, experiments by Blum (1998) [54] demonstrated that microorganisms utilize reversibly adsorbed phenolic acids almost as quickly as free phenolic acids in solution, with only a slight delay. Blum suggested that once free phenolic acids in the soil solution were depleted, the reversibly adsorbed acids would be rapidly released and consumed by microorganisms, preventing significant accumulation. In our experiment, the concentrations of HYD and VAN were lower during the second crop, indicating that these phenolic acids did not accumulate in the soil. In contrast, COU displayed a trend of accumulation, suggesting that certain phenolic acids may reach higher concentrations, affecting soil microbial communities and potentially leading to allelopathic effects. This observation aligns with the findings by Bai et al. (2019) [22]. However, the addition of WP400, which exhibited a strong affinity for COU, may have reduced the release of absorbed COU, potentially decreasing its allelopathic effect on celery. This suggests that WP400 biochar could play a role in mitigating the negative impacts of phenolic acids in continuous cropping systems.

4.3. Phenolic Acids in the Soil Solution and Nontargeted Allelochemicals Exploration

The results of the soil pore water analysis suggest that biochar could efficiently adsorb phenolic acids from the soil solution, or that rhizosphere microorganisms rapidly immobilize these compounds, thereby reducing the risk of phytotoxic effects [55]. This indicates that biochar, along with microbial transformation and utilization, plays a crucial role in influencing phenolic acid concentrations in the soil solution [55]. Furthermore, prior research has suggested that phenolic acid concentrations in the range of 10−5 to 10−4 M may cause autotoxicity in plants [56]. However, given the extremely low concentrations of phenolic acids detected in the soil solution, it is unlikely that these levels significantly contribute to the negative effects observed in continuous celery cropping. Additionally, although phenolic acids may cause temporary physiological toxicity in plants, most adverse effects tend to subside once phenolic acids in the rhizosphere are depleted [57].
Allelochemicals are often not isolated compounds but rather mixtures, and their autotoxic effects frequently result from synergistic or additive interactions among multiple compounds [45]. This suggests that other allelopathic compounds, beyond phenolic acids, may be present in continuous cropping systems. Through mass spectrometry (MS) analysis and the use of the Metlin database, several suspected allelopathic substances were identified, many of which were fatty acid-related compounds. This points to a significant role for fatty acids as allelopathic compounds in celery.
Alsaadawi et al. (1983) [58] were among the first to propose that fatty acids might function as allelochemicals in plants [59]. They demonstrated the phytotoxicity of several fatty acids—including myristic acid, palmitic acid, linolelaidic acid, oleic acid, and stearic acid—using GC-MS, showing that these compounds notably inhibited bermudagrass root growth. In this study, we identified myristic acid ethyl ester (tetradecanoic acid, ethyl ester), which has also been reported to be phytotoxic in previous studies [60]. Additionally, 9-HODE, a compound released by stressed tomatoes, acts as a signaling molecule to attract Trichoderma harzianum [61]. Although 2-Linoleoyl glycerol is not a fatty acid, it has been found to be phytotoxic and can lead to the accumulation of abscisic acid (ABA), jasmonic acid (JA), and salicylic acid (SA) [62]. To confirm whether these suspected compounds are indeed allelochemicals causing autotoxicity in celery under continuous cropping, further qualitative and quantitative analyses using standard substances, along with toxicity testing on celery and associated microbes, are necessary.

