soil loss due to harvesting of various crop types in contrasting agro-ecological environments

e
www.elsevier.com/locate/age
Agriculture, Ecosystems and Environment 120 (2007) 153–165

Soil loss due to harvesting of various crop types in

contrasting agro-ecological environments

G. Ruysschaert 1, J. Poesen *, G. Verstraeten 2, G. Govers

Physical and Regional Geography Research Group, K.U. Leuven, Geo-Institute, Celestijnenlaan 200E, 3001 Heverlee, Belgium

Received 13 February 2006; received in revised form 20 August 2006; accepted 21 August 2006

Available online 30 October 2006

Abstract

Soil erosion studies on cropland usually only consider water, wind and tillage erosion. However, significant amounts of soil are also lost

from the field during the harvest of crops such as sugar beet (Beta vulgaris L.), potato (Solanum tuberosum L.), chicory roots (Cichorium

intybus L.), cassava (Manihot spp.) and sweet potato (Ipomoea batatas (L.) Lam). During the harvest soil adhering to the crop, loose soil or

soil clods and rock fragments are exported from the field together with these crops.

This soil erosion process is referred to as ‘soil losses due to crop harvesting’ (SLCH). Most of the studies investigated SLCH variability and

its controlling factors for one crop type in similar agro-ecological environments and for comparable harvesting techniques. In this study, a

compilation of SLCH studies was made in order to investigate the effect of crop type, agricultural systems, ecological conditions and

harvesting technique on SLCH variability. SLCH rates ranged from few to tens of Mg ha�1 harvest�1 and SLCH was highly variable both in

space and time. Comparison of four studies on SLCH for sugar beet revealed that harvesting technique and soil moisture content at harvesting

time can be equally important for SLCH variability. The occurrence of soil clods harvested with the crop explained why SLCH was

significantly larger for mechanically harvested potato in Belgium compared to manually harvested potato in China. SLCH values for manually

harvested sugar beet, potato, cassava and sweet potato in China and Uganda were in general smaller than SLCH values for mechanically

harvested sugar beet, potato and witloof chicory roots measured in Belgium and France. However, SLCH may also vary significantly within

Europe due to differences in harvesting techniques. Soil moisture content at harvesting time was besides harvesting technique one of the key

factors controlling SLCH variability. There were no systematic differences in SLCH between crop types, although the soil–crop contact area–

crop mass ratio could explain more than 40% of the means from several SLCH studies.

# 2006 Elsevier B.V. All rights reserved.

Keywords: Soil erosion; Soil loss; Crop harvest; SLCH; Sugar beet; Potato; Cassava; Sweet potato; Chicory

1. Introduction

Most soil erosion research on cropland focuses on soil

redistribution caused by water, wind or tillage (e.g.,

mouldboard ploughing) and neglects the fact that con-

siderable masses of soil may also be lost from arable land

during the harvest of crops such as sugar beet (Beta vulgaris

L.), potato (Solanum tuberosum L.), carrot (Daucus carota

L.), chicory roots (Cichorium intybus L.), leek (Allium

* Corresponding author. Tel.: +32 16 326425; fax: +32 16 322980.

E-mail address: [email protected] (J. Poesen).1 Post-doctoral researcher of the Research Fund K.U. Leuven.2 Fund for Scientific Research-Flanders, Belgium.

0167-8809/$ – see front matter # 2006 Elsevier B.V. All rights reserved.

doi:10.1016/j.agee.2006.08.012

porrum L.), sweet potato (Ipomoea batatas (L.) Lam)

and cassava (Manihot spp.). Soil adhering to the crop, loose

soil or soil clods and rock fragments are exported from the

field together with these harvested crops to external

locations such as headlands, farmsteads and crop proces-

sing factories. This soil erosion process is referred to as

‘soil loss due to crop harvesting’ or ‘SLCH’ (Ruysschaert

et al., 2004).

Mean SLCH values for sugar beet calculated from soil tare

data measured in sugar factories were 6 Mg ha�1 harvest�1

for The Netherlands, 14 Mg ha�1 harvest�1 for France,

9 Mg ha�1 harvest�1 for Belgium and 5 Mg ha�1 harvest�1

for Germany for the period 1978–2000 (Ruysschaert et al.,

2005). Average SLCH values for potato, measured in field

mailto:[email protected]

http://dx.doi.org/10.1016/j.agee.2006.08.012

G. Ruysschaert et al. / Agriculture, Ecosystems and Environment 120 (2007) 153–165154

studies were 3 Mg ha�1 harvest�1 in Belgium (Ruysschaert

et al., 2006a) and 7 Mg ha�1 harvest�1 in Germany (Auers-

wald et al., 2006). Maximum soil losses caused by crop

harvesting may rise to tens of Mg per hectare and per harvest

(e.g., Poesen et al., 2001). Although SLCH values may thus be

from the same order of magnitude as water and tillage erosion

values, few studies have incorporated SLCH as a soil erosion

process. Some of these studies measured SLCH at field plot

scale and aimed at assessing SLCH variability and the

importance of controlling factors. These controlling factors

were divided by Ruysschaert et al. (2004) into four categories,

i.e., soil (e.g., soil texture, soil moisture content at harvest),

crop characteristics (e.g., crop shape), agronomic practices

(e.g., plant density and crop yield) and harvesting technique.

Other studies estimated SLCH variability based on soil tare

data measured in crop-processing factories. From the latter

studies it is impossible to investigate the effects of harvesting

conditions on SLCH. All studies, most from western Europe,

investigated SLCH for one or at maximum two crop types and

are only representative for similar ecological conditions, a

specific agricultural system and comparable harvesting

techniques. The overall objectives of this study are therefore

(1) to compile all available data on SLCH and (2) to

estimate the effect of crop type, agricultural system,

ecological conditions and harvesting technique on SLCH

variability in addition to the effect of factors investigated in

the individual studies (e.g., soil texture and soil moisture

content at harvest). The results of this study allow one to

assess the importance of SLCH in a range of contrasting

agro-ecological environments.

2. Materials and methods

2.1. SLCH terminology

SLCH can either be expressed as mass of oven-dry soil

per unit of net crop mass or on an area-unit basis. Therefore,

Ruysschaert et al. (2004) distinguished between mass-

specific SLCH (SLCHspec) and crop-specific SLCH

(SLCHcrop), i.e.:

SLCHspec ðMg Mg�1Þ ¼ Mds þMrf

Mcrop

(1)

where Mds is the mass of oven-dry soil (Mg), Mrf the mass of

rock fragments (Mg), and Mcrop is the net crop mass (Mg),

i.e., mass of clean roots or tubers:

SLCHcrop ðMg ha�1 harvest�1Þ ¼ SLCHspec �Mcy (2)

where Mcy is the net crop yield (Mg ha�1 harvest�1).

