*Article* **Residue Mulching Alleviates Coastal Salt Accumulation and Stimulates Post-Fallow Crop Biomass under a Fallow–Maize (***Zea mays* **L.) Rotation System**

**Yifu Zhang 1,2,\*, Wei Yuan <sup>1</sup> and Lianjie Han <sup>1</sup>**


**Abstract:** Fallow, a field where living plants are unplanted for a period, is continually implemented to accumulate moisture for the upcoming cultivation. However, there are less studies on the fallow strategies in one-crop-per-annum cropping system for coastal saline soils. In this study, 2-year "fallow + maize (*Zea mays* L.)" rotation experiments were carried out from 2016 to 2018 to assess how the mulching determine post-fallow soil moisture, salt distribution, and crop performance. Three treatments were designed, i.e., traditional cultivation without residue retention (TT), traditional tillage with total straw mulching during fallow (TT + SM), and no-till cultivation combined fallow mulching (NT + SM). After 2 years of fallow mulching with maize rotation, TT + SM reduced soil electrical conductivity (EC) and total salt of the upper 30 cm soil profile by 22.9% and 25.4% (*p* = 0.05), respectively, compared with the TT treatment. The results also indicate an improvement in volumetric soil water content (SWC) by 10.3%, soil organic matter (SOM) by 17.8%, and ultimately grain yield by 11.3% (*p* = 0.05) under the TT + SM treatment. Fallow mulching is recommended as an acceptable way to protect soil health in coastal fresh-starved or rain-fed farming practice.

**Keywords:** coastal salt-affected soil; one-crop-per-annum cropping; fallow mulching; salt accumulation; crop growing

#### **1. Introduction**

Soil salinization is a process during which the salt in the deep soil and groundwater rises to the surface via evaporation, and then accumulates in the topsoil. Salt accumulation has been one of the most severe ecological environmental problems that restricts the agricultural sustainable development in arid and semi-arid areas [1–4]. Currently in China, principally distributed in the northeast, northwest, and coastal areas, more than 36 million hectare farmlands are suffering from salinity, accounting for approximately 4.9% of the whole available lands [5–7].

Stimulating grain yield in coastal farmlands is a vital part of ensuring food security. Focusing on the special climate and hydrological conditions, soil desalination for coastal areas was conducted mainly by following three aspects, i.e., salt leaching, capillary water blocking, and biological desalination [8–10]. However, it is of great importance to introduce different ways to minimize salt constraints and expanding agricultural output. Generally, coastal croplands are vulnerable to anthropogenic activities and climatic changes. Especially in the coastline of Bohai bay, east China, the fluctuation in sea level and the excessive consumption of groundwater will inevitably induce the invasion from seawater. Reasons for the severe salt stress primarily come from the following three aspects [11,12]. Firstly, year-round intrusion by seawater leads to excessively groundwater salinity concentration. Secondly, mainly concentrated in summer, the precipitation in this region is uneven

**Citation:** Zhang, Y.; Yuan, W.; Han, L. Residue Mulching Alleviates Coastal Salt Accumulation and Stimulates Post-Fallow Crop Biomass under a Fallow–Maize (*Zea mays* L.) Rotation System. *Agriculture* **2022**, *12*, 509. https://doi.org/10.3390/ agriculture12040509

Academic Editors: Chengfang Li and Lijin Guo

Received: 26 February 2022 Accepted: 31 March 2022 Published: 3 April 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

throughout the four seasons as affected by the oceanic climate. Thirdly, from autumn to next spring, salt accumulates upward into the topsoil via evaporation, a result from the monsoon and drought. Therefore, "fallow + maize (*Zea mays* L.)" rotation cultivation has been applied for decades in this region, and the local farmers tend to cultivate summer maize due to the scarce fresh water and fallow in the post season.

Fallow, a period during which no living plants are grown, is frequently utilized to collect moisture and nutrition for subsequent cultivation [13]. Fallow is feasible to solve environmental deterioration through the self-recovery of the barren or low-yield lands. It was reported that fallow practice had advantages in improving soil hardening, desertification, enhancing biodiversity, and thereby increasing grain production and ensuring food security [14,15]. Overall, fallow is a feasible practice in arid and part of subhumid regions, when the accessible rainfall during cropping season is less than that required for expected yield [16,17]. However, fallow inevitably incurs shrinking output due to the extended time without cash crop cover.

Straw mulching, soil cover with crop residues, has been well confirmed to have positive influences on soil water and heat redistribution, soil physicochemical properties and nutrient, and ultimately facilitate crop performance [18–21]. In addition, straw mulching also produced the expected effect in salt-affected soils. Wang et al. [22] found that water evaporation decreased significantly, while the saline soil was covered. Moreover, cotton straw was demonstrated to have a positive effect on soil fertility and crop yields [23]. Based on the previous studies, straw, as a by-product from farmland crops, has great potential in improving the soil environment, especially because it is available and easy to apply. More importantly, Yang [24] indicated that fallow rotation under straw mulching was beneficial to improve soil structure, which provides a feasible reference for the exploration on the "fallow + summer maize" rotation.

Therefore, this study aims to achieve a fallow–maize rotation crop system with severe salt accumulation and insufficient freshwater, and we attempt to introduce reasonable fallow managements, as well as to survey appropriate agronomic solutions for coastal saltaffected croplands. We hypothesized that, if maize straw mulching is beneficial to reduce the upward salt accumulation during fallow, the subsequent cropping season would obtain better water and salt conditions. In this study, a 2-year fallow–maize rotation cultivation was carried out, and during the fallow period, the field was covered with maize straw after harvest to ascertain how they impact the salt movement and crop growth. Before each cropping season, soil electrical conductivity (EC), total salt, soil organic matter (SOM), bulk density, and volumetric soil water content (SWC) were measured, as well as the relevant grain yield, to investigate the comprehensive response in comparison to traditional management. Accordingly, the objective of this study was to assess the response of soil moisture distribution and crop performance to fallow straw mulching, and to provide a reproducible approach to cultivate coastal saline croplands.

#### **2. Materials and Methods**

#### *2.1. Experimental Site and Soil*

From May 2016 to September 2018, fallow combined with summer maize rotation experiments were conducted in the Binhai district, Tianjin city, China (38◦46 N, 117◦13 E, Figure 1). The climate is semi-humid and monsoons with 211 frost-free days and 12.3 ◦C of annual average temperature. The 570 mm annual precipitation is fluctuant and imbalanced, mainly (>70%) concentrated from June to September. The annual evaporation is about 1800 mm, and the evaporation–precipitation ratio exceeds 3:1.

