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Article

Effects of the Rapid Construction of a High-Quality Plough Layer Based on Woody Peat in a Newly Reclaimed Cultivated Land Area

by
Sicheng Zhang
1,†,
Rui Zhao
1,†,
Kening Wu
1,2,3,*,
Qin Huang
1 and
Long Kang
1
1
School of Land Science and Technology, China University of Geosciences, Beijing 100083, China
2
Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing 100035, China
3
Technology Innovation Center of Land Engineering, Ministry of Natural Resources, Beijing 100083, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2022, 12(1), 31; https://doi.org/10.3390/agriculture12010031
Submission received: 29 November 2021 / Revised: 21 December 2021 / Accepted: 27 December 2021 / Published: 28 December 2021
(This article belongs to the Special Issue Effects of Fertilizer and Irrigation on Crop Production)
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Abstract

:
To implement the balance system of cultivated land in occupation and supplement and to adhere to the principle of “supplement the occupied cultivated land of high quality with the one bearing same quality”, in the thesis, a field experiment was conducted to study the effects of woody peat on soil physical, chemical, and biological properties of the plough layer and its crop yield. Furthermore, the correlation between soil indexes and crop yield under the best fertilization mode through the addition of the natural material of woody peat instead of lengthy cultivation of the plough layer to rapidly construct a high-quality plough layer and solve the practical problem that the natural endowment of newly reclaimed cultivated land is far less than the occupied high-quality cultivated land was explored. The land remediation project of Fuping County, Hebei Province, was taken as the experimental area, and the five most representative and effective datasets were selected and studied. The results demonstrated that the addition of woody peat and rotten straw could reduce soil particle size and bulk density and alleviate soil viscosity and acidification. An increase in soil organic matter, soil microbial biomass carbon (MBC), alkali-hydrolyzable nitrogen, available phosphorus, and available potassium and a decrease in the heavy metal content were also observed. The results indicated that the application of woody peat achieved the expected effect of the rapid construction of a high-quality plough layer. The best mode of fertilization was A2, which provided a good reference for the rapid construction of a high-quality plough layer in the future. The analysis of the correlation between soil indexes and crop yield illustrated that the organic matter content, soil available nutrients, and crop yield had a significant positive correlation; the organic matter content and soil available nutrients showed the same tendency, which suggests that soil organic matter content and soil fertility level are closely related and that soil fertility plays a decisive role in crop yield under the same external conditions. Woody peat exerted an eminent influence on the organic matter content and soil available nutrients to determine the change in crop yield, which provides a reliable basis for future research on land improvement projects to increase crop yield.

1. Introduction

The lack of high-quality cultivated land has been recognized as a major problem affecting food security worldwide [1,2]. In China, there is a focus “supplementing occupied cultivated land of high quality with the soil of the same quality”, but this is often not followed through on. Thus, there is poor protection of cultivated land resources, leading to the over-occupation of high-quality fertile land and low soil quality of newly reclaimed cultivated land [3,4,5].
The quality of cultivated land is influenced by the lack of a high-quality plough layer in newly reclaimed cultivated land areas. In addition, the previously intensive long-term misuse of pesticides has negatively impacted soil biodiversity, agricultural sustainability, and food security to the long-term detriment of nutrition security and human and animal health [6,7,8]. Recent research has focused on determining the characteristics of high-quality plough layers for long-term cultivation, proposing the rapid construction of a high-quality plough layer to replace elements needed for long-term cultivation and to improve the quality of cultivated land over a short period of time [9,10,11]. As a new soil improvement material, woody peat, with a carbon content of up to 60–65%, has attracted significant attention, but research is only at a basic stage of determining whether woody peat can promote crops, with few studies on the effects of the addition of woody peat to fertilizers [12,13], which is now a research focus [14].
Woody peat is an intermediate product of the conversion of plant residues to coal and, as the main component of soil organic matter, it is rich in humus, having a high humic acid content [10,11,15,16]. Soil organic matter [17] affects metal mobility in soil through adsorption, complexation, and redox reactions. Researchers have investigated the metal adsorption mechanism of woody peat. Hu et al. [18] reported that peat can fix heavy metals effectively as a result of specialized metal adsorption mechanisms, which depend on the type of peat, preparation method, and the type and concentration of metal [19]. Wang [14] showed that the combination of peat and iron-containing compounds contributed to the fixation of As and Cd in the soil. In addition, Wei et al. [20] determined the quantitative and qualitative changes of different forms of phosphorus during composting by adding biochar and woody peat through the sequential extraction method and X-ray absorption near-edge structure, which demonstrated that the addition of woody peat is conducive to the humic acidification of compost, indirectly improving refractory phosphorus by adjusting the microbial community. Fu et al. [21] investigated the impact of eroded soils of different textures on crop growth and physiology, soil evaporation, and soil organic matter after adding woody peat and found that the addition of woody peat increased the soil organic matter (SOM) concentration in degraded soils, with a suitable amount of woody peat and the clay content significantly contributing to SOM protection. Research in China on woody peat has focused on the effects of woody peat on soil nutrients, soil organic matter, crop growth, yield and quality indicators, but there are few systematic studies on physical and chemical soil indexes, such as the soil bulk density, pH, organic matter content, electrical conductivity, alkali-hydrolyzable nitrogen, available phosphorus, available potassium, the content of soil heavy metal of arsenic (As), cadmium (Cd), chromium (Cr), lead (Pb), mercury (Hg) and soil biological indexes, including the soil microbial biomass carbon (MBC), etc. Moreover, there is a lack of studies on how to combine woody peat with inorganic fertilizers and the suitable proportions [14,22,23,24,25,26]. Consequently, the effects of woody peat, as a new soil conditioner, on physical and chemical soil properties, soil biological properties, and crop yield are open to further research.
Nabiollahi et al. [27] reported that soil organic matter is vital for agricultural productivity. Soil organic matter comprises stable compounds with unique chemical properties, i.e., 80–95% refractory (stable) humus and 5–20% easily decomposed (active) organic matter [28,29]. Application of rotten straw with woody peat promotes easily decomposed (active) organic matter and shortens cultivation times and the rapid construction of a high-quality plough layer [30]; nonetheless, the addition of woody peat only improves the soil structure; thus, if the diversity and abundance of microorganisms were promoted by adding a bio-activating regulator, woody peat would be activated to improve the soil organic matter, facilitate mass increases, enrich the diversity of microorganisms, and improve the fertility of the plough layer, by linking soil organic matter–aggregate–biological activity to result in improved crop yields [31,32].
The current study focuses on the land improvement project area of Fuping County, Hebei Province, using newly reclaimed farmland sown with millet. The study analyzes both the characteristics and properties of the fertile plough layer formed by long-term cultivation, the soil physical, chemical, and biological indices, and crop yield before and after the application of woody peat. The results provide insights into the mechanism of action of woody peat in terms of soil improvement and the correlation between the soil index and crop yield under the best fertilization mode. Such information is useful for developing high-quality plough layers and for laying a theoretical foundation for improving the soil quality of newly cultivated land and the healthy and sustainable development of agriculture. In so doing, it will address several aims:
  • to study the effects of woody peat on the soil physical, chemical, and biological properties of the plough layer and its crop yield;
  • to study the correlation between soil indexes and crop yield under the best fertilization mode.

