Long-Term Application of Manure and Different Mineral Fertilization in Relation to the Soil Organic Matter Quality of Luvisols

Abstract

Long-term field experiments were conducted on luvisol at five sites in the Czech Republic (42–48-year duration). The average total organic carbon content in the soil varied between 9.0 and 14.0 g kg⁻¹. In these trials, seven crops were rotated in the following order: clover, winter wheat, early potato, winter wheat, spring barley, potato, and spring barley with interseeded clover. Five treatments were studied: unfertilized treatment (Con), farmyard manure (F), and combinations of farmyard manure with three mineral fertilization levels (F+M1, F+M2, F+M3). Plant residues were not incorporated into the soil. An amount of 40 t ha⁻¹ of farmyard manure fresh matter was applied twice during crop rotation. Intensive mineral fertilizer (F+M3) increased the average value of the carbon sequestration efficiency (CSE) by 12.9% and up to 26.3%. Combining organic and mineral fertilizers at moderate and higher intensities increased the soil organic matter quantity and quality compared to the unfertilized or manure treatment. Data on the glomalin content can be used to study the organic matter quality. We determined a strong correlation between the total glomalin content and the soil organic matter carbon, fulvic acid content, humic acid content, extractable carbon content, and dissolved organic carbon content, as well as the potential wettability index and aromaticity index.

1. Introduction

The quantity and quality of soil organic matter (SOM) are two of the basic pillars of soil fertility. Many factors influence the quality and quantity of SOM, such as: crop rotation, agrotechnical approach (till or no-till system), irrigation, etc. Other considerations include the quality and intensity of mineral and organic fertilizers. At present, there are several different methods for determining the SOM quality parameters. The fractionation of SOM into individual forms is important for the SOM quality degradability [1,2,3]. SOM can be divided into stable and labile fractions. The stable fraction is represented by humic acids (C_HA), fulvic acids (C_FA), and humins [4]. The labile forms are represented by potentially mineralizable carbon (C_HWC) [5] or dissolved organic carbon (C_DOC) [6,7].

Glomalin has been widely studied as an indicator of soil organic matter quality [8]. Glomalin is produced by arbuscular mycorrhiza and is one of the most important soil proteins. The accurate molecular composition of glomalin has not been defined because the glomalin fraction extracted from soil is often not sufficiently clean [9,10]. The glomalin content in soil increased with long-term compost [11,12] and manure [12,13] applications. An increase in the glomalin content was also determined after applying sewage sludge [14,15] and straw alongside mineral fertilizer [16]. Relatively significant correlations between the quality of the soil parameters and the soil organic matter, or some fraction of soil organic matter, have been found, particularly in the C_SOM, humic and fulvic acids, C/N ratio, and glomalin [17]. Owing to the positive correlation between the glomalin and C_SOM content [15,18], glomalin can be considered a good indicator of soil fertility [11,19]. In our previous study [6], we found a positive correlation between the glomalin content and humic acid content (C_HA), as well as the gloma lin content and humic acid and fulvic acid ratio (C_HA/C_FA), under long-term maize production on luvisol. We also found a positive correlation with the potential wettability index (PWI).

The humus quality absorbance ratio at a 400 and 600 nm (E4/E6) ratio has been used as a standard parameter to assess the characterization of humic substances [20]. The ratio is inversely related to the condensation degree of the aromatic network in humic substances. A low E4/E6 ratio indicates a relatively high degree of aromatic constituent condensation, whereas a high ratio reflects a low degree of aromatic condensation and the presence of relatively large proportions of aliphatic structures [21]. After farmyard manure application, an increased humic acid content with higher “aromaticity” was observed, indicating favorable conditions for humification [22]. On the other hand, an increase in fulvic acid production was observed after the application of farmyard manure, leading to an increased E4/E6 ratio over other treatments [23]. Similar results were presented by Song et al. [24] and Galantini and Rossel [25]. No significant correlation between the E4/E6 values and the fractions of soil organic carbon, humification index (HI), or humification rate (HR) was found in the field long-term crop rotation experiments with different organic fertilizers (manure, straw, scab) at 10 sites across the Czech Republic [26]. Furthermore, no significant relationship between the C_SOM and E4/E6 was observed in the long-term experiments with maize monoculture [6].

Another method for SOM quality assessment is diffuse reflectance infrared Fourier transform spectrometry (DRIFTS). SOM is also characterized by the ratio of aliphatic C–H and carboxylic (C–O) bonds, known as the potential wettability index (PWI). Demyan et al. [27] used the DRIFTS method to monitor SOM quality in long-term trials in Bad Lauchstadt. All of their observations obtained using DRIFTS showed the influence of fertilization. They also mentioned a correlation between the PWI and C_SOM content. A strong correlation between the PWI and total glomalin content (TG) was estimated for luvisol [6], but was not confirmed for chernozem [7].

We calculated the aromaticity index (iAR) according to the reflectance of aliphatic and aromatic bands [28]. Increased soil organic matter mineralization and the formation of aliphatic compounds in aggregates may cause increased iAR values [28].

Our aim for this work was to (i) evaluate the changes in the SOM quality and quantity in luvisol under the influence of long-term organic and mineral fertilizers; (ii) evaluate the suitability of data on the glomalin content as an indicator of the soil organic matter quality; (iii) establish whether the easily extractable or total glomalin content is more suitable for soil organic matter quality determination. We hypothesize that glomalin content determination will be a viable method for soil organic matter quality determination and one of the two glomalin fractions (EEG or TG) will be more suitable for this purpose than the other. For this study, we selected long-term field experiments on luvisol at five sites in the Czech Republic (42–48-year duration). Most luvisols are fertile soils and suitable for a wide range of agricultural uses. Luvisol occupies 500–600 million hectares worldwide [29].

