issn (p): 2349-8242 impact of integrated disease

~ 1349 ~

The Pharma Innovation Journal 2021; 10(5): 1349-1357

ISSN (E): 2277- 7695

ISSN (P): 2349-8242

NAAS Rating: 5.23

TPI 2021; 10(5): 1349-1357

© 2021 TPI

www.thepharmajournal.com

Received: 10-03-2021

Accepted: 29-04-2021

Arunasri P

Department of Plant Pathology, S.V.

Agricultural College, Tirupati,

Acharya N.G, Ranga Agricultural

University, Guntur, Andhra Pradesh,

India

Padmodaya B

Department of Plant Pathology,

DAATTC,Kadapa, Acharya N.G,

Ranga Agricultural University,

Guntur, Andhra Pradesh, India

Prasanthi A

Department of Soil Science and

Agril.Chemistry, S.V. Agricultural

College, Tirupati, Acharya N.G,



Naidu MVS

Department of Soil Science and

Agril.Chemistry , S.V. Agricultural

College, Tirupati, Acharya N.G,



Tirumala Reddy S

Department of Agronomy, RARS,

Tirupati, Acharya N.G, Ranga

Agricultural University, Guntur,

Andhra Pradesh, India

Reddi Kumar M

Department of Plant Pathology,

KVK,Kalikiri, Acharya N.G, Ranga

Agricultural University, Guntur,

Andhra Pradesh, India

Koteswara Rao SR

Department of Entomology,

Agricultural College, Bapatla,



India

Ravindra Reddy B

Department of Statistics and

Computer Applications, S.V.




India

Corresponding Author:

Arunasri P

Department of Plant Pathology, S.V.




India

Impact of integrated disease management practices on

soil health and disease incidence of stem rot of

groundnut incited by Sclerotium rolfsii Sacc

Arunasri P, Padmodaya B, Prasanthi A, Naidu MVS, Tirumala Reddy S,

Reddi Kumar M, Koteswara Rao SR and Ravindra Reddy B

Abstract Sclerotium rolfsii Sacc. is a major soil borne pathogen that causes stem rot of groundnut. Per cent

incidence of stem rot will be influenced by soil health that include soil pH, electrical conductivity,

organic carbon and which in turn influence soil microflora (fungi, actinomycetes and bacteria). Integrated

Disease Management practices like combination of Indigenous Technology Knowledge inputs like

Modified Panchagavya, Combination fungicide Hexaconazole 4%+Zineb 68% (Avtar), biocontrol agent

Trichoderma asperellum GT4 and organic amendment (Neem cake) were combined in the form of 14

treatments including inoculated control and un-inoculated control. In the present investigation impact of

these soil health aspects on disease incidence of stem rot of groundnut was studied. With the soil pH 7.4

(at 45 DAS) and 7.2 (at the time of harvest) per cent disease incidence of stem rot was least (9.08% and

14.13%) in treatment T12 that includes seed treatment with Hexaconazole 4%+Zineb 68%(Avtar),seed

treatment with T. asperellum GT4 and neem cake application@500kg/ha. With the highest electrical

conductivity (0.79) and organic carbon (0.87), disease incidence of stem rot was least (9.08% and

14.13%)in treatment T12. Soil microflora responded differently to these treatments and edaphic factors.

Soil fungal population increased even upto harvest and were highest in T9 (94 ×104 cfu/g soil) with mean

of 88 ×104 cfu/g soil in treatment T9. Actinomycetes were highest (72.22×105 cfu/g soil) in treatment T8

where as bacteria were highest (72.56 ×106 cfu/g soil) in treatment (T12). Overall mean soil microflora

were highest in treatment T12 (63.37 cfu) and thus neem cake was found to influence disease incidence

and soil health.

Keywords: Sclerotium rolfsii, soil pH, electrical conductivity, organic carbon, percent disease incidence

and soil microflora

Introduction

Groundnut (Arachis hypogaea L.) is an important oilseed crop in India which occupies first

position in terms of area and second position in terms of production. China ranks first in

groundnut production with 17.39 million tonnes followed by India 6.69 million tonnes (Pocket

book of Agricultural Statistics, 2019). Stem rot of groundnut is a major disease of groundnut

incited by Sclerotium rolfsii Sacc. and it causes yield loss of 15-70% in groundnut singly or in

combination with leaf spot or rust (Adiver, 2003) [1].

