Decoding the Sustainability Code: Enzyme Thermodynamic and Kinetic Parameters Reveal the Efficacy of Straw, Biochar, and Nanocarbon in Black Soil

Abstract

For sustainable soil management, the link between carbon amendment structure and soil health is paramount, yet how the particle size of carbon governs hydrolase activity through kinetic and thermodynamic mechanisms remains poorly understood. A three-year field experiment with four treatments, including Control, Straw, Biochar, and Nanocarbon, was conducted in black soil. After harvest, the activities of invertase (INV), urease (URE), and acid phosphatase (ACP) were assayed from 15 to 55 °C. Kinetic parameters—including half-saturation constant (K_m), maximal reaction rate (V_max) and catalytic efficiency (K_a)—and thermodynamic parameters—including Gibbs free energy (ΔG), enthalpy (ΔH) and entropy (ΔS)—were determined. INV and ACP activities increased with temperature, peaking at 55 °C, whereas URE peaked at 45 °C. The V_max, K_a, and ΔG of the enzymes also increased with temperature. With straw, INV activity remained stable, whereas INV-K_a, INV-ΔH, and INV-ΔS increased with decreased INV-K_m. URE activity declined with thermodynamic elevation. For ACP, ACP-K_m and ACP-V_max increased, whereas ACP-K_a and ACP-ΔG decreased. With biochar or nanocarbon, the enzyme activities, V_max, and K_a decreased, whereas ∆G increased, with stronger inhibition by nanocarbon. Correlation analysis revealed ∆G as the dominant factor for activity after carbon addition, while redundancy analysis identified organic carbon (OC) and total phosphorus (TP) as the key regulators. Overall, straw, biochar, and nanocarbon had different sustainable values on hydrolase systems, with thermodynamic parameters, especially ∆G, better reflecting system shifts than kinetic traits.

1. Introduction

Long-term excessive application of nitrogen (N) fertilizer is one of the key drivers of soil degradation, such as soil acidification, reduced soil organic matter, and C/N ratio imbalance, this not only restricts the exertion of soil ecological functions but also poses a challenge to the sustainable development of agriculture [1,2,3]. Previous studies have demonstrated that the incorporation of exogenous organic carbon can effectively mitigate the decline in the soil C/N ratio and the disruption of elemental balance resulting from prolonged excessive application of nitrogen fertilizer [4]. Straw is one of the most important agricultural byproducts for soil improvement. Composed primarily of cellulose, hemicellulose, lignin, and other macromolecular carbon sources, straw plays a critical role in regulating the soil carbon cycle and sustaining microbial activity [5]. Lignin contributes to stable organic carbon pools through its aromatic structure, while cellulose and hemicellulose serving as degradable components stimulate short-term microbial proliferation [6]. The release of these compounds supplies energy to microorganisms and accelerates aggregate formation. For example, three consecutive years of straw return increased the proportion of large aggregates (>2 mm) by 27% and increased the organic carbon content by 15.6% [7]. Biochar is produced by pyrolyzing straw at 300–500 °C. Its surface area is 50–300 times greater than that of straw [8,9]. Owing to its porous microstructure, biochar exhibits high stability, adsorption, and retention capacity, thereby improving soil nutrient dynamics [10,11]. In soil remediation, biochar reduces atmospheric CO₂, enhances fertility, promotes microbial activity, and strengthens plant resistance to diseases [12]. Once introduced into the environment, biochar may degrade into nanoparticles ≤ 100 nm [13,14,15]. These nanocarbon particles possess graphene-like sp² skeletons, abundant oxygen-containing functional groups, and hierarchical porosity. Nanocarbon surface area is 5–8 fold higher than biochar’s, ranging from 800–1500 m²/g, and resulting in strong adsorption and electron transfer capacities [16,17]. These properties suggest significant potential for environmental remediation. However, current applications of nanocarbons focus mainly on energy storage (e.g., lithium-ion batteries) and catalysis (e.g., improving hydrogen production efficiency), while their transformation mechanisms and agronomic effects in soil systems remain unclear [18,19]. Therefore, further research is required to clarify its practical value in agricultural production.