2. Materials and Methods

The Central Institute for Supervising and Testing in Agriculture established long-term farm trials between 1975 and 1981 on luvisols at five experimental sites under various climatic conditions in the Czech Republic.

Table 1. Characteristics of the experimental sites and year of experiment establishment.

Site/Parameter	Staňkov	Chrastava	Jaroměřice	Hradec Nad Svitavou	Pusté Jakartice
GPS coordinates	N 49°19′59.2716″ E 13°20′10.4388″	N 50°29′30.7638″ E 14°33′56.6634″	N 49°33′21.8052″ E 15°31′22.875″	N 49°26′6.882″ E 16°18′7.2648″	N 49°34′57.201″ E 17°34′20.6178″
Established	1981	1977	1975	1981	1979
Altitude (m.a.s.l)	370	345	425	460	290
Precipitation (mm) 1	549	738	488	616	584
Air temperature (°C) 1	8.3	8.0	8.2	7.4	8.3
Soil group 2	Haplic luvisol	Haplic luvisol	Haplic luvisol	Haplic luvisol	Albeluvisol
Soil texture 2	Silt loam	Silt loam	Silt loam	Sandy loam	Silt loam
Clay (%) (<0.002 mm)	9.4	12.2	20.5	12.6	12.7
Silt (%) (0.002–0.05 mm)	57.2	73.9	56.3	32.1	65.0
Sand (%) (0.05–2 mm)	33.4	13.9	23.2	55.3	22.3
Bulk density (g cm−3)	1.39	1.34	1.41	1.35	1.38
CSOM in 2022 (%)	1.37	1.23	1.41	0.93	1.15
pHCaCl2 (Con, F, F+M1, F+M2, F+M3) *	5.7, 6.0, 5.9, 5.9, 5.8	5.3, 6.2, 6.2, 6.2, 6.3	5.6, 6.6, 6.5, 6.3, 6.1	5.9, 6.5, 6.3, 6.3, 6.2	5.9, 6.4, 6.3, 6.2, 5.9
P in 2022 (Con, F, F+M1, F+M2, F+M3) (mg kg−1) 3,*	61, 75, 93, 97, 118	56, 60, 77, 86, 102	59, 80, 109, 127, 164	70, 76, 92, 100, 124	91, 75, 193, 97, 118
K in 2022 (Con, F, F+M1, F+M2, F+M3) (mg kg−1) 3,*	94, 99, 121, 152, 195	127, 142, 174, 202, 221	155, 179, 196, 235, 301	122, 131, 147, 175, 223	94, 99, 121, 152, 195
C input in F since the establishment (t ha−1)	25.7	28.2	30.8	25.7	28.2
Plot size (m2)	58	64	52	48	58

C_SOM—soil organic matter carbon content; ¹ long-term (30 years) annual average; ² according to NRCS USDA [30]; ³ Mehlich 3 extractable content; * values in these rows respect the order of presented treatments; Con—control, F—farmyard manure, F+M—farmyard manure with increasing levels of mineral fertilizer.

presents the characteristics of the experimental sites. The average total organic carbon content in the soil varies between 9.0 and 14.0 g kg⁻¹. Within these trials, seven crops were rotated in the following order: clover, winter wheat, early potato, winter wheat, spring barley, potato, and spring barley with interseeded clover. An identical tillage system and crop varieties were used on all sites. Except for the unfertilized control, liming was performed as needed based on the pH_CaCl2 of the fertilizer treatment and soil texture.

The experiment is set up in a randomized complete block design on all sites. Blocks are replicated three times. The plot sizes on the individual sites are described in Table 1. As shown in

Table 2. Experimental design and nutrient doses applied in mineral fertilizers.

Treatment	Average Annual Nutrient Dose in Mineral Fertilizers (kg ha−1)
	N	P	K
1. Con	0	0	0
2. F	0	0	0
3. F+M1	57	13	33
4. F+M2	85	26	66
5. F+M3	114	53	133

, five treatments were studied: unfertilized treatment (Con), farmyard manure (F), and combinations of farmyard manure with three levels of mineral fertilization (F+M1, F+M2, F+M3). Plant residues were not incorporated into the soil. The amount of 40 t ha⁻¹ of farmyard manure fresh matter is applied to early potatoes and potatoes, i.e., twice during a crop rotation. We calculated the carbon input for the entire duration of the experiment using dry matter of 23.0% and a carbon content of 27.9% in dry matter (values based on results of long-term site monitoring).

The fertilizer application rates were selected to reflect low, medium, and high intensity (M1, M2, and M3 treatments, respectively) of mineral fertilizer inputs in the Czech Republic at the beginning of the experiment. The fertilizers were applied in the following forms: N—calcium ammonium nitrate; P—triple superphosphate; K—60% potassium salt. A constant fertilizer dose was used during the entire experiment (Table 2).

2.1. Soil Analysis

For clarity and convenience, Appendix A,

Table A1. List of variables and their descriptions.