Soil fertility and chemistry including soil pH, calcium, phosphorus and zinc levels and

nitrogen form can all play a major role in the management of soil borne diseases. Although the

use of biological control methods for the effective management of soil borne diseases has been

a long-term goal in sustainable agriculture, the efficacy of this method is highly dependent on

the integrated approaches to maintaining soil health and controlling soil borne pathogens

(Milan Panth et al., 2020) [20]. Although the effect of compost and organic matter on soil borne

disease suppression has been demonstrated in many studies, the efficacy of these amendments

widely depends upon the amount added, type of soil, physical properties like structure and

chemical properties such as cation exchange capacity, pH, electrical conductivity of the soil

(Scheuerell et al., 2005) [26]. The collar rot incidence and sclerotial population of S.rolfsii of

tomato were positively correlated with the available Nitrogen (N) and Organic Carbon (OC)

content of the respective soils. Whereas, soil pH had an inverse influence on the disease

incidence and sclerotia population (Prabir Kumar et al., 2020) [22].

Soil microorganisms are the engine of nutrient cycling. Soil microbes degrade soil organic

materials in the soil, releasing nutrients for plant uptake through the mineralization process

with the rate of all these processes dependent on microbial population and activity.

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The Pharma Innovation Journal http://www.thepharmajournal.com

Generally, organic amendment in arable soil might stimulate

microbial activity (Lee et al., 2015a and Lee et al., 2015b) [15,

16]. These shifts are induced alongside changes in water

contents, carbon substrate, and soil pH depending on the crop

cultivation condition such as fertilization and irrigation

(Marschner et al., 2003) [18]. Over dosages of chemicals

(herbicides, fertilizers, insecticides, fungicides, nematicides

and antibiotics) affects the soil quality by changing the

physical, chemical and biological properties of soil. They

adversely affect the soil microflora by which ecological

balance gets disturbed (Naresh and Dhaliwal, 2020) [20].

Microbial communities in soil will have major impact on soil

health as they produce secondary metabolites and nutrients

recycling and decomposition. Organic amendments like neem

seed cake affects soil microbial population, soil catabolic

processes which affect crop yield. Soil organic amendments

also provide diversified food base, which can diversify and

change the microbial population equilibrium in the soil

(Bonanomi et al., 2018) [3]. Larkin (2015) [14] reviewed the

strategies for soil health management in which he suggested

importance of maintaining and diversifying soil biota by

integrated soil health management approaches. Saralamma

and Vithal Reddy (2003) [25] reported that T. harzianum +

Thiophanate methyl + neem cake proved effective against

increasing efficiency of suppression of root rot of S.rolfsii and

increasing yields of groundnut.

The present investigation was taken up with an objective to

study about the impact of integrated disease management

aspects on soil health properties like soil pH, EC, OC,

microflora and their effect on PDI of stem rot of groundnut

and also soil microbial load.

Materials and Methods

Field experiment was conducted on impact of treatments

imposed for integrated disease management of stem rot of

groundnut incited by S. rolfsii on soil health parameters like

soil pH, EC, OC, soil microflora during kharif 2019. Data

pertaining to PDI in response to different soil health

properties were recorded.

Soil Sample collection Soil samples were collected at thrice at the time of sowing, at

45 DAS and before harvesting during groundnut crop season.

The samples were initially transferred aseptically to the

plastic bags that were labelled appropriately and then

transported to the laboratory. In the laboratory, fractions of

samples were immediately processed for pH determination

and microbial analysis. The rest of the samples were then air-

dried, sieved through a 2mm sieve to remove stones and

packed into plastic bags, each containing approximately 500g.

Soil samples were stored at 4oC until they were used for

further analysis.

Determination of soil pH

In a clean conical flask 20 g of air-dried soil was taken and

100 ml distilled water was added for making 1:5 soil

suspension. It was shaken for one hour at regular intervals.

After shaking, the suspension was filtered through Whatmann

No. 42 filter paper. The pH of the sample was determined

using a pH meter (Jackson, 1973) [7].

