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Article

Nitrification and Denitrification Gene Abundances under Stable Soil Chemical Properties Established by Long-Term Compost Fertilization

by
Denver I. Walitang
1,2,†,
Kiyoon Kim
3,†,
Yi Lee
4,
Tae-Young Heo
5 and
Tongmin Sa
1,6,*
1
Department of Environmental and Biological Chemistry, Chungbuk National University, Cheongju 28644, Republic of Korea
2
College of Agriculture, Fisheries and Forestry, Romblon State University, Romblon 5505, Philippines
3
National Forest Seed Variety Center, Chungju 27495, Republic of Korea
4
Department of Industrial Plant Science and Technology, Chungbuk National University, Cheongju 28644, Republic of Korea
5
Department of Information and Statistics, Chungbuk National University, Cheongju 28644, Republic of Korea
6
The Korean Academy of Science and Technology, Seongnam 13630, Republic of Korea
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Appl. Sci. 2023, 13(20), 11146; https://doi.org/10.3390/app132011146
Submission received: 7 September 2023 / Revised: 29 September 2023 / Accepted: 6 October 2023 / Published: 10 October 2023
(This article belongs to the Section Agricultural Science and Technology)
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Abstract

:
Rice paddies are dynamic areas for microbe-mediated nitrogen cycling and this could be driven by the long-term alteration of paddy soil edaphic factors. The objective of this study is to evaluate the lasting impact of long-term compost fertilization on the soil chemical properties of paddy fields, determining the size of the microbial guilds involved in nitrification and denitrification. Soil sampling was done on paddy fields without fertilizer, with NPK + compost, and with compost application, and the soil chemical properties of the fields were determined from 2018 to 2021. The abundance of genes related to nitrogen cycling was measured using quantitative PCR (qPCR). Annual analyses showed that the studied soils have attained stable, baseline chemical properties with significantly increased phosphorus (P2O5), potassium (K), SOM, and total nitrogen (TN) due to decades of fertilization with NPK + compost and compost. Consequently, the genes related to bacterial amoA, nosZI, and nosZII were significantly increased in Com- and NPKCom-amended soils compared to the NF paddy field. The nirK gene abundance was unaffected after long-term amendment with compost. A positive correlation was found between the archaeal amoA gene abundance and DOC, while SOM and TN were consistently positively correlated with the abundances of bacterial amoA, nosZI, and nosZII genes, in addition to interactions with potassium and DOC. Principal component analysis (PCA) indicated soil variabilities across treatments, where the unfertilized paddy field contained lower SOM and nutrient contents with a characteristic nirK gene abundance. Similar variabilities in terms of the SOM, TN, K, nosZI, and nosZII gene abundances were observed in the Com and NPKCom paddy fields. Long-term amendment with NPK + compost and compost created soil paddy fields with stable soil chemical properties with higher SOM and nutrient contents, which established higher abundances of genes associated with denitrification and nitrification that were observed during the fallow period.

1. Introduction

Nitrogen transformations in the nitrogen cycle involve dynamic microbe-driven processes including nitrogen fixation, nitrification, ammonia oxidation, and denitrification. Microbial guilds and the communities involved in these processes accumulate nitrogen or acquire energy based on their growth requirements [1]. Global warming and climate change are connected to the changes and disturbances in these processes due to inappropriate use and the imbalance of diverse nitrogen compounds, leading to negative consequences. To prevent further environmental issues and to improve the conditions of our agroecosystems, obtaining detailed information about the interactions of nitrogen cycling-related microorganisms with soils and the different disturbances requires understanding and investigation [2].
Nitrogen immobilization into crops is the main goal of fertilizer application; however, nitrogen fertilization has become a potent source for nitrogen transformation processes in soil, particularly nitrification and denitrification [3]. Long-term fertilization and the selection of fertilizer sources are important to maximize nutrient efficiency [4]. To predict soil productivity and understand critical processes and linkages in soil, predicting long-term changes in the microbial composition and structure over extended periods is critical [5]. For instance, the ammonia-oxidizing clades at the genus level responded differently to long-term inorganic nitrogen amendment in paddy fields [6]. Long-term nitrogen application also led to taxon-specific responses in the different microbial guilds associated with nitrogen cycling microbial communities [2].
The 16S rRNA is the most-commonly utilized microbial indicator to research structure, composition, and diversity. However, difficulty in the detection of less abundant and less dominant microbial groups performing common functions can occur using 16S rRNA gene-based probes. An alternative technique is to use functional gene markers that provide greater resolution below the species level. The selection of appropriate functional gene markers takes into account their high evolutionary rates for detecting and quantifying microbial communities such as those associated with nitrogen cycling [7,8].
The utilization of compost in agroecosystems is known to enhance soil fertility and increase agricultural productivity while also promoting soil health [9]. On the other hand, to increase global rice production requires intensified fertilizer application, but an increase in the nitrogenous inorganic fertilizers as well as the addition of organic fertilizers can enhance nitrogen transformative losses [1]. Organic compost application, as well as its combination with inorganic fertilizers, primarily determines the flow of nitrogen in organically fertilized land, becoming a major point source of carbon and nitrogen in the nitrogen cycle [10]. Their long-term application can also result in alterations in edaphic components and dynamic structural and diversity changes in soil microbiomes [11].
Thus, the current study assessed the impact of long-term non-fertilization, and compost and NPK + compost amendment, on soil edaphic factors and microbial guilds associated with nitrogen cycling, which would ultimately affect the dynamic transformations of nitrogen in the studied paddy fields. Particularly, we assessed the lasting alterations in soil chemical properties as a result of fertilization with NPK + compost and compost, evaluated the absolute abundance of key microbial guilds through functional gene markers involved in nitrogen transformations, and correlated the changes in edaphic factors as a result of long-term compost fertilizer application and the changes in the gene abundances of the different microbial groups. These alterations were observed during the paddy fallow periods created due to long-term compost application.

