The Potential of Biochar Made from Agricultural Residues to Increase Soil Fertility and Microbial Activity: Impacts on Soils with Varying Sand Content

agronomy Article The Potential of Biochar Made from Agricultural Residues to Increase Soil Fertility and Microbial Activity: Impacts on Soils with Varying Sand Content Martin Brtnicky 1,2,3,* , Tereza Hammerschmiedt 1,3 , Jakub Elbl 4,5 , Antonin Kintl 1,4 , Lucia Skulcova 1, Maja Radziemska 1,6 , Oldrich Latal 1, Tivadar Baltazar 1, Eliska Kobzova 1and Jiri Holatko 1,*   Citation: Brtnicky, M.; Hammerschmiedt, T.; Elbl, J.; Kintl, A.; Skulcova, L.; Radziemska, M.; Latal, O.; Baltazar, T.; Kobzova, E.; Holatko, J. The Potential of Biochar Made from Agricultural Residues to Increase Soil Fertility and Microbial Activity: Impacts on Soils with Varying Sand Content. Agronomy 2021,11, 1174. https://doi.org/ 10.3390/agronomy11061174 Academic Editors: Lukas Trakal and Stephan M. Haefele Received: 3 March 2021 Accepted: 5 June 2021 Published: 9 June 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Department of Agrochemistry, Soil Science, Microbiology and Plant Nutrition, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, 61300 Brno, Czech Republic; [email protected] (T.H.); [email protected] (A.K.); [email protected] (L.S.); [email protected] (M.R.); [email protected] (O.L.); tivadar[email protected] (T.B.); [email protected] (E.K.) 2 Institute of Chemistry and Technology of Environmental Protection, Faculty of Chemistry, Brno University of Technology, Purkynova 118, 61200 Brno, Czech Republic 3Department of Geology and Soil Science, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemedelska 1, 61300 Brno, Czech Republic 4Agricultural Research, Ltd., Zahradni 400/1, 66441 Troubsko, Czech Republic; [email protected] 5Department of Agrosystems and Bioclimatology, Faculty of AgriSciences, Mendel University in Brno, Zemedelska 1, 61300 Brno, Czech Republic 6Institute of Environmental Engineering, Warsaw University of Life Sciences, 159 Nowoursynowska, 02-776 Warsaw, Poland *Correspondence: [email protected] (M.B.); [email protected] (J.H.); Tel.: +420-607-036-907 (M.B.); +420-603-968-780 (J.H.) Abstract: Different types of soil respond variably to biochar amendment. Soil structure and fertility are properties which strongly affect the impacts of biochar on soil fertility and microbial activity. A pot experiment with lettuce was conducted to verify whether biochar amendment is more beneficial in sandy soil than in clay soil. The nutrient content (carbon and nitrogen), microbial biomass carbon, soil respiration, metabolic quotient, and plant biomass yield were determined. The treatments were prepared by mixing silty clay loam (Haplic Luvisol) with a quartz sand in ratios of 0%, 20%, 40%, 60%, 80%, and 100% of sand; the same six treatments were prepared and amended with biochar (12 treatments in total). Soil carbon and nitrogen, microbial biomass carbon, and soil respiration were indirectly dependent on the descending sand ratio, whereas the metabolic quotient increased with the ascending sand ratio. The biochar’s effects were positive for total carbon, microbial biomass carbon, metabolic quotient, and plant biomass in the sand-rich treatments. The maximum biochar-derived benefit in crop yield was found in the 100% sand + biochar treatment, which exhibited 24-fold (AGB) and 11-fold (root biomass) increases compared to the unamended treatment. The biochar application on coarse soil types with lower fertility was proven to be favorable. Keywords: pot experiment; Lactuca sativa; soil respiration; metabolic quotient; crop yield; total soil nitrogen 1. Introduction The soil structure is the key feature that controls microbially mediated processes of organic matter degradation in terrestrial ecosystems [ 1 ]. Soil texture is the important soil property that conditions the variability in the carbon (C) and nitrogen (N) turnover, and these differences have been assessed to be most significant between clay and sandy soils [ 2 , 3 ]. The content of microbial C compared to that of non-microbial C is higher (reaching up to 20% of oxidizable C) in clay soils than in coarse-textured soils [ 4 ]. Contrarily, activity of the microbial biomass can be twice as large in sandy or loam soils as in clay soils. Agronomy 2021,11, 1174. https://doi.org/10.3390/agronomy11061174 https://www.mdpi.com/journal/agronomy Agronomy 2021,11, 1174 2 of 17 Additionally, the amounts of mineralized N per microbial biomass