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\begin{document}

\title{Crop rotation combined with controlled-release fertilizer promoted the
utinization of the reclaimed land along Yanze River through improving
soil fertility and nutrients use efficiency}



\author[1]{Xuebin Xu}%
\author[1]{Fei Ma}%
\author[1]{Jianmin Zhou}%
\author[1]{Changwen Du}%
\affil[1]{State Key Laboratory of Soil and Sustainable Agriculture}%


\vspace{-1em}



  
  \date{May 18, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Although fertilization of controlled-release fertilizer (CRF) and crop
rotation have been shown the contribution to improving yield, nutrient
use efficiency, and soil fertility, their interactions on the quality of
relcalimed land remains unclear. Hence, a field experiment was conducted
in a reclaimed land along Yangze River to investigate their
interactions. Results indicated that application of bulk blending urea
(BBU) of conventional urea and controlled-release urea (CRU) with
appropriate dosage and frequency increased the rice yield and nitrogen
agronomic efficiency (NAE). Crop rotation also improved the rice yield
and NAE through enhancing the retention capability of fertility. Crop
rotation combined with fertilization significantly increased the soil
pH, organic carbon (SOC), total N (TN), and permanganate oxidizes carbon
(POXC). The rice-green manure (RG) rotation improved soil pH and TN
most, and the rice-rape (RR) rotation improved SOC most. Fertilization
of conventional urea and BBU both significantly increased the labile SOC
functional groups and reduced the the stabled SOC functional groups
under RG rotation. Under RR rotation, however, only fertilization of
conventional urea increased the labile SOC functional groups and reduced
the the stabled SOC functional groups. The rice-wheat (RW) rotation
showed no significant effects on the changes in soil organic functional
groups. The changes in soil properties had significant effects on
improving rice yield or NAE under RG and RR rotations instead of RW
rotation. The findings suggested that BBU combined with crop rotations
could make good use of reclaimed land through improved nutrient use
efficiency and soil fertility.%
\end{abstract}%



\sloppy


\textbf{1. Introduction}

An extreme imbalance between the arable area and population exists in
China which has 20 percent of the world's population but only 7 percent
of the world's arable land (Piao et al., 2010). With the rapid
socio-economic development, more and more arable lands are occupied by
industry and urban construction, resulting in a sharp decrease in the
arable land (Li, Liu, \& Yang, 2018). So far, under the pressures of
food safety and the arable land red line continued to increase, enclose
tideland for cultivation are widely used to increase the arable land and
ensure the adequate production of grain (L. Chen et al., 2020; Li et
al., 2018; J. Zhao et al., 2020). However, the soil in reclamation land
usually is seriously impoverished which mainly manifests as salination,
soil nutrient deficiency, extremely low organic matter content , etc.
The high fertility of the soil is the basis for maintaining a high yield
of crops (Stewart, Pierzynski, Middendorf, \& Prasad, 2020). Therefore,
it is necessary to take a series of measures to improve soil fertility
and reduce the risk of crop failure for reclamation land.

Application of chemical fertilizer is the most common way to improve the
permeability of soil structure and provide abundant nutrients for crops
to maintain grain production (Huang et al., 2019). However, traditional
fertilizers, especially nitrogen (N) fertilizer, are extremely
water-soluble and are easily transferred and transformed between the
soil-water-atmosphere environment according to the soil structure and
property (Fu, Duan, Zhu, Gao, \& Xu, 2021). The soil in reclamation land
is mainly sandy loam with lower fertility holding capacity, resulting in
the inefficient of traditional fertilizers. Moreover, unreasonable
application of fertilizer has the risk of the non-point source due to
the losses of reactive N to the surface water, groundwater, and
atmosphere (J. Chen et al., 2018; Liu et al., 2021; Yang \& Lin, 2019).
Coated controlled-release fertilizer (CRF) is prepared by coating the
conventional fertilizer with a hydrophobic material and it has the
characteristics of controlled nutrient release (Shen, Du, Zhou, \& Ma,
2017). Nutrients in coated CRF are regulable to supply for crop growth
according to the requirement by adjusting the amount and property of
coating (Tomaszewska \& Jarosiewicz, 2002). The improvements of the
water efficiency, N-use efficiency, and grain yield of maize by
application of controlled-release urea (CRU) combined with subsoiling
had been confirmed by Hu et al. (2013) in northern China. Guo et al.
(2019) also demonstrated that the CRU treatment decreased the annual
NH\textsubscript{3} volatilization, CH\textsubscript{4} emission by
64.8\%, 19.7\%, and 35.2\%, respectively in a paddy field. Gao et al.
(2021) showed that the CRF treatment significantly improved soil
aggregate characteristics and increased humic acid, fulvic acid,
lignin-like molecules, and protein-like molecules content. Therefore,
CRF has the potential to improve fertilizer use efficiency, soil
structure, and soil fertility and relieve a series of environmental
problems, such as eutrophication and groundwater pollution. However, the
effects of CRF on the improvement of soil fertility and the change in
soil organic and mineral components in the soil from reclamation land
are few studied.

Crop rotation has been applied for millennia across China which mainly
includes the maize-wheat rotation, peanut-wheat rotation, rice-rape
rotation, rice-wheat rotation, and rice-green manure rotation (Zeng et
al., 2016). As an environmentally friendly strategy, crop rotation can
adequately control nutrients, water, weeds, pests, and diseases, as well
as maintain soil structure and fertility which increases the
productivity of the land (Bender, Wagg, \& van der Heijden, 2016;
German, Thompson, \& Benton, 2017). For example, Ghosh et al. (2020)
indicated that replacing wheat with chickpea in the rice-wheat rotation
increased grain yield by 5-8\%. A previous study also suggested that the
adoption of 2- and 4-year of crop rotations in rain-fed environments
could result in high yield compared with continuous cropping (Sindelar,
Schmer, Jin, Wienhold, \& Varvel, 2016). Malobane, Nciizah, Mudau, and
Wakindiki (2020) indicated that the sweet sorghum-grazing vetch-sweet
sorghum rotation increased ammonium
(NH\textsubscript{4}\textsuperscript{+}-N) and nitrate
(NO\textsubscript{3}\textsuperscript{-}-N) by 3.42\% to 5.98\%,
respectively. A 9-year
corn-wheat-corn-wheat-corn-wheat-alfalfa-alfalfa-alfalfa
(\emph{Lotuscorniculatus} L.) rotation indicated that rotation had
positive effects on soil organic carbon (SOC), total nitrogen (TN), and
soil microbial biomass C, N, and activity (Giacometti et al., 2021).
Recently, a meta-analysis across China had demonstrated that crop
rotation increased yields by 20\% compared to continuous monoculture and
the improvement performed better in coarse or medium soil texture and
medium level of initial SOC and at low N fertilization rate (J. Zhao et
al., 2020). Even so, the impacts of the combination of crop rotation and
CRF application on grain yield, soil fertility, and changes in soil
organic and mineral components remain unclear, especially in barren
soil.