4.4. CLPP Analysis

The AWCD value is commonly used to assess the total metabolic potential of soil microbes [63]. In the first cropping experiment, the BS8 treatment displayed the lowest AWCD at 120 h, significantly lower than that of the BS2 treatment, suggesting that a higher application rate of WP400 biochar may reduce the metabolic potential of the bacterial community. Additionally, the application of WP400 biochar altered the utilization patterns of soil bacteria for amines/amides (AA), indicating that WP400 may influence the structure and function of the microbial community [64,65]. However, this effect was not apparent by the end of the second cropping cycle, implying that the impact of WP400 biochar may diminish over time and not persist into the later stages of the second crop.
In terms of functional diversity, there were no significant differences between treatments in either the first or second crops (Table S5). While EcoPlate™ primarily assesses the functional diversity of microorganisms, it can sometimes underestimate the taxonomic diversity but remains a valuable tool for estimating microbial diversity in soils [66]. Previous studies have underscored the crucial role of rhizosphere microorganisms in protecting plants from soil-borne pathogens [67,68,69,70]. For instance, Wei et al. (2015) [71] demonstrated that the ability of the plant pathogen Ralstonia solanacearum to invade the rhizosphere microbial community depended on competition for carbon sources. They suggested that microbial communities with more ecological niche overlap with pathogens were better able to suppress infections, indicating that a more diverse microbial community was more capable of resisting pathogen invasion [72,73]. Although our experiment did not reveal significant differences in the functional diversity of soil bacterial communities across treatments, the addition of WP400 biochar may still reduce the occurrence of celery yellow wilt disease. This could be due to mechanisms such as altering the microbial community composition or potentially reducing celery’s autotoxicity caused by allelochemicals.
Allelochemicals can have significant effects on both plants and microorganisms. Li et al. (2014) [74] analyzed the phenolic compounds secreted by peanuts and their impact on microbial communities, emphasizing that changes induced by phenolic acids played a pivotal role in continuous cropping obstacles. Similar findings have been reported in various studies, showing how phenolic acids can influence microbial communities [20,75,76]. In our study, continuous cropping of celery led to the accumulation of p-coumaric acid (COU), and the application of WP400 biochar appeared to increase COU adsorption in the soil. This adsorption may not only reduce celery’s autotoxicity but also alter the availability of carbon sources, thereby enhancing the rhizosphere environment for celery. These changes, including the presence of fatty acids, could potentially drive shifts in the microbial communities, leading to alterations in metabolic activities or species composition. These microbial community changes may have contributed to the reduction in disease incidence associated with continuous cropping of celery observed in this study.

5. Conclusions

The experimental results strongly suggest that the application of WP400 biochar to soils cultivated with celery holds significant potential. Soil analysis indicated that p-coumaric acid (COU) may be the primary phenolic acid allelochemical secreted by celery, and WP400 biochar enhances the adsorption of COU in the soil, reducing its availability. Furthermore, the findings suggest that under continuous cropping, celery may also accumulate certain fatty acid-related compounds. To our knowledge, this is the first report linking such compounds to continuous cropping challenges in celery. These compounds may synergize with phenolic acids, exerting allelopathic effects that influence celery growth and soil microbial communities.
Community-level physiological profile (CLPP) analysis revealed that the introduction of WP400 biochar significantly affected the metabolic potential of soil microbes, particularly for amines/amides (AA). These shifts likely led to changes in the microbial community structure, potentially playing a role in alleviating continuous cropping issues in celery when WP400 biochar was applied. However, it is important to note that higher doses of biochar, such as 0.8% w/w, may not be beneficial for celery growth. This highlights the critical need to carefully optimize the biochar application rate, as excessive amounts could counteract the benefits by impeding celery development.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy14112685/s1: Section 1.1: Celery pathogen identification; Section 1.2: Community-level physiological profiles (CLPP) analysis; Section 1.3: Adsorption of phenolic acids on WP400 biochar; Table S1: Nutrient content of experimental soil; Table S2: Agilent 1200 series liquid chromatography (LC) operating conditions; Table S3: Agilent 6530 quadrupole-time-of-flight mass spectrometry (QTOF/MS) operating parameters; Table S4: Carbon substrates individually utilized in the Biolog EcoPlateTM; Table S5: Shannon index diversity (H), richness (S), and Shannon evenness (E) for the first and second crop after 120 h of EcoPlateTM incubation; Figure S1: Adsorption of phenolic acids by WP400 biochar (HYD: 4-hydroxybenzoic acid, VAN: vanillic acid, FER: ferulic acid, COU: p-coumaric acid). Reference [34] is cited in the supplementary materials.

Author Contributions

Conceptualization, C.-C.L., Y.-H.C. and Y.-C.H.; methodology, C.-C.L., Y.-H.C., F.-T.S., W.-H.C., C.-Y.C. and Y.-T.L.; investigation, C.-C.L., Y.-H.C., F.-T.S., W.-H.C. and C.-Y.C.; formal analysis, C.-C.L. and S.-H.J.; writing—original draft, C.-C.L.; writing—review and editing, Y.-H.C., F.-T.S., W.-H.C., Y.-T.L., Y.-C.H., Y.-M.T. and S.-H.J.; supervision, Y.-M.T. and S.-H.J.; funding acquisition, Y.-M.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Ministry of Science and Technology, Republic of China (ROC) grant numbers 107-2321-B005-018, 108-2321-B-005-012, and 109-2327-B-005-002. This work is also financially supported by the “K. T. Li Foundation of Science and Technology” and “Innovation and Development Center of Sustainable Agriculture” from the Featured Areas Research Center Program within the framework of Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.

