Organic Agriculture

, Volume 1, Issue 4, pp 203–216

Does organic farming increase soil suppression against Fusarium wilt of melon?

Authors

  • Anat Yogev
    • Institute of Plant SciencesAgriculture Research Organization, Newe Ya’ar Research Center
    • Department of Plant Pathology and Microbiology, Faculty of Agricultural, Food and Environmental SciencesHebrew University of Jerusalem
  • Yael Laor
    • Institute of Soil, Water and Environmental SciencesAgricultural Research Organization, Newe Ya’ar Research Center
  • Jaacov Katan
    • Department of Plant Pathology and Microbiology, Faculty of Agricultural, Food and Environmental SciencesHebrew University of Jerusalem
  • Yitzhak Hadar
    • Department of Plant Pathology and Microbiology, Faculty of Agricultural, Food and Environmental SciencesHebrew University of Jerusalem
  • Rony Cohen
    • Institute of Plant ProtectionAgricultural Research Organization, Newe Ya’ar Research Centre
  • Shlomit Medina
    • Institute of Plant SciencesAgriculture Research Organization, Newe Ya’ar Research Center
    • Institute of Plant SciencesAgriculture Research Organization, Newe Ya’ar Research Center
Article

DOI: 10.1007/s13165-011-0016-1

Cite this article as:
Yogev, A., Laor, Y., Katan, J. et al. Org. Agr. (2011) 1: 203. doi:10.1007/s13165-011-0016-1

Abstract

Under Israeli organic farming conditions, compost (mostly made of animal manure) is annually applied as a source of plant nutrients, to enhance soil microbial activity and nutrient cycling and to improve soil structure. Composts are also known for their suppressive properties against soil-borne diseases. The objective of the present study was to assess the level of suppressiveness against Fusarium oxysporum f. sp. melonis (FOM) that may develop in soils with a history of organic farming as compared with conventional farming. Pairs of organic vs. conventional taxonomically identical soil samples were collected from adjacent plots, at various sites throughout the main agricultural areas in Israel. Out of 15 pairs, four of the organically managed soils were significantly more suppressive than their corresponding conventional plots. On the average, the area under the disease progress curve and the final disease incidence of the inoculated plants grown in conventionally managed soils were higher at 12% and 21%, respectively, than those of the plants grown in the organically managed soils. Both differences were significant when examined using two-factor ANOVA test (site and farming system). Microbial activity of the organic soils, as expressed by heat production rate, was positively correlated with soil suppressiveness and was significantly higher by a factor of 2.2 as compared with the conventionally managed paired soils. It is suggested that organic farming practices and especially compost application may lead, with time, to some reduction of the problems caused by FOM. This beneficial effect of organic farming seems non-specific to soil type or climatic region in Israel.

Keywords

CompostCucumis melo L.Fusarium oxysporum f. sp. melonisMicrocalorimetryOrganic agricultureSoil-borne diseases

Abbreviations

AUDPC

Area under disease progress curve

FOM

Fusarium oxysporum f. sp. melonis

Introduction

Among the essentials of organic farming are the avoidance of pesticides and the improvement of soil properties by means of maintaining crop rotation and annual application of organic matter such as compost. One of the indirect benefits of organic management may be the build-up of a healthier soil. Van Bruggen and Semenov (2000) defined a healthy soil as a stable system, characterized by resilience to stress and having high biological diversity and a high level of nutrient cycling. Multiple studies showed increased microbial activity under organic farming. Mäder et al. (2002) and van Diepeningen et al. (2006) found that organically managed soils were, on the average, more stable and healthier (as defined by van Bruggen and Semenov 2000) than their equivalent conventionally managed soils.

An essential aspect of soil health is the ability of the soil to resist soil-borne plant pathogens. Van Bruggen (1995) indicated a lower incidence of corky root disease of tomato, caused by Pyrenochaeta lycopersici in organically managed farms. Sterilization of the organic soils by irradiation increased the disease level, suggesting the involvement of biological mechanisms. Knudsen et al. (1999) found that organically managed soils suppressed the incidence of brown foot rot of cereals caused by Fusarium culmorum in comparison to disease levels in conventionally managed soils. Liu et al. (2007) reported that soils from organic farms, which showed higher microbial activity (measured by respiration), were more suppressive to Southern blight of tomato, caused by Sclerotium rolfsii than soils from conventional farms.