Abbreviation	Full Variable Description	Unit/Scale
CSOM	Soil organic carbon	%
CHS	Carbon humic substances	%
CFA	Carbon in fulvic acid	%
CHA	Carbon in humic acids	%
HA (CHA/CFA)	Degree of polymerization	-
HR (CHS/CSOM)	Humification rate	-
HI (CHA/CSOM)	Humification index	-
E4/E6	Humus quality ratio (E4/E6)	-
CHWC	Carbon—hot water extraction	mg kg−1
CDOC	Carbon—0.01 M L−1 CaCl2	mg kg−1
Nt	Total nitrogen	%
CSOM/Nt	Ratio CSOM and Nt	-
EEG	Easily extractable glomalin	mg kg−1
TG	Total glomalin	mg kg−1
DG	Difficult extractable glomalin	mg kg−1
PWI	Potential wettability index	-
iAR	Aromaticity index	-
CSE	Carbon sequestration efficiency	%

provides a list of variable abbreviations that are commonly used in this paper, including variable descriptions and units or scales.

The experimental sites were established between 1975 and 1981 with a crop rotation of seven crops (rotation mentioned above). Soil sampling was performed after the barley harvest in 2022, when the crop rotation was finished using a soil probe (30 cm depth). Fifteen soil samples were collected from every experimental plot and pooled. These samples were air-dried at 25 °C, homogenized, and sieved through a 2 mm sieve. The soil samples were later used for chemical analysis. Furthermore, a 0.4 mm soil size fraction was also prepared for the C_SOM determination. The soil was analyzed as follows:

The soil organic carbon (C_SOM) content in the air-dried samples of soils was determined through oxidation using the CNS Analyzer Elementar Vario Macro (Elementar Analysensysteme, Hanau-Frankfurt am Main, Germany).

The fractionation of humic substances (C_HS) was performed according to Pospíšilová et al. [31], and Kononova [4] to obtain the pyrophosphate extractable fraction, which represents the sum of carbon in humic acids (C_HA) and fulvic acids (C_FA). The C_HA and C_FA were extracted from a 5 g soil sample with a mixed solution of 0.10 mol L⁻¹ NaOH (Lach-ner, s.r.o., Neratovice, Czech Republic) and 0.10 mol L⁻¹ Na₄P₂O₇ (1:20 w/v) (Penta Chemicals Unlimited, Prague, Czech Republic). The following fractions of carbon were isolated: C_FA was obtained from a solution that was acidified by dilute H₂SO₄ (Lach-ner, Neratovice, Czech Republic) to a pH of 1.0–1.5 and left undisturbed for 24 h, and C_HA was obtained through the dissolution of the previously formed precipitate in a hot 0.05 mol L⁻¹ NaOH solution. Before iodometric titration, the dry matter formed by the vaporization of each sample was dissolved in a mixture of 0.067 mol L⁻¹ K₂Cr₂O₇ (Lach-ner, s.r.o., Neratovice, Czech Republic) and concentrated H₂SO₄ at an elevated temperature.

The humus quality (E4/E6) was analyzed according to the spectrophotometric method. The soil samples were extracted using sodium pyrophosphate (0.05 M Na₄P₂O₇) and measured by determining the absorbance ratio at 400 and 600 nm [32] (Lambda 25 UV/Vis (Perkin Elmer, Waltham, MA, USA).

The extractable organic carbon was determined using CaCl₂ and hot water extraction.

For the 0.01 mol L⁻¹ CaCl₂ (Lach-ner, s.r.o., Neratovice, Czech Republic) extraction (C_DOC), the extraction agent 0.01 mol L⁻¹ CaCl₂ was used (1:10, w/v) [33]. The C_DOC content was determined in the soil samples through segmental flow analysis using infrared detection on a Skalarplus System (Skalar, Breda, The Netherlands).

Hot water extraction (C_HWC) was used to assess the extractable soil organic carbon. The soil samples were dried at 40 °C and extracted with water (1:5, w/v). The suspension was boiled for one hour [5]. The C_HWC was determined through segmental flow analysis using infrared detection on a Skalarplus System (Skalar, Breda, The Netherlands).

The potential wettability index (PWI) and index of aromaticity (iAR) were determined using DRIFTs (diffuse reflectance infrared Fourier transform spectroscopy) spectra. The DRIFT spectra were recorded using the infrared spectrometer (Nicolet IS10, Waltham, MA, USA). The spectra with a range of 2.50 to 25.0 μm (4000 to 400 cm⁻¹) were used. A gold mirror was used as a background reference. Sixty-four scans with a resolution of 4.00 cm⁻¹ and Kubelka–Munk units were applied. The OMNIC 9.2.41 software (Thermo Fisher Scientific Inc., Waltham, MA, USA) was applied for spectra analysis. The bands of the alkyl C–H groups (A-2948–2920 cm⁻¹ and 2864–2849 cm⁻¹) were assumed to indicate the hydrophobicity, and bands of the C=O groups (B-1710 and 1640–1600 cm⁻¹) indicated hydrophilicity. The ratio of hydrophobicity and hydrophilicity was used to determine the potential wettability index [34].

PWI = A/B

The aromaticity index was calculated according to the reflectance of aliphatic bands ranging from 3000–2800 cm⁻¹ (AL) and an aromatic band at 1520 cm⁻¹ (AR) [35].

iAR = AL/(AL + AR)

The easily extractable glomalin (EEG) and total glomalin (TG) were determined according to Wright and Upadhyaya [26]. Briefly, 8 mL of sodium citrate (Penta Chemicals Unlimited, Prague, Czech Republic) (20 mmol L⁻¹ of pH 7.0—EEG, 50 mmol L⁻¹ pH 8.0—TG) was added to the 1.00 g of air dried soil (<2 mm), followed by autoclaving at 121 °C (30 min—EEG, 60 min—TG), cooling, and centrifugation at 5000 rpm (10 min—EEG, 15 min—TG). For the TG, the centrifugation of the supernatant of the same sample was repeated 5 times until the supernatant no longer showed the red-brown color that is typical of glomalin. Both forms of glomalin were determined colorimetrically using bovine albumin (BSA) as a standard for quantification and the Bradford protein assay (both from Bio-Rad, Hercules, CA, USA) to achieve the color change.

