1. Introduction
Chemical fertilizers improve soil fertility and crop yields, but their excessive use can lead to global warming, decline in soil organic matter and soil quality, eutrophication in estuaries and contamination of other water bodies through leaching and runoff [
1,
2,
3]. Unlike chemical fertilizers, organic amendments may offer other benefits including improved soil fertility by stimulating nutrient cycle mechanisms through mineralization of nitrogen and phosphorus [
4,
5,
6]. In addition, organic amendments can help in the formation and stabilization of soil aggregates, carbon sequestration, improved microbial population, enzyme activity and improved functioning of the agroecosystem [
6,
7,
8]. These benefits enable longer-term soil health and sustainable agricultural practices, which in turn support increased soil fertility and improved crop yields [
6]. According to Diacono and Montemurro [
9], soil fertility may be defined as the capacity of the soil to provide physical, chemical, and biological needs for the growth of plants for productivity, reproduction, and quality, which depends on the plant and soil type, land use and climatic conditions.
Nitrogen mineralization is a process that involves transformation (organic matter breakdown by microorganisms) of organic nitrogen into inorganic forms (ammonium (NH
4+) and nitrate (NO
3-) ions) that are easily absorbed by plants and is therefore essential for soil fertility and plant growth [
10,
11]. The transformation or breakdown of organic nitrogen compounds such as amino acids and proteins into NH
4+ is called ammonification - the first step of the N mineralization process. The second step is called nitrification - a process where NH
4+ is oxidized to nitrite (NO
2-) by Nitrosomonas bacteria, and then further oxidized to NO
3- by Nitrobacter bacteria [
10]. The quality and quantity of organic residues (especially their carbon-to-nitrogen ratio) retained or applied in the field as mulch [
12] determines the N mineralization rate of any given soil [
10,
13]. Generally, the rate of nitrogen mineralization for any organic material is governed by many soil factors such as moisture [
10,
14,
15], texture and structure [
10], microbial activity [
16,
17], soil temperature [
1,
14], soil pH [
10], C-to-N ratio [
10,
17,
18], lignin-to-N ratio and Polyphenols-to-N ratio [
10,
18].
The examination of nitrogen (N) release capacity from organic materials is of utmost importance in the quantification of N supply capacity and fertilizer values of organic amendments [
8]. The use of algae biomass as a biofertilizer has been recommended as an efficient technique to increase crop growth parameters and total yields of many plants due to its high nutrient content, especially N [
19,
20]. Algae biomass is a nutrient-dense soil conditioner that has the potential to increase soil microbial population and enzyme activity, which elevates inorganic forms of nitrogen levels in the soil such as ammonium and nitrate through mineralization [
21]. Mgolozeli et al [
22], reported that algae residues have the capacity to increase water absorption and water-holding capacity while improving nutrient status and electrical conductivity of agri-mats, making them more beneficial not only as the runoff combating technology but as a soil conditioner. Agri-mats are novel and innovative mulching materials that can increase soil organic matter content [
23] and improve crop biomass yields [
24]. Agri-mats are solid organic mulch mats derived from agricultural waste other organic waste materials such as grass, weed biomass, municipal sewage sludge, algae residues, bagasse, and forestry waste, created by hot or cold pressing biomass into soil mats. These environmentally friendly mulches serve as effective ground cover while releasing nutrients into the soil. Agri-mats provide remarkable benefits including conserving soil and moisture, regulating temperature, improving soil structure and microbial activity, enhancing fertility, and increasing crop productivity - especially in drier regions. They suppress weeds, reducing herbicide needs and costs. As biodegradable materials, agri-mats decompose over time into a valuable soil organic matter source without hazardous residues, and can eliminate or significantly cut costs for weeding compared to compost. Their utilization recycles agricultural and forestry wastes, aligning with conservation agriculture and land rehabilitation principles [
22,
23,
24].
Although the mineralization rate of algae and many other organic residues have been studies by several authors [
4,
8,
19,
20], research on nitrogen mineralization rate of agri-mats is scanty. Moreover, in South Africa and the world at large, there is a paucity of information on the combined effects of agri-mats and inorganic nitrogen fertilizer on soil fertility and crop growth under different soil textural classes.
Soil texture and particle size of organic amendments have direct influence on N mineralization, with finer organic particle sizes resulting in more rapid N release than the larger or coarser particles [
10,
18]. On the other hand, N mineralization rates are often lower in fine textured (clay) soils compared to coarse-textured soils [
25,
26]. Generally, soil particle size (texture) has a major influence on soil carbon and nitrogen dynamics [
27]. The practice of applying organic amendments such as grass, algal biomass, crop and/or forestry residues etc. in soil could play a significant role in improving not only soil fertility but overall soil health and crop productivity [
10,
18,
19,
28,
29]. According to Shahid and Al-Shankiti [
19], organic amendments increase the efficiency of inorganic fertilizers through positive interactions on soil biological, chemical, and physical properties. The objectives of current study were, i) To investigate nitrogen mineralization rate of selected organic residues (ground agri-mats, dry micro-algal residues, and grass mulch) and their combined effects with lime-ammonium nitrate, 2) To investigate the combined effect of selected organic residues with lime-ammonium nitrate on growth and biomass yield of spinach (
Spinacia oleracea L.) in loamy sand and loam soils. Spinach was chosen as a test crop because it is a staple food in South Africa along with maize and is more suitable for pot experiments than maize.