2. Materials and Methods

2.1. Study Area

The study was carried out in Xiaoshifang Village, Fuping Town, south-central Fuping County, Hebei Province, China (114°15′11″–114°16′41″ East, 38°48′26″–38°47′35″ North) (Figure 1). Featuring complex terrain, the study region has vertical and horizontal gullies, with a gradual increase in altitude from southeast to northwest. The area is dominated by a continental monsoon climate, whereby winters are cold and dry, with little snow, spring is characterized by dry, warm winds, summer by rainfall, high temperature and humidity, and autumns are cool and sunny. The average annual temperature is 12.6 ℃, and annual accumulated temperature is 801.9 ℃. The average annual precipitation ranges from 550 to 790 mm, the frost-free period lasts for 140–190 days, and there are various local microclimate characteristics. The soil in the study area of the Taihang Mountains comprises ochrepts, weathered from granite and gneiss and guest soil; the soil sits on gneiss, sandstone, and gravel; thus, the area is well drained, although this leads to significant fertilizer leaching [33]. As newly reclaimed cultivated land, the experimental area is uniformly dry terraced fields with guest soil and even soil fertility. The soil texture is characterized by sandy soil with a bulk density of 1.39 g/cm3, a pH of 8.45, a conductivity of 128.72 μS/cm, a low soil organic matter content and nutrients, and lower heavy metal element concentrations (Cr, As, Cd, Pb, and Hg) compared with screening values from the soil environmental quality control standard for soil pollution risk of agricultural land trial in China [34,35]. The limiting factors of poor soil, little rainfall, and deficient nutrient elements and organic matter impose the primary restriction on agricultural production in this area.

2.2. Experiment Material

Woody peat is the core material for constructing a high-quality plough layer; it formed under eutrophic swamp conditions and comprised woody plant residues. Table 1 details the basic physical and chemical properties of the woody peat used in the study, indicating its lower heavy metal content compared with background soil values.
The additional excipients used in the study were as follows: (1) rotten straw, comprising plant straw and traditional Chinese medicine residues, with a total nutrient content ≥5% and organic matter ≥45%; (2) biochar, comprising crop straw; (3) organic fertilizer, prepared by the mixed fermentation and decomposition of pig manure, cow manure, and crop straw; (4) bio-activating regulator I; (5) bio-activating regulator II; (6) compound fertilizer; and (7) urea.
The millet test crop was Jigu No. 38, a variety bred by the Millet Research Institute of Hebei Academy of Agriculture and Forestry Sciences, Hebei Province, China. It is herbicide, lodging, and disease resistant.

2.3. Experimental Design

The experiment was initiated on 20 May 2017. In accordance with the experimental design, different optimization models (Table 2) were constructed on the basis of different auxiliary materials applied to the woody peat (Table 2). The soil samples were collected before the start of the study to determine the background values. The land was given a spiral rotation to mix the added material to guarantee more than 20 cm of revolved plough depth and full blending. On 15 June 2017, sowing, thinning, weeding, water, and fertilizer management were completed based on local millet cultivation techniques. Soil samples were collected and retested before harvest. On 1 October 2017, the millet was harvested and its yield determined.

2.4. Soil Sampling and Analysis

2.4.1. Sample Collection

Before the experiment, the method of five-point sampling in which the midpoint of the diagonal is taken as the central point for sampling and then four points on the diagonal with the same distance from the central point are selected as the other sampling points in an S shape similar to that of a serpent was used to sample the soil from the plough layer of each plot. After the removal of impurities, such as plant roots and gravel, 250 g soil samples were weighed, passed through a 2 mm sieve and then put into sealed bags; from these samples, 150 g of soil was removed and placed in an incubator at 4 ℃ to measure the MBC. Finally, for the collection of soil samples from each plot to determine the soil bulk density, we utilized the cutting-ring method, that is, through the application of a ring knife with known mass and volume to cut a soil sample; the volume of the ring knife was used to determine the volume of the soil, and the mass of the soil was obtained after weighing and subtracting the mass of the ring knife.

2.4.2. Sample Analysis

Various approaches were used for the collection and analysis of soil samples: potentiometry [pH with the extraction of deionized water (water:soil ratio 2.5:1)]; a conductivity meter [conductivity with extraction of deionized water (water:soil ratio: 5:1)], the ring knife method (bulk density); the diffusion absorption method (alkaline hydrolyzable nitrogen content); molybdenum blue colorimetry (available phosphorus); the ammonium acetate extraction-flame photometer method (available potassium content); the high-temperature external heating potassium dichromate volumetric method (organic matter content); the chloroform fumigation–extraction method (MBC content); atomic fluorescence spectrometry (As and Hg); and inductively coupled plasma mass spectrometry (Cr, Cd, and Pb) [36].

2.4.3. N.L. Nemerow Index

The N.L. Nemerow index [37] is used to calculate the comprehensive pollution index. The single factor index Pi is first obtained from Equation (1):
P i = C i S i
where Pi is the pollution index of the i-th heavy metal; Ci is the measured value of the heavy metal content; and Si is the standard value of soil environmental quality (China’s national second-class standard value).
A single-factor index only reflects the degree of pollution of individual heavy metals; however, the N.L. Nemerow index takes into account the average value and the highest value of the single factor pollution index, which highlights the role of heavy metal pollutants in pollution. The comprehensive pollution index is calculated using Equation (2):
P total   = ( P ¯ ) 2 + P i m a x 2 2 2
where Ptotal is the N.L. Nemerow index of the sampling point; Pimax is the maximum value of the single pollution index of heavy metals at the i-th sampling point; and P ¯ is the average single factor index.

2.5. Analyses

The mean of each group of soil variables measured at each study site and the corresponding values of the control group were determined initially. SPSS Statistics 20 software was used for all analyses. Duncan’s new multiple range method was used for multiple comparisons (repeated three times) [38], and one-way ANOVA [39] was used to determine the significance (at p < 0.05) of the results of different treatments. Correlation analysis is a statistical method to study the correlation between two or more variable elements. In this study, it measured the correlation between soil pH (P1), electrical conductivity (P2), alkali-hydrolyzable nitrogen (P3), available phosphorus (P4), available potassium (P5), MBC (P6), soil organic matter content (P7), soil heavy metal pollution index (P8), and soil bulk density (P9) and the yield (Y). Origin 2021 was used to sort out and map the data for the graphical illustration of soil properties (see Figures 2–4).

3. Results

3.1. Effects of Different Woody Peat Optimization Models on Soil Physical and Chemical Properties

3.1.1. Effects on the Distribution of the Soil Particle Size

There was a high gravel content in all treated soils, with 3.64% of the soil particles >2 mm and only 26.81% <0.02 mm. Based on a comparative analysis, there were no soil particles >2 mm in any optimization model, and the content of small soil particles (<0.02 mm) was higher than in the control soils (proportion of small soil particles in A1, A2, B1, B2, and C1 was 19.84%, 15.95%, 18.83%, 23.28%, and 21.59%, respectively), indicating that optimization model B2 (23.28%) had the most significant effect on soil structure improvement (Figure 2A). However, all optimization models tested improved the size of soil particles in this region.

3.1.2. Effect on Soil Bulk Density

Through analysis of the soil bulk density in the study area before and after the experiment [40], the soil bulk density decreased compared with the control group. The control group showed a minimum decline of 0.43%, whereas the bulk soil density in experimental groups A1, A2, B1, and B2 decreased by 10.53%, 11.97%, 4.76%, and 3.31%, respectively. Group A, with the bio-activating regulator, showed the most obvious decrease in soil bulk density (Figure 2B).

3.1.3. Effects on Soil Electrical Conductivity

The soil electrical conductivity [41] of each experimental group decreased compared with controls but was only significantly different in B2, with a reduction of 40.35 units (31.35%) (Figure 2C). This might be because the levels of some bases are too high and some bases are missing, given that woody peat can absorb bases from the soil.

3.1.4. Effects on Heavy Metals in Soils

The N.L. Nemerow index [37] was used to determine the As, Cr, Cd, Pb, and Hg contents in the different soils. The results showed that the heavy metal content of experimental soils from A2 and B2 after the experiment was significantly lower than in the control samples or compared with the soil environmental quality control standard for the soil pollution risk of agricultural land (a decline of 29.73% and 33.20%, respectively; Figure 2D). During crop growth, a small amount of heavy metal elements can be absorbed with nutrients; additionally, humic acid in woody peat can absorb excessive heavy metal elements from the soil, reducing their availability and decreasing their likelihood of being absorbed by the crops, thus improving crop quality.