2.2. Data and data analysis

A literature study allowed compiling an overview table of

SLCHcrop rates. SLCH values were either obtained from

direct field measurements or derived from soil tare data

collected at crop processing factories. The field studies with

sufficient information on the harvesting conditions were

used to assess the importance of soil texture, soil moisture

content at harvest, average crop mass, harvesting technique

(manual versus mechanized harvesting), crop type and

seedbed type (mounds or ridges versus flat) by means of

linear regression analyses or ANOVA linear models (SAS

Institute Inc., 1999) with continuous and dummy variables.

Firstly, an analysis of SLCH for sugar beet was made,

secondly studies of SLCH for potato were compared and

finally, field studies of other crop types were added in order

to assess the effect of crop type on SLCH variability.

Smaller roots or tubers are expected to yield larger

adhering SLCHspec values (i.e., soil adhering to the crop and

excluding soil clods), as they have larger soil–crop contact

area–crop mass ratios. For sugar beet, this ratio was defined

by Vermeulen (2001) as the specific soil–beet contact area

and is generalized here as the specific soil–crop contact area

(Ss). As it can be expected that adhering soil losses are

linearly related to the contact area of the crop with the soil,

adhering SLCHspec should increase linearly with increasing

specific soil–crop contact area. Therefore, the effect of crop

type on adhering SLCHspec was investigated by estimating

the specific soil–crop contact area (Ss) for each crop type and

performing linear regression analysis. Ss for potato and

sweet potato was derived from Ruysschaert et al. (2006a):

the average Ss value measured was 1.16 cm2 g�1. For all

other crops, crop density was assumed to be equal to

1 g cm�3, so that crop mass could be assessed by crop

volume. Ss was then calculated by estimating the largest

diameter and by assuming that the crop is cone-shaped

(sugar beet, cassava, inulin chicory) or has a shape in

between a cone and cylinder (carrot, black salsify, witloof

chicory). If mean sugar beet mass was known, the soil–beet

contact area was estimated with an equation proposed by

Koch (1996):

Soil�beet contact area ðcm2Þ

¼ 86:58þ 0:49ðMcrop=pÞ � 9:06� 10�5ðMcrop=pÞ2 (3)

where Mcrop/p is the mean sugar beet mass (g).

3. Results

3.1. Overview of spatial and temporal SLCH variability

for several crop types grown in contrasting agro-

ecological environments

An overview of all SLCHcrop (Mg ha�1 harvest�1) values

calculated from data reported in the literature is provided in

Table 1. Distinction is made between crop and data types,

i.e., data based on field measurements and soil tare data

provided by factories. Where possible, the temporal (daily,

G. Ruysschaert et al. / Agriculture, Ecosystems and Environment 120 (2007) 153–165 155

Table 1

Overview of calculated soil losses due to crop harvesting (SLCHcrop) for various crops grown in different countries (based on Ruysschaert et al., 2005 and

updated according to Ruysschaert, 2005)

Number Country/region SLCHcrop (Mg ha�1 harvest�1),

mean (min–max)

M.P. n Source

Sugar beet

Field data

1 Belgium 3.6 (0.7–30.1) 2002–2004 611 Ruysschaert et al. (2006b)

2 France 14.0 (2.0–44.3) 1984–1986 82 Duval (1988) and Poesen et al. (1999)

3 Belgium (H) 13.4 (5.6–25.7) 2001–2002 48 Ruysschaert (2005)

4 China (H) 1.0 (0.2–1.9) 2002 14 Li et al. (2006)

Factory data

5 Belgium 8.7 (4.4–19.5a/c/all)(1–100i) 1968–1996 29 Poesen et al. (2001)

6 Belgium 8.8 (4.4–19.5a/c/all) 1968–2000 33 Ruysschaert et al. (2005)

7 Belgium 9.3 (4.7–19.4a/c/all) 1978–2000 23 Ruysschaert et al. (2005)

8 Belgium 8.5 (3.0–24.5d/r/s) 1993–1995 373 Ruysschaert (2005)

9 Belgium 8.6 (1.2–18.8w/r/all) 1990–1996 918 Ruysschaert (2005)

10 Belgium 8.3 (4.1–15.6w/c/all) 1990–1996 90 Ruysschaert (2005)

11 The Netherlands 6.2 (3.4–13.4a/c/all) 1972–2001 30 Ruysschaert et al. (2005)

12 The Netherlands 5.9 (3.4–9.8a/c/all) 1978–2000 23 Ruysschaert et al. (2005)

13 The Netherlands 4.7 (0.1–10.3d/c/s) 1984–2004 280 Ruysschaert (2005)

14 The Netherlands 3.5 (0.1–15.5w/r/all) 2004 453 Ruysschaert (2005)

15 The Netherlands 3.3 (2.1–5.3w/c/all) 2004 13 Ruysschaert (2005)

16 The Netherlands 5.2 (0.6–20.8a/r/all) 1984–2004 860 Ruysschaert (2005)

17 The Netherlands 5.0 (2.0–8.0a/c/all) 1984–2004 21 Ruysschaert (2005)

18 The Netherlands 4.6 (0.0–10.9a/c/all) 1949–2004 56 Ruysschaert (2005)

19 France 13.8 (7.7–20.5a/c/all) 1978–2000 23 Ruysschaert et al. (2005)

20 FRG 6.9 (3.7–11.1a/c/all) 1977–1989 13 Ruysschaert et al. (2005)

21 GDR 5.0 (2.0–9.5a/c/all) 1959–1989 31 Ruysschaert et al. (2005)

22 Germany 3.7 (2.2–5.5a/c/all) 1990–2000 11 Ruysschaert et al. (2005)

23 Germany 5.2 (2.2–10.7a/c/all) 1978–2000 23 Ruysschaert et al. (2005)

24 Germany/Bavaria 6.0 (2.9–9.1a/r/all)* 1983–1985 12 Auerswald and Schmidt (1986)

25 Turkey 3.8* (a/c/all) 1989–2000 n.a. Oruc and Gungor (2000) and

Oztas et al. (2002)