Humification indices were calculated according to Iqbal et al. [35] and Raiesi [36]:

degree of polymerization: HA = C_HA/C_FA

(1)

humification rate: HR = (C_FA + C_HA)/C_SOM

(2)

humification index: HI = C_HA/C_SOM

(3)

where C_FA is the fulvic acid carbon, C_HA is the humic acid carbon, and C_SOM is the total organic carbon in the soil.

The carbon sequestration efficiency (CSE) was calculated as follows:

CSE (%) = ((C_SOMtreatment − C_SOMunfert)/TCI) × 100

(4)

C_SOMtreatment is the amount of C in the soil of the fertilized treatment. C_SOMunfert is the amount of C in the soil of the unfertilized Con treatment. TCI is the total C input (t ha⁻¹) applied in the organic fertilizers during the duration of the individual experiments [37].

2.2. Statistical Analysis

The results were assessed through ANOVA analysis and Pearson’s correlation coefficient using the Statistica program ver. 12 (TIBCO, Paolo Alto, CA, USA). One-way ANOVA statistical analysis was performed with Tukey’s for treatment and site effects (p < 0.05). Pearson’s correlation coefficients were used to analyze the relationships among the studied variables. The level of significance of p < 0.05 or less was considered statistically significant. Principal component analysis (PCA) was performed to evaluate the relationships between the content of glomalin (EEG, TG) and the qualitative parameters of SOM using XLSTAT ver. 2022.4.5 (Addinsoft, New York, NY, USA). The variables were submitted to PCA, and eigenvalues > 1, variance (%), and cumulative (%) criteria were used to define the association among the variables.

3. Results

For the statistical evaluation, all of the observed values of the soil organic matter quality indicators from all the treatments were used (

Table 3. Carbon content and qualitative parameters of soil organic matter content at each of the experimental sites.

Site/Indicator	CSOM	CHS	CFA	CHA	E4/E6	CHWC	CDOC	Nt
	(%)	(%)	(%)	(%)		(mg kg−1)	(mg kg−1)	(%)
Staňkov	1.37 c	0.410 a	0.236 c	0.138 b	6.36 b	477 b	72.6 b	0.120 b
Chrastava	1.23 b	0.508 b	0.271 d	0.124 b	7.22 c	425 ab	52.8 a	0.117 b
Jaroměřice	1.41 c	0.520 b	0.270 d	0.170 c	5.40 a	493 b	45.8 a	0.148 c
Hradec and Svitavou	0.927 a	0.372 a	0.180 b	0.071 a	8.05 d	384 a	45.4 a	0.102 a
Pusté Jakartice	1.15 b	0.414 a	0.151 a	0.130 b	5.41 a	437 ab	55.2 a	0.125 b
Site/indicator	EEG	TG	DG	PWI	iAR	HA	HR	HI
	(mg kg−1)	(mg kg−1)	(mg kg−1)			(CHA/CFA)
Staňkov	894 c	3320 c	2427 c	0.019 b	0.04 b	0.587 b	0.273 a	0.101 b
Chrastava	634 a	2712 bc	2077 bc	0.019 b	0.04 b	0.462 a	0.324 b	0.101 b
Jaroměřice	809 b	3078 bc	2269 bc	0.016 a	0.03 a	0.629 b	0.312 b	0.120 c
Hradec nad Svitavou	702 a	2408 ab	1705 ab	0.015 a	0.03 a	0.392 a	0.272 a	0.076 a
Pusté Jakartice	706 a	1926 a	1220 a	0.015 a	0.03 a	0.860 c	0.246 a	0.114 bc

Different letters describe statistically significant differences between sites. Tukey’s HSD test, p < 0.05.

). The significant influence of the sites is visible in the presented results. There were significant differences among the monitored soil organic matter indicators. Several sites may show agreement on individual indicators, but not in general. The smallest differences between sites were recorded for the following indicators: humic substance content (C_HS), easily extractable carbon (C_DOC), potential wettability index (PWI), and aromaticity index (iAR). Based on the results of the soil organic matter quality indicators, we found the highest quality luvisol at the Jaroměřice site, which reached the highest C_SOM, C_HWC, C_HS, and C_HA/C_FA ratios. The lowest E4/E6 ratio was determined on the Jaroměřice and Pusté Jakartice sites. On the other hand, the results of the soil organic matter quality indicators showed that the luvisol from the Hradec and Svitavou sites had the lowest quality (highest E4/E6, 8.05; lowest C_HA/C_FA, 0.392).

Table 4. The influence of fertilization on soil carbon content and qualitative parameters of soil organic matter.

