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Saudi Journal of Biological Sciences logoLink to Saudi Journal of Biological Sciences
. 2024 Mar 12;31(5):103978. doi: 10.1016/j.sjbs.2024.103978

Assessment of soil microbial diversity and soil enzyme activities under inorganic input sources on maize and rice ecosystems

M Jeya Bharathi a,⁎, Mariyappillai Anbarasu b, R Ragu c, E Subramanian d
PMCID: PMC10973183  PMID: 38549841

Abstract

Background

To increase crop productivity, modern agricultural practices comprises fertilizers, algaecides, herbicides and fungicides.

Objective

The purpose of this study was to evaluate the effects of soil microbial population and soil enzyme activity by the use of fertilizer in maize and inorganic input in the rice ecosystem.

Methods

A field experiment (2021 to 2023) was carried out using synthetic fertilizer doses with maize crops followed by rice crops using inorganic inputs. Soil microbial population and enzyme activities were examined.

Results

Maize field experiment revealed that the plots treated with 75 % Standardized Dose of Fertilizer (SDF) of NPK had the highest populations of diazotrophs (124 × 105cfu / g), Phosphobacteria (66.33 × 105cfu / g), and Azospirillum (0.409 × 105 MPN / g) than 100 % and 150 % SDF of NPK. The soil enzyme activity was higher in the unfertilized control plot than fertilized plot. These experimental results revealed that a low amount of fertilizer and no fertilizers favour the growth of soil microorganisms and soil enzyme activities, respectively. Followed by the rice field experiment, revealed that the soil microbial population was decreased by the application of inorganic inputs viz., fertilizer, algaecide, herbicide and fungicide. However, the maximum soil microbial population was found in algaecide application followed by herbicide and fungicide.

Conclusion

The field experiment concluded that soil microbial population and enzyme activity were affected by inorganic amendments. Less inorganic fertilizers and no fertilizers improve soil microbial activities and soil enzyme activities.

Keywords: Fertilizer, Algaecide, Herbicide, Fungicide, Microbial population, Soil enzyme activities

1. Introduction

Extended application of inorganic fertilizers produces a negative impact on the soil biota and reduces the variety of microorganism species, which facilitates the emergence of niches for the colonization of pathogenic organisms. In addition to providing plants with a variety of available and necessary compounds, soil microorganisms are essential for the cycling of nitrogen. The quantity and activity of microorganisms have dramatically decreased since the development of agricultural science and the spray of pesticides, fungicides, fertilizers, and herbicides, leading to subpar plants and crop yields. Therefore, research on the activity of soil microorganisms is concentrated as agricultural activities become more intense. The purpose of fertilizers, particularly synthetic ones, is to boost crop yield. Over application of inorganic fertilizers can cause water contamination, soil acidification, ammonia volatilization, denitrification, air pollution, and agricultural product quality degradation (Zhang et al., 2013).

Variability in soil microbial communities may result from improper farming methods such as overusing chemical fertilizers and pesticides and frequent land use changes, which can have a substantial impact on soil fertility and productivity (Onet et al., 2016). On the other hand, organic farming with the use of environmentally friendly organic fertilizers (such as compost, manure, and microbial fertilizers (Aurelia onet et al., 2019) can be a good substitute and help lessen the negative effects of synthetic fertilizer pollution on the environment. Wen et al., 2015 reported that Fusarium oxysporum f. sp. cubense population was varied in the flooded and organic amendment soil. Luo et al., (2015) reported that monocultures maintained for extended periods without the addition of organic fertilizers or crop rotation, long-term mineral fertilizer applications cause a considerable loss in soil organic matter. It has also been discovered that mineral fertilization reduces the porosity and nutrient availability of the soil (Song et al., 2015). Furthermore, the quantity of microorganisms and the qualitative selection of entire communities of soil microorganisms are both significantly impacted by mineral fertilization. By reducing internal biological cycles and pest control, the use of synthetic fertilizers and herbicides alters interactions within and between below- and above-ground components of the soil microbial community, ultimately increasing the negative environmental impacts of agriculture (Lucian Constantin Dincă et al., 2022).

