Environment, Soil, and Digestate Interaction of Maize Silage and Biogas Production

Abstract

In this study are presented the possibilities of using maize silage for biogas production. An experiment with maize silage took place over three years (2016–2018) in two localities, Ilandža, Alibunar municipality (L1—Locality 1) and Dolovo (L2—Locality 2), Serbia, and using two variants: a control with no digestate (C) and a variant with digestate, which was organic manure from biogas facilities (AD). In the AD variant, 50 t ha⁻¹ of digestate was introduced into the soil just before sowing the maize. The following traits were examined: plant height (PH), biomass yield (BMY), biogas yield (BGY), and methane yield (MY). The effects of the studied factors (year, fertilization, and locality) on the biogas yield were significant (p < 0.5). The most favorable year for biogas production was 2016 (207.95 m³ ha⁻¹), while the highest values of maize plant height, biomass, and methane yield were recorded in 2018 (2.48 m, 51.15 t ha⁻¹ dry matter, and 258.25 m³ ha⁻¹). The digestate exerted a significant influence (p < 0.5) on the values of all the tested maize parameters in all three experimental years. The biomass yield was positively associated with the plant height, biogas, and methane yield (r = 0.62 *; r = 0.70 *; r = 0.81 **) and positively but nonsignificantly associated with temperature (r = 0.42) and precipitation (r = 0.12). The application of the digestate before sowing improves the anaerobic digestion of maize silage and biogas production.

1. Introduction

Based on the area used for growing agricultural crops, maize (Zea mays L.) is third in the world. Maize is one of the most profitable crops in 20th century agriculture, being third globally in terms of distribution (143 million ha), after wheat (215 million ha) and rice (151 million ha), and first in Serbia. According to recent years’ averages, the area of Serbia occupied by maize is around 1.2 million ha, with oscillations occurring in the range of 1–1.2 mil.ha. The global average maize yield is 5.6 tons per hectare of dry matter of grain [1,2,3,4]. In light of the limited availability of traditional energy supplies, concerns about rising energy consumption, and global warming challenges, the supply of energy has been moving from traditional to renewable resources, such solar, biomass, wind, hydro, geothermal, and biogas. Biomass is an intensively explored and prospective energy source alternative to fossil fuels that might decrease global warming [5,6,7,8,9]. Renewable biofuels are known in the industry as alternative fuels. However, until now, cheap petroleum has put a brake on their global expansion. Additionally, there is a lack of environmental awareness about how serious the consequences of the emissions of fossil fuels are on the climate around the world. As a consequence, the emergence of ethanol and biodiesel has become important for the future of the world’s energy. Clean, renewable, globally available fuels for transport, whose production also develops the agricultural industry, reduces the need for imports of fossil fuels and creates new jobs. This is highly attractive for governments around the world; hence, the global trend of expansion is obvious. Over 6% of Europe’s needs for diesel fuel could be met by using waste materials that have no other practical use, such as sawdust and other forms of wood waste and plants. An additional 14% can be met by using existing grass or uncultivated areas.

One type of renewable energy is biogas. It is environmentally benign and is created when bacteria and microbes break down cellulose without oxygen. Anaerobic bacteria can produce biogas through the breakdown of carbon monoxide or through the fermentation of decomposable materials like sewage, municipal trash, green waste (from parks and gardens), plant matter, and agricultural goods. Anaerobic digestion—that is, digestion without oxygen—is how fertilizers and trash are converted into biogas. The mixture of gases generated when biodegradable materials break down without oxygen is called biogas. It contains primarily 50–70% methane (CH₄) by volume, 30–50% carbon dioxide (CO₂), and trace amounts of other gases such as water vapor (H₂O) and hydrogen sulfide (H₂S). To effectively utilize biogas, the fermentation process can be carried out under regulated conditions in readily accessible equipment known as digestion reservoirs [10].

A great resource that is readily available, affordable, and renewable is lignocellulosic biomass, which comprises kitchen scraps, paper trash, and agricultural residues [11].

Maize straw is one of the most ample lignocellulose wastes. In order to maximize the use of lignocellulosic resources and prevent damage to the environment, it is crucial to address agricultural waste [12]. Compared to medium and early maize hybrids, late types of maize show a higher concentration of ash and lignin but lower amounts of fat and protein [13].

When growing maize for biogas and methane production, a study in Germany [14] found that late variants of the crop had higher concentrations of ash and lignin but lower proportions of fat and protein compared to medium and early maize hybrids.

One way to lessen the demand for non-renewable resources is to employ sewage sludge in crop production. The impact of sewage sludge rates (0, 10, 20, 40, and 60 Mg ha⁻¹ dry matter (DM)) on the energy balance of plant biomass was investigated by Jankowski et al. [15]. In comparison to the control, the application of 10 Mg SS ha⁻¹ DM increased the dry matter yield by 36%, energy production by 43%, energy gain by 43%, and energy efficiency ratio by 25%.