2. Materials and Methods

2.1. Research Design of Fields and Soils Samples

Long-term fertilization studies in agroecosystems were initiated in 1967, focusing on rice monoculture paddy fields situated within the RDA (Rural Development Administration; coordinates: 36°36′ N Latitude, 128°45′ E Longitude) in the Republic of Korea [12]. The research station employed an arrangement of experimental plots measuring 10 m × 10 m each, in a completely randomized design and in triplicate for every treatment. Different fertilization treatments were applied including no fertilizer application (NF), NPK fertilizer in combination with compost (NPKCom), and compost application (Com). Urea (120 kg ha−1), superphosphate (80 kg ha−1), and KCl (80 kg ha−1) were applied as the NPK fertilizers. The initial application, administered just prior to transplantation, contributed 50% N, 100% P, and 70% K. On the other hand, the compost was produced by six months decomposition of cattle manure and rice straw mixture resulting in a compost with composition values of 19.8 g kg−1 N, 5.2 g kg−1 P, 29.1 g kg−1 K, and 431 g kg−1 total C. The compost treatment received an annual equivalent of 10 tons ha−1. Before flooding and rice seedling transplantation, samples were gathered in a soil depth of approximately 20 cm (five soil subsamples, three replicates per treatment). A composite sample for each treatment replicate was made by pooling the subsamples. They were immediately sieved (<2 mm) after removing plant residues, placed in bags (sterile polypropylene), and transported on ice packs. Soils intended for standard analyses were kept at −20 °C (molecular) and 4 °C (chemical).
For the physical properties of the soils, paddy field soils are characterized as fine silty, mixed, nonacid, mesic, and Typic Endoaquepts based on the USDA soil taxonomy and classification. The bulk density of the soil in different treatments in different soil depths of 5, 10, 15, and 20 cm was 1.29, 1.32, 1.42, and 1.54 g/cm−3, respectively, for NF soils; 1.07, 1.21, 1.26, and 1.49 g/cm−3, respectively, for Com fertilized soils; and 1.18, 1.14, 1.24, and 1.42 g/cm−3, respectively, for NPKCom treated soils.

2.2. Testing Edaphic Properties of the Soil

Soil organic matter was quantified following the Tyurin titrimetric method [13]. Total N was quantified through the conventional Kjeldahl method [14]. Available P was quantified through the Lancaster method [5]. The NO3-N contents were quantified using ion selective electrode method prior to extraction of 5 g of soil samples with Al2(SO4)3 (50 mL, 0.025 M). Suspensions with a ratio of 1:5 soil:water were prepared for soil pH and electrical conductivity (Orion Star A215, Thermo Scientific, Waltham, MA, USA).

2.3. Quantification of Functional Gene Markers Using Quantitative PCR

To quantify nitrogen cycle-related functional genes, quantitative PCR (qPCR) was used. qPCR reaction conditions are mentioned in Table S1 and optimized for each functional gene. Prior to qPCR, microbial DNA extraction was conducted using a PowerSoil® DNA isolation kit (Mobio Laboratories Inc., Carlsbad, CA, USA). Gel electrophoresis and Nanodrop were employed for quality and quantity of the genomic DNA.
For the qPCR assays, a stock solution of plasmids containing target sequence ranging from 104 to 108 copies was created by serial dilution for the standard curve for each functional gene. The qPCR reaction mixtures (10 μL) contain SYBR Green Master Mix (Thermo Fisher Scientific Inc., Waltham, MA, USA) (5 μL), F and R primers for each functional gene (0.8 μL), genomic/plasmid DNA (1 μL), and milliQ sterilized distilled H2O. Negative controls and triplicates were added in each qPCR run for all the qPCR measurements.

2.4. Description of the Statistical Analyses Used

The quantified soil chemical properties and abundances of target functional genes were assessed for significant differences among treatments means using SAS version 9.4., (SAS Institute, Cary, NC, USA, 2003, [15]) employing Tukey’s test at p < 0.05. A model based on stepwise multiple regressions and Spearman’s correlation were conducted with SPSS, version 25 (IBM, Armonk, NY, USA). This model was made to predict which edaphic factors potentially determine the abundance of each functional gene. The R statistics V4.1.1 with “ggfortify”, “mixOmics”, and “pca3D” packages [16,17,18] were used for PCA (principal component analysis).

