Abstract
Despite straw application within rice agriculture being widely
practiced, both in China and globally, there remain few studies on the
maize straw substituted for chemical fertilizers. In this study, maize
straw substituted for chemical fertilizers to a double-cropping rice
field and compared the effects of medium (MS 9,600
kg·ha−1·year−1) and high (HS 19,200
kg·ha−1·year−1) application on rice
yield and soil characteristics with that of the application of single
chemical fertilizers (CF) over a period of 1982 to present. The yields
of late and early rice increased by 42.66 and 25.04% in 2019 and 2020,
respectively. The soil bulk density of MS and HS decreased significantly
by 15.94 and 33.35% compared with that of CF, whereas total soil
porosity increased significantly by 9.46 and 20.17%, respectively.
Long-term straw application significantly improved the soil stable
aggregates content (> 0.25 mm).
Straw application increased soil
urease, protease, alkaline phosphatase (ALP), acid phosphatase (ACP) and
catalase activities, microbial biomass carbon (C), microbial biomass
nitrogen (N), and soil nutrients content compared with CF, especially
HS. Correlation analysis showed that double-cropping rice yield was
highly significantly correlated with soil bulk density, total porosity,
catalase, microbial biomass C, microbial biomass N, and available P. In
conclusion, maize straw substituted for chemical fertilizers not only
makes rational use of straw resources, but also improves soil
characteristics to improve crop yield.
Keywords: Maize straw substituted; Double-cropping rice; Yield;
Soli microbial biomass; Soil physicochemical properties
Introduction
Agricultural
production results in a considerable quantity of straw that include
maize, rice, wheat and so on. In fact, China produced 1.04 billion tons
of total crops straw in 2015, approximately one-third of global output
(Lal, 2005; Medhn, et al., 2017; Li et al., 2018). While the burning of
straw is widely practiced in developing countries (Yao et al., 2017;
Zhou et al., 2017), it has resulted in a serious waste of resources and
environmental pollution, including the loss of almost all C and N and
the emissions of various greenhouse gases (Sun et al., 2016).
Consequently, the Chinese government has strictly prohibited the direct
burning of straw, promoting instead the return of straw to agricultural
fields as the most environmentally-friendly option (Zhao et al., 2018).
The crops straw is rich in N, phosphorus (P), potassium (K), and other
nutrient elements. The decomposition of straw can improve soil fertility
by supplementing available soil nutrients such as N or K as well as soil
enzyme activities, which in turn increase the efficiency of N use and
crop yields (Zhao et al., 2016a; Yang et al., 2017; Akhtar et al., 2018;
Gao et al., 2020; Yang et al.,
2020a). Moreover, straw application can promote the accumulation of soil
organic matter and improved soil structure by decreasing soil bulk
density and increasing porosity (Zhang et al., 2016). Soil
microorganisms play a key role in soil nutrient conversion, energy
transformation, the formation of humus, and the mediation of straw
decomposition (Chen et al., 2014; Guo et al., 2014; Cong et al., 2020).
Straw application can promote the
growth and activity of soil microorganisms and enhance soil microbial
biomass (Xia et al., 2019). Long-term straw application can increase
soil microbial diversity and change the microbial community structure
(Peng et al., 2016; Maarastawi et al.,
2018). However, the effect of
straw incorporation is affected by many factors. Wang et al. (2018a)
determined that straw application amount more than 9,000
kg·ha−1 year−1 to achieve
significant differences in soil physical properties and soil available
nutrients. The CH4 annual emission of ditch-buried wheat
straw application was significantly lower than that of wheat straw
application with rotary tillage, and the N2O annual
emission was significantly lower than wheat straw application with
plowing (Hu et al., 2016). Chen et al. (2017) showed that total
phospholipid fatty acid (PLFA), bacterial biomass, and actinomycetes
biomass of Luvisols soil were significantly increased through the return
of straw, whereas no significant difference was identified in Anthrosols
soil. In addition, Su et al.
(2020) showed that lower fungal community diversity and higher abundance
of fungal pathogen were observed with maize straw application,
especially at high application rates, compared with wheat straw
application. In summary, it implied
that the effects of straw application to the field are related to the
amounts of straw application, the methods of straw application, soil
types, straw types and so on.