Data Availability Statement

The dataset is available on request from the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Agronomy 14 02685 g001
Figure 1. Changes in soil phenolic acid concentrations following the addition of 0% (N), 0.2% (BS2), 0.4% (BS4), or 0.8% (BS8) (w/w) WP400 biochar. * Indicates significant differences in the LSD test (p < 0.05) between treatments of the first crop. ☆: <limit of quantification. HYD: 4-hydroxybenzoic acid; VAN: vanillic acid; COU: p-coumaric acid; FER: ferulic acid.
Figure 1. Changes in soil phenolic acid concentrations following the addition of 0% (N), 0.2% (BS2), 0.4% (BS4), or 0.8% (BS8) (w/w) WP400 biochar. * Indicates significant differences in the LSD test (p < 0.05) between treatments of the first crop. ☆: <limit of quantification. HYD: 4-hydroxybenzoic acid; VAN: vanillic acid; COU: p-coumaric acid; FER: ferulic acid.
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Figure 2. Changes in average well color development (AWCD) for the (a) first crop and (b) second crop over a 24 to 120 h period following the addition of 0% (N), 0.2% (BS2), 0.4% (BS4), or 0.8% (BS8) (w/w) WP400 biochar. Means with the same letter for a given factor do not significantly differ at p < 0.05 (LSD test). The inserted figures represent the AWCD at 120 h reaction times.
Figure 2. Changes in average well color development (AWCD) for the (a) first crop and (b) second crop over a 24 to 120 h period following the addition of 0% (N), 0.2% (BS2), 0.4% (BS4), or 0.8% (BS8) (w/w) WP400 biochar. Means with the same letter for a given factor do not significantly differ at p < 0.05 (LSD test). The inserted figures represent the AWCD at 120 h reaction times.
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Figure 3. Utilization of different carbon source categories (C: carbohydrates; C&K: carboxylic and ketonic acids; P: polymers; A: amino acids; AA: amines/amides) by soil bacteria during the (a) first crop and (b) second crop following the addition of 0% (N), 0.2% (BS2), 0.4% (BS4), or 0.8% (BS8) (w/w) WP400 biochar. * Indicates a significant difference in the LSD test (p < 0.05).
Figure 3. Utilization of different carbon source categories (C: carbohydrates; C&K: carboxylic and ketonic acids; P: polymers; A: amino acids; AA: amines/amides) by soil bacteria during the (a) first crop and (b) second crop following the addition of 0% (N), 0.2% (BS2), 0.4% (BS4), or 0.8% (BS8) (w/w) WP400 biochar. * Indicates a significant difference in the LSD test (p < 0.05).
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Table 1. Recoveries and relative standard deviations (RSDs) of target phenolic acids from soils using the modified QuEChERS method.
Table 1. Recoveries and relative standard deviations (RSDs) of target phenolic acids from soils using the modified QuEChERS method.
Phenolic AcidsRecovery (%) 1RSDs (%) 2
4-hydroxybenzoic acid9019
Vanillic acid7611
p-coumaric acid10320
Ferulic acid855
1 Tested concentration was 400 ng g−1 through standard addition. 2 Triplicate.
Table 2. Plant characteristics of the first crop under different treatments.
Table 2. Plant characteristics of the first crop under different treatments.
Treatments 1
NBS2BS4BS8
Shoot height (cm)13.0 ± 0.9 a214.1 ± 1.1 a13.8 ± 1.4 a13.9 ± 0.9 a
Shoot dry weight (g)0.97 ± 0.20 c1.32 ± 0.10 b1.58 ± 0.18 a1.28 ± 0.12 b
Root dry weight (g)0.40 ± 0.15 b0.42 ± 0.13 ab0.58 ± 0.20 a0.27 ± 0.14 b
1 N (No WP400 Application), BS2 (Mixed with 0.2% w/w WP400), BS4 (Mixed with 0.4% w/w WP400), and BS8 (Mixed with 0.8% w/w WP400). 2 Means followed by different letters are significantly different according to the LSD test (p < 0.05).
Table 3. Disease incidence, mortality, and disease severity of second crop celery under various treatments.
Table 3. Disease incidence, mortality, and disease severity of second crop celery under various treatments.
Treatments 1
NBS2BS4BS8
Disease incidence (%)50132563
Mortality (%)2501325
Disease severity (%)33 ± 441 ± 321 ± 4037 ± 46
1 N (No WP400 Application), BS2 (Mixed with 0.2% w/w WP400), BS4 (Mixed with 0.4% w/w WP400), and BS8 (Mixed with 0.8% w/w WP400).
Table 4. Mass spectral information for the selected phenolic acids established in the PCDL for target analysis.
Table 4. Mass spectral information for the selected phenolic acids established in the PCDL for target analysis.
Compounds
(Molecular Formula)		Monoisotopic
Mass		[M-H] 1MS/MS
Fragments 2		RT 3
(min)
4-Hydroxybenzoic acid
(C7H6O3)		138.0317137.024493.0346, 65.0397, 75.0240, 41.0033, 39.02403.43
Vanillic acid
(C8H8O4)		168.0423167.0350108.0217, 152.0115, 123.0452, 91.0189, 80.02683.53
Cinnamic acid
(C9H8O2)		148.0524147.0452103.0553, 77.03976.07
p-Coumaric acid
(C9H8O3)		164.0473163.0401119.0502, 93.0346, 117.0346, 91.0553, 65.03973.88
Ferulic acid
(C10H10O4)		194.0579193.0506134.0373, 133.0295, 178.0272, 149.0608, 132.02174.07
1 for quantification. 2 Highlighted fragments were used for qualification. 3 Retention time.
Table 5. Tentatively identified allelochemicals direct from celery in both soil and soil pore water.
Table 5. Tentatively identified allelochemicals direct from celery in both soil and soil pore water.
Tentatively Identified Allelochemicalsm/zMS/MS
Fragments 1
Ethyl 3-hydroxybutyrate133.086241.0386, 43.0178, 45.0335, 69.0335, 73.0648
2-Octenoic acid143.106545.0335, 53.0386, 55.0178, 55.0542, 67.0542
Myristic Acid ethyl ester255.23383.0502, 44.9982, 115.0765, 207.1754, 209.1911
9-HODE297.241959.0139, 277.2173, 295.2279, 123.1179, 171.1027
5-Oxo-ETE319.225995.0855, 109.1012, 113. 0597, 115.0390, 301.2162
Phytosphingosine318.3014109.1012, 270.2791, 60.0444, 282.2791, 300.2897
2-Linoleoyl Glycerol355.285757.0699, 71.0855, 97.1012, 265.2526, 281.2475
5′-Deoxyadenosine395.2796136.0618, 45.0335, 92.0243, 94.0400, 119.0352
1 At least one fragment was used for qualification (mass error < 5 ppm).
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Lin, C.-C.; Chuang, Y.-H.; Shen, F.-T.; Chung, W.-H.; Chen, C.-Y.; Liu, Y.-T.; Hsieh, Y.-C.; Tzou, Y.-M.; Jien, S.-H. Alleviating Continuous Cropping Obstacles in Celery Using Engineered Biochar: Insights into Chemical and Microbiological Aspects. Agronomy 2024, 14, 2685. https://doi.org/10.3390/agronomy14112685