unit are highest in the sandy soils [ 5 ]. Soil texture and organic matter content are the factors that control the soil functions, resilience, and fertility, even under the application of organic amendments, e.g., biochar [ 6 ]. There have been several studies that have shown that the dependence of the microbial properties (e.g., biomass) on the soil structure and fertility is strongly affected by the type of biochar amendment [ 7 – 9 ]. Slow-pyrolyzed, high-temperature biochars (>600 ◦ C) significantly lower microbial biomass and enzyme activities in coarse-textured soil, whereas they do not in clay soils [ 7 ]. Crop productivity increased significantly (10% in average) in soils of both medium and coarse textured in comparison to unchanged clay soils in previous studies [ 8 , 9 ]. The most significant positive impacts on biomass and activity of soil microbiota were evidenced in sandy soils [ 10 , 11 ] rather than in clay soils [ 12 ]. Some authors have ascribed enhanced soil respiration to biochar-derived C rather than to available soil organic matter (SOM) [ 1 ]. Concurrently, biochar-stimulated mineralization of native soil organic carbon (SOC) is limited only to the low-C clay soils because stabilization of SOC by biochar-induced organomineral interactions are involved [ 2 ]. However, a strong beneficial effect was also reported for these [ 13 ], dependent on the biochar pyrolysis temperature. This is possibly because biochar properties, e.g., the temperature of pyrolysis, also play roles in putative adverse [ 14 ] or positive effects [ 15 ] in coarse-structured soils; nevertheless, many studies have shown the largest impact of biochar application occurring in acidic and sandy-textured soils, which suggests aggregating and moistening effects of biochars [ 9 ]. Several studies have compared the effects of biochars with specific characteristics on chemical (nutrient content and turnover) and biological (microbial biomass carbon (MBC), CO 2 fluxes, diversity) properties of different types of soil (sand, loam, clay) under specific defined conditions [16,17]; however, some of them did not deliver clear results [18,19]. In this study, a short-term pot experiment with a test crop of lettuce (Lactuca sativa L. var. capitata L. cv. Brilliant) was designed and carried out to clarify the roles of soil texture and nutrient content in microbial and plant biomass production properties. In order to reduce the effects of various chemical, physical, and biological properties of particular soil types with different textures, as in other studies [ 20 ], we prepared a set of artificial soil types by mixing a silty clay loam, Haplic Luvisol, with a quartz sand in six specified decreasing ratios (6 treatments) ranging from 100% soil to 100% sand. We hypothesized that in this experimental setting, we would observe a positive effect of amendment of biochar from agricultural residues on soil in the respective selected properties, presuming the highest positive effects on soil microbial abundance and activity in the soil treatments with higher sand content. 2. Materials and Methods 2.1. Biochar Amendment, Soil and Pot Experiment Preparation The biochar used in this study was prepared by pyrolysis of agricultural grain waste (cereal and sunflower husks) at moderate temperatures of approximately 600 ◦ C. According to the manufacturer, the properties of the biochar were as follows: elements (in g · kg −1 ) –C 866, N 3.0, O 10.0, H 14.2; Ash550 ◦C11.7%; salts 0.42%; pH (CaCl2) 8.5. The growth substrates used for the reported pot experiment were prepared by mixing a quartz sand with topsoil (0–15 cm), a silty clay loam (according to USDA Textural Triangle), Haplic Luvisol (according to WRB soil classification [ 21 ]). This field soil was collected near the town of Troubsko, Czech Republic (49 ◦ 10’28”N 16 ◦ 29’32”E), in autumn 2018. The topsoil properties were determined before the start of the experiment as follows: soil macronutrients (in g · kg −1 )—total carbon (TC) 7.0, total nitrogen (TN) 0.80, P 0.049, S 0.073, Ca 1.60, Mg 0.118, K 0.115; N forms (in mg · kg −1 )—N mineral 32.8, N-NO 3 29.6, N-NH 4 3.2; Si 220.0 g · kg −1 ; soil reaction = pH (CaCl 2 ) 7.3. This heavy soil was chosen to ensure sufficiently different textures for all tested treatments depending on the sand:soil ratio. In order to remove the coarse particles, the soil was sieved through a grid with a size of 2.0 mm. The sieved soil was mixed with fine quartz sand (0.1–1.0 mm; ≥ 95% SiO 2 ) in the following ratios (w + w): (1) 100% sand; (2) 80% sand + 20% soil; (3) 60% sand + 40% soil; Agronomy 2021,11, 1174 3 of 17 (4) 40% sand + 60% soil; (5) 20% sand + 80% soil; (6) 100% soil (Table 1). Each treatment was prepared in two versions: (A) without biochar; (B) with biochar in the amount of 32 g per 1 L of pot substrate, equaling 40 t · ha −1 (the dose was adopted from the method used by Sadowska et al. 2020 [ 22 ]). Here, 1 kg of each of the thoroughly mixed substrate treatments was used to fill experimental plastic pots (volume 1 L [ 23 ], top diameter 11 cm, bottom diameter 9 cm, height 13 cm); each treatment was carried out in 3 replicates (pots). Table 1. Experimental treatments of soil and sand mixtures tested in the study. Treatment % Sand % Soil Biochar * Abbreviation (1) 100% sand 100 0 0 g·kg−1d.s. 100:0, 100:0 no-BC (2) 80% sand + 20% soil 80 20 0 g·kg−1d.s. 80:20, 80:20 no-BC (3) 60% sand + 40% soil 60 40 0 g·kg−1d.s. 60:40, 60:40 no-BC (4) 40% sand + 60% soil 40 60 0 g·kg−1d.s. 40:60, 40:60 no-BC (5) 20% sand + 80% soil 20 80 0 g·kg−1d.s. 20:80, 20:80 no-BC (6) 100% soil 0 100 0 g·kg−1d.s. 0:100, 0:100 no-BC (7) 100% sand + biochar 100 0 32 g·kg−1d.s. 100:0 BC, 100:0 BC+ (8) 80% sand + 20% soil + biochar 80 20 32 g·kg−1d.s. 80:20 BC, 80:20 BC+ (9) 60% sand + 40% soil + biochar 60 40 32 g·kg−1d.s. 60:40 BC, 60:40 BC+ (10) 40% sand + 60% soil + biochar 40 60 32 g·kg−1d.s. 40:60 BC, 40:60 BC+ (11) 20% sand + 80% soil + biochar 20 80 32 g·kg−1d.s. 20:80 BC, 20:80 BC+ (12) 100% soil + biochar 0 100 32 g·kg−1d.s. 0:100 BC, 0:100 BC+ Note: * d.s. = dry soil. The following controlled conditions were applied: test crop lettuce (Lactuca sativa L. var. capitata L.), cv. Brilliant; cultivation in growth chamber—full-spectrum stable white LED lighting, intensity 20,000 lx [ 24 ] ~200 µ mol.m −2· s −1 [ 25 ]; photoperiod 12 h [ 26 ]; temperature 18/22 ◦ C (night/day); relative humidity 70% [ 27 ]. A two-day sprouting of the lettuce seeds on wet filter paper preceded sowing to the depth of approximately 2 mm in each pot. After sowing, each pot was watered with 100 mL of distilled water. The 10-day-old seedlings were reduced to only one plant (the most robust) per pot. Pot placement in the growth chamber was randomized. Soil humidity was controlled and water content was maintained during the experiment. The pots were variably rotated once per week [ 28 ]. Six weeks after sowing, the plants were harvested [ 29 ]. A mixed soil sample was collected from each pot (5 subsamples were taken and amalgamated). 2.2. Plant Sampling and Biomass Determination The lettuce shoots were cut at ground level, and the roots were gently cleaned of soil and washed with water [ 28 ]. The lettuce shoots and roots were dried at 60 ◦ C to a constant weight, and dry AGB and root biomass were estimated gravimetrically by weighing on the analytical scales. 2.3. Soil Sampling and Preparation The soil samples were taken after harvesting the lettuce (1 mixed sample per pot). Samples were homogenized by sieving them through a 2 mm mesh sieve under sterile conditions. The samples for MBC determination and respiration (basal and substrateinduced) measurement were stored at 4 ◦ C for 14 days (based on the method [ 30 ]) before they were analyzed. Agronomy 2021,11, 1174 4 of 17 2.4. Soil Chemical, Biological, and Statistical Analyses Soil properties were determined and the data obtained were statistically analyzed using the methods listed in Table 2, for which the specifications were identical to our previously published work [ 31 ]. The results of the Pearson’s correlation analysis were evaluated according to [ 32 ]: 0.5 < ρ < 0.7 meaning moderate correlation and 0.7 < ρ < 0.9 meaning strong correlation. Table 2. Methods used to determine the soil properties for statistical analysis with relevant references. Property Method Unit Reference Total soil carbon dry combustion using LECO TruSpec analyzer (MI USA) mg·g−1[33] Total soil nitrogen [34] Microbial biomass carbon fumigation extraction method mg·g−1[30] Basal soil respiration MicroResp®device µg CO2·g−1·h−1(Technical Manual v2.1) [35] Substrate induced soil respiration MicroResp ® device + inducers (sugars, amino acids) Processing Tool Method Reference Statistical analysis Program R version 3.6.1. Multivariate analysis of variance (MANOVA), principal component analysis (PCA), one-way analysis of variance (ANOVA), Duncan’s multiple range test, Pearson’s correlation analysis [31] 3. Results 3.1. General