3. Results

3.1. Alteration and Stability of Edaphic Soil Factors Attained through Decades of Long-Term NPK + Compost and Compost Amendment

The paddy fields with significantly different soil chemical properties compared to the unfertilized (NF) paddy field were established by long-term fertilization with compost (Com) or a mixture of NPK inorganic fertilizers and compost (NPKCom) (Table 1). The current study showed a clear trend in the change in soil chemical properties distinguishing paddy soils fertilized with NPK + compost and compost and the unfertilized paddy soils. Except in the year 2018, the SOM, TN, P, and K were consistently significantly higher in the Com and NPKCom treatments for each successive year of soil testing observed in the fallow non-planting season, before soil fertilization amendment, flooding with water, and the transplantation of rice seedlings. The NPKCom treatment also showed a significant decrease in soil acidity with cases of significantly higher P, Ca, and Mg contents when compared to both the unfertilized and Com treatments.
Patterns in changes and stability of soil chemical properties could be observed in each treatment under long-term compost fertilization from 2018 to 2021 (Table 2). In general, the Com and NPKCom treatments showed minor statistically significant fluctuations in each of their soil chemical properties throughout the years. For variabilities existing in the different paddy fields, the Com and NPKCom treatments had similar ranges for EC, OM, TN, K, and Na. On the other hand, the pH, P, Ca, and Mg contents had higher ranges for the NPKCom treatment, with values in the ranges of 5.95–6.23, 128.08–179.84 mg kg−1, 6.37–7.35 cmol kg−1, and 1.58–1.91 cmol kg−1, respectively. Interestingly, the unfertilized paddy field showed soil chemical property fluctuations and variabilities. The OM, TN, P, K Mg, and Na contents statistically fluctuated in the unfertilized paddies from 2018 to 2021.

3.2. Nitrification and Denitrification Functional Gene Abundances

Employing quantitative qPCR, the nitrogen cycling functional gene abundances were determined. In general, the numbers of nitrification (AamoA, BamoA) and denitrification (nosZI, nosZII) functional genes were significantly higher in the Com and NPKCom treatments relative to the NF treatment (Figure 1). For the abundance of nitrification functional genes, archaeal amoA increased by 1.26 and 1.95 times while bacterial amoA increased by 3.97 and 2.82 times in the NPKCom and Com treatments, respectively. For the abundance of denitrification functional genes, nosZI increased by 2.08 and 2.36 times while nosZII increased by 1.6 and 1.52 times in the NPKCom and Com treatments, respectively. The nirK gene abundance was not statistically altered and ranged from 6.83 × 108 to 7.81 × 108 copy numbers per gram of dry soil.
We also attempted to quantify other nitrogen cycling-related genes, namely comammox, nrfA and nirS. However, the nrfA gene was not detected in any of the paddy fields tested, nirS was slightly amplified through PCR with the appearance of a faint and fuzzy band in some treatments, while the comammox primer set resulted in two bands. The quantification of nitrogen-cycling-associated microbial communities using these molecular markers were not successfully determined.

3.3. Correlation and Multiple Regression of Soil Chemical Properties and the Gene Copy Number

The correlation and multiple regression analysis indicated a potential relationship between the soil edaphic factors and the gene copy number of the nitrification and denitrification functional genes. The archaeal amoA was significantly and positively correlated with the dissolved organic carbon (DOC). The bacterial amoA, nosZI, and nosZII were all significantly and positively correlated with SOM, TN, and K, with additional correlations for each gene. The nirK gene abundance did not show correlation with any edaphic factor as well as to the other genes included in the study (Table 3).
The multiple regression analysis pointed to a more specific soil chemical property that may directly influence the gene abundance (Table 4 and Figure 2). For archeal amoA, DOC is the only significant factor that influences its gene abundance while total nitrogen is the most important factor influencing bacterial amoA. The nirK gene abundance is significantly influenced by P2O5, OM, and pH. For the abundance of denitrification-related genes, nosZI is mainly affected by TN, P2O5, and pH, while nosZII is significantly affected by TN. It is noteworthy that, during the multiple regression analysis, SOM, TN, P, and K always showed a collinear relationship.