One option for agricultural output diversification that has the potential to greatly boost farm profitability is growing and using energy crops for biogas production. By dispersing excess energy, biogas produced by the anaerobic digestion of energy crops can improve a farm’s energy balance. Silage made from maize generates high amounts of total solids (TS) (10–30 t/ha [16,17,18,19]), making it an ideal energy crop for biogas production. More than 17,000 biogas plants in Europe use mostly maize silage as their primary substrate. According to one example, by the end of 2015, there were over 8000 biogas plants operating in Germany, over 52% using plant biomass and 43% using livestock manure [20]. The remainder is made up of municipal biowaste as well as waste from industry, agriculture, and food processing. The fact that 52% of the total substrates processed in the biogas plants generated 79% of the energy highlights the advantages of using plant biomass. While energy makes up 72% of total energy output, maize silage makes up 73% of the plant biomass processed in biogas facilities. In Germany, 56.88 percent of the energy generated by biogas plants in 2014 came from maize silage [20]. It is clear that maize silage is the main substrate for biogas plants in other EU nations, even though precise data on the species makeup of these substrates are lacking.

In terms of anaerobic digestion, the essential benefit associated with ensiling is the conservation of plant substrates, which allows for biogas production throughout the entire year.

In a laboratory batching reactor, Zauner and Kuntzel observed the anaerobic digestion of maize silage, achieving a methane generation value of 0.270–0.289 m³ kg⁻¹ of TS [19,21].

Thus, the purpose of this study was to examine the impact of using digestates on the productivity of silage maize that has been considerably degraded. This study’s primary goal was to assess how the year, digestate, and location affected the amount of biomass, methane, plant height, and biogas produced from silage maize.

2. Materials and Methods

2.1. Field Trial

The three-factorial microtrial was designed according to a randomized block design with three replications over a period of three years (2016–2018) and in two localities: L1—Ilandža, Alibunar municipality (N 55°10′, E 20°55′, 59 als) and L2—Dolovo, Pancevo municipality (N 44°54′, E 20°52′, 110 als), South Backa District in Vojvodina, Serbia. The third factor was additional plant fertilization, using two variants: C—control, no digestate and AD—variant with digestate. The maize silage hybrid NS 6010 was sown at the optimum time, in the last ten days of April, with a sowing machine for wide-area crops. The area of the plots was 10 m². The previous crop was soybean. The crop density was 70,000 plants per ha. During the experiment, the usual technology for the genotypes was applied.

In the digestate variant of biogas production, digestate was introduced into the soil at an amount of 50 t ha⁻¹, just before the sowing of maize with digestate (AD). For both variants, 115 kg N ha⁻¹ (250 kg ha⁻¹, UREA-46% N) was added to the soil. Digestate was introduced before sowing in the second variant with fertilization in liquid form.

Mineral fertilizers were applied using basic treatment methods in October and the pre-sowing treatment was applied 2 days before sowing. Digestate was applied in liquid form immediately before sowing. The digestate is a product of the company Biogas energy, which is located near the experimental plots and owns 480 ha of arable land. Anaerobic digestion produces digestate, which passes through a separator, which separates solids from liquids. The liquid phase is a high-quality fertilizer that is immediately ready for use. Annually, 16,000 t of raw compost and 8000 t of processed organic compost are produced. The digestate was stored for seven months before application.

When the water content reached 35% DM (dry matter), maize was harvested at the start of the tassel phase (second half of August). From each plot, ten plants were randomly selected for assessing plant height (PH), biomass yield (BMY), biogas yield (BGY), and methane yield (MY). The maize biogas yield (BGY) from each elemental plot was also estimated and converted into m³ ha⁻¹.

For each year and locality, composite samples of maize silage were taken from all basic plots under each variety. All analyses were performed according to accredited methods [22,23,24,25,26,27]. By analyzing silage maize in the Faculty of Technology laboratory in Novi Sad using the VDI 4630 method, the biogas yield (BGY) was calculated and converted into N m³ t⁻¹ [28,29].

Ten plants were taken from each of the 6 plots (6 × 10), from both localities, just before harvest. The plants were pulled out of the ground by hand. Plant height was measured with a meter stick in the laboratory for morphological analysis and, after drying in a draft dryer, the biomass yield was measured on a scale, while the methane yield and biogas yield were determined in the laboratory of the Faculty of Technology in Novi Sad according to accredited methods. The maize was chopped by hand on the same day and placed in silos, then covered with foil, where it fermented for 40 days. After that, the silage was put in a fermenter to produce biogas.

2.2. Soil Conditions

The experimental fields, which were in Vojvodina, Serbia, contained the Chernozem type of soil. The digestate composition was determined by standard methods: organic matter was measured according to the Turin method [23,24], Corg was calculated from organic matter using a factor of 1.724 [22,23,24,25], as was the moisture content and dry matter [26]. Ntot content was estimated using the Kjeldal method, while the P₂O₅ and K₂O content was determined using the Egner–Riehm AL method [24]. Analyses were performed in the laboratory of the Institute of Soil Science, Belgrade.