Applying herbicides to soil microorganisms can inhibit, activate, or have no effect at all. Bezuglova et al. (2019) showed that foliar application of sulfonylurea herbicide decreased the abundance of bacteria, especially for the quickly growing ones on winter wheat soil. Jie chen et al. (2021) reported that sterane first decreased soil bacterial diversity and abundance in maize fields 10 days after sowing but increased them 60 days after application. Herbicides changed the population and diversity of the cultivatable soil bacteria, actinomycetes, and fungi, according to research done by Borowik et al. (2017) after applying a mixture of herbicide consisting of terbuthylazine, S-metolachlor, and mesotrioneto pot culture maize soil (Bezug et al., 2017). According to Borowik (2017), the spray of sulfonylurea herbicide on winter wheat soil caused stress on the soil, which in turn affected the plants and soil bacteria. Herbicides may affect the soil microbial diversity by changing the plant root growth and root exudates secretion since it is well known that plant root exudates regulate the soil microbial community.

The growth of microbial groups involved in the transformation or breakdown of the pesticide may change the structure of the microbial community, while the decline of sensitive groups may occur. Pesticide introduction into the soil environment can initiate mechanisms that promote, inhibit, or suppress soil microbial activity. Certain pesticides can inhibit or even eradicate specific microbial populations, while other pesticides promote the growth of specific soil microorganism populations. The capacity of microorganisms to break down crop protection products or alter the microbial community composition is responsible for those alterations. The bioavailability of insecticides is one of the key factors that determine how they affect microbes that live in soil. According to Mehjin (2019), insecticide reduced the number of bacteria in all pesticide types and throughout all incubation times. According to Mehjin, the application of Glyset (Glyphosate 48 %) at 50 ppm, 100 ppm, and 200 ppm reduced the number of bacteria by 4 %, 11 %, and 13 %, respectively, during the first 7 days of incubation.

In contrast, the number of bacteria reduced by 6 %, 9 %, and 9 %, respectively, at the seventh week of incubation. Even at 100 and 200 ppm, this depression was noteworthy. These findings support the findings of (Newman et al., 2016), which found that glyphosate reduced the population of acid bacteria, microbial biomass, and total number of bacteria. They thought that a protracted decline in the bacteria population might weaken some of the biogeochemical reactions that these microbes were able to carry out.

With this background, the research was focused on finding the impact of inorganic input sources on soil microbial and enzyme activities.

2. Materials and methods

2.1. Field experiment with maize and rice

Maize and rice field experiments were carried out at the Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai. The maize field experiment's specifics were as follows: Blocks with Randomized Designs Create, Season: 2021 Kharif; Crop: Maize (COMH 1) Five treatments total; three replications; Seeding date: 10.08.2021; Harvest date: 20.11.2022. Dosage of fertilizer: 150: 75:75 kg NPK/ha as Urea, Single Super Phosphate, and Muriate of potash. The following are the specifics of the treatment. T1: Unfertilized and uninoculated control, T2: 75 % of NPK SDF; T3: 100 % of NPK SDF; T4: 150 % of NPK SDF; and T5: 100 % SDF of NPK (Water soluble fertilizers).

The same field followed rice experiment specifics as follows: Blocks with Randomized Block design Season: 2022–2023 Kharif; Crop: Rice (ADT 43); Ten treatments; three replications. DOT: 25.11.2022; Harvest date: 05.03.2023. The rate of fertilizer application was 150:50:50 kg NPK/ha. N was applied in two top dressings of 25 % each during the active tillering and panicle initiation stages, with 50 % acting as the basal dressing. The experimental plot was set up to be 3 × 4 m with 2 seedlings per hill. The following are the specifics of the treatment. T1: Sodium bispyriphos, T2: Almix, T3: Pyrosulfuran T4: Londox power, T5: CuSO4, T6: CaO, T7: CuSO4 + CaO, T8: Butachlor, T9: Propiconaole, T10: Hexaconazole and T11 - Control.