**Figure 1.** Location of the experimental site.

Before the initiation of field experiments, the soil was defined as solonchak, with 2.67 mg kg−<sup>1</sup> of sodium, 7.08 g kg−<sup>1</sup> of salt content, 10.4 g kg−<sup>1</sup> of SOM, 64.5 mg kg−<sup>1</sup> of alkaline-hydrolysable nitrogen, 31.4 mg kg−<sup>1</sup> of available phosphorus (by Olsen), and 63.2 mg kg−<sup>1</sup> of available potassium. The soil texture was silty clay loam, according to the USDA classification. The physical properties of the 0–30 cm profile prior to experiments are shown in Table 1.

**Table 1.** Soil physical properties of the 0–30 cm profile before experiments.


#### *2.2. Experimental Design*

Prior to 2016, the site was farmed traditionally for decades with summer maize cultivation. In this study, the whole sites were ploughed to eliminate the existing plough pan in early June. Then, the seedbed was renovated by rotary harrowing to a depth of 0.15 m and smoothing before planting. In late September, maize harvest and total stubble removing were executed manually, according to traditional tillage management. This research was performed after maize harvest, and three treatments were designed in this study: (1) TT, traditional tillage for maize cultivation with no straw being returned to the field after maize harvest, as the control group; (2) TT + SM, traditional tillage for maize cultivation with 100% fallow straw mulching from harvest to planting in the next year; and (3) NT + SM, 100% fallow straw mulching without tillage. The three treatments were applied to a randomized design with three replicates. The plots were ridged against cross contamination, and each was 36 m long and 15 m wide.

Table 2 describes the cultivated details of the fallow–maize rotation. In late September 2016, dry maize stubble was equally supplied in each mulch-treated plot at 4000 kg ha−<sup>1</sup> for the TT + SM and NT + SM treatments. In late September 2017, the residues harvested from the previous cropping season were all retained (i.e., 100% straw retention) in each site by mulching. For the sowing procedure of the NT + SM treatment, the maize was planted directly without seedbed renovation.

**Table 2.** Cropping schedules for the fallow–maize rotation system. The precipitation was calculated during the cropping season or fallow period, i.e., from maize planting to harvest and from maize harvest to the next year planting, respectively).


During each in-season cultivation, a coincident cropping method was applied in accordance with the local farming practice. A no-till maize seeder was applied to execute sowing and fertilizing simultaneously. In detail, the experimental cultivar was Zhengdan958 with a row spacing of 60 cm and 28 cm seed spacing in a row, which was sown on 9 June 2017 and harvested on 29 September and again sown on 6 June 2018 and harvested on 27 September. The fertilizer was incorporated at a rate of 45 kg hm−<sup>2</sup> of N, 45 kg hm−<sup>2</sup> of P2O5, and 40 kg hm−<sup>2</sup> of K2O, while sowing. In addition, 40 kg hm−<sup>2</sup> of N was supplied as topdressing at the jointing stage. Plant protection, such as weeds, insect pests, and diseases. was performed when needed in accordance with the local agronomic specifications.

#### *2.3. Sampling and Measurement*

Soil samples were collected at the end of fallow period, i.e., early June of 2017 and 2018, before the seedbed renovation for maize sowing. The disturbed samples were air dried, then pulverized and screened for chemical properties measurements. Soil EC was measured using the soil water suspension (1:5, *w*/*v*) by an EC meter. SOM was determined under the dichromate oxidation method by Liu et al. [25]. Total salt storage to the calculated soil profile was measured as the mass per unit area, as described by [26]:

$$\text{Total salt} = 10 \sum \rho\_{li} \text{ s}\_{i} \, z\_{i\prime} \,\tag{1}$$

where *ρbi* is the soil bulk density of the *i* soil layer; in g cm−3; *si* is the soil salt content of the *i* soil layer, in g kg<sup>−</sup>1; and *zi* is the thickness of the *i* soil layer, in cm.

The undisturbed soil cores were taken before the seedbed renovation using the constant volume cutting ring. The volumetric SWC investigation was performed using the oven drying method, as described by He et al. [27]:

$$b\_{\upsilon} = b\_{m} \times (\rho\_{b}/\rho\_{w})\_{\prime} \tag{2}$$

where *bv* expresses the volumetric SWC, in cm<sup>3</sup> cm<sup>−</sup>3; *bm* is the gravimetric SWC, in g g<sup>−</sup>1; *ρ<sup>b</sup>* and *ρ<sup>w</sup>* are the soil bulk density and water density, respectively, in g cm<sup>−</sup>3.

Plant samples were collected at maturity stage from five randomly selected plants in each plot. Root samples were collected within a 0.15 × 0.15 m square, and to a depth of 0.40 m. Adhered soil particles and unrelated impurities were removed by running tap water, and then the roots were air dried and oven dried at 70 ◦C unto constant weight to provide the root biomass. Three 5 m long rows were randomly selected under different treatment to determine maize yields. The grain yield was adjusted to 12.0% moisture content.

#### *2.4. Statistical Analyses*

The mean values were calculated for each measurement, and analysis of variance (ANOVA) was performed to evaluate the effect of different treatments on the variables with SPSS software (International Business Machines Corporation, New York, NY, USA). Normality and homoscedasticity were tested for original data before the ANOVA test. If the homogeneity did not show, the original data were classified to conform to the requirement. Multiple comparisons were conducted based on the least significant difference test (LSD) at a 5% level of probability (*p* = 0.05).

#### **3. Results**

#### *3.1. Soil EC*

Figure 2 compared mean soil EC in the top 30 cm soil layer at the end of the fallow period, i.e., before the seedbed renovation for maize sowing. In the entire 2-year observation, the TT treatment showed the highest values in soil EC in comparison with the TT + SM and NT + SM treatments (*p* = 0.05). The mean EC under the TT + SM treatment appeared to be the lowest, which showed a reduction by 9.8% in 2017 and 22.9% in 2018, in comparison to the TT treatment (*p* = 0.05). Additionally, despite the lack of a significant difference in 2017 (by 7.9%), the NT + SM treatment had a 12.6% significant improvement in EC, as compared to TT (*p* = 0.05).

**Figure 2.** Mean soil electrical conductivity (EC) in the upper 30 cm profile for the TT, TT + SM, and NT + SM treatments. TT: traditional tillage for maize cultivation without straw return after maize harvest; TT + SM: traditional tillage with 100% straw mulching after harvest; NT + SM: no-till cultivation combined with 100% straw mulching. Data were measured at the end of fallow period, i.e., early June of 2017 and 2018 before maize sowing. Means in the same year followed by a different letter are significantly different (*p* = 0.05).

#### *3.2. Total Salt*

The total salt in the top 30 cm soil layer was calculated and is shown in Table 3, which reveals its similar tendency with that of soil EC. Compared with the TT treatment, total salt under the TT + SM treatment significantly decreased by 11.3% in 2017 and 25.4% in 2018, respectively (*p* = 0.05). The NT + SM treatment showed an 8.9–13.2% decrease in total salt (*p* = 0.05). Additionally, the total salt under the TT + SM treatment tended to be lower, and a significant decrease was observed in 2018 by 14.0%, when compared with the NT + SM treatment (*p* = 0.05).