The average values for the soil’s agrochemical characteristics are presented in Table 1. The values for humidity, pH, and EC are from 6.6 (L1—Ilanđža) to 7.30 (L2—Dolovo). According to the measurements, the content of total nitrogen varied from 3.4% (L1—Ilanđža) to 5.00% (L2—Dolovo), and the content of organic matter varied from 35.50% (L1—Ilanđža) to 42.60% (L2—Dolovo).

The composition of the digestate and its biochemical properties depend mainly on the biomass—inputs (feedstock)—and the type—configuration of the fermenter. The amount of organic matter is the essential indicator that describes the condition of soil amendment and relative rations of C/N, as well as the ratio of mineral and organic N content that determines the degree of humification [25,26].

The composition of the digestate that was utilized is described in Table 2. The dry matter and moisture content did not differ much between the tested years.

The amount of N, P, and K varied according to the manure (various ratios of pig and beef dung) and the raw material used to produce biogas (different ratios of maize, wheat, and sorghum). Using ADD- digestate, about 200 kg C ha⁻¹, 27 kg N ha⁻¹, 1.6 kg P ha⁻¹, and 9.8 kg K ha⁻¹ were introduced into the soil.

2.3. Meteorological Data

Vojvodina belongs to a climatic area characterized by changeable, unstable, and unforeseeable weather conditions, especially in terms of precipitation, both in quantity and schedule [4,27,28,29,30,31,32,33]. Due to the economic and nutritional importance of maize, monitoring and predicting its production characteristics have been investigated by many researchers [29,33,34]. These results are very important and useful both for agricultural producers and the agribusiness sector as a whole, as well as for agricultural policymakers [33,34]. The vegetation periods of the tested years have been different between themselves, and they also had differed in terms of the average perennial values, according to meteorological parameters.

The average multi-year temperature was 19.93 °C (Ilandza) and 19.75 °C (Dolovo) and the total precipitation was 371 mm (Ilandza) and 361 mm (Dolovo); Figure 1a,b. In the first year in L1—Ilandža, 2016, the average temperature was 19.05 °C; in the second year, it was 18.70 °C; and it was 19.18 °C in 2018. The total precipitation was 222.5 mm, 339.9 mm, and 324.3 mm; Figure 1a.

In the first year in L2—Dolovo, 2016, the average temperature was 18.73 °C; in the second year, it was 18.70 °C; and it was 19.40 °C in 2018. The total precipitation was 397.1 mm, 437.5, and 493.9 mm; Figure 1a,b.

2.4. Statistical Analyses

The statistical software STATISTICA 12 for Windows was used to evaluate the experiment’s outcomes using descriptive and analytical statistics. A three-factor model of variance analysis [35] was used to determine the significance of the differences between the computed mean values of the examined parameters (years, nutrition variant, and locality):

i = 1, 2 j = 1, 2 l = 1, 2, 3, 4 k = 3

The F-test and LSD test were used to calculate the significance levels at the 0.05% and 0.01% levels, respectively. Pearson’s correlation coefficients were used to quantify the relative dependency of the tested maize parameters, and the t-test was used to test the derived coefficients at the 0.05 and 0.01 percent significance levels, respectively.

3. Results

3.1. Plant Height of Maize

The Y × L interaction did not significantly affect the investigated parameter. The V × L interaction significantly affected the examined parameter. The highest values for plant height were achieved in the digestate variant V2, and were statistically substantially higher than the values obtained in the control variant V1, as shown in Table 3 and Figure 2. The mean maize plant height across all the analyzed factors, including the year, variant, and cultivation location, was 2.42 m, with a standard deviation of 0.27. The plant height ranged from 2.20 m (C) to 2.63 m (AD).

The digestate exhibited a statistically significant influence on the maize plant height. The digested variety resulted in plants that were 0.43 m bigger, or 19.55% larger (Table 3).

The location did not have a substantial influence on the plant height. The plant height ranged from 2.41 m (Ilandza) to 2.42 m (Dolovo).

The production year has no significant impact on the maize plant height. The parameters tested ranged from 2.48 m (2018) to 2.39 m (2016) to 2.37 m (2017). In 2018, the plant heights were 4.64% higher than the values for 2016; Table 3 and Table 4.

3.2. Biomass Yield

The interaction of the studied factors, Y × V, Y × L, and L × Y × V, had a statistically significant effect on the biomass yield; the standard deviation was 4.87, as shown in Table 3 and Table 5.

The average biomass yield for all tested factors, including the year, variant, and cultivation locality, was 47.68 t ha⁻¹ and the standard deviation was 4.874; Table 5.

The digestate showed a statistically significant impact on the biomass yield. The range of the biomass yield was 44.12 t ha⁻¹ (C) to 51.23 t ha⁻¹ (AD). In the variant with digestate, 7.11 t ha⁻¹ or 16.12% more biomass was obtained; Table 3 and Table 5.

The locality did not have a significant impact on the biomass yield. The production year had a statistically significant impact on the level of biomass yield. The biomass yields were 45.83 t ha⁻¹ (2017), 46.05 t ha⁻¹ (2016), and 51.15 t ha⁻¹ (2018).