3.4. Visualization and Analysis of Soil Variabilities Found in the Different Paddy Fields Established through Decades of Long-Term Compost and NPK + Compost Fertilization

A summary of the overall effects of the fertilization treatments on the paddy fields’ variabilities was achieved through the PCA of their gene abundances and soil edaphic factors (Table 5 and Figure 3). Eigenvalues higher than 1 were observed for PC 1–5 with cumulative loading of 96%. PC1 and PC2 contributed 50% and 17%, respectively, resulting in an overall loading of 67%. The greatest loading effect for PC1 came from the individual loading factors TN, K, NO3.N, OM, and Ca, followed by nosZI, P2O5, and nosZII, cumulating in a 50% soil variability. A 17% of the overall soil variability was attributed to PC2 contributed by DOC, NH4.N, archeal amoA, and Na.
The ordination plot of the PCA visualized the overall variability in soil the edaphic factors and the abundances of the nitrogen cycling-related genes and their effect on the clustering of soil treatments. The PC1 clearly separates the unfertilized (NF) from the Compost and NPK + compost treatments. The prominent clustering of the NF treatment is partly attributed to the effect of the nirK gene abundance. The PC2 further created a sub-clustering of the Compost and NPK + compost treatments. The distinct separation of the Compost treatment is mainly attributed to DOC, EC, and archeal amoA gene abundance, and the Na loading factor. On the other hand, the clustering of the NPK + compost treatment is partly affected by NH4.N, pH, P, Ca, Mg, and DION. The cumulative effects of all of the loading factors coming from gene abundances and soil edaphic factors contribute to the overall soil variability and clustering of the characteristic paddy fields established through decades of long-term compost and NPK + compost fertilization.

4. Discussion

Insights into the dynamic shifts in soil chemical properties and ecosystem functioning though changed microbial dynamics could be attained through studies involving the long-term fertilization of paddy fields. The current study evaluated the changes in soil edaphic factors along with the concurrent changes in gene abundances related to nitrogen cycling in rice paddy fields established through decades of fertilization amendment. Potential correlations that exist between changes in edaphic factors and the population size indicated by the copy number of nitrification and denitrification functional genes together with the overall soil variabilities that exist between different paddy field treatments were also assessed.

4.1. Paddy Fields with Stable Soil Chemical Properties Rich in SOM and Nutrients Were Established by Long-Term Compost and NPK + Compost Fertilization

The long-term input of a mixture of composted cattle manure and rice straw compost along with its combination with NPK chemical fertilizer in rice paddy fields significantly changed their soil chemical properties but have attained compositional stability over decades of long-term fertilization. The significant increase in chemical properties, SOM, TN, P, and K, could be attributed to a net accumulation, especially by SOM/SOC and TN [4,19,20,21], under long-term fertilization. In addition, the increase in these nutrient contents could also be due to the increased input, as in the case of SOM through enhanced carbon input [22]. Paddy fields under long-term fertilization also showed higher carbon sequestration efficiency, leading to an increased SOM [23]. These changes in chemical properties were also observed in previous long-term fertilization studies [24,25,26,27,28].
Soil chemical stability was also observed in the current study. Stability was detected in terms of non-significant fluctuations in soil edaphic factors, especially chemical properties, during the continuous soil testing, at least during the fallow period. This soil chemical stability was observed in paddy fields amended with NPK + compost and compost. In contrast, paddy fields without any fertilization input showed significant fluctuations in their soil chemical properties from 2018 to 2021. The non-significant fluctuations in soil chemical properties could indicate some scenarios where the paddy fields may have attained a nutrient saturation level or have maintained nutrient input and loss particularly in the case of soil carbon and soil organic matter [29,30]. It is more probable that the nutrient input and loss has stabilized in paddy fields under long-term compost and NPK + compost application, since a higher input of organic matter into the paddy fields adds nutrients into the soil, particularly at the initial stages, but attains stability over decades of fertilizer amendment [21,22]. In contrast, the soil chemical fluctuations occurring in the unfertilized lands could be due to natural nutrient cycling processes such as nitrogen fixation, phosphate solubilization, and organic compound mineralization, which are mainly affected by the cultivation of Hwayeong rice cultivar without additional nutrient input and are potentially greatly influenced by external environmental conditions.

4.2. Soil Organic Matter, Total Nitrogen and Soil Nutrients Interact to Establish Abundances of Nitrigen Cycle Functional Genes and Their Implications