Different types of composts are known to suppress a wide variety of diseases incited by soil-borne pathogens, such as the soil fungi S. rolfsii, Rhizoctonia, Pythium, and Fusarium (Hadar and Mandelbaum 1986; Trillas-Gay et al. 1986; Gorodecki and Hadar 1990; Hoitink et al. 1993, 1997). Similarly, we found that various composts induced suppressiveness towards soil-borne pathogens including Clavibacter michiganensis and four formae speciales of Fusarium oxysporum (Yogev et al. 2006, 2009). It was also found that compost-amended soils attained with time some level of disease suppressiveness against soil-borne pathogens such as F. oxysporum, Rhizoctonia solani, Colletotrichum coccodes (Abbasi et al. 2002; Steinberg et al. 2004; Darby et al. 2006). However, in most of these studies only a limited number of soil types were tested.

In Israel, organic growers typically amend their soils annually with 10–20 t of compost/ha. These composts are based mainly on animal manure (cattle and chicken). Under Israeli conditions, in addition to its beneficial effect on soil biological activity and physical properties, compost is the only required source for both K and P and is also an important source for N (Raviv et al. 2006). Being of extra value for organic farming, it was found that this compost type could efficiently suppress several soil-borne diseases (Aryantha et al. 2000; Reuveni et al. 2002; Raviv et al. 2005; Saadi et al. 2010). Thus, the aim of the present study was to examine the assumption that repeated compost application to Israeli organic soils will lead to the development of soil suppressiveness. We tried to determine the extent of this phenomenon over a wide range of soil types, crops, and climatic conditions. A second objective was to examine the association between selected soil characteristics and degree of suppressiveness, which may lead to the identification of useful indicators for the development of soil suppressiveness.

Materials and methods

Samples collection

Fifteen pairs of soil samples were collected between February and September 2006. Fourteen pairs from farms of collective communities (Kibbutzim) in Israel that grow similar crops under both conventional and organic management in adjacent taxonomically identical plots, and one pair from the organic (plus conventional control) plots of Newe Ya’ar Research Center (Fig. 1). Three of the sites, Afikim, Newe Ya’ar, and Shluhot were planted with orchards—avocado, stone fruits, and grapefruit, respectively. The rest of the sites were planted with annual field crops grown in rotation, suited for the specific conditions of each location. Soil types, average annual precipitation, cropping history of at least 5 years, and the amounts of applied compost are presented in Table 1. The applied composts were made mostly of cattle manure, with some chicken manure and crop residues. The soil pairs show identical taxonomic definitions, except for one case (Shluhot), where there was a taxonomical difference between the organic and the conventional soil. Notably, some of the conventional soils were also amended with composts (Table 1).
https://static-content.springer.com/image/art%3A10.1007%2Fs13165-011-0016-1/MediaObjects/13165_2011_16_Fig1_HTML.gif
Fig. 1

Locations of the farms sampled in this study. In each site, soil samples were taken from adjacent organic and conventional plots

Table 1

Soils classification, crop types, and cumulative amounts of compost applied during the last 3 years prior this study (2003–2005)

Field location

Farming system

Soil classification

Crop

Years after conversion

Cumulative amount of compost applied (ton ha−1)

Average annual precipitation (mm)

Afikim

Org.

Typic Haploxerert

Avocado

14

60

408

Conv.

None

Alumim

Org.

Calcixerollic Xerochrept

AFC

23

20

340

Conv.

15

Amir

Org.

Typic Haploxerert

AFC

4

90

540

Conv.

None

Beit Alfa

Org.

Chromic Haploxerert

AFC

7

45

420

Conv.

None

Ein Harod

Org.

Chromic Haploxerert

AFC

5

40

430

Conv.

None

Heftsiba

Org.

Chromic Haploxerert

AFC

16

25

420

Conv.

None

Ifat

Org.

Chromic Haploxerert

AFC

5

25

540

Conv.

25

Kisufim

Org.

Xeric Quartzipsamment

AFC

9

52

300

Conv.

None

Newe Ya’ar

Org.

Chromic Haploxerert

Stone fruits orchard

10

34

570

Conv.

None

Nir Oz

Org.

Xeric Quartzipsamment

AFC

6

55

240

Conv.

None

Ramat David

Org.

Chromic Haploxerert

AFC

6

60

550

Conv.

20

Ruhama

Org.

Xeric Quartzipsamment

AFC

4

95

320

Conv.

20

Sde Eliyahu

Org.

Typic Haplargid

AFC

30

34

292

Conv.

20

Shluhot

Org.

Typic Haplargid

Grapefruit orchard

14

48

310

Conv.

Typic Haploxerert

AFC

None

Tse’elim

Org.

Typic Torripsamment

AFC

15

35

220

Conv.