3.2. Effects of Different Optimization Models Based on Woody Peat on Soil Fertility Characteristics

The results (Figure 3) demonstrate that, except for soil pH [42], different soil fertility indexes based on woody peat were optimized to different degrees compared with those before the experiment. Both the experimental and control groups showed decreased soil pH (Figure 3A) compared with before the experiment, and there were no significant differences between the experimental and control groups. Given that the soil is alkaline in the experimental area, the fertilization schemes used in the experiment all failed to make the plough layer soil more neutral, which would be conducive to crop growth. SOM, a crucial index affecting soil fertility [43,44], can not only provide various nutrients to crops but can also contribute to the absorption of other nutrient elements by plants and the reproduction and other activities of soil microorganisms [45]. The organic matter content in the four experimental groups increased significantly (Figure 3), by 352.75% in A2, 140.10% in A1, 167.54% in B1, and 33.77% in B2, whereas the control group C1 decreased by 34.83%. Based on the analysis of alkali-hydrolyzable nitrogen, available phosphorus, and available potassium in the soils, the soil nutrient content of the experimental groups and the control group increased (Figure 3C), with the available potassium content in C1 being slightly higher than that in B1. However, the effects were more obvious in the experimental groups, with A2 showing the most improved availability of alkaline-hydrolyzable nitrogen, available phosphorus and available potassium (increases of 79.64%, 485.61%, and 7.38%, respectively), followed by B1 (47.72%, 420.45%, and 7.38%, respectively). The smallest increases were seen in B2 (35.75%, 281.06%, and 6.54%, respectively). Compared with the other experimental groups, the highest concentrations of all soil nutrients in the plough layer were found in A2, indicating that the plough layer fertility level would be highest in this model.

3.3. Effects of Different Optimization Models Based on Woody Peat on MBC

MBC [46] is used to evaluate the availability of soil nutrients and the change in microbial status with the environment. There was poor soil with low microbial carbon in the experimental area. After the application of woody peat, the MBC content of the experimental and control groups increased significantly, with A1 showing the highest increase in MBC content (1827.81%), followed by A2, B1, and B2 (1402.39%, 1637.89%, and 1601.82%, respectively) compared with 1664.50% in C1 (Figure 3D).

3.4. Effects of Different Optimization Models Based on Woody Peat on Crop Yield

Based on the yield from each experimental group, A1, A2, and B1 had higher yields than either B2 or C1. A2 had the highest yield (2538.46 kg/ha), an increase of 39.70% compared with C1, followed by A1 (37.84%) and B1 (31.33%). There was no significant difference between B2 and C1, with a decline of 7.96% compared with the control group (Figure 4).

3.5. Correlation Analysis of Influential Factors and Yield

Based on the above results, it was concluded that the treatment used in the A2 group was optimal for improving soil quality and crop yield. Correlation analysis was used on data from subgroups A21, A22, and A23 to determine the woody peat index with the highest influence on yield and to provide an optimal plan for improving agriculture in this region going forward (Table 3).
There was slightly negative correlation between soil pH (P1) and crop yield (Y); electrical conductivity (P2), the soil heavy metal pollution index (P8), and soil bulk density (P9) were positively correlated with yield (Y), although the correlation was nonsignificant. There was a significant positive correlation between alkaline-hydrolyzable nitrogen (P3), available potassium (P5), soil organic matter content (P7), and yield (Y). Thus, woody peat improved the organic matter content and available nutrients in the soil, enhancing crop yield.

4. Discussion

4.1. Effects of Different Optimization Models Based on Woody Peat on Soil Physical and Chemical Properties

As a result of the influence of natural soil-forming factors [47], such as parent material, topography, and climate, there are pervasive problems of poor tillage, heavy texture, and low fertility in the study area. Soil is a complex porous medium comprising different particles with irregular shapes and varying structures, with the distribution of soil particle size [48] having a significant impact on soil hydraulic properties, soil fertility, and soil erosion. The current results showed that fertilization based on woody peat reduced the soil particle size and improved the soil structure [49]. Qiuxia et al. [50] reported “abundant organic matter in woody peat and organic materials featured with excellent pore structure, and to a certain extent, the soil can be diluted through the addition of woody peat and organic materials”; thus, woody peat is able to reduce the soil particle size, improve soil aeration, and contribute to the enhancement of the crop root system and soil microbial activity. Soil bulk density is also closely related to soil compactness. Soane et al. [51] concluded that there might be a coating that increases the friction among soil particles and organic matter to change soil compactness. Although there are few studies on the effect of woody peat on soil bulk density, soil might not be effectively restored by adding woody peat directly after compaction, but it would be possible to improve soil compactness through indirect effects (e.g., via soil organic matter and hydrology). For example, research revealed that the addition of woody peat to soil is beneficial to the rapid growth of fungi and improvements in plant productivity, while the development of roots and hyphae also influences soil bulk density [52].
The current results demonstrated that each optimization model reduced soil conductivity. The level of soil electrical conductivity is positively correlated with water-soluble NH4+, HCO3−, Na+, SO42−, K+, Ca2+, and Mg2+ and, given that humic acid [53,54] contains various functional groups, “After applying humic acid, the release of nutrients slows down, and the mineral-organic complex formed is conducive to facilitating the buffering effect of soil to salt” [55,56], effectively inhibiting the increase in base ions, such as K+, Ca2+, and Mg2+, to reduce soil conductivity. Thus, the application of humic acid in different optimization models contributes to the stabilization of soil conductivity [26,57].
Through measurement of the soil N.L. Nemerow index before and after the experiment [37], woody peat was found to improve the degree of heavy metal pollution in the soil. Monser [58] modified activated carbon with sodium dodecyl sulfonate to reduce the heavy metal content in phosphoric acid and the soil content of cadmium and chromium. Boostani [59] reported the fixation effect of biochar in sheep and earthworm excrement on lead in contaminated calcareous soil to conclude that the addition of biochar would cause a significant increase in the lead content in the residual state. Reducing soil conductivity also facilitates a reduction in the degree of heavy metal pollution in cultivated soil; further analysis showed that woody peat achieves this via four modes: (1) ion exchange. The acidic oxygen-containing functional groups (e.g., carboxyl, carbonyl, and hydroxyl) on the surface of woody peat can ionize H+ or surface basic ions (such as Na+, K+, Ca2+, and Mg2+) and exchange them with heavy metal ions or cationic organic pollutants. Ion exchange has similar effects on reducing soil conductivity [60]. (2) Physical adsorption indicates that woody peat takes advantage of its porosity and large specific surface area to adsorb pollutants, such as heavy metals, or organic matter on its surface or micropores. Generally, the smaller the diameter of a heavy metal, the more it is able to penetrate biochar pores [61]. (3) Electrostatic interaction refers to the electrostatic adsorption between the surface charge of woody peat and heavy metal ions. When the pH of the solution is higher than the charge point of biochar, the negatively charged and positively charged heavy metals on the surface of woody peat cause electrostatic adsorption, whereas the positively charged heavy metal ions on the biochar surface will combine with oxygen-containing functional groups, such as carboxyls, carbonyls, and hydroxyls [62]. (4) Precipitation: combined with heavy metal ions, mineral components in woody peat, including CO32−, PO43−, SiO34−, Cl−, SO42−, SO32−, and OH−, tend to constitute water-insoluble substances, such as metal oxides and metal phosphates, and metal carbonates accelerate the adsorption and solidification of heavy metals. Xu reported the precipitation of CO32− and PO43− as the primary reason for the adsorption of copper, zinc, and cadmium by woody peat [63].