Determination of soil Electrical Conductivity (EC)

To 1g of soil sample, 1ml of water was mixed in the ratio of

1:1.Then this suspension was filtered using suction. A round

Whatmann no.42 filter paper was placed in the Buchner

funnel and filter paper was moistened with distilled water and

made sure that it was tightly attached to the bottom of the

funnel and their pores were covered. With suction attached to

vacuum pump suspension was collected in Buchner funnel.

Filtrate was then transferred into 50 ml bottle and the

conductivity cell was immersed into the solution and readings

were noted (Jackson, 1973) [7].

Determination of soil organic carbon (C)

Organic matter plays an important role in supplying nutrients

and water and provides good physical conditions to the plants.

The quantity of organic carbon of the soil was estimated by

the method of Walkley and Black (1934) [28]. One gram finely

ground soil sample passed through 0.5 mm sieve without loss

was taken into 500 ml conical flask, to which 10ml of 1 N

potassium dichromate and 20 ml Con. H2SO4 were added with

measuring cylinder. The content was shaken for a minute and

allowed to set aside for exactly half an hour. Then 200 ml

distilled water, 10 ml orthophosphoric acid and 1 ml

diphenylamine indicator were added or ferrous sulphate, till

colour flashes from blue violet to brilliant green. The blank

titration was carried at the beginning without soil.

1. Weight of soil taken

2. Vol. of 1N Potassium dichromate added

3. Vol. of 0.5N FAS required to neutralize 10ml of 1 N

Potassium Dichromate solution

B = Blank without soil, T= Titre value

4. Vol. of 0.5N FAS required for soil

5. Vol. of 1 N H2Cr2O7 solution used for the oxidation of

organic carbon present in the sample. =10(B-T)

The organic carbon % was calculated by the following

formula

10 (B- T) x 0.003 100

Organic Carbon % = –––––––––––––––– x ––––––––––––

B wt. of soil (g).

The solution was titrated against standard ferrous ammonium

sulphate (FAS)

Soil microflora (fungi, bacteria and actinomycetes) in soil

Serial dilution technique (Johnson and Curl, 1972) [8] was

used to isolate fungi, bacteria and actinomycetes from

rhizosphere soil of Groundnut. Composite soil sample

collected from rhizosphere of healthy plants and stem rot

infected Groundnut plants thrice at 9DAS, 60DAS and at the

time of harvesting and soil samples were shade dried, sieved

and then used for serial dilution.

Preparation of culture medium used for isolation of

rhizosphere microflora Three different specific medium mentioned underneath were

prepared as per the recommendation for isolation of different

microbes such as bacteria (NA), fungi (Rose Bengal Agar

medium), and actinomycetes (SCA).

Enumeration of rhizosphere soil microflora (fungi,

bacteria and actinomycetes)

To estimate the number of rhizosphere soil microflora, counts

were calculated on the basis of serial 10 fold dilution

technique, using the pour plate methods and replicate of 10

gm soil samples, and an appropriate dilution as described by


~ 1351 ~


Johnson and Curl, (1972) [8]. Ten g of air dried soil was taken

from each soil sample and were sieved properly to discard all

the foreign particles and added to 100ml of sterilized distilled

water to make a dilution of 10-1, from this dilution 10ml of the

aliquot was transferred to 90 ml of sterilized distilled water to

make dilution of 10-2. Likewise, the soil samples were serially

diluted (six fold series). Aliquots of 1 ml from dilution 10-6

were spread on nutrient agar, a medium for total bacterial

counts respectively, and from 10-4 on Rose Bengal Agar for

fungi and from 10-5 on starch Casein Agar medium for

actinomycetes. Each dilution was spread onto three replicates.

The number of colonies forming on each medium was

counted at 48-72 hrs for bacteria and after 120 hrs for fungi

and actinomycetes, after incubation at 32 ± 2oC for bacteria

and 25± 2oC for fungi and actinomycetes.

Colony forming units per g of soil (cfu/g) was calculated

using the equation of Johnson and Case (2007) [9].

No. of colonies

CFU/g= × Dilution factor

Volume plated (ml)

Results and Discussion

Soil samples were collected at the time of sowing, at 45 DAS

and at the time of harvest with an objective of studying the

influence of treatments imposed for the integrated

management of stem rot of Groundnut on edaphic factors like

pH, EC, OC on the PDI of stem rot of Groundnut.