26 Belgium 13.3* (a/c/all) 1981–1991 n.a. Anonymous (1994) and FAO (2002)

27 Denmark 10.4* (a/c/all) 1981–1991 n.a. Anonymous (1994) and FAO (2002)

28 France 16.9* (a/c/all) 1981–1991 n.a. Anonymous (1994) and FAO (2002)

29 Germany 8.0* (a/c/all) 1981–1991 n.a. Anonymous (1994) and FAO (2002)

30 UK 4.7* (a/c/all) 1981–1991 n.a. Anonymous (1994) and FAO (2002)

31 Italy 5.3* (a/c/all) 1981–1991 n.a. Anonymous (1994) and FAO (2002)

32 The Netherlands 9.3* (a/c/all) 1981–1991 n.a. Anonymous (1994) and FAO (2002)

33 Northern Spain 5.6* (a/c/all) 1981–1991 n.a. Anonymous (1994) and FAO (2002)

34 Central Belgium �5.0y 1956–1987 n.a. Vanden Berghe and Gulinck (1987)

35 Germany/Bavaria 15.0* n.a. n.a. Maier and Schwertmann (1981)

Mean sugar beet 7.4

Fodder beet

Field data

36 Russia 2.3* (1.9–2.6) 1985 4 Belotserkovsky and Larionov (1988)

37 Russia 3.5 (s)* 1985–1986 1 Belotserkovsky and Larionov (1988)

Mean fodder beet 2.9

Potato

Field data

38 Belgium 3.2 (0.2–21.4) 2002–2003 51 Ruysschaert et al. (2006a)

39 Germany 6.7 (1.0–13.4) 1996–2002 56 Auerswald et al. (2006)

40 China (H) 1.2 (0.2–3.0) 2002 30 Li et al. (2006)

41 Russia 2.5 (1.8–3.4)* 1985 6 Belotserkovsky and Larionov (1988)

Factory data

42 Belgium 2.2 (0.0–45.2i) 1999–2001 1151 Ruysschaert et al. (2006c)

43 Russia 0.6 (0.1–1.1s)* 1985–1986 14 Belotserkovsky and Larionov (1988)

Mean potato 2.7


Table 1 (Continued )

Number Country/region SLCHcrop (Mg ha�1 harvest�1),

mean (min–max)

M.P. n Source

Inulin chicory

Factory data

44 Belgium 8.1 (3.2–12.7a) 1990–1996 7 Poesen et al. (2001)

Witloof chicory

Field data

45 Belgium 11.9 (1.7–70.5) 1996–1997 43 Poesen et al. (2001)

Cassava

Field data

46 Uganda (H) 3.4 (0.4–25.8) 2002–2003 149 Isabirye et al. (in press)

Sweet potato

Field data

47 Uganda (H) 0.1 (0.0–0.2) 2002 20 Isabirye et al. (in press)

Carrot

Factory data

48 Belgium 15.8 (0.5–65.5i) 1995–1996 2001–2002 225 Soenens (1997) and Van Esch (2003)

49 Russia 1.3 (0.7–1.7s)* 1985–1986 2 Belotserkovsky and Larionov (1988)

Black salsify

Factory data

50 Belgium/The Netherlands 6.8 (3.6–19.0i) 1995 77 Soenens (1997)

51 Belgium/The Netherlands 10.8 (1.4–28.4i) 2001–2002 95 Ruysschaert (2005)

Radish

Factory data

52 Russia 1.7 (s)* 1986 1 Belotserkovsky and Larionov (1988)

M.P., measurement period (year); n, number of observations; H, harvest by hand instead of by machine for the other studies; FRG, former West Germany; GDR,

former East Germany; y, SLCHy (Mg ha�1 year�1) instead of SLCHcrop; *SLCHcrop = mass of oven-dry soil + mass of soil moisture instead of mass of oven-dry

soil only; i, minimum and maximum values for individual deliveries; a, based on annual averages; d, based on daily averages; w, based on weekly averages; c,

based on averages for the country; r, based on regional averages; s, based on a selective number of data; all, based on all factory data; n.a., not available.

weekly or annual) and spatial scale (regional or national) of

data based on soil tare values from factories is indicated.

SLCHcrop values varied from few Mg to tens of

Mg ha�1 harvest�1, with a maximum observed of

100 Mg ha�1 harvest�1 for a sugar beet delivery to a factory

in Belgium (Poesen et al., 2001). Considerable variability in

SLCH values was observed at various temporal and spatial

scales. Differences in SLCHcrop values for manually

harvested sugar beet in Belgium, within a field plot, were

at maximum 14.2 Mg ha�1 harvest�1. This was for a field plot

with highly variable sand content of the soil (Ruysschaert,

2005). Total SLCHcrop values (i.e., adhering soil and soil

clods) for a potato field (ca. 1.7 ha large), sampled several

times during the harvesting season of 2002, ranged between

1.0 and 4.9 Mg ha�1 harvest�1. Total soil losses could be

divided in adhering soil and loose soil (soil clods). The

adhering soil loss component appeared to vary mainly over

time, while the loose soil loss component showed mainly

within field plot differences (Ruysschaert et al., 2006a).

Spatial differences in weekly average SLCH values (i.e.,

average of SLCH values for all sugar beet deliveries to the

district factory in a given week) for 40 Dutch sugar beet

districts were on average 6.5 Mg ha�1 harvest�1 in 2004,

which was larger than the temporal variation within that

season per district, i.e., on average 4.5 Mg ha�1 harvest�1.

The opposite could be concluded from annual average SLCH

values (i.e., average of the SLCH values for all sugar beet

deliveries to the district factory in a given harvesting season)

for the 1984–2004 period; the temporal variability per district

was on average 7.7 Mg ha�1 harvest�1, which is larger than

the yearly differences between the districts, i.e., on average

5.6 Mg ha�1 harvest�1 (Ruysschaert, 2005).

An overview of the harvesting conditions of the field

studies listed in Table 1, is provided in Table 2. This table

distinguishes between mechanized harvesting and harvest-

ing by hand and forms the basis for the analyses of Sections

3.2, 3.3 and 3.4.

3.2. SLCH for manually and mechanically harvested

sugar beet grown in contrasting agro-ecological

environments

Four experiments on soil losses due to sugar beet

harvesting could be compared; two on manual harvesting

and two on mechanized harvesting (Table 2).

The study of Duval (1988) on mechanically harvested

sugar beets in the French sugar beet region (northern France)

(Tables 1 and 2, no. 2) is discussed by Ruysschaert et al.