Soil enzymes are essential drivers of soil biogeochemical cycles [20,21]. As “biosensors” of ecosystem functioning, enzyme activities respond sensitively to environmental changes including land use, pollution stress, and climate variation, while simultaneously influencing soil fertility and carbon storage capacity [22,23]. Compared with oxidoreductases and lyases, hydrolases exhibit unique traits by directly mediating immediate nutrient supply. They cleave glycosidic, peptide, and ester bonds in organic compounds, converting complex substrates into bioavailable small molecules for plants and microorganisms [24,25]. This property renders hydrolase activity as one of the most sensitive indicators of nutrient turnover efficiency [26]. In recent years, studies on exogenous carbon inputs and hydrolase activity have expanded significantly, driven by the demands for global carbon cycling and fertility management. Distinct effects of carbon sources with different particle sizes have been documented [27,28]. For instance, Wu et al. [29] observed that straw increased β-glucosidase, cellulase, urease, and alkaline phosphatase activities in bauxite residues by 7.2–9.1, 5.8–7.1, 11.1–12.5, and 1.1–2.2 folds, respectively. Chen et al. [30] reported that straw markedly enhanced α-glucosidase, β-glucosidase, cellulase, leucine aminopeptidase, and N-acetylglucosaminidase activities. Jaffar et al. [31,32] demonstrated that biochar from citrus peel and sugarcane bagasse activated soil urease and phosphatases. However, biochar effects are context-dependent and strongly influenced by pyrolysis temperature. One study suggested that most enzyme activities decreased as pyrolysis temperature increased, with biochar prepared at 200 °C being more favorable for fertility [33]. Nanocarbons applied with fertilizers have also been shown to increase soil urease, catalase, phosphatase, and sucrase activities [34]. Graphite nano-additives (GNA) significantly enhance carbon-related enzyme activities in rhizosphere soils [35]. Nonetheless, most investigations of novel carbon materials are limited to short-term, small-scale experiments, restricting the comprehensive evaluation of their practical potential.

Soil enzyme kinetics and thermodynamics provide quantitative methods for describing catalytic and energy changes [36]. Evaluating these parameters yields comprehensive insights into intrinsic enzyme properties and resistance to environmental stress, thereby advancing our understanding of enzyme stability [37,38]. Research on how exogenous carbon affects kinetic and thermodynamic characteristics of soil hydrolases remains limited. Available studies have shown that the addition of exogenous carbon can alter kinetic parameters (K_m, V_max, and K_a) and thermodynamic properties (ΔG, ΔH, and ΔS). For example, Guo et al. [39] found that straw, biochar, and nanocarbon all increased the V_max and K_a of soil catalase, while decreasing its K_m, ΔG, ΔH, and ΔS. In the study by Chintala et al. [40], biochar application led to a significant decline in the kinetic indices (K_a, V_max) of soil denitrifying enzymes, whereas their ΔH was markedly increased. Additionally, Yan et al. [41] found that biochar addition led to a higher K_m for soil invertase in grey desert soil, with the V_max of alkaline phosphatase and catalase being notably enhanced; in contrast, in aeolian soil, there was a distinct reduction in the K_m, V_max, and K_a of urease, phosphatase, invertase, and catalase. However, systematic comparisons of macro-sized straw, micro-sized biochar, and nano-sized carbon materials remain scarce, leaving a knowledge gap in understanding how carbon source properties govern hydrolase responses.

Our previous work has reported that sustained warming and addition of straw, biochar, and nanocarbon can promote catalase activity and its kinetic and thermodynamic processes in black soil [39]. However, their effects on hydrolases remain unclear. Here, we selected invertase (INV), urease (URE), and acid phosphatase (ACP) to examine activity, kinetics, and thermodynamics under straw, biochar, and nanocarbon treatments in cold-region black soil in northeast China. Three hypotheses were proposed as follows. (1) Straw, biochar, and nanocarbon each demonstrated the ability to enhance soil hydrolase activity. (2) Enzyme responses to different particle sizes of carbon addition were all regulated by both kinetic and thermodynamic processes. (3) Changes in hydrolase activity were closely related to ∆G and soil physicochemical properties after different carbon sources addition. This study can further supplement and improve the theory of soil carbon cycling in low-temperature environments, and at the same time provide certain scientific guidance for black soil fertility maintenance and sustainable agricultural development.

2. Materials and Methods

2.1. Experimental Site

The experiment was conducted at the long-term fertilizer field experiment station at Harbin Normal University, Heilongjiang Province, China (45°51′ N, 126°33′ E). The area has a temperate continental monsoon climate, with mean annual temperature of −1 °C, a frost-free period of 110 d, and annual precipitation of 450 mm. The adopted soil type was Haplic Chernozem. The test field previously used for non-agricultural purposes was replanted with a 15-year rotation cycle, and tillage followed a maize–soybean rotation system.