The best year for biomass production was 2018. In 2018, the biomass yield was 58.78 t ha⁻¹ or 11.62% higher than that in 2017 and 5.1 t ha⁻¹ or 11.08% higher than that in 2016; Table 3 and Table 5 and Figure 3.

3.3. Biogas Yield

The interplay between the factors under study, Y × V, Y × L, L × V, and L × Y × V, indicated a statistically significant effect on the biogas yield; the standard deviation was 17.74, as shown in Table 3 and Table 6.

The average biogas yield for all the tested factors, including the year (Y), variant (V), and locality (L), was 205.83 m³ ha⁻¹, and the standard deviation was 17.74. The digestate had a statistically significant effect on the biogas yield; Table 6.

The biogas yield varied from 189.67 m³ ha⁻¹ (C) to 221.99 m³ ha⁻¹ (AD). In the variant with digestate, 32.32 m³ ha⁻¹ or 17.04% more biogas was obtained. The cultivation locality had a statistically significant effect on the biogas yield.

The biogas yield varied from 201.22 m³ ha⁻¹ (L2—Dolovo) to 210.44 m³ ha⁻¹ (L1—Ilandza). Locality L1 had higher biogas production by 9.22 m³ ha⁻¹ or 4.58% compared to that in L2; Table 6 and Figure 4.

The amount of biogas yield was statistically influenced by the production year. The biogas yields were 204.10 m³ ha⁻¹ (2017), 205.47 m³ ha⁻¹ (2018), and 207.93 m³ ha⁻¹ (2016). The best year for biogas production was 2016. In 2016, the biogas yield was 1.21% higher than that in 2017 and 1.21% higher than that in 2018; Table 3.

3.4. Methane Yield

The average methane yield for all years (Y), variants (V) and localities (L) was 248.41 m³ ha⁻¹, the standard error was 213.60, and the standard deviation 17.49; Table 3 and Table 7.

All the tested factors, including the year, variant (digestate), and locality, and the interaction of the studied factors, Y × V, Y × L, L × V, and L × Y × V had a statistically significant effect on the methane yield; Table 3 and Table 7.

The digestate exhibited a statistically significant impact on the methane yield. The methane yield varied from 236.18 m³ ha⁻¹ (C) to 260.64 m³ ha⁻¹ (AD). In the variant with digestate, 24.46 m³ ha⁻¹ or 10.36% more methane was obtained; Table 4 and Table 7.

The locality displayed a statistically significant effect on the methane yield. The methane yield varied from 246.79 m³ ha⁻¹ (L2—Dolovo) to 250.05 m³ ha⁻¹ (L1—Ilandza). Locality L1 had a higher biogas production by 3.24 m³ ha⁻¹ or 1.31% compared to that in L2; Table 4 and Figure 5.

The production year had a statistically significant influence on the level of biogas yield. The maize biogas yields were 236.90 m³ ha⁻¹ (2017), 250.13 m³ ha⁻¹ (2016), and 258.20 m³ ha⁻¹ (2018). The best year for biogas production was 2018. In 2018, the biogas yield was 21.30 m³ ha⁻¹ or 9.00% higher than that in 2017; Table 4.

The most favorable year for biogas production was 2016 (207.95 m³ ha⁻¹), while the highest values for the maize plant height, biomass, and methane yield were recorded in 2018 (2.48 m, 51.15 t ha⁻¹, and 258.25 m³ ha⁻¹).

3.5. Correlations of Factors Examined

The biogas yield displayed a positive correlation with the plant height, biomass, and methane yield (r = 0.78 *; r = 0.70 *; r = 0.76 *) and was positively nonsignificantly correlated with temperature (r = 0.07) and had a negative nonsignificant correlation with precipitation (r = 0.24); Table 8.

The identification of the relationship between various parameters is described in greater detail using correlation matrices (Figure 6). The maize plant height was positively associated with the biomass, biogas, and methane yield (r = 0.62 *; r = 0.78 *; r = 0.63 *) and positively nonsignificantly correlated with temperature and precipitation (r = 0.16 *; r = 0.18 *); Table 8 and Figure 6.

Table 8 shows that the biomass yield was positively nonsignificantly connected with temperature (r = 0.42) and precipitation (r = 0.12), and positively correlated with the plant height, biogas, and methane yield (r = 0.62 *; r = 0.70 *; r = 0.81 **).

4. Discussion

It is crucial to create appropriate crop cultivars that are renewable sources in order to achieve the highest methane production yield per hectare, especially in the twenty-first century, when the globe is struggling with rising energy demands and declining fossil resources [36]. Research aiming at assessing the energetic efficiency of technologies associated with biomass production for energy purposes must be carried out [37,38]. By managing the anaerobic digestion (AD) process to produce biogas precisely when energy is needed, biogas production has been positioned as a key strategy for attaining a demand-oriented biogas supply [39]. Simulating the impact of substrate feeding levels on the biogas production process is possible using anaerobic digestion [40,41,42].