	Con	F	F+M1	F+M2	F+M3	Average = 1
relative CSOM (%)	0.920 a	0.988 b	1.025 bc	1.020 bc	1.047 c	1.22%
relative CHS (%)	0.983 a	0.989 a	0.959 a	1.018 a	1.050 a	0.445%
relative CFA (%)	0.979 a	0.940 a	1.036 a	1.015 a	1.019 a	0.222%
relative CHA (%)	0.875 a	0.981 a	0.950 a	1.061 a	1.135 a	0.127%
relative HA (CHA/CFA)	0.890 a	1.06 a	0.922 a	1.03 a	1.09 a	0.586
relative HR (CHS/CSOM)	1.03 a	0.956 a	0.978 a	1.02 a	1.02 a	0.286
relative HI (CHA/CSOM)	0.954 a	0.992 a	0.926 a	1.04 a	1.09 a	0.102
relative CHWC (%)	0.926 a	0.938 a	1.03 a	1.03 a	1.08 a	443 mg kg−1
relative CDOC (%)	0.951 a	0.914 a	1.03 ab	0.969 ab	1.14 b	54.4 mg kg−1
relative CHWC/CSOM (%)	1.00 a	0.949 a	1.00 a	1.01 a	1.04 a	0.037
relative CDOC/CSOM (%)	1.03 a	0.920 a	1.01 a	0.958 a	1.09 a	0.005
relative Nt (%)	0.921 a	0.979 b	1.02 ab	1.03 ab	1.05 b	0.123%
relative CSOM/Nt	0.997 a	1.01 a	1.00 a	0.994 a	1.00 a	9.97
relative EEG (%)	0.971 a	0.984 a	0.982 a	1.02 a	1.04 a	749 mg kg−1
relative TG (%)	0.805 a	0.969 ab	0.950 ab	1.05 bc	1.22 c	2689 mg kg−1
relative DG (%)	0.746 a	0.964 ab	0.938 a	1.06 ab	1.29 b	1940 mg kg−1
relative EEG/TG (%)	1.17 b	0.993 ab	0.998 ab	0.967 ab	0.870 a	0.279
relative EEG/CSOM (%)	1.06 a	0.992 a	0.955 a	1.00 a	0.992 a	0.063
relative TG/CSOM (%)	0.883 a	0.984 ab	0.930 a	1.038 ab	1.16 b	0.221
relative E4/E6 (%)	0.955 a	0.974 ab	1.021 b	1.021 b	1.029 b	6.49
relative PWI (%)	0.961 a	0.969 a	0.979 a	1.00 a	1.09 a	0.017
relative iAR (%)	0.955 a	0.977 a	0.977 a	1.01 a	1.08 a	0.033
relative CSE (%)	-	0.696 a	1.02 ab	1.00 ab	1.37 b	19.2%

Different letters describe statistically significant differences among treatments. Tukey’s HSD test, p < 0.05.

presents the results describing the influence of the treatments on the soil organic matter quality indicators. We evaluated the effect of the treatments by replacing the current variable values with relative ones. The relative values were calculated as V_treatment/V_site-average, where V_treatment was the value of each treatment, and V_site-average was the average value of a particular site among all treatments. Evaluating the results in this way helped eliminate individual site characteristics while maintaining the influence of the treatment. The average value of the indicators calculated for all five sites is presented along with the relative results.

The first indicator presented is the organic carbon content (C_SOM). The average C_SOM content was 1.22%. Farmyard manure (F) fertilization and farmyard manure with mineral fertilizers (F+M) significantly increased the C_SOM content compared to the Con treatment. The C_SOM content for the intensive mineral fertilization treatment (F+M3) was significantly higher than all of the other treatments. Compared with the average value (C_SOM, 1.22%), it increased by 4.7%, and compared with the Con treatment, it was 5.5%.

We performed the fractionation of humic substances and evaluated the C_HS, C_FA, and C_HA content. These indicators showed no significant difference among treatments. Estimating these indicators allowed us to calculate the humification degree (HA), humification rate (HR), and humification index (HI). There were no significant differences among the treatments for HA, HR, and HI. However, the treatments combining manure and mineral fertilizer (F+M3) showed an obvious trend of increasing values. The combined F+M3 treatment increased the C_SOM content and other soil organic matter quality indicators (e.g., C_HA/C_FA). The lowest C_SOM values were recorded for the unfertilized Con treatment, which goes hand in hand with lower soil organic matter quality.

We estimated the C_SOM quality using two extraction methods: hot-water extraction (C_HWC) and 0.01 M L⁻¹ CaCl₂ extraction (C_DOC). The intensive mineral fertilizer treatment (F+M3) recorded higher values than the Con and other treatments. These differences were significant for the C_DOC indicator. The C_DOC content was 14% higher for this treatment compared to the average and was almost 19% higher than the Con treatment. The average C_DOC and C_HWC content was 54.4 and 443 mg kg⁻¹, respectively. We also calculated the C_HWC/C_SOM and C_DOC/C_SOM ratios to provide better insight into the results. The averages for the C_HWC/C_SOM and C_DOC/C_SOM ratios were 0.037 and 0.005, respectively. Therefore, C_HWC and C_DOC can be described as potentially mineralizable carbon and easily extractable carbon, respectively. Our statistical evaluation showed no differences among the treatments for these indicators. On the other hand, there was a certain trend of increased values for the F+M3 treatment. Further investigation is necessary to confirm the increasing trend in the less stable fraction of soil organic matter for this treatment.

We also used the easily extractable glomalin content (EEG) and total glomalin content (TG) as indicators for evaluating the organic matter quality. The difficult extractable glomalin content (DG) was calculated as the TG–EEG content. There were no significant differences in EEG among the fertilizer treatments. On the other hand, the F+M2 and F+M3 treatments were significantly different from Con in terms of the TG indicator. The F+M3 treatment was also different from the other treatments. This increase is significant and attributed to the increase in DG. The average EEG/TG ratio was 0.279. The F+M3 treatment had the lowest values for EEG/TG, whereas the Con treatment had the highest values. Both of these differences are significant. The average value of the EEG/C_SOM ratio was 6.26%. There were no significant differences among the treatments in this indicator. The average value for TG/C_SOM was 0.221. A significant increase was recorded for the F+M3 treatment (25.6%). A significant decrease in the ratio was recorded for the Con treatment (19.5%).