As shown in the results of this study, long-term amendment with compost and a combination of compost and NPK have led to stable yet significantly higher nutrient content in and changed the chemical properties of the paddy fields. Concurrent to this is the altered microbial community, both in terms of abundance and potential composition, as indicated by molecular markers. The direct relationships between the fertilizer input and soil chemical properties and the composition and size of microbial functional guilds have been observed in relation to nitrogen cycling [2,31] and other important soil-based biogeochemical processes [9,11,20,26,28]. Their relationships under long-term compost fertilizer amendment, even during the rice fallow period, should be assessed, especially in terms of their potential impact, particularly greenhouse gas (GHG) emissions.
Under compost and NPK + compost fertilization, the abundances of the nitrogen cycling-related gene bacterial ammonia monooxygenase (Bamo) and nitrous oxide reductase genes (nosZI, nosZII) were significantly greater compared to the unfertilized paddy fields. In addition, the archaeal ammonia monooxygenase (Aamo) gene was also significantly more abundant in the compost amended paddy fields. The nitrite reductase gene (nirK) abundance does not seem to be affected by any fertilization amendment. Correlation and multiple regression analyses pointed to some soil chemical properties attributed to these observations. The gene abundance of Aamo is correlated to DOC; Bamo to SOM, TN, and K; nosZI to SOM, TN, K, Ca, and DOC; and nosZII to SOM, TN, P, K, and DOC.
Studies with long-term fertilizer amendment showed differentiated soil properties, altering microbial communities, which consequently led to changes in the microbial activity [31,32]. The bacterial abundance under long-term fertilization was also positively correlated with the soil nutrient content [3]. Bacterial communities dynamically change in terms of abundance or composition due to alteration in the soil nutrient status under short-term fertilization [33,34,35]. This is most probably due to a change in the metabolic lifestyle involving a more active microbial community adapted to higher nutrient input [36]. As observed in the current study, a stable and higher nutrient status in paddy fields even in the fallow period could have also maintained more abundant microbial guilds related to nitrogen cycling due to decades of the standardized application of NPK + compost and compost. Organic fertilization becomes a prominent source of dissolved or labile carbon, with higher nutrient content similarly observed in previous studies [20,37,38]. It was also observed that the input of livestock manure restored the decreased microbial community composition and population, stably maintaining the microbial diversity of soils under long-term fertilization with inorganic fertilizer [3].
The effects of compost and NPK + compost long-term amendment on specific microbial guilds associated with nitrogen cycling may have different trends compared to the overall microbial diversity and abundance. However, similar to the observation by Sun et al. [2], most nitrogen cycling-related genes had an elevated abundance due to long-term N fertilization, suggesting paddy field agroecosystem succession where nitrification and denitrification microbial guilds have a higher abundance, which was also observed in the current study. This was particularly true for the Bamo, Aamo, nosZI, and nosZII genes. On the other hand, a correlation between SOM and the denitrifier abundance has been reported [39]. This is due to organic carbon donating electrons for denitrification, and, thus, its accessibility greatly controls denitrification [1]. However, taxon-specific responses of microbial guilds related to nitrogen cycling to a particular type of fertilizer amendment may also occur. For instance, in our study, the nirK gene, which encodes the nitrate reductases, was non-responsive to compost and NPK + compost amendment. The nirS gene, another functionally equivalent nitrate reductase, was not amplified using the primer set we employed, which potentially indicates a minor undetected abundance of this microbial guild in the studied paddy fields or that other factors were involved. However, microbial guilds which have the nitrite copper-containing reductase gene (nirK) are generally more dominant than the microbial guilds which have the nitrite cytochrome cd1-containing reductase gene (nirS) in rice paddy soils [1,40,41,42]. The nirS gene was not affected by long-term urea application as observed by Sun et al. [2]. The nrfA gene, a usual molecular marker for DNRA, was also not amplified in our samples. Under regular conditions, dissimilatory nitrate reduction to ammonia had lesser activity in rice agroecosystems [1].
The implication of the changed abundance of molecular markers associated with microbial guilds related to nitrogen cycling, particularly nitrification and denitrification, may only by assumed in our study. The paddy soils were also collected during the fallow period before soil tilling, fertilization amendment, water submersion, and rice seedling transplantation. It is possible that, under our experimental conditions, increases in both N2O and NO emissions occur in paddy soils with higher rather than lower nutrient content soils, as observed by Bouwman et al. [10]. During the fallow period, a potentially higher than expected emission of nitrous oxide may occur from drained paddy fields [43,44]. This is similar to the dry season, where populations of ammonia oxidizers, nitrite oxidizers, and denitrifiers were significantly higher compared to the wet season, which may also lead to increased activities under long-term fertilization, although the fallow periods have a lower amount of N2O-N flux compared to the planting season [20].

4.3. Characteristic Paddy Fields Associated with Nitrogen Cycling-Related Microbial Guilds and Soil Chemical Fertilizers under Long-Term Compost Fertilization

The principal component analysis clearly supported the clustering of paddy fields according to treatment amendments. A clear separation of three distinct groups according to the different fertilizer input could be observed in the current study, mainly influenced by soil edaphic (chemical) factors and the population density of microbial guilds measured through the abundance of denitrification and nitrification genes. The effects of PC1 and PC2 in the PCA analysis explained 67% of the overall soil variabilities, incorporating both soil chemical properties and gene abundances. This implies that the paddy fields receiving different fertilization treatments had characteristic soil variabilities exemplified through long-term fertilizer amendments. Long-term fertilization regimes have changed multiple physical, chemical, and biological properties of paddy fields [20,28]. Groups of microbial guilds associated with nitrogen cycling have also responded differently to long-term fertilization, as evidenced by the distinct microbial guilds, in terms of diversity and abundance, particularly associated to the different fertilization treatments. These are observed in long-term amendments with compost and NPK + compost [20,42,45], and inorganic or chemical fertilizer including urea [6,20,42,45]. Differences in the fertilization application in terms of the amount of fertilization over long-term fertilization also show group-specific changes in microbial communities associated to nitrogen cycling [2,46], creating paddy fields with distinct microbial guilds that are directly affected by fertilization treatments and soil properties. These results were also reflected in our study, where long-term NPK + compost and compost fertilization created characteristic paddy soils. The unfertilized paddy fields were characterized with soil containing a lower nutrient content and lower population of nitrifying and denitrifying microbial guilds. The NPK + compost- and the compost-fertilized paddy fields had soils containing a higher nutrient status with more abundant nitrifying and denitrifying microbial guilds. The archaeal microbial guilds containing the amoA have more impact on the compost-fertilized paddy fields, the bacterial microbial guilds containing amoA, nosZI, and nosZII have greater impact on the NPK + compost amended soils, and microbial guilds containing the nirK gene have more impact on the unfertilized paddy fields.

