J. agric. Engng Res. (2001) 79 (2), 231}237doi:10.1006/jaer.2000.0693, available online at http://www.idealibrary.com onSW*Soil and Water

Crop Residue Management E!ects on Soil Mechanical Impedance

M. Maiorana; A. Castrignano; F. Fornaro

Istituto Sperimentale Agronomico, Via C. Ulpiani 5, 70125 Bari, Italy; e-mail of corresponding author: a. castrignano: agronba@interbusiness.it

(Received 29 May 2000; accepted in revised form 15 December 2000; published online 5 April 2001)

Soil penetration resistance was evaluated in di!erent crop residue management practices. The experimentaldesign was a randomized complete block with "ve replications (block). The soil strength data, measuredto a depth of 52)5 cm using a recording penetrometer, were corrected to a common water content andthen submitted to a multivariate approach consisting of a combination of principal component analysis(PCA) and multivariate variance analysis, considering crop season and sampling date within season as repeatedfactors. The "rst two principal components (PC) explained 95% of the variance. The "rst one, related to the&25}52 cm deep layer, accounted for 84% of total variance, while the second PC, which seems to measure thepenetration resistance at 3}25 cm depth, explained more than 11% of total variance. The results of varianceanalysis proved that crop residue management had signi"cant e!ects on soil penetration resistance only for the"rst PC. Crop season, date of measurement within each season, the two-way interactions: season with date,season with management, date with management and the three-way interactions: season with date and block,and season with date and management were highly signi"cant in both PCs. This study has also shown thelocation e!ect of penetrometer measurements is fundamental when soil characteristics are altered by cropresidue management.

( 2001 Silsoe Research Institute

1. Introduction

In southern Italy, the scanty use of animal manure andthe cultivation of winter cereals in continuous croppingare causing, as years go by, a decrease in soil organicmatter and main nutrient components, not alwayscounterbalanced by the application of increasing levels ofmineral fertilizers. Soil management procedures, that ad-dress soil chemical and organic fertility conservation onsustainable crop yield need to be developed. Amongthese, ploughing in of crop residue can compensate forthe loss of soil organic matter content (Convertini et al.,1998) and slow down the progressive deterioration ofsome chemical and physical soil properties. Nevertheless,stubble and straw burning is still widely practised incropping systems in Mediterranean areas and is oftenutilized as a means of reducing crop residue loads on soilsurface. In the light of these considerations, the Ag-ronomic Research Institute has been carrying outa long-term study, started in 1978 and still in progress, ondi!erent straw and stubble management practices in

0021-8634/01/060231#07 $35.00/0 23

a continuous cropping of durum wheat. The resultsconcerning the quanti}qualitative aspects of productionand some chemical characteristics of soil have been re-ported (Convertini et al., 1985; Di Bari et al., 1987;Maiorana et al., 1992). This paper reports the e!ectsover time of those treatments on one of the most impor-tant physical soil parameters, the soil strength. Itsmeasurement is important in agriculture as it character-izes mechanical impedance to root penetration. Never-theless, cone penetration resistance measurements havenot yet been developed to such a point that a routinemeasurement is unambiguous enough for precise recom-mendations for modi"cation of soil. An important aspectof why it is di$cult to interpret resistance dataunambiguously is that soil strength is a dynamic charac-teristic, depending on many soil physical and chemicalproperties, water content, position, depth and soil man-agement procedures. Therefore, we developed a statist-ical analysis able to show statistically signi"cantdi!erences in mechanical impedance for various manage-ment practices.

1 ( 2001 Silsoe Research Institute

Table 1List of the crop residue management treatments

Crop residuetreatments

Nitrogen onresidue,kg ha~1

Water onresidue,m3 ha~1

Treatmentsidentixcation

Burning * * BPloughing in * * PPloughing in 50 * PN

1100 * PN

2150 * PN

3Ploughing in 50 500 PN

1W

100 500 PN2W

150 500 PN3W

M. MAIORANA E¹ A¸ .232

2. Materials and methods

2.1. ¹he site and the climate

The experiment was carried out at Foggia (41327@latitude N, 15336@ longitude E, 90 m above sea level), ina typical coastal area of southern Italy, the ApulianTavoliere, in the experimental farm of the Institute. Themain crop in the area is durum wheat in continuouscropping or in rotation with industrial crops (sugar beet,sun#ower, tomato), pulses and vegetables.