**Table 3.** Total salt and mean soil organic matter (SOM) in the top 30 cm soil layer at the end of the fallow period, i.e., early June of 2017 and 2018 before maize sowing, for the TT, TT + SM, and NT + SM treatments. TT: traditional tillage for maize cultivation without straw return after maize harvest; TT + SM: traditional tillage with 100% straw mulching after harvest; NT + SM: no-till cultivation combined with 100% straw mulching. Means in the same year followed by a different letter are significantly different (*p* = 0.05).


#### *3.3. SOM*

Table 3 describes the pre-planting mean SOM in the top 30 cm soil layer at the end of the fallow period. Generally, the mean SOM tended to be highest under the TT + SM treatment, while TT had the lowest values, i.e., TT + SM > NT + SM > TT. Before the first cropping season of early June 2017, the three treatments had no significant difference in SOM. However, in 2018, TT + SM accelerated SOM significantly by 17.8% and 13.4%, in comparison to the TT and NT + SM treatments, respectively (*p* = 0.05).

#### *3.4. Soil Bulk Density*

Mean soil bulk density in the top 30 cm profile of the soil is shown in Figure 3; the means were measured prior to maize sowing. Generally, prior to the first cropping season (early June 2017), no significant difference in soil bulk density was observed between the TT, TT + SM, and NT + SM treatments. However, a significant improvement was observed in 2018 under the TT + SM treatment, which decreased the soil bulk density by 3.4% and by 2.7%, respectively (*p* = 0.05), in comparison to the TT and NT + SM treatments. In addition, the difference in 2018 between TT and NT + SM was not significant.

**Figure 3.** Mean soil bulk density to the depth of 30 cm for traditional tillage without straw return (TT), traditional tillage with straw mulching (TT + SM), and no-till cultivation combined with straw mulching (NT + SM) treatments. Data were measured before maize sowing. Mean values within the same year followed by a different letter are significantly different (*p* = 0.05).

#### *3.5. SWC*

Figure 4 shows the mean volumetric SWC in the upper 30 cm soil profile after each fallow period. Volumetric SWC under treatments with straw mulching tended to be higher throughout the 2-year experiments. Particularly, prior to the second cropping season in 2018, TT + SM significantly accumulated more volumetric SWC by 10.3% (*p* = 0.05), in comparison to the TT treatment. Furthermore, the mean values in volumetric SWC under the NT + SM treatment tended to be medium, but no significant variation was observed, both compared with the TT and TT + SM treatments.

**Figure 4.** Mean volumetric soil water content (SWC) in the top 30 cm profile at the end of each fallow period, for the TT, TT + SM, and NT + SM treatments. TT: traditional tillage for maize cultivation without straw return after maize harvest; TT + SM: traditional tillage with 100% straw mulching after harvest; NT + SM: no-till cultivation combined with 100% straw mulching. Means in the same year followed by a different letter are significantly different (*p* = 0.05).

#### *3.6. Crop Performance*

At the end of the fallow period in early June, in-season maize cultivation was conducted, and the crop growth at maturity stage is listed in Table 4. No significant difference was observed regarding plant height among various treatments. Moreover, for root dry weight, means under treatments with straw mulching tended to be higher. In detail, TT + SM increased root dry weight by 16.2–18.7%, as compared with the TT treatment (*p* = 0.05). Moreover, compared with the TT treatment, no significant promotion was observed in root dry weight under the NT + SM treatment.

**Table 4.** Plant height and root dry weight at maturity stage, as well as the final grain yield for maize cultivation under the traditional tillage without straw return (TT), traditional tillage with straw mulching (TT + SM), and no-till cultivation combined with straw mulching (NT + SM) treatments. Mean values within a column in the same year followed by a different letter are significantly different (*p* = 0.05).


Grain yield for each crop season followed a similar trend with that of root dry weight (Table 4). Treatments with straw mulching tended to harvest more grain, while the yield in TT was lower, i.e., TT + SM > NT + SM > TT. In detail, TT + SM increased grain yield by 7.6% in 2017 and 11.3% in 2018, when compared with the TT treatment (*p* = 0.05). Moreover, compared with the TT treatment, no significant promotion was observed for grain yield under the NT + SM treatment.

#### **4. Discussion**

It was reported that, under the one-crop-per-annum system of coastal regions, rather than the rhizosphere nutritional conditions within the cropping season, farmers must pay attention to salt fluctuations during fallow [28]. Due to monsoon and tidal activities, the farmland environment in coastal areas is difficult to predict and utilize. Particularly in the domestic Tianjin Binhai district of the west Bohai Gulf (the experimental plot in this paper), local farmers prefer to conduct maize cultivation resorting to the rainfall leaching in summer. However, salt accumulation in the topsoil during the fallow periods is less reported. Therefore, this study was extremely different from previous demonstrations.

Firstly, in response to such a "fallow + summer maize" rotation cropping system, we attempted to optimize fallow management to provide an acceptable rhizosphere environment for subsequent sowing. Prior to the fallow, we covered soil surface with the maize residues, and at the end of the fallow, positive information was obtained. After 2 years of "fallow + summer maize" rotation cultivation, the TT + SM treatment reduced EC and total salt in the upper 30 cm soil profile by 22.9% and 25.4% (*p* = 0.05) compared with TT. The results confirmed that fallow mulching was conducive to minimize the upward salt accumulation, which was consistent with Deng et al. [29] within an adjacent experimental region. This may be attributed to the following three reasons: first, the solar radiation on the surface is shielded by maize straw, thereby reducing the temperature of the topsoil; second, the exposed area was reduced; third, straw mulching is also conducive to the prevention of wind, which may result in the weakened soil evaporation and reduced the upward movement of water. Hence, we infer that fallow mulching is conducive to diminishing salt accumulation through inhibiting bottom salt rising to the topsoil via water evaporation, which was also reported by Yusefi et al. [30].

Secondly, we also focused on the physicochemical properties of the top 30 cm soil profile after fallow mulching. Beneficial results were observed in volumetric SWC, bulk density, and SOM before the second cropping season, as affected by mulching treatment. From farmland measurements, TT + SM appeared to increase volumetric SWC by 10.3%, accelerate SOM by 17.8%, and decrease bulk density by 3.4% (*p* = 0.05) in comparison to the TT treatment. Adequate soil water storage is a requisite for crop germination, growth, and thereby gaining higher grain yield in fresh-starved farming [31]. The results showed that pre-seeding volumetric SWC had a significantly positive correlation relationship with grain yield, with a correlation coefficient of 0.827 (*p* = 0.05, Figure 5). Similar to our findings, Choudhary and Kumar [32] reported that a higher soil moisture while sowing contributes to a better crop performance with mulching under maize-based cropping practice. Importantly, maize grain yield under different treatments was significantly related to the applied mulching practices (*p* = 0.05, Tables 4 and 5); the crop performance showed a trend of TT + SM > NT + SM > TT. The post-fallow SOM and grain yield with straw mulching were significantly accelerated than those without mulching (*p* = 0.05), which was consistent with Zhao et al. [33] and Xue et al. [34]. This could be explained by the alleviation of salt accumulation and the improvement of nutrients in the topsoil treated by fallow mulching.