5. Future Prospects

As paddy fields are important sources of GHG emissions, predictive models and management schemes aimed at maximizing rice yields while optimizing nutrient application and minimizing the environmental impact are essential over short- and long-term paddy utilization. In a previous study [11], methane turnover-related genes were also found to be increased in the same long-term fertilized lands during the fallow period, similar to the results in the present study. These studies indicate potential contributions of fallow paddy fields in terms of methane and nitrous oxide emissions. Although fallow paddy fields have relatively lower emissions compared to other stages of rice cultivation [20], the thorough investigation of all related factors (nitrogen and methane cycling-related genes, actual quantification of nitrous oxide, methane, and carbon dioxide emissions, changes in soil physical and chemical parameters, etc.) in every rice stage cultivation stage is essential to develop effective predictive models for greenhouse gas mitigation schemes. This will also help to pinpoint key indicator parameters (particular nitrogen and methane cycling-related genes, soil edaphic property, etc.) which could be continually globally monitored and that are related to specific goals (increased productivity, reduced GHG emission etc.), increasing our success in implementing sustainable agriculture.

6. Conclusions

This study showed that paddy fields with stable soil chemical properties containing higher nutrient contents, including SOM, total N, phosphorus, and potassium, were established through long-term fertilization. The alteration in soil edaphic factors subsequently increased the abundance of nitrification- (bacterial and archaeal clades containing the amoA gene) and denitrification- (bacterial clades containing the nosZI and nosZII genes) related functional microbial groups, which also leads to characteristic paddy fields with more distinct soil chemical properties and varying abundances of nitrification- and denitrification-related microbial guilds. These conditions could potentially be consistently observed during the non-rice growing period, potentially affecting nitrogen transformative processes, especially concerning nitrous oxide emissions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app132011146/s1, Table S1: Characteristics of qPCR primer pair and programs. References [47,48,49,50,51,52,53,54,55,56,57] are cited in Supplementary Materials.

Author Contributions

Conceptualization, D.I.W. and T.S.; methodology, D.I.W. and T.S.; software, D.I.W.; validation, T.-Y.H.; formal analysis, D.I.W. and T.-Y.H.; investigation, D.I.W. and K.K.; resources, T.S. and Y.L.; data curation, D.I.W. and K.K.; writing—original draft preparation, D.I.W. and K.K.; writing—review and editing, D.I.W.; visualization, D.I.W. and K.K.; supervision, T.S. and Y.L.; project administration, K.K., T.S. and Y.L.; funding acquisition, T.S. and Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Basic Science Research Program, National Research Foundation of Korea (NRF), Ministry of Education, Science and Technology [2021R1A2C1006608], Republic of Korea.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

We would like to acknowledge the support of Romblon State University Board of Regents, Merian Catajay-Mani, and RSU for their support on the Invited Research Fellowship of D.I.W. to Chungbuk National University.

Conflicts of Interest

The authors declare no conflict of interest.