2.2. Experimental Materials

The materials included corn straw (C content: 40%), corn straw biochar (C content: 79.68%), and nanocarbon (C content: 14.06%). Corn straw was pre-treated by the experimenters themselves, it from the previous season was cut into 1 cm × 1 cm fragments. Corn straw biochar was procured from Liyang Yuanfeng Activated Carbon Co., Ltd. (Liyang, China), prepared by carbonizing corn straw at 600 °C. Nanocarbon was procured from Liyang Yuanfeng Activated Carbon Co., Ltd. (Liyang, China), it consisted of granular C blended with corn straw, columnar activated C, coconut sheath activated C, and nano mineral crystals. Fertilizers included urea (N ≥ 46.4%) and Red Square compound fertilizer (N + P + K ≥ 45%; Zhongyang Red Square Co., Ltd., Hefei, China).

2.3. Experiment Preparation and Design

A randomized block design was applied, with 12 test plots of 24 m² each. Four treatments were established: (1) control with no carbon source (CK), (2) straw addition only (Straw), (3) biochar addition only (Biochar), and (4) nanocarbon addition only (Nanocarbon). Each treatment was replicated three times. A soybean-corn rotation system was employed, in which the fields were preceded by corn from 2022 to 2023 and were planted with soybean in 2024. Based on the above-ground corn straw yield (6 t ha⁻¹ dry weight) and its air-dried carbon concentration (40.3%), the total carbon input from full stover return was estimated at ≈2500 kg·hm⁻² (6000 kg × 0.403). Using this value as the target carbon-equivalent input (2500 kg·hm⁻²). After the autumn harvest in 2022–2023, C sources were applied for two consecutive years at a rate equivalent to 2500 kg·hm⁻² of carbon. Accordingly, 15 kg of straw, 7.53 kg of biochar, and 42.67 kg of nanocarbon were added to each plot. In May 2024, the basic physical and chemical properties of the topsoil (0–20 cm) were initially determined: pH 6.51, organic carbon 9.26 g·kg⁻¹, available nitrogen 57.83 mg·kg⁻¹, available phosphorus 72.65 mg·kg⁻¹, and available potassium 101.20 mg·kg⁻¹. Then compound fertilizer (375 kg·hm⁻¹; N:P₂O₅:K₂O = 15:15:15) was applied before sowing and incorporated into the top 20 cm of soil. The CK treatment received only the base fertilizer with no C addition or topdressing during crop growth. Other field practices followed standard local agricultural management.

2.4. Soil Collection and Chemical Analysis

On the 28 September 2024, following the soybean harvest, soil samples (0–20 cm) were collected from each field plot. Three randomly selected sites within each plot were sampled, and crop residues were removed before collection. The samples were placed in containers and transported to the laboratory, where they were divided into two parts. One portion was air-dried and sieved (2 mm) for chemical property analysis, whereas the other portion was sieved (1 mm) and stored at −20 °C for enzyme activity determination.

The soil pH was measured in a 1:2.5 soil-to-water suspension using a digital pH meter (STARTER 300, OHAUS, Shanghai, China). The bulk density (BD) was determined using the cutting ring method based on the weight of the air-dried soil per unit volume. Soil organic carbon (OC) was determined using the potassium dichromate volumetric method, and total nitrogen (TN) was determined using the Kjeldahl method. Available nitrogen (AN) was measured using alkaline hydrolysis diffusion. Total phosphorus (TP) was determined using the molybdenum-antimony colorimetric method after H₂SO₄-HClO₄ digestion. Available phosphorus (AP) was extracted with 0.5 mol·L⁻¹ sodium bicarbonate and quantified by the molybdenum blue-ascorbic acid method. All analyses were conducted in triplicate. These soil physicochemical properties were determined using a reported method [42].

2.5. Enzyme Activity Assay

The activities of INV, URE, and ACP were determined using a reported method [26]. Enzyme activities were measured at five temperatures (15, 25, 35, 45, and 55 °C), with 35 °C as the optimum. Each measurement was conducted with three replicates to ensure the robustness of the experimental findings. The INV activity was quantified using the 3,5-dinitrosalicylic acid colorimetric method. Briefly, 2 g of soil was incubated for 24 h at different temperatures with 1 mL toluene, 10 mL of sucrose solution at varying concentrations (0.01, 0.05, 0.1, 0.2 mol·L⁻¹), and 10 mL acetate buffer (pH 5.0). After incubation, shaking, and filtration, 2 mL of the filtrate was mixed with 3 mL of 3,5-dinitrosalicylic acid and boiled for 10 min, and the optical density was measured by spectrophotometer (UV-2000, UNIC, Shanghai, China) at 508 nm.