Soil pH

At the time of sowing soil pH varied from 5.8 to 6.8, at 45

DAS soil pH varied from 5.7 to 7.4 and at the time of harvest

soil pH varied from 5.8 to 7.2 (Table 1). In the present

investigation it was observed that treatments involving neem

cake amendment to soil has resulted in increase in soil pH at

45 DAS and at harvest. Treatment T12 recorded highest soil

pH of 7.4 at 45DAS and 7.2 at the time of harvest whereas

PDI was least in this treatment at 45 DAS (9.08%) and even

at the time harvest (14.13%). Krishnaraj et al. (2018) [12]

revealed that application of neem cake to soil increased pH

from 6.8 to 7.2 due to decomposition and they also reported

that population of biocontrol agents like Trichoderma and

Pseudomonas fluorescens increased due to utilization of

nutrients from neem cake.

In the present investigation low pH values were recorded in

treatment T13(Table 1) with pH value of 5.7 and 5.5 at 45

DAS and at the time of harvest respectively and

corresponding PDI was maximum at 45 DAS (37.51%) and at

the time of harvest (64.24%). Maximum PDI was reported in

soils with pH 5.5 (treatment T13). After treatment T12,

treatments T10 and T11 recorded next highest pH values of 7.2

and 7.4 (at 45 DAS and at time of harvest).This rise in soil pH

in Fig.1 in treatments T10 and T11 (Fig. 1) might be due to

influence of modified panchagavya. These findings were in

corroboration with the investigation of Naresh and Dhaliwal

(2020) [20] who reported soil pH was increased from 6.8 to 7.8

due to micro-organisms present in panchagavya.

Banyal et al. (2008) [2] also recorded increase in soil pH with

least PDI whereas low pH value resulted in maximum PDI.

They observed significant positive correlation between pH

and collar rot incidence in tomato caused by S.rolfsii. Tomato

plants grown in soils of Indora with soil pH 5.7 recorded

highest PDI of collar rot (45.1%) and no.of sclerotia per gram

soil was found to be maximum (4.0) when compared to other

soil samples with different pH values. They reported that

highest PDI as S.rolfsii prefers near acidic to alkaline

conditions (pH 5.5 to 7.5). In the present investigation also

T13 with soil pH (5.5 and 5.7) recorded highest PDI at the

time of harvest and even at 45 DAS whereas T12 with soil pH

7.2 reported least PDI (Fig.2). Kator et al. (2015) [10] also

reported that S.rolfsii produced maximum growth at acidic pH

as optimum pH for maximum growth of mycelium of S.rolfsii

was in between 3.0 to 5.0 whereas for sclerotia germination at

pH from 2.0 and 5.0. Mahato et al. (2017) [17] also recorded

highest PDI (100%) collar rot of tomato caused by S.rolfsii at

pH 6.5 and 7.0 whereas least PDI was observed (51.67%) at

pH 8.0. They also opined that growth and proliferation of

S.rolfsii was favoured by pH 5.5 to 7.5 in decreasing order.

Prabir Kumar et al. (2020) [22] investigated on influence of

soil pH on Disease incidence (DI) of collar rot of betelvine

caused by S. rolfsii and also on no. of sclerotia produced.

They concluded that highest DI (17.67%) was recorded in

Namkhana village soil sample (Location 1) with soil pH 5.56

and proved to produce highest no. of sclerotia of 11.56 per

100 g soil, whereas in case of Bamkhana village soil sample

with

Table 1: Impact of Integrated Disease Management treatments on edaphic factors and PDI of stem rot of Groundnut (Field experiment during

kharif 2019)

Treatment

pH* EC(ds/m)* OC(%)* PDI*

At the

time of

sowing

45

DAS

At the

time of

harvest

At the

time of

sowing

45

DAS

At the

time of

harvest

At the

time of

sowing

45

DAS

At the

time of

harvest

At the time

of sowing

45

DAS

At the

time of

harvest

T1 Seed treatment with Hexaconazole 4% +

Zineb 68% WP(0.01%) 5.9 6.1 6.2 0.27 0.52 0.61 0.21 0.49 0.61 0.00 12.21 24.87

T2 Seed treatment with Modified

Panchagavya(10 dilution) 6.5 6.4 6.3 0.26 0.48 0.59 0.21 0.52 0.58 0.00 21.79 25.56