4.2. Effects of Different Optimization Models Based on Woody Peat on Soil Fertility Characteristics

Soil pH [42], which directly reflects the acid–base status of the soil, influences the existing forms, availability and transformation of soil nutrients and soil biological activity [64]. In the current study, the different optimization models all resulted in a significant increase in soil pH. Major et al. [65] reported an increase in pH from 3.91 to 4.19 after applying biochar, whereas Sukartono et al. [66] revealed an increase from 5.97 to 6.25 after the addition of biochar. The main reason for such changes is that the humic acid content in woody peat is as high as 45%, which far exceeds that of other organic fertilizers; humic acid molecules are excellent ion exchangers, containing functional groups including carboxyl, phenolic hydroxyl, quinone, and methoxy groups, among which hydroxyls and others can combine with hydrogen ions in acidic soil to form water, thus removing excess hydrogen ions to gradually convert soil from acidic to neutral. Sekar et al. [67] reported that the addition of woody peat to soil enhanced soil pH, which contributed to the improvement of acidic soil but had an opposite effect on crop growth in alkaline soil; thus, woody peat would have more positive effects when applied to acidic versus alkaline soils.
The current results indicated that each optimization model increased the soil organic matter, alkali-hydrolyzable nitrogen, available phosphorus, and available potassium contents to different degrees (Figure 3B), which is consistent with the research of Chengchuang et al. [21,26]. A2 had the most significant optimization effect, related to the activation of woody peat by applying bio-activating regulator II; the significant improvement in soil organic matter following the application of woody peat is directly connected to the structural characteristics of woody peat itself. Lychuk et al. [68] showed that adding biochar to soil increased the SOC mass fraction because woody peat contains woody plant residues with a high carbon content, which suggests that its application to soil is equivalent to the direct input of exogenous organic carbon into soil. Another study illustrated that humic substances can form organic–inorganic complexes with clay minerals that contribute to the formation and stability of aggregates [69], which are not easily decomposed by microorganisms over a short period of time and are sealed in soil as inert carbon. Other researchers claim that “water-soluble organic carbon is the most active component in the carbon pool, and soil can collect more water-soluble organic carbon by adding organic materials” [70] and that adding a bio-activating regulator [71] can promote the collection function of woody peat, which is in agreement with the current results. Water, nitrogen, phosphorus, and potassium in fertilizers can be converted to ammonium ions, phosphate ions, and potassium ions, which are soluble in water and lost from the soil during the rainy season or following watering, thus reducing the effects of the fertilizer. However, when fertilizer is used with woody peat, the humic acid in woody peat undergoes ion exchange or adsorption, so that the ammonium, phosphate, and potassium ions are retained in the soil, being quickly released for crop growth [56,72]. Humic acid can also accelerate the reproduction of numerous beneficial microorganisms that promote the decomposition of soil organic matter and release nutrients necessary for crop growth, such as organic nitrogen and organic phosphorus. In addition, humic acid can improve the activity of phosphatase in soil to facilitate the conversion of organic phosphorus into available phosphorus; it can also cause the release of insoluble potassium and increase the content of available potassium in soil, especially water-soluble potassium [73,74]. Moreover, each optimization model in the current study improved the physical and chemical conditions of plough soil, providing a suitable environment for microbial activity. Given that woody peat is an organic material rich in carbon source, it provides sufficient nutrients for microbial reproduction and metabolism; the resulting increase in microbial quantity and abundance indirectly strengthens the nitrogen, phosphorus, and potassium cycles in soil, improving the available nutrient content.

4.3. Effects of Different Optimization Models Based on Woody Peat on Soil Biological Properties and Crop Yield

Microbial biomass carbon (MBC), an important indicator of soil biological fertility, is the most active part of soil organic matter. Each optimization model increased the content of soil MBC in the plough layer in the current study, probably because of the large surface area and loose porous structure of woody peat, which improves soil porosity and the stability of soil aggregates to provide suitable living conditions for the growth and reproduction of microorganisms. Zimmerman et al. [75] reported that the addition of biomass carbon can have positive or negative activation effects or no effect on MBC. There are various reasons for the positive activation effects. For example, by adding a suitable amount of biomass carbon, the surface can adsorb a large amount of active organic carbon, becoming a suitable habitat for soil microorganisms and, thus, increasing the MBC content and activity. In terms of the negative activation effect (or no effect), when excess biomass carbon is added, soluble organic carbon easily mineralized in soil organic matter can diffuse and be adsorbed into the micropores of biomass carbon particles, the average pore size of which is smaller than that of most soil microorganisms. This would prevent microorganisms from entering micropores and mineralizing soluble organic carbon, restricting the decomposition of original soil organic carbon. Jones et al. [76] reported that the application of biomass carbon with high porosity and large specific surface area can have a negative activation effect on the mineralization of organic matter in soil itself. Given that woody peat has a high carbon content, moderate addition can improve the content of MBC in soil, provide long-term nutrients for the growth of microorganisms [77], and enable soil microorganisms to make better use of soil nutrients and have a stronger ability to decompose organic matter; by contrast, excessive addition of woody peat would have an adverse influence on the decomposition of soil organic carbon. Therefore, the effect of woody peat on soil microbial activity depends on the proportion of woody peat, the nutrient content of biomass carbon, and the content of available inorganic nutrients in soil. Thus, the fertilization plan proposed based on the results of the current study could lay the basis for determining the appropriate amount of woody peat to improve the MBC of cultivated soil.
All the optimization models tested herein would ameliorate the poor soil and low fertility of the plough layer in the experimental area, building a high-quality plough layer in a short time to improve the biochemical indexes of the soil and provide a suitable soil environment for the growth and development of crops. Ukoma et al. [78] reported a similar result by studying the influence of biochar on crop yield. The current study concluded that the A2 model had the most significant effect on the promotion of crop yield, with a positive correlation between alkali-hydrolyzable nitrogen, available potassium, soil organic matter content, and crop yield. Biochar, as a soil conditioner, can ameliorate soil physical and chemical properties and enhance soil fertility and crop yield. Stegarescu [69] reported that the application of biochar improved the living environment of soil microorganisms, increased the proportion of soil water-stable aggregates, and upgraded the water-stable structure of soil. Woody peat rich in various mineral elements also significantly improves the nitrogen, phosphorus, potassium, and organic carbon components in soil, resulting in increased microbial activity and stable soil aggregate structure to strengthen the ability of the soil to retain water and fertilizer. These impacts also explain why nutrient elements necessary for crop growth are fully supplied under good soil environmental conditions, resulting in increased yields [15,79]. In general terms, the combined application of woody peat and fertilizer contributes to the promotion of crop yield, although the degree of the effect depends on soil type, biochar addition, and other factors. Likewise, the effects of different organic fertilization models based on loamy soils with vegetable peat in commercial banana farms [80,81,82] had an effect on the physical, chemical, and biological properties of the soil such as biological activity, texture, dry consistency, reaction to HCl (hydrochloric acid), structure type, total microbial respiration, soil bulk density, and free-living omnivorous nematodes, showing that the use of organic substrates increased productivity (adequate sprouting and more vigorous seedlings). Likewise, the report of studies in tropical crops [83,84] show that substrates such as woody peat similar to those reported in our study positively influence the content of organic matter and the nutrients available in the soil and therefore in the improvement of the yield of these crops. However, other studies have shown that the effect of the combined application of biochar and fertilizer on crop yield is not necessarily positively correlated with the amount of biochar applied. The current results are inconclusive regarding the suitable amount of woody peat; thus, further work is required to clarify the response of crop yield to the addition of woody peat when combined with fertilizer. Such an understanding would enable efficient utilization of fertilizers to promote crop growth and yield.