An additional qualitative indicator of humic substances that characterizes the process of soil humification is the optical density ratio (E4/E6). The high values of the E4/E6 ratio correspond to a low aromaticity of humic substances and the presence of large quantities of carbohydrates, amides, and several aliphatic structures in humic substances. The average E4/E6 value was 6.49. Applying mineral fertilizer (specifically, the F+M2 and F+M3 treatments) significantly increased the values. Increased values indicate higher aliphatic structure content and lower aromatic content.

We determined the potential wettability index (PWI) and index of aromaticity (iAR) using the DRIFT spectra. The bonds of the alkyl C–H groups (2948–2920 cm⁻¹ and 2864–2849 cm⁻¹) were assumed to indicate hydrophobicity and the bands of the C=O groups (1710 and 1640–1660 cm⁻¹) indicate hydrophilicity. We determined the potential wettability index using the ratio of hydrophobicity to hydrophilicity. The aromaticity index was calculated according to the reflectance of the aliphatic bands ranging between 3000 and 2800 cm⁻¹ (AL) and the aromatic band at 1520 cm⁻¹ (AR). We found no significant differences among the treatments using the PWI and iAR parameters. However, the F+M3 treatment showed an increasing trend.

We calculated the carbon sequestration efficiency (CSE) from the difference in C_SOM for the fertilized and unfertilized treatments in relation to the total applied carbon in manure (for the entire experiment) (Table 4). Applying mineral fertilizer increased the organic matter content more than pure manure. This manifested after using the same calculation as an “increase” in CSE. The average CSE value was 13.4% for the F treatment. Intensive mineral fertilizer (F+M3) increased the average value by 12.9% and up to 26.3%. Combining balanced mineral fertilizer with farmyard manure increased the soil sequestration of carbon.

We used Pearson’s correlation coefficients to analyze the relationships among the studied variables (

Table 5. Pearson’s correlation coefficients (r) among variables.

	CSOM	CHS	CFA	CHA	HA	HR	HI	E4/E6	CHWC	CDOC	Nt	CSOM/Nt	EEG	TG	PWI
CHS	0.505 ***
CFA	0.608 ***	0.643 ***
CHA	0.805 ***	0.717 ***	0.481 ***
HA	0.323 **	0.197	−0.363 **	0.616 ***
HR	0.068	0.652 ***	0.725 ***	0.332 **	−0.291 *
HI	0.429 ***	0.668 ***	0.237 *	0.872 ***	0.708 ***	0.446 ***
E4/E6	−0.503 ***	−0.271 *	−0.004	−0.671 ***	−0.744 ***	0.074	−0.646 ***
CHWC	0.622 ***	0.303 **	0.314 **	0.555 ***	0.283 *	0.010	0.323 **	−0.302 **
CDOC	0.357 **	−0.063	0.078	0.236 *	0.210	−0.124	0.119	−0.108	0.348 **
Nt	0.822 ***	0.513 ***	0.381 ***	0.795 ***	0.490 ***	0.001	0.520 ***	−0.622 ***	0.590 ***	0.077
CSOM/Nt	0.511 ***	0.094	0.499 ***	0.216	−0.169	0.136	−0.019	0.041	0.196	0.522 ***	−0.058
EEG	0.497 ***	−0.007	0.177	0.406 ***	0.182	−0.076	0.192	−0.285 *	0.409 ***	0.348 **	0.358 **	0.331 **
TG	0.534 ***	0.293 *	0.497 ***	0.420 ***	−0.046	0.212	0.196	0.018	0.268 *	0.324 **	0.325 **	0.434 ***	0.364 **
PWI	0.547 ***	0.328 **	0.399 ***	0.358 **	0.036	0.064	0.126	0.067	0.406 ***	0.457 ***	0.270 *	0.521 ***	0.203	0.383 ***
iAR	0.651 ***	0.438 ***	0.530 ***	0.471 ***	0.030	0.163	0.203	−0.021	0.455 ***	0.400 ***	0.377 ***	0.543 ***	0.242 *	0.455 ***	0.967 ***

* p < 0.05; ** p < 0.01; *** p < 0.001; n = 75.

). C_SOM was significantly correlated with all other soil organic matter quality indicators, except HR. A strong inverse correlation was revealed between C_SOM and E4/E6. The E4/E6 ratio is generally regarded as a soil organic matter quality indicator that describes the humification process in soil. A strong negative correlation was indicated between E4/E6 and the following soil organic matter quality indicators: C_HA, degree of polymerization (C_HA/C_FA), and humification index (C_HA/C_SOM)—which aligns with the aforementioned supposition. As there is a strong correlation between C_SOM and N_t, there is also a strong negative correlation between E4/E6 and N_t. We observed a weaker relationship with extractable carbon (C_HWC and C_DOC).

An important indicator of soil organic matter quality is the glomalin content. EEG and TG were both strongly correlated with the C_SOM content, along with the C_HA content. The C_HA and glomalin content are both important contributors to stable soil organic matter. A stronger relationship was observed for the correlation with the total glomalin content. The repeated extraction of the total glomalin probably causes the release of more stable proteins, which likely contribute to a strong TG correlation with C_SOM. We estimated a correlation of moderate strength (p < 0.01) between the EEG and TG content.