Assessment of the Effects of Biochar on Soil and Plant Characteristics The results of the MANOVA analysis showed significant differences among all experimental treatments in most of the determined soil and plant properties at the level of p< 0.001 (with the exception of the dry root biomass, which differed at p= 0.001). The data can be found in the Appendix A, Table A1. A two-way ANOVA was carried out to evaluate the effects of either biochar (the first factor) or sand content (the second factor) on the determined soil properties; the results are mentioned below and displayed in the Appendix A, Table A2. A scheme with the results of the Pearson’s correlation analysis is shown in the Appendix A(Figure A1). The evaluation of the mutual dependence between the soil and plant properties and their values for each of the experimental treatments are shown in the Rohlf PCA biplot (Figure 1). The effects of the applied biochar in each experimental treatment were rated to identify potential beneficial or detrimental effects on soil properties. 3.2. Soil Nutrient Content, Plant Biomass Soil TC and TN values in all treatments were indirectly related to the sand content and were increased by the biochar amendment (Figure 2A,C). The differences between BC and non-BC treatments (for each sand:soil ratio) were all significant. The greatest difference in TC was between the 100% sand and 100% sand + biochar treatments (Figure 2A). Except for treatments 100:0 and 80:20, 100:0 BC and 80:20 BC, 40:60 BC and 20:80 BC, there were no significant differences between treatments that differed by ± 20% sand content (either unamended or plus BC). The TC value of the 100% soil + biochar showed no significant difference to the 60% sand + 40% soil, 40% sand + 60% soil, or 20% sand + 80% soil treatments (Figure 2A). Agronomy 2021,11, 1174 5 of 17 Agronomy 2021, 11, x FOR PEER REVIEW 5 of 17 Figure 1. Variable correlation PCA plot describing the relationships between all variables. Color scale (of arrows) from blue to red indicates the increasing ‘weight’ of variables. 3.2. Soil Nutrient Content, Plant Biomass Soil TC and TN values in all treatments were indirectly related to the sand content and were increased by the biochar amendment (Figures 2A,C). The differences between BC and non-BC treatments (for each sand:soil ratio) were all significant. The greatest difference in TC was between the 100% sand and 100% sand + biochar treatments (Figure 2A). Except for treatments 100:0 and 80:20, 100:0 BC and 80:20 BC, 40:60 BC and 20:80 BC, there were no significant differences between treatments that differed by ±20% sand content (either unamended or plus BC). The TC value of the 100% soil + biochar showed no significant difference to the 60% sand + 40% soil, 40% sand + 60% soil, or 20% sand + 80% soil treatments (Figure 2A). These results were influenced by the different soil particulate conditions of the treatments. Decreases in sand content (from 100% to 0%) led to the relatively high increases in TC values of the biochar-amended treatments in comparison to the treatments without biochar (the Appendix, Figure A2A). This trend is apparent in the sharper slope of the regression curve of the dependence of TC on soil content (%) in the BC treatments as compared to the slightly slope in biochar-untreated treatments. However, the two-way ANOVA detected an equally significant (p < 0.001) effect of either the biochar or sand:soil ratio on the values and differences in TC. The TC content in the soil correlated highly positively with soil TN (ρ = 0.71) and also with the dry root biomass (ρ = 0.71), which suggested that a surplus of biochar-derived C in the soil enhanced the plant (root) growth. TC agonism with the dry root biomass is also shown on the PCA plot (Figure 1). Figure 1. Variable correlation PCA plot describing the relationships between all variables. Color scale (of arrows) from blue to red indicates the increasing ‘weight’ of variables. These results were influenced by the different soil particulate conditions of the treatments. Decreases in sand content (from 100% to 0%) led to the relatively high increases in TC values of the biochar-amended treatments in comparison to the treatments without biochar (the Appendix A, Figure A2A). This trend is apparent in the sharper slope of the regression curve of the dependence of TC on soil content (%) in the BC treatments as compared to the slightly slope in biochar-untreated treatments. However, the two-way ANOVA detected an