4. Materials and Methods
4.1. Incubation Study
A 2-month incubation study was conducted to investigate nitrogen mineralization of organic-inorganic and organic amendments alone under two contrasting soil types, in a laboratory at Agricultural Research Council – Natural Resources & Engineering campus in Pretoria, Gauteng, South Africa. The current study adopted and modified the methods described by Abbasi and Khaliq [
8] and Shahbaz et al [
35]. Briefly, soil samples were collected from two different agro-ecological zones (Durban, which represents Humid and Pretoria, which represents Semi-arid region) in November 2018 at a depth of 0 – 0.15 m, using a spade. The detailed textural analyses and physico-chemical properties of the soils from each site are shown in
Table 1 and
Table 2, respectively. The soils were air-dried by spreading samples on the floor of a well-ventilated room for a week to minimize changes caused by microbial and chemical reactions [
11,
41] and passed through a 2-mm sieve. A 100 g sample of soil was transferred into 250 mL transparent plastic containers with perforated lids (to allow gaseous exchange) and treated with required quantities of dry algae (DA), ground agri-mat (GA), ground grass (GG), and combined with LAN as a nitrogen fertilizer (NF). The scientific name of the grass used is
Megathyrus maximus, commonly known as Guinea grass. The algae residue used was green algae (
Chlorophyta) which was collected from a wastewater treatment plant in Durban after oil extraction.
Table 1.
Soil textural analyses of the sandy loam and loam soils.
Table 1.
Soil textural analyses of the sandy loam and loam soils.
|
Sand |
Silt |
Clay |
Sampling site |
Very Coarse (mm) 2–1 |
Coarse (mm) 1–0.5 |
Medium (mm) 0.5–0.25 |
Fine (mm) 0.25–0.1 |
Very fine (mm) 0.1–0.05 |
Coarse (mm) 0.05–0.02 |
Fine (mm) 0.02–0.002 |
Clay (mm) < 0.002 |
Sandy loam |
4.00% |
2.00% |
17.20% |
37.50% |
15.60% |
5.60% |
8.70% |
9.40% |
Loam |
3.90% |
3.00% |
9.70% |
10.20% |
11.00% |
12.00% |
25.90% |
24.30% |
Table 2.
Physico-chemical properties of loam and sandy loam soil sampled at the top 15 cm depth.
Table 2.
Physico-chemical properties of loam and sandy loam soil sampled at the top 15 cm depth.
Soil Properties |
Pretoria |
Durban |
Physical characterization |
|
|
Textural class |
Sandy loam |
Loam |
Clay % |
9.30% |
24.30% |
Chemical characterization |
|
|
pH in H20 (1:2.5) |
6.20 |
6.50 |
Available P (mg/kg) |
3.11 |
19.97 |
Total N (%) |
0.064 |
0.20 |
Total C (%) |
0.59 |
2.30 |
C:N ratio |
9.22 |
11.50 |
Exchangeable bases |
|
|
Ca (meq/100 g) |
220.00 |
436.00 |
Mg (meq/100 g) |
156.70 |
301.00 |
K (meq/100 g) |
73.40 |
212.70 |
Na (meq/100 g) |
74.00 |
84.40 |
CEC (meq/100 g) |
12.00 |
46.00 |
The application rates were calculated to provide an estimated amount of 150 kgN·ha-1. For example, assuming a bulk density of 1200 kg·m-3 for both soil types and using a soil sampling depth of 0.15 m, the 5 grams of algae (with 6.8%N) was equivalent to applying 340 mg of nitrogen per kilogram of soil. Similarly, the ground grass (with 0.56%N) and ground agri-mat (0.25%N) were calculated accordingly to achieve the 340 mg of nitrogen per kilogram soil or 150kgN·ha-1. Thus, 2.5 grams of dried algae, 61 grams of ground grass and 136 grams of ground agri-mat were applied per kilogram of soil to achieve 150 kgN·ha-1, respectively. Finally, the 50% treatment was calculated by dividing each organic material or compound fertilizer by two. Thus, the following treatment were achieved.