The DRIFT analyses (potential wettability index (PWI) and aromaticity index (iAR)) indicated that both the PWI and iAR correlate strongly with C_SOM, C_HS, C_FA, and C_HA, and with C_WHC and C_DOC. A relationship between E4/E6 and the PWI and iAR was not established, although the PWI, iAR, and E4/E6 are all strongly correlated with C_HA. On the other hand, we demonstrated a strong, significant relationship between (p < 0.001) the TG and PWI, and iAR. This positive correlation was likely caused by repeated soil sample extraction during the TG estimation as the C–H groups (of hydrophobic character) are likely released in higher quantities.

Principal component analysis (PCA) can be used to comprehensively evaluate data. We selected the principal components (PCs) using a cross-validation method based on three criteria: eigenvalue > 1.3, loading factors > 0.67, and percentage of variability > 10%, as mentioned in

Table 6. Principal components (PCs) and their loading factor values, eigenvalues, variabilities (%), and cumulative variance (%).

Variables	PC1	PC2	PC3
CHS	0.75	0.43	−0.5
CFA	0.70	−0.65	−0.19
CHA	0.93	0.19	0.14
E4/E6	0.86	−0.35	0.37
CSOM	0.89	0.02	0.46
CHWC	0.96	−0.26	0.12
CDOC	0.81	−0.11	−0.09
Nt	0.92	−0.05	0.38
CSom/Nt	−0.34	0.67	0.54
EEG	0.95	0.1	−0.2
TG	0.96	0.26	0.05
PWI	0.91	0.26	−0.27
iAR	0.93	0.31	−0.19
Eigenvalue	9.5	1.5	1.3
Variability (%)	73	12	10
Cumulative variance (%)	73	85	94

. Based on the biplot position described in Figure 1, PC₁ has an eigenvalue of about 9.5, which explains 73% of the total cumulative variance, and PC₁ is highly dominated by positively associated variables such as C_HS, C_FA, C_HA, E4/E6, C_SOM, C_HWC, C_DOC, N_t, EEG, TG, PWI, and iAR. Based on the contribution of the variables, C_HA, C_HWC, iAR, EEG, and TG provide 9.2%, 9.6%, 9.1%, 9.5%, and 9.7% to PC₁, respectively. The variables in this component are all negatively correlated with the C_SOM/N_t ratio, but are positively influenced by the F+M₂ and F+M₃ treatments. The second PC has an eigenvalue of about 1.5, which is 85% of the total cumulative variance and primarily dominated by the C_Som/N_t variable. This variable contributes about 29%, and F treatment positively influences 49% of the variable. By contrast, the third PC has an eigenvalue of 1.3, 94% of the total cumulative variance, with no variables dominating this principal component.

4. Discussion

We calculated the carbon sequestration efficiency (CSE) from the difference in SOM for fertilized and unfertilized (Con) treatments in relation to the total applied carbon in manure. According to Wang et al. [37], carbon sequestration efficiency is primarily related to soil fertility. These values are below those reported by Sedlář et al. [26]. The aforementioned authors estimated 30.8 and 43.2% for the F and F+NPK treatments, respectively. Similar to our results, Sedlář et al. [26] described increased carbon sequestration in the soil after mineral fertilizer treatments. In our experiment, the highest C_HA content and C_HA/C_FA ratio were observed in the F+M3 treatment. This finding confirms the conclusions of Klik et al. [38], who stated that highly stable forms of carbon (e.g., C_HA) are beneficial for carbon sequestration in soil.

Based on the E4/E6 results, the Jaroměřice and Pusté Jakartice sites had the highest quality luvisol (Table 3). These sites also had the greatest degree of polymerization (C_HA/C_FA). In contrast, the highest E4/E6 values were recorded at the Hradec nad Svitavou site (8.05), which corresponds to the lowest value of C_HA/C_FA (0.392). The relationship between E4/E6 and C_HA/C_FA is site-specific [39,40]. No statistically significant differences in the C_HA/C_FA or E4/E6 ratios were found between the manure-only fertilized (F) and unfertilized (Con) treatments (Table 4). Menšík et al. [23] reported similar values, where E4/E6 produced no significant difference between fertilized and unfertilized treatments. Their experiment was also conducted in long-term luvisol field trials. Song et al. [24] and Galantitni and Rosell [25] reported a higher C_HA/C_FA ratio for the fertilized treatment than for the control group. They mentioned similar increases in E4/E6 in farmyard manure treatments while reporting on an increased fulvic acid content from farmyard manure treatment. Galantini and Rossel [25] found that higher aliphatic and phenolic -OH group contents usually developed after organic fertilizer application. Changes in the E4/E6 ratio caused by fertilization were more pronounced than changes in the carbon fractions (C_FA, C_HA, HI, HR, HA). Similarly, Gerzabek et al. [41] and Oktaba et al. [42] presented significant changes in the E4/E6 ratio caused by fertilization, despite it having no effect on the C_HA/C_FA ratio. Mineral fertilizer treatments showed a higher E4/E6 ratio than Con treatment. F+M3 treatment produced a significantly different E4/E6 ratio than Con (Table 4). A different study with similar results estimated a higher E4/E6 ratio for treatments with mineral + organic fertilizer over control or pure organic fertilizer [43]. A high E4/E6 ratio from F+M3 treatment likely corresponds to the low aromaticity of humic substances and the presence of large quantities of aliphatic structures. A strong inverse correlation appears between the E4/E6, C_SOM, and indicators of soil organic matter quality (C_HA, HA, HI, HR), which gives this method a certain perspective as a soil organic matter quality indicator (Table 5).

