Linking nitrous oxide emissions from starch wastewater digestate amended soil to the abundance and structure of denitrifier communities

Journal Pre-proof Linking nitrous oxide emissions from starch wastewater digestate amended soil to the abundance and structure of denitrifier communities

Sining Zhou, Zhe Xu, Xiangui Zeng, Zhihui Bai, Shengming Xu, Cancan Jiang, Shengjun Xu PII:

S0048-9697(20)30916-5

DOI:

https://doi.org/10.1016/j.scitotenv.2020.137406

Reference:

STOTEN 137406

To appear in:

Science of the Total Environment

Received date:

14 July 2019

Revised date:

28 January 2020

Accepted date:

16 February 2020

Please cite this article as: S. Zhou, Z. Xu, X. Zeng, et al., Linking nitrous oxide emissions from starch wastewater digestate amended soil to the abundance and structure of denitrifier communities, Science of the Total Environment (2020), https://doi.org/10.1016/ j.scitotenv.2020.137406

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© 2020 Published by Elsevier.

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Linking nitrous oxide emissions from starch wastewater digestate amended soil to the abundance and structure of denitrifier communities

Sining Zhou

a,b,c

, Zhe Xu a,d, Xiangui Zeng a, Zhihui Bai

b,c

, Shengming Xu d, Cancan

Jiang c, Shengjun Xu c* Shenzhen DiDa Water Engineering Limited Company, Shenzhen, 518116, China.

b

Sino-Danish Center, University of Chinese Academy of Sciences, Beijing 101408,

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a

CAS Key Laboratory of Environmental Biotechnology, Research Center for

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c

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China

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Eco-Environmental Science, Chinese Academy of Sciences, Beijing 100085, China Agricultural College, Hunan Agricultural University, Changsha 414699, China

*

Corresponding author: Shengjun Xu, E-mail addresses: [email protected]

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Abstract Anaerobic digestion is widely used in starch wastewater pre-treatment and can remove the COD effectively, however, the effluents are nutritious and often need supplemental aerobic treatments to remove nutrients prior to discharge. The objective of this study was to investigate the feasibility of using the liquid digestate of starch

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wastewater (LDSW) as a fertilizer. This pot experiment was conducted with Ipomoea aquatica Forsk in a greenhouse with six treatment groups. The crop growth was

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significantly promoted, while the accumulation of soil nitrate was not influenced after

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LDSW addition, compared to the control. In addition, at the same nitrogen input, the

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yield of high-LDSW treatment was 65.2%, 92.3% and 69.2% higher than those of

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chemical fertilizer treatment during the three growth periods. Furthermore, average

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N2O emission with high-LDSW addition was 15.8 g N/(ha.d), accounting for 15.0% of which under high chemical fertilizer treatment, due to the significantly enhanced

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denitrification genes (nirK, nirS and nosZ) abundance. Besides, the changes of soil N2O-reducing bacteria were performed by high-throughput sequencing of nosZ. Our findings suggested that LDSW had many opportunities for sustainable agriculture to guarantee high yields while reducing negative environmental impacts. Keywords: digested starch wastewater; soil property; N2O emission; denitrification functional gene; denitrifier community

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1. Introduction Sweet potato (Ipomoea batatas L.) is a crucial food crop as it yields over 100 million tons annually and half of which are allotted to starch industries. According to the estimate released by China starch industry association, annual starch production has reached over 27 million tons, resulting in the generation of about 79 million m3 of

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starch wastewater (calculated based on Technical guidelines of accounting method for pollution source-starch and starch product manufacturing industry, HJ 996.2-2018).

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Untreated starch wastewater can cause severe environmental hazards due to its high

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concentration of chemical oxygen demand (COD) and nutrients, thus treating the

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starch wastewater appropriately is of prime importance. Over the past decades, starch

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wastewater treatments have been well developed, while anaerobic-aerobic biological

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treatments are widely employed (Xu et al., 2017a). Anaerobic technique has been particularly regarded as an appealing solution for

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treating high-strength wastewater (Rajbhandari and Annachhatre, 2004), because of their resilience to hydraulic shock loads, low yields of sludge, and the outstanding ability of gas-solid-liquid separation (Ji et al., 2009). In spite of these advantages, anaerobic digestion technology is often limited by inadequate treatment efficiency and unsatisfactory operational stability (Antwi et al., 2017), indicating that the effluents often need supplemental aerobic treatments to remove nutrients (i.e. nitrogen and phosphorus). Consequently, much more energy would be consumed before reusing or discharging the effluents to meet prescribed environmental laws. There is an urgent need to find out better ways to dispose of the digested starch wastewater driven by

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economics and environics. In parallel, starch wastewater can potentially function as raw materials for biochemical industry since it contains little toxic substance. Reutilization of starch wastewater, such as producing electricity and cultivating microalgae for third-generation biofuels (Chu et al., 2015; Lu et al., 2009), is being proposed.

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On the other hand, agriculture acts as an important source of greenhouse gases (GHGs), particularly in China. Moreover, nitrous oxide (N2O) makes a profound

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contribution to global warming since the warming potential of N2O is ~300-time

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greater than that of CO2 (IPCC, 2007). Besides, agricultural extensification and

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intense application of N fertilizers have been suggested as primary causes of the

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emission of N2O (Galloway et al., 2008). Reducing agricultural N2O emissions in

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combination with sustainable agriculture has been investigated in the global effort to alleviate global warming. In our previous study (Xu et al., 2017a), raw starch

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wastewater was treated in a modified anaerobic baffled reactor (ABR) system. Even though the ABR could remove 92.7% of COD, its effluent (that is the liquid digestate from the ABR treating starch wastewater, abbreviated as LDSW) carried a store of decomposed organic carbon, readily available forms of N and other nutrients. In reality, most of the COD in wastewater would be eliminated after undergoing anaerobic treatment, while the total N and P remain, but this just satisfies the nutrients needed for vegetable growth. Moreover, many studies have demonstrated that inorganic fertilizers can be replaced by anaerobic digestate, which can maintain crop productivity and reduce reliance on chemical fertilizers (Walsh et al., 2012).