Much work has been performed to enhance the production of biogas by anaerobic digestion (AD), which focuses on comprehending the related microbial processes to optimize reactor design, substrates, and environmental conditions [43,44,45]. Biogas plants facilitate flexible power generation, allowing fluctuating renewable energy sources to be integrated into the supply of the energy system [46,47,48]. When the electrical power balance is necessary, the biogas output can be controlled by altering the mass addition of the substrate, feeding schedules, or substrate types [49].

Lipids, proteins, and carbohydrates—the latter of which includes fibers like cellulose, hemicellulose, and lignin—are the main chemical components that define the substrates for biogas generation and influence gas yields and production rates [50].

Plant height: The plant height is a significant factor in determining the maize production capacity because of its effect on genotype and environmental interactions [51,52]. There was a significant difference (p < 0.01) in the plant height between years. There was a significant genotype x year interaction because the effect of the genotypes on the plant height differed across the years (Table 3). The plant height differences were caused by variations in cultivar responses to varied environmental conditions such as soil, temperature, humidity, and rainfall [52]. According to Hallauer and Miranda [53], variations in the plant height between maize cultivars can be explained by differences in genetic factors.

Maize yield: the maize yield is the most significant and complex trait for the genetic improvement of crops and its expression is influenced by a large number of components, where the contributions of every single component can vary depending on the environmental conditions [51].

Maize yield parameters including the plant height and biomass and grain yield are crucial parameters in managing fertilizer usage for sustainable agriculture with maize hybrids [51]. The cultivation of agro-energy crops on degraded or marginal soils using waste from the energetic conversion process allows for the long-term achievement of the SDGs.

The variation in yield was significant at the 0.01 level for the genotype, and at the 0.05 level between years. In addition to differences in the genetic materials employed, the ecological circumstances of the experimental sites—particularly the impact of climatic elements like temperature and precipitation—were responsible for the variances in maize yields [52]. The use of mineral fertilizers (27.1–33.0 g DM (dry matter) per plant) and digestate treatment (22.6–26.4 g DM per plant) resulted in the best yields of total aboveground biomass of maize compared to those from the unfertilized control (8.9 g dry matter per plant) [54]. China produced 19.98 ± 6.93 Mg ha⁻¹ of silage maize on average [55].

The 2017 and 2016 production years, which were unfavorable for maize production in terms of the amount and distribution of precipitation, had a lower biomass yield compared to that in 2018; Table 3.

Fabris et al. [56] point out that later maize sowing can result in a weaker plant structure, a less developed root system, and weaker absorption of nutrients, which, altogether, negatively affect the achievement of maximum yields.

Biogas production: During the 2016 production year, the biogas yield was higher compared to that in 2018 and 2017; Table 3. During the anaerobic digestion of maize grains, the maximum specific biogas generation was 0.72 m³ ha⁻¹ of volatile suspended solids (VSS) (nonacidified maize) at 35 °C and 0.770 m³ ha⁻¹ VSS (acidified maize). Maize silage’s low nitrogen content causes anaerobic digestion to be unstable. Anaerobic process stabilization can be achieved using alkali or complementing substrates with a greater amount of nitrogen (for example, surplus sludge from a wastewater treatment plant or manure). The highest specific biogas production from maize silage that was tested was 0.655 m³ kg⁻¹ VSS. Methane generation from dry maize silage can reach 9058 Nm³ ha⁻¹ at an average rate of 30 t ha⁻¹ [57,58].

Methane production: in the 2016 production year, the methane yield was higher in Ilandža than in the years 2017 and 2018, whereas in Dolovo, the greatest value was in 2018; Table 3.

Zauner and Küntzel [21] investigated the anaerobic breakdown of silage made from maize. They produced 0.270–0.289 m³ kg⁻¹ of ts of specific methane in batch laboratory reactors. The specific methane production was somewhat lower in a laboratory flow reactor, at 0.181–0.184 m³ kg⁻¹ of ts.

For the production of biogas, the SMY-specific methane yields a crucial metric that represents the quality of the agricultural biomass. There are no restrictions on the ensilability of different varieties of sorghum if the ultimate goal is biomethanation. Additionally, a variety of sorghum varieties have a broad harvest window, which can be advantageous for methane generation, ensiling, and cropping schemes [59].

The maize yields of methane varied between 342 and 354 LN kg⁻¹ OD. Both before and after ensiling, 344–381 LN kg⁻¹ ODM was added. The methane output was up to 10% higher when silage fermentation was altered [55].

At an average yield of 9 tha⁻¹ of dry maize, nonacidified maize can produce 5450 Nm³ ha⁻¹ of methane, while acidified maize grains can produce 5828 Nm³ ha⁻¹ of methane [59].

Climate change could impact arable farming, diminishing yields in maize belts at the same time [4,5,58]. For a stronger understanding of plant growth, the interaction between the genotype and the external environment becomes extremely important.

Over wide regional scales, environmental factors (such as temperature, precipitation, and sunshine hours) significantly alter the physiological processes and growth of fodder [60,61], which can have an impact on the yield and quality.