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Applsci 13 11146 g001
Figure 1. Gene abundance of nitrogen cycling genes influenced by decades of long-term compost and NPK + compost amendment. The abundance of nitrification-related genes (A) as quantified with archaeal ammonia monooxygenase gene (Aamo) and bacterial monooxygenase gene (Bamo), and denitrification-related genes (B) as quantified with nitrite reductase gene (nirK) and nitrous oxide reductase genes (nosZI and nosZII). Same letters in the plot indicate non-significant difference (p > 0.05; Tukey’s test). The standard error is denoted in the error bars.
Figure 1. Gene abundance of nitrogen cycling genes influenced by decades of long-term compost and NPK + compost amendment. The abundance of nitrification-related genes (A) as quantified with archaeal ammonia monooxygenase gene (Aamo) and bacterial monooxygenase gene (Bamo), and denitrification-related genes (B) as quantified with nitrite reductase gene (nirK) and nitrous oxide reductase genes (nosZI and nosZII). Same letters in the plot indicate non-significant difference (p > 0.05; Tukey’s test). The standard error is denoted in the error bars.
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Figure 2. Linear relationship between abundances of nitrogen cycling-related genes and their major soil chemical determinant selected based on multiple regression analysis: the archaeal amoA gene abundance and dissolved organic carbon (DOC) (A), the bacterial amoA gene abundance and total nitrogen (B), the nosZ1 gene abundance and total nitrogen (C), and the nosZII gene abundance and total nitrogen (D).
Figure 2. Linear relationship between abundances of nitrogen cycling-related genes and their major soil chemical determinant selected based on multiple regression analysis: the archaeal amoA gene abundance and dissolved organic carbon (DOC) (A), the bacterial amoA gene abundance and total nitrogen (B), the nosZ1 gene abundance and total nitrogen (C), and the nosZII gene abundance and total nitrogen (D).
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Figure 3. PCA score plot showing variability in soil chemical properties and copy number of functional genes associated to denitrification and nitrification observed in different paddy fields amended with long-term compost fertilization.
Figure 3. PCA score plot showing variability in soil chemical properties and copy number of functional genes associated to denitrification and nitrification observed in different paddy fields amended with long-term compost fertilization.
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Table 1. Significant alterations of edaphic factors of rice paddy fields from 2018–2021.
Table 1. Significant alterations of edaphic factors of rice paddy fields from 2018–2021.
YearTreatmentpHECOMTNP2O5KCaMgNa
dS m−1%%mg kg−1cmol kg−1
NF5.76 a0.39 b2.46 a0.19 a30.15 a0.18 a5.19 a1.20 a0.29 a
2018NPKCom5.95 a0.44 a3.14 a0.25 a128.08 a0.27 a6.37 a1.58 a0.33 a
Com5.67 a0.47 a3.08 a0.25 a59.86 a0.29 a5.72 a1.28 a0.33 a
NF5.86 b0.55 b2.16 b0.38 b24.230 c0.15 b5.33 c1.28 b0.34 b
2019NPKCom6.18 a0.71 a2.97 a0.56 a175.19 a0.38 a7.24 a1.91 a0.43 a
Com5.90 b0.63 ab2.95 a0.49 a59.40 b0.40 a6.14 b1.41 b0.39 ab
NF5.90 b0.44 a2.64 b0.19 b36.14 b0.28 b6.96 a1.37 a0.36 a
2020NPKCom6.23 a0.55 a3.29 a0.26 a179.84 a0.50 a7.21 a1.66 a0.35 a
Com5.91 b0.42 a3.09 a0.25 a75.74 b0.56 a7.75 a1.52 a0.40 a
NF5.80 ab0.90 a2.11 b0.15 b28.00 c0.13 b5.70 b1.13 b0.29 a
2021NPKCom5.99 a1.23 a2.90 a0.22 a141.33 a0.53 a7.35 a1.71 a0.31 a
Com5.64 b1.09 a2.69 a0.21 a63.00 b0.49 a6.46 ab1.22 b0.32 a
The same letter after the mean values under each column indicates non-significant differences (p > 0.05; Tukey’s). OM: organic matter; EC: electrical conductivity; TN: total nitrogen; Com: compost; NPKCom: chemical fertilizer (NPK) + Compost; NF: unfertilized control.
Table 2. The stability of soil chemical properties of NF, NPKCom, and Com treatments from 2018 to 2021.
Table 2. The stability of soil chemical properties of NF, NPKCom, and Com treatments from 2018 to 2021.
TreatmentYearpHECOMTNP2O5KCaMgNa
(1:5)dS m−1%%mg kg−1cmol kg−1
20185.76 a0.39 b2.46 a0.20 b30.15 ab0.18 b5.19 b1.20 bc0.29 b
20195.86 a0.55 b2.16 b0.38 a24.23 b0.15 bc5.35 b1.28 ab0.34 a
NF20205.91 a0.44 b2.64 a0.19 b36.14 a0.28 a6.96 a1.37 a0.36 a
20215.80 a0.90 a2.11 b0.15 c28.00 ab0.13 c5.70 b1.13 c0.29 b
20185.95 a0.44 a3.14 a0.25 b128.08 a0.27 b6.37 a1.58 a0.33 a