Table 2

Overview of field studies in which soil losses during crop harvest (SLCH) have been measured

Mechanized harvest

Crop type Sugar beet Sugar beet Potato Witloof chicory

Study number* 1 2 38 45

Source Ruysschaert et al. (2006b) Duval (1988) Ruysschaert et al. (2006a) Poesen et al. (2001)

Country Belgium France Belgium Belgium

n 611 82 51 43

SLCHspec (Mg Mg�1) 0.047 (0.009–0.460) 0.255 (0.037–0.806) 0.069 (0.008–0.565) 0.270 (0.019–1.03)

SLCHcrop (Mg ha�1 harvest�1) 3.6 (0.7–30.1) 14.0 (2.0–44.3) 3.2 (0.2–21.4) 11.9 (1.7–70.5)

GMC (g g�1) 0.21 (0.08–0.35) 0.19 (0.06–0.29) 0.15 (0.06–0.24) 0.21 (0.12–0.34)

%Clay 15 (7–36) n.a. (10–30) 10 (2–20) 10 (0–49)

%Sand 28 (11–65) n.a. 40 (11–86) 48 (9–86)

Soil type Haplic Luvisols/eutric

Cambisols/eutric Regosols (i)

Calcaric/calcic/haplic

Luvisols (ii)

Haplic Luvisols/eutric

Cambisols/plaggic

Anthrosols (i)

Haplic Luvisols/eutric

Cambisols/eutric Regosols (i)

Mcrop/p (kg) 0.9 (0.4–1.6) n.a. 0.1 (0.06–0.2) 0.21 (0.08–0.36)

Mcy (Mg ha�1) 79 (38–104) n.a.** 48 (26–79) 44 (19–87)

Seedbed Flat Flat Ridge Flat

Manual harvest

Crop type Sugar beet Sugar beet Potato Cassava Sweet potato

Study number 3 4 40 46 47

Source Ruysschaert (2005) Li et al. (2006) Li et al. (2006) Isabirye et al.

(in press)

Isabirye et al.

(in press)

Country Belgium China China Uganda Uganda

n 48 14 30 149 20

SLCHspec (Mg Mg�1) 0.18 (0.07–0.35) 0.014 (0.005–0.029) 0.032 (0.008–0.065) 0.021 (0.003–0.161) 0.003 (0.002–0.007)

SLCHcrop

(Mg ha�1 harvest�1)

13.4 (5.6–25.7) 1.0 (0.2–1.9) 1.2 (0.2–3.0) 3.4 (0.4–25.8) 0.1 (0.0–0.2)

GMC (g g�1) 0.22 (0.14–0.28) 0.16 (0.10–0.24) 0.15 (0.07–0.24) 0.13 (0.04–0.35) 0.09 (0.04–0.11)

%Clay 17 (12–21) 30 (24–38) 27 (16–39) 23 (9–39) 23 (23–26)

%Sand 15 (9–47) 15 (6–25) 25 (7–52) 67 (56–80) 68 (66–68)

Soil type Haplic Luvisols/eutric

Cambisols/eutric

Regosols (i)

Haplic Chernozems/haplic

Phaeozems/haplic

Kastanozems/calcic

Cambisols (iii)

Haplic Chernozems/haplic

Phaeozems/haplic

Kastanozems/calcic

Cambisols (iii)

Rhodi lixic ferralsols Rhodi lixic

ferralsols

Mcrop/p (kg) 1.0 (0.6–2.1) 0.70 (0.40–1.02) 0.14 (0.95–0.29) n.a. n.a.

Mcy (Mg ha�1) 77 (44–114) 64 (42–91) 36 (18–78) 161 28

Seedbed Flat Ridge Ridge Flat Mound

Distinction is made between manually and mechanically harvested crops. Besides the mean values, observed minimum and maximum values are indicated

between brackets. *See Table 1; **a sugar beet yield of 55 Mg ha�1 was assumed for calculation of SLCHcrop. (i) Belgian soil map (1:20 000); committee for

mapping soils and vegetation in Belgium and FAO et al. (1998); (ii) Duval (1988) and FAO et al. (1998); (iii) FAO (1974); n, number of observations; GMC,

gravimetric soil moisture content at harvest; Mcrop/p, mean root or tuber mass; Mcy, net crop yield; n.a., not available.

(2004). The most important predictor variable was gravi-

metric soil moisture content (GMC) during the harvest,

which was exponentially and positively related to SLCHspec

(R2 = 0.50). Other factors that could explain part of the

variability were %clay, soil organic matter content and

diameter of the beet crown.

The second data set on mechanically harvested sugar

beets (Tables 1 and 2, no. 1) is described by Ruysschaert

et al. (2006b) and is based on soil losses occurring during the

harvest of beets grown for sugar beet variety trials,

representatively distributed over the Belgian sugar beet

area and organised by the sugar beet research institute

(KBIVB-IRBAB). GMC was also the best predictor variable

in this study and, in accordance with Duval (1988),

positively and exponentially related to SLCHspec. Other

factors determining SLCHspec were %clay, mean beet mass

(Mcrop/p) and plant density (PD).

Sugar beet was manually harvested in Belgium during an

experiment investigating topography-induced variability of

SLCH (Ruysschaert, 2005; Tables 1 and 2, no. 3).

Researchers harvested sugar beet following a standard

procedure. In this study, only 18% of the variability could be

explained by a positive and linear relationship with GMC.

Soil organic matter content, mean beet mass and plant

density were other factors determining SLCHspec.

Li et al. (2006) measured soil losses caused by the

harvest of sugar beets in northeast China (Tables 1 and 2,

no. 4). In this study, the sugar beets were manually

harvested by farmers (owners of the field plots) as they are

used to do it in practice. The coefficient of determination

was largest for positive power (R2 = 0.50) and exponential

(R2 = 0.47) regression equations between GMC and

SLCHspec. Good relationships were also obtained with

soil texture, mean root mass, plant density and crop yield.


The correlation with %clay was, in contrast with the

studies by Duval (1988) and Ruysschaert et al. (2006b; no.

1), negative and could be attributed to co-linearity between

the independent variables.

Fig. 1. Illustration of the studies on soil losses due to crop harvesting (SLCH) for s

(SLCHcrop) and gravimetric soil moisture content during the harvest (GMC) and

natural logarithm of mass-specific SLCH (SLCHspec; Mg Mg�1) and GMC. Bold

dummy variables for each study as independent variables (Eq. (4); R2 = 0.84), wh

GMC fitted for each study separately.