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Wastewater is increasingly recognized as an asset for exploitation rather than a burden to be disposed of. Thus, applying LDSW to agricultural irrigation is expected to be a promising way to provide relief for the use of chemical fertilizers and water scarcity in agriculture, as well as its further treatment costs. Although many studies revealed the biological conversion and microbial

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community changes during anaerobic digestion (Kobayashi et al., 2011) and the growth promotion effects on plants (Walsh et al., 2012), there is very little

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information on the influence of digested wastewater on soil, especially in terms of soil

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properties and soil microbial community. Besides, many studies lost sight of the

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emissions of GHGs but emphasized the reduced apparent loss of N. Accordingly, the

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study presented here evaluated the feasibility of using LDSW as a liquid fertilizer and

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the subsequent influences on crop, soil and N transformation. Crop yields, soil properties and N2O fluxes response to different fertilizers amendment were

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determined, and the shifts of corresponding key functional genes of nitrogen cycle were investigated to explain the pathway of N in these systems. Illumina high-throughput sequencing of the nitrous oxide reductase (nosZ) gene was also applied to exhibit the correlation between N2O fluxes and N2O-reducing bacteria. Compared with chemical fertilizer application, we tested the hypothesis that LDSW can improve crop yields and soil physiochemical properties, and reduce N2O emissions from agroecosystems. 2. Materials and Methods 2.1 Pot experiment

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The studies were conducted at the Changsha Agricultural and Environmental Monitoring Research Station (28° 32′ 50″N, 113° 19′ 58″E, and 50–430 m a.s.l.) in Hunan province, China. The local soil is classified as Perudic Luvisols according to the China Soil Classification System or as Ultisol based on the USDA taxonomy system, which has been developed from granite. Shallow soil (5-20 cm) from a tea

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garden where Camellia sinensis was cultivated for years was collected randomly and dried in the shade. Afterwards, all soil was mixed thoroughly and archived at room

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temperature (<25 ℃) for subsequent pot experiment.

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A pilot-scale ABR with five compartments and a working volume of 480L (150

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cm long, 40 cm wide and 80 cm high) was applied to treat real sweet potato starch

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wastewater at ambient temperature. The ABR system was seeded with the sludge

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from an anaerobic digester in a local pig farm and steadily operated for over one year prior to this study. During reactor operation, influent and effluent pH was maintained

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at 3.5 ± 0.2 and 6.7 ± 0.3, respectively. More details on the operation and performances of the ABR system can be found in our previous study (Xu et al., 2017a). The effluents of ABR were sampled once a month (the total nitrogen of three samplings were 120, 110 and 83 mg N/L respectively), and refrigerated at 4℃ for short-term storage (< 3 days). The experimental pots (22 cm × 18 cm, diameter by height) were placed in a greenhouse and arranged in a completely random design with three replicates for each treatment. 5.0 kg of soil were filled into each pot, along with the transplant of three Ipomoea aquatica Forsk seedlings with similar aboveground and belowground biomass (i.e. four leaves and 8.0 cm of root). Treatments included

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(1) CK, no fertilization; (2) sweet potato starch wastewater treatment (SW, diluted starch wastewater); (3) chemical fertilizers treatments (CH and CL, prepared by dissolving urea and NPK fertilizer in deionized water); and (4) LDSW treatments (EH and EL). The pot experiment lasted from May 24th to August 17th. Additional, treatments were thrice irrigated with 400 ml of liquid fertilizers, at the beginning of

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the pot trail (May 24th) and after harvesting the aboveground biomass (June 23th and July 17th), while they were irrigated with deionized water every 3 days for the rest of

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the experimental period. Full details of the fertilization strategies and total nitrogen

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input for each growth period are described in Table 1.

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2.2 Determination of soil physiochemical properties

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Soil samples were collected at the end of the pot experiment, and soil pH,

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electrical conductivity (EC), ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3–-N), total dissolved nitrogen (TDN), and dissolved organic carbon (DOC) were determined

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to assess the effects of different fertilizers on soil physiochemical properties. After removing the visible plant residues and debris, the fresh soil of each pot was mixed thoroughly and divided into several subsamples to await analysis. According to ISO 10390:2005 and HJ 802-2016 (Chinese standard: determination of conductivity), a proportion of homogenized soil samples was air dried, grinded, and sieved through 2-mm mesh; soil water suspensions (1:2.5 w/v soil-to-solution ratio for pH and 1:5 w/v for EC) were vibrated using a vortex mixer and then kept still. Soil pH and EC were measured from the supernatants via pH and conductivity meters, respectively.

Journal Pre-proof Parameters of soil NH4+-N、NO3–-N and TDN were measured as described below. Briefly, 10.0 g of fresh soil was shaken with 50 ml of 2M KCl for 1 hour on a reciprocating shaker at 180 r/min. The supernatants were recovered after centrifugation and used for NH4+-N and NO3–-N analyses. Prior to TDN measurements, a proportion of aforementioned supernatants were digested with 2:1 (v/v) alkaline potassium persulfate at 121℃ for 30 min since it could oxidize organic

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N to NO3–, that is the TDN equals to the sum of NH4+-N and NO3–-N in the digested

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samples. Afterwards, soil NH4+-N、NO3–-N and TDN were assayed colorimetrically

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using a continuous flow analytical system (AA3, Seal Analytical, Germany). The

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level of NH4+-N、NO3–-N and TDN in the soil were all expressed as mg N per kg of

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the soil dry weight (mg N kg-1 DW). In addition, DOC extractions were performed

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with field-moist soil and 0.5M K2SO4 at a 1:5 w/v ratio for 1 hour according to the method proposed in Jones and Willett (2006), and the extracts were detected using a

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TOC automatic analyzer (Phoenix-8000, Japan). 2.3 Measurement of N2O fluxes To gather soil N2O in-situ, cylindrical opaque PVC chambers (15 cm × 18 cm, internal diameter by height) were installed onto the soil in each pot (Li et al., 2013). The lower ends of the chambers were sharp so that the chambers can be inserted vertically into the soil to ensure gas tightness. Besides, screw lids fitted with rubber diaphragms for gas samplings were mounted on the top of the chambers. Twelve times of gas samplings were conducted one day after fertilization during the period from May 31th to August 17th at 6-day interval, while two biomass-harvesting days

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were excluded. Each sampling time was strictly controlled between 9:30 am and 10:30 am, and the gas sample from each pot was collected into a 12-ml vacuum tube (Exetainers, Labco, High Wycombe, UK) at 0 and 30 min after the lids were closed. The N2O concentration in the gas samples were determined via a gas chromatograph (Agilent 7890A, Agilent, USA) equipped with an 63Ni-electron capture detector. More

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details regarding the sampling methods and gas chromatograph configurations are provided in Xu et al. (2014) and Xu et al. (2018). Using the equation described by Li

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et al. (2013) and Xu et al. (2014), the N2O fluxes (g N ha-1 d-1) were then calculated

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based on three factors: averaged air temperatures inside the chambers, the elevated

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N2O concentrations within the gas samplings and the effective height of chambers.