T3 Seed treatment with Hexaconazole 4% + Zineb 68% WP (0.01%)+Seed treatment

with T. asperellum GT4@ 10g/ kg seed

5.8 5.9 5.8 0.30 0.47 0.55 0.22 0.47 0.52 0.00 19.49 20.10

T4 Soil application of T. asperellum

GT4(Talc based multiplied in

FYM@5q/ha)

6.1 6.2 6.3 0.27 0.58 0.62 0.21 0.48 0.59 0.00 20.67 27.92

T5 Soil application of neem

cake@500kg/ha 5.8 6.4 6.8 0.28 0.64 0.71 0.31 0.52 0.73 0.00 17.06 24.62

T6 Soil drenching with modified

panchagavya (10 dilution) 6.0 5.8 5.9 0.27 0.54 0.64 0.29 0.43 0.77 0.00 20.85 27.50

T7 T1+ T4 5.8 6.0 6.1 0.26 0.47 0.71 0.21 0.34 0.49 0.00 17.84 27.85

T8 T1+ T5 6.4 7.1 6.8 0.32 0.54 0.60 0.30 0.61 0.74 0.00 19.48 26.19

T9 T1+ T6 5.8 6.0 6.1 0.25 0.45 0.59 0.21 0.58 0.71 0.00 17.47 24.02

T10 T2+ T4 5.8 7.3 7.1 0.34 0.63 0.77 0.26 0.63 0.84 0.00 10.74 19.93


~ 1352 ~


T11 T2+ T5 6.2 7.2 7.0 0.38 0.69 0.74 0.32 0.61 0.78 0.00 12.04 20.91

T12 T3+ T5 6.6 7.4 7.2 0.32 0.67 0.79 0.28 0.68 0.87 0.00 9.08 14.13

T13 Inoculated control 6.4 5.7 5.5 0.27 0.40 0.45 0.25 0.34 0.41 0.00 37.51 64.24

T14 Un-inoculated control 6.8 6.9 6.8 0.26 0.42 0.51 0.39 0.41 0.49 0.00 26.59 33.33

C.D. 0.109 0.081 0.042 0.027 0.007 0.027 0.008 0.006 0.006 Not

significant

1.479 3.311

SE(m) 0.037 0.028 0.014 0.009 0.002 0.009 0.003 0.002 0.002 0.506 1.133

C.V. 1.045 0.746 0.389 5.376 0.731 2.479 1.87 0.7 0.536 3.442 6.216

*Mean of three replications

Fig 1: Impact of integrated disease management treatments on soil pH at different time interval

Fig 2: Impact of integrated disease management treatments on PDI of stem rot of groundnut at different time interval

pH of 5.24 with second highest (10.78) no.of sclerotia per 100

g soil were produced with DI of 14.67%. Kulkarni and Hegde

(2019) [11] revealed that highest germination of sclerotia of

S.rolfsii in potato occur at pH 6.5 (90%) and least germination

of sclerotia was noticed at pH level of 9.5 (58.33%) whereas

percent colonization of sorghum seeds by the mycelial growth

of S.rolfsii that indicates competitive saprophytic ability was

highest at soil pH 6.0(76.67%) and least was recorded with

pH 9.5(46.67%).

Chaurasia et al. (2014) [5] revealed that oxalic acid produced

by S.rolfsii that plays major role in pathogenesis was

produced to maximum at pH 5.0 even though S.rolfsii


~ 1353 ~


produces this organic acid at wide pH values of 3.0 to pH 9.0

(i.e., extreme acidic to alkaline pH). But at pH 5.0 maximum

accumulation of oxalic acid was detected when S. rolfsii was

cultured on the medium. As oxalic production was correlated

to PDI of stem rot of Groundnut caused by S. rolfsii and in the

present investigation this was proved as PDI of stem rot was

highest at soil pH 5.5 (treatment T13).

Soil electrical conductivity (EC)

Soil EC in the soils collected at the time of sowing varied

from 0.25 to 0.38, at 45 DAS it varied from 0.40 to 0.69 and

at the time of harvest varied from 0.45 to 0.79 (ds/m). At 45

DAS highest EC was recorded in the treatment T11, T12 and

T10 with PDI (least) of stem rot values 14.29, 8.96 and

10.73% (Table 1). At the time of harvest, highest EC values

were reported in treatments T12, T10 and T11 (Fig.3) with least

PDI of 12.50, 17.39 and 22.70%. In the present investigation

negative correlation was observed with EC and PDI of stem

rot. Treatment T13 recorded 0.40 and 0.45 at 45 DAS and at

the time of sowing with PDI of stem rot (37.51 and 72.70%).