Rhizosphere soil samples (3 replications) were collected from the test crops (maize and rice) fields for analyzing soil microbial diversity and enzyme activity. Collected soil samples were kept 5°C in a BOD incubator.

2.2. Specifics of the microbial diversity and soil enzyme observations

Maize rhizosphere soil samples were collected and analyzed to count Phosphobacteria (Srinivasan et al., 2012), diazotrophs (Rashedul Islam et al., 2010), and Azospirillum (Bashan and Levanony, 1985). Four soil enzymes were measured for their activities: dehydrogenase (Małachowska-Jutsz and Matyja, 2019), acid phosphatase (Margalef et al., 2017), alkaline phosphatase (Margalef et al., 2017), urease (Tabatabai and Bremner, 1972) and nitrogenase (Payá-Tormo et al., 2022).

A 50 g rhizosphere soil sample was taken from a rice field at 30, 60, and 90 days after transplanting (DAT) to count actinomycetes (Malcolm et al., 2018), fungi (Ameh and Kawo, 2017), and bacteria (Ameh and Kawo, 2017). The survival of Azospirillum (Bashan and Levanony, 1985) and Phosphobacteria (Srinivasan et al., 2012) in the rhizosphere of ADT 43 was estimated as per the reference cited. Pseudomonas population was estimated by following the procedure given by Amelie Deredjian et al., 2014.

3. Result

3.1. Chemical fertilizers on the survival of soil microorganisms and the soil enzymes activity in a maize field

Utilizing 75 %, 100 %, and 150 % recommended doses of NPK fertilizer, we examined the effects of synthetic fertilizer input sources on the populations of total diazotrophs, Azospirillum, and Phosphobacteria in the rhizosphere of maize (COMH 1) as well as soil enzymatic activities, including urease, dehydrogenase, acid phosphatase, and alkaline phosphatase.

3.1.1. Chemical fertilizers on the population of Phosphobacteria, Azospirillum, and total Diazotrophs in the Maize rhizosphere (COMH 1)

The experiment result revealed that compared with a higher dose of 150 % SDF of NPK treated plot 75 % SDF of NPK recorded, maximum rhizosphere microbial population viz., total diazotrophs (124.33 × 105cfu/g), Azospirillum (0.409 × 105 MPN/g), and Phosphobacteria (66.33 × 105cfu/g). Whereas, 150 % SDF of NPK treated plot recorded, less microbial population viz., diazotrophs (31 × 105cfu/g), Azospirillum (0.299 × 105 MPN/g), and Phosphobacteria (39 × 105cfu/g) than 100 and 75 % SDF of NPK (Table 1, Table 2, Table 3). To a certain extent, the usage of chemical pesticides and fertilizers serves a purpose because of their capacity to release nutrients quickly and promote faster and more effective plant growth (Sneha et al., 2018). However, frequent application of chemical fertilizers causes the soil's fertility to gradually decline and its quality to deteriorate. This can also result in the build-up of heavy metals in plant tissue, which can impact the yield's nutritional value and edibility (Farnia and Hasanpoor, 2015).

Table 1.

Chemical fertilizer on the survival of Azospirillum in the rhizosphere of soil planted with maize (COMH 1).