The soil is a silty}clay Vertisol of alluvial origin, classi-"ed as "ne, mesic, Typic Chromoxerert by the USDASoil Taxonomy, with a satisfactory content of total nitro-gen (0)122%), available phosphorus (measured as P

2O

5,

41 p.p.m.) and exchangeable potassium (as K2O,

1561 p.p.m.) and a good supply of organic matter(2)07%). In summer the soil often shows several cracks,both at the surface (4}5 cm wide) and throughout the50 cm deep layer (1}2 cm wide).

The climate is classi"ed as &accentuated thermo-medi-terranean', according to the FAO-UNESCO classi"ca-tion, with summer temperatures which can rise above403C, winter temperatures which can fall below 03C andrains concentrated mainly in the winter months.

The weather during the period of soil strengthmeasurements (1994}1996) was characterized by greatvariability. Referring to the interannual cycle Au-gust}April (ranging from the main soil ploughing to theend of penetrometer use), in the 3 trial years the rainfallwas lower (416)0, 319)8 and 447)4 mm, respectively) thanthe long-term average 1952}1992 (461)5 mm).

2.2. Experimental design and treatments

The experimental "eld design is a randomized com-plete block with "ve replications (block) and sub plots of80 m2 each.

The straw and stubble treatments, namely, burning ofcrop residues (B) and ploughing in of crop residues (P),the latter with or without the application on the residuesof three nitrogen levels (as urea) (N

1, N

2and N

3) and of

500 m3 ha~1 of water (W), are shown in Table 1.The whole trial "eld received 100 kg P

2O

5ha~1 in

summer, at the time of main soil ploughing and100 kgNha~1 (NH

4NO

3) as a top dressing on the wheat,

half in February (at the 5th}6th leaf stage) and half inApril (at the start of booting stage).

After harvesting of wheat, straw and stubble werechopped to 10}15 cm lengths and spread back on theplot. The various doses of urea were then applied, andeverything were buried with a ploughing depth of 40 cm.In the treatments requiring water, it was applied before

ploughing. Finally, the residues of the B treatment wereburnt.

The sowing of wheat was carried out in the last tendays of November, with a rate of 450 seeds per m2 anda 15 cm row spacing.

2.3. Resistance to penetration

The measurements of soil penetration resistance (conepenetration resistance) were taken on two of the "vereplications four times per year, in January}April1994}1996, the most important months of the durumwheat cropping cycle, that starts with the sowing inNovember and ends with the harvesting in June. In May,because of the soil dryness, most readings fell at thebottom of measurement scale (exceeding 50 MPa), thenresulting not very accurate. Five random measurementswere made in each experimental plot between the wheatrows.

The soil strength was measured using a Bush recordingsoil penetrometer (Findlay Irvine) with a 303 angle and12)83 mm diameter cone, corresponding to the AmericanSociety of Agricultural Engineering standard.

The penetrometer resistance measurements were doneat 3)5 cm depth increments up to the total depth of52)5 cm (labelled from R

1to R

15) and recorded on a data

storage unit. The "rst depth of measurement(R

1, 0}3)5 cm depth) was excluded from the analyses, as it

usually showed values near 0 MPa, owing to an incom-plete contact of the penetrometer base plate on the un-even soil surface.

2.4. Correction of resistance to penetration valuesfor soil water content

Since the penetrometer resistance is mainly a!ected bysoil moisture (Perumpral, 1987; Vyn & Raimbault, 1993;

Table 2Parameter estimate, its con5dence internal and residual error of the relationship among penetration resistance, soil water content and

bulk density at the two soil depths

Parameter Estimate Conxdence interval

Lower Upper

Depth 0}25 cmA 0)14949 0)09035 0)20864B !1)94560 !2)23013 !1)66106C 0)47469 !0)01516 0)96454