The URE activity was determined using the indophenol blue method. The soil (2 g) was incubated with 1 mL toluene, 10 mL of urea solution at different concentrations (0.1, 0.2, 0.4, 0.8 mol·L⁻¹), and 10 mL citrate buffer (pH 6.7) for 24 h at different temperatures. After incubation, shaking, and filtration, 10 mL of the filtrate was mixed with 4 mL of sodium phenolate and 3 mL of sodium hypochlorite solution, and the optical density was measured by spectrophotometer (UV-2000, UNIC, Shanghai, China) at 578 nm.

ACP activity was measured using the sodium phenyl phosphate colorimetric method. Specifically, 2 g of soil was incubated with 0.2 mL toluene, 10 mL of disodium phenyl phosphate hydrate solution at varying concentrations (5, 10, 20, and 40 mmol·L⁻¹) and 10 mL of acetate buffer (pH 5.0) for 24 h at different temperatures. After incubation, shaking, and filtration, 2 mL of the filtrate was mixed with 5 mL borate buffer (pH 9.6) and 1 mL Gibb’s reagent, and optical density was measured by spectrophotometer (UV-2000, UNIC, Shanghai, China) at 578 nm.

2.6. Calculations and Statistical Analyses

The half-saturation constant (K_m) indicates substrate affinity, with smaller values reflecting a higher affinity. V_max represents the maximal reaction rate as enzyme-substrate complexes decompose, thus indicating total enzyme concentration and production. Catalytic efficiency (K_a), defined as V_max/K_m, reflects enzymatic performance. Thermodynamic parameters, such as ∆G, ∆H, and ∆S, represent the Gibbs free energy, enthalpy, and entropy, respectively, which indicate spontaneity, structural change, and transition-state disorder [36].

The enzyme kinetic parameters (K_m and V_max) were calculated by measuring the enzyme activity at different substrate concentrations using the Michaelis-Menten equation [36,43]:

$$V_0 = {\displaystyle \frac{V_{\max }·\left[\mathrm{S}\right]}{K_{\mathrm{m}} + \left[\mathrm{S}\right]}}$$

(1)

where V₀ is the initial reaction velocity (mg product release g⁻¹ soil 24 h⁻¹), [S] is the substrate concentration (mol·L⁻¹ or mmol·L⁻¹), K_m is the Michaelis-Menten constant (mol·L⁻¹ or mmol·L⁻¹), and V_max is the maximum velocity of the enzymatic reaction [mg·(g·24 h)⁻¹]. Catalytic efficiency (K_a) was calculated as the ratio of V_max to K_m.

The potential enzyme activity was measured at 15, 25, 35, 45, and 55 °C. The Arrhenius equation was used to determine ∆G, ∆H, and ∆S of INV, URE, and ACP [36]:

$$\mathrm{lnk} = \mathrm{lnA} - {\displaystyle \frac{E_{\mathrm{a}}}{\mathrm{RT}}}$$

(2)

$$∆G=\mathrm{RT}\ln \left({\displaystyle \frac{\mathrm{RT}}{\mathrm{Nhk}}}\right)$$

(3)

where k represents the enzymatic reaction constant at a given temperature, A represents the pre-exponential factor, E_a represents the activation energy (kJ·mol⁻¹), R represents the gas constant (8.314 J·mol⁻¹·K⁻¹), T represents the absolute temperature (Kelvin) 273 + t (K), ∆G represents the activation free energy (kJ·mol⁻¹), N represents the Avogadro constant (6.023·10²³ mol⁻¹), h represents the Planck constant (6.626·10⁻³⁴ J·s).

$$∆H={ E}_{\mathrm{a}} - \mathrm{RT}$$

(4)

where ∆H represents the activation enthalpy (kJ·mol⁻¹), E_a represents the activation energy (kJ·mol⁻¹), R represents the gas constant (8.314 J·mol⁻¹·K⁻¹), T represents the absolute temperature (Kelvin) 273 + t (K).

$$∆S={\displaystyle \frac{∆H-∆G}{\mathrm{T}}}$$

(5)

where ∆S represents the activation entropy (J·mol⁻¹), ∆H represents the activation enthalpy (kJ·mol⁻¹), ∆G represents the activation free energy (kJ·mol⁻¹), T represents the absolute temperature (Kelvin) 273 + t (K).