None

Organic (Org.) and conventional (Conv.) soils were sampled at each location. Taxonomy data were provided by Dr. Pinchas Fine, Institute of Soil, Water and Environmental Sciences, the Volcani Center, ARO

AFC annual field crops

Ten soil samples of about 2 kg each were randomly collected from each organic and conventional plot from the 5–30 cm top layer, combined and mixed thoroughly. Soil analyses were conducted within a few days after sampling. All samples were taken from fields where melons were not grown previously, and no historic record of F. oxysporum f. sp. melonis (FOM) is known.

Soil analyses

Composite soil samples were dried at 70°C and ground to <2 mm (except for the samples used for microbial activity determination). Organic matter content was determined by means of wet oxidation in potassium dichromate and sulphuric acid (the Walkley and Black method; Allison 1965). CaCO3 was determined by adding HCl to the soil and measuring the volume of the released CO2 (Loeppert and Suarez 1996). N–NH4 was analyzed by extracting the soil with 1 N KCl solution and using a colorimetric method (Mulvaney 1996). The pH was measured directly in a saturated soil paste using an electrode with a single-pore capillary reference junction and a spear tip (Eutech instruments, EC-620-133). The following analyses were performed in the saturated paste extract: EC, K (using flame photometer), and P (determined colorimetrically after shaking the soil with 0.5 M NaHCO3, according to the Olsen method; Olsen 1965). N–NO3 was measured in 1:10 water extract by UV difference (Mulvaney 1996). Soil texture was determined by the hydrometer method (Day 1965).

Microbial activity was assessed by microcalorimetry as previously described by Laor et al. (2004) and Medina et al. (2009). Two kilograms of each sample were sieved through 4.75-mm screen. Then, 5 g of the sieved soil was wetted to achieve 70% of field capacity, 24 h before use. The microcalorimeter used was CSC 4100 (Calorimetry Science Corp., UT), operated under isothermal mode at a set temperature of 25°C. Fifty microliters of water was added to the test ampoules while the reference ampoule was left empty at all times. After reaching a stable baseline, soil samples equivalent to 200 mg of dry weight were placed in the test ampoules. All the tests were carried out in at least three replicates. The effect of organic management on soil microbial activity is expressed as the ratio between the amount of heat released from organic soil (J g dry soil−1 day−1) and that of the respective conventional soil:
$$ {\text{Microbial}}\,{\text{activity}}\,{\text{index}} = \frac{{{\text{Hea}}{{\text{t}}_{\text{organic}}}}}{{{\text{Hea}}{{\text{t}}_{\text{conventional}}}}} $$
whereas values above 1 indicate enhanced microbial activity under organic farming.

Evaluating disease suppression

Disease suppression was evaluated in pot-based assays using melon seedlings (Cucumis melo L. cv. ofir), as previously described (Yogev et al. 2006). Microconidia of FOM were originally isolated from diseased melon plants, showing typical disease symptoms. The conidia were found pathogenic to melon plants in repeated experiments and were identified as race 0. The Microconidia were produced on yeast extract agar medium: in 1 l deionized water, 20 g bacteriological agar (Acumedia, Neogen Co., Lansing, MI), 5 g Bacto™ yeast extract, 5 g Bacto™ peptone (Both from Becton, Dickinson and Company, Sparks, MD), 20 g d-glucose, and 0.25 g chloramphenicol (both from Sigma-Aldrich Co, St. Louis, MO). The culture was incubated at 27°C for 7 days. Then, conidia were scraped into tap water with a glass slide and filtered through four layers of cheesecloth. Conidial suspension was centrifuged at 3,775×g for 25 min, and the precipitate was resuspended in tap water. Conidial density was determined with haemocytometer.

Seeds of melons were planted in sand and irrigated with tap water. Six days after sowing, the seedlings were removed; their roots were washed, cut to 2 cm, and dipped for 2 min in the conidial suspension that contained 1.5 × 105 conidia ml−1. The seedlings were then transplanted into the tested soils or peat (Plantobalt, Riga, Latvia). The tested soils were mixed with perlite no. 4 (HaBonim, Israel), at a 1:1 volumetric ratio in order to improve water infiltration through the pots. Eight 0.25-l pots were filled with each soil, seven of them were planted with inoculated seedlings, and one was planted with non-inoculated seedlings, five seedlings in each pot. Eight more pots were filled with peat moss and served as a non-suppressive control (Cohen et al. 2008). Seven of them were planted with inoculated seedlings and one was planted with non-inoculated seedlings, five seedlings in each pot. The test lasted 12–21 days, according to the virulence of the disease.