Double-cropping rice and maize agriculture is widely implemented in
Hunan province, China, the sown area of double-cropping rice was
2,254,000 hectares and that of maize was 387,000 hectares, which were
the first and second largest of sown area in 2019 (Hunan Statistics
Yearbook, 2020).The disposal of the large quantities of straw produced
through maize agriculture has been a perpetual challenge At present,
maize straw can be used to make feed, industrial raw materials and fuel
in addition to returning to the field. However, the above uses have
higher production cost, greater technical difficulty, lower economic
benefits and easier to cause environmental pollution, compared with
maize straw application to the field.
Chemical fertilizers partly
replaced by maize straw has many advantages, such as reducing the amount
of fertilizer can reduce the production cost, reduce the risk of
agricultural non-point source pollution and so on. However, it is not
clear how maize straw substituted for chemical fertilizers affects crop
yield. In this study, the crushed maize straw replaced part of chemical
fertilizers was applied in double-cropping rice field to examine the
effects of maize straw application on the yield of double-cropping rice
and soil characteristics. The purpose of this study is to have a
relatively comprehensive understanding of the effects of long-term maize
straw replaced part of chemical fertilizers on the yield and soil
characteristics of double-cropping rice. The present study would make
rational use of straw resources, reduce agricultural production costs
and reduce agricultural non-point source pollution caused by excessive
application of chemical fertilizer. It is hoped to provide a scientific
basis for building a resource-saving and environment-friendly
agricultural production environment.
Materials and methods
Site description
The
experimental site is hosted by the experimental farm of Hunan
Agricultural University in Changsha City, Hunan Province, China (28° 18′
N, 113° 08′ E, 50 m above sea level). The paddy soil of the site is
dryland soil developed from Quaternary red clay and is classified as an
Oxisol according to the United States Department of Agriculture (USDA)
Soil Taxonomy (Yang et al., 2020b).
Experimental design
The present study shows the results of a long-term double-cropping
winter fallow rotation rice cultivation experiment that was initiated in
1982 and contained 36 experimental plots. The experiment involved three
experimental treatments: (1) application of chemical fertilizers only
(CF); (2) medium maize straw replaced 1/3 of N fertilizer, and straw
application amount was 9,600
kg·ha−1·year−1 (MS); (3)high maize
straw replaced 2/3 of N fertilizer, and straw application amount was
19,200 kg·ha−1·year−1 (HS),
fertilizers (urea, superphosphate and potassium chloride) were used in
both the MS and HS treatments to supplement deficiencies in N, P and K
within straw application and to ensure their uniform content among three
treatments. The present study randomly selected 9 replicates under the
same environmental conditions for each treatment. The fertilizer rates
applied during both the early and late rice seasons were 150 kg N
ha-1, 75 kg P2O5ha-1, and 150 kg K2O
ha-1. Maize straw was chopped and incorporated into
the approximately 0–20 cm soil depth. And maize straw was used in the
treatments characterized by average contents of N, P, and K of 10.4 g
kg−1, 5.93 g
kg−1, and 12.6 g kg−1, respectively.
In the past five years, the Xiangzaoxian15 was selected for early rice
varieties, which was transplanted in late April and harvested in early
July, while VY46 was selected for late rice varieties, transplanting in
mid-July and harvested in late October.
Sampling
Rice was harvested to calculate yield, during which rice plants were
randomly selected from each plot for the analysis of yield components.
Soil samples (depth of 0–20 cm) were collected at different points in
each plot in 2019 in the late and early
rice harvest periods according to
the S path method, labeled as 2019LR and 2020ER, respectively. Each soil
sample was divided into two parts. The first part was air-dried for the
determination of soil water-stable aggregates, pH, soil organic matter,
and soil nutrition content. The second part was stored at 4 °C for the
determination of soil microbial biomass C and N and soil enzyme
activities (Lu et al., 2018). In addition, within each plot, a steel
support was used to push a uniform volume ring knife (5 cm in diameter;
100 cm3 in volume) into the soil for the collection of
three soil samples in 2020ER for determining the
soil
bulk density and porosity (Secco et al. 2021).