A field trial of three types of crop rotation (rice-green manure,
rice-rape, and rice-wheat) combined with different N fertilizer
treatments was conducted in a reclamation land. The types of N
fertilizer included conventional urea and bulk blending urea (BBU) of
conventional urea and CRU. Soil organic and mineral components were
characterized by Fourier transform infrared photoacoustic spectroscopy
(FTIR-PAS) and mid-infrared attenuated total reflection spectroscopy
(FTIR-ATR). The main objective of this study was to investigate the
influences of fertilization, crop rotation, and their interaction on
rice grain yield, dynamics of soil inorganic N and plant N uptake, soil
properties, and soil organic and mineral components.

\textbf{2. Materials and methods}

\emph{2.1. Experiment site and design}

The field experiment was conducted in a reclamation land in Zhangjiagang
city, Jiangsu province (31\selectlanguage{ngerman}°57\selectlanguage{english}'N, 120deg46\selectlanguage{english}'E, Fig. 1). The soil is composed
of alluvium from the Yangtze River and classified as Fluvo-aquic
according to the Chinese Soil Taxonomy (Gong et al., 2001). The basic
soil chemical properties are as follows: pH (H\textsubscript{2}O)
8.00+-0.30; SOC 3.86+-1.35 g kg\selectlanguage{english}\textsuperscript{-1}; TN 0.41+-0.16 g
kg\selectlanguage{english}\textsuperscript{-1}; NH\textsubscript{4}\textsuperscript{+}-N
1.36+-0.34 mg kg\selectlanguage{english}\textsuperscript{-1};
NO\textsubscript{3}\selectlanguage{english}\textsuperscript{-}-N 11.58+-5.37 mg
kg\selectlanguage{english}\textsuperscript{-1}; available phosphorus (AP) 20.57+-12.67 mg
kg\selectlanguage{english}\textsuperscript{-1}; and available potassium (AK) 7.34+-1.95 mg
kg\selectlanguage{english}\textsuperscript{-1}.

A plot design with replicates was adopted with 60 m x 35 m (Fig. 1).
Rice-green manure (RG), rice-rape (RR), and rice-wheat (RW) rotations
were included. Five fertilization treatments were set as follow: without
N fertilizer (WN), farmer's conventional urea fertilizing practice with
a thrice-split application (CU), single-dose application of BBU with the
conventional amount of N (CB1), twice-split application of BBU with the
conventional amount of N (CB2), single-dose application of BBU with 20\%
reduction of N (RB1), and twice-split application of BBU with 20\%
reduction of N (RB2). The BBU consisted of 75\% CRU and 25\%
conventional urea. The CRU coated with 10\% waterborne polyacrylate was
purchased from Jiangsu Issas New Fertilizer Engineering \& Technology
Co., Ltd., China and had an N content of 42\% and an N release longevity
of 3 months. The farmer's conventional N application rates are 300 and
270 kg N ha\selectlanguage{english}\textsuperscript{-1} for rice and wheat, respectively. There
was no fertilization during the rape oil and green manure seasons.
Superphosphate, potassium chloride, zinc sulfate, and silicon fertilizer
were incorporated into the 10\selectlanguage{english}-15 cm soil layer for all treatments at
rates of 75 kg
P\textsubscript{2}O\textsubscript{5}ha\selectlanguage{english}\textsuperscript{-1}, 120 kg
K\textsubscript{2}O ha\selectlanguage{english}\textsuperscript{-1}, 3 kg Zn
ha\selectlanguage{english}\textsuperscript{-1}, and 0.8 kg SiO\textsubscript{2}
ha\selectlanguage{english}\textsuperscript{-1} as basal fertilizers in rice and wheat seasons.

\emph{2.2. Crop culture and management}

Two rice seasons and one crop rotation season were conducted from June
2019 to November 2020. The field had always been cropped with rice-wheat
rotation before the experiment. The paddy rice (\emph{Oryza sativa} L.)
with the variety of ``Nanjing 46'' was planted on June 14, 2019, and
harvested on November 7, 2019, for the first season (Rice2019), and on
June 13, 2020, and harvested on November 17, 2020, for the second season
(Rice2020). The winter wheat (\emph{Triticum aestivum} L.) with the
variety of ``Yangmai 13'' was seeded on November 17, 2019, and harvested
on May 22 in 2020 (Wheat). The oilseed rape (\emph{Brassica napus} L.)
with the variety of ``Huayouza No.8'' and the green manure of Chinese
milkvetch (\emph{Astragalus sinicus} L.) with the variety of ``Zhezi
No.5'' were seeded at the same time as wheat. Straws of rice and wheat
were turned over after grain harvesting by a rotary cultivator. Shoots
of oilseed rape and Chinese milkvetch were also turned over after
maturing. Crops were planted by a planter with the conventional plant
density. The base fertilizer was incorporated into the 10\selectlanguage{english}-15 cm soil
layer before planting and the topdressing fertilizer was broadcasted
artificially. Conventional weeding, irrigation, and UAV plant protection
were carried out to maintain crop growth.