Disease incidence was expressed both as the area (integral) under disease progress curve (AUDPC) (Shaner and Finney 1977) using PSI-Plot software (Poly Software International, Pearl River, NY), and as the percentage of diseased plants at the end of the experiment (final incidence). To demonstrate the effect of organic farming, the following suppression indices were defined:
$$ {\text{AUDPC - based}}\,{\text{suppression}}\,{\text{index}} = \left( {1 - \frac{{{\text{AUDP}}{{\text{C}}_{\text{organic}}}}}{{{\text{AUDP}}{{\text{C}}_{\text{conventional}}}}}} \right) \times 100 $$
and
$$ {\text{Final}}\,{\text{incidence - based}}\,{\text{suppression}}\,{\text{index}} = \left( {1 - \frac{{{\text{Fina}}{{\text{l}}_{\text{organic}}}}}{{{\text{Fina}}{{\text{l}}_{\text{conventional}}}}}} \right) \times 100 $$
whereas positive values indicate induced soil suppressiveness and negative values indicate relative conducive conditions compared with the respective conventional soil.

When indicated, it was calculated as the percentage of those values, either in organic or conventional soil, as compared with those obtained for the peat treatment in the same trial. In all experiments, the non-inoculated plants remained healthy.

Statistical analyses

Mean values of suppression (AUDPC and final incidence) and microbial activity (heat generation) obtained for organic and conventional soil of each pair were compared by using the Tukey–Kramer honestly significant difference test (p ≤ 0.05). Additionally, these values were compared between all pairs of organic and conventional soils using a two-factor ANOVA test (site and farming system) with interaction (p ≤ 0.05). Replicate values included replicate pots (suppression evaluation) or replicate ampoules (microbial activity measured by microcalorimetry). All statistical tests were performed by JMP software (Ver. 5.0.1, SAS Institute Inc.). Pearson’s r correlations among all variables were also calculated with JMP.

Results

Soil samples were taken from various sites located in the main agricultural regions of Israel (Fig. 1). The measured soil characteristics are summarized in Table 2, and some of them are plotted as histograms in Fig. 2. The content of organic matter was significantly higher in the organic as compared with the paired conventional plots by an average factor of 1.63. The range of increase in organic matter content of the organic plots varied substantially. It increased by ≥0.5% in eight of the soil pairs, whereas it was roughly comparable (<0.5% difference) in the rest seven pairs (with percent change ranging from −10% to +280%). The levels of N–NH4, N–NO3, P, K, and EC were also higher in the organic soils, although the differences were significant only for P (by factor of 3.15) and K (by factor of 3.09), at p ≤ 0.05. The pH level, soil texture, and calcium carbonate content were all less affected by organic farming. The histograms presented in Fig. 2 illustrate the variability of the data with some “tailing” of the organic soils toward higher values. One exceptional case was observed for N–NO3 in Kisufim, where the concentration was the highest among all other organic soils and the factor representing the difference between the organic and conventional paired soil was one of the greatest as well. The correlation matrix shown in Table 4 presents some of the general geographical trends that are typical to Israeli soils: at the more arid regions (lower precipitations), the soils are characterized by lower contents of organic matter, lower nutrient concentrations (significant for N–NH4), higher salinity (EC), and more sandy texture.
Table 2

Selected physical and chemical characteristics of the tested soils

Field location

Farming system

Organic matter (%)

N–NH4 mg kg−1 dry soila

N–NO3 mg kg−1 dry soil

P mg kg−1 dry soil

K meq l−1b

EC dS m−1

pH

Clay (%)

Silt (%)

Sand (%)

CaCo3 (%)

Afikim

Org.

6.1

6.8

21.6

92.4

1.00

2.4

7.7

47.4

32.7

19.9

23.2

Conv.

1.6

7.2

9.2

42.8

0.20

1.5

7.9

49.4

30.7

19.9

40.7

Alumim

Org.

1.4

9.5

29.6

68.1

2.20

3.8

7.3

13.7

31.2

55.1

12.7

Conv.

1.0

5.0

87.0

38.2

0.80

3.8

7.3

21.7

27.2

51.1

11.9

Amir

Org.

2.5

11.1

14.0

214.1

0.90

0.7

7.6

36.1

33.3

30.6

30.0

Conv.

2.0

8.3

13.0

32.4

0.40

0.5

7.6

68.1

21.3

10.6

15.2

Beit Alfa

Org.

2.8

12.0

23.0

99.0

1.20

1.2

7.1

50.3

28.6

21.1

17.1

Conv.

1.2

4.5

3.0

23.9

0.10

0.4

7.0

49.1

32.5

18.4

14.2

Ein Harod

Org.

1.6

16.7

5.6

39.0

0.30

0.5

7.0

54.3

28.6

17.1

15.4

Conv.

0.9

11.7

10.5

20.2

0.10

0.5

7.0

54.3

24.6

21.1

15.4

Heftsiba

Org.