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2.4 Soil DNA extraction and real-time quantitative PCR (qPCR)

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DNA from each soil sample was extracted using the FastDNA SPIN Kit for Soil (MP Biomedicals, Santa Ana, USA) according to the manufacturer’s instructions and

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quantified using a Nanodrop 2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA). The purified DNA was stored at -80℃ to await downstream assays including qPCR and Illumina sequencing. To reduce the inhibition effects of humic acids on PCR amplification, all DNA samples were diluted to a concentration of 10 ng/μl to await amplify. Key functional genes involved in the nitrogen cycle including amoA, nirK, nirS, and nosZ were amplified with Premix Ex Taq (TaKaRa Biotechnology, Japan), and their abundances were determined by qPCR with a CFX ConnectTM Real-Time System (Bio-Rad, Hercules, CA, USA). In this study, the quantity of amoA genes in AOA was measured

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with the primer set Arch-amoAF/ Arch-amoAR (Francis et al., 2005), while that of which in AOB was measured with amoA-1F/amoA-2R (Okano et al., 2004). Primer sets NirS-cd3F /NirS-R3cd (Michotey et al., 2000) and NirK-F1aCu/NirK-R3Cu (Chen et al., 2016) were used for nirS and nirK quantification, respectively. Additionally, nosZ genes were measured with primer set nosZ-F/nosZ1622R (Jin et al.,

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2014) quantitatively. All amplified samples were evaluated for purity using agarose

specificity of the amplification products.

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2.5 High-Throughput Sequencing of nosZ

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gel electrophoresis after PCR and melting curves were employed to confirm the

primers

nosZF

(5′-CGYTGTTCMTCGACAGCCAG-3′)

and

nosZ1622R

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the

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After DNA extraction, a portion of DNA were used as a template for PCR using

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(5′-CGSACCTTSTTGCCSTYGCG-3′) (Jin et al., 2015), which were chosen to amplify the nosZ genes, and thereby investigate the community of N2O reducing

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bacteria through high-throughput sequencing analysis. PCR reaction mixture consisted of 20 to 30 ng of template DNA, 1.5 μL of each primer at 0.3 μM, and 25 μL of Premix Ex Taq (TaKaRa, Dalian, China). The PCR thermal condition was performed as described by Xu et al. (2018) previously: 95 °C for 1 min, followed by 35 cycles at 95 °C for 10 s, 55 °C for 30 s, 72 °C for 1 min, and followed by an extension at 72 °C for 10 min. The amplicons were purified using the Gel Extraction Kit (D2500-02, OMEGA BioTek). Paired-end sequencing was realized through Illumina platform (Miseq), then the reads receiving a less than 20 average quality score were eliminated before further

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analysis. The overlapping paired end reads were merged into tags using the COPE software (Connecting Overlapped Pair-End, V1.2.3.3), and separated sequences of each sample were obtained according to barcodes and primers (allowing one nucleotide mismatching). Moreover, COPE software was used to remove the reads containing ambiguous bases and the low-quality sequences (lengths < 200 bp).

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QIIME Pipeline Version 1.8.0 (http://qiime.org/tutorials/tutorial.html) was employed to cluster all sequences into operational taxonomy units (OTUs) at a 97% identity

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threshold. Besides, singleton OTUs were filtered out. More detailed descriptions of

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sequence data processing were performed as previously reported (Xu et al., 2018).

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2.7 Statistical analysis

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Unless stated otherwise, data presented in this study are means of triplicated ±

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standard deviation (SD) and the threshold for significance level was set at 0.01. The within-sample diversities (α-diversity) including Chao 1 estimator of richness,

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observed species, PD whole tree and Shannon diveristy index of the soil N2O-reducing microbial community were calculated in QIIME. Levene’s test was applied to verify the homogeneity of variance prior to variance analysis. Furthermore, significant differences between treatments were tested by one-way ANOVA, followed by Duncan’s multiple range tests performed in SPSS sofeware (Version 20.0, IBM, NY, USA). 3. Results and Discussion 3.1 Crop yields response to different fertilizers Crop production highly depends on the availability of soil nutrients, and

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harvested crop biomass is a direct indicator of fertility in soil. The I. aquatica Forsk growth responses to different fertilization strategies in microcosm pot experiment were compared as shown in Fig. 1. The yields for unfertilized treatment (CK) in three growth periods were 13.3 ± 1.3, 12.8 ± 1.6, and 26.4 ± 9.3 g, respectively. Moreover, the harvested biomass of I. aquatica Forsk revealed a general trend of increase when

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nutrients were imposed across all growth periods except for SW treatment, compared to the CK. No statistically significant changes in biomass were observed between EL

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and CL treatments. Notably, under CH condition, a significant increase of biomass

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was observed only in the first growth period compared with CL group, indicating that

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additional chemical fertilizers did not stimulate the growth of I. aquatica Forsk.