5. Conclusions

The addition of woody peat and rotten straw contributes to a reduction in the soil particle size, bulk density, and heavy metal content, alleviation of soil viscosity and acidification and increases in soil organic matter, MBC, alkali-hydrolyzable nitrogen, available phosphorus, and available potassium to improve soil physical and chemical properties and further stimulate crop yields. This demonstrates that the rapid construction of a high-quality plough layer can be achieved by applying woody peat based on a combination of woody peat 37.50 t/h m2 + rotten straw 3.00 t/h m2 + bio-activating regulator II 1.50 t/h m2 + conventional fertilization (A2); this provides a reference for the rapid construction of a high-quality plough layer for agricultural use.
The organic matter content, soil-available nutrients, and crop yield were significantly positively correlated, as was the organic matter content with soil-available nutrients; this illustrates a close connection between the soil organic matter content and soil fertility, the latter having a vital role in crop yield. Woody peat significantly influenced the organic matter content and soil-available nutrients, determining crop yields and laying a reliable foundation for future research on land improvement projects to increase crop yield.

Author Contributions

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

Funding

This study was supported by the National Key R&D Program of China (No. 2018YFE0107000).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. De Amorim, W.S.; Valda, I.B.; Ribeiro, J.M.P.; Williamson, V.G.; Krauser, G.E.; Magtoto, M.K.; Guerra, J.B.S.O.D.A. The nexus between water, energy, and food in the context of the global risks: An analysis of the interactions between food, water, and energy security. Environ. Impact Assess. Rev. 2018, 72, 1–11. [Google Scholar] [CrossRef]
  2. Jones, A.D.; Ngure, F.M.; Pelto, G.; Young, S. What Are We Assessing When We Measure Food Security? A Compendium and Review of Current Metrics. Adv. Nutr. 2013, 4, 481–505. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. He, G.; Zhao, Y.; Wang, L.; Jiang, S.; Zhu, Y. China’s food security challenge: Effects of food habit changes on requirements for arable land and water. J. Clean. Prod. 2019, 229, 739–750. [Google Scholar] [CrossRef]
  4. Ding, X.C. Contemplations over China’s Arable Land Utilization and Protection. In Proceedings of the 2nd Academic Conference of Geology Resource Management and Sustainable Development, Lushan, China, 2 August 2010; pp. 189–191. [Google Scholar]
  5. Shifu, L.; Yapeng, W. Evolution and Path Selection of Food SecuritY Policy in China. Res. Agric. Mod. 2008, 29, 1–5. [Google Scholar]
  6. Meena, R.S.; Kumar, S.; Datta, R.; Lal, R.; Vijayakumar, V.; Brtnicky, M.; Sharma, M.P.; Yadav, G.S.; Jhariya, M.K.; Jangir, C.K.; et al. Impact of Agrochemicals on Soil Microbiota and Management: A Review. Land 2020, 9, 34. [Google Scholar] [CrossRef] [Green Version]
  7. Qi, X.; Zhong, L.; Liu, L. A framework for a regional integrated food security early warning system: A case study of the Dongting Lake area in China. Agric. Hum. Values 2014, 32, 315–329. [Google Scholar] [CrossRef]
  8. Shah, F.; Wu, W. Soil and Crop Management Strategies to Ensure Higher Crop Productivity within Sustainable Environments. Sustainability 2019, 11, 1485. [Google Scholar] [CrossRef] [Green Version]
  9. Bünemann, E.K.; Bongiorno, G.; Bai, Z.; Creamer, R.E.; De Deyn, G.; de Goede, R.; Fleskens, L.; Geissen, V.; Kuyper, T.W.; Mäder, P.; et al. Soil quality—A critical review. Soil Biol. Biochem. 2018, 120, 105–125. [Google Scholar] [CrossRef]
  10. Wu, Y.; Shan, L.; Guo, Z.; Peng, Y. Cultivated land protection policies in China facing 2030: Dynamic balance system versus basic farmland zoning. Habitat Int. 2017, 69, 126–138. [Google Scholar] [CrossRef]
  11. Yu, Y.; Wan, Y.; Camara, A.Y.; Li, H. Effects of the addition and aging of humic acid-based amendments on the solubility of Cd in soil solution and its accumulation in rice. Chemosphere 2018, 196, 303–310. [Google Scholar] [CrossRef]
  12. Banik, C.; Koziel, J.; Bonds, D.; Singh, A.; Licht, M. Comparing Biochar-Swine Manure Mixture to Conventional Manure Impact on Soil Nutrient Availability and Plant Uptake—A Greenhouse Study. Land 2021, 10, 372. [Google Scholar] [CrossRef]
  13. Thomas, C.L.; Acquah, G.E.; Whitmore, A.P.; McGrath, S.P.; Haefele, S.M. The Effect of Different Organic Fertilizers on Yield and Soil and Crop Nutrient Concentrations. Agronomy 2019, 9, 776. [Google Scholar] [CrossRef] [Green Version]
  14. Wang, X.; Yu, H.-Y.; Li, F.; Liu, T.; Wu, W.; Liu, C.; Liu, C.; Zhang, X. Enhanced immobilization of arsenic and cadmium in a paddy soil by combined applications of woody peat and Fe(NO3)3: Possible mechanisms and environmental implications. Sci. Total Environ. 2018, 649, 535–543. [Google Scholar] [CrossRef]
  15. Silitonga, M.; Sipayung, P.; Sitorus, I.M.; Siahaan, R.; Hutauruk, S.; Fajar, T.S.A.; Sarumaha, S.R.D.; Panjaitan, D. The effect of biochar dose and NPK fertilizer on the production and growth of pak choi plant. IOP Conf. Ser. Earth Environ. Sci. 2018, 205, 012028. [Google Scholar] [CrossRef]
  16. Hua, L.; Chen, Y.-X.; Wu, W.-X.; Ma, H.-R. Effect of bio-charcoal on the trans of polycyclic aromatic hydrocarbons in soil-plant system with composted sludge application. Huan Jing Ke Xue 2009, 30, 2419–2424. [Google Scholar]
  17. Francaviglia, R.; Álvaro-Fuentes, J.; Di Bene, C.; Gai, L.; Regina, K.; Turtola, E. Diversified Arable Cropping Systems and Management Schemes in Selected European Regions Have Positive Effects on Soil Organic Carbon Content. Agriculture 2019, 9, 261. [Google Scholar] [CrossRef] [Green Version]
  18. Hu, L.; Diez-Rivas, C.; Hasan, A.R.; Solo-Gabriele, H.; Fieber, L.; Cai, Y. Transport and interaction of arsenic, chromium, and copper associated with CCA-treated wood in columns of sand and sand amended with peat. Chemosphere 2010, 78, 989–995. [Google Scholar] [CrossRef] [Green Version]
  19. Stanislawska-Glubiak, E.; Korzeniowska, J.; Kocon, A. Effect of peat on the accumulation and translocation of heavy metals by maize grown in contaminated soils. Environ. Sci. Pollut. Res. 2014, 22, 4706–4714. [Google Scholar] [CrossRef] [PubMed]
  20. Wei, Y.; Wang, J.; Chang, R.; Zhan, Y.; Wei, D.; Zhang, L.; Chen, Q. Composting with biochar or woody peat addition reduces phosphorus bioavailability. Sci. Total Environ. 2020, 764, 142841. [Google Scholar] [CrossRef] [PubMed]