equally significant (p< 0.001) effect of either the biochar or sand:soil ratio on the values and differences in TC. The TC content in the soil correlated highly positively with soil TN ( ρ = 0.71) and also with the dry root biomass ( ρ = 0.71), which suggested that a surplus of biochar-derived C in the soil enhanced the plant (root) growth. TC agonism with the dry root biomass is also shown on the PCA plot (Figure 1). The TN content showed no significant differences (at a significance level of p ≤ 0.05) between most of the treatments, with the same sand:soil ratio and either with or without biochar amendment (with the exception of the 80% sand + 20% soil and the 100% soil). The treatments that differed by ± 20% sand content exhibited significant differences when either unamended or biochar-amended (Figure 2C). The decreasing sand content (from 100% to 0%, by − 20%) led to a relatively smaller increase, coupled with a slighter regression curve slope (the Appendix A, Figure A2B) in the TN of biochar-amended treatments as compared to the sharper regression curve slope with the rise of the TN values in the treatments without biochar. TN strongly correlated with dry ( ρ = 0.90) AGB; the agonism of these properties is also shown via the PCA biplot (Figure 1). As such, we anticipated the growth stimulated by increased N assimilation in plants under higher available soil TN. The two-way ANOVA again revealed equally Agronomy 2021,11, 1174 6 of 17 significant (p< 0.001) effects of either biochar or sand:soil ratio on the values and differences in TN. The dry root biomass showed no significant differences at a certain sand:soil ratio between the two treatments (with or without biochar addition)—see Figure 2D. However, the 20:80 BC treatment differed significantly from the 80:20 BC in dry root biomass. This is evidence of only a weak effect of the various sand:soil ratios (without biochar) on the root biomass, whereas the biochar may enhance these contrasts. The two-way ANOVA results were supportive and revealed a significant (p< 0.001) effect of biochar on the values and differences in the dry root biomass, but it was less significantly (p< 0.05) affected by the sand:soil factor. Agronomy 2021, 11, x FOR PEER REVIEW 6 of 17 Figure 2. (A) Total soil carbon. (B) Dry aboveground biomass. (C) Total soil nitrogen. (D) Dry root biomass. Average values shown with SD (error bars), treatments amended with biochar (dark colors) and unamended treatments (light colors) are sorted by decreasing sand:soil ratios (percentages ranging from 100:0 to 0:100). Different letters indicate statistically significant differences of MANOVA at p ≤ 0.05. The TN content showed no significant differences (at a significance level of p ≤ 0.05) between most of the treatments, with the same sand:soil ratio and either with or without biochar amendment (with the exception of the 80% sand + 20% soil and the 100% soil). The treatments that differed by ±20% sand content exhibited significant differences when either unamended or biochar-amended (Figure 2C). The decreasing sand content (from 100% to 0%, by −20%) led to a relatively smaller increase, coupled with a slighter regression curve slope (the Appendix, Figure A2B) in the TN of biochar-amended treatments as compared to the sharper regression curve slope with the rise of the TN values in the treatments without biochar. TN strongly correlated with dry (ρ = 0.90) AGB; the agonism of these properties is also shown via the PCA biplot (Figure 1). As such, we anticipated the growth stimulated by increased N assimilation in plants under higher available soil TN. The two-way ANOVA again revealed equally significant (p < 0.001) effects of either biochar or sand:soil ratio on the values and differences in TN. The dry root biomass showed no significant differences at a certain sand:soil ratio between the two treatments (with or without biochar addition)—see Figure 2D. However, the 20:80 BC treatment differed significantly from the 80:20 BC in dry root biomass. This is evidence of only a weak effect of the various sand:soil ratios (without biochar) on the root biomass, whereas the biochar may enhance these contrasts. The two-way ANOVA results were supportive and revealed a significant (p < 0.001) effect of biochar on the values and differences in the dry root biomass, but it was less significantly (p < 0.05) affected by the sand:soil factor. A high positive correlation of soil TC content and dry root biomass (ρ = 0.71) and moderately strong