\emph{2.3. Sampling and chemical analyses}

Soil samples were collected from each plot before the experiment and
after the rice had been harvested to analyze the basic soil properties
including pH, SOC, TN, NH\textsubscript{4}\textsuperscript{+}-N,
NO\textsubscript{3}\selectlanguage{english}\textsuperscript{-}-N, AP, AK, permanganate oxidizes
carbon (POXC), and other available medium and trace elements. Soil
samples were collected for determining
NH\textsubscript{4}\textsuperscript{+}-N and
NO\textsubscript{3}\selectlanguage{english}\textsuperscript{-}-N contents at the seeding,
tillering, elongation, earing, flowering, and maturation stages,
respectively. Quadruplicate soil samples from a depth of 0\selectlanguage{english}-20 cm for
each plot were collected and mixed thoroughly. The soil samples were
air-dried at room temperature and then sieved to \textless{} 2 mm and/or
\textless{} 0.15 mm after removing the residues and plant roots. Soil pH
was measured with a pH meter (PH-21, Sartorius, Goettingen, Germany) in
a 1:2.5 mass: volume soil/water suspension (Thomas, 1996). SOC content
was determined using the potassium dichromatic oxidation titration
method (Walkley \& Black, 1934). TN content was determined using the
Kjeldahl method (Pansu \& Gautheyrou, 2006). AP was extracted with
sodium bicarbonate solution and then was measured by the molybdenum
antimony blue colorimetric method (Olsen, 1954). AK was extracted with 1
N ammonium acetate and then was determined by flame spectrometry
(Jackson, 1958). POXC was measured using the colorimetric method after
oxidating by 0.02 M KMnO\textsubscript{4} (Blair, Lefroy, \& Lisle,
1995). Available medium and trace elements were extracted with
DTPA-CaCl\textsubscript{2}-TEA solution and then were measured using an
ICP-OES (ICAP7000, ThermoFisher, USA) (Jackson, 1958). Soil
NH\textsubscript{4}\textsuperscript{+}-N and
NO\textsubscript{3}\selectlanguage{english}\textsuperscript{-}-N were extracted with 2 M KCl and
then were measured using a flow analyzer (San\textsuperscript{++}System,
SAKLAR, Netherlands). The shoot and/or grain of rice and wheat were also
collected at seeding, tillering, elongation, earing, flowering, and
maturation stages, respectively. The oven-dried and ground shoot and
grain were digested with sulfuric acid-hydrogen peroxide, and the N
content was determined by the Kjeldahl method. The grain yield and the
grain moisture were measured during harvesting. Grain yield was adjusted
to standard moisture of 15\% for rice and 12\% for wheat. The N
agronomic efficiency (NAE, kg kg\selectlanguage{english}\textsuperscript{-1} N) was calculated
as follow:

\begin{equation}
\begin{matrix}\text{NAE}=\frac{Y_{N}-Y_{0}}{F_{N}}\#\left(\ AUTONUM\ \ \backslash*\ Arabic\ \right)\\
\end{matrix}\nonumber \\
 \end{equation}

where \(\mathrm{Y}_{\mathrm{0}}\) and \(\mathrm{Y}_{\mathrm{N}}\) (kg
ha\textsuperscript{-1}) are the dry grain yields without N fertilizer
and with N treatments respectively, \(\mathrm{F}_{\mathrm{N}}\) (kg N
ha\textsuperscript{-1}) is the N fertilization rate.

\emph{2.4. Spectral acquisitions}

Soil FTIR-PAS spectra were measured using an FTIR spectrometer (Nicolet
6700, ThermoFisher, USA), equipped with an MTEC model 300 PA accessory.
A nitrogen purge was continuously done in the optical system to
eliminate the interferences from CO\textsubscript{2} and water vapor.
Approximately 5 g soil samples were placed in the photoacoustic cell and
the dry helium was then purged into the cell for 10 s. The spectrum of
the reference black carbon was used as background to correct the soil
spectra. Each spectrum between the wavenumbers of 4000 and 650
cm\textsuperscript{-1} with a resolution of 8 cm\textsuperscript{-1} was
finally recorded by averaging 32 successive scans under moving mirror
velocity of 0.32 cm s\textsuperscript{-1}.

Soil FTIR-ATR spectra were acquired using an attenuated total
reflectance infrared spectrophotometer (Agilent 4300, Agilent
Technologies Inc., USA). Approximately 2 g soil samples were placed on
the FTIR-ATR crystal and then were compressed for measuring. Each
spectrum was finally recorded by averaging 64 successive scans between
the wavenumbers of 4000 and 650 cm\textsuperscript{-1} with a resolution
of 0.466 cm\textsuperscript{-1}. A background spectrum of air was
measured to correct the soil spectra before sample screening.

\emph{2.5. Statistical analyses}

All soil spectra were smoothed and normalized before spectral analysis
in MATLAB R2020b (The Math Works, Natick, USA). A one-way analysis of
variance (ANOVA) was used to analyze the effects of various treatments
on grain yield, NAE, changes in soil properties, soil
NH\textsubscript{4}\textsuperscript{+}-N and
NO\textsubscript{3}\textsuperscript{-}-N contents, and plant N content.
Differences between treatments were determined by comparing their means
using the least significant difference (LSD) at the 0.05 probability
level. A two-way ANOVA was applied to evaluate the main and interactive
effects of crop rotation and fertilization on grain yield, NAE, changes
in soil properties, soil NH\textsubscript{4}\textsuperscript{+}-N and
NO\textsubscript{3}\textsuperscript{-}-N contents, and plant N content.
A pairwise samples test was conducted to compare the significant changes
in soil properties and characteristic spectral bands after various
treatments. Principal component analysis (PCA) was performed to
illustrate the internal structure of spectra. A two-way permutational
multivariate analysis of variance (PERMANOVA) was applied to evaluate
the effect of crop rotation, fertilization, and their interaction on the
changes in spectral structures. Regressions between spectral data and
SOC, TN, and POXC were built by the partial least squares regression
(PLSR) model. The five-fold cross-validation was performed to obtain the
optimal number of latent variables in the PLSR model. The variable
importance in projections of spectral bands in the PLSR model was used
for identifying the great changes in molecular structure for soil
organic matter and TN. Structural equation modeling (SEM) was applied to
determine the direct and indirect effects of selected variables on grain
yield and NAE based on known correlations. The chi-square,\emph{P}
-value, root-mean-square error of approximation (RMSEA), and good fit
index (GFI) were used to evaluate the model fitness. All data
processing, statistical analysis, and visualization were implemented in
R 4.1.0 software (R Development Core Team, 2018).

\textbf{3. Results}

\emph{3.1. Grain yield and}

\emph{nitrogen agronomic efficiency}

Under the RG rotation, RG-CB1 and RG-CB2 treatments only increased
inappreciable grain yields in both Rice2019 and Rice2020 seasons
compared with RG-CU (Fig. 2a). RG-RB1 treatment decreased the grain
yields in both Rice2019 and Rice2020 seasons, while the RG-RB2 treatment
increased the grain yield in the Rice2019 season. Under the RR rotation,
RR-CB2 treatment significantly increased the grain yield in the Rice2019
season compared with RR-CU. Both RR-RB1 and RR-RB2 treatments had
significantly lower grain yields than RR-CU in both Rice2019 and
Rice2020 seasons. Under the RW rotation, RW-CB2 treatment showed
significantly highest rice grain yield in Rice2019 season and wheat
grain yield in Wheat season. Grain yield was significantly affected by
fertilization in the Rice2020 season (Table S1, supplementary
materials). Crop rotation and the interaction between crop rotation and
fertilization had no significant effects on grain yield.

RG-RB2 and RR-RB2 treatments had the highest NAE in the Rice2019 season
(Fig. 2b). Under the RW rotation, both the RW-CB2 and RW-RB2 treatment
increased the NAE of rice than other treatments in the Rice2019 season.
Both the RW-RB2 and RW-RB2 treatments showed significantly higher NAE of
wheat than RW-CU. Crop rotation had a significant effect on rice NAE in
the Rice2020 season, while fertilization and the interaction between
crop rotation and fertilization had no significant effects (Table S1).