  21. Fu, W.; Fan, J.; Wang, S.; Wang, H.; Dai, Z.; Zhao, X.; Hao, M. Woody peat addition increases soil organic matter but its mineralization is affected by soil clay in the four degenerated erodible soils. Agric. Ecosyst. Environ. 2021, 318, 107495. [Google Scholar] [CrossRef]
  22. Xi, G.; Shi, G.; Li, Q.; Li, Y.; Xu, Q.; Li, X. Adsorption performance of woody peat for Cr(VI). Environ. Chem. 2019, 38, 202–208. [Google Scholar]
  23. Huang, J.; Ji, J.; Chen, D.; Wang, Q.; Huang, Z.; Tan, J.; Xing, W.; Li, J. Effect of Woody Peat and Other Materials Application on the Yield and Quality of Mango. Chin. J. Trop. Crops 2016, 37, 1458–1462. [Google Scholar]
  24. Jiang, J.; Zhou, J.; Zhang, Y.; Li, Q.; Wang, C. Effects of Different Woody Peat Fertilizers on Quality and Neutral Aroma Components of Flue-cured Tobacco. Southwest China J. Agric. Sci. 2017, 30, 830–835. [Google Scholar]
  25. Yu, B.; Wu, K.; Huang, Q. Study on the effect of woody peat on the dry matter accumulation and yield of millet. Soil Fertil Sci. China 2018, 5, 102–108. [Google Scholar]
  26. Qu, C.; Chen, X.; Zhang, J.; Fan, S.; Tan, J.; Ruan, Y.; Zhang, Y.; Wu, D.; Han, Z.; Zhang, Z. Techniques and Effects of Quickly Constructing High-quality Tillage Layers for Newly-cultivated Arable Land in Red Soil and Paddy Field Based on Woody Peat and Organic Materials. J. Soil Water Conserv. 2018, 32, 134–140. [Google Scholar]
  27. Nabiollahi, K.; Heshmat, E.; Mosavi, A.; Kerry, R.; Zeraatpisheh, M.; Taghizadeh-Mehrjardi, R. Assessing the Influence of Soil Quality on Rainfed Wheat Yield. Agriculture 2020, 10, 469. [Google Scholar] [CrossRef]
  28. Lehmann, J.; Kleber, M. The contentious nature of soil organic matter. Nature 2015, 528, 60–68. [Google Scholar] [CrossRef]
  29. López-Vicente, M.; Calvo-Seas, E.; Álvarez, S.; Cerdà, A. Effectiveness of Cover Crops to Reduce Loss of Soil Organic Matter in a Rainfed Vineyard. Land 2020, 9, 230. [Google Scholar] [CrossRef]
  30. Błońska, E.; Piaszczyk, W.; Staszel, K.; Lasota, J. Enzymatic activity of soils and soil organic matter stabilization as an effect of components released from the decomposition of litter. Appl. Soil Ecol. 2020, 157, 103723. [Google Scholar] [CrossRef]
  31. Fierer, N. Embracing the unknown: Disentangling the complexities of the soil microbiome. Nat. Rev. Genet. 2017, 15, 579–590. [Google Scholar] [CrossRef]
  32. Rezanezhad, F.; Price, J.S.; Quinton, W.L.; Lennartz, B.; Milojevic, T.; Van Cappellen, P. Structure of peat soils and implications for water storage, flow and solute transport: A review update for geochemists. Chem. Geol. 2016, 429, 75–84. [Google Scholar] [CrossRef]
  33. Wang, F.; Peng, J.; Lu, Q.; Cheng, Y.; Meng, Z.; Qiao, J. Mechanism of Fuping ground fissure in the Weihe Basin of northwest China: Fault and rainfall. Environ. Earth Sci. 2019, 78, 1–10. [Google Scholar] [CrossRef]
  34. Mariotte, P.; Mehrabi, Z.; Bezemer, M.; De Deyn, G.; Kulmatiski, A.; Drigo, B.; Veen, C.; van der Heijden, M.G.; Kardol, P. Plant–Soil Feedback: Bridging Natural and Agricultural Sciences. Trends Ecol. Evol. 2018, 33, 129–142. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Wang, R.; Zhang, F.-L.; Xu, S.-S.; Zhang, Y.-W. Method of Dividing the Value of Soil Heavy Metal Pollution Risk Screening: Using Cd as an Example. Huan Jing Ke Xue 2019, 40, 5082–5089. [Google Scholar]
  36. Möller, J.N.; Löder, M.G.J.; Laforsch, C. Finding Microplastics in Soils: A Review of Analytical Methods. Environ. Sci. Technol. 2020, 54, 2078–2090. [Google Scholar] [CrossRef] [PubMed]
  37. Liu, Y.; Yang, L.; Chun, Y.; Yang, J.; Wang, C. VFS-based OFSP model for groundwater pollution study of domestic waste landfill. Environ. Sci. Pollut. Res. 2021, 28, 30783–30806. [Google Scholar] [CrossRef] [PubMed]
  38. Calvo, B.; Santafé, G. scmamp: Statistical Comparison of Multiple Algorithms in Multiple Problems. R J. 2016, 8, 248–256. [Google Scholar] [CrossRef] [Green Version]
  39. Kim, T.K. Understanding one-way ANOVA using conceptual figures. Korean J. Anesthesiol. 2017, 70, 22–26. [Google Scholar] [CrossRef] [Green Version]
  40. Haghverdi, A.; Leib, B.; Washington-Allen, R.; Wright, W.C.; Ghodsi, S.; Grant, T.; Zheng, M.; Vanchiasong, P. Studying Crop Yield Response to Supplemental Irrigation and the Spatial Heterogeneity of Soil Physical Attributes in a Humid Region. Agriculture 2019, 9, 43. [Google Scholar] [CrossRef] [Green Version]
  41. Calixto, W.P.; Neto, L.M.; Wu, M.; Kliemann, H.J.; de Castro, S.S.; Yamanaka, K. Calculation of soil electrical conductivity using a genetic algorithm. Comput. Electron. Agric. 2010, 71, 1–6. [Google Scholar] [CrossRef]
  42. Penn, C.; Camberato, J. A Critical Review on Soil Chemical Processes that Control How Soil pH Affects Phosphorus Availability to Plants. Agriculture 2019, 9, 120. [Google Scholar] [CrossRef] [Green Version]
  43. El-Naggar, A.; Lee, S.S.; Rinklebe, J.; Farooq, M.; Song, H.; Sarmah, A.K.; Zimmerman, A.R.; Ahmad, M.; Shaheen, S.M.; Ok, Y.S. Biochar application to low fertility soils: A review of current status, and future prospects. Geoderma 2018, 337, 536–554. [Google Scholar] [CrossRef]
  44. Solaiman, Z.; Shafi, M.; Beamont, E.; Anawar, H. Poultry Litter Biochar Increases Mycorrhizal Colonisation, Soil Fertility and Cucumber Yield in a Fertigation System on Sandy Soil. Agriculture 2020, 10, 480. [Google Scholar] [CrossRef]
  45. Aschonitis, V.; Karydas, C.G.; Iatrou, M.; Mourelatos, S.; Metaxa, I.; Tziachris, P.; Iatrou, G. An Integrated Approach to Assessing the Soil Quality and Nutritional Status of Large and Long-Term Cultivated Rice Agro-Ecosystems. Agriculture 2019, 9, 80. [Google Scholar] [CrossRef] [Green Version]
  46. Kuht, J.; Eremeev, V.; Talgre, L.; Alaru, M.; Loit, E.; Mäeorg, E.; Salestani, K.E.; Luik, A. Changes in the Soil Microbial Hydrolytic Activity and the Content of Organic Carbon and Total Nitrogen by Growing Spring Barley Undersown with Red Clover in Different Farming Systems. Agriculture 2019, 9, 146. [Google Scholar] [CrossRef] [Green Version]
  47. Lin, H.; Bouma, J.; Wilding, L.P.; Richardson, J.L.; Kutilek, M.; Nielsen, D.R. Advances in hydropedology. Adv. Agron. 2005, 85, 1–89. [Google Scholar]
  48. Qi, F.; Zhang, R.; Liu, X.; Niu, Y.; Zhang, H.; Li, H.; Li, J.; Wang, B.; Zhang, G. Soil particle size distribution characteristics of different land-use types in the Funiu mountainous region. Soil Tillage Res. 2018, 184, 45–51. [Google Scholar] [CrossRef]
  49. Or, D.; Keller, T.; Schlesinger, W.H. Natural and managed soil structure: On the fragile scaffolding for soil functioning. Soil Tillage Res. 2020, 208, 104912. [Google Scholar] [CrossRef]