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However, EH treatment produced significantly superior yields as compared to all

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other treatments throughout the experiment. Besides, compared to the treatment applying high rate of chemical fertilizer (CH), EH increased yields by 65.2%, 92.3%

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and 69.2% during crop growth periods, respectively, suggesting that the LDSW has the potential to be used as a liquid fertilizer. Despite the fact that the N application rate of SW treatment was equivalent to that of CH and EH groups, raw starch wastewater led to extremely low yields of crop, which was consistent with the findings of a previous study on tea field (Xu et al., 2014). It has long been proven that the employment of anaerobic digestate as fertilizers is feasible (Han et al., 2019), this may be because macromolecular organic compounds such as polysaccharides and proteins are hydrolyzed into micromolecular substances that are more conducive to crop uptake with the action of acidogenic

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bacteria during anaerobic digestion (Schink, 1997). On the other hand, LDSW reuse for irrigation can alleviate agricultural water scarcity, reduce the chemical fertilizers application and the NOx– accumulation in crops, and realize wastes recycling to a certain extent. Although the application of anaerobic digestate has above advantages, more studies should be done to determine the health implications and potential

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adverse effects that the presence of heavy metals and emerging contaminants in crops may have for consumers. Furthermore, a long-term monitoring of crop yield and

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quality in field trials are more convincing on the feasibility of applying LDSW to

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agricultural irrigation.

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3.2 Change in soil physiochemical properties

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3.2.1 soil pH, EC and DOC

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The effects of different fertilization conditions on soil physiochemical properties including pH, EC, DOC (Table 2), NH4+-N, NO3–-N and TDN (Fig. 2) were

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investigated after the 12-week pot experiment. Obviously, the experimental soil was acidic and the pH values of CK at sampling time fluctuated between 3.98 and 4.28. As shown in Table 2, soil pH increased significantly in soil treated with SW, EL and EH as compared to the control, and slightly decreased under chemical fertilizer treatments (CL and CH). In addition, the pH decreased as the application rate of chemical fertilizer increased, but the application of LDSW had the opposite effect. Both soil EC and DOC exhibited significant differences in all the treatments when compared to CK, apart from a non-significant decrease of DOC was observed under CL condition. Hunan province is one of the most intensively used agricultural regions in China

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and its intensive fertilization has largely accelerated soil acidification. Large inputs of chemical fertilizers have been confirmed to be one of the main drivers to anthropogenic soil acidification, but the theoretical mechanisms remain controversial (Guo et al., 2010). Yang et al. (2018) suggested that the major mechanism is related to the hydrolysis of N fertilizers and production of hydrogen ion via nitrification process while Wan et al. (2012) reported that the dynamics of soil pH corresponded to the root

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uptake of NH4+ and Al(Ⅲ) during crop growth. Excessive levels of N fertilization

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would also affect biota adversely, lead to severe yield reductions, changes of the

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biogeochemistry of ecosystems and low nitrogen use efficiency (Guo et al., 2010).

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Furthermore, acidic condition would increase the metal (e.g. As(Ⅲ), Cr, Pb and Cd)

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bioavailability and mobility in soil, and the subsequent uptake by crop have

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increasingly been reported in the last few decades (Wan et al., 2019). Therefore, soil acidification due to large annual applications of N fertilizer is a major problem in

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Chinese agricultural systems. Reportedly, anaerobic digestate is suitable for agricultural soil amendment (Solé-bundó et al., 2017). In this study, the result that chemical fertilizer application had a reduced effect on soil pH was consistent with previous conclusions. In contrast, pH increased significantly when LDSW was applied, probably because LDSW imparted alkaline properties that raised soil pH, reflecting its potential to retard soil acidification and enhance heavy metals immobilization without affecting crop yields. EC was mentioned as a variable aff ected by management and considered as a major parameter influencing yield (de Paul Obade and Lal, 2014). Husson et al. (2018) proposed that the higher the organic

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matter content and the CEC, the higher was the EC, which was in line with our results. As expected, the application of starch wastewater and LDSW can significantly enhance the concentration of soluble salts and organic matters in the soil, indicating that more nutrients are available for crop uptake. However, raw starch wastewater carries a large amount of refractory and macromolecular organic substances, once

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applied to the soil, it will consume lots of soil oxygen and result in plant hypoxia and wilting (Vartapetian et al., 2014). This also helps explain why the crop yields in SW

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3.2.2 soil NH4+-N, NO3–-N, TDN

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treatment were extremely low.

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As observed in Fig.2, various degrees of increased soil NH4+-N, NO3–-N and

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TDN contents occurred after the addition of nutrients for 12 weeks. When urea and

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NPK fertilizer was added, the contents of NH4+-N, NO3–-N and TDN under CL treatment had increased by 156.8%, 88.4% and 14.5%, respectively, whereas under

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CH treatment they had significantly increased by 903.9%, 465.5% and 246.2% as compared to CK. Besides, CH treatment resulted in greater concentrations of NO3–-N than all the other treatments. In contrast, no significant changes were detected in N contents under both EL and EH treatments when compared with CK. This provides further evidence that the LDSW treatment was more effective in promoting plant uptake of N or inducing a highly active nitrification and denitrification process within the soil, the loss of N as N2O in each treatment will be provided hereinbelow. Surprisingly, even if the raw starch wastewater application had negative impacts on crop development and could accumulate high levels of soil N, this treatment resulted

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in significantly lower accumulation of N than CH in the soil. Based on above-mentioned results, direct application of the starch industry wastewater to the fields will carried significant risks to the crop and soil. These findings well agree with most previous studies (Arienzo et al., 2009; Szuba and Lorenc-Plucińska, 2015). It also should be noted that NO3–-N was the dominant form of inorganic N presented in

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soil irrespective of treatments, besides, both NH4+-N and NO3–-N increased with increasing N application rate.

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The form of nitrogen will affect the fate of ions, as NH4+ ions are less mobile

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than NO3– in the soil due to their opposite charges (Husson et al., 2018). Hence, an

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abundant amount of NO3– is likely to be transported with soil water and accelerate N

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leaching, which will further lead to risks of eutrophication and aquatic toxicity.