Azospirillum population (×105MPN/g)
Treatments Vegetative growth stage
 Flowering stage
 Harvesting stage
14 DAS 21 DAS 28 DAS Mean 42 DAS 49 DAS 56 DAS Mean 70 DAS 77 DAS 85 DAS Mean
T1- uninoculated and unfertilized control 0.063 0.763 0.253 0.359 0.241 0.117 0.103 0.153 0.053 0.021 0.018 0.0306
T2 – 75 % SDF of NPK 0.323 0.466 0.479 0.409 0.439 0.357 0.264 0.353 0.156 0.133 0.042 0.110
T3-100 % SDF of NPK 0.303 0.479 0.425 0.402 0.187 0.097 0.061 0.115 0.049 0.042 0.025 0.038
T4-150 % SDF of NPK 0.173 0.363 0.363 0.299 0.175 0.073 0.039 0.095 0.033 0.028 0.019 0.260
T5-100 % SDF of NPK (water soluble fertilizer) 0.281 0.358 0.295 0.311 0.284 0.274 0.163 0.240 0.067 0.029 0.022 0.039
SEd 0.29 0.32 0.31 0.306 0.30 0.28 0.27 0.283 0.26 0.24 0.23 0.243
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SEd: Standard Error deviation

Table 2.

Chemical fertilizer on the survival of Phosphobacteria in the rhizosphere of soil planted with maize (COMH 1).

Phosphobacteria population (×105cfu/g)
Treatments Vegetative growth stage
 Flowering stage
 Harvesting stage
14 DAS 21 DAS 28 DAS Mean 42 DAS 49 DAS 56 DAS Mean 70 DAS 77 DAS 85 DAS Mean
T1- uninoculated and unfertilized control 54 65 45 54.66 42 16 15 24.33 13 10 8 10.33
T2 – 75 % SDF of NPK 61 73 65 66.33 61 37 30 42.66 25 13 11 16.33
T3-100 % SDF of NPK 43 60 45 49.33 32 21 20 24.33 16 14 8 12.66
T4-150 % SDF of NPK 38 52 27 39.00 26 19 17 20.66 13 9 5 2.90
T5-100 % SDF of NPK (Water soluble fertilizer) 58 69 53 60.00 51 23 26 33.33 21 11 10 14
SEd 0.46 0.46 0.45 0.45 0.30 0.43 0.43 0.436 0.43 0.41 0.40 0.413
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SEd: Standard error deviation

Table 3.

Chemical fertilizer on the population of diazotrophs in the rhizosphere of soil planted with maize (COMH 1).

Diazotrophs population (×105cfu/g)
Treatments Vegetative growth stage
 Flowering stage
 Harvesting stage
14 DAS 21 DAS 28 DAS Mean 42 DAS 49 DAS 56 DAS Mean 70 DAS 77 DAS 85 DAS Mean
T1- uninoculated and unfertilized control 33 38 50 40.33 45 39 16 33.33 14 13 12 13.00
T2 – 75 % SDF of NPK 111 129 133 124.33 62 46 21 43.00 19 17 15 17.00
T3-100 % SDF of NPK 85 116 126 109.00 38 33 13 28.00 12 11 9 10.66
T4-150 % SDF of NPK 35 45 55 45.00 31 30 16 25.66 11 10 8 9.66
T5-100 % SDF of NPK (water soluble fertilizer) 53 63 75 63.66 52 41 19 37.33 16 14 13 14.33
SEd 0.46 0.46 0.47 0.463 0.45 0.45 0.42 0.44 0.42 0.41 0.41 0.413
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SEd: Standard error deviation

Due to a decrease in root growth and root exudations, the maximum microbial populations were observed during the vegetative growth stage, which subsequently declined from the flowering to the harvesting stage.