  50. Li, Q.; Chen, X.; Jin, Z.; Huang, Q.; Zhang, J.; Zhu, B.; Zhang, Y.; Shen, X. Persistent Effects of Biochar on Soil Physicochemical Properties and Crop Yields in Upland Red Soil. J. Soil Water Conserv. 2015, 29, 208. [Google Scholar]
  51. Soane, B. The role of organic matter in soil compactibility: A review of some practical aspects. Soil Tillage Res. 1990, 16, 179–201. [Google Scholar] [CrossRef]
  52. Barna, G.; Makó, A.; Takács, T.; Skic, K.; Füzy, A.; Horel, A. Biochar Alters Soil Physical Characteristics, Arbuscular Mycorrhizal Fungi Colonization, and Glomalin Production. Agronomy 2020, 10, 1933. [Google Scholar] [CrossRef]
  53. Qin, K.; Leskovar, D.I. Humic Substances Improve Vegetable Seedling Quality and Post-Transplant Yield Performance under Stress Conditions. Agriculture 2020, 10, 254. [Google Scholar] [CrossRef]
  54. Sandepogu, M.; Shukla, P.S.; Asiedu, S.; Yurgel, S.; Prithiviraj, B. Combination of Ascophyllum nodosum Extract and Humic Acid Improve Early Growth and Reduces Post-Harvest Loss of Lettuce and Spinach. Agriculture 2019, 9, 240. [Google Scholar] [CrossRef] [Green Version]
  55. Guimarães, D.V.; Gonzaga, M.I.S.; da Silva, T.O.; da Silva, T.L.; Dias, N.D.S.; Matias, M.I.S. Soil organic matter pools and carbon fractions in soil under different land uses. Soil Tillage Res. 2013, 126, 177–182. [Google Scholar] [CrossRef] [Green Version]
  56. Tang, W.-W.; Zeng, G.-M.; Gong, J.-L.; Liang, J.; Xu, P.; Zhang, C.; Huang, B. Impact of humic/fulvic acid on the removal of heavy metals from aqueous solutions using nanomaterials: A review. Sci. Total Environ. 2014, 468–469, 1014–1027. [Google Scholar] [CrossRef]
  57. Chang, R.; Li, Y.; Chen, Q.; Gong, X.; Qi, Z. Effects of carbon-based additives and ventilation rate on nitrogen loss and microbial community during chicken manure composting. PLoS ONE 2020, 15, e0229880. [Google Scholar] [CrossRef]
  58. Monser, L.; Ben Amor, M.; Ksibi, M. Purification of wet phosphoric acid using modified activated carbon. Chem. Eng. Process. Process. Intensif. 1999, 38, 267–271. [Google Scholar] [CrossRef]
  59. Boostani, H.R.; Najafi-Ghiri, M.; Hardie, A.G.; Khalili, D. Comparison of Pb stabilization in a contaminated calcareous soil by application of vermicompost and sheep manure and their biochars produced at two temperatures. Appl. Geochem. 2019, 102, 121–128. [Google Scholar] [CrossRef]
  60. Hassan, M.M.; Carr, C.M. A critical review on recent advancements of the removal of reactive dyes from dyehouse effluent by ion-exchange adsorbents. Chemosphere 2018, 209, 201–219. [Google Scholar] [CrossRef]
  61. Qiu, Y.; Xiao, X.; Cheng, H.; Zhou, Z.; Sheng, G.D. Influence of Environmental Factors on Pesticide Adsorption by Black Carbon: pH and Model Dissolved Organic Matter. Environ. Sci. Technol. 2009, 43, 4973–4978. [Google Scholar] [CrossRef]
  62. Xu, R.-K.; Xiao, S.-C.; Yuan, J.; Zhao, A.-Z. Adsorption of methyl violet from aqueous solutions by the biochars derived from crop residues. Bioresour. Technol. 2011, 102, 10293–10298. [Google Scholar] [CrossRef] [PubMed]
  63. Xu, X.; Cao, X.; Zhao, L. Comparison of rice husk- and dairy manure-derived biochars for simultaneously removing heavy metals from aqueous solutions: Role of mineral components in biochars. Chemosphere 2013, 92, 955–961. [Google Scholar] [CrossRef]
  64. Rees, F.; Simonnot, M.-O.; Morel, J.L. Short-term effects of biochar on soil heavy metal mobility are controlled by intra-particle diffusion and soil pH increase. Eur. J. Soil Sci. 2013, 65, 149–161. [Google Scholar] [CrossRef]
  65. Major, J.; Rondon, M.; Molina, D.; Riha, S.J.; Lehmann, J. Maize yield and nutrition during 4 years after biochar application to a Colombian savanna oxisol. Plant Soil 2010, 333, 117–128. [Google Scholar] [CrossRef]
  66. Sukartono; Utomo, W.H.; Kusuma, Z.; Nugroho, W.H. Soil fertility status, nutrient uptake, and maize (Zea mays L.) yield following biochar and cattle manure application on sandy soils of Lombok, Indonesia. J. Trop. Agric. 2011, 49, 47–52. [Google Scholar]
  67. Sekar, S.; Hottle, R.D.; Lal, R. Effects of Biochar and Anaerobic Digester Effluent on Soil Quality and Crop Growth in Karnataka, India. Agric. Res. 2014, 3, 137–147. [Google Scholar] [CrossRef] [Green Version]
  68. Lychuk, T.E.; Izaurralde, R.C.; Hill, R.L.; McGill, W.B.; Williams, J.R. Biochar as a global change adaptation: Predicting biochar impacts on crop productivity and soil quality for a tropical soil with the Environmental Policy Integrated Climate (EPIC) model. Mitig. Adapt. Strat. Glob. Chang. 2014, 20, 1437–1458. [Google Scholar] [CrossRef]
  69. Stegarescu, G.; Escuer-Gatius, J.; Soosaar, K.; Kauer, K.; Tõnutare, T.; Astover, A.; Reintam, E. Effect of Crop Residue Decomposition on Soil Aggregate Stability. Agriculture 2020, 10, 527. [Google Scholar] [CrossRef]
  70. Dasari, S.; Andersson, A.; Bikkina, S.; Holmstrand, H.; Budhavant, K.; Satheesh, S.; Asmi, E.; Kesti, J.; Backman, J.; Salam, A.; et al. Photochemical degradation affects the light absorption of water-soluble brown carbon in the South Asian outflow. Sci. Adv. 2019, 5, eaau8066. [Google Scholar] [CrossRef] [Green Version]
  71. Calvo, P.; Nelson, L.; Kloepper, J.W. Agricultural uses of plant biostimulants. Plant Soil 2014, 383, 3–41. [Google Scholar] [CrossRef] [Green Version]
  72. Wang, T.; Liu, W.; Xiong, L.; Xu, N.; Ni, J. Influence of pH, ionic strength and humic acid on competitive adsorption of Pb(II), Cd(II) and Cr(III) onto titanate nanotubes. Chem. Eng. J. 2012, 215–216, 366–374. [Google Scholar] [CrossRef]
  73. Nebbioso, A.; Piccolo, A. Molecular characterization of dissolved organic matter (DOM): A critical review. Anal. Bioanal. Chem. 2012, 405, 109–124. [Google Scholar] [CrossRef]
  74. Van Oosten, M.J.; Pepe, O.; De Pascale, S.; Silletti, S.; Maggio, A. The role of biostimulants and bioeffectors as alleviators of abiotic stress in crop plants. Chem. Biol. Technol. Agric. 2017, 4, 5. [Google Scholar] [CrossRef] [Green Version]
  75. Zimmerman, A.R.; Gao, B.; Ahn, M.Y. Positive and negative carbon mineralization priming effects among a variety of bio-char-amended soils. Soil Biol. Biochem. 2011, 43, 1169–1179. [Google Scholar] [CrossRef]
  76. Jones, D.; Murphy, D.; Khalid, M.; Ahmad, W.; Edwards-Jones, G.; DeLuca, T. Short-term biochar-induced increase in soil CO2 release is both biotically and abiotically mediated. Soil Biol. Biochem. 2011, 43, 1723–1731. [Google Scholar] [CrossRef]