\emph{3.2.Dynamics of} \emph{soil inorganic nitrogen and plant nitrogen}

Soil inorganic N increased to the highest at the middle of the tillering
stage, then decreased to stability in the Rice2019 season (Fig. 3a). At
the middle of the tillering stage, RG-CU, RR-CU, and RW-CU had higher
soil inorganic N contents than other treatments, respectively (Table
S2). The rice plant under the treatments of BBU also had higher plant N
contents at tillering and elongation stages in the Rice2019 season (Fig.
3b, Table S4). In wheat season, soil inorganic N under RW-CU treatment
increased to the highest at the middle of the tillering stage, while
that under BBU treatments increased to the highest at flowering and
mature stages (Fig. 3a). Reduction of N decreased the plant N contents
of wheat at seeding stages (Fig. 3b). The dynamics of soil inorganic N
were significantly changed after crop rotation (Fig. 3a). Soil inorganic
N contents in all N treatments remained at a high level at seeding,
tillering, elongation, and flowering stages. The plant N of rice in all
N treatments were considerable at seeding, tillering, elongation,
flowering, and mature stages (Fig. 3b). Soil inorganic N contents were
significantly affected by crop rotation at elongation and flowering
stages and significantly affected by fertilization at seeding,
tillering, and mature stages in the Rice2020 season (Table S3). Crop
rotation, fertilization, and interaction between them both had
significant effects on rice plant N content at tillering and elongation
stages in the Rice2020 season (Table S5).

\emph{3.3. Changes in soil properties}

RG and RR rotations significantly increased soil pH under most
fertilization treatments, while RW rotation had no significant
influences on soil pH (Fig. S1a). In general, RG rotation increased soil
pH more than RR rotation (Fig. 4a). Crop rotation, fertilization, and
their interaction had significant effects on the changes in soil pH
(Table S6). Three rotation treatments significantly increased SOC and TN
under most fertilization treatments (Fig. S1b, c). The application of
BBU could facilitate the increase of SOC under RG and RW rotations (Fig.
4b) and TN under RG and RR rotations (Fig. 4c) compared with CU. Both
crop rotation, fertilization, and their interaction had no significant
effects on the changes in SOC and TN (Table S6). RG-CB1, RR-CU, RW-WN,
RW-CU, and RW-CB1 significantly altered the soil POXC contents (Fig.
S1d). The N treatments weakened the increase of POXC in comparison to WN
under RG rotation, while it facilitated the increase of POXC under RR
and RW rotations (Fig. 4d). Only the interaction between crop rotation
and fertilization showed a significant effect on the change in POXC
(Table S6). Soil AK and available Al, Fe, Cu, Zn were increased, while
soil available Ca, Mg, and Mn were decreased after crop rotation and
fertilization (Fig. S2). Soil AP had no significant change in most of
the treatments (Fig. S2). Crop rotation had significant effects on the
changes in soil AK and available Ca, Mg, Al, Mn, Zn. Fertilization had
significant effects on the changes in soil AP and available Ca, Mg, Al,
Mn, Fe, Cu. Interaction between crop rotation and fertilization had
significant effects on the changes in soil AP, AK, and available Mg, Al,
Mn, Fe, Cu (Table S6).

\emph{3.4. Soil FTIR spectra}

The FTIR-PAS spectra featured a broad peak at 3900-3700
cm\textsuperscript{-1} attributed to the stretching vibration (\selectlanguage{greek}ν\selectlanguage{english}) of O-H
from clay minerals (Table 1, Fig. 5a). A sharp peak of \selectlanguage{greek}ν\selectlanguage{english}O-H from clay
minerals at 3620 cm\textsuperscript{-1} in FTIR-ATR spectra was also
observed (Fig. 5b). The broadband ranged from 3600 to 3400
cm\textsuperscript{-1} attributed to \selectlanguage{greek}ν\selectlanguage{english}O-H from water, alcohols, phenols,
carboxyl, and hydroxyl groups and \selectlanguage{greek}ν\selectlanguage{english}N-H from amides was both found in
FTIR-PAS and FTIR-ATR spectra. The broadband at 3000-2800
cm\textsuperscript{-1} in FTIR-PAS spectra was dominated by \selectlanguage{greek}ν\selectlanguage{english}N-H from
aliphatic methyl and methylene groups. The overtone of \selectlanguage{greek}ν\selectlanguage{english}COH ranged from
2200 to 2000 cm\textsuperscript{-1} was derived from carbohydrates. The
broadband ranged from 1720-1600 cm\textsuperscript{-1} was associated
with \selectlanguage{greek}ν\selectlanguage{english}C-O from carboxylic acids and amides and \selectlanguage{greek}ν\selectlanguage{english}C-C from aromatics. The
band at 1570-1540 cm\textsuperscript{-1} in FTIR-ATR spectra was
dominated by \selectlanguage{greek}ν\selectlanguage{english}N-H and \selectlanguage{greek}ν\selectlanguage{english}C-N in plane from amide II. An obvious sharp peak
at 1515 cm\textsuperscript{-1} in FTIR-PAS spectra attributed to \selectlanguage{greek}ν\selectlanguage{english}C-C
from aromatics. The absorption band of
\selectlanguage{greek}ν\selectlanguage{english}CO\textsubscript{3}\textsuperscript{2-} from carbonates also was
confirmed at 1500-1300 cm\textsuperscript{-1} in FTIR-ATR spectra. The
shoulder at 1445-1350 cm\textsuperscript{-1} in FTIR-PAS spectra was
assigned to \selectlanguage{greek}ν\selectlanguage{english}C-H from methyls. The \selectlanguage{greek}ν\selectlanguage{english}C-O and bending vibration (\selectlanguage{greek}δ\selectlanguage{english}) of C-O
in FTIR-ATR were derived from polysaccharides, nucleic acids, proteins,
and carbohydrates. The FTIR-ATR showed an intensive peak at 990
cm\textsuperscript{-1} which was associated with \selectlanguage{greek}ν\selectlanguage{english}Si-O from clay
minerals. A shoulder at 915 cm\textsuperscript{-1} attributed to \selectlanguage{greek}δ\selectlanguage{english}Al-OH
from kaolinite and smectite.