2.2

11.7

16.0

83.1

0.30

0.6

7.7

54.1

31.3

14.6

23.6

Conv.

1.0

7.3

10.5

19.5

0.10

0.5

7.7

54.1

31.3

14.6

19.2

Ifat

Org.

1.6

7.2

5.2

45.1

0.20

0.4

7.0

53.1

24.5

22.4

10.2

Conv.

1.2

4.3

3.3

28.5

0.10

0.3

7.0

54.3

28.6

17.1

7.3

Kisufim.

Org.

1.3

5.1

48.7

67.5

0.80

2.5

7.4

6.4

6.8

86.8

20.0

Conv.

0.9

3.5

10.4

19.4

0.40

1.7

7.5

5.4

7.8

86.8

16.9

Newe Ya’ar

Org.

3.3

84.9

34.8

129

1.50

1.9

7.0

45.9

24.5

29.6

1.9

Conv.

2.7

37.4

10.8

98.8

0.60

1.1

7.0

49.9

26.5

23.6

1.9

Nir Oz

Org.

0.5

6.4

11.3

23.5

0.90

1.4

7.5

3.7

5.2

91.1

4.6

Conv.

0.5

3.0

11.4

19.4

0.70

2.6

7.4

11.7

5.2

83.1

1.9

Ramat David

Org.

2.5

17.7

7.1

105

0.30

0.5

7.0

50.3

24.6

25.1

4.1

Conv.

1.8

25.2

7.2

23.8

0.20

0.5

7.0

54.3

24.6

21.1

4.1

Ruhama

Org.

1.0

2.5

29.3

17.3

0.50

1.7

7.6

5.4

8.8

85.8

13.8

Conv.

0.9

2.4

20.7

27.2

0.20

1.2

7.7

5.4

7.8

86.8

15.4

Sde Eliyahu

Org.

2.5

4.8

8.9

97.7

0.50

0.6

7.2

34.3

32.6

33.1

48.8

Conv.

1.5

5.8

8.4

46.2

0.60

0.7

7.2

22.3

24.6

53.1

63.0

Shluhot

Org.

1.8

18.9

7.4

353

0.70

1.0

7.2

22.3

24.6

53.1

23.6

Conv.

2.0

5.5

5.5

42.0

0.30

0.8

7.1

50.3

28.6

21.1

25.2

Tse’elim

Org.

0.5

1.5

13.9

38.2

2.00

1.9

7.4

5.7

3.2

91.1

1.5

Conv.

0.3

2.6

9.3

12.1

0.60

0.6

7.7

7.7

1.2

91.1

3.8

Average

Org.

2.1

14.5

18.4

98.1

0.89

1.4

7.3

32.2

22.7

45.1

16.7

Conv.

1.3

8.9

14.7

33.0

0.36

1.1

7.3

37.2

21.5

41.3

17.1

SD

Org.

1.4

20.2

12.6

86.0

0.62

0.97

0.26

20.4

10.9

29.6

12.5

Conv.

0.6

9.7

20.5

20.8

0.24

0.97

0.32

22.0

10.5

30.9

16.2

Significant at p ≤ 0.05

 

a

  

a

a

      

Average ratio (Org./Conv.)

 

1.63

1.60

2.02

3.15

3.09

1.46

1.0

0.88

1.16

1.26

1.14

Organic (Org.) and conventional (Conv.) soils were sampled at each location from the top 30 cm. The average and standard deviation of each property obtained for all organic or conventional soils is presented. The significant level of Tukey–Kramer is provided for those properties, which were significantly different between organic and conventional soils at p ≤ 0.05

a70°C

bSaturated paste water

https://static-content.springer.com/image/art%3A10.1007%2Fs13165-011-0016-1/MediaObjects/13165_2011_16_Fig2_HTML.gif
Fig. 2

Histograms of selected soil properties showing the distribution of values obtained for the organic and conventional soils used in this study. The values as related to their specific site locations are listed in Table 2

The suppressiveness of the soils was evaluated by comparing AUDPC and final disease incidence in melon plants, following artificial inoculation, in both organic and conventional soils from the same site. The course of one of those assays is demonstrated for Ein Harod (Fig. 3). In this case, there is a significant increase in disease suppression to Fusarium wilt in the organic vs. the conventional soil (both are more suppressive as compared with peat). As shown in Fig. 4, such significant increases in suppressiveness in organic plots were found for three or four pairs (for AUDPC or final incidence, respectively) out of the 15 pairs tested. Six additional pairs showed higher (but non-significant) suppressiveness in the organic soils. The rest of the pairs showed only minor differences between the organic and conventional plots. One exceptional pair was that of Kisufim, for which a significant opposite effect was observed. On the average, AUDPC of the inoculated plants grown in conventionally managed soils was 12% higher than that of the plants grown in the organically managed soils. An even greater difference was observed between the organic and conventional soils, based on the final disease incidence (21%). Both differences were significant when examined using two-factor ANOVA test (site and farming system).
https://static-content.springer.com/image/art%3A10.1007%2Fs13165-011-0016-1/MediaObjects/13165_2011_16_Fig3_HTML.gif
Fig. 3