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Previously, applying urea with the rate of 450 kg N ha−1 yr−1 had prompted NO3– accumulation and suffered the loss of 11.9% of N as NO3– leaching in a field

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experiment (Xu et al., 2017b), which are consistent with our findings. On the other hand, high levels of N-related parameters in the soils implied that nitrogen use efficiency (NUE) under CH treatment was low, which would explain why additional chemical fertilizers cannot stimulate the growth of I. aquatica Forsk in our study. The sustainability of current agricultural patterns in China has been questioned because of its prevalent high N fertilization rate and low NUE. Therefore, many studies have been investigated in efforts to maximize crop yield with improved NUE, such as inorganic N application stage and irrigation management (Zhang et al., 2018). A comprehensive understanding of soil N dynamics and the determination of optimal

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application rate of chemical fertilizer seem to be one of the most effective solutions, while the reuse of LDSW and suchlike anaerobic digestate appears to be a promising solution to reduce or replace some of the applied fertilizers since these materials are an alternative source of nutrients. Many studies have demonstrated that employing anaerobic digestates as replacements for chemical fertilizers can maintain high NUE

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and low nitrate leaching (e.g. Yin et al., 2019). The present study revealed that the addition of LDSW indeed led to significantly higher soil pH and lower N contents

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than chemical fertilizer, yet these results did not corroborate the conclusion of some

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studies that an increase of soil pH will decrease denitrification, promote nitrification

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rate, and eventually strengthen the nitrogen leaching (Yang et al., 2018). Possible

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interpretation is that the I. aquatica Forsk can assimilate substantial N under slightly

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acidic conditions as it is commonly used for phytoremediation in the nutrient-rich soil or sludge (Stabnikova et al., 2005). It is also interesting to note that EH treatment had

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the same effect on soil N-related parameters as EL treatment (p<0.01). This indicates that factors other than soil properties, such as plant uptake and exogenous microorganisms introduced by LDSW are needed to be considered. However, more investigations should be involved to test this hypothesis. 3.3 N2O fluxes from each treatment N application is a key factor in regulating N2O fluxes from soil to the atmosphere. Gas samples from each treatment were collected and used for determination of N2O fluxes every 6 days except when harvesting crop biomass. The variation of N2O fluxes under different treatments over a 12-week period are presented in Fig.3.

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Although the soil used in the pot experiment experienced long-term fertilization, N2O fluxes were still relatively low without external fertilizers addition. Under unfertilized condition, soil N2O fluxes obtained in this study (3.7 to 25.5 with a mean of 9.4 g N ha-1 d-1) were consistent with the estimation of the range of N2O fluxes in China reported by Sun et al. (2012). However, this background emission is relatively lower than those tea soil in China (~19.5 g N ha-1 d-1, Fu et al. (2012)) or in Japan (~10.0 to

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11.6 g N ha-1 d-1 Akiyama et al. (2006)), while these data were highly affected by the

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application rate of N fertilizers in previous years. The average N2O fluxes from soil

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for SW, CL, CH, EL, EH were 52.1, 38.1, 105.6, 30.0, 15.8 g N ha-1 d-1, respectively.

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Moreover, analysis of variance demonstrated that the differences in N2O fluxes among

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CK, SW, CL, EL and EH treatments were not statistically significant, while CH

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treatment induced significantly higher N2O emissions than all other treatments. Similar N2O emission patterns can be observed in CL, EL and EH treatments, as they

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all had an upward trend at first and then peaked on June 30th, then decreased, and increased again in July 30th.

After receiving N, the soil N2O fluxes were greatly enhanced. Due to the general lack of understanding of the mechanisms for manipulating N2O production, the pulse times of N2O emissions after adding fertilizers are remain inconclusive. As can be seen in Fig.3, almost all N2O emission pulses following N application events occurred within three weeks, which was in accordance with the study reported by Zhou et al. (2014) but rather longer than the conclusion of Yin et al. (2019). In general, the application of chemical N fertilizers is associated with stronger N2O emissions

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than other N sources. Furthermore, soil organic matter, pH and temperature are considered to be three important regulators for manipulating N2O emissions (Ludwig et al., 2001). It has been widely proposed that the incorporation of organic matters (e.g. straw) can reduce direct N2O emissions because it increases the soil C/N ratio and further stimulates soil microbes to immobilize the input N, but conflicting

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findings were also reported frequently (for instance, Harrison and Matson (2003) found that DOC was positively related to the N2O emissions).

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In our study, at the same N application rate, irrigation of organic-rich raw starch

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wastewater or LDSW significantly reduced cumulative N2O emissions compared to

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CH treatment, although raw starch wastewater can elicit several negative

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environmental responses. The foregoing assumption is further supported by the

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significant lower soil soluble N contents (Fig.2) in SW and EH as compared to CH treatment, then the limited N availability will suppress the production and emission of

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N2O. However, Zhou et al. (2014) mentioned that the correlation between N2O fluxes and NO3– leaching losses is negative while Xu et al. (2014) held a contrary opinion. On the other hand, although onsite N2O emissions could be alleviated when N leaches, the leaching N from pedosphere to hydrosphere would cause offsite N2O emissions, which may still lead to global warming. But encouragingly, the application of LDSW especially in high rate (i.e. EH treatment) was performing well, which was characterized by significantly lower soil N contents and N2O fluxes but higher crop yields in comparison with CH treatment. The above results strongly suggested that LDSW is suitable for agricultural fertilization since the application of LDSW meets

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the requirements of modern agriculture, which aims at increasing product yields while reducing negative impacts on the environment. In addition, reuse of LDSW is expected to promote sustainable development and achieve zero waste generation in starch production industry, thereby reducing the energy consumption for further starch wastewater treatment. Although some investigators have demonstrated it is safe and

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cost-effective to reuse anaerobic digestates including starch wastewater effluents considered in this study, additional studies are still needed to define the risks of

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contaminants such as heavy metals, hormones and drug residues that can be uptake by

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crops.