It was found that EC was negatively correlated with PDI.

These findings are in corroboration with Kulakarni and Hegde

(2019) [11] who proved that negative correlation between EC

and PDI of collar rot of potato caused by S. rolfsii who

reported at lowest EC value 0.4 (ds/m) highest competitive

saprophytic survival of S. rolfsii on sorghum (90%) and per

cent germination of sclerotia (100%) were observed. They

recorded decreased competitive saprophytic survival of S.

rolfsii on sorghum (90%) and per cent germination of

sclerotia (6.25%) at EC of 10.0dS/m. Highest EC was

recorded in T12 which might be due to neem cake. These

findings were corroboration with Elnasikh et al. (2011) [6]

who proved that neem seed cake was positively related with

EC.

Soil organic carbon

Soil organic carbon of the treatments varied from 0.21 to 0.32

(at the time of sowing, 0.34 to 0.68 at 45 DAS and 0.41 to

0.87 (at the time of harvesting).The PDI at the time sowing at

45DAS and at the time of harvesting was least with soils

having highest organic carbon. In

Fig 3: Impact of integrated disease management treatments on soil EC at different time interval

the treatment T12 OC was 0.68 (at 45 DAS) and 0.87 (at the

time of harvesting) with PDI of stem rot 9.08% (at 45 DAS)

and 14.13% (at the time of sowing) whereas in the treatment

T13 OC was 0.34 and 0.41(at 45 DAS and at the time of

harvest) with corresponding PDI of stem rot as 37.51 and

64.24% indicating negative correlation between OC and PDI.

In the present investigation increase in OC in T12 and

T11(Fig.4) might be due to organic amendment neem cake as

it gets decomposed in the soil. This was in accordance with

the findings of Krishnaraj et al. (2018) [12] who revealed that

application of neem cake to soil increase organic carbon from

0.59 to 1.05. Lalnunpuia et al. (2018) [13] also proved that

treatment T8 @ [NPK100% Recommended Dose of Fertilizer

(RDF)+Neem cake 100 kg ha-1] increased soil organic carbon

(0.52) and electrical conductivity (0.96ds/m) but at the same

decreased pH.

Soil microflora

At 9 DAS soil fungi were highest in the treatment T9 (81.67

×104 cfu/g soil) followed by T6 (58.67×104 cfu/g soil) and

least soil fungi were observed in T2 (15.67×104 cfu/g soil). At

60 DAS highest soil fungi were recorded in T9 (88.33 ×104

cfu/g soil) followed by T6 (84.67×104 cfu/g soil) and least soil

fungi were observed in T1 (Table 2) and followed by T13

(32×104 cfu/g soil). At the time of harvesting highest soil

fungi were recorded in T9 (94 ×104 cfu/g soil) followed by T7

(91.67×104 cfu/g soil) and T6 (89×104 cfu/g soil) and least soil

fungi were observed in T13 (35.33×104 cfu/g soil). It was

observed that soil fungi increased from 9 DAS to time of

harvesting in all the treatments. Mean soil fungi were highest

in T9 (Fig.5). In case of soil actinomycetes at 9 DAS soil

actinomycetes were highest in the treatment T8 (84 ×105 cfu/g

soil) followed byT12 (79.33×105cfu/g soil) and least soil

actinomyctes were observed in T13 (33×105 cfu/g soil). At 60

DAS highest soil actinobacteria were recorded in T8 (75.33

×105 cfu/g soil) followed byT10 (61.67×105 cfu/g soil) and

least soil actinobacteria were observed in T13 (21.33×105 cfu/g

soil). At the time of harvesting highest soil actinobacteria


~ 1354 ~


were recorded in T10 (69×105 cfu/g soil) followed by

T6(58.67×105 cfu/g soil) and least soil actinobacteria were

observed in T13 (24.33×105 cfu/g soil). It was observed that

soil actinobacteria decreased from 9 DAS to 45DAS and even

at time of harvesting in all the treatments except T12 in which

actinobacteria at 45DAS were increased slightly at the time of

harvest. Mean Actinobacteria were highest in T10 (60.67)