Fusarium wilt development in melon planted in organic soil vs. conventional soil from Ein Harod as compared with peat. Different letters indicate significant difference between AUDPC values (p ≤ 0.05)

https://static-content.springer.com/image/art%3A10.1007%2Fs13165-011-0016-1/MediaObjects/13165_2011_16_Fig4_HTML.gif
Fig. 4

Fusarium wilt suppression indices in melon in the studied soils (\( {\text{AUDPC}}\,{\text{based}} = \left( {1 - \frac{{{\text{AUDP}}{{\text{C}}_{\text{organic}}}}}{{{\text{AUDP}}{{\text{C}}_{\text{conventioal}}}}}} \right) \times 100 \) and \( {\text{Final}}\,{\text{incidence}}\,{\text{based}} = \left( {1 - \frac{{{\text{Fina}}{{\text{l}}_{\text{organic}}}}}{{{\text{Fina}}{{\text{l}}_{\text{conventional}}}}}} \right) \times 100 \)). Values above 0 indicate enhanced soil suppressiveness under organic farming. *p ≤ 0.05, paired soils in which the organic soil was significantly different from the conventional soil. Overall, disease suppression by the organic soils was significantly higher than that of the conventional soils (two-factor ANOVA test; p ≤ 0.05)

Similarly, in eight out of 15 soil pairs the microbial activity measured by heat production rate (using microcalorimetry) was significantly higher in the organic soils compared with the respective conventional soils from the same site (Table 3; Fig. 5). Again, a two-factor ANOVA test showed significantly higher microbial activity of the organic soils (by a factor of 2.17). The correlation matrix presented in Table 4 shows significant correlations between heat generation and both suppression indices; i.e., the more microbially active soils were more suppressive against FOM.
Table 3

Final disease incidence in artificially inoculated melon seedlings and heat generation of organic and conventional soils from 15 farms in Israel

Field location

Final disease incidence

Heat generation (J g dry soil−1 day−1)

% organic plot/% peat

% conventional plot/% peat

Organic plots

Conventional plots

Afikim

0.19 ba

0.68 a

7.26 a

1.21b

Alumim

0.53

0.62

2.40 a

1.62 b

Amir

NA

NA

1.47

0.95

Beit Alfa

0.55

0.55

2.16 a

1.21 b

Ein Harod

0.17 b

0.49 a

2.25 a

1.30 b

Heftsiba

NA

N.A

2.94 a

0.86 b

Ifat

0.60

0.52

0.78

0.95

Kisufim

0.69

0.36

1.83

1.30

Newe Ya’ar

0.03 b

0.31 a

7.78 a

4.58 b

Nir Oz

0.65

0.62

1.64 a

0.77 b

Ramat David

0.49

0.51

3.72

2.59

Ruhama

0.26

0.44

0.40

0.48

Sde Eliyahu

0.26

0.23

3.54 a

4.67 b

Shluhot

0.16

0.48

4.75 a

0.86 b

Tse’elim

0.55 b

0.96 a

0.33

0.17

Average

0.39

0.52

2.88

1.57

SD (%)

0.22

0.18

2.25

1.35

Final incidence is expressed as the disease percentage of the soil (organic or conventional) divided by that of the peat control

NA not available

aDifferent letters in each location indicate a significant difference between the organic and conventional paired soils (p ≤ 0.05). A two-factor ANOVA test (site and farming system) showed significantly higher suppression and higher heat generation in the organic soils (p ≤ 0.05)

https://static-content.springer.com/image/art%3A10.1007%2Fs13165-011-0016-1/MediaObjects/13165_2011_16_Fig5_HTML.gif
Fig. 5

Microbial activity index as measured by microcalorimetry. \( {\text{Activity}}\,{\text{index}} = \frac{{{\text{Hea}}{{\text{t}}_{\text{organic}}}}}{{{\text{Hea}}{{\text{t}}_{\text{conventional}}}}} \times 100 \). Values higher than 1 indicate increased microbial activity under organic farming. *p ≤ 0.05, paired soils in which the organic soil was significantly different from the conventional soil. Overall, heat generation was significantly higher in the organic soils (two-factor ANOVA test; p ≤ 0.05)

Table 4

Pearson’s r linear correlation coefficients among the soil and site properties summarized in Tables 1, 2, and 3