3.1.2. Chemical fertilizers on the rhizosphere soil's urease, dehydrogenase, acid, and alkaline phosphatase and nitrogenase enzyme activities in the maize rhizosphere (COMH 1)

Compared to the 75 %, 100 % and 150 % SDF of NPK treated plot, the control plot (without fertilizer) showed higher soil enzyme activities viz., urease (79.6 µg of NH4/g/24 h), dehydrogenase (110 µg of TPF/g/24 h), acid phosphatase (251 µg of p – nitrophenol/g/hr), and alkaline phosphatase (811 µg of p – nitrophenol/g/hr). The 150 % SDF of NPK treated plot showed the highest inhibition of soil enzyme activities viz., urease (55 µg of NH4/g/24 h), dehydrogenase (69 µg of TPF/g/24 h), acid phosphatase (151 µg of p – nitrophenol/g/hr), and alkaline phosphatase (585 µg of p – nitrophenol/g/hr) than 75 and 100 % SDF of NPK. This might be due to the higher dose of fertilizer leading to more enzyme-substrate complex which suppresses the normal enzymatic function in the soil. (Fig. 1).

Fig. 1.

Fig. 1

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Chemical fertilizer on urease, dehydrogenase and acid phosphatase activities in the soil planted with maize (COMH 1).

Compared to the fertilized plot, the unfertilized and uninoculated control plots showed the highest nitrogenase activity (1913.30 µmol of C2H4/g of soil/hr), followed by the 75 % SDF of NPK (1802.60 µmol of C2H4/g of soil/hr). There was significant variation was observed between fertilized and unfertilized plots. Out of all the treatments, 150 % SDF of NPK showed a higher degree of nitrogenase activity inhibition (953.70 µmol of C2H4/ g of soil/hr) than the other treatments (Fig. 2.). This might be due to the increased amount of N fertilizers showed inhibitory role on nitrogenase activity. The results declared that the addition of fertilizer disturbs the soil enzyme activities and the native soil ecosystems support the positive impact on soil enzyme activity than fertilizer application.

Fig. 2.

Fig. 2

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Chemical fertilizer on nitrogenase activities in the soil planted with maize (COMH 1).

3.2. Inorganic inputs on soil microbial population’s survival in rice fields

Algaecide, herbicide, and fungicide were applied during the rice field experiment. It investigated how the inorganic input affected the population of soil microbes.

3.2.1. In rice fields, the recommendation of algaecide, herbicide and fungicide application on the microbial population

The current investigation reported that all the inorganic inputs drastically reduced the soil's beneficial microbial population. There was significant variation had been observed in the inorganic input sources treated plots and control plots. Control treatment showed more bacterial population than inorganic input treatments. Among the inorganic amendments, algaecide is less inhibition than herbicide and fungicide application concerning soil bacteria, fungi, actinomycetes, Azospirillum, Phosphobacteria, and Pseudomonas population

The influence of Algaecide on soil microbial population is as follows. The algaecide application significantly decreased microbial population than control treatment. However among the algaecide, maximum bacteria and Pseudomonas populations were recorded in the treatment CuSo4 application (30.0, 32.33 × 104cfu/g) followed by CuSo4 + Cao (29.33, 30.33 × 104cfu/g) and Cao (25.66, 24.66 × 104cfu/g) respectively. Maximum fungi and Azospirillum populations were observed in the treatment CuSo4 (19.33 × 103cfu/g, 1.93 × 105MPN/g) followed by Cao (17.0 × 103cfu/g, 1.36 × 105 MPN/g) and CuSo4 + Cao (12.33 × 103cfu/g, 0.86 × 105MPN/g) respectively. Actinomycetes population was abundance (less inhibition) in CuSo4 + Cao (20.0 × 102cfu/g) followed by CuSo4 (19.0 × 102cfu/g) and Cao (16.33 × 102cfu/g). Phosphobacteria population was higher in the treatment CuSo4 (23.3 × 104cfu/g) followed by Cao (21.0 × 104cfu/g) and CuSo4 + Cao (20.66 × 104cfu/g).