Analytical methods
Rice yield and yield components
1 × 1m was selected from each experimental area to determine the yield
of rice. Rice yield components were measured according to Zhong (2021).
Five plants were randomly sampled from each plot at harvest season in
each year, and the yield components were calculated about the plant
individual level.
Soil physical properties
The soil samples were placed in a water bath for 48 h, following which
the volumetric water content at saturation was taken as the total
porosity. Soil samples were then dried and the ratio of dry soil mass to
the volume of the cylinder was taken as a measure of soil bulk density
(Awe et al., 2020). Determination
of soil water-stable aggregates
was as according to Lu et al. (2018).
Soil organic matter, pH,
and nutrient levels
The analytical methods used to determine soil organic matter, pH, and
nutrient levels are described in Zhang et al (2021). Soil organic matter
(SOM; g kg−1) was determined by the potassium
dichromate external heating method; pH by the use of deionized water to
remove CO2 (1:1 soil/water, w/v ); TN (g
kg−1) by the Kjeldahl N method; TP (g
kg−1) by the NaOH fusion molybdate blue colorimetric
method; total K (TK, g kg−1) by flame photometry after
NaOH fusion; available N (AN, mg
kg−1) by alkaline hydrolysis diffusion; available P
(AP, mg kg−1) by colorimetry following extraction with
0.5 mol L−1 NaHCO3 (pH = 8.5);
available K (AK, mg kg−1) by flame photometry
following extraction with 1 mol L−1CH3COONH4 (pH = 7.0).
Soil enzyme activity
Sodium phenate-sodium hypochlorite colorimetry was used to determine
urease activity (Yu et al., 2019); protease activity by the
Folin-Ciocalteu colorimetry method using casein as a substrate and
culturing in tris-hydrochloric acid buffer (Borase et al., 2020); acid
phosphatase (ACP) and alkaline phosphatase (ALP) activities by the
colorimetric method with p -nitrophenyl phosphate as substrate
(Xie et al., 2017); catalase activity by potassium permanganate
titration (Liu et al., 2020). All samples were analyzed without a matrix
control and all enzyme activities were measured without a soil control.
Soil microbial biomass
Soil microbial biomass C and N (MBC & MBN) were determined by the
chloroform fumigation–K2SO4 extraction
method, following which extract C and N were measured using the same
methods as that for soil organic C and soil TN, respectively (Zhao et
al., 2016b).
Computational formula that
the rice yield and soil characteristics rate of changes
The rice yield and soil
characteristics rate of changes after long-term maize straw substituted
for chemical fertilizers was calculated by the following formula:
\begin{equation}
\mathrm{R=(S}\mathrm{-}\mathrm{CF)/CF\times 100\%}\nonumber \\
\end{equation}where R is the rate of changes, S is the rice yield and
soil characteristics under maize straw substituted for chemical
fertilizers treatments, and CF is the rice yield and soil
characteristics under single chemical fertilizers treatment.
Statistical analyses
All data were collated using Microsoft Office Excel 2016. One-way
analysis of variance (ANOVA) was applied to all data in SPSS19.0 (IBM),
followed by Duncan’s multiple range test (P < 0.05).
GraphPad Prism 7.0 was used for plotting. Principal component analysis
(PCA) was conducted and visualized in Origin 2018. Mantel tests were
also performed between rice yield and soil characteristics in R with the
mantel function in the ”vegan” package (version 4.0.4) (Yuan et al.,
2021)
Results
Effect of maize straw substituted for chemical fertilizers
on double-cropping rice yield and its components
There was no significant difference in rice yield between the CF and MS
treatments in 2019LR (Fig. 1), whereas the yield of the HS treatment
exceeded that of CF by 42.66% (Fig. 5a). The same trend was observed in
2020ER, with the yield of HS exceeding that of CF by 25.04% (Fig. 5b).
The increase in rice yield was due to the increases in panicle number
and grain filling rate (Table 1). The panicle numbers of MS and HS in
2019LR exceeded those of CF by 19.59 and 31.96%, respectively. In
contrast, the panicle number of only HS was significantly higher than
that of CF by 15.16% in 2020ER, whereas there was no significant
difference between MS and CF.