The scatterplots of the first two PCA scores (PC1 and PC2) from FTIR-PAS
and FTIR-ATR spectra indicated an obvious separation between soil
samples before and after treatments (Fig. S5a, b). The PC1 and PC2
scores of soil FTIR-PAS spectra were mostly positive after treatments
and both the PC1 and PC2 had positive loadings at the wavenumbers of
\selectlanguage{greek}ν\selectlanguage{english}O-H, \selectlanguage{greek}ν\selectlanguage{english}O-H/\selectlanguage{greek}ν\selectlanguage{english}N-H, \selectlanguage{greek}ν\selectlanguage{english}C-C/\selectlanguage{greek}ν\selectlanguage{english}C-O, \selectlanguage{greek}ν\selectlanguage{english}C-C, \selectlanguage{greek}ν\selectlanguage{english}C-H, and \selectlanguage{greek}ν\selectlanguage{english}Si-O, (Fig. S5c),
indicating that these functional groups in soil increased after crop
rotation and fertilization. Soils after treatments mostly had negative
PC2 scores for FTIR-ATR spectra and had positive PC2 loading at the
wavenumbers of \selectlanguage{greek}ν\selectlanguage{english}CO\textsubscript{3}\textsuperscript{2-}and \selectlanguage{greek}ν\selectlanguage{english}Al-OH (Fig.
S5d), which suggested that soil CO\textsubscript{3}\textsuperscript{2-}
and Al-OH decreased after crop rotation and fertilization. We further
applied PCA on the differential spectra of FTIR-PAS and FTIR-ATR. Crop
rotation, fertilization, and their interaction had significant effects
on PCA scores for FTIR-PAS differential spectra, while only their
interaction had a significant effect on PCA scores of FTIR-ATR
differential spectra (Fig. 5c, d). An obvious separation between soils
after RG and RW rotations was observed according to PC1 for FTIR-PAS
differential spectra. PC1 showed high positive scores for soils after RG
rotation but high negative scores for soils after RW rotation (Fig. 6a).
In addition, PC1 had high positive loadings at the wavenumbers of
\selectlanguage{greek}ν\selectlanguage{english}C-C/\selectlanguage{greek}ν\selectlanguage{english}C-O and \selectlanguage{greek}ν\selectlanguage{english}C-C, and high negative loadings at the wavenumbers of
\selectlanguage{greek}ν\selectlanguage{english}O-H/\selectlanguage{greek}ν\selectlanguage{english}N-H (Fig. S5). This suggested that RG rotation increased the soil
functional group of O-H and N-H and decreased the soil functional groups
of C-C, C-O, and C-C (Fig. 6).

SOC, TN, and POXC contents had a commonly significant relationship with
the stretching vibrations of O-H (3900-3700 cm\textsuperscript{-1}) in
the PLSR model of FTIR-PAS. However, SOC content showed a unique
relationship with the stretching vibrations of C-C (1515
cm\textsuperscript{-1}) and POXC content presented a unique relationship
with the stretching vibrations of C-H (1445-1350 cm\textsuperscript{-1})
in the PLSR model of FTIR-PAS (Fig. 5a). For FTIR-ATR, SOC, TN, and POXC
contents were all significantly related to the stretching vibrations of
CO\textsubscript{3}\textsuperscript{2-} (1500-1300
cm\textsuperscript{-1}), C-O (1160 cm\textsuperscript{-1}), Si-O
(1030-950 cm\textsuperscript{-1}), and the bending vibrations of Al-OH
(915 cm\textsuperscript{-1}) in the PLSR model (Fig. 5b).

\emph{3.5. Structural equation model}

SEM analysis indicated that three crop rotation patterns showed the
different direct and indirect effects of fertilization on grain yield
and NAE (Fig. 7). Under RG rotation, fertilization had a directly
positive effect on NAE (0.453) but no significant effect on grain yield.
The change of pH showed a negative effect on NAE (-0.337). The change of
POXC presented negative effects on grain yield (-0.723) and NAE
(-0.776), respectively. Under RR rotation, fertilization showed a
directly negative effect on grain yield (-0.343) but no significant
effect on NAE. Both the changes of pH and SOC had positive effects on
grain yield and NAE under RR rotation. The change of POXC under RR
rotation presented lower negative effects on grain yield (-0.502) and
NAE (-0.427), respectively compared with that under RG rotation.
Fertilization had no significant effect on grain yield and NAE under RW
rotation. Only the change of SOC had a positive effect on NAE under RW
rotation. In general, fertilization had no direct significant effect on
the changes in soil pH, SOC, POXC, and nutrients under the three crop
rotation patterns.

\textbf{4. Discussion}

\emph{4.1. Effects of crop rotation and fertilization ondynamics of soil
inorganic N and plant N uptake}

In the two rice seasons, CU treatments had higher soil inorganic N
content than BBU treatments under the three crop rotations at the middle
of the tillering and flowering stages because of the second and third
topdressings of N (Fig. 3). The plant N contents, in contrast, were not
significantly higher under CU treatments than BBU treatments at the
middle of the tillering stage. Hydrolysis of urea in the soil is a rapid
reaction, resulting in a sharp increase in the content of inorganic N in
the soil in a short period (Skiba \& Wainwright, 1984). However, limited
by the N uptake rate of crops, only a small part of this
high-concentration N is assimilated, and the rest is discharged into the
environment through runoff, ammonia volatilization, etc. As shown in
Fig. 3a, the soil inorganic N contents in CU treatments were
significantly lower than that in BBU treatment at the elongation stage
in the Rice2019 season (Table S2). The CU treatments also resulted in
more inorganic N in the soil at the later periods of rice growth, which
might cause late ripening or lodging of rice. Advantageously, inorganic
N in the soils under BBU treatments was released slowly according to the
N uptake rate of rice, which maintained inorganic N in the soil at an
appropriate concentration. Therefore, application of BBU could increase
the N uptake of rice and reduce the loss of reactive N into the
hydrosphere and atmosphere, thereby increasing the NAE. There was no
significant difference in the soil inorganic N between the single-dose
and twice-split applications of BBU (Table S2). However, twice-split
application of BBU slightly increased plant N content at seeding,
tillering, and elongation stages. This demonstrated that twice-split
application of BBU also improved suitability between the N demand and
supply in rice, thereby increasing the NAE. In this study, the release
period of N was delayed for wheat season, increasing soil inorganic N
content in soil at the mature stage under BBU treatment (Fig. 3a).
Although there was no obvious difference in soil inorganic N and plant N
contents between different crop rotation systems at various stages
(Table S2), the dynamic pattern of soil inorganic N significantly
changed after the rotation season, especially under the BBU treatments
(Fig. 3a). Soil inorganic N in BBU treatments under RG and RW rotations
was higher than in CU treatment at the seeding stage, because of the
residual N from the wheat season and the biologically fixed N from the
green manure season. In addition, soil inorganic N in RG and RW
rotations still presented a high concentration at the elongation stage.
RG and RW rotations enhanced the retention capacity of soil fertility to
supply sufficient N for rice even at the elongation stage. In addition,
the residual N in RW rotation and biologically fixed N in RG rotation
were released and mineralized in the Rice2020 season, respectively.