**Figure 5.** Relationship between pre-seeding volumetric soil water content (SWC) in the top 30 cm profile and in-season maize grain yield.

**Table 5.** ANOVA of the maize grain yield in line with the diverse treatments from 2016 to 2018. Y: year; T: treatments; Y × T: interaction influence of treatment and year. \*\* indicates significant difference at *p* = 0.01 level.


In terms of seedbed preparation (i.e., tillage mainly), we compared the effects of rotary tillage and no-till on crop growth in coastal salinized farmlands. The results showed that, under fallow mulching conditions, the rotary tillage seemed to be more favorable for matter accumulation (between the TT + SM and NT + SM treatments). This was due to better root development, which ultimately resulted in a higher maize yield [35], because rotary harrowing could loosen soil particles, cut off soil capillaries, and thereby slow down water evaporation, which is conducive to providing a better seedbed environment for sowing [36,37]. However, in coastal farmlands, soils are highly argillaceous with poor permeability, and in undisturbed soil, it is difficult to have positive impacts on root growing under the no-till treatment.

Meanwhile, this study was an adaptability exploration of conservation agriculture (CA) in coastal salt-affected soils. Despite the positive effects from the fallow mulching treatment, the no-till treatment did not achieve an optimal ecological environment and grain accumulation. In fact, we also conducted a no-till treatment alone (no-till seeding without fallow mulching), but only seldom was emergence monitored (results not shown). Pittelkow et al. [38] found that the no-till application alone had a negative impact on crop yield, while the negative effects of no-till could be minimized when other principles of CA (i.e., mulching or crop rotation) were applied. In dry or hydropenic climates, the yield profits with no-till combined with mulching may be due to improved soil moisture [39]. In this study, NT + SM gained an advantage in the post-fallow volumetric SWC by 5.8% and maize yield by 2.6% over the TT treatment after a 2-year cultivation, which was consistent with previous ones.

In the one-crop-per-annum cropping system, grain yield is only one of the diverse components that reflect soil productivity, and there is an urgent need for farmers and researchers to ameliorate farming management, among other socio-economic and ecological indicators. Especially in "fallow + summer maize" rotation systems, we are required to focus on both of seasonal cultivation and fallow management, rather than crop cultivation alone. The findings confirm our hypothesis that rational fallow management can reach a lower salt stress and higher water conditions for subsequent maize sowing. This will help to increase post-fallow crop yields.

However, there are several deficiencies in this research. Firstly, despite the improved soil physicochemical properties before sowing, soil evaporation during fallow was not monitored. In fact, the upward salt accumulation via capillaries is closely related to soil evaporation. Secondly, the principles of CA (i.e., no-till, soil cover, and crop rotation) were discussed in this study, but their positive influence under the no-till treatment was limited in response. A deeper interpretation of the farming patterns in coastal areas is required.

#### **5. Conclusions**

Compared with traditional tillage, fallow mulching showed an advantage in reducing the total salt of topsoil, increasing water storage, and enhancing maize growth. After 2 years of the "fallow + maize" rotation system cultivation, TT + SM reduced soil EC and the total salt of the upper 30 cm soil profile by 22.9% and 25.4% (*p* = 0.05), respectively, compared with the TT treatment. The results also indicate an improvement in volumetric SWC by 10.3%, SOM by 17.8%, and ultimately, grain yield by 11.3% (*p* = 0.05) under the TT + SM treatment.

Based on the above findings, this study could provide some guidance for scholars. Firstly, as a by-product from croplands after harvest, residues provide a method (retention by mulching) for solving agriculture-related social and economic problems, such as straw burning and biomass recycling. Secondly, aiming at coastal salinized soils, fallow mulching combined with crop rotation can also be extended to inland dry agricultural areas that require fallow to preserve soil moisture. Of course, agricultural production is a complicated, multifaceted collaborative system, and fallow cover is not an immediate management. In the coastal farming practice, it is recommended to carry out long-term fallow mulching to maintain an acceptable water and salt environment in the rhizosphere. Future studies will focus on the long-term impact of fallow mulching on rotation farming and multifaceted analyses in terms of transpiration, microorganism, soil structure, etc., will be introduced. In the meantime, this study will be applied in other soil environments, such as dryland or fresh-starved farming systems.

**Author Contributions:** Conceptualization, Y.Z.; methodology, L.H.; software, W.Y. and L.H.; formal analysis, Y.Z.; investigation, Y.Z.; data curation, L.H.; writing—original draft preparation, W.Y.; writing—review and editing, Y.Z.; funding acquisition, Y.Z. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Natural Science Foundation of the Jiangsu Higher Education Institutions (20KJB416008), the Jiangsu Modern Agricultural Machinery Equipment and Technology Demonstration and Promotion Project (NJ2021-16), the Yangzhou University Interdisciplinary Research Foundation for Crop Science Discipline of Targeted Support (yzuxk202007).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


## *Article* **Fenlong-Ridging Promotes Microbial Activity in Sugarcane: A Soil and Root Metabarcoding Survey**

**Mingzheng Duan 1,2, Yanyan Long 1,2,3, Hongzeng Fan 1,2, Li Ma 1,2, Shijian Han 1,2, Suli Li 1,2, Benhui Wei <sup>3</sup> and Lingqiang Wang 1,2,\***


**Abstract:** Fenlong-ridging (FL) is a recently proposed conservation tillage technology which has dramatic differences to traditional ones. Previous studies have demonstrated in many crops that FL has yield-increasing effects without additional inputs. However, little is known about the role that microbes play in mediating the growth-promoting effects of FL, which restricts its further application and improvement. Here, we characterized variation in the soil and root microbial diversity of sugarcane (GT44) under FL and traditional turn-over plough tillage (CK) by conducting 16S rRNA and ITS metabarcoding surveys. We also measured several phenotypic traits to determine sugarcane yields and analyzed the chemical properties of soil. We found that: (i) plant height (PH) and total biomass weight (TW) of sugarcane plants were 9.1% and 21.7% greater under FL than those under CK, indicating\increased biomass yield of the sugarcane in FL operation; (ii) contents of organic matter, total nitrogen, available phosphorus, and available potassium were lower in soil under FL than those under CK, which indicates the utilization of soil nutrients was greater in FL soil; (iii) FL promoted the activity of endophytic microbes in the roots, and these diverse microbial taxa might have an effect on sugarcane yield and soil chemical properties; and (iv) *Sphingomonas, Rhizobium*, and *Paraburkholderia* and *Talaromyces, Didymella*, and *Fusarium* were the top three most abundant genera of bacteria and fungi, respectively, in soil and root samples. In addition, strains from *Rhizobium* and *Talaromyces* were isolated to verify the results of the metabarcoding survey. Overall, our study provides new insights into the role of microbes in mediating the growth-promoting effects of FL. These findings could be used to further improve applications of this novel conservation tillage technology.