Normality was tested using the Kolmogorov–Smirnov test, variance homogeneity with Levene’s test, and correlation analysis with SPSS 27 (IBM, Armonk, NY, USA). The treatment differences were assessed by two-factor ANOVA, and the means were compared using the least significant difference (LSD) test at p < 0.05. The variance was expressed using Waller Duncan’s method. Graphs were generated using Origin 2021 (Origin Lab Company, Northampton, MA, USA), and redundancy analysis was performed using Canoco 5 (Microcomputer Power, Ithaca, NY, USA).

3. Results

3.1. Soil Physicochemical Properties

Physicochemical characteristics of soil samples are listed in

Table 1. Variations in soil physicochemical properties after three carbon sources addition.

Treatment	pH	Bulk Density (BD) (g·cm−3)	Organic Carbon (OC) (g·kg−1)	Total Nitrogen (TN) (g·kg−1)	Available Nitrogen (AN) (mg·kg−1)	Total Phosphorus (TP) (g·kg−1)	Available Phosphorus (AP) (mg·kg−1)
CK	6.66 ± 0.02 a	1.52 ± 0.01 a	9.28 ± 0.10 b	0.84 ± 0.03 ab	66.22 ± 0.88 b	0.92 ± 0.02 b	74.72 ± 1.26 b
Straw	6.65 ± 0.00 a	1.47 ± 0.03 ab	11.11 ± 0.10 a	0.97 ± 0.06 a	85.17 ± 6.15 a	1.03 ± 0.06 a	72.93 ± 3.79 b
Biochar	6.69 ± 0.08 a	1.45 ± 0.04 b	9.88 ± 0.10 b	0.76 ± 0.03 b	83.71 ± 3.15 a	1.02 ± 0.02 a	100.71 ± 6.94 a
Nanocarbon	6.66 ± 0.00 a	1.46 ± 0.02 b	8.31 ± 0.60 c	0.73 ± 0.08 b	61.83 ± 8.75 b	1.01 ± 0.02 a	98.49 ± 4.73 a

All values are given as mean ± standard deviation (n = 3). The different lowercase letters corresponding to the treatment bars are significantly different at a 0.05 probability level.

. Straw, biochar, and nanocarbon did not alter soil pH but markedly reduced soil bulk density (BD) (p < 0.05). Total phosphorus (TP) significantly increased under all carbon treatments. After straw addition, soil organic carbon (OC), total nitrogen (TN), available nitrogen (AN) was notably elevated. Following biochar amendment, AN and available phosphorus (AP) increased substantially, while TN declined markedly. With nanocarbon addition, only AP rose significantly, whereas OC and TN all decreased (p < 0.05). No appreciable changes were observed in other parameters.

3.2. Soil Enzyme Activities

Temperature, carbon source, and their interaction had significant effects on the activities of the three hydrolases (p < 0.05, Figure 1). With increasing temperature, invertase (INV) and acid phosphatase (ACP) activities consistently increased under all treatments, reaching a maximum at 55 °C. Urease (URE) activity first increased and then declined, with a peak at 45 °C.

At each temperature tested, straw markedly reduced URE activity but increased ACP activity (p < 0.05), whereas INV activity exhibited no clear change. Biochar and nanocarbon both decreased the activities of all three hydrolases, with nanocarbon showing stronger inhibition than biochar (Figure 1).

3.3. Soil Enzyme Kinetic Parameters

Carbon sources and the interaction of temperature with carbon sources had no pronounced effects on INV-K_m and URE-K_m, whereas ACP-K_a remained unaffected. Marked effects were observed for other parameters (p < 0.05, Figure 2). Across treatments, as temperature increased, INV-K_m decreased and then increased, reaching the minimum at 35 °C; URE-K_m and ACP-K_m increased and then decreased, peaking at 25 °C. INV-V_max and ACP-V_max increased with temperature, whereas URE-V_max first increased and then declined, with the maximum at 45 °C. INV-K_a and URE-K_a demonstrated an increasing–decreasing trend, peaking at 45 °C, whereas ACP-K_a continued to increase.