which is statistically significant when compared to all other

treatments. In case of bacteria at 9 DAS soil bacteria were

highest in the treatment T1 (80.67 ×105 cfu/g soil)followed

byT10 (60.67×105cfu/g soil) and least soil bacteria were

observed in T11 (35.67×105 cfu/g soil).At 60 DAS highest soil

bacteria were recorded in T10(75.33 ×105 cfu/g soil) followed

byT10 (61.67×105 cfu/g soil) and least soil actinobacteria were

observed in T13 (21.33×105 cfu/g soil). At the time of

harvesting highest soil bacteria were

Fig 4: Impact of integrated disease management treatments on soil OC at different time interval

Table 2: Efficacy of treatments on Rhizosphere microflora of Groundnut (Field experiment during kharif 2019)

S.N

o. Treatment

FUNGI(×104)cfu/g soil* ACTINOMYCETES(×105)

cfu/g soil *

BACTERIA(×106) cfu/g

soil * Overall

mean 9

DAS

60

DAS

At

harvest Mean 9 DAS

60

DAS

At

harvest Mean

9

DAS

60

DAS

At

harvest Mean

T1 Seed treatment with Hexaconazole 4% + Zineb 68%

WP(0.01%) 18.67 32.00 40.00 30.22 42.33 34.33 28.33 35.00 80.67 58.67 41.33 60.22 41.81

T2 Seed treatment with Modified Panchagavya (10 dilution) 15.67 41.67 56.00 37.78 61.33 40.67 34.67 45.56 41.00 37.67 40.67 39.78 41.04

T3 Seed treatment with Hexaconazole 4% + Zineb 68% WP (0.01%)+Seed treatment with T. asperellum GT4@ 10g/

kg seed

18.33 58.67 63.67 46.89 74.33 60.33 43.67 59.44 42.33 36.00 26.33 34.89 47.07

T4 Soil application of T. asperellum GT4(Talc based

multiplied in FYM@5q/ha) 31.67 39.67 72.33 47.89 49.33 31.67 23.33 34.78 53.33 39.67 32.33 41.78 41.48

T5 Soil application of neem cake@500kg/ha 19.00 47.00 82.33 49.44 54.00 40.67 34.00 42.89 43.33 31.33 28.00 34.22 42.19

T6 Soil drenching with modified panchagavya (10 dilution) 58.67 84.67 89.00 77.44 42.67 50.33 58.67 50.56 40.67 57.33 50.00 49.33 59.11

T7 T1+ T4 38.67 80.67 91.67 70.33 56.00 44.33 32.33 44.22 45.33 38.67 30.67 38.22 50.93

T8 T1+ T5 21.33 54.67 64.33 46.78 84.00 75.33 57.33 72.22 58.67 43.67 35.67 46.00 55.00

T9 T1+ T6 81.67 88.33 94.00 88.00 65.00 50.33 40.33 51.89 48.33 38.67 31.67 39.56 59.81

T10 T2+ T4 18.00 64.33 68.00 50.11 70.33 61.67 69.00 67.00 60.67 80.67 72.00 71.11 62.74

T11 T2+ T5 25.33 69.33 79.00 57.89 52.33 47.33 42.33 47.33 35.67 56.33 48.33 46.78 50.67

T12 T3+ T5 18.33 66.00 71.00 51.78 79.33 60.67 57.33 65.78 56.00 74.33 87.33 72.56 63.37

T13 Inoculated control 24.67 32.00 35.33 30.67 33.00 21.33 18.67 24.33 38.33 30.33 24.67 31.11 28.70

T14 Un-inoculated control 40.00 41.33 46.00 42.44 36.67 41.33 26.33 34.78 40.00 41.33 30.67 37.33 38.19

Overall mean 30.71 57.17 68.05 51.98 57.19 47.17 40.45 48.27 48.88 47.48 41.40 45.92