Herbicide application affects the soil microbial population more than control and algaecide application. The influence of herbicide application on soil microbial population is as follows. Among the herbicide applications, Almix (28.33 × 104cfu/g) showed more bacteria population via less inhibition followed by londox power (27.33104cfu/g) and butachlor (26 × 104cfu/g). The maximum fungal population was observed in the butachlor (17.66 × 103cfu/g) followed by londox power (15.66  × 103cfu/g) and Almix (13.3  × 103cfu/g) (Table 4). Maximum actinomycetes population was observed in butachlor (17 × 102cfu/g) followed by bisphyriphos sodium (16.33 × 102cfu/g) and Almix (12.66  × 102cfu/g) application (Table 4). Maximum phosphobacteria population was observed in the londox power (19.66 × 104cfu/g) followed by Almix (18.66 × 104cfu/g) and butachlor (14.66 × 104cfu/g). Maximum Azospirillum population was observed in the treatment londox power (1.73 × 105 MPN/g) followed by butachlor (1.66 × 105 MPN/g) and pyrosulfuran 1.56 × 105 MPN/g) application. Maximum Pseudomonas population via less inhibition was observed in the treatment butachlor (27  × 104cfu/g) followed by Almix (22 × 104cfu/g) and pyrosulfuron (20 × 104cfu/g) application.

Table 4.

Wetland rice ecosystem: weedicides, fungicides, and algaecides application on microbial population in the rhizosphere of soil cropped with rice (ADT 43).

Treatments Bacteria
(×104cfu/g)
 Fungi
(×103cfu/g)
 Actinomycetes
(×102cfu/g)
30DAT 60DAT 90DAT Mean 30DAT 60DAT 90DAT Mean 30DAT 60DAT 90DAT Mean
T1 - Bispyriphossodium (H) 28 16 9 17.66 6 4 0 3.3 25 16 8 16.33
T2–AlmixH) 35 29 21 28.33 21 13 6 13.3 19 13 6 12.66
T3 -Pyrosulfuran (H) 31 25 13 23.0 13 9 4 8.66 14 10 5 9.66
T4 - Londox power (H) 33 28 21 27.33 23 16 8 15.66 11 8 6 8.33
T5 - ButachlorH) 35 27 16 26.00 26 17 10 17.66 24 15 12 17.00
T6 -CuSO4(A) 41 33 16 30.00 28 18 12 19.33 28 20 9 19.00
T7-CaO(A) 33 26 18 25.66 26 16 9 17.00 26 16 7 16.33
T8 -CuSO4 + CaO(A) 36 29 23 29.33 19 13 5 12.33 28 19 13 20.00
T9 –Propiconaole (F) 29 1 8 9 18.66 23 15 7 15.00 23 12 8 14.33
T10 -Hexaconazole (F) 33 24 12 23.00 21 13 8 14.00 20 9 7 12.00
T11 - Control 120 80 60 86.60 20 10 5 11.66 25 12 5 14.00
SEd 1.93 1.49 0.93 1.45 1.23 0.79 0.41 0.81 1.20 0.75 0.44 0.796
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Note: SEd: Standard error deviation, H = herbicide, A = Algaecide, F = Fungicide.

The influence of fungicide application on soil microbial population is as follows. Maximum phosphobacteria and Pseudomonas populations via less inhibition were observed in the treatment propiconazole (12.66, 20.0 × 104cfu/g) followed by Hexaconazole (7.66, 15.33 × 104cfu/g) (Table 5). Maximum Actinomycetes and Azospirillum were observed in the treatment propiconazole (14.33 × 102cfu/g, 1.53 × 105 MPN/g) followed by Hexaconazole (12 × 102cfu/g, 1 × 105 MPN/g) respectively. Maximum abundance of bacteria and fungi population was observed in propiconozole (23 × 104cfu/g, 8 × 103cfu/g) followed by Hexaconazole (18 × 104cfu/g, 7 × 103 cfu/g) respectively (Table 5).

Table 5.

Weedicides effect of wetland rice ecosystem on beneficial microbial population in the rhizosphere of soil.