**Keywords:** conservation tillage; metabarcoding; smash ridging; soil chemical properties; soil microbial diversity; sugarcane

#### **1. Introduction**

The sustainable production of food is being increasingly challenged by human population growth and climate changes [1]. Conservation tillage is primarily used to protect soils from erosion and compaction, conserve soil moisture, and reduce production costs [2]. Soil and root microbial diversity and community composition are important for sustainable agriculture and conservation tillage because microbes mediate the processes supporting agricultural production [3–5]. However, many of these agriculturally important soil and root microbial taxa, and the impacts of different tillage practices on their abundances are largely unknown [6]. More studies are required to identify the soil and root microbial taxa under different types of tillage operations [7].

**Citation:** Duan, M.; Long, Y.; Fan, H.; Ma, L.; Han, S.; Li, S.; Wei, B.; Wang, L. Fenlong-Ridging Promotes Microbial Activity in Sugarcane: A Soil and Root Metabarcoding Survey. *Agriculture* **2022**, *12*, 244. https://doi.org/ 10.3390/agriculture12020244

Academic Editors: Chengfang Li and Lijin Guo

Received: 30 November 2021 Accepted: 1 February 2022 Published: 8 February 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

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Fenlong-ridging (i.e., smash ridging, FL) is an advanced conservation tillage technology that has recently been proposed to increase the yields of many crops, such as rice and sugarcane, without requiring increases in fertilizer application [8,9]. Whereas traditional tillage methods involve plowing the soil, FL is a deep tillage technology (up to 40 cm in depth) that works by horizontally crushing the soil in situ. It maintains soil nutrients and moisture and increases soil air permeability, thereby enhancing the growth of crop roots [8]. This sustainable tillage method has become increasingly used in China in recent years and has helped contribute to achieving China's carbon neutrality target [10,11]. Several studies have been tried to reveal the agronomic and/or physiological mechanism underlying the yield differences under Fenlong-ridging processing [9,12–17] but little work has been done on the alteration of the physicochemical properties of the soils surrounding plants root systems. As we know, the soil and endophytic microbial diversity have substantial effects on crop yield, play an important role in regulating the supply of nutrients for crops, and mediate resistance to plant diseases and insect pests [7]. Plants and the associated microbiota form a "holobiont" [7]. When plants are facing biotic stress, they may combat stress by altering root exudates to recruit beneficial microbes from the soil, and also can improve soil chemical properties condition by the same approach [7,18]. We can speculate that the FL should causes many differences in root micro-ecological environments. Understanding the role of microbes in FL will be benefit to the application and improvement of this technology.

Sequencing technology is generally considered one of the most effective approaches for characterizing the diversity of soil microbes [19]. Many previous studies have used various sequencing technologies to study bacterial communities, and these studies have provided key insights into the diverse ways in which microbes can affect plants. For example, Wang et al. [20] studied the response of the sugarcane rhizosphere bacterial community to drought stress, Achouak et al. [21] examined the control of microbial denitrification activity by plant hosts; and Guyonnet et al. [22] found that plant nutrient resource use strategies shape active rhizosphere microbiota through root exudation using metabarcoding sequencing.

Here, we studied the role of microbes in mediating the growth-promoting effects of FL in sugarcane (*Saccharum officinarum* L.), which is the world's largest sugar-yielding crop and the second largest source of biofuel globally [23]. Specifically, we measured phenotypic indicators of yield, the chemical properties of soil, and the diversity of fungi and bacteria in the roots and rhizosphere of sugarcane through metabarcoding under FL tillage and conventional tillage. The results of the metabarcoding survey were verified by a culture-omics experiment.

#### **2. Materials and Methods**

#### *2.1. Materials*

#### 2.1.1. Experimental Design

The experiment was conducted on the campus of Guangxi University, Nanning City, China. The experimental sugarcane field was surrounded by other fields of crops, including rice, corn, and multiple fruit trees covering 380 m2 (Figure 1a). Two tillage methods were used before planting sugarcane, FL and conventional tillage (CK), each of which were applied every other row (i.e., tillage methods were alternated among rows). For FL, the soil layers were crushed and loosened to a depth of 40 cm. CK was conducted by turnover plowing with a mini-tiller, and the soil was tilled to a depth of 20 cm. Our tillage methods were based on the procedures described by Zhang et al. [8]. To minimize the effect of sampling on sugarcane phenotype data, we established protection rows and designated specific areas from which phenotype data and soil and root samples were collected (Figure 1a).

**Figure 1.** Design of the plots in field experiment (**a**) and the procedure of the sampling and analysis (**b**). "Fenlong" indicates Fenlong-ridging while "CK" is conventional tillage. At the sixth month after planting, the samples of sugarcane roots and rhizosphere soil were collected for metabarcoding sequencing and testing of the soil chemistry properties. Meanwhile, artificial isolation of endophytic bacteria and fungi from roots were conducted. At the ninth month, the sugarcane yield traits were investigated. Based on the data obtained from above processes, the microbial process of Fenlong-ridging in sugarcane was evaluated and analyzed.

#### 2.1.2. Soil and Root Sampling

Soil and roots were sampled after six months of growth (Figures 1b and 2b). We randomly selected six sugarcane plants in CK and FL rows from the soil and root sample collection areas (Figure 1a) for sampling. First, we extracted entire sugarcane plants, removed the soil directly under the root system, crushed the soil, and then sifted it through a 0.6-mm sieve to obtain soil samples. The taproots were then cut and washed three times with sterile water, three times with 75% ethanol, and finally three times with sterile water (cleaning with residual ethanol) to obtain root samples.

#### *2.2. Methods*

This study was conducted per the procedures shown in Figure 1b.

#### 2.2.1. Estimation of Sugarcane Yield

We evaluated sugarcane yields using two phenotypic traits, including total biomass weight (TW) and plant height (PH). A violin plot was created in R using the ggplot2 package (version 3.3.5; http://CRAN.R-project.org/package=ggplot2; accessed on 1 May 2021).

#### 2.2.2. Analysis of Soil Chemical Properties

The mixed soil samples from FL and CK rows were used to determine chemical indicators, including organic matter (OM), total nitrogen (TN), available phosphorus

(AP), and available potassium (APO), which were measured at the Center of Agricultural Analysis, Testing and Research, Guangxi University, Nanning City, China.