From all four studies, it could be concluded that GMC is a

key factor explaining SLCH variability. In Fig. 1(a), SLCHcrop

is plotted against GMC. Large differences in SLCHcrop and

SLCHspec values between the four studies exist for similar soil

ugar beet described in Table 2. (a) Scatter plot between crop-specific SLCH

the exponential curves fitted through the data. (b) Scatter plot between the

lines represent the results of the linear regression analysis with GMC and

ile the regular lines indicate the regression lines between ln(SLCHspec) and


moisture contents. The linear regression equation for the

natural logarithm of SLCHspec (ln(SLCHspec)) with GMC and

study type, reflecting the overall effect of soil, agronomic

practices and harvesting technique related factors, as

independent variables yielded the following result:

lnðSLCHspecÞ

¼ �5:42þ 10:43 GMC� 0:64 dumHC þ 1:38 dumHB

þ 1:83 dumMF;

p< 0:0001; R2-adj: ¼ 0:84

(4)

where GMC is the gravimetric soil moisture content at

harvesting time (g g�1), dumHC = 1 for sugar beet harvested

by hand in China (Li et al., 2006; no. 4), dumHB = 1 for sugar

beet harvested by hand in Belgium (Ruysschaert, 2005; no.

3) and dumMF = 1 for mechanized harvested sugar beet in

France (Duval, 1988; no. 2). In all other cases the dummy

variables are zero. All parameters were significant

( p < 0.0001).

Fig. 1(b) illustrates this regression equation by means of

bold lines, while regular (thin) lines are results of the

regression analysis between ln(SLCHspec) and GMC for all

four studies separately. The regular and bold lines are in

good agreement for mechanized sugar beet harvesting in

Belgium and France and manual harvesting in China. This

means that the relative effect of GMC on ln(SLCHspec) is

equal in these studies but that there is a constant difference in

ln(SLCHspec) values for similar soil moisture contents. An

exception is the study on manually harvested sugar beets in

Belgium. The regression is biased by SLCHspec values at the

lowest soil moisture contents. Hard and dry soil clods were

attached to the rootlets and were not broken by the standard

cleaning procedure applied. This is in contrast with

mechanized harvesting during which rootlets are broken

when the beets are uplifted. Omitting the data for the soil

moisture contents <0.19 g g�1 yielded a slope of the

regression equation that is larger than the slopes for the other

studies, but this is possibly attributed to the limited soil

moisture range. Although sugar beet in China was also

manually harvested, soil clods were not removed from the

field at dry conditions. A crucial difference between both

studies is the harvesting operator. In Belgium, researchers

applied a standard cleaning procedure for the harvest

regardless of the soil conditions, whereas in China farmers

harvested the crop. Farmers might decide to adjust the

harvesting technique according to the soil conditions to

make sure that they never need to transport soil clods, and

thus extra weight, from the field.

The question remains as to what the systematic

differences between the studies (intercept of the regression

lines) can be assigned to. As soil texture and mean beet mass

appeared also to be important determining factors for

SLCHspec, it was investigated whether there was correlation

between the residuals of Eq. (4) and %clay, %sand and mean

beet mass (Mcrop/p). The study by Duval (1988) was not

included in this analysis as data on soil texture and Mcrop/p

were not available. Systematic differences between the

studies could not be attributed to soil texture and mean beet

mass. Clay contents were considerably larger for the

Chinese experiments (Table 2), but this did not yield larger

SLCHspec values as would be expected from other studies.

It may thus be assumed that the systematic differences

between the studies (intercepts of the bold lines of Fig. 1) are

mainly attributed to differences in harvesting technique and

agronomic practices. It cannot be concluded that harvesting

sugar beets by hand systematically leads to lower SLCHspec

values (Fig. 1) as the manually harvested sugar beet in

Belgium caused larger soil losses than the mechanically

harvested sugar beets. The smaller SLCH values of the latter

were caused by the fact that sugar beet was harvested under

experimental conditions with a special designed machine

and at very low speed and with high precision. SLCH values

for manually harvested sugar beet in China were smallest

and this might, besides harvesting technique, also have been

caused by the fact that the sugar beet was, in contrast to West

Europe, grown in soil types rich in organic matter and

planted on ridges. Possible effects of the ridges may be that

sugar beet develops less side branches of the tap root

between which soil can adhere and that the looser soil of the

ridges sticks less to the beet.

The GMC values of the studies indicated on Fig. 1 are

representative for the range of soil moisture contents at

which sugar beet harvesting is possible. The difference in

predicted SLCHspec values (Eq. (4)), caused by these

differences in GMC (0.05–0.30 g g�1), was at minimum

0.05 Mg Mg�1 (manually harvested sugar beet in China)

and at maximum 0.58 Mg Mg�1 (mechanically harvested

sugar beet in France). The difference in SLCHspec, mainly

caused by harvesting technique, is dependent on the soil

moisture content. If the soil is dry (GMC = 0.05 g g�1), the

maximum difference in SLCHspec values between the

studies is only 0.04 Mg Mg�1. However, for wet soils

(GMC = 0.30 g g�1), this maximum difference rose to

0.58 Mg Mg�1. Therefore, it can be concluded that soil

moisture content and harvesting technique can contribute

equally to the variability in SLCHspec for sugar beet.

3.3. SLCH for manually and mechanically harvested

potato grown in contrasting agro-ecological

environments

Total soil losses for mechanized potato harvesting in

Belgium (Ruysschaert et al., 2006a; Tables 1 and 2, no. 38)

were significantly ( p < 0.01) larger than soil losses measured

during manual potato harvesting in northeast China (Li et al.,

2006; Tables 1 and 2, no. 40). In both studies farmers

harvested potatoes using the typical technique for the area.

The Chinese study yielded a mean SLCHspec value of

0.032 Mg Mg�1 and a mean SLCHcrop value of 1.2 Mg ha�1


harvest�1 with a maximum of 3.0 Mg ha�1 harvest�1. Mean

total SLCHspec (0.069 Mg Mg�1) and mean total SLCHcrop

(3.2 Mg ha�1 harvest�1) values for mechanically harvested

potato in Belgium were larger than the maximum values

for China.

Maximum soil loss measured for potato harvesting in

Belgium was 21.4 Mg ha�1 harvest�1. The large variability

in soil losses for mechanically harvested potatoes is caused

by the occurrence of soil clods. The harvesting machine lifts

the entire soil ridge. Not all clods can be separated from the

potatoes and are hence exported from the field. No soil clods

are exported if potatoes are harvested manually and then soil

losses are only caused by soil adhering to the potatoes.