Treatments Phosphobacteria
(×104cfu/g)
 Azospirillum
(×105 MPN/g)
 Pseudomonas
(×104cfu/g)
30DAT 60DAT 90DAT Mean 30DAT 60DAT 90DAT Mean 30DAT 60DAT 90DAT Mean
T1 - Bispyriphossodium (H) 16 11 5 10.66 1.3 1.0 1.1 1.13 19 8.0 6 11.00
T2–Almix (H) 26 19 11 18.66 1.5 0.9 0.2 0.86 26 21 19 22.00
T3–Pyrosulfuran (H) 19 13 7 13.00 2.6 1.5 0.6 1.56 26 21 13 20.00
T4 - Londoxpower (H) 27 21 11 19.66 2.6 1.9 0.7 1.73 24 19 12 18.33
T5 – Butachlor (H) 21 15 8 14.66 2.6 1.7 0.7 1.66 36 29 16 27.00
T6 -CuSO4(A) 31 26 13 23.33 2.9 1.9 1.0 1.93 41 33 23 32.33
T7–CaO (A) 29 21 13 21.00 2.3 1.6 0.2 1.36 31 26 17 24.66
T8 -CuSO4 + CaO (A) 28 21 13 20.60 1.5 0.9 0.2 0.86 37 31 23 30.33
T9 –Propiconaole (F) 18 13 7 12.66 1.9 1.6 1.1 1.53 25 23 12 20.00
T10 -Hexaconazole (F) 13 7 3 7.66 1.5 0.9 0.6 1.00 21 16 9 15.33
T11 - Control 40 20 10 23.3 30 20 10 20 160 120 90 123.30
SEd 1.35 1.02 0.52 0.963 0.12 0.08 0.042 0.080 1.66 1.33 0.86 1.28
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SEd: Standard error deviation

Note: H = herbicide, A = Algaecide, F = Fungicide.

4. Discussion

Microbial activity in soil is thought to act as a storehouse, contributing significantly to soil processes that ultimately determine plant productivity. The maize field experiment's findings revealed that higher fertilizer dosages reduced both the microbial population and soil microbial enzyme activity. Plots treated with 75 % SDF of NPK had the highest populations of Azospirillum (0.409 × 105 MPN/g), Phosphobacteria (66.33 × 105cfu/g), and diazotrophs (124 × 105cfu/g) followed by 100 % and 150 % SDF of NPK. The soil enzyme activity viz., urease (79.6 µg of NH4/ g /24 h), dehydrogenase (110 µg of TPF /g/24 h), acid phosphatase (251 µg of p – nitrophenol/g/hr), alkaline phosphatase (811 µg of p – nitrophenol/g/hr) and nitrogenase (1913.30 µmoles of ethylene produced/g of soil/hr) were higher in the unfertilized control plot than fertilized plot.

The data from the findings indicated that the survival of microorganisms is unaffected by the addition of a small amount of fertilizer to the soil. Higher amounts of inorganic nutrients build up in the soil as a result of increased fertilizer dosage, which reduces microbial survival and enzyme activity. Long-term fertilizer application significantly affects soil microbial communities throughout the soil profile in fact, the relative abundance of ammonia-oxidizing archaea at 0–40 cm depth was noticed (Li et al., 2014). In all tillage systems, chemical fertilizers decreased the enzyme activity. A possible reason might be that organic matter could increase microbial activity in the soil. Acid and alkaline phosphatase activity in the soil significantly depended on the type of organic manure and whether or not chemical fertilizers were employed. Higher acid and alkaline phosphatase activities of soil treated with organic manures could be related to microbial biomass production. The application of chemical fertilizer decreased urease activity (Heidari et al., 2016). To preserve the sustainability of the soil's biological ecosystem and soil organic carbon content, we must reduce the amount of chemical fertilizer that is available and replace it with organic amendments and biofertilizers.

Overuse of chemical fertilizers has detrimental effects on biodiversity, climate change, soil and water quality, and human health (Pirttilä et al., 2021). One method to address this issue that guarantees food safety, preserves soil biodiversity, and upholds ecological balance is organic agriculture (Du et al., 2022).