correlation between soil TC content and dry ABG (ρ = 0.61) supported the presumed relation between plant biomass and the biochar amendment in the soil. Further, the calculation showed the increase in proportion between plant biomass values of the biochar-treated and plant biomass values of untreated treatments (Figure 3A,B). We Figure 2. ( A ) Total soil carbon. ( B ) Dry aboveground biomass. ( C ) Total soil nitrogen. ( D ) Dry root biomass. Average values shown with SD (error bars), treatments amended with biochar (dark colors) and unamended treatments (light colors) are sorted by decreasing sand:soil ratios (percentages ranging from 100:0 to 0:100). Different letters indicate statistically significant differences of MANOVA at p≤0.05. Agronomy 2021,11, 1174 7 of 17 A high positive correlation of soil TC content and dry root biomass ( ρ = 0.71) and moderately strong correlation between soil TC content and dry ABG (ρ= 0.61) supported the presumed relation between plant biomass and the biochar amendment in the soil. Further, the calculation showed the increase in proportion between plant biomass values of the biochar-treated and plant biomass values of untreated treatments (Figure 3A,B). We suggest that the biochar’s beneficial fertilizing effect on the plant biomass reached the maximum positive effect in the 100% sand sample. Agronomy 2021, 11, x FOR PEER REVIEW 7 of 17 suggest that the biochar’s beneficial fertilizing effect on the plant biomass reached the maximum positive effect in the 100% sand sample. Figure 3. (A) Dry aboveground biomass and (B) dry root biomass trends, i.e., the ratio (of average values) between the plant biomass of the biochar-amended (BC+) and the plant biomass of the unamended (no-BC) treatments, sorted according to decreasing sand:soil ratios (aligned from 100:0 to 0:100). Note: The blue (left) axis belongs to the blue bar (100:0 treatment), while the black (right) axis belongs to the other bars (treatments). 3.3. Microbial Biomass and Respiration Activity We observed significant differences in the MBC values related to the sand:soil ratio in both the biochar-amended and unamended treatments, with the exception of the comparison between the 80% sand + 20% soil and the 60% sand + 40% soil treatments (both BC-treated and untreated). No significant difference in MBC was found between the 20:80 BC and 0:100 BC (Figure 4A). The MBC values of 100% sand, 80% sand + 20% soil, and 60% sand + 40% soil did not significantly differ in pairs of unamended and amended treatments with the same sand:soil ratio (Figure 4A). Significant differences in MBC related to the biochar addition were detected in the untreated 20% sand + 80% soil and 100% soil treatments as compared to the respective 20:80 BC and 0:100 BC treatments (Figure 4A). The two-way ANOVA revealed an equally significant (p < 0.001) effect of either biochar or sand:soil ratio, as well as a significant (p < 0.001) synergic effect of both factors. The MBC showed the highest positive correlation with the AGB dry (ρ = 0.82), and the increase in MBC values was coupled with increasing crop yields. The concordant trends for MBC and dry AGB in the variable correlation PCA plot (Figure 1) corroborated the correlation analysis results. Figure 3. ( A ) Dry aboveground biomass and ( B ) dry root biomass trends, i.e., the ratio (of average values) between the plant biomass of the biochar-amended (BC+) and the plant biomass of the unamended (no-BC) treatments, sorted according to decreasing sand:soil ratios (aligned from 100:0 to 0:100). Note: The blue (left) axis belongs to the blue bar (100:0 treatment), while the black (right) axis belongs to the other bars (treatments). 3.3. Microbial Biomass and Respiration Activity We observed significant differences in the MBC values related to the sand:soil ratio in both the biochar-amended and unamended treatments, with the exception of the comparison between the 80% sand + 20% soil and the 60% sand + 40% soil treatments (both BC-treated and untreated). No significant difference in MBC was found between the 20:80 BC and 0:100 BC (Figure 4A). The MBC values of 100% sand, 80% sand + 20% soil, and 60% sand + 40% soil did not significantly differ in pairs of unamended and amended treatments with the same sand:soil ratio (Figure 4A). Significant differences in MBC related to the biochar addition were detected in the untreated 20% sand + 80% soil and 100% soil treatments as compared to the respective 20:80 BC and 0:100 BC treatments (Figure 