\emph{4.2. Effects of crop rotation and fertilization on the changes in
soil properties}

Soil pH plays an important role in crop production, nutrient chemistry,
soil organisms, and shaping plant community composition (Sun et al.,
2020). Both CU and BBU fertilizations resulted in a significant
short-term increase in soil pH under RG and RR rotations (Figs. 4a,
S1a), which was caused by the production of OH\textsuperscript{-} from
the hydrolysis of urea and the limitation of nitrification under paddy
soil (Curtin, Peterson, Qiu, \& Fraser, 2020). However, fertilization
did not significantly increase the soil pH under RW rotation. This might
be due to the strong nitrification process in the aerobic environment
during the wheat cropping season in which more H\textsuperscript{+} was
generated to counteract the increase in pH from paddy rice season. SOC
is critical for soil structure and workability, the ability of soils to
store nutrients and water, and for the global C cycle (Sun et al.,
2020). In this study, almost all treatments significantly enhanced the
SOC, which was dominated by the retention of straw residues (Y. Zhao et
al., 2018). The previous study indicated that SOC stock changes in
Chinese croplands were positively correlated with N fertilizer input and
crop residue C input (Y. Zhao et al., 2018). BBU enhanced the plant
growth leading to more inputs of C from straw and roots, which
presumably contributed to the higher SOC in BBU fertilizations
(Pampolino, Laureles, Gines, \& Buresh, 2008). Generally, crop rotation
had a direct impact on the dynamic of SOC by altering the input C to the
soil and the soil microbial activity (D'Acunto, Andrade, Poggio, \&
Semmartin, 2018; Osanai, Knox, Nachimuthu, \& Wilson, 2021). However,
our result showed that there was no significant difference in the
changes in SOC among the three cropping rotations, which might be due to
the short experiment period. Similarly, soil TN contents were increased
after crop rotation and fertilization, which presumably was attributed
to the straw turnover. The changes in soil TN contents under RG and RR
rotations were higher than that under RW rotation. This difference was
caused by the additional N fixed by Chinese milk vetch during RG
rotation and a greater amount of residual including rape straw and grain
during RR rotation (Alam, Bell, Haque, Islam, \& Kader, 2020). Soil
POXC, which stands for labile SOC fraction, is useful as an indicator
for assessing soil health and C sequestration potential (Lucas \& Weil,
2021). Both CU and BBU fertilizations significantly increased the soil
POXC contents compared with WN treatment except for RG rotation. The
change in soil POXC content was positively correlated with the changes
in SOC and TN contents (Fig. S3). Fertilization enhanced the soil C
input by improving crop growth and promoted the decomposition of stubble
and straw residuals. The decreases of soil AP and available Mg were
mainly caused by crop uptake and the increase of available Zn mostly due
to the application of Zn fertilizer. Other available trace elements such
as Mn, Fe, and Cu had a positive correlation with SOC and TN, indicating
that the availability of these elements was related to SOC and TN
contents.

\emph{4.3. Effects of crop rotation and fertilization on the organic and
mineral functional groups}

The soil FTIR-PAS and FTIR-ATR spectra could discover the changes in the
molecular structure of soil organic and mineral as the adsorption bands
of FTIR had a high correlation with SOC (R\textsuperscript{2}=0.617,
0.650), TN (R\textsuperscript{2}=0.585, 0.606), and POXC
(R\textsuperscript{2}=0.606, 0.584) in the PLSR model (Fig. 6b).
According to the variable in projections of POXC in the PLSR model, the
POXC content showed a unique correlation with the bands of \selectlanguage{greek}ν\selectlanguage{english}C-H from
aliphatic and methyl compounds which were considered as intrinsically
easily degradable (Smidt \& Meissl, 2007). Peltre, Bruun, Du, Thomsen,
and Jensen (2014) also reported a chiefly positive correlation between
the labile fraction of SOC and the similar band at 1520-1400
cm\textsuperscript{-1}. Moreover, the POXC content was also correlated
with the bands of \selectlanguage{greek}ν\selectlanguage{english}C-O (1160 cm\textsuperscript{-1}) and \selectlanguage{greek}δ\selectlanguage{english}C-O (1050
cm\textsuperscript{-1}) which attributed to polysaccharides, nucleic
acids, proteins, and carbohydrates. The polysaccharides and
carbohydrates are considered intrinsically labile (Amelung, Brodowski,
Sandhage-Hofmann, \& Bol, 2008). The soil \selectlanguage{greek}ν\selectlanguage{english}C-H band in some treatments
significantly increased under RG and RR rotations while it had no
significant change under RW rotation (Fig. 6), which was consistent with
the change in soil POXC content. These results suggested that
fertilization under RG and RR rotations increased the labile fraction of
SOC. The bands of \selectlanguage{greek}ν\selectlanguage{english}O-H/\selectlanguage{greek}ν\selectlanguage{english}N-H at 3600-3400
cm\textsuperscript{-1}attributed to water, alcohols, phenols, carboxyl,
hydroxyl groups, and amides also significantly increased under the RG
rotation. An increase of amides groups under RG rotation confirmed a
greater increase of TN under RG rotation which potentially attributed to
the biological N fixation of rhizobia on Chinese milk vetch. The
\selectlanguage{greek}ν\selectlanguage{english}C-C/\selectlanguage{greek}ν\selectlanguage{english}C-O and \selectlanguage{greek}ν\selectlanguage{english}C-C bands at 1720-1600 cm\textsuperscript{-1} and 1515
cm\textsuperscript{-1} were associated with carboxylic acids, amides,
and aromatics, respectively. These compounds are considered to be
degradation-resistant due to the recalcitrant nature of aromatic
structures and due to the organo-mineral associations (L\selectlanguage{ngerman}ützow et al.,
2006). The organo-mineral associations are possibly formed through
polyvalent cation bridges with clay surfaces and enhancing
hydrophobicity to resist the microorganisms and their enzymes (Peltre et
al., 2014). In this study, the intensities of \selectlanguage{greek}ν\selectlanguage{english}C-C and \selectlanguage{greek}ν\selectlanguage{english}C-O bands were
significantly reduced after RG rotation rather than RR and RW rotations,
suggesting RG rotation reduced the relative abundance of the stabilized
SOC. In addition, the decrease of
\selectlanguage{greek}ν\selectlanguage{english}CO\textsubscript{3}\textsuperscript{2-} and \selectlanguage{greek}δ\selectlanguage{english}Al-OH demonstrated that
the relative abundances of soil carbonates, kaolinite, and smectite
decreased after crop rotation and fertilization, especially for the
fertilization treatments. The decrease of these soil minerals possibly
was caused by the dilution effect by increased organic matter in the
soil.