The same trends were observed in the
grain
filling rate in 2019LR and 2020ER, with no significant difference
between CF and MS, while the grain
filling rate of HS exceeded those of CF and MS by 11.29 and 17.73%,
respectively. There were no significant differences in plant height and
panicle length between the three treatments.
Effect of maize straw substituted for chemical fertilizers on
soil physical properties
The soil bulk densities of MS and HS were significantly reduced
by 15.94 and 33.35%, respectively
compared to that of CF (Fig. 2a, Fig. 5b), whereas soil total porosity
significantly increased by 9.46
and 20.17%, respectively (Fig. 2b, Fig. 5b).
The diameters of soil aggregates among the three treatments were mainly
within 0.25–2 mm, followed by 0.053–0.25 mm, <0.053 mm, and
>2 mm, and there were no significant differences between
the three treatment in the dominance of the >2 mm and
<0.053 mm diameter categories (Fig. 2c). The proportions of
soil aggregates with a diameter of 0.25–2mm were significantly higher
in MS and HS compared to that in
CF, whereas the proportions of soil aggregates with a diameter of
0.053–0.25mm where significantly lower in MS and HS. There were no
significant differences in the proportions of soil aggregates with
diameters of 0.25–2mm and 0.053–0.25mm between MS with HS.
Long-term straw application significantly increased the proportion of
stable aggregate content (SAC; > 0.25 mm) in soil (Fig.
2d), with SAC in MS and HS exceeding that in CF by 11.79 and 14.07%,
respectively (Fig. 5b), whereas there was no significant difference
between MS with HS.
Effect of maize straw substituted for chemical fertilizers on
soil enzyme activities and microbial biomass
Urease activity in HS
significantly exceeded that in CF by 52.42 and 36.43% in 2019LR and
2020ER, respectively (Fig. 3a, Fig. 5), whereas there was no significant
difference between CF and MS.
The activity of soil protease in HS significantly exceeded that in CF by
58.55 and 122.91% in 2019LR and 2020ER, respectively (Fig. 3b, Fig. 5),
whereas there was no significant difference between MS with CF.
The ALP activities in MS and HS exceeded that of CF by 39.25 and 77.47%
in 2019LR and by 28.13 and 59.09% in 2020ER (Fig. 3c, Fig. 5),
respectively, whereas there was no significant difference between MS and
HS.
The ACP activities of MS and HS
significantly exceeded that of CF by 43.62 and 98.30% in 2019LR and by
64.81 and 89.02% in 2020ER (Fig. 3d, Fig. 5), respectively.
Soil catalase activity among the three treatments increased with
increasing straw application (Fig. 3e), with soil catalase activity in
MS and HS significantly exceeding that in CF by 45.93 and 108.50% (Fig.
5a) and by 28.33 and 68.94% (Fig. 5b) in 2019LR and 202ER,
respectively.
The MBC contents of MS and HS
significantly exceeded that of CF by 72.25 and 129.49% in 2019LR,
respectively, whereas only MBC contents of HS significantly exceeded
that of CF by 85.11% in 2020ER (Fig. 4a, Fig. 5), with no other
significant differences between treatments.
The MBN contents of MS and HS significantly exceeded that of CF by
154.29 and 250.53% and by 50.71 and 108.21% in 2019LR and 2020ER,
respectively.
Fig. 4b and Fig. 5 shown the
significant differences among the treatments in 2019LR and 2020ER.
Effect of maize straw substituted for chemical fertilizers on
soil pH and nutrients
The highest SOM content was observed in HS, exceeding that in CF by
41.66 and 44.49% in 2019LR and 2020ER, respectively (Table 2, Fig. 5).
There was no significant difference in SOM between MS and CF in 2019LR,
whereas the SOM of MS exceeded that of CF by 22.34% in 2020ER.
The soil TN contents of MS and HS significantly exceeded that of CF by
25.04 and 44.94% and by 35.82 and 45.83% in 2019LR and 2020ER
respectively, whereas there was no significant difference between MS
with HS.