Residual error 0)025012Depth 25}50 cm

A 0)26777 0)15675 0)37879B !1)73307 !2.01433 !1)45180C 0)38452 0)01101 0)75803

Residual error 0)019128

233SOIL MECHANICAL IMPEDANCE

Busschler et al., 1997), gravimetric soil water contents h,from regular depth intervals (0}20, 21}40 and 41}60 cm)and for all treatments and recording dates, were alsomeasured. Correcting strengths for signi"cant di!erencesin water contents among the various treatments permitsexamination of soil strength aspects other than thosecaused by water (Busscher, 1987). Perumpral (1987)examined various soil}water correction methods;Campbell and O'Sullivan (1991) showed that cone pen-etration resistance could be predicted as a function ofmoisture content and bulk density by

Rp"AhB (o

b)C (1)

where Rp

is cone penetration resistance in MPa, ob

is bulk density in g cm~3, h is gravimetric watercontent in g g~1 and A, B and C are positive coe$cientsdepending on soil properties. To correct cone penetra-tion resistance measurements for di!erences in watercontent and then make them comparable, the model (1)takes the form

Rc/R

u"(h

c/h

u)B (2)

where the subscripts c and u are for corrected and uncor-rected values.

The empirical coe$cients, A, B and C were determined"tting the Eqn (1) to the experimental data collected onthe same site and at two depths (0}25 and 25}50 cm) ina previous experiment. Two di!erent equations wereestimated by least-squares method separately at the twoabove depths, as reported in Table 2.

All penetrometer values were standardized to a com-mon water content equal to the maximum soil water

content recorded over the whole three-season period, toobtain values varying within the interval [0, 1].

2.5. Statistical analysis

As measurements made at di!erent depths in eachpenetration are not independent, principal componentanalysis* PCA * (Rao, 1964) was applied to penetra-tion data, using correlation matrix (Stelluti et al., 1998).That allowed the derivation of a smaller number of linearcombinations (principal components, PC) of the originalvariables (R

2}R

15), which retained most of the informa-

tion. To make easier the interpretation of PCs, a Varimaxrotation was applied to PCs.

The penetration data distributions were tested tobe very skewed; in this case the arithmetic mean is anine$cient estimator, because the estimation error isvery large (Webster & Oliver, 1990). As the distributionswere approximately lognormal, penetration datawere transformed to neperian logarithms and allmeans and variances were computed in the logarithms.Finally, to obtain unbiased estimates of the means,the logarithms of penetration data (y) were transformedback using the standard formula (Aitchison & Brown,1957):

Rp"exp(SyT#1/2p2

y) (3)

where SyT is the mean of the transformed values of Rpand

p2y

is the estimated variance of the logarithms. Since thevalues of penetration resistance represent repeatedmeasurements over time on the same experimental unit,each PC was submitted to multivariate variance analysis(Winer, 1971; Castrignano, 1990). This technique allowed

Table 3Rotated principal component pattern

Variables Principal component value

PC1 PC2*

R13

0)92s 0)30R

120)92s 0)31

R14

0)92s 0)30R

150)90s 0)31

R11

0)89s 0)38R

100)87s 0)42

R9

0)84s 0)45R

80)81s 0)49

R4

0)32 0)86s

R3

0)20 0)84s

R5

0)47 0)79s

R6

0)58 0)72s

R2

0)25 0)70s

R7

0)64 0)67s

Note: R2}R

15, penetrometer readings.

*PC1, PC

2, "rst and second principal component.

sSigni"cant values at P(0)05.

M. MAIORANA E¹ A¸ .234

testing hypotheses about the factors of the statisticalmodel. Di!erent types of sources of variation wereconsidered:

(1) measurement factor, also called within-subject factor;in this case the crop season (SEASON) and themeasurement date within the season (DATE);

(2) the main factor, also called between-subject factor; inthis case the crop residue management (MANAGE-MENT);

(3) all the two- and three-way interactions among thetwo above within-subject factors and the between-subject factor.

To study temporal trend of penetration resistance andthe likely factors a!ecting it, orthogonal polynomial con-trasts were generated for each within-subject factor anda variance analysis was produced for each contrast.Finally, a variety of single degree-of-freedom contrastswere performed to test some of the hypotheses deemedthe most interesting: (1) burning against ploughing inwithout any fertilization and irrigation; (2) ploughing inplus nitrogen against ploughing in plus nitrogen andirrigation; (3) PN

1against PN

1W; (4) PN

2against

PN2W; (5) PN

3against PN

3W and (6) burning against

all the other treatments using ploughing in, pooledtogether.