\emph{4.4. Effects of crop rotation and fertilization on rice grain
yield and NAE}

In this study, crop rotation and fertilization affected grain yield and
NAE directly by regulating N supply in the soil on the one hand and
indirectly by altering soil chemical property on the other. In general,
fertilization showed more direct effects through regulating N supply
while crop rotation had more indirect effects by altering soil chemical
property. By regulating the release of N, BBU maintained the soil
inorganic N at a high and stable level during the period of rice growth,
especially during the elongation stage, which not only improved the N
uptake of the rice plant but also effectively reduced the losses of
reactive N into the environment. As a result, the grain yield and NAE
were improved. Twice-split application of BBU improved grain yield and
NAE because it was better to balance the N requirement of rice and
supply, especially in the soil with poor fertility retention. However,
reduction of N fertilization rate was adverse to rice growth and
resulted in unsatisfactory grain yield because of the relatively low
basic soil fertility. Crop rotation had no direct effect on grain yield
and NAE but showed significant indirect impacts on the changes in soil
properties. Under RG rotation, changes in soil pH and POXC had
significant negative effects on grain yield and NAE (Fig. 7a). As
mentioned above, RG rotation increased soil pH and the labile fraction
of SOC most and decreased the stable SOC. In other words, the strong
increase in pH and degradation of stable SOC were adverse to improving
grain yield and NAE under RG rotation. RR rotation indirectly affected
grain yield and NAE by changing soil properties as strong correlations
between grain yield and NAE and changes in soil pH, SOC, and POXC were
observed. Only the change in SOC showed a significant effect on NAE
under RW rotation, indicating the weakly indirect impact of RW rotation
on grain yield and NAE. On the whole, application of BBU had direct
positive effects on improving grain yield and NAE under RG and RW
rotations but direct negative effects under RR rotation.

\textbf{5. Conclusions}

The BBU could controlla bly release N to improve the N uptake according
to the requirement of rice during various growth stages. Accordingly,
fertilization of BBU with twice-split application increased both the
rice grain yield and NAE in comparison to conventional urea. At the same
time, crop rotation combined with fertilization significantly increased
the soil pH, SOC, TN, and POXC, resulting in the enhancement of soil
fertility retention. The RG rotation showed a higher increase in soil pH
and TN than other crop rotations, which benefited from the biological
nitrogen fixation of Chinese milk vetch. FTIR spectra indicated that RG
rotation combined with fertilization significantly increased the
aliphatic and methyl compounds which were considered as the labile
fraction of SOC and reduced the relative abundance of carboxylic acids,
amides, and aromatics which were regarded as the stabled fraction of
SOC. Crop rotation also significantly reduced the soil carbonate. The
rice grain yield and NAE were influenced more by the changes in soil
properties under RG and RR rotations than that under RW rotation.

\textbf{Declaration of competing interest}

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.

\textbf{Acknowledgments}

This work was supported by the Strategic Priority Research Program of
the Chinese Academy of Sciences (XDA28040500, XDA28120400) and the
``STS'' Project from Chinese Academy of Sciences (KFJSTS-QYZX-047).

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\textbf{Table 1}

Assignment of the absorption bands in FTIR-PAS and FTIR-ATR spectra.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Wavenumber (cm\textsuperscript{-1}) & Wavenumber
(cm\textsuperscript{-1}) & Vibration & Functional group or
component\tabularnewline
\midrule
\endhead
FTIR-PAS & FTIR-ATR & &\tabularnewline
3900-3700 & - & \selectlanguage{greek}ν\selectlanguage{english}O-H & Clay minerals (Churchman et al., 2010; Xing et
al., 2019)\tabularnewline
& 3620 & \selectlanguage{greek}ν\selectlanguage{english}O-H & Clay minerals (Xu, Du, Ma, Shen, \& Zhou,
2020)\tabularnewline
3600-3400 & 3600-3000 & \selectlanguage{greek}ν\selectlanguage{english}O-H, N-H & Water, alcohols, and phenols;
carboxyl and hydroxyl groups, amides (Ellerbrock \& Gerke, 2004;
Pedersen, Simpson, Bockheim, \& Kumar, 2011)\tabularnewline
3000-2800 & - & \selectlanguage{greek}ν\selectlanguage{english}C-H & Aliphatic methyl and methylene groups (Ellerbrock
\& Gerke, 2004; Soriano-Disla, Janik, Viscarra Rossel, Macdonald, \&
McLaughlin, 2014)\tabularnewline
2200-2000 & 2200-2000 & Overtone \selectlanguage{greek}ν\selectlanguage{english}COH & Carbohydrates (Janik, Skjemstad,
Shepherd, \& Spouncer, 2007)\tabularnewline
1720-1600 & 1720-1600 & \selectlanguage{greek}ν\selectlanguage{english}C-O, \selectlanguage{greek}ν\selectlanguage{english}C-C & Carboxylic acids; amides; Aromatics
(Changwen Du, Goyne, Miles, \& Zhou, 2014; C. Du, Linker, \& Shaviv,
2007)\tabularnewline
- & 1570--1540 & \selectlanguage{greek}ν\selectlanguage{english}N-H, \selectlanguage{greek}ν\selectlanguage{english}C-N in plane & Amide II (Calder\selectlanguage{ngerman}ón, Haddix,
Conant, Magrini-Bair, \& Paul, 2013) (Leifeld, 2006)\tabularnewline
1515 & 1515 & \selectlanguage{greek}ν\selectlanguage{english}C-C & Aromatics (Calder\selectlanguage{ngerman}ón et al., 2013)\tabularnewline
- & 1500-1300 & \selectlanguage{greek}ν\selectlanguage{english}CO\textsubscript{3}\textsuperscript{2-} & Carbonates
(Viscarra Rossel \& Behrens, 2010)\tabularnewline
1445-1350 & - & \selectlanguage{greek}ν\selectlanguage{english}C-H & Methyls (Janik et al., 2007; Rossel \& Behrens,
2010)\tabularnewline
- & 1160 & \selectlanguage{greek}ν\selectlanguage{english}C-O & Polysaccharides, nucleic acids, proteins (Calder\selectlanguage{ngerman}ón et
al., 2013)\tabularnewline
- & 1050 & \selectlanguage{greek}δ\selectlanguage{english}C-O & Carbohydrates (Movasaghi, Rehman, \& ur Rehman, 2008;
Viscarra Rossel \& Behrens, 2010)\tabularnewline
1030-950 & 990 & \selectlanguage{greek}ν\selectlanguage{english}Si-O & Clay minerals (Madejov\selectlanguage{ngerman}á, 2003)\tabularnewline
- & 915 & \selectlanguage{greek}δ\selectlanguage{english}Al-OH & Kaolinite and smectite (Viscarra Rossel \& Behrens,
2010)\tabularnewline
850 & - & NH\textsubscript{2} out of plane & Primary amine (Smidt \&
Meissl, 2007)\tabularnewline
- & 770 & NH\textsubscript{2} out of plane & Primary amine (Nayak \&
Singh, 2007)\tabularnewline
\bottomrule
\end{longtable}

Where \selectlanguage{greek}ν \selectlanguage{english}and \selectlanguage{greek}δ \selectlanguage{english}denote stretching vibration and bending vibration,
respectively.