T1 = control, (no amendments)
T2 = 5 g of dry algae per kg of soil (100% DA),
T3 = 136 g of ground agri-mat per kg of soil (100% GA),
T4 = 61 g of ground grass per kg of soil (100% GG),
T5 = 2.5 g of N using Lime Ammonium Nitrate (LAN) + 2.5 g of dry algae per kg of soil (50% DA50NF),
T6 = 50% GA50NF
T7 = 50% GG50NF
Phosphorus and potassium were applied to the treatments at a rate of 90 mg P2O5 kg−1 and 45 mg KCL kg-1 soil in the form of superphosphate and potash, respectively. After treatment application, the soil in all the units was irrigated with deionized water to 80% field capacity instantly, and every third day thereafter. Three samples were drawn per treatment at 0, 3, 7, 15, 30, 45, and 60 days for mineral N (nitrate and ammonium) content determination. Therefore, the incubation study consisted of seven treatments, seven sampling dates (at day 0, 3, 7, 15, 30, 45, and 60), and three replications per sampling date, to make 147 experimental units (250 mL plastic containers) per sampling site at the beginning of the experiment.
The experiment was laid out in a complete randomized design in an incubator set at 25 °C for 60 days (8 weeks). Soil water content was monitored throughout the incubation days according to Abbasi and Khaliq (2016) as follows; every second day the soil moisture content was checked and was adjusted back to 80% field capacity by weighing the mass of each plastic container when the water loss was greater than 0.05 g. The deficit was added using deionized water to maintain the initial soil moisture content. During this process, precautionary measures were taken to avoid soil disturbance, through either stirring or shaking. Nitrate and ammonium were determined using a method described by Mulbry et al [
15]. Briefly, a 10 g sample was extracted with 100 mL 2 M KCL on a rotary shaker for 30 minutes. Extracts were filtered using a 0.45 µm membrane and the pH of the filtrates was adjusted to 3-5 with H
2SO
4 as needed for preservation. Filtrates were stored frozen until further analysis. Ammonium and nitrate were determined calorimetrically by flow injection analysis (Lachat Instruments, Milwaukee, WI).
4.2. Glasshouse Experiment
The glasshouse experiment was conducted for two months (8 weeks) at Agricultural Research Council – Vegetable and Ornamental Plants Institute in Roodeplaat, 35 km North-East of Central Pretoria, to determine the effect of organic-inorganic amendments on spinach growth and biomass yield. Soil was collected from each site, during the same time as incubation study and transferred into plastic pots. The length of the glasshouse experiment was informed by the results obtained in the incubation study as well as the test crop (spinach grown in pots). The pots had a height of 25 cm, top diameter and bottom diameter of 20 cm and 15 cm, respectively. Each pot was treated with required quantities of dried algae (DA), ground agri-mat (GA), ground grass (GG), and nitrogen fertilizer (NF) using the following treatments for each soil type;
T1 = control,
T2 = 2.5 g of dry algae (DA) per kg of soil + 75 kgN·ha-1 using LAN (50% DA),
T3 = 68 g of ground agri-mat (GA) per kg of soil + 75 kgN·ha-1 using LAN (50% GA),
T4 = 30.5 g of ground grass (GG) per kilogram of soil + 75 kgN·ha-1 using LAN (50% GG),
T5 = 150 kgN·ha-1 using LAN (100NF).
The five treatments shown above were selected based on the results observed in the incubation study, which indicated that the combination of organic and inorganic amendments may lead to the release of ammonium and nitrate. The sole application treatment of organic materials did not lead to mineralization after two months of incubation (
Figure 1,
Figure 2,
Figure 3 and
Figure 4), hence the singular treatments of organic amendments were omitted for the 2-month glasshouse experiment. Each treatment was replicated three times in a complete randomized design. Therefore, 15 pots per site (soil type) were established to make a total of 30 experimental units (pots).
Table 2. shows the initial characterization of the three organic materials used.
Spinach (Spinacia oleracea L.) (cultivar - Fordhook Giant) was used instead of maize as the test crop for the glasshouse experiment due to the limited space for root growth in pot experiments. Three spinach seeds were planted per pot and all the pots were irrigated immediately after planting and soil moisture was monitored afterwards. The pots were weighed to determine the deficit and distilled water was used irrigate the soil to 80% of field capacity every third day. In each case, seedlings were thinned to one seedling per pot two weeks after sowing. Weeds were removed manually every other week while pesticides were not applied due to no signs of pests and diseases throughout the experiment. The temperature in the glasshouse was regulated between 28 and 25 °C for day and night, respectively. Growth parameters (plant height, leaf length and number of leaves) were measured and recorded at every two weeks until harvest on the eighth week.
4.3. Statistical Analysis
Analysis of variance (ANOVA) was carried out to test the effects of spinach development and yield parameters using JMP 14.0 statistical software (SAS Institute, Inc., Cary, NC, USA). The mean comparison was performed using the least significant difference test (LSD) at α = 0.05.