**Figure 2.** Improved agronomic performance and phenotypes of sugarcane plants and the soil nutrients alteration in Fenglong compared to traditional tillage. (**a**) Statistical analysis of agronomic traits of sugarcanes under conventional tillage (CK) and Fenlong (FL) at six months. The violinshaped columns indicate the distributions of the data. The curves of the violin-shaped columns represent the probability curve of the data distribution. The number of data points at a particular value is positively correlated with the width of the probability curve. The upper and lower ends of each violin-shaped column indicate the maximum and minimum values of non-outlier data, respectively. The upper and lower edges of the vertical line in each violin-shaped column indicate the 75th and 25th percentiles of the data, respectively; and the central dot indicates the median. (**b**) Phenotypes of the sugarcane plants at six months. (**c**) Soil nutrient traits of the soils under CK and FL conditions. The box-plot shows the maximum (top whisker), minimum (bottom whisker), median (line inside the box), upper quartile (top margin of the box), and lower quartile (lower margin of the box).

#### 2.2.3. Metabarcoding Sequencing

Microbial DNA was extracted using HiPure Soil DNA Kits (Magen, Guangzhou, China) and DNA Isolation Kits (Sangon, No. B518231, China) per the manufacturer's protocols. The 16S rRNA V5–V7 and ITS 1–2 regions of the metabarcoding biomarkers were amplified by PCR with the primers 799F: AACMGGATTAGATACCCKG and 1193R: ACGTCATCCCCACCTTCC [24] for bacteria and the primers ITS1-F: CTTGGTCATTTA-GAGGAAGTAA and ITS2: GCTGCGTTCTTCATCGATGC [25] for fungi. The purified amplicons were pooled in equimolar ratios and paired-end sequenced (PE250) on an Illumina platform (Novaseq 6000 sequencing) following standard protocols.

#### 2.2.4. Statistical Analysis

Representative operational taxonomic unit (OTU) sequences were classified by a naïve Bayesian model using an RDP classifier [26] (version 2.2) based on the SILVA database (for 16S rRNA metabarcoding data) [27] (version 132) and UNITE database (for ITS metabarcoding data) [28] (version 8.0), with a confidence threshold value of 0.8. All figures were made using R projects. Venn analysis was used to show OTU differences among different groups and was performed in R using the VennDiagram package (version 1.6.16); [29] (version 1.6.16); Sob (to assess species richness level), Shannon and Simpson (to comprehensively assess richness and evenness of species), and Good's coverage (to assess sequencing saturation of samples). Indices were calculated in QIIME [30] (version 1.9.1). Principal component analysis (PCA, to assess sample composition relation) and Tukey's honestly significant difference test (HSD, to assess genera significance of differences in abundance between groups) were performed in R using the vegan package (version 2.5.3; http://CRAN.R-project.org/package=vegan; accessed on 4 March 2021). Circular layout representations of species abundance were graphed using Circos [31] (version 0.69-3). All the above data were based on quantitative statistics of OTU numbers without any model transformation before analysis.

#### 2.2.5. Isolation and Identification of Bacterial and Fungal Strains

First, clean sugarcane taproots from FL rows were collected, cut into pieces, and coated in medium (Fungi: PDA, which consisted of 200 g of potatoes, 20 g of glucose, and 16 g of agar per liter; bacteria: NB, which consisted of nutrient broth, 10 g of peptone, 3 g of beef extract powder, and 5 g of NaCl per liter) for culture at 25 ◦C (fungi) and 37 ◦C (bacteria). After 12 to 72 h, single colonies were selected for culture and preserved. We used two pairs of primers of ITS 16S rRNA as the DNA barcoding markers to identify the isolated strains, ITS1: TCCGTAGGTGAACCTGCGG and ITS4: TCCTCCGCTTATTGATATGC [32] (fungi) and 27f: AGAGTTTGATCATGGCTCAG and 1492r: ACGGTTACCTTGTTACGACTT [33] (bacteria). We identify the taxon of isolated strains by comparing with reference sequences in the database via phylogenetic trees. The reference sequences used in this study were downloaded from Genbank, and all DNA barcoding sequences together with reference sequences were aligned using Clustal X (1.83). Phylogenetic analysis based on the neighborjoining method with 1000 bootstrap replications was conducted using MEGA v.4.0.

#### **3. Results**

#### *3.1. The Improved Agronomic Performace and the Altered Soil Properties Were Found in Fenlong Compared with the CK*

We evaluated sugarcane yield using two agricultural traits: total biomass weight (TW) and plant height (PH). The mean values of TW for FL and CK were 4.6 kg and 3.6 kg per plant (21.7% increase in FL), and the mean values of PH were 1.32 m and 1.2 m per plant (9.1% increase in FL), respectively (Figure 2a). Generally, TW and PH were increased under FL compared with CK. The growth-promoting effects of FL were apparent at six months into the experiment, as the mean PH was approximately 9% higher under FL at this point compared with CK (CK: 2.18 m; FL: 2.39 m, Figure 2b). Overall, sugarcane yield was higher under FL than under CK.

We evaluated soil chemical properties by measuring five soil nutrient parameters. For FL and CK, the mean values of OM were 19.13 and 20.96 g/kg; the mean values of TN were 1.07 and 1.13 g/kg; the mean values of AP were 121.87 and 134.41 mg/kg; and the mean value of APO were 154.66 and 158 mg/kg, respectively (Figure 2c). The mean values of OM, TN, AP, and APO were lower in the FL group than in the CK group, which suggests that sugarcane cultivated by FL utilized soil nutrients more effectively than when it was cultivated by CK.

#### *3.2. Metabarcoding Survey of Soil and Root Microbes*

3.2.1. Sequencing Analysis Revealed the Greater Diversity in Fenlong Samples than in CK Samples for Fungi and/or Bacteria