The soil AN contents of MS and HS significantly exceeded that of CF by
29.40 and 42.62% and by 21.57 and 42.87 in 2019LR and 2020ER,
respectively. There was no significant difference in AN between MS and
HS in 2019LR, whereas there were significant differences among the three
treatments in 2020ER.
The soil AK content of HS significantly exceeded that of CF by 106.58%
in 2019LR, whereas there was no significant difference between CF and
MS. The AK contents of MS and HS significantly exceeded that of CF in
2020ER by 87.30 and 185.41%, respectively.
The soil pH values of MS and HS were significantly lower than that of CF
by 4.63 and 6.00%, respectively in 2019LR, although there was no
significant difference between MS and HS. In 2020ER, the pH values of MS
and HS were significantly lower than that of CF by 4.11 and 6.63%,
respectively, and the pH of HS significantly decreased by 2.78% in
comparison to that of MS.
The soil TP of HS significantly reduced by 31.54 and 29.29% compared to
that of CF in 2019LR and 2020ER, respectively, whereas there was no
significant difference between CF and MS.
The soil AP of HS was significantly lower than that of CF by 43.96% in
2019LR, whereas there was no significant difference between MS and HS.
The AP values of MS and HS were significantly reduced by 19.48 and
56.57% compared with that of CF in 2020ER, respectively, and there were
significant differences among all treatments.
There was no significant difference in soil TK contents among all
treatments.
Correlations between double-cropping rice yield and soil
characteristics
The results of principal component analysis (PCA) showed that
correlations between double-copping rice yield and soil characteristics
differed among the different treatments (Fig. 6). The first two
principal components, PC1 and PC2, of 2019LR explained 77.1 and 7.6% of
observed variation, respectively (Fig. 6a), whereas that of 2020ER
explained 81.5 and 7.9%, respectively (Fig. 6b). There were significant
differences in rice yield and soil characteristics among all three
treatments.
The Mantel test showed that yield was highly significantly correlated
with soil TP, AP, MBC, and MBN and with the activities of urease, ALP,
and catalase. Yield was significantly correlated with AK and the
activities of protease and ACP. There were no significant correlations
between yield and TN, TK, SOM, AN, and pH in 2019LR (Fig. 7a).
However, yield was highly significantly correlated with soil AN, AP, AK,
MBC, and MBN as well as with catalase activity, soil bulk density, and
total porosity. Yield was significantly correlated with TN, SOM, pH, and
SAC as well as with ACP and ALP activities. There was no significant
correlation between yield and TP and TK and between urease and protease
activities in 2020ER (Fig. 7b).
Pearson’s correlation analysis showed that there were no significant
correlations between TK and all soil characteristics. TN was
significantly positively correlated with SOM, AN, AK, MBC, and MBN and
with activities of urease, protease, ALP, and catalase in 2019LR,
whereas TN was significantly negatively correlated with TP, AP, and pH,
and not significantly correlated with ACP (Fig. 7a).
SOM was significantly positively correlated with AN, AK, MBC, and MBN
and the activities of protease and catalase, whereas it was
significantly negatively correlated with TP, AP, and pH. However, there
was no significant correlation between SOM and the activities of urease,
ACP, and ALP. ACP had a significantly positive correlation with AN, a
significantly negative correlation with pH, and no significant
correlation with TP, TK, AP, and AK. There was a significant positive
correlation between microbial biomass and soil enzyme activities, with
only the relationships between microbial biomass and ACP and protease
not reaching a significant level.
TN was positively correlated with SOM, AN, AK, MBC, MBN, ACP, ALP,
catalase, total porosity, and SAC in 2020ER, whereas it was negatively
correlated with pH, AP, and soil bulk density, and not significantly
correlated with TP and protease. TP was significantly positively
correlated with pH, AP, and bulk density, whereas it was significantly
negatively correlated with SOM, AK, MBN, urease, ALP, catalase, and
total porosity, but not significantly correlated with AN, MBC, protease,
and ACP.
SOM was significantly positively correlated with AN, AK, MBC, MBN,
urease, ACP, ALP, catalase, total porosity, and SAC, whereas it was
significantly negatively correlated with pH, AP, and soil bulk density.