Author Contributions
Conceptualization, S.M., A.N. and I.W.; methodology, S.M., A.N. and I.W.; software, S.M.; validation, A.N. and I.W.; formal analysis, A.N., F.M. and I.W.; investigation, S.M., A.N. and I.W.; resources, F.M., A.N. and I.W.; data curation, S.M., A.N. and I.W.; writing—original draft preparation, S.N.; writing—review and editing, S.M., A.N. and I.W.; visualization, A.N.; supervision, S.M., A.N. and I.W.; project administration, F.N.; funding acquisition, F.M., A.N. and I.W. All authors have read and agreed to the published version of the manuscript.
Figure 1.
Ammonium dynamics in a sandy loam soil from Pretoria, Gauteng. Means with the same letter within the same day indicates there were no significant (P < 0.05) differences between treatment means. The statistical differences were detected using LSD test at 0.05 confidence level, n = 42.
Figure 1.
Ammonium dynamics in a sandy loam soil from Pretoria, Gauteng. Means with the same letter within the same day indicates there were no significant (P < 0.05) differences between treatment means. The statistical differences were detected using LSD test at 0.05 confidence level, n = 42.
Figure 2.
Nitrate dynamics in a sandy loam soil from Pretoria, Gauteng. Means with the same letter within the same day indicates there were no significant (P < 0.05) differences between treatment means. The statistical differences were detected using LSD test at 0.05 confidence level, n = 42.
Figure 2.
Nitrate dynamics in a sandy loam soil from Pretoria, Gauteng. Means with the same letter within the same day indicates there were no significant (P < 0.05) differences between treatment means. The statistical differences were detected using LSD test at 0.05 confidence level, n = 42.
Figure 3.
Ammonium dynamics in a loam soil from Durban, Kwa-Zulu Natal. Means with the same letter within the same day indicates there were no significant (P < 0.05) differences between treatment means. The statistical differences were detected using LSD test at 0.05 confidence level, n = 42.
Figure 3.
Ammonium dynamics in a loam soil from Durban, Kwa-Zulu Natal. Means with the same letter within the same day indicates there were no significant (P < 0.05) differences between treatment means. The statistical differences were detected using LSD test at 0.05 confidence level, n = 42.
Figure 4.
Nitrate dynamics in a loam soil from Durban, Kwa-Zulu Natal. Means with the same letter within the same day indicates there were no significant (P < 0.05) differences between treatment means. The statistical differences were detected using LSD test at 0.05 confidence level, n = 42.
Figure 4.
Nitrate dynamics in a loam soil from Durban, Kwa-Zulu Natal. Means with the same letter within the same day indicates there were no significant (P < 0.05) differences between treatment means. The statistical differences were detected using LSD test at 0.05 confidence level, n = 42.
Figure 5.
Effect of various integrated nutrient management in spinach growth planted in loam and sandy loam soil.
Figure 5.
Effect of various integrated nutrient management in spinach growth planted in loam and sandy loam soil.
Figure 6.
Effect of organic-inorganic amendments on sandy loam (a) and loam soil (b) on spinach height. WAP = weeks after planting. Means with the same letter within the same measuring period are not significantly (P < 0.05) different from each other. The statistical differences were detected using LSD test at 0.05 confidence level, n = 30.
Figure 6.
Effect of organic-inorganic amendments on sandy loam (a) and loam soil (b) on spinach height. WAP = weeks after planting. Means with the same letter within the same measuring period are not significantly (P < 0.05) different from each other. The statistical differences were detected using LSD test at 0.05 confidence level, n = 30.
Figure 7.
Effect of organic-inorganic amendments on spinach leaf length planted under sandy loam and loam soil. WAP = weeks after planting, Pta = Pretoria sandy loam soil, Dbn = Durban loam soil. Means with the same letter within the same measuring time are not significantly (P < 0.05) different from each other. The statistical differences were detected using LSD test at 0.05 confidence level, n = 30.
Figure 7.
Effect of organic-inorganic amendments on spinach leaf length planted under sandy loam and loam soil. WAP = weeks after planting, Pta = Pretoria sandy loam soil, Dbn = Durban loam soil. Means with the same letter within the same measuring time are not significantly (P < 0.05) different from each other. The statistical differences were detected using LSD test at 0.05 confidence level, n = 30.
Figure 8.
Effect of organic-inorganic amendments on the number of leaves for Spinach planted under sandy loam soil. WAP = weeks after planting Means with the same letter within the same measuring time are not significantly (P < 0.05) different from each other. The statistical differences were detected using LSD test at 0.05 confidence level, n = 30.
Figure 8.
Effect of organic-inorganic amendments on the number of leaves for Spinach planted under sandy loam soil. WAP = weeks after planting Means with the same letter within the same measuring time are not significantly (P < 0.05) different from each other. The statistical differences were detected using LSD test at 0.05 confidence level, n = 30.