A total of 5,613,900 metabarcoding tags were obtained from the sequencing data. The clustering analyses of the soil and root samples revealed 1618 and 648 operational taxonomic units (OTUs) on average for bacteria (based on 16S rRNA) and fungi (based on ITS), respectively (Table 1). A Venn diagram is a picture showing sets of things that have a shared quality as circles that cross over each other, to show which qualities the different sets have in common. It was revealed that 36.5% (859/2356) of bacterial OTUs and 23.3% (309/1325) of fungal OTUs were shared among the four groups of samples (ROOT-FL, SOIL-FL, ROOT-CK, and SOIL-CK) (Figure 3a,b). Alpha diversity was analyzed by Tukey's HSD to assessing species diversity. The mean values of the observed species (Sob) index

of soil samples from the CK and FL groups were 2058 and 2057.5 (bacteria) and 854.16 and 823.66 (fungi), respectively. The mean values of the Sob index of root samples from the CK and FL groups were 1141.83 and 1215.66 (bacteria) and 470.16 and 444.16 (fungi), respectively. The mean values of the Shannon index of soil samples from the CK and FL groups were 8.54 and 8.55 (bacteria) and 5.75 and 5.47 (fungi), respectively. The mean values of the Shannon index of root samples from the CK and FL groups were 7.03 and 6.95 (bacteria) and 3.98 and 3.0 (fungi), respectively. The mean values of the Simpson index of soil samples from the CK and FL groups were 0.99 and 0.99 (bacteria) and 0.94 and 0.92 (fungi), respectively. The mean values of the Simpson index of root samples from the CK and FL groups were 0.98 and 0.97 (bacteria) and 0.85 and 0.68 (fungi), respectively. The mean values of the Good's coverage index were all under 0.99, indicating that the level of sequencing was adequate for elucidating microbial diversity (Figure 3c,d). To further assess sample composition relation, we performed principal components analysis (PCA). It was shown that the PC1 alone could divided the OTU of bacteria into the soil group and the root group, while the PC2 further distinguish the differences existed within root group (Figure 3e). However, the differences in OTU of fungi between soil and root was not obviously (Figure 3f). It was revealed that greater variation in FL samples than in CK samples for fungi in both root samples and soil samples (Figure 3f), while the greater variation in FL samples than in CK samples for bacteria in root samples but not in soil samples (Figure 3e). Overall, the diversity of endophytic bacteria and fungi in roots was generally lower than that of soil bacteria and fungi, and there was no significant difference in the diversity of OTUs between FL and CK soil and root samples according to the Sob index (Figure 3c,d). However, significant range variation in the Shannon and Simpson indices was observed among FL and CK soil and root samples. For example, Simpson index values ranged from 0.78 to 0.90 in CK root samples but ranged from 0.47 to 0.90 in FL root samples (Figure 3c,d).


**Table 1.** Statistics of the metabarcoding sequencing data for soil and root samples. FL stands for Fenlong-ridging, and CK stands for conventional tillage.

**Figure 3.** Venn analysis, alpha diversity analysis, and principal component analysis based on the recovered OTUs. (**a**,**b**) Venn analysis of bacteria and fungi, respectively; (**c**,**d**) alpha diversity analysis for bacteria and fungi using Tukey's HSD; (**e**,**f**) principal component analysis of the OUT of the bacteria and fungi from soil and roots under FL and CK. The colored dots in the figures correspond to the different sample groups.

#### 3.2.2. The Predominant Microbial Genera Identified in Fenlong Operation

We analyzed differences in the community compositions of bacteria and fungi in soil and root samples from the CK and FL groups based on the SILVA and UNITE databases. The main microbial genera detected are shown in Figure 4a,b. After low-abundance taxa and unmatched OTUs were removed, the top 10 most abundant bacteria were *Sphingomonas* (24.57, 21.38, 25.17%, and 28.89 in SOIL-CK, SOIL-FL, ROOT-CK, and ROOT-FL, respectively), *Rhizobium* (6.22, 6.3, 33.76, and 53.72%), *Paraburkholderia* (13.16, 12.03, 49.18, and 25.63%), *Bradyrhizobium* (11.17, 12.21, 33.63, and 42.98%), *Dyella* (10.74, 10.95, 42.26, and 36.06%), *Amycolatopsis* (5.89, 5.05, 35.85, and 53.21%), *Pseudolabrys* (26.41, 27.14, 24.16, and 22.29%), *Nocardioides* (36.18, 32.21, 13.63, and 18.09%), *Devosia* (9.49, 9.39, 48.73, and 32.39%), and *Haliangium* (17.4, 16.61, 46.01, and 19.98%). The top 10 most abundant fungi were *Talaromyces* (14.83, 19.79, 27.92, and 34.46%), *Didymella* (48.08, 43.3, 4.48, and 4.15%), *Fusarium* (34.51, 36.69, 15.89, and 12.91%), *Corynascella* (6.78, 7.42, 56.12, and 29.68%), *Ramichloridium* (39.63, 53.22, 3.61, and 3.54%), *Rhizoctonia* (50.3, 17.41, 29.33, and 6.65%), *Penicillium* (47.23, 27.39, 19.96, and 5.42%), *Cladosporium* (41.86, 50.69, 3.38, and 4.08%), *Curvularia* (42.44, 36.53, 11.8, and 9.24%), and *Zopfiella* (20.64, 7.96, 63.45, and 7.95%).

**Figure 4.** Microbial community composition and taxa (genera) of the top three biomarker species of bacteria and fungi at the genus level. (**a**,**b**) Top 10 abundant bacterial and fungal genera in soil and roots in the CK and FL groups. The colors of the upper half of the circle indicate the different sample groups, and the color of the lower half of the circle indicates the main genera. The colors of the outermost ring of the lower half of the circle indicate the genera, and the innermost ring of the circle indicates the abundance of the genera in the different groups. The thickness of the lines connecting genera to samples indicates the abundance of the genera in particular samples. (**c**,**d**) Biomarker genus abundance analysis for bacteria and fungi by Tukey's HSD.

We characterized differences in the distribution of the top three abundant genera between all groups (including low-abundance taxa and unmatched OTUs). The mean total relative abundances of the top three bacterial genera *Sphingomonas*, *Rhizobium*, and *Paraburkholderia* were 6.62, 3.77, and 2.9%, respectively (Figure 4c). The mean total relative abundances of the top three fungal genus *Talaromyces*, *Didymella*, and *Fusarium* were 40.04, 2.88%, and 2.4%, respectively (Figure 4d). No significant differences in the relative abundances of fungal genera in soil and root samples in the CK and FL groups were observed.

Although no statistically significant differences between CK and FL samples were detected, two bacterial and fungal genera, *Rhizobium* and *Talaromyces*, were more common in the ROOT-FL group than in the ROOT-CK group. Specifically, the abundance of *Rhizobium* was 33.76 and 53.72% in the ROOT-CK and ROOT-FL groups, respectively, and the abundance of *Talaromyces* was 27.92 and 34.46% in the ROOT-CK and ROOT-FL groups, respectively (Figure 4a,b).