Under straw addition, ACP-K_m showed an appreciable increase compared with CK (p < 0.05). INV-V_max and URE-V_max exhibited no pronounced changes, whereas ACP-V_max increased significantly (p < 0.05). INV-K_a increased at 15–45 °C, while no significant change was observed at 55 °C. URE-K_a decreased to a certain extent at 25–55 °C. For ACP-K_a, it decreased at 15–35 °C but showed no obvious change at 45–55 °C.

With biochar or nanocarbon, ACP-K_m increased pronouncedly compared with CK, the V_max values of all three hydrolases and the K_a values of INV and URE significantly decreased (p < 0.05), with a stronger reduction under nanocarbon. ACP-K_a decreased at 15–35 °C.

3.4. Soil Enzyme Thermodynamic Parameters

Figure 3 depicted the Eyring plots for three hydrolases after three carbon sources addition at 15–55 °C. Under different carbon source treatments, the ln(K_a/T) of the three hydrolases showed a linear decreasing trend with the increase of 1/T, the temperature dependence of hydrolases was consistent with the theoretical prediction of the Eyring equation when the temperature rises.

Further quantifying the thermodynamic parameters in depth, the temperature, carbon source, and their interaction showed a statistically meaningful effect on the ∆G of the three hydrolases (p < 0.05). Carbon sources markedly influenced ∆H and ∆S, whereas temperature and the interaction of temperature with carbon sources had no statistically significant effects (Figure 4). In all treatments, ∆G gradually increased with temperature, reaching a maximum at 55 °C.

After straw addition, INV-∆G showed no marked change, whereas ACP-∆G decreased notably at all tested temperatures compared with CK (p < 0.05). URE-∆G increased to a certain extent at 15–55 °C. Both ∆H and ∆S of INV and URE increased, whereas ACP-∆H and ACP-∆S decreased slightly.

With biochar or nanocarbon, the ∆G of all three hydrolases substantially increased at each tested temperature compared with CK (p < 0.05). For INV, both the ΔH and ΔS exhibited a moderate decrease, whereas for URE and ACP, both parameters notably exhibited a certain degree of elevation.

3.5. Correlation Analysis Between Hydrolase Activity and Catalytic Characteristics

After three carbon sources additions, the correlation analysis of three hydrolase activities with kinetic and thermodynamic parameters was shown in Figure 5. In CK treatment, the activities of three hydrolases all exhibited a distinct negative correlation with ΔG (p < 0.01). Additionally, URE activity showed a marked negative correlation with K_a, and ACP activity displayed a significant negative correlation with ΔS. After adding straw, biochar, and nanocarbon, the activities of three hydrolases only demonstrated a conspicuous negative correlation with ΔG (p < 0.01), showing a consistent correlation trend, and had no apparent relationship with other parameters.

3.6. Redundancy Analysis

Redundancy analysis indicated that Axis-1 and Axis-2 explained 53.93% and 23.71% of the total variation in the soil environmental factors and enzyme parameters, respectively (Figure 6). Compared with CK, distinct directional separations were observed in the hydrolase reaction system under different carbon source amendments. Soil physicochemical properties were significantly correlated with enzyme activities and with their kinetic and thermodynamic parameters. The relative contribution of soil physicochemical properties to the variations in enzyme characteristics followed the order OC > AP > TP > pH > AN > TN > BD. Among these, OC and AP exerted highly notable influences (p < 0.05), explaining 41.1% and 24.4% of the variation in carbon-treated soils, respectively (Figure 7).

4. Discussion

4.1. Response of Hydrolase Activities to Straw, Biochar, and Nanocarbon in Black Soil

Previous studies have reported that incorporating straw into saline-alkali soil increases INV, URE, and ACP activities at the optimal temperature (37 °C) [44,45,46]. Conversely, Ortega et al. [47] found that straw mulching in post-fire soil did not affect URE but reduced ACP. However, the effect of straw on hydrolase activity under warm conditions remains unclear. In this study, straw addition caused the INV and ACP activities to increase progressively with temperature (15–55 °C), peaking at 55 °C, while the URE activity increased and then decreased, peaking at 45 °C. This was consistent with observations without straw and followed the general rule that enzyme activity could increase with temperature within a certain range [48], indicating that straw could not alter the temperature response trend. Compared with CK, straw addition resulted in no significant change in INV activity, a decrease in URE, or an increase in ACP across all temperatures. These results are not completely consistent with previous findings [44,45]. This newly observed phenomenon suggests that the enhanced enzyme activity after straw incorporation is not absolute and may depend on straw properties, application rates, and the specific conditions of cold-region black soil [49,50].