 

Rain

Years after conversion

Cumulative compost

Organic matter

N–NH4

N–NO3

P

K

Final incidence

AUDPC

Heat

EC

pH

Clay

Silt

Sand

Years after conversion

−0.197

               

Cumulative compost

0.047

−0.533*

              

Organic matter

0.458*

0.129

0.319

             

N–NH4

0.531**

−0.093

0.040

0.389*

            

N–NO3

−0.140

0.006

0.168

0.018

0.091

           

P

0.163

0.094

0.436*

0.408*

0.336

−0.015

          

K

−0.257

0.324

0.281

0.143

0.228

0.371*

0.236

         

Final incidence

−0.273

−0.153

−0.344

−0.540**

−0.502**

0.075

−0.470

−0.067

        

AUDPC

−0.011

−0.199

−0.375*

−0.332

−0.380*

−0.070

−0.349

−0.121

0.884***

       

Heat

0.295

0.257

0.231

0.770***

0.672***

0.089

0.513**

0.272

−0.702***

−0.543**

      

EC

−0.378*

0.293

0.082

0.015

−0.003

0.753***

−0.028

0.660***

0.079

−0.055

0.118

     

pH

−0.381*

0.077

0.066

−0.066

−0.395*

0.125

−0.110

0.034

0.283

0.192

−0.251

0.215

    

Clay

0.791***

−0.112

−0.215

0.476**

0.302

−0.315

0.047

−0.417*

−0.223

0.092

0.222

−0.535**

−0.347

   

Silt

0.584***

0.304

−0.027

0.560**

0.213

−0.077

0.314

−0.153

−0.376**

−0.062

0.391*

−0.209

−0.290

0.756***

  

Sand

−0.765***

−0.035

0.161

−0.534**

−0.289

0.249

−0.145

0.348

0.289

−0.041

−0.295

0.451*

0.347

−0.973***

−0.887***

 

CaCO3

−0.191

0.514*

0.048

0.195

−0.265

−0.103

0.190

−0.174

−0.273

−0.149

0.175

−0.160

0.209

0.058

0.395*

−0.181

Except for the column “years after conversion” which is based on the data of the organic soils only (n = 15), the other columns are based on the data of both organic and conventional soils. n = 26 for “final incidence” and “AUDPC” (missing data of two pairs) and n = 30 for the rest of properties

*p < 0.05, **p < 0.01, ***p < 0.001

Significant correlations (at p < 0.05) were also found between AUDPC and the cumulative amount of applied compost and N–NH4 concentration, as well as between final incidence and organic matter content, N–NH4 and P concentrations. The content of organic matter was also significantly correlated with heat production and nutrient concentrations (N–NH4 and P).

Discussion

The addition of composted organic wastes to field soils has been shown to reduce the severity of soil-borne diseases (Chellemi and Rosskopf 2004; Lewis et al. 1992; Ros et al. 2005; Rotenberg et al. 2007a, b; Stone et al. 2003; van Bruggen 1995). Composts are frequently applied to organically managed soils, and are presumably the main reason (coupled with the minimal use of pesticides) for the repeatedly observed greater biological activity in organic soils as compared with conventionally managed soils (Gunapala and Scow 1998; Leita et al. 1999; Carpenter-Boggs et al. 2000; Mäder et al. 2002; van Diepeningen et al. 2006). Compost amendment was also shown to affect soil microbial community structure (Saison et al. 2006; Perez-Piqueres et al. 2006; Benitez et al. 2007).

In line with these observations, we studied the effect of organic management on disease suppressiveness of organic vs. conventional soils, across various pedoclimatic conditions in Israel. The chosen pathosystem was melon and FOM. Although melon is an important crop in many parts of the country, including in the studied regions, melon plants had not been previously grown in the tested plots, suggesting that FOM was not a ubiquitous pathogen in these soils. This was also verified by the fact that non-inoculated plants grown in these soils as controls did not show disease symptoms (data not shown). In the inoculation experiment, a high inoculation rate was used, leading to a 100% mortality of the peat-grown plants. Even under this high inoculation rate, the soils from all sites, either organic or conventional, had lower disease incidence than peat (Table 3). On the average, the disease was suppressed to a somewhat larger extent in the organically managed soils than in the conventional soils. The opposite result obtained for Kisufim could be attributed to the high N–NO3 concentration of 48.7 mg kg dry soil−1 in the organic plot, as compared with 10.4 mg kg dry soil−1 in the conventional plot (Table 2). High nitrate levels may lead to increased Fusarium wilt severity in various crops (Lemmens et al. 2004; Waters and Bingham 2007). Similarly, the relatively high N–NO3 content that was found in the organic plots of Beit Alfa, as compared with the conventional plots, may explain the lack of relative suppressiveness of this soil.