  77. Guo, B.; Chen, X.; Jing, F.; Yang, Z.; Liu, W.; Liu, W.; Huang, R. Effects of Biochar Addtion on Physicochemical Properties and Microbial Biomass of the Red Paddy Soil Polluted by Heavy Metals. J. Soil Water Conserv. 2018, 32, 279. [Google Scholar]
  78. Uzoma, K.C.; Inoue, M.; Andry, H.; Fujimaki, H.; Zahoor, A.; Nishihara, E. Effect of cow manure biochar on maize productivity under sandy soil condition. Soil Use Manag. 2011, 27, 205–212. [Google Scholar] [CrossRef]
  79. Mahmoud, Y.; Njenga, M.; Sundberg, C.; de Nowina, K.R. Soils, sinks, and smallholder farmers: Examining the benefits of biochar energy transitions in Kenya. Energy Res. Soc. Sci. 2021, 75, 102033. [Google Scholar] [CrossRef]
  80. Olivares, B.O.; Calero, J.; Rey, J.C.; Lobo, D.; Landa, B.B.; Gómez, J.A. Correlation of banana productivity levels and soil morphological properties using regularized optimal scaling regression. Catena 2021, 208, 105718. [Google Scholar] [CrossRef]
  81. Rondon, T.; Hernandez, R.M.; Guzman, M. Soil organic carbon, physical fractions of the macro-organic matter, and soil stability relationship in lacustrine soils under banana crop. PLoS ONE 2021, 16, e0254121. [Google Scholar] [CrossRef] [PubMed]
  82. Olivares, B.O.; Araya-Alman, M.; Acevedo-Opazo, C.; Rey, J.C.; Cañete-Salinas, P.; Kurina, F.G.; Balzarini, M.; Lobo, D.; Navas-Cortés, J.A.; Landa, B.B.; et al. Relationship between Soil Properties and Banana Productivity in the Two Main Cultivation Areas in Venezuela. J. Soil Sci. Plant Nutr. 2020, 20, 2512–2524. [Google Scholar] [CrossRef]
  83. Fernández Bravo, C.; Urdaneta, N.; Silva, W.; Poliszuk, H.; Marín, M. Germination of tomato seeds (Lycopersicon esculentum Mill.) cv Río Grande sown in plastic trays, using different substrates. Rev. Fac. Agron. Univ. Zulia 2006, 23, 88–195. [Google Scholar]
  84. Andrade-Rodríguez, M.; Ayala-Hernández, J.J.; Alia-Tejacal, I.; Rodríguez-Mendoza, H.; Acosta-Durán, C.M.; López-Martínez, V. Effect of germination promoters and substrates in the development of papayo seedlings. Rev. Fac. Agron. Univ. Zulia 2009, 25, 617–635. [Google Scholar]
Agriculture 12 00031 g001 550
Figure 1. Location of the study area.
Figure 1. Location of the study area.
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Agriculture 12 00031 g002 550
Figure 2. Effects of different optimization models based on woody peat on soil physical and chemical properties. (A) Soil particle size distribution. (B) Soil electrical conductivity. (C) Soil electrical conductivity. (D) Comprehensive soil pollution index.
Figure 2. Effects of different optimization models based on woody peat on soil physical and chemical properties. (A) Soil particle size distribution. (B) Soil electrical conductivity. (C) Soil electrical conductivity. (D) Comprehensive soil pollution index.
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Figure 3. Effects of different optimization models based on woody peat on soil fertility characteristics and MBC. (A) Soil pH. (B) Soil organic matter content. (C) Soil effective nutrient content. (D) Soil microbial carbon content.
Figure 3. Effects of different optimization models based on woody peat on soil fertility characteristics and MBC. (A) Soil pH. (B) Soil organic matter content. (C) Soil effective nutrient content. (D) Soil microbial carbon content.
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Figure 4. Crop yield in the different optimization models.
Figure 4. Crop yield in the different optimization models.
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Table
Table 1. Specific basic physical and chemical properties of woody peat.
Table 1. Specific basic physical and chemical properties of woody peat.
Dry Weight
(g/cm3)		pHOrganic Matter
(%)		Total Humic Acid
(%)		Total N
(%)		Total P2O5
(%)		Total K2O
%		As
μg/g		Pb
μg/g		Cr
μg/g		Cd
μg/g		Hg
μg/g
0.4125.1490.9845.350.6850.0070.0151.193.673.680.130.04
Table
Table 2. Type and amount of excipients added in the different optimization models.
Table 2. Type and amount of excipients added in the different optimization models.
Optimization ModelMaterial Added
A1Woody peat 37.50 t/hm2 + rotten straw 3.00 t/hm2 + bio-activating regulator I 1.50 t/hm2 + conventional fertilization 1
A2Woody peat 37.50 t/hm2 + rotten straw 3.00 t/hm2 + bio-activating regulator II 1.50 t/hm2 + conventional fertilization 1
B1Woody peat 37.50 t/hm2 + rotten straw 3.00 t/hm2 + conventional fertilization 1
B2Woody peat 15.00 t/hm2 + rotten straw 3.00 t/hm2 + conventional fertilization 1
C1Rotten straw 3.00 t/hm2 +conventional fertilization 1
1 Conventional fertilization refers to the application of compound fertilizer 0.60 t/hm2 + urea 0.15 t/hm2.
Table
Table 3. Correlation coefficients between soil properties and crop yields.
Table 3. Correlation coefficients between soil properties and crop yields.
ProjectP1P2P3P4P5P6P7P8P9Y
P11.000
P20.7891.000
P3−0.6150.0001.000
P4−0.828−0.3090.9511.000
P5−0.6150.0001.000 **0.9511.000
P6−0.2440.4040.9150.7400.9151.000
P7−0.5760.0480.999 *0.9350.999 *0.9331.000
P80.4240.8910.4540.1570.4540.7750.4961.000
P90.5150.9330.3590.0540.3590.7060.4040.9951.000
Y−0.1640.0011.000 **0.9511.000 **0.9150.999 *0.4550.3601.000
P1 indicates Soil pH, P2 indicates Electrical conductivity, P3 indicates Alkali-hydrolyzable nitrogen, P4 indicates Available phosphorus, P5 indicates Available potassium, P6 indicates MBC, P7 indicates the Soil organic matter content, P8 indicates the Soil heavy metal pollution index, P9 indicates Soil bulk density, and Y indicates Yield. ** Significantly correlated at the 0.01 level (both sides). * Significantly correlated at the 0.05 level (both sides).
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Zhang, S.; Zhao, R.; Wu, K.; Huang, Q.; Kang, L. Effects of the Rapid Construction of a High-Quality Plough Layer Based on Woody Peat in a Newly Reclaimed Cultivated Land Area. Agriculture 2022, 12, 31. https://doi.org/10.3390/agriculture12010031

AMA Style

Zhang S, Zhao R, Wu K, Huang Q, Kang L. Effects of the Rapid Construction of a High-Quality Plough Layer Based on Woody Peat in a Newly Reclaimed Cultivated Land Area. Agriculture. 2022; 12(1):31. https://doi.org/10.3390/agriculture12010031

Chicago/Turabian Style

Zhang, Sicheng, Rui Zhao, Kening Wu, Qin Huang, and Long Kang. 2022. "Effects of the Rapid Construction of a High-Quality Plough Layer Based on Woody Peat in a Newly Reclaimed Cultivated Land Area" Agriculture 12, no. 1: 31. https://doi.org/10.3390/agriculture12010031

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