#### *3.3. Isolation and Classification of the Specific Endophytic Root Bacteria and Fungi from Sugarcane Rhizosphere*

To verify the above findings, we performed a culture-omics experiment on sugarcane samples from the ROOT-FL group. A total of 100 bacterial strains and 50 fungal strains were isolated, and 14 bacterial strains and 11 fungal strains could be resolved by DNA barcoding sequencing (16S rRNA 27f/1492r was used for bacteria, and ITS 1/4 was used for fungi). The sequences of related species downloaded from Genbank (Table 2) were used to construct phylogenetic trees of fungi and bacteria to identify the isolated strains. A total of 13 of the 14 bacterial strains clustered with sequences from Genbank (Figure 5a; Table 3). R1 was not closely clustered with sequences of type species, but instead was most closely clustered with *Rhizobium* species (Figure 5a; Table 3). R3, Lx2.2, Rx11, and R2 were most closely clustered with *Bacillus aryabhattai*; Rx4 and Lx2.1 were most closely clustered with *Bacillus aerius*; Rx12 and Rx18 were most closely clustered with *Bacillus safensis*; and Rx1, Rx16, Rx5, Rx13, and R5 were most closely clustered with *Ralstonia* sp. (Figure 5a; Table 3). Among fungi, T16 and T13 were most closely clustered with *Penicillium ludwigii*; RT8 was most closely clustered with *Penicillium raperi*; T5 was most closely clustered with *Penicillium refeldin*; T24 was most closely clustered with *Penicillium* sp.; T3 was most closely clustered with *Aspergillus terreus*; T19 was most closely clustered with *Talaromyces* sp.; RT4, T8, and R3 were most closely clustered with *Talaromyces argentin*; and T18 was most closely clustered with *Curvularia petersoni* (Figure 5b; Table 3). We thus successfully isolated species from the high-abundant genera *Rhizobium* and *Talaromyces* from sugarcane roots.

**Table 2.** Sequence information (Genbank ID) used in this study.


Note: 16S rRNA 27f/1492r was used to identify bacteria, and ITS1/4 was used to identify fungi.

**Figure 5.** Phylogenetic tree of bacteria (**a**) and fungi (**b**). The similarity distance scale is provided in the lower left corner. Values on the nodes of the phylogenetic tree are bootstrap values.


**Table 3.** Endophytic strains of fungi and bacteria isolated in this study.

#### **4. Discussion**

The development of sustainable systems of tillage with reduced effort and reduced expenditure is important for agriculture [34,35]. Fenlong (FL) is an advanced tillage operation newly developed that has been shown to significantly increase the yield of many crops, including sugarcane, without extra inputs [9,12,13,17]; however, the mechanism by which FL promotes crop growth has not been far from enough explored to date. We identified the bacteria and fungi in both soil and roots of sugarcane under FL and CK to provide insight into how soil and root microbiota mediate the growth-promoting effects of FL.

Some previous work reported that FL significantly increased sugarcane yield up to 20% [9,12]. Plant height of the sugarcane was the most robust indicator of crop yield in our data set (Figure 2a,b). Similar increases in yield have been reported in rice [8]. Our results were basically consistent with these previous studies. In addition, we also found that FL increased the yield of sugarcane by increasing the efficiency with which soil nutrients could be utilized by plants (Figure 2). The effects of tillage practices on the chemical properties of soil as well as crop growth and yields vary [36]. In FL, the soil can be deeply plowed with minimal disturbance [8]. Thus, FL provides the advantages of deep tillage, including the stability of tilled soil, which promotes the development of crop roots. There was no significant difference in the available potassium content of soil in the FL and CK groups. Potassium is key for the synthesis and translocation of sucrose [37]. This finding suggests that FL does not affect Brix value of sugarcane. Overall, our findings confirmed the efficacy of FL for increasing crop yields.

Our microbial metabarcoding survey revealed that FL promoted the activity of endophytic microbes in sugarcane roots. Although FL affected the Sob index slightly in sugarcane soil and roots, analysis of alpha indices revealed significant differences in the abundance of specific OTUs in the ROOT-FL group relative to the other three groups (Figure 3c,d), indicating that the abundance of endophytic bacteria and fungi varied greatly after FL. In addition, principal components analysis revealed that FL could increase differences in the abundances of OTUs among root samples (Figure 3d–f). These findings indicate that FL increases the diversity of the root environment. We supposed FL may enhance soil-root interaction due to the soil being smashed while the main soil layer that makes the contact area between the roots and the soil is not disturbed. This may increase intensity of competition among microbial taxa. Competition between microbial taxa might also result in the appearance of additional metabolic processes [18], and this might contribute to explaining the sugarcane yield-promoting effects of FL.

Among the top three most abundant bacterial genera, *Rhizobium* was particularly noteworthy because the abundance of this genus varied greatly among all groups (Figure 4c), and was most abundant in the FL group (Figure 4a). Rhizobia species are plant growthpromoting bacteria that provide nitrogen to hosts by binding to plant roots [38]. Rhizobia populations have been previously studied in the soil and roots of sugarcane [20,39]. We also isolated a strain (R1) from the roots of sugarcane under FL that was most closely clustered with *Rhizobium*, and the phylogenetic tree suggested that this isolate might represent a new species (Figure 5a). Other strains of soil and root bacteria that were isolated or identified included: *Sphingomonas*, which is a common genus that has been widely isolated from soil [40]; *Paraburkholderia*, which plays a role in promoting soil metabolism [41]; *Bacillus* spp., which produce various compounds that contribute to the biocontrol of plant pathogens and promote plant growth [42]; and *Bacillus aryabhattai*, which plays a role in soil bioremediation [43] (Figure 5a); *Ralstonia* sp., which has been reported produce volatile compounds that promote plant growth [44], and that may related to the growth-promoting properties of FL. Among the top abundant fungal genera detected and isolated strains, *Talaromyces* was dominant in both soil and root samples. *Talaromyces* is known to be able to carry out phosphate solubilization [45]. The abundance of *Talaromyces* was higher in root and soil samples from the FL group (Figure 4d). Thus, *Talaromyces* might affect PLT and TW traits; however, this hypothesis requires further testing. Besides, with respect to the other two fungal top genera and isolated strains (genera of *Didymella*, *Fusarium, Penicillium*, *Aspergillus* and *Curvularia*), their relative abundance was low which implies their association with FL may not significant.

In summary, we revealed differences in the diversity of microbial taxa in the soil and roots of sugarcane under FL and CK. Our findings provide new insights that could be used to enhance sugarcane yields. The results of this research will also aid further improvement and application of FL.

**Author Contributions:** Conceptualization, L.W. and B.W.; methodology, M.D. and S.H.; software, M.D.; investigation, M.D., H.F., L.M. and Y.L.; resources, L.W. and Y.L.; data curation, M.D.; writing original draft preparation, M.D.; writing—review and editing, L.W. and Y.L.; visualization, M.D.; supervision, L.W.; project administration, L.W. and S.L.; funding acquisition, L.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by China Postdoctoral Science Foundation (2020M683619XB); Guangxi innovation driven development project (No. AA20302020-3); Natural Science Foundation of Guangxi (2020GXNSFDA238027).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The raw amplicon sequencing dataset is available in the NCBI Sequence Read Archive under BioSample accession PRJNA783171.

**Acknowledgments:** We thank TopEdit (www.topeditsci.com, accessed on 11 November 2021) for linguistic assistance during the preparation of this manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

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