All the statistical procedures used were applied usingof the statistical software package of SAS/STAT (SASInstitute, 1998).

3. Results and discussion

The results of the PCA indicated that two of the PCsprovided a good summary of the data. The "rst PCaccounted for 84% of the total variance and the secondPC more than 11%, so both totalling more than 95%.Therefore, only the "rst two PCs are retained in theanalysis (Table 3). The "rst principal component (PC

1) is

a measure of the overall penetration resistance represen-tative of the layer &25}52 cm, having high positive loadson all variables R

7}R

15. On the contrary, the second

principal component (PC2) is more related to the

penetration resistance measurement in the topsoil. Prin-cipal component analysis has then disclosed the existenceof a discontinuity along the soil pro"le, approximately at25 cm depth, which is thought to be caused by annualtillage at the same depth.

From the multivariate variance analysis, it resulted the"rst principal component was signi"cantly a!ected bycrop residue management at the probability level ofP(0)0001.

As regards the within-subject factors, SEASON and DATE,were signi"cant at P(0)0001, whereas their two-way

interactions with the between-subject factor (MANAGE-

MENT) were signi"cant at P(0)05 and P(0)0001,respectively. Moreover, the two-way interaction betweenthe two within-subject factors (SEASON with DATE) as wellas the three-way interactions SEASON WITH DATE AND BLOCK

and SEASON WITH DATE AND MANAGEMENT were signi"cantat P(0)0001. The signi"cance of the former three-wayinteraction points out the in#uence of surface location(BLOCK) on soil strength, revealing the probable existencealso of a horizontal gradient in soil structure. The lattersigni"cant three-way interaction stresses the importanceof the speci"c meteorological pattern within a crop sea-son on the di!erentiation of the crop residue manage-ment treatments.

To disclose any temporal trend in soil strength moreclearly, polynomial contrasts were also performed forboth within-subject factors. As regards the factor SEASON,only the quadratic component was signi"cant atP(0)0001 and was signi"cantly in#uenced by cropresidue management at P(0)01. On the contrary, asregards the factor DATE, both linear and quadratic com-ponents were highly signi"cant at P(0)0001, but onlythe linear component di!ered signi"cantly among thevarious crop residue management treatments atP(0)0001. These results then revealed a general increaseof soil resistance over a crop season (means not reportedfor brevity), owing to the decrease of soil water content;this trend was di!erent among the management treat-ments, but it was mainly a!ected by the meteorological#uctuations characterizing each crop season.

Since the above statistical analysis revealed that themeteorological pattern of each season caused the main

Table 4Results of linear contrast between treatments for the 5rst principal component in terms of probability level

Contrasts for Probability levelcomponent 1

1994 1995 1996s.d. 1 s.d. 2 s.d. 3 s.d. 4 s.d. 1 s.d. 2 s.d. 3 s.d. 4 s.d. 1 s.d. 2 s.d. 3 s.d. 4

B versus P 0)0216 0)0215 0)3053 0)2641 0)0045 0)1737 0)1823 0)7779 0)1404 0)5461 0)1697 0)1904PN versus PNW 0)0061 0)7828 0.0278 0)0001 0)0487 0)0165 0)0104 0)0288 0)0014 0)0019 0)0835 0)0018PN

1versus PN

1W 0)1643 0)2689 0)4996 0)0005 0)5352 0)0001 0)0888 0)8857 0)0128 0)0069 0)0612 0)0996

PN2

versus PN2W 0)0419 0)0245 0)0217 0)4206 0)0077 0)2714 0)0024 0)3595 0)2950 0)0188 0)8860 0)1634

PN3

versus PN3W 0)1543 0)0854 0)4102 0)0099 0)2265 0)4184 0)7542 0)0082 0)0278 0)6305 0)1825 0)0119

B versus PTOT

0)0366 0)0016 0)0689 0)9112 0)0043 0)0314 0)0025 0)5249 0)0002 0)5551 0)3179 0)6163

Note: s.d., sampling date: 1 in January, 2 in February, 3 in March, 4 in April; B, burning; P, ploughing in without N and water; N,all nitrogen treatment; N

1, N

2and N

3, nitrogen levels; W, water application; P

TOT, all treatments using ploughing in.