4A). The two-way ANOVA revealed an equally significant (p< 0.001) effect of either biochar or sand:soil ratio, as well as a significant (p< 0.001) synergic effect of both factors. The MBC showed the highest positive correlation with the AGB dry ( ρ = 0.82), and the increase in MBC values was coupled with increasing crop yields. The concordant trends for MBC and dry AGB in the variable correlation PCA plot (Figure 1) corroborated the correlation analysis results. Agronomy 2021,11, 1174 8 of 17 Agronomy 2021, 11, x FOR PEER REVIEW 8 of 17 Figure 4. Microbial biomass carbon values (A). Soil basal values (B). Respiration induced by D-glucose (C), D-trehalose (D), N-acetyl-β-D-glucosamine (E), L-alanine (F), L-lysine (G), and L-arginine (H). Average values shown with standard error of mean (error bars), treatments amended with biochar (dark colors) and unamended (light colors) are sorted by decreasing sand:soil ratios (from 100:0 to 0:100). Different letters indicate statistically significant differences of MANOVA at p ≤ 0.05. The microbial biomass determined the microbial activity in the soil, which was measured as the soil respiration. An assumptive basal respiration (BR) relation with the content of sand in the substrate was, however, not observed (Figure 4B). The only significant increase in the BR value due to the sand content was detected in the 20% sand + 80% soil treatment (compared to other unamended treatments) and in the 100% soil + biochar treatment (compared to the other amended treatments). We found it contradictory that the respiration activity of soil microorganisms did not increase with both the increase Figure 4. Microbial biomass carbon values ( A ). Soil basal values ( B ). Respiration induced by D-glucose ( C ), D-trehalose ( D ), N-acetylβ -D-glucosamine ( E ), L-alanine ( F ), L-lysine ( G ), and L-arginine ( H ). Average values shown with standard error of mean (error bars), treatments amended with biochar (dark colors) and unamended (light colors) are sorted by decreasing sand:soil ratios (from 100:0 to 0:100). Different letters indicate statistically significant differences of MANOVA at p≤0.05. The microbial biomass determined the microbial activity in the soil, which was measured as the soil respiration. An assumptive basal respiration (BR) relation with the content of sand in the substrate was, however, not observed (Figure 4B). The only significant increase in the BR value due to the sand content was detected in the 20% sand + 80% soil treatment (compared to other unamended treatments) and in the 100% soil + biochar treatment (compared to the other amended treatments). We found it contradictory that the respiration activity of soil microorganisms did not increase with both the increase in the Agronomy 2021,11, 1174 9 of 17 soil content and the microbial biomass (Figure 4A). Nevertheless, the BR values adjusted to the amount of MBC (i.e., metabolic quotient) showed a clearer picture, which (except for outlying values of the 40% sand + 60% soil treatments, both BC-treated and untreated) evidenced a descending respiration rate with decreasing sand content in the pot substrate (Figure 5A). Agronomy 2021, 11, x FOR PEER REVIEW 9 of 17 in the soil content and the microbial biomass (Figure 4A). Nevertheless, the BR values adjusted to the amount of MBC (i.e., metabolic quotient) showed a clearer picture, which (except for outlying values of the 40% sand + 60% soil treatments, both BC-treated and untreated) evidenced a descending respiration rate with decreasing sand content in the pot substrate (Figure 5A). Figure 5. The dependence of the metabolic (basal (A) and substrate-induced (B and C) quotients (respiration and MBC ratio) on the sand:soil ratio (expressed as a percentage of soil) and biochar amendment. Not all biochar-amended treatments showed decreased BR as compared to the unamended treatments. BR was significantly lowered due to biochar application only in the 100% sand, 40% sand + 60% soil, and 20% sand + 80% soil samples as compared to the untreated treatments. The metabolic quotient qCO2 in the biochar-treated treatments directly responded to the decreasing sand content (Figure 5A). Only the BR value of the 100% soil + biochar treatment did not follow this trend. As documented by the agonisms among all types of respiration in the variable correlation PCA plot (Figure 1) and in the Pearson’s correlation plot (Figure A1, the respiration induced by various sugar substrates (D-trehalose (Tre-SIR), D-glucose (GlcSIR), N-acetyl-β-D-glucosamine (NAG-SIR)) and amino acid substrates (L-alanine (AlaSIR), L-lysine (Lys-SIR), L-arginine (Arg-SIR)) showed very similar results. Soil respiration (SIR) values did not significantly decrease with biochar amendment in the 100% sand and 80% sand + 20% soil treatments, whereas NAG-, Ala-, Lys-, and Arg-SIR values were significantly lowered by biochar application to the soil, with all having a lower sand:soil ratio (60:40, 40.60, 20:80, except for the 100% soil (Figure 4E‒H). Glc-SIR and Tre-SIR were significantly lower in the 40:60 BC and 20:80 BC samples as compared to the unamended 40:60 and 20:80 samples (see Figures 4C,D). Of interest was the fact that all SIRs showed comparable, insignificantly variable values for both the 100% soil and 100% soil + biochar samples. The sand:soil ratio from 100:0 to 60:40 among the respective treatment (both BC-treated and untreated) samples demonstrated mostly insignificant differences in SIR values (except for Glc-SIR, Tre-SIR, Ala-SIR 100:0 vs. 60:40, and Lys-SIR, Arg-SIR 80:20 vs. 60:40). Contrarily, the treatments showed significantly lower SIRs as compared to the respective 40:60, 20:80, and 0:100 treatments (with and without biochar) (Figure 4C‒H). While the Glc-SIR and Lys-SIR in the 100% soil were significantly lower as compared to the 20% sand + 80% soil treatment, all SIRs in the 100% soil + biochar were significantly increased in comparison to the 20% sand + 80% soil + biochar and the other higher sand:soil ratios. However, substrate-induced qCO2 was also lowered due to the biochar amendment. Both the amended and unamended treatments followed an opposite trend to soilsubstrate-induced respiration: the direct decrease in qCO2 related to the descending amount of sand in the substrate (Figure 5B,C). Nevertheless, the two-way ANOVA showed an equally significant (p < 0.001) effect of either the biochar or sand:soil ratio, as Figure 5. The dependence of the metabolic (basal ( A ) and substrate-induced ( B , C ) quotients (respiration and MBC ratio) on the sand:soil ratio (expressed as a percentage of soil) and biochar amendment. Not all biochar-amended treatments showed decreased BR as compared to the unamended treatments. BR was significantly lowered due to biochar application only in the 100% sand, 40% sand + 60% soil, and 20% sand + 80% soil samples as compared to the untreated treatments. The metabolic quotient qCO 2 in the biochar-treated treatments directly responded to the decreasing sand content (Figure 5A). Only the BR value of the 100% soil + biochar treatment did not follow this trend. As documented by the agonisms among all types of respiration in the variable correlation PCA plot (Figure 1) and in the Pearson’s correlation plot (Figure A1, the respiration induced by various sugar substrates (D-trehalose (Tre-SIR), D-glucose (Glc-SIR), N-acetylβ -D-glucosamine (NAG-SIR)) and amino acid substrates (L-alanine (Ala-SIR), L-lysine (Lys-SIR), L-arginine (Arg-SIR)) showed very similar results. Soil respiration (SIR) values did not significantly decrease with biochar amendment in the 100% sand and 80% sand + 20% soil treatments, whereas NAG-, Ala-, Lys-, and Arg-SIR values were significantly lowered by biochar application to the soil, with all having a lower sand:soil ratio (60:40, 40.60, 20:80, except for the 100% soil (Figure 4E–H). Glc-SIR and Tre-SIR were significantly lower in the 40:60 BC and 20:80 BC samples as compared to the unamended 40:60 and 20:80 samples (see Figure 4C,D). Of interest was the fact that all SIRs showed comparable, insignificantly variable values for both the 100% soil and 100% soil + biochar samples. The sand:soil ratio from 100:0 to 60:40 among the respective treatment (both BC-treated and untreated) samples demonstrated mostly insignificant differences in SIR values (except for Glc-SIR, Tre-SIR, Ala-SIR 100:0 vs. 60:40, and Lys-SIR, Arg-SIR 80:20 vs. 60:40). Contrarily, the treatments showed significantly lower SIRs as compared to the respective 40:60, 20:80, and 0:100 treatments (with and without biochar) (Figure 4C–H). While the Glc-SIR and Lys-SIR in the 100% soil were significantly lower as compared to the 20% sand + 80% soil treatment, all SIRs in the 100% soil + biochar were significantly increased in comparison to the 20% sand + 80% soil + biochar and the other higher sand:soil ratios. However, substrate-induced qCO 2 was also lowered due to the biochar amendment. 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