SLCH for mechanically harvested potatoes is also limited to

adhering soil losses if all soil clods are removed by persons

Fig. 2. Box plots of soil losses due to crop harvesting (SLCH) for different stud

(SLCHspec) and crop-specific SLCH (SLCHcrop). Numbers on the X-axis correspo

witloof chicory; C, cassava; SP, sweet potato. Grey coloured boxes correspond to

studies from China and Uganda.

working at the sorting table of the harvesting machine. Both

adhering SLCHspec and adhering SLCHcrop did not

significantly differ between both studies.

More than half of the variability in adhering SLCHspec

values for Belgium could be explained by soil moisture

content at harvesting time, but this factor was not significant

in the Chinese study. An important factor determining

SLCHspec for potato in China was %clay. Regression

analysis (R2 = 0.46) with %clay and a dummy variable for

study type learned that adhering SLCHspec is more or less

similarly related to %clay for both studies but also that

adhering SLCHspec values in Belgium are significantly

larger compared to China for similar clay contents. The

explanatory value (R2 = 0.49) could slightly be improved by

adding GMC to %clay and the dummy variable, but partial

ies reported in Table 2. Distinction is made between mass-specific SLCH

nd to the ‘study numbers’ of Tables 1 and 2. SB, sugar beet; P, potato; WC,

studies from Belgium or France, while white coloured boxes correspond to


correlation coefficients (Pcorr; type II sums of squares)

revealed that %clay (Pcorr = 0.36) is the most important

variable, followed by study type (Pcorr = 0.20), representing

overall differences in crop and harvesting technique related

factors, and GMC (Pcorr = 0.09). Another possible explana-

tion for the differences in SLCH between both studies could

also be attributed to the different soil types, which were in

China (haplic Chernozems/haplic Phaeozems/haplic Kasta-

nozems/calcic Cambisols) richer in organic matter than in

Belgium (haplic Luvisols/eutric Cambisols/plaggic Anthro-

sols).

3.4. Comparison between SLCH values for several crop

types and harvesting techniques in contrasting agro-

ecological environments

One study on mechanically harvested witloof chicory

roots in Belgium (Poesen et al., 2001; Tables 1 and 2, no. 45)

and another study on manually harvested cassava and sweet

potato in Uganda (Isabirye et al., in press; Tables 1 and 2,

Fig. 3. Scatter plots between soil moisture content (GMC) and the natural logarit

Mg Mg�1) for each study described in Table 2. The lines are the results of the regressi

study, but without interaction term. The slope of the regression equals 7.6. SB, sugar

efficiency values (Nash and Sutcliffe, 1970). Dashed, bold lines are for crops harveste

nos. 46 and 47) were added to the studies on SLCH for

potato and sugar beet, described in the previous sections, for

overall comparison between SLCH values for different crop

types, harvesting techniques and agro-ecological environ-

ments. At the global scale, the areas where SLCH may occur

are 19,940,000 ha for potato, 17,032,000 ha for cassava,

9,112,000 ha for sweet potato, 5,969,000 ha for sugar beet

and 24,000 ha for chicory roots. In this study, four out of the

five most important SLCH crops are included, representing

59 per cent of the world area subject to SLCH (FAO, 2002;

based on data for 2000). All studies are summarised by box

plots in Fig. 2.

The explanatory values of gravimetric soil moisture

content at harvesting time (GMC), percentage clay,

percentage sand, mean crop mass (Mcrop/p), specific soil–

crop contact area (Ss), crop type (i.e., sugar beet, potato,

witloof cichory, cassava, sweet potato), harvesting technique

(mechanized versus manual), seed bed (mounds or ridges

versus flat) and study type (each study number of Table 2

being considered as separate study type) for SLCHspec

hm (ln) of total mass-specific soil losses due to crop harvesting (SLCHspec;

on (R2 = 0.79) between ln(SLCHspec) and GMC and dummy variables for each

beet; P, potato; WC, witloof chicory; C, cassava; SP, sweet potato; ME, model

d by hand (H), while solid thin lines are for mechanically (M) harvested crops.


variability were calculated. Study type represents a

combination of controlling factors related to soil, crop type

and variety, harvesting technique and agronomic practices.

The best results were obtained for the natural logarithm of

SLCHspec (ln(SLCHspec)) and the most important explana-

tory variable for all data was study type (R2 = 0.69),

followed by crop type (R2 = 0.38) and GMC (R2 = 0.30). If

soil moisture content at harvest is added to study type, 79%

of the variability of ln(SLCHspec) could be explained. In

general, SLCHspec is thus exponentially related to GMC.

The results of the linear regression model between

ln(SLCHspec) and GMC and dummy variables for study

type (without interaction term) is illustrated in Fig. 3. The

model efficiencies (Nash and Sutcliffe, 1970) for this model

calculated for each data set is shown as part of the study code

on Fig. 3. The values of ME in principle can range from�1to 1. The closer ME is to one, the better SLCH is predicted

by the model. The model efficiencies were in general largest

for the studies on sugar beet, but the predictive power for the

other crops was rather low, indicating that the effect of GMC

on SLCHspec is not equal for all crop types. This is also

indicated by the fact that the interaction term for the

regression model between ln(SLCHspec) and GMC and study

type is significant as well. If this interaction term is included,

the model has a coefficient of determination of 0.81.

Fig. 4 illustrates this interaction by showing both the

regression lines for the model shown in Fig. 3 and the

regression lines between ln(SLCHspec) and GMC for each

Fig. 4. Results of the linear regression between soil moisture content (GMC) a

explanation of the symbols) and the natural logarithm of total mass-specific soil lo

and long dashed lines (mechanized harvest) show the results of the regressions f

data set separately. Adding %clay, %sand, Mcrop/p or Ss to

the model hardly enlarged the coefficient of determination of

the regressions. Regression equations with GMC and/or soil

texture and/or mean crop mass performed worse if study

type was not included, indicating that overall differences in

harvesting technique, crop characteristics, agronomic

practices and possibly also clay mineralogy and soil organic

matter content had an important effect on SLCH variability.