However, there was no significant correlation between MBC and protease
activity and the correlation between microbial biomass and enzyme
activity was basically consistent with the results of 2019LR (Fig. 7b).
Bulk density was significantly positively correlated with TP, AP, and
pH, whereas it was significantly negatively correlated with other soil
characteristics. The correlations between total soil porosity and other
soil properties were completely opposite to that for soil bulk density.
SAC was positively correlated with TN, SOM, AN, AK, MBC, MBN, ACP, and
catalase, whereas it was negatively correlated with AP and not
significantly correlated with TP, pH, urease, protease, ALP, bulk
density, and total porosity.
Discussion
Rice yield
Wang et al.(2018a) showed that straw application under equal amount of
chemical fertilizers increased the maize yield, and the maize yield
increased with straw application amount increased. It might be that
straw application provided a lot of nutrients, promoted crop growth and
increased yield. The results of the present study also showed that straw
substituted for chemical fertilizers increased rice yield (Fig.1), but
it might be that chemical fertilizers partly replaced by maize straw
increased rice yield by improving soil characteristics. Meanwhile, straw
substituted for chemical fertilizers can reduce non-point source
pollution while rationally using straw resources, which has a positive
effect on the agricultural environment.
The number of panicles and grain filling rate are influenced by
fertilizers input, water management, and rice variety, and reasonable
fertilization model can increase crop yield by increasing panicles
number, grain filling rate and so on (Zhong et al., 2021).The results of
the present study showed that long-term straw substituted for chemical
fertilizers improved rice yield by increasing the panicles number and
grain filling rate (Table 1), moreover, HS treatment had a better
yield-increasing effect compare with MS treatment, consistent with the
results of Xia et al. (2018).
Maize straw application significantly increased 1,000-grain weight in
2019LR, whereas there was no significant difference in 2020ER (Table 1),
which could be attributed to differences in rice varieties and climatic
conditions. In this study, maize straw substituted for chemical
fertilizers increased rice yield by improving soil physical properties,
increasing soil enzyme activity, microbial biomass, and soil nutrients
compared with CF.
Soil physical properties
Straw forms humus under the action of soil microorganisms, which
effectively increases SOM content, changes the overall soil properties,
reduces soil bulk density and increases soil total porosity. Soil bulk
density is an important physical parameter of soil that is commonly used
to quantify soil compactness. Soil compactness reflects the tightness of
soil and directly affects soil aeration and the development of plant
roots (Silva et al., 1997). Soil total porosity contributes to soil
structure and positively contributes to the conduction of soil water and
air and plant root growth (Luo et al., 2010). Straw application reduced
soil bulk density and increased soil total porosity (Fig. 2a; Fig. 2b),
thereby promoting the growth of rice roots and increasing rice yield,
consistent with the results of Yang et al. (2020a).
There were highly significant correlations between yield and soil bulk
density, total porosity (Fig. 7b), indicating that long-term straw
application improved soil physical structure and promoted the growth of
rice roots and nutrient uptake, thereby partly explaining the increase
in rice yield.
Soil aggregates are the structural units of soil and their physical
stability is considered a key parameter of soil quality (Menon et al.,
2020). Soil aggregates, particularly water-stable aggregates, have a
great influence on soil structure and are very important for the
migration and maintenance of soil moisture and nutrients (Bailey et al.,
2013; Merino-Martín et al., 2020). The diameters of soil aggregates in
the present study mainly fell within the range of 0.053–2 mm (Fig. 2c),
consistent with the results of Zhang et al. (2021). At the same time,
long-term straw application increased the proportion of SAC
(> 0.25 mm) (Fig. 2d), indicating that nutrients released
by straw degradation directly or indirectly promote the growth of soil
aggregates, but also improve the stability of soil aggregates,
consistent with the results of Huang et al. (2020). The present study
found that SAC benefitted rice yield and noted a significant correlation
between soil stability aggregates and yield (Fig. 7b). This might be
that maize straw substituted for chemical fertilizers has improved SAC,
maintained soil nutrients, improved soil quality, and thereby increased
crop yields.