Biochar and nanocarbon, characterized by high surface area and porosity, have been shown to improve soil structure and nutrient efficiency [51,52]. However, due to the significant variations in soil properties across different regions, the applicability of existing research findings in other areas remains to be verified. Research on the underlying internal mechanisms associated with these differences is also relatively scarce. Considering severe degradation and organic matter loss at the study site, a three-year field experiment was undertaken to assess how continuous biochar and nanocarbon application could influence hydrolase activity under warming. The results showed that as temperature increased (15–55 °C), the hydrolase activities under biochar and nanocarbon followed trends similar to straw, with no change in the overall temperature response. At all tested temperatures, biochar and nanocarbon reduced the enzyme activities, with nanocarbon exhibiting stronger inhibition. These results are not entirely consistent with our initial hypothesis that “carbon sources can enhance soil hydrolase activity,” suggesting that the influence of carbon sources on enzyme activity may be more complex. Our findings contrast with most previous reports that biochar and nanocarbon can stimulate enzyme activity [31,32,34]. The discrepancy may be due to their stable, inert, aromatic-rich structures [53,54]. In black soils of northeast China, such inert carbons may fail to provide energy to microorganisms, instead suppressing enzyme-substrate interactions through the adsorption of enzymes or substrates, leading to lower apparent activity [55]. Notably, nanocarbon caused greater inhibition than biochar, suggesting stronger sensitivity of hydrolases to nanocarbon. This may be explained by its larger surface area and smaller particle size, which enhances adsorption and coupling with soil nutrients and microelements. By preferentially adsorbing low-molecular-weight organics, nanocarbons likely reduce the availability of substrates to microbes, thereby indirectly lowering enzyme activity [56,57]. These findings offered a scientific basis for making informed decisions regarding the balanced management of straw incorporation alongside biochar and nanocarbon amendments.

4.2. Response of Hydrolase Kinetic and Thermodynamic Characteristics to Straw, Biochar, and Nanocarbon in Black Soil

The kinetic and thermodynamic properties of soil enzymes provide effective indicators of how exogenous carbon inputs can influence apparent activities. After straw addition, the changes in INV and ACP were opposite: K_a, ΔH, and ΔS of INV increased, while INV-K_m decreased. The K_m and V_max of ACP increased, whereas K_a and ΔG decreased at all temperatures. These results suggested that INV stabilization was driven by accelerated kinetic reactions combined with slower thermodynamic processes, while ACP enhancement reflected increased enzyme production and concentration and reduced activation free energy. In contrast, the URE kinetic parameters remained unchanged, whereas the thermodynamic parameters increased. Thus, the reduced URE activity under straw addition was mainly associated with higher energy demand, enthalpy, and entropy. This indicated distinct response mechanisms among hydrolases, which could be consistent with the resource allocation theory of microbial metabolism [58,59]. Previous studies have confirmed that straw incorporation can modify enzyme kinetics and thermodynamics through multiple pathways, including altering substrate adsorption efficiency, modulating catalytic rates, affecting activation energy, and shifting enthalpy and entropy [39,60]. Although it remains difficult to determine whether straw universally enhances or suppresses enzyme activities, the observed measurable changes in kinetic and thermodynamic traits confirmed that hydrolase responses were shaped by both processes, supporting our second hypothesis.

With the addition of biochar or nanocarbon, the three hydrolases exhibited consistent responses, where ΔG increased, whereas V_max and K_a decreased. Hence, the reduction in hydrolase activity reflected slower kinetic and thermodynamic processes, in agreement with our second hypothesis. Compared with straw, biochar and nanocarbon mainly decreased enzyme secretion and catalytic efficiency, increased activation energy barriers, and exerted similar effects on soil C, N, and P metabolism. Few studies have examined enzyme kinetics and thermodynamics under biochar and nanocarbon, and the reported trends remain inconsistent. For example, Raiesi found that biochar in sandy soil increased the V_max and K_a of β-glucosidase while decreasing K_m and thermodynamic parameters [61], whereas Khadem suggested that biochar increased the thermodynamic parameters of arylsulfatase in sandy soil [62]. In our recent study, both biochar and nanocarbon increased the V_max and K_a of catalase but reduced K_m, ΔG, ΔH, and ΔS in northeastern black soil [39]. Therefore, the responses of enzyme kinetic and thermodynamic parameters to biochar and nanocarbon appeared to vary depending on enzyme type and soil properties, which could explain the differences between our results and those reported previously.