Although the categorical variable harvesting technique

(mechanized versus manual) appeared not to be one of the

most important explanatory variables, from Fig. 2 and the

illustrated statistical analysis in Fig. 3, it is clear that

manually harvested crops generally lead to smaller soil

losses than crops harvested by machines. There were two

exceptions. The first one is for mechanically harvested sugar

beet in Belgium (Ruysschaert et al., 2006b; no. 1). These

data were collected during beet variety trials and do not

entirely represent normal harvesting conditions; the sugar

beets were harvested with a specially designed machine

harvesting at very low speed and with high precision. The

second exception is the study on manually harvested sugar

beet in Belgium (Ruysschaert, 2005; no. 3). Unlike the other

manually harvested crops, sugar beets were harvested in this

study by researchers. The harvesting method may not have

been representative for manual harvest by farmers. The latter

most likely make sure that soil adhering to the roots is

reduced by manual cleaning in order to avoid extra weight

that needs to be transported from the field. Soil type could

nd dummy variables for each study described in Table 2 (see Fig. 3 for

sses due to crop harvesting (SLCHspec; Mg Mg�1). Dotted (manual harvest)

or each study separately.


also have contributed to the fact that SLCH was smaller in

China and in Uganda than in Belgium and France. Soils in

China were rich in organic matter and the physical properties

of soils in Uganda might have been different due to the

presence of pseudo-sand (i.e., stable micro-aggregates).

Although crop type could explain 38% of the variability

in ln(SLCHspec), SLCH for potato was not systematically

larger or smaller than for sugar beet. The slope parameters of

the regression equations between ln(SLCHspec) and GMC,

established for each study separately (Fig. 4), appeared to be

very similar for three of the four studies on sugar beet. This

may indicate that the slope parameter of the exponential

regression equation is crop type dependent. More research

on other crops is needed to verify this hypothesis.

3.5. Effect of specific soil–crop contact area on

mass-specific SLCH

Based on the field studies reported in the previous

section, the specific soil–crop contact area (Ss) could not be

assigned as a major determining factor of SLCHspec,

although it was expected that harvesting smaller roots and

tubers would lead to larger soil losses.

In Fig. 5, SLCHspec is plotted against estimated Ss for the

field studies described in the previous section and for

additional studies based on individual deliveries to crop

processing factories, i.e., for carrot (Soenens, 1997; Van

Esch, 2003; Table 1, no. 48) and black salsify (Ruysschaert,

Fig. 5. Effect of the specific soil–crop contact area (Ss) on adhering mass-specific

studies and for data derived from individual deliveries to crop-processing factories a

75th percentile) for these studies. The other symbols represent averages for regiona

study numbers refer to Tables 1 and 2. M, mechanized harvest; H, harvest by hand; B

regression between Ss and SLCHspec means is shown as well.

2005; Table 1, no. 51). For mechanically harvested potatoes,

only adhering SLCHspec was plotted. For the other crops, it

was assumed that soil losses only consisted of adhering soil.

In addition, national average SLCHspec values for sugar beet

for Belgium (Table 1, no. 7), The Netherlands (Table 1, no.

12), France (Table 1, no. 19) and Germany (Table 1, no. 23)

(1978–2000 period; Ruysschaert et al., 2005), for inulin

chicory for Belgium (Poesen et al., 2001; 1990–1996 period;

Table 1, no. 44) and average SLCHspec values for black

salsify for some deliveries from Belgium and The Nether-

lands (Soenens, 1997; 1995–1996 period; Table 1, no. 50)

are plotted on Fig. 5 as well.

Linear regression through the means of each study could

explain 43% of the variability (plotted line on Fig. 5). The

intercept of this regression is not significant ( p = 0.75). This

was expected as no soil loss occurs if the soil–crop contact

area is zero. SLCHspec values for potato and sweet potato

were considerably smaller than expected from their Ss value.

This is most probably attributed to a smoother crop skin

compared to the other crops and the fact that (sweet)

potatoes do not have side branches or root grooves in

contrast to sugar beet and/or cassava. If only taproot crops,

i.e., sugar beet, chicory root, carrot and black salsify, are

considered, Ss could even explain 66% of the study means.

For some conditions, SLCH for sugar beet (small Ss) was as

large as for crops with much larger specific soil–crop contact

areas, indicating that other factors such as harvesting

technique can play an equally important role as crop type for

soil losses due to crop harvesting (SLCHspec). Means of SLCHspec for field

re indicated by diamonds. Vertical lines indicate SLCHspec variability (25th–

l SLCHspec data derived from soil tare values from processing factories. The

, Belgium; F, France; NL, The Netherlands; U, Uganda, C, China. The linear


SLCHspec variability. More research on SLCH for different

crop types, harvested under similar conditions is needed to

obtain a better understanding of the role of crop type for

SLCHspec variability.

4. Conclusions

SLCH values measured at various spatial and temporal

scales and for various crop types and agro-ecological

conditions vary between few to tens of Mg ha�1 harvest�1.

On cropland, SLCH may thus be as important as soil losses

by water and tillage erosion and should therefore not be

neglected in soil erosion research.

A comparison of soil losses due to sugar beet harvesting

reported in four studies revealed that harvesting technique

and soil moisture content during the harvest can be equally

important for explaining SLCHspec variability. Differences

in SLCH were not only found between manually and

mechanically harvested sugar beet but also between studies

within one of these groups.

Stable soil clods induce the largest variations in soil

losses caused by mechanically harvested potatoes. These

soil clods are not exported from the field if potatoes are

harvested by hand. As a consequence, differences in

harvesting technique are the main reason why SLCH values

for potato were larger in Belgium than in China.

In general, SLCHspec values measured in non-mechan-

ized agricultural systems were smaller than for mechanized

agricultural systems in Europe. Overall, it can be stated that

it is not only difficult to extrapolate results from mechanized

agriculture in Europe to non-mechanized agricultural

systems elsewhere but also within Europe, large variability

in SLCH may exist due to differences in harvesting

technique.

Soil moisture content at harvesting time (GMC) was,

besides harvesting technique, one of the most important

factors explaining SLCH variability. SLCH increases in

general exponentially with GMC, but the effect of GMC on

SLCHspec was not the same for each crop type. The slope of

the linear regression between ln(SLCHspec) and GMC was

similar for most studies on sugar beet. More research on

other crop types is needed to verify if this slope parameter is

crop type dependent. Soil properties other than texture and

moisture content such as clay mineralogy and soil organic

matter may also be important at the continental and world

scale. More research outside Europe is needed for testing the

importance of these factors.

No systematic differences in SLCH between crop types

could be found, e.g., potato versus sugar beet, if only field

studies were considered. For a larger number of crop types,

the specific soil–crop contact area could explain more than

40% of the variability in SLCHspec.