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Notably, soil N2O fluxes fluctuated between 11.9 and an extremely high value of

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423.5 g N ha-1 d-1 under CH condition, and its average flux was much higher than the

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previous reported values in fields with N fertilization; for example, the average N2O emissions from a tea garden with a fertilizer application rate of 450 kg N ha-1 yr-1 was

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estimated as 50.3 g N ha-1 d-1 (Fu et al., 2012), while in our previous study (Xu et al., 2014), the soil N2O emission ranged from 24.8 to 49.0 g N ha-1 d-1 upon the application of urea. High observed N2O fluxes under different treatments may also be ascribed to high temperature in the third quarter, because the increased soil temperature may lead to higher soil respiration rate and promote the microbial metabolism, then accelerate the movement of produced N2O within the soil matrix (Yin et al., 2019). It has been reported that soil temperature above 10℃ helps to generate N2O (Ma et al., 2010) when the average ambient temperature during our experiment was above 30℃ in the daytime, which may greatly accelerate N2O

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emissions. Besides, soil moisture is one of the major driving forces behind N2O emissions (Fu et al., 2012). Dobbie and Smith (2001) found that the soil N2O emissions increased by 30 times as the water filled pore space (WFPS) increased from 60% to 80%, while the maximum N2O emission rates may occur when the soil moisture level is 90% WFPS (Ruser et al., 2006). Therefore, frequent irrigation

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throughout the pot experiment may also contribute to higher N2O emissions. Furthermore, the effect of pH on N2O emission cannot be ignored. Low pH is likely to

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be responsible for the boost of N2O emission since Russenes et al. (2016) showed that

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decreasing pH would impede the denitrifiers to synthesize N2O reductase enzyme

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efficiently. Similarly, Jones et al. (2014) found that low pH could eliminate the

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microbes lacking the genes for N2O reductase expression, which may explain why the

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N2O fluxes increased under CH treatment with low pH, while decreased under EH treatment. Nevertheless, opinions are not uniform. For instance, increased pH will

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enhance the nitrite accumulation in soil, which can serve as a favorable substrate for N2O production (Tierling and Kuhlmann, 2018). In general, we are in no position to determine the correlation between environmental variables and N2O fluxes in the present study as they are associated with more sophisticated patterns, further studies are ongoing to draw an objective evaluation. It is worth restating that the results presented here confirmed our preliminary hypothesis that LDSW can increase crop production, reduce N2O emissions, and improve soil physiochemical properties. This implied that LDSW can be regarded as an alternative agricultural nutrient source for synthetic N fertilizers, which appears to

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be the case, although its potential environmental risks remain unknown. Last but not least, careful inspection of Fig. 3 reveals that not only did the EH treatment exhibit a much lower average N2O flux than SW and CH treatments, this flux was even lower than that observed for CL and EL treatments with a lower level of N input. These results raised a fundamental question that where did the N go under EH treatment? In

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root zones, N commonly loses via NH3 volatilization, denitrification and crop uptake, and the mechanisms behind the lower N2O release in EH treatment can be attributed

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to NH3 volatilization, lower N2O generation, enhanced conversion of N2O to N2 or

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mixed factors (Xu et al., 2018). To identify the potential mechanisms, the responses of

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corresponding key functional genes for nitrogen cycle (including ammonium

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oxidation and denitrification) to different fertilizers were investigated.

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3.4 Quantification of functional genes for each treatment The microbial community and enzyme activities involved in nitrogen cycle are

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strongly influenced by N application (Xue et al., 2006). As presented in the bar chart of Fig.4a, the gene regulating ammonium oxidation, i.e. amoA, was quantified in both ammonium oxidizing bacteria (AOB) and archaea (AOA). Under unfertilized condition CK, the mean copy numbers of amoA in AOA and AOB were 1.37×107 and 0.23×107 /g dry soil, while the denitrifying genes nirK, nirS and nosZ were 1.45×107, 1.41×106 and 1.41×106 copies /g dry soil, respectively. After the addition of nutrients, AOA amoA was significantly suppressed while the other four genes were affected to varying degrees. In short, SW and EH treatments increased all genes copy numbers except AOA amoA remarkably but effects from CL, CH and EL treatments were

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negligible as compared to CK. It is worth pointing out that high application rate of LDSW increased the copy number of AOB amoA to 3.70×107, that of nirK to 19.41×107, that of nirS to 11.22×106 and that of nosZ to 18.05×106 copy numbers /g dry soil, respectively. In other words, EH treatment resulted in the highest abundance of AOB amoA, but at the same time, its copy numbers of nirS and nosZ genes were

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also the highest among treatments. The responses of these functional genes in all treatments were very similar to those previously reported.

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Ammonium oxidation is the origin of N2O generation, and AOA are reported to

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be ubiquitous in soil, but they are inert and do not involve in NH4+ oxidation and N2O

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production in agricultural soils (Huang et al., 2014), also Xu et al. (2018) reported that

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the application of urea or biofertilizer did not influence the abundance of AOA amoA

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gene copy numbers. Although Prosser and Nicol (2012) emphasized an exception that AOA play a predominant role in nitrification in the acidic soils, it was observed that

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the abundance of AOA amoA gene was significantly decreased with the addition of nutrients irrespective of the treatments, which may be due to the selective force of salinity or pH during the pot experiment. The substantial increase of AOB amoA reflected a strong ammonium oxidation activity under CH treatment (6.5 times higher than CK, p=0.19), however, genes other than amoA were not significantly different between CK and CH treatments, which would ultimately strengthen the transformation from ammonium to nitrite or nitrate, as well as the generation of N2O, these are supported by the presented results in Fig. 2 and Fig. 3. Consequently, we can draw an unequivocal conclusion that the high fluxes of N2O emissions induced by

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applying synthetic N fertilizers (NPK and urea) in this study were originated from the first stage of nitrification, i.e., NH4+ to NH2OH to NO2– or NO3– (Huang et al., 2014). By contrast, the addition of high-level LDSW largely affected the functional genes abundance. Although the AOB amoA gene in EH group was significantly elevated, which was 2.4 times higher than that in CH, the copy numbers of nitrite reductase

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genes (nirK/nirS) and nitrous oxide reductase gene (nosZ) in EH were also significantly increased, the same was true for the changes of SW treatment. Therefore,

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these consequences could perfectly decipher the pathway of N under EH treatment

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and explain why EH resulted in even lower N2O fluxes than the EL treatment. The Fig.

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4b performed a conceptual sketch of the nitrogen cycles under CK, CH and EH

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treatments to more intuitively present the dynamic changes of their functional genes.

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In addition, the role of plants should not be overlooked, since their roots can secrete various organic compounds as the carbon and energy sources for soil microorganisms,

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while the metabolism of these compounds would reduce oxygen levels and further enhance the expression of nitrogen oxide reductases in the soil matrix (Wertz et al., 2009).