In five locations, compost was applied also to the conventional plots (Alumim, Ifat, Ramat David, Ruhama, and Sde Eliyahu; Table 1). In these five locations, comparable or no significant differences were found between the suppression levels of both management practices (Fig. 4), suggesting that the main factor controlling the development of suppressiveness is the applied compost. Thus, compost amendment in some of the conventional soils may confound the effect of compost vs. possible effects of other elements of organic management, such as minimum use of pesticides and avoidance of chemical fertilizers. Similarly, except for Alumim, no difference was found in heat generation rate of organic vs. conventional soils in the other four locations where compost was applied to both management practices (Fig. 5). Thus, compost application seems to have an effect on soil suppressiveness. This is also evident by the negative correlation between AUDPC (significant) or final incidence (non-significant at p < 0.05) and the cumulative amounts of composts applied during the 3 years preceded this study. Also, negative correlations were obtained between final incidence (significant) or AUDPC (non-significant at p < 0.05) and organic matter content.

Considering the time that passed since conversion to organic farming, a significant negative correlation was obtained between the number of years and cumulative amount of applied compost (in the 3 years preceding this study for which we could record the compost amounts with confidence). The most probable explanation for this conflicting correlation is the fact that much higher quantities of compost are applied annually during the first years of conversion to organic farming, whereas at later stages, lower amounts of compost are annually applied (Raviv et al. 2006). Thus, at those sites where conversion to organic farming was more recent, the effect of larger amounts of fresh compost could be expected. Notably, Darby et al. (2006) found a reduction of the suppression capacity with time after the application of compost, which may point to a similar phenomenon; a soil that was recently amended with compost is more suppressive, and this capacity decreases with time, until additional compost is applied.

To explore possible relationships between soil suppressiveness and microbial activity, microcalorimetry was used as a quantitative, non-invasive tool to continuously evaluate basal activity (heat production rate) (Núñez-Regueria et al. 2006; Zheng et al. 2009). Among all tested soil characteristics (Table 4), this measure of microbial activity yielded the highest regression coefficients with soil suppressiveness, suggesting that it may become an indicator for the development of suppressiveness in organic farming. A multi-regression analysis which includes other predictors besides heat production did not increase significantly the correlation with soil suppressiveness.

Higher suppressiveness of organic as compared with conventional soils was also reported by other researchers (Escuadra and Amemiya 2008; Liu et al. 2007; Messiha et al. 2007). Most studies where soil suppressiveness was compared between organic and conventional farming (Gunapala and Scow 1998; Carpenter-Boggs et al. 2000; Mäder et al. 2002; van Diepeningen et al. 2006) were conducted under temperate climatic conditions (North Europe and North America). In these regions, the soils are inherently richer in organic matter and their biological activity is higher than that of most of the soils in Israel, a country located in the arid and semi-arid regions. The physical and chemical parameters of soils typical to the temperate regions exhibited only few differences under organic and conventional farming methods (van Diepeningen et al. 2006).

In cases where no differences were found (e.g., Grünwald et al. 2000), only a limited number of soils were sampled. Considering the large variability of the effect of organic management on soil suppressiveness found in this study, a large number of soils need to be tested before significant differences might be observed. The fact that not all organically managed soils showed increased suppressiveness as compared with the respective conventional soil is not surprising since these soils have different histories of cropping and compost amendments. Also, composts are known to differ in their capacities to suppress diseases (Termorshuizen et al. 2006).

In conclusion, this study shows for the first time the potential of repeated compost amendment to induce soil suppressiveness against Fusarium wilt of melon caused by FOM under a wide range of pedoclimatic conditions. This positive outcome of organic farming can be predicted to some extent based on soil microbial activity as measured by heat generation rate. In general terms, the soil heat generation is affected by organic matter content and its level of biodegradability. This, in turn, is affected by the time elapsed since the last application of compost and the maturity of the applied compost. To elucidate the varying extent of this positive effect, future studies should concentrate on both biotic and abiotic factors apparently involved, including organic matter characteristics, mineralization rates and microbial communities that characterize each of the amended and non-amended tested soils.

Acknowledgments

The authors are grateful to the growers of 14 kibbutzim, who kindly allowed the sampling mission and provided historical information. The soil taxonomical definitions made by Dr. Pinchas Fine are gratefully acknowledged. The research was supported in part by the Chief Scientist of the Ministry of Agriculture and Rural Development, Israel (grant number 132-1357 to R.C., M.R., Y.L., Y.K., and Y.H.).

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© Springer Science & Business Media BV 2011