The forage yield and quality are influenced by temperature and precipitation [61]. The forage growth duration and growth rate were influenced by temperature [62,63,64,65,66,67,68]. The production and quality of silage maize may also be impacted by the soil nutrient content [69], the relationship between soil nutrients and fertilizer application quantity [69], and varieties and genotypes [58], in addition to climate conditions and management approaches.

The nitrogen use efficiency in maize (Zea mays L.) is a key feature for increasing production while using the least amount of nitrogen (N) fertilizer [70]. Permanent impacts of delayed nitrogen administration at the 6- and 10-leaf stages have been linked to yield losses of 12 and 17 percent, respectively [71].

The most popular substrate for producing biogas is maize silage. Because of its high yield per hectare and high specific biogas output, maize silage is a good choice for biogas generation [19].

Using maize silage, the maximum measured specific biogas production was 0.72 m³·kg⁻¹ of volatile suspended solids, or VSS. Nonacidified maize can produce 5450 Nm³·ha⁻¹ of methane at an average yield of 9 t·ha⁻¹ of the dry maize silage [57]. Previous studies have found that the stem diameter, wall thickness, and dry weight per unit length will all rise at low plant densities [67].

Maize hybrids produce various yields in different situations, and reorienting the production area may improve the overall maize productivity. Technology that provides yield levels close to the genetic potential should be adopted, making is easier to prevent expensive mistakes in production procedures [1,2,3]. Evaluating high-yielding genotypes for tolerance to changing environments is essential for long-term agricultural production [72,73,74,75]. The use of nutrition must be carefully researched given that its effects can differ [75]. In addition to reducing soil and pollution, a sustainable and climate-resilient agricultural output can be attained by integrating effective field management practices with fertilizer and irrigation [76].

According to Krzystek et al. [77], depending on the soil conditions, the lowest fertilization amount of 80 kg N ha⁻¹ produced high yields of biogas from maize silage, ranging from 194.5 to 315.33 m³ t⁻¹ of green mass (g.m.). According to the investigations, the most energy-efficient agricultural production technologies were generally those that applied minimal doses of nitrogen fertilizer. Despite the significantly varying nutrient contents between maize cultivars, there was no clear-cut relationship between the chemical composition and particular methane yield [78].

Two distinct plant densities (90,000 and 130,000 plants ha⁻¹) and their impacts on the yield and biogas generation were investigated by Fuksa et al. [79]. Compared to the biogas hectare production of stover (3943–4865 m³ ha⁻¹), the biogas hectare yield of ears (5039–8962 m³ ha⁻¹) was 1.3–1.8 times greater. A higher plant density promoted faster dynamics of specific biogas yield of ears in both years and higher volatile solids degradation of ears in 2014; however, the effect of the plant density on the dry matter yield and biogas hectare production was not statistically significant.

Correlations of the factors examined: Table 8 showed the considerable positive relationships between the examined parameters. A considerable positive connection between the various sorts of investigated parameters was clearly seen. Because they represented how the relatively constant soil microflora responded to the addition of readily degradable energy sources, all of the variations showed a positive correlation with one another. Although the dependency was clearly lower there, a positive association was found between substrate-induced respiration and basal soil respiration. This can be explained by how available nutrients and soil water content affect BR [80,81]. How digestate affects soil microbial activity depends on the kind and quality of the input biomass (silage).

The silage maize yield and quality characteristics are crucial factors [62,82] in assessing the production of biogas [28]. Compared to the control variety, the digestate-fertilized varieties exhibited significantly greater biomass production values (>0.57 g) [83].

5. Conclusions

Maize silage has become the most utilized substrate for biogas production in Serbia. The findings show that maize silage is a suitable substrate for the production of biogas and anaerobic digestion. The locality, digestate, and year showed a statistically significant impact on the maize biomass yield, methane, and biogas yield. The most favorable year for biogas production was 2016 (207.95 m³ ha⁻¹), while the highest values for the maize plant height, biomass, and methane yield were recorded in 2018 (2.48 m, 51.15 t ha⁻¹ dry matter and 258.25 m³ ha⁻¹). It is evident that every parameter that was examined showed a significant positive dependence. The biomass yield was positively correlated with the plant height, biogas, and methane yield and positively nonsignificantly correlated with temperature and precipitation. The digestate exerted a significant influence on the values of all the tested maize parameters in all three experimental years and is recommended as a desirable measure for increasing the profitability of biomass, biogas, and methane production.

According to this study’s findings, digested maize silage is a suitable substrate for anaerobic digestion and the production of biogas. High biogas yields per unit of processed material are produced by the anaerobic digestion of maize silage. Our findings support an improved understanding of the relationship between the plant height and silage maize biomass, methane, and biogas yield, as well as provide a basis for cost-effective maize silage exploitation as an animal feed and energy crop.