The above results demonstrated that applying LDSW could effectively alleviate the N2O release from soil because of the reinforced denitrification. Furthermore, put aside the intrinsic factors of the soil (e.g. indigenous microorganism), LDSW or more broadly, the anaerobic digestates can be classified as a biofertilizer due to their abundant microbes. The application of biofertilizers can introduce exogenous microorganisms into the soil systems, promote root development, induce resistance to

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abiotic stresses, and propel the processes of nitrogen cycle (Harman et al., 2004), while chemical fertilizers cannot provide these benefits. On the other hand, shifts in functional genes abundance may imply changes in microbial community structure, particularly in the denitrifier community (Xu et al., 2018), while the nitrous oxide reductase gene nosZ is an important biomarker for denitrifying microorganisms.

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Moreover, investigating the effects of N fertilizers on the structure and diversity of denitrifying microbes in farmland is beneficial to provide an important theoretical

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basis for the sustainable development of agriculture. Therefore, we chose nosZ

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harbored by N2O reducing bacteria to inspect the community structure of N2O

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reducers under different treatments via high-throughput sequencing technology.

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3.5 Shift of N2O reducing microbial community composition

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Environmental stimuli are strong driving forces on the phylogenetic and physiological alternations of soil bacterial community, and high-throughput

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sequencing enabled a more detailed look than ever before at the microbial community structure. In the present study, high-throughput sequencing of soil N2O-reducing microbial communities was performed. Could different types of N fertilizers account for differences in the structure of N2O-reducing microbial community such as previously reported by Xu et al. (2018)? As compared to CK treatment, the α-diversity including Chao 1, observed species, PD whole tree and Shannon index of N2O-reducing microbial community for SW and EH treatments were all significantly enhanced (Table 3, P < 0.05). In contrast, the Chao 1 and Shannon index of CH and CL treatments were significantly higher than

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those of CK, while the observed species and PD whole tree were similar among these three treatments. In addition, the α-diversity except PD whole tree were all significantly affected by EL treatment according to the one-way ANOVA analysis, compare to CK. It also should be noted that EH induced the highest α-diversity indices and OTUs numbers (data not shown) among all treatments, suggesting the

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application of high-level LDSW can enhance the abundant and diversity of the members of N2O-reducing bacterial microbiota. A large quantity of studies was

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conducted to investigate the relationship between nutrient additions and biodiversity

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responses, for instance, Pascual-García and Bastolla (2017) found that the nutrients

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supply could support biodiversity when the interspecific competitions among soil

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microbes were weak. The results presented here are concordant with earlier work

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showing that both the application of urea and starch-wastewater-derived biofertilizer (inoculated with Trichoderma viride) can significantly lift up the bacterial abundance

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and diversity (Xu et al., 2018). On account of previous long-term fertilization, it is speculated that the microorganisms in the soil used in the present study were highly tolerant to and, at the same time, in great need of nitrogen. Therefore, the addition of nutrients after a long time without fertilization could stimulate and enhance the interactions among microorganisms to adapt to the altered environmental conditions. Hitherto, N2O-reducing bacteria are the only known biotic sink for N2O in the environment, and they are strongly related to the fate of N2O released from soil (Xu et al., 2018). Proteobacteria was the most abundant phylum within the N2O-reducing bacterial community, accounting for over 99.5% of the total bacteria in all soil

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samples, while the rest of bacteria was unclassified (data not shown). Furthermore, a heat map was conducted on MORPHEUS online software (available on https://software.broadinstitute.org/morpheus) with the identified 29 bacterial genera. As can be seen in Fig. 5, the addition of different fertilizers, to a great extent, altered the relative abundance of the N2O-reducing bacteria at genus level. Hierarchical

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cluster analysis on the basis of Euclidean distance and group average was also performed to observe how similar the changes of bacterial community were under

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different treatment conditions. Additionally, a relative color scheme was employed in

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Fig. 5, that is the values were converted to colors based on the maximum and

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minimum values in each row.

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Bradyrhizobium and Mesorhizobium were the two predominant genera

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irrespective of the treatments, and this finding is in accordance with our previous report using soil from the same study site (Xu et al., 2018). In the CK treatment,

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Mesorhizobium and Bradyrhizobium constituted 28.24% and 52.79% of all detected bacterial sequences, respectively. Moreover, in comparison with CK, the proportion of Mesorhizobium increased significantly while that of Bradyrhizobium declined sharply under the other treatments, that is, all bacterial communities were shifted from Bradyrhizobium-dominant to Mesorhizobium-dominant. Shah and Subramaniam (2018) reviewed that microorganisms from the Bradyrhizobium genus are playing crucial roles in the nitrogen cycle and they are the most ubiquitous bacteria in the soil across the world. Therefore, they suggested Bradyrhizobium could be considered as an eco-toxicity pointer based on its prevalence and environmental sensitivity (Shah

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and Subramaniam, 2018). On top of that, both Bradyrhizobium and Mesorhizobium are classified as members of the rhizobium, and numerous studies in literature validate its ability to fix atmospheric N2 and promote crop growth (Çakmakçi et al., 2006). In this study, the addition of nutrients had adverse effects on Bradyrhizobium, presumably due to the changed soil physicochemical properties, or they were

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outcompeted by Mesorhizobium. Heat-map analysis indicated that the changes of bacterial community under CH and SW treatments were similar, while EH treatment

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influenced the bacterial community inimitably. Achromobacter, Azospirillum,

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Oligotropha, Paracoccus, Shinella Pseudogulbenkiania were relatively abundant

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genera (>0.5%) among the microbiota in all treatments. More specifically, CH

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treatment decreased the relative abundance of Achromobacter, Bradyrhizobium,

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Alcanivorax, Herbaspirillum, Ochrobactrum, Pseudogulbenkiania, Massilia and Rhizobium, while increased that of Ralstonia. By comparison, EH treatment resulted

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in an apparently increased in the relative abundance of Brucella, Hoeflea, Acidovorax, Halomonas, Alkalilimnicola, Cupriavidus, Rhodanobacter. These denitrifiers, some of which were defined to be relevant to denitrification as well as N2O reduction (Verbaendert et al., 2011; Xu et al., 2018), may be affiliated with the mitigation of N2O after treating with EH as compared to CH (Fig.3). It is also worth mentioning that the Alkalilimnicola, a genus for alkaliphilic bacteria (Yakimov et al., 2001), was only detected in the LDSW treatments, which was in line with the results of soil pH (Table 2). Although our results were consistent with studies performed under different conditions, more work is required to better understand which member of the

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community is the most important player in the production or mitigation of GHGs under the field of synthetic biology, and to determine which environmental variables are major contributors to changes in the denitrifier community with redundancy analysis. 4. Conclusions

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In conclusion, the application of LDSW had the potential to guarantee high crop yields while reducing negative environmental impacts such as N2O emissions and

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NO3– leaching. Therefore, reuse of LDSW or general anaerobic digestates in

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agriculture should be strongly encouraged because it could reduce the use of chemical

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fertilizers and associated N losses, alleviate the problem of water scarcity in

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agriculture, and save the energy for further wastewater treatments. Further studies are

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ongoing to determine the optimal LDSW application rate and screen out the

development.