*Mean of three replications C.D. at 5%

Treatment 0.913

Rhizosphere microflora 0.423

Interval 0.423

Treatment X Rhizosphere microflora X Interval 2.738


~ 1355 ~


Fig 5: Impact of integrated disease management treatments on soil fungal population at different time interval

recorded in T10(80.67×105 cfu/g soil) followed by

T12(74.33×105 cfu/g soil) and least soil bacteria were observed

in T13 (30.33×105 cfu/g soil). Soil bacteria decreased in all the

treatments from 9 DAS to 45 DAS except T12 in which

bacterial count was increased. It was observed that soil

bacteria decreased from 45 DAS and at the time of harvesting

in all the treatments except T2 and T12 in which actinobacteria

at 45DAS were increased. Mean actinobacteria were highest

in T10 (60.67×105 cfu/g soil) which is statistically significant

when compared to all other treatments. Soil bacteria varied

from 35.67 to 80.67 ×106 cfu/g soil at 9 DAS, 30.33 to

80.67×105 cfu/g soil at 60 DAS and 24.67 to 87.33×106 cfu/g

soil at the time of harvest. Mean soil bacteria were highest in

T12(72.56×106cfu/g soil) and least in T13 (30.33 ×106cfu/g

soil). At 9 DAS highest bacterial counts were reported in T1

(80.67×106cfu/g soil) and least bacterial population was

recorded in T11(35.67×106cfu/g soil).

In the present investigation fungal population was highest in

T9 (88×104cfu/g soil) and this was statistically significant

when compared to all other treatments. Fungal population was

highest even at 9 DAS, 45 DAS and at the time of harvest

which might be due to involvement soil drenching with

modified panchgavya which consists of different fungi in its

composition itself and soil drenching with might have

influenced soil fungi. These are in accordance with the

findings of Boomiraj and Christopher (2007) [4] who reported

that higher bacterial and fungal count were recorded in the

treatment involving poultry manure (145×106cfu) and

panchagavya (103×104cfu). Next best treatment included

application of neem cake and panchagavya (140×106 cfu and

102×104cfu). Ram et al. (2018) [24] also revealed that

Panchagavya contained highest number of total bacteria (6.25

× 109 cfu/ml).

The present investigation revealed that treatment T8 recorded

highest mean actinomycetes (72.22×105cfu/g soil). The reason

might be due to involvement soil application of neem cake

that might have increased soil pH to neutral which might be

favourable for the growth of actinomycetes (Fig.6). These

findings were in accordance with Elnasikh et al. (2011) [6]

who investigated on the effect of neem cake on fungi, bacteria

and actinomycetes. They reported that neem seed cake

positively affected the microbial load of actinomycetes and

affected negatively the fungal population and bacteria. Zanane

et al. (2018) [29] investigated on microbial population of

bacteria, actinomycetes and fungi in different soil samples

and correlated with edaphic factors like soil pH, EC and

organic carbon. They found that S3 with soil pH 7.4 was rich

with the microflora with bacteria (146±1.250 cfu×108/g),

actinomycetes (209±0.251cfu×105/g) and fungi 10.33± 32.145

cfu ×105 / g). As pH in this treatment T12 was 7.2 at the time

of harvest and 7.4 at 45 DAS, actinomycetes were also

highest.

In the present investigation mean bacterial population were

highest in treatment T12 (63.37×106 cfu/g soil) which might be

due to neem cake. These findings were in accordance with

Zanane et al. (2018) [29]. Next highest bacterial count was

recorded in T10 (62.74×106 cfu/g soil) and in T9


~ 1356 ~


Fig 6: Impact of integrated disease management treatments on soil Actinomycetes population at different time interval

Fig 7: Impact of integrated disease management treatments on soil bacterial population at different time interval

(59.81×106 cfu/g soil) as shown in fig.7. Rakesh et al. (2017) [23] reported that Panchagavya plays a major role in

influencing microbial loads (bacteria, fungi and

actinomycetes) and reported increased microbial load of

110×106 cfu, 25×105 cfu and 21×105 cfu.

Conclusion

Soil borne pathogens can be managed with integrated disease

management with treatments that maintain equilibrium

between the ecosystems. Management practices that maintain

soil health along with crop health are to be integrated. Future

line of work is to be conducted on influence of all the

important edaphic factors on stem rot of groundnut and soil

microbial communities at different locations.

Acknowledgement

The Author was thankful to Acharya N.G.Ranga Agricultural

University (A.P) for providing facilities for conducting

experiments.

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