Author Contributions

Conceptualization, V.P., V.V. and N.L.; methodology, N.R.; software, V.P., V.V. and J.I.; validation, V.P., J.I. and N.L.; formal analysis, V.P. and N.L.; investigation, V.P.; resources, V.P.; data curation, V.P.; writing—original draft preparation, V.P., V.V., N.L. and N.R.; writing—review and editing, V.P., V.V., J.I. and N.R.; visualization, V.P.; supervision, V.P.; project administration, V.P. and N.L. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

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Figures and Tables

Figure 1. Average temperature (T, °C) (a) and total precipitation (P, mm) (b) in L1—Ilandza, and L2—Dolovo, Serbia, in the 2016 and 2018 growing seasons. Long-term T and P values from 1988 to 2018.

Figure 2. Interaction of variant, year, and locality of maize plant height, cm.

Figure 3. Interaction of variant, year, and locality of maize biomass yield, t ha−1.

Figure 4. Interaction of variant, year, and locality of maize biogas yield, m3 ha−1.

Figure 5. Interaction of variant, year, and locality of maize methane yield, m3 ha−1.

Figure 6. Correlations of tested maize productivity parameters.

Table 1

Chemical analysis of soil in tested localities.

Parameter	pH		TotalN *	Humus	Organic C *	C	P2O5	K2O
Locality	KCl	H2O	%			mg kg−1 N	mg 100 g−1 Soil
L1 *—Ilanđza	6.2	6.7	3.1	2.5	31.1	36.1	11.1	14.0
L2 *—Dolovo	6.7	7.3	5.0	3.9	38.1	43.0	21.0	24.1

* L1—Locality 1; L2—Locality 2; C—carbon; N—nitrogen.

Table 2

Characteristics of the used substrates.

Year	Moisture Content (%)	Dry Matter (%)	C org. * (%)	Ntot * (%)	PEgner *(g/kg)	KEgner *(g/kg)
2016	87.3	12.7	4.3	0.6	0.5	2.1
2017	87.7	12.3	4.1	0.5	0.2	1.9
2018	87.6	12.4	4.1	0.5	0.3	1.9
Average	87.6	12.5	4.2	0.5	0.3	2.0

* C—carbon; N_tot—total nitrogen; P—phosphorus; K—potassium.

Table 3

Descriptive statistics for maize productivity traits, average value and standard deviation, Ilandza and Dolovo, 2016–2018.

Variable	Plant Height, m			Biomass Yield, t ha−1			Biogas Yield, m3 ha−1			Methane Yield,m3 ha−1
Locality 1, L1—Ilandža
Year	C	D	$\overline{x}$	C	D	$\overline{x}$	C	D	$\overline{x}$	C	D	$\overline{x}$
2016	2.10 ± 0.20	2.67 ± 0.20	2.38 ± 0.37	44.60 ± 0.98	48.23 ± 0.30	46.61 ± 2.09	198.1 ± 2.53	225.3 ± 0.95	211.7 ± 15.0	251.6 ± 6.55	261.0 ± 1.00	256.3 ± 6.64
2017	2.17 ± 0.11	2.67 ± 0.15	2.42 ± 0.29	42.57 ± 0.72	47.50 ± 0.43	45.03 ± 2.75	198.7 ± 0.43	224.1 ± 3.55	211.4 ± 14.1	236.2 ± 1.50	249.3 ± 3.78	239.4 ± 11.16
2018	2.23 ± 0.20	2.60 ± 0.26	2.42 ± 0.29	44.97 ± 2.63	58.78 ± 1.30	51.87 ± 7.78	190.5 ± 9.43	226.0 ± 0.32	208.3 ± 20.3	240.4 ± 2.51	268.4 ± 2.94	254.4 ± 15.55
$\overline{x}$-average	2.17 ± 0.18	2.64 ± 0.19	2.41 ± 0.30	44.04 ± 1.83	51.50 ± 5.50	47.77 ± 5.52	195.7 ± 6.29	225.2 ± 2.02	210.4 ± 15.8	240.7 ± 10.5	259.6 ± 8.67	250.1 ± 13.45
Locality 2, L2—Dolovo
2016	2.23 ± 0.11	2.54 ± 0.05	2.39 ± 0.21	43.07 ± 1.10	48.30 ± 1.27	45.68 ± 3.05	186.5 ± 2.40	221.9 ± 1.66	204.2 ± 19.5	238.6 ± 2.81	249.3 ± 3.05	243.9 ± 6.45
2017	2.14 ± 0.15	2.55 ± 0.05	2.34 ± 0.48	44.03 ± 0.15	49.20 ± 0.26	46.62 ± 2.83	182.9 ± 5.06	210.3 ± 0.20	196.8 ± 15.5	219.7 ± 2.08	249.1 ± 1.01	234.4 ± 16.18
2018	2.32 ± 0.18	2.75 ± 0.06	2.53 ± 0.27	45.47 ± 0.42	55.40 ± 0.43	50.43 ± 5.45	181.4 ± 0.72	224.0 ± 1.10	202.7 ± 23.3	237.4 ± 2.52	286.7 ± 1.52	262.1 ± 27.07
$\overline{x}$-average	2.23 ± 0.17	2.62 ± 0.11	2.42 ± 0.25	44.19 ± 1.20	50.97 ± 3.41	47.58 ± 4.28	183.6 ± 3.61	218.8 ± 6.30	201.2 ± 18.8	231.9 ± 9.41	261.0 ± 18.8	246.8 ± 21.07
Variable	Plant Height			Biomass Yield			Biogas Yield			Methane Yield
LSD	0.05		0.01	0.05		0.01	0.05		0.01	0.05		0.01
Variant—V	0.101		0.165	0.609		0.997	2.726		4.458	1.702		2.783
Year—Y	0.123		0.175	0.748		1.123	2.430		3.973	2.084		3.408
Locality—L	0.101		0.165	0.609		0.997	2.726		4.458	1.702		2.783
Y × V	0.175		0.202	1.056		1.727	3.436		5.619	2.471		4.042
V × L	0.484		0.285	0.862		1.410	2.805		4.586	2.948		4.482
L × Y	0.175		0.202	1.056		1.727	3.436		5.619	2.948		4.042
Y × V × L	0.246		0.403	1.607		2.628	4.869		7.947	4.169		6.817