The quality of soil organic matter is determined by the potential wettability index (PWI), representing the ratio between aliphatic (C–H) and carboxyl (C=O) bonds. High PWI values indicate lower aggregate wettability [44]. We did not observe any significant differences in the PWI values among the treatments; however, the F+M3 treatment showed an increasing trend (Table 4). Unlike our previous results [6], farmyard manure did not significantly influence the PWI. Demyan et al. [27] observed an increase in the PWI after farmyard manure application. Organic fertilizer application increased the hydrophobic particle content and contributed to forming larger soil aggregates under these treatments. Secondary metabolites created during the decay of organic matter can be hydrophobic in character [42]. There may be several reasons for the increased PWI values under the F+M3 treatment. Mineral fertilization contributed to greater root biomass production, increased root exudate production, and an enhanced formation of stable aggregates [44]. A significant correlation between the PWI and C_SOM, C_HS, C_FA, C_HA, as well as C_HWC and C_DOC, is present (Table 5). A strong correlation between the PWI and C_SOM is also mentioned in other studies [6,45]. We also demonstrated a strong correlation between the TG and PWI in our experiment (Table 5). This relationship was already established in our previous study with maize monoculture on luvisol [6], but was not confirmed for chernozem [7]. Glomalin is a temperature-stable, sticky, hydrophobic glycoprotein [19]. Following simple through-chain analysis, we can conclude that if the glycoprotein content increases, hydrophobic particles and the PWI also increase. A significant correlation between the TG and PWI is in accord with this hypothesis (Table 5).

The aromaticity index (iAR) was calculated according to the reflectance of the aliphatic and aromatic bands [28]. There were no significant differences in the iAR among the treatments (Table 4). A strong correlation was established between the iAR and C_SOM and its indicators of quality (C_HS, C_FA, C_HA, C_HWC, and C_DOC). A significant relationship was also demonstrated regarding the glomalin content. These results conflict with the results of Balík et al. [7], where no significant effect of organic fertilizer application on the iAR was observed.

We established a significant correlation between the glomalin content (EEG and TG) and C_SOM, C_HA, C_HWC, and C_DOC (Table 5). Additionally, the TG was also strongly correlated with the C_FA content. Řezáčová et al.’s [46] conclusions were not confirmed, as they presented a tighter relationship between the EEG and C_SOM than the TG and C_SOM. Repeated extraction may cause higher correlations for the TG. With the exception of the glomalin glycoprotein, additional humic substances are released. A cross-reaction in the Bradford assay, which includes humic acids, polyphenolic compounds, sugars, and lipids, can interfere with glomalin determination [47]. The aforementioned organic compounds can also lead to misestimations of the glomalin content [18]. In our previous work, we observed a positive correlation between the glomalin content and the C_SOM, C_HA, and C_HA/C_FA ratio in long-term experiments with maize monoculture on luvisol [6]. Similarly, Vlček and Pohanka [17] established a correlation between the C_ox, humic and fulvic acids, C/N ratio, and glomalin content. The soil quality and type significantly influence the relationship between the glomalin content and C_SOM (including soil organic matter quality indicators such as C_FA, C_HA, C_HA/C_FA, C_HWC, and C_DOC). We found no significant correlations between the SOM quality and quantity indicators and the glomalin content on long-term maize monoculture with different fertilizer treatments on chernozem [7]. This result is caused by the high stability of the soil organic matter content in chernozem. The different fertilizer treatments caused no significant changes in the C_SOM content and quality. The glomalin content in soil has a tight relationship with the soil organic matter (SOM) content [15,18,48]. We observed no significant increase in the glomalin content after using farmyard manure in our study. The results from a long-term experiment on luvisol with crop rotation at the Červený Újezd site [22] could not be confirmed. Similarly, Bertagnoli et al. [49], Zhang et al. [13], Valarini et al. [50], Turgay et al. [12], and Dai et al. [11] observed an increase in TG after applying cattle or farmyard manure fertilizers. Combining organic and mineral fertilizers increased the TG content, especially in the F+M3 treatment. This treatment produced high biomass yield, which is connected to the highest post-harvest residues (stubble) and root biomass production, as well as a likely increase in exudate production. This was manifested as an increase in the C_SOM content.

The average proportion of EEG in the TG was almost 27.9%. Interestingly, the Červený Újezd experimental site estimated a similar proportion (28.8%) for luvisol [6]. Furthermore, the proportion of EEG in the TG was significantly higher in the control treatment (34.6%). The proportion of TG in the C_SOM is 22.1% on average; however, intense fertilizer application increases this value. For example, Comis [51] reported the proportion of TG in the C_SOM as 27%. Glomalin can add up to 25% of C_SOM [52], which is a significant proportion (22.1%). Therefore, glomalin plays an important role in soil carbon sequestration and promotes the stability of soil organic carbon through its slow degradation (and low soil turnover rate) [53].

5. Conclusions

Based on the results of long-term field experiments on luvisols at five sites in the Czech Republic, we concluded that:

(i)

Combining organic and mineral fertilizers at moderate and higher intensity increases the soil organic matter quantity and quality in comparison with unfertilized or pure organic treatment. Intensive mineral fertilizer (F+M3) increased the average value of the carbon sequestration efficiency (CSE) by 12.9% and up to 26.3%.

(ii)

Data on the glomalin content can be used to study the organic matter quality. We demonstrated a strong correlation between the total glomalin content (TG) and soil organic matter quality and quantity (C_SOM, C_FA, C_HA, C_HWC, C_DOC), as well as the potential wettability index (PWI) and aromaticity index (iAR). No significant relationship was established between the E4/E6 and glomalin content (both EEG and TG).

(iii)

Neither EEG nor TG seem to be more suitable than the other for SOM quality determination.