4.3. Factors Influencing Changes in Soil Hydrolase Activity

Correlation analysis revealed a significant negative correlation between soil hydrolase activity and ΔG after the addition of straw, biochar, and nanocarbon, ΔG consistently served as a key regulatory factor. This suggests that the energy barrier of enzymatic reactions is the fundamental mechanism by which carbon sources alter soil enzyme functionality. This ΔG-dominated mechanism of carbon-mediated regulation of hydrolase activity supports our hypothesis. Particularly notable was the consistent increase in ΔG following carbon amendments, indicating a trend towards reduced spontaneous enzymatic reactions, in contrast with most previous studies. Our three-year experiment on continuously cultivated boreal black soil in northeast China suggested that the ΔG elevation may result from (1) the long-term cultivation-induced depletion of organic matter and microenvironments protecting enzymes, coupled with microbial imbalance, which may delay electron transformation and elevate transition-state energy barriers [63,64,65]; and (2) low temperatures restricting microbial metabolism, disrupting functional balance, and leading to insufficient enzyme synthesis and increased activation energy [66,67]. Collectively, these mechanisms contribute to the thermodynamic constraints observed in this unique agroecosystem. This discovery refines our traditional perspective on the regulation of soil enzyme activity by establishing a critical thermodynamic constraint for biogeochemical processes within global carbon cycle models. It thereby significantly improves the predictive accuracy of these models for carbon turnover dynamics in high-latitude agricultural ecosystems.

The activity of soil hydrolases is regulated by soil physicochemical properties, a conclusion that is further supported by redundancy analysis. The analysis indicated that in the unique boreal black soil ecosystem of northeast China, both OC and AP played critical roles in modulating the hydrolase system. Prolonged low temperatures and tillage practices substantially slowed OC mineralization rates, establishing OC as the primary limiting factor for hydrolase systems. OC functioned not only as an enzyme substrate and stabilizer but also reflected the carbon preservation mechanism typical of cold-region soils, where microbial activity was suppressed by low temperatures, resulting in the accumulation of partially decomposed organic matter [68]. In contrast, AP emphasized the unique phosphorus cycling dynamics of cold soils, where seasonal freeze-thaw cycles induced asynchrony between P fixation-release patterns and crop growth seasons. This positioned AP as the second major limiting factor after OC [69], directly constraining the energy metabolism required for microbial hydrolase synthesis.

Therefore, the activity of soil hydrolases is jointly determined by soil physicochemical properties, kinetic parameters, and thermodynamic parameters. Among these, thermodynamic factors, particularly ΔG of enzyme reactions, are critical determinants of enzyme activity changes. Although this study has achieved some progress, it still has several limitations. Moving forward, continuous monitoring of the seasonal fluctuation rules of soil enzyme reactions is required, along with further expansion of the research scope and systematic conduct of correlation studies between soil enzymes, crop yield, and nutrient use efficiency, so as to construct a more comprehensive soil science analysis system.

5. Conclusions

Based on investigating soil hydrolase activities, their kinetic and thermodynamic parameters after adding straw, biochar, and nanocarbon, the study conclusions are summarized as follows:

(1)

Although all carbon inputs did not alter the temperature response trends of INV, URE, and ACP, their effects on enzyme activities were distinct. Straw exerted different influences on the enzymes (no significant change in INV, a decrease in URE, and an increase in ACP), whereas both biochar and nanocarbon consistently inhibited all three enzymes, with nanocarbon exhibiting a stronger inhibitory effect.

(2)

The changes in hydrolase activity following carbon addition were regulated through the coupling of kinetic and thermodynamic processes.

(3)

Thermodynamic properties, particularly ∆G, were identified as the key limiting factors driving enzyme activity changes, whereas soil OC and TP acted as important physicochemical regulators.

These findings elucidate the mechanisms by which exogenous carbon inputs could influence enzymatic processes in cold-region black soils, underscoring the critical role of thermodynamic constraints and soil specificity. In addition, this study provides the scientific basis for designing carbon amendment strategies that maximize soil sustainability. By linking carbon particle size to enzymatic energy pathways, our work offers a framework for balancing short-term productivity with long-term soil health, guiding the development of resilient agricultural systems in cold-region black soil.