C—control; D—digestate; $\overline{x}$—average.

Table 4

Analysis of variance for plant height.

Effect	DF	SS	MS	F Test	p Sign.
Intercept	1	209.67	209.67	6738.20	0.000000
Variant—V	1	1.68	1.68	54.03	0.000000 **
Year—Y	2	0.07	0.04	1.11	0.346970 ns
Locality—L	1	0.01	0.02	0.07	0.793610 ns
Year × Variant	2	0.01	0.03	0.08	0.082173 ns
Variant × Locality	1	0.02	0.02	0.60	0.446040 ns
Year × Locality	2	0.06	0.03	0.91	0.417270 ns
Variant × Year × Locality	2	0.04	0.02	0.62	0.547690 ns
Error	24	0.75	0.03

DF—Degrees of Freedom; SS—Sum of square; MS—Middle of square; ^ns—nonsignificant; **—significant at 0.01.

Table 5

Analysis of variance for biomass yield.

Effect	DF	SS	MS	F	p
Intercept	1	81,824.61	81,824.61	71,549.34	0.000000
Variant—V	1	455.82	455.82	398.58	0.000000 **
Year—Y	2	217.68	108.02	95.17	0.000000 **
Locality—L	1	0.34	0.34	0.30	0.590450 ns
Year × Variant	2	102.10	51.05	44.64	0.000000 **
Variant × Locality	1	1.03	1.03	0.90	0.351230 ns
Year × Locality	2	14.96	7.48	6.54	0.005400 *
Year × Variant × Locality	2	12.14	6.07	5.31	0.012330 *
Error	24	27.75	1.14

DF—Degrees of Freedom; SS—Sum of square; MS—Middle of square; ^ns—nonsignificant; * and **—significant at 0.05 and 0.01.

Table 6

Analysis of variance for biogas yield.

Effect	DF	SS	MS	F	p
Intercept	1	152,522.13	152,522.13	126,095.24	0.000000
Variant—V	1	9403.28	9403.28	777.30	0.000000 **
Year—Y	2	90.10	45.07	3.70	0.000690 **
Locality—L	1	765.01	765.17	63.35	0.018760 *
Year × Variant	2	242.40	121.10	10.00	0.000996 *
Variant × Locality	1	77.13	77.16	6.40	0.018760 *
Year × Locality	2	136.10	68.17	5.60	0.009960 *
Year × Variant × Locality	2	15.50	7.10	0.60	0.550030 ns
Error	24	290.16	12.10

DF—Degrees of Freedom; SS—Sum of square; MS—Middle of square; ^ns—nonsignificant; * and **—significant at 0.05 and 0.01.

Table 7

Analysis of variance for methane yield.

Effect	DF	SS	MS	F	p
Intercept	1	2,221,426.30	2,221,426.30	249,547.44	0.000000
Variant—V	1	5385.85	5385.85	605.03	0.000000 **
Year—Y	2	2773.70	1386.87	155.80	0.000000 **
Locality—L	1	95.00	94.77	10.65	0.003297 *
Year × Variant	2	1226.40	613.18	68.90	0.000000 **
Variant × Locality	1	259.30	259.26	29.12	0.000015 *
Year × Locality	2	612.11	306.07	34.40	0.000000 **
Year × Variant × Locality	2	150.60	75.20	8.46	0.001659 *
Error	24	213.6	8.90

DF—Degrees of Freedom; SS—Sum of square; MS—Middle of square; *—significant at 0.05; **—significant at 0.01.

Table 8

Correlations of examined factors.

Variable	Plant Height	Biomass Yield	Biogas Yield	Methane Yield	Precipitation	Temperature
Plant height	-	0.62 *	0.78 *	0.63 *	0.16 ns	0.18 ns
Biogas yield	0.78 *	0.70 *	-	0.76 *	−0.24 ns	0.07 ns
Biomass yield	0.62 *	-	0.70 *	0.81 **	0.12 ns	0.42 *
Methane yield	0.63 *	0.81 **	0.76 *	-	−0.06 ns	0.55 *

^ns—nonsignificant; * and **—significant at 0.05 and 0.01.

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