\textbf{Figure legends}

\textbf{Fig. 1.} Geographic coordinates and maps showing of the
split-plot design in this experiment. WN, withdrawal of N fertilizer;
CU, farmer's conventional urea fertilizing practice with the
thrice-split application; CB1, single-dose application of bulk blending
urea (BBU) with the conventional amount of N; CB2, twice-split
application of BBU with the conventional amount of N; RB1, single-dose
application of BBU with 20\% reduction of N; and RB2, twice-split
application of BBU with 20\% reduction of N.

\textbf{Fig. 2.} Grain yields (a) and nitrogen agronomic efficiencies
(NAE, b) of rice and wheat as affected by crop rotation and
fertilization. Different lowercase letters present the statistical
differences among different treatments at \emph{P} \textless{} 0.05
according to the least significant difference (LSD) method.

\textbf{Fig. 3.} Dynamics of soil total inorganic N contents (a) and
plant N contents (b) at various growth stages under different
treatments. Rice2019, rice growth season in 2019; Wheat, wheat growth
season from 2019 to 2020; Rice2020, rice growth season in 2020.

\textbf{Fig. 4.} Changes in soil pH (a), soil organic carbon (SOC, b),
total N (TN, c), and permanganate oxidize carbon (POXC, d) after
different treatments. Different lowercase letters present the
statistical differences among different treatments at
\emph{P}\textless{} 0.05 according to the least significant difference
(LSD) method.

\textbf{Fig. 5.} PLSR (a, b) and PCA (c, d) analyses of soil FTIR-PAS
(a, c) and FTIR-ATR (b, d) spectra. The bar codes under the spectral
curves show wavenumbers of the top 10\% spectral variables according to
the scores of variables important in projections in the PLSR model. The
density curves along the axis show the independent distributions of the
first and second components under different
fertilizations.\emph{R\textsuperscript{2}} values represent the
independent and interactional effects of crop rotation and fertilization
according to the two-way permutational multivariate analysis of variance
(PERMANOVA). Significance levels are denoted with * \emph{P} \textless{}
0.05, **\emph{P} \textless{} 0.01, and *** \emph{P} \textless{} 0.001,
respectively.

\textbf{Fig. 6.} Comparison of the intensities of soil FTIR-PAS bands as
affected by different treatments. Significance levels are denoted with
*\emph{P} \textless{} 0.05, ** \emph{P} \textless{} 0.01, and ***
\emph{P}\textless{} 0.001, respectively according to paired-samples
T-test.

\textbf{Fig. 7.} Structural equation modeling shows the effects of
fertilization, and soil properties on the grain yield and NAE under
different crop rotation patterns. Green lines indicate positive effects,
while red lines indicate negative effects. Gray lines indicate
nonsignificant effects. The width of arrows indicates the strength of
significant standardized path coefficients. Soil nutrients include soil
total nitrogen (TN), NH\textsubscript{4}\textsuperscript{+}-N,
NO\textsubscript{3}\textsuperscript{-}-N, available phosphorus (AP),
available potassium (AK), and available- Ca, Mg, Mn, Fe, Cu, Zn.

\textbf{Supplementary materials}

\textbf{Table S1.} Two-way ANOVA analysis of the crop rotation (R) and
fertilization (F) on grain yield and NAE of paddy rice 2020 growing
season.

\textbf{Table S2.} Dynamics of soil total inorganic nitrogen contents in
different crop growing periods under various treatments.

\textbf{Table S3.} Two-way ANOVA analysis the crop rotation (R) and
fertilization (F) on soil total inorganic nitrogen contents in 2019 and
2020 growing seasons.

\textbf{Table S4.} Dynamics of plant nitrogen contents in different crop
growing periods under various treatments.

\textbf{Table S5.} Two-way ANOVA analysis of the crop rotation (R) and
fertilization (F) on plant nitrogen contents in 2019 and 2020 growing
seasons.

\textbf{Table S6.} Two-way ANOVA analysis the crop rotation (R) and
fertilization (F) on the change of soil properties after 2019 and 2020
growing seasons.

\textbf{Fig. S1.} Comparison of soil pH (a), soil organic carbon (SOC,
b), total nitrogen (TN, c), and permanganate oxidizes carbon (POXC, d)
between before and after treatments. Significance levels are denoted
with * \emph{P} \textless{} 0.05, ** \emph{P} \textless{} 0.01, and
***\emph{P} \textless{} 0.001, respectively according to paired-samples
T-test.

\textbf{Fig. S2.} Comparison of soil available medium and trace elements
between before and after treatments. Significance levels are denoted
with * \emph{P} \textless{} 0.05, ** \emph{P} \textless{} 0.01, and
***\emph{P} \textless{} 0.001, respectively according to paired-samples
T-test.

\textbf{Fig. S3.} Pearson correlations between various soil properties.
Significance levels are denoted with * \emph{P} \textless{} 0.05,
**\emph{P} \textless{} 0.01, and *** \emph{P} \textless{} 0.001,
respectively.

\textbf{Fig. S4.} The first (PC1) and second (PC2) loadings in PCA of
differential spectra as changed by wavenumber.

\textbf{Fig. S5.} Comparison of the intensities of soil FTIR-PAS bands
as affected by different treatments. Significance levels are denoted
with * \emph{P} \textless{} 0.05, ** \emph{P} \textless{} 0.01, and
***\emph{P} \textless{} 0.001, respectively according to paired-samples
T-test.

\textbf{Fig. S6.} Comparison of the intensities of soil FTIR-ATR bands
as affected by different treatments. Significance levels are denoted
with * \emph{P} \textless{} 0.05, ** \emph{P} \textless{} 0.01, and
***\emph{P} \textless{} 0.001, respectively according to paired-samples
T-test.\selectlanguage{english}
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