The obtained results allow one to make a first assessment

of SLCH for various crops grown in different agro-

ecological environments.

Acknowledgement

This study is financially supported by the Fund for

Scientific Research-Flanders (FWO-Vlaanderen) (project

G.0167.02).

References

Anonymous, 1994. Evolution des materiels de recolte. Le Betteravier

francais Hors serie 27, 10–11.

Auerswald, K., Schmidt, F., 1986. Atlas der Erosionsgefahrdung in Bayern.

GLA-Fachberichte 1, Munchen 1, 74 pp.

Auerswald, K., Gerl, G., Kainz, M., 2006. Influence of cropping system on

harvest erosion under potato. Soil Till. Res. 89 (1), 22–34.

Belotserkovsky, Y., Larionov, A., 1988. Removal of soil by harvest of

potatoes and root crops. Vestnik Moskovskogo Universiteta Seriia 5:

Geografia 4, 49–54 (in Russian).

Duval, Y., 1988. Pour reduire la tare, connaıtre et observer les sols. Le

Betteravier Francais 531, 27–29.

FAO, 1974. FAO-UNESCO Soil Map of the World, 1:5000000. UNESCO,

Paris.

FAO, 2002. FAOSTAT. Agriculture Data. Agricultural Production. http://

www.apps.fao.org (accessed 22 May 2002).

FAO, ISRIC, ISSS, 1998. World Reference Base for Soil Resources. World

Soil Resources Report, vol. 84. FAO, Rome, 88 pp.

Isabirye, M., Ruysschaert, G., Van Linden, L., Poesen, J., Magunda, M.K.,

Deckers, J., in press. Soil losses due to cassava and sweet potato

harvesting: a case study from low input traditional agriculture. Soil

Till. Res.

Koch, H.J., 1996. Moglichkeiten und Grenzen der Verringerung des Erdan-

hangs von Zuckerruben durch Bodenbearbeitung, Bestandesdichte, N-

Dungung, Sorte und Abreinigung. In: Proceedings of the 59th IIRB

Congress, Brussels, Belgium, pp. 483–497.

Li, Y., Ruysschaert, G., Poesen, J., Zhang, Q.W., Bai, L.Y., Li, L., Sun, L.F.,

2006. Soil losses due to potato and sugar beet harvesting in NE China.

Earth Surf. Process. Landf. 31 (8), 1003–1016.

Maier, J., Schwertmann, U., 1981. Das Ausmass des Bodenabtrags in einer

Losslandschaft Niederbayerns. Bayerisches Landwirtschaftliches Jahr-

buch 58 (2), 194.

Nash, J.E., Sutcliffe, J.V., 1970. River flow forecasting through

conceptual models. Part I. A discussion of principles. J. Hydrol.

10, 282–290.

Oruc, N., Gungor, H., 2000. A study on the soil tare of sugar beet in

Eskisehir-Turkey. In: Proceedings of the International Symposium

on Desertification. Konya, (Accessed 2 September 2004), pp. 258–

261.

Oztas, T., Ozbek, A.K., Turan, M., 2002. The cost of soil lost from fields due

to removal on harvested sugarbeet: a case study in Turkey. Soil Use

Manage. 18, 236–237.

Poesen, J.W.A., Verstraeten, G., Seynaeve, L., Soenens, R., 1999. Soil losses

caused by chicory root and sugar beet harvesting in Belgium: impor-

tance and implications. In: Stott, D.E., Mohtar, R.H., Steinhardt, G.C.

(Eds.), Sustaining the Global Farm. Selected papers from the 10th

International Soil Conservation Organization Meeting, Purdue Univer-

sity and the USDA-ARS National Soil Erosion Research Laboratory,

May 24–29, pp. 312–316.

Poesen, J.W.A., Verstraeten, G., Soenens, R., Seynaeve, L., 2001. Soil losses

due to harvesting of chicory roots and sugar beet: an underrated

geomorphic process? Catena 43, 35–47.

Ruysschaert, G., 2005. Spatial and temporal variability of soil losses due to

crop harvesting. Unpublished PhD Thesis, Department of Geography-

Geology, K.U. Leuven, Leuven, Belgium.

Ruysschaert, G., Poesen, J., Verstraeten, G., Govers, G., 2004. Soil loss due

to crop harvesting: significance and determining factors. Prog. Phys.

Geogr. 28 (4), 467–501.

http://www.apps.fao.org/

http://www.apps.fao.org/

http://www.topsak.org.tr/isd/isd-46.htm


Ruysschaert, G., Poesen, J., Verstraeten, G., Govers, G., 2005. Interannual

variation of soil losses due to sugar beet harvesting in West Europe.

Agric. Ecosyst. Environ. 107, 317–329.

Ruysschaert, G., Poesen, J., Verstraeten, G., Govers, G., 2006a. Soil losses

due to mechanized potato harvesting. Soil Till. Res. 86 (1), 52–72 DOI

information: doi:10.1016/j.still.2005.02.016.

Ruysschaert, G., Poesen, J., Wauters, A., Verstraeten, G., Govers, G., 2006b.

Factors controlling soil loss during sugar beet harvesting at field plot

scale in Belgium. Eur. J. Soil Sci., submitted for publication.

Ruysschaert, G., Poesen, J., Auerswald, K., Verstraeten, G., Govers, G.,

2006c. Soil losses due to potato harvesting at the regional scale in

Belgium. Soil Use Manage., submitted for publication.

SAS Institute Inc., 1999. SAS/Enterprise Guide version 2.0.0.417.

Soenens, R., 1997. Bodemverlies bij het rooien van wortelgewassen.

Unpublished MSc Thesis, Department of Geography-Geology, K.U.

Leuven, Leuven.

Van Esch, L., 2003. Bodemverliezen ten gevolge van het rooien van

wortelen (Daucus carota L.). Unpublished MSc Thesis, Department

of Geography-Geology, K.U. Leuven, Leuven.

Vanden Berghe, I., Gulinck, H., 1987. Fallout 137Cs as a tracer for soil

mobility in the landscape framework of the Belgian loamy region.

Pedologie 37 (1), 5–20.

Vermeulen, G.D., 2001. Reduction of soil tare by improved uprooting of

sugar beet; a soil dynamic approach. PhD Thesis, Wageningen Uni-

versity, Wageningen, The Netherlands.

doi:10.1016/j.still.2005.02.016

soil loss due to harvesting of various crop types in contrasting agro-ecological environments

Documents