Fertilization can indirectly impact soil microorganisms by changing soil properties or directly by input of nutrients (Pan et al., 2020, Yan et al., 2021). A study indicated that long-term application of chemical fertilizer resulted in a significant decline in soil bacterial diversity due to a decrease in soil pH value, while the addition of manure effectively alleviated this decline (Sun et al., 2015).

The results of the rice field experiment showed that the microbial population was decreased by the addition of fungicide, herbicide, and algaecide than control treatment. Among the inorganic amendments added, algaecide recorded highest microbial population via less inhibition than herbicide and fungicide application. Among the algaecide application, maximum bacteria and Pseudomonas population were recorded in the treatment CuSo4 application (30.0, 32.33 × 104cfu/g) followed by CuSo4 + Cao (29.33, 30.33 × 104cfu/g) and Cao (25.66, 24.66 × 104cfu/g) respectively. Maximum fungi and Azospirillum populations were found in the treatment CuSo4 (19.33 × 103cfu/g, 1.93 × 105 MPN/g) followed by Cao (17.0 × 103cfu/g, 1.36 × 105 MPN/g) and CuSo4 + Cao (12.33 × 103cfu/g, 0.86 × 105 MPN/g) application respectively. Actinomycetes population was abundance in CuSo4 + Cao (20.0 × 102cfu/g) followed by CuSo4 (19 × 102cfu/g) and Cao (16.33 × 102cfu/g) application. Phosphobacteria population was higher in the treatment CuSo4 (23.3 × 104cfu/g) followed by Cao (21 × 104cfu/g) and CuSo4 + Cao (20.66 × 104cfu/g) application.

Prior research has mostly offered broad insights into the diversity, evenness, and abundance of the soil microbial community that was sensitive to various fertilization treatments (Li et al., 2017).When compared to the chemical fertilizer treatment, the organic fertilizer treatment improved potential ecosystem function by increasing the diversity of soil microorganisms, changing the network structure, and influencing key microbial organisms (Gu et al., 2019). The diversity of soil microbes responded differently to environmental disturbances (Cai et al., 2020). Additionally, it has been demonstrated that the emergence of soil-borne plant diseases was caused by a decline in soil microbial diversity, addressing the possibility that variations in the rhizosphere microbial community could influence variations in disease resistance.

5. Conclusion

Long-term accumulation of chemical fertilizers, herbicides, pesticides, and fungicides has altered the innate behavior of the soil and altered the diversity of microbes growing there. Since microbes are present, the soil is referred to as a living ecosystem. The cycling of nutrients and the breakdown of soil depend on these processes. The soil microbial population was less affected by algaecide followed by herbicide and fungicide application based on the rice field study. Reduced use of chemical fertilizers increased soil microbial population, and without fertilizer, plots had higher soil enzyme activities than 100 % and 150 % standardized doses of NPK-treated plots, according to the maize field experimental study. Hence, to maintain soil health organic amendment and less inorganic input supply is a more positive response to soil microbial diversity and soil enzyme activities of soil.

Author contribution

M. Jeya Bharathi: Conducted research trial in maize and rice, enumeration of soil microorganism and analysis of soil enzyme activities. M. Anbarasu: Soil analysis and process of article. R. Raghu: Technical writing and submission of article. E. Subramanian: Biometrics and analysis rice and maize field data.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

My profound thanks to Dr. D. Balachandar, Professor, Department of Agricultural Microbiology at Tamil Nadu Agricultural University in Coimbatore, who has motivated me to pursue this field of study.

Contributor Information

M. Jeya Bharathi, Email: jeyabharathi@tnau.ac.in.

Mariyappillai Anbarasu, Email: manbarasu102@gmail.com.

R. Ragu, Email: ragu.r@tnau.ac.in.

E. Subramanian, Email: esubramanian@tnau.ac.in.

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