20196.18 a0.71 a2.97 a0.56 a175.19 a0.39 ab7.24 a1.91 a0.42 a
NPKCom20206.23 a0.55 a3.29 a0.26 b179.84 a0.50 a7.21 a1.66 a0.35 a
20215.99 a1.23 a2.90 a0.22 b141.33 a0.53 a7.35 a1.71 a0.31 a
20185.67 a0.47 a3.08 a0.25 b59.86 b0.29 b5.72 b1.27 a0.33 a
20195.90 a0.63 a2.95 a0.49 a59.40 b0.40 ab6.14 b1.41 a0.39 a
Com20205.19 a0.42 a3.09 a0.25 b75.74 a0.56 a7.75 a1.52 a0.40 a
20215.64 a1.09 a2.69 a0.21 b63.00 b0.49 a6.46 b1.22 a0.32 a
The same letter after the mean values under each column indicates non-significant differences (p > 0.05; Tukey’s). EC: electrical conductivity; TN: total nitrogen; OM: organic matter; Com: compost; NPKCom: chemical fertilizer (NPK) + Compost; NF: unfertilized control.
Table 3. Correlation coefficient showing the relationship of the edaphic factors and the gene copy number.
Table 3. Correlation coefficient showing the relationship of the edaphic factors and the gene copy number.
GenespHECOMTNPKCaMgDOCAamoBamonirKnosZInosZII
1:5dS m−1%%mg kg−1cmol+ kg−1mg kg−1Copy Number g−1 Dry Soil
Aamo−0.07−0.030.2830.2540.1330.3670.200−0.020.783 *1.0000.183−0.350.6330.250
Bamo0.1000.0670.767 *0.695 *0.6500.683 *0.3500.4000.2830.1831.0000.0500.5330.717 *
nirK−0.63−0.250.050−0.050.117−0.30−0.33−0.35−0.03−0.350.0501.000−0.500.167
nosZI0.2170.5000.750 *0.780 *0.5830.867 **0.717 *0.5670.717 *0.6330.533−0.501.0000.650
nosZII0.0000.2500.750 *0.763 *0.767 *0.717 *0.5830.4670.700 *0.2500.717 *0.1670.6501.000
The asterisks mark the value of p: * means p < 0.05, ** means p < 0.01.
Table 4. Relationships between soil edaphic factors and gene copy numbers of nitrogen cycling genes as shown through multiple regression analyses.
Table 4. Relationships between soil edaphic factors and gene copy numbers of nitrogen cycling genes as shown through multiple regression analyses.
GeneVariableCoeff.S.E.S. Coeff.RankingT-Valuep-ValueVIFF-Valuep-ValueR2
AamoAConstant13.3980.460 0.0000.000 4.9400.050.622
DOC0.0120.0040.76613.0310.0231.013
NH4-N−0.0200.042−0.1222−0.4810.6481.013
BamoAConstant11.4601.114 10.2890.000 5.7720.0400.658
TN23.7347.1300.98613.3290.0161.541
DOC−0.0150.010−0.4222−1.4230.2051.541
nirKConstant42.8191.973 21.6980.000 52.2390.0010.981
NO3-N−0.0140.015−0.1914−0.9710.3878.231
P2O50.0220.0021.841110.7880.0006.200
pH−2.9840.270−1.3443−11.0360.0003.157
OM−2.5230.335−1.6202−7.5220.0029.874
nosZIConstant11.1050.962 11.5460.000 60.1730.0000.973
TN19.7591.7601.6000111.2250.0003.769
P2O5−0.0070.001−0.8862−5.8630.0024.233
pH0.6600.1400.42834.6980.0051.538
nosZIIConstant16.80.347 48.4600.000 10.5150.0210.913
TN13.6973.1451.81714.3550.0128.017
NO3—N−0.0290.012−0.9062−2.3320.0806.948
DOC−0.0020.002−0.2114−1.1180.3261.640
NH4-N0.0250.0220.21931.1450.3161.678
Table 5. PCA analyses of soil edaphic factors combined with genes related to nitrogen cycling and the principal component’s loading coefficient.
Table 5. PCA analyses of soil edaphic factors combined with genes related to nitrogen cycling and the principal component’s loading coefficient.
Principal Component (PC)Eigen ValuesLoading of PCCumulative Loading
13.010.500.50
21.730.170.67
31.400.110.78
41.290.090.87
51.260.090.96
60.650.020.98
70.500.010.99
80.320.011.00
PC loading for individual variable
pHECOMTNP2O5KCaMgNaDOCDIONNH4.NNO3.NAamoABamoAnirKnosZInosZII
PC10.060.180.300.320.270.320.300.270.120.170.280.020.310.120.20−0.070.290.26
PC2−0.530.190.120.11−0.190.05−0.19−0.210.300.33−0.20−0.33−0.130.32−0.040.220.110.14
PC3−0.000.55−0.07−0.12−0.14−0.170.180.290.53−0.05−0.020.23−0.10−0.22−0.32−0.120.02−0.10
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Walitang, D.I.; Kim, K.; Lee, Y.; Heo, T.-Y.; Sa, T. Nitrification and Denitrification Gene Abundances under Stable Soil Chemical Properties Established by Long-Term Compost Fertilization. Appl. Sci. 2023, 13, 11146. https://doi.org/10.3390/app132011146

AMA Style

Walitang DI, Kim K, Lee Y, Heo T-Y, Sa T. Nitrification and Denitrification Gene Abundances under Stable Soil Chemical Properties Established by Long-Term Compost Fertilization. Applied Sciences. 2023; 13(20):11146. https://doi.org/10.3390/app132011146

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Walitang, Denver I., Kiyoon Kim, Yi Lee, Tae-Young Heo, and Tongmin Sa. 2023. "Nitrification and Denitrification Gene Abundances under Stable Soil Chemical Properties Established by Long-Term Compost Fertilization" Applied Sciences 13, no. 20: 11146. https://doi.org/10.3390/app132011146

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