AMA Style

Lin C-C, Chuang Y-H, Shen F-T, Chung W-H, Chen C-Y, Liu Y-T, Hsieh Y-C, Tzou Y-M, Jien S-H. Alleviating Continuous Cropping Obstacles in Celery Using Engineered Biochar: Insights into Chemical and Microbiological Aspects. Agronomy. 2024; 14(11):2685. https://doi.org/10.3390/agronomy14112685

Chicago/Turabian Style

Lin, Chia-Chia, Ya-Hui Chuang, Fo-Ting Shen, Wen-Hsin Chung, Chi-Yu Chen, Yu-Ting Liu, Yi-Cheng Hsieh, Yu-Min Tzou, and Shih-Hao Jien. 2024. "Alleviating Continuous Cropping Obstacles in Celery Using Engineered Biochar: Insights into Chemical and Microbiological Aspects" Agronomy 14, no. 11: 2685. https://doi.org/10.3390/agronomy14112685

APA Style

Lin, C. -C., Chuang, Y. -H., Shen, F. -T., Chung, W. -H., Chen, C. -Y., Liu, Y. -T., Hsieh, Y. -C., Tzou, Y. -M., & Jien, S. -H. (2024). Alleviating Continuous Cropping Obstacles in Celery Using Engineered Biochar: Insights into Chemical and Microbiological Aspects. Agronomy, 14(11), 2685. https://doi.org/10.3390/agronomy14112685

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