Soil enzyme
activities
Soil urease, protease, ACP, and
ALP play an important role in the cycle of soil N and P, and their
products are easy to be absorbed and utilized by crops (Li et al.,
2017). Wu et al. (2020) showed that straw application significantly
increased activities of soil enzymes, and Zhang et al. (2016) found that
soil urease, phosphatase, and invertase activities increased with
increasing amount of straw application, consistent with the results of
the present study. There were significantly increased activities of soil
urease, protease, ACP, and ALP in HS as compared to that in CF (Fig. 3),
which could possibly be attributed to increased soil microbial
metabolism resulting from straw application (Yang et al., 2021). The
increase of soil urease, protease, ACP, and ALP activities indicated the
increase of nutrients that can be absorbed and utilized by rice, which
might be one of the reasons for increasing rice yield.
Catalase enables the decomposition of peroxide during metabolism,
thereby preventing its toxic effects on crops (Liu et al., 2017). The
present study found chemical fertilizers partly replaced by maize straw
increased catalase activity, especially HS treatment. And a highly
significant correlation between rice yield and catalase and a positive
correlation between soil porosity and catalase. (Fig. 7). This result
could be indicated that straw application improved the soil environment
and increased rice yield.
Soil microbial
biomass
Soil microbial biomass is not only a storage of soil nutrients, but also
an important source of nutrients available for plant growth, which plays
an important role in increasing the number and activity of soil
microorganisms, accelerating soil nutrient cycling, improving soil
bioavailability and increasing rice nutrient absorption, so as to
increase rice yield (Lundquist et al., 1999). MBC and MBN both reflect
the growth and activities of soil microorganisms and generally increase
through the incorporation of straw (Shahbaz et al., 2017). Straw
application has also significantly increased soil MBC and MBN in paddy
fields (Wang et al., 2018b). Maize straw application significantly
increased MBC and MBN, especially HS treatment (Fig. 4), it might be
straw input increase the C source. MBC and MBN were highly significantly
correlated with rice yield (Fig. 7).
SOM, soil nutrients and pH
SOM is a major determinant of soil ecosystem quality and includes a
complex mixture of organic matter from litter, root turnover, and
microorganisms. These components are important sources of plant
nutrients and play a key role in the global C cycle and climate warming
(Li et al., 2019). Numerous
studies have demonstrated that the amount of maize straw application
showed a positive correlation with SOM (Ren et al., 2018; Hao et al.,
2019; Wu et al., 2019; Yan et al. al., 2020), it might be that straw
application increased soil microbial biomass, this study showed a same
result (Fig.4). At the same time, SOM increased crop yield (Liu et al.,
2021). The present study showed that maize straw application improved
SOM content, and HS treatment had a better effect than MS treatment
(Table 2). Meanwhile, this is one of the reasons for increasing yield.
The maize straw application in the present study improved all soil
nutrients, except TP, AP, and TK (Table 2), consistent with the results
of Zhao et al. (2014) and Guan et al. (2020), but contradicting those of
Dong et al. (2012), who found no significant difference in AN and AK
between straw application treatments and CF. These conflicting different
results depend on soil type, straw type, fertilization quantity, and
planting system.
The present study showed that
straw application reduced soil pH (Table 2), consistent with the
findings of Zhao et al. (2009) and Wang et al. (2018a). However, Zhao et
al. (2020) showed that straw incorporation increased soil pH. This
difference might be caused by soil type, straw type and so on Maize
straw application also significantly reduced TP and AP (Table 2), which
may be attributed to differences in straw decomposition rates between MS
and HS due to differences in the amount of straw application. Meanwhile,
the decomposition of straw released organic P, and loss of organic P by
runoff significantly exceeded that of inorganic P (Wang et al., 2014).
In addition, the increase in soil organic matter reduced adsorption of P
to soil, thereby facilitating the transfer soil P to the liquid phase
and increasing soil P loss through runoff (Nobile et al., 2020).
In addition, only two straw replacement amounts were set in this study,
so it is necessary to further study the effects of different straw
replacement amounts on soil quality and rice yield in order to confirm
an optimal straw replacement amount.