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functional microorganisms in the soil systems to bolster future sustainable agricultural

5. Acknowledgements

This work was supported by the Knowledge Innovation Program of Shenzhen (JSGG20171012143231779), the National Science Fund Projects (No. 31700429) and the Key State Science and Technology Program of China (No. 2015ZX07203-007).

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Journal Pre-proof Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

☐The authors declare the following financial interests/personal relationships which

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may be considered as potential competing interests:

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Fig. 1. Fresh weight of harvested I. aquatica Forsk under different fertilization conditions during three growth periods.

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CK: control group, no fertilization; SW: sweet potato starch wastewater treatment; CL and CH: chemical fertilizer treatments at low and high nitrogen application rates; EL and EH: ABR effluent treatments at low and high nitrogen application rates. Data presented are means of triplicates ± SD and differences among means were tested using one-way ANOVA with Duncan’s tests. Letters above the bars (α, a, A…) indicated the significant differences between treatments for different growth periods (p<0.01).

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Fig. 2. Soil nitrogen contents under different fertilization conditions during three growth periods. Mean values with their SD (n = 3) are presented. Data with different letters are significantly different within the six treatments (P < 0.01; one-way ANOVA with Duncan’s tests).

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Data presented are means of triplicates ± SD.

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Fig. 3. N2O fluxes under different fertilization conditions during the pot experiment.

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Fig. 4. Differences in functional gene copy numbers under different treatments after the 12-week experiment period. The functional gene copy numbers were determined through quantitative PCR. (a) Mean values with their SD (n = 3) are presented. Differences in functional gene abundances were tested between treatments according to the one-way ANOVA analysis, and the significance levels were set at P < 0.01; (b) Conceptual sketch of the dynamic changes of functional genes in nitrogen cycles under CK, CH and EH

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treatments.

Fig. 5. Relative abundance of N2O-reducing bacteria at genus level under different treatments after the 12-week experiment period.

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Table 1. Fertilization strategies for different treatments throughout the pot experiment.

--

SW

--

--

CL

400

--

CH

400

--

EL

200

200

EH

--

400

--

--

0.80 + 0.258

0.80 + 0.121

0.80 + 0.772

0.80 + 0.498

0.80 + 0.455

--

--

--

--

--

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400

0.80 + 0.100

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CK

-p

ABR effluent (ml pot-1)

--

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Treatment

Deionized water (ml pot-1)

NPK + urea fertilizer (g pot-1) First Second Third growth growth growth period period period ----

--

Total nitrogen input (g N pot-1) First Second Third growth growth growth period period period 0

0

0

0.480

0.352

0.332

0.240

0.176

0.166

0.480

0.352

0.332

0.240

0.176

0.166

0.480

0.352

0.332

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Note: first growth period: from May 24th to June 23th; second growth period: from June 23th to July 17th; third growth period: from July 17th to August 17th.

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CK: control group, no fertilization; SW: sweet potato starch wastewater treatment; CL and CH: chemical fertilizer treatments at low and high nitrogen application rates; EL

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and EH: ABR effluent treatments at low and high nitrogen application rates.

Journal Pre-proof Table 2. Soil pH, EC, and DOC for different treatments pH

EC (μS cm-1)

DOC (mg C kg-1 DW)

CK

4.10±0.16a

86.83±5.00a

192.62±19.78a

SW

4.72±0.54b

387.67±20.13e

514.14±14.86d

CL

3.81±0.16a

213.00±11.14c

177.36±7.40a

CH

3.58±0.05a

119.50±14.60b

227.33±2.79b

EL

5.96±0.39c

319.33±10.69d

260.15±13.43c

EH

6.94±0.07d

360.67±2.08e

279.82±1.79c

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Treatment

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Data presented are means of triplicates ± SD and differences among means were

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tested using one-way ANOVA with Duncan’s tests. The difference significance in the

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group was expressed in lowercase letters a, b, c, d and e (p < 0.01). Among them, EC

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respectively.

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and DOC are abbreviations for electrical conductivity and dissolved organic carbon,

Journal Pre-proof Table 3. Comparison of within-sample diversity (α-diversity) of Chao 1, Observed species, PD whole tree and Shannon index in different treatments. Chao 1

Observed species

PD whole tree

Shannon index

CK

1794.8±182.2a

852.5±154.9a

32.1±3.1a

8.6±0.6a

SW

2457.1±107.5b

1134.0±43.8b

37.4±1.4b

9.5±0.1b

CL

2553.2±90.7b

1050.5±7.8ab

35.5±0.2a

9.3±0.0b

CH

2409.9±165.0b

1120.5±98.3ab

36.8±3.8ab

9.4±0.2b

EL

2708.2±92.8c

1213.0±22.6c

35.3±0.6a

9.7±0.0c

EH

3080.5±44.5d

1302.5±21.9d

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Treatment

9.8±0.1c

-p

41.0±0.2b

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tested using one-way ANOVA with Duncan’s tests. The same letter in one column

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treatments (p<0.05).

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indicates that the differences in the parameter are not significant between the

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HIGHLIGHTS 1. The application of digested starch wastewater produced superior crop yields. 2. Digested starch wastewater alleviated soil acidification and nitrogen accumulation. 3. Digested starch wastewater strongly mitigated nitrous oxide emissions. 4. Digested starch wastewater increases the abundance of nirK, nirS and nosZ genes.

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5. Changes of denitrifier community were linked to the reduced nitrous oxide

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emissions.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5