235SOIL MECHANICAL IMPEDANCE

variation in subsoil strength, a variety of univariate con-trasts was performed at the measurement dates relativeto each individual crop season (Table 4). The objectivewas to disclose some relevant di!erences among thetreatments.

From Table 4, there is no well-de"ned behaviour ofa treatment in comparison with another treatment. Inparticular, burning di!ered from all treatments usingcrop residue incorporation in late season and also inFebruary 1995. The application of water on residues insummer produced signi"cant e!ects on soil impedance,but not in all years and in di!erent periods of the cropseason. The results of Student}Newman}Keuls multipletest among the means of the "rst principal component(not reported) did not show any clear trend among thetreatments, therefore it is not possible to prefer onetreatment against another (burning against ploughing in;fertilization against fertilization with irrigation of thestraws) on the ground of the only subsoil impedancecriterion.

The interpretation of results becomes still more con-fused for the second principal component. In fact, themanagement factor did not result in signi"cant di!er-ences, whereas the factor SEASON was signi"cant atP(0)01 as well as the two-way interaction SEASON WITH

MANAGEMENT at P(0)0001. In the same way the factorDATE was signi"cant at P(0)0001 as well as the two-wayinteractions DATE WITH BLOCK at P(0)0002 and DATE

WITH MANAGEMENT at P(0)05. Also, the two-way inter-action SEASON WITH DATE resulted in signi"cant di!erencesat P(0)0001 as well as the three-way interactions SEA-

SON WITH DATE AND BLOCK and SEASON WITH DATE AND MAN-

AGEMENT at P(0)002 and P(0)001, respectively. Allthese statistically signi"cant interactions prove that anyprobable e!ect of management on soil impedance isgreatly a!ected by spatial heterogeneity and meteoro-logical pattern.

The results of the temporal trend analysis showed thatfor the factor SEASON only the linear component wassigni"cant at P(0)005, whereas for the factor DATE, thelinear, quadratic and cubic components were signi"cantat P(0)0001, 0)004 and 0)0001, respectively.

The interpretation of the results of the univariatecontrasts (Table 5) is still more di$cult than the onefor the "rst PC, owing to the greater in#uence ofspatial and temporal variability on the soil impedance atthe surface. Even though the treatments di!erentiated,such di!erences appeared randomly distributed duringthe crop season and no clear trend could then be dis-closed.

To have a clearer idea of the behaviour of soil strengthover time, the temporal pattern of the two PCs averagedover the crop residue treatments is reported in Fig. 1. Thesoil impedance was generally greater in depth than at thetop, with the exception of the season 1995. However, itunderwent many #uctuations over the three cropseasons, mostly a!ected by rainfall pattern. The meanvalues of soil strength in January and in February 1994appeared very high, quite probably because the soil con-ditions were not well "tted for mouldboard ploughing.The exceptionally plentiful autumn rains of 1993, in fact,did not allow working the mellow soil, with the produc-tion, as a consequence, of large and dense clods after themain tillage. Even if the generally accepted criteria(Taylor & Gardner, 1963; Taylor & Brar, 1991) assumethat cone penetration resistance values greater than2 MPa frequently reduce crop yields, nevertheless the"nal grain yields were not a!ected by soil compactionobserved in January and February 1994 (Maiorana,1998).

The muddle aspect of these results derives quite prob-ably from the fact that this type of study was aimed atcharacterizing soil strength in "eld using the meansof several measurements without speci"c regard to

Table 5Results of linear contrast between treatments for the second principal component in terms of probability level

Contrasts for Probability levelcomponent 2

1994 1995 1996s.d. 1 s.d. 2 s.d. 3 s.d. 4 s.d. 1 s.d. 2 s.d. 3 s.d. 4 s.d. 1 s.d. 2 s.d. 3 s.d. 4

B versus P 0)0027 0)6250 0)8476 0)1313 0)1989 0)2014 0)1383 0)1450 0)8907 0)0740 0)5107 0)2483PN versus PNW 0)0007 0)6948 0)0935 0)0269 0)6355 0)0223 0)9523 0)3277 0)9344 0)2413 0)8651 0)2236PN

1versus PN

1W 0)1050 0)9367 0)7727 0)2743 0)4858 0)2629 0)0417 0)8477 0)8540 0)0230 0)0925 0)4373

PN2

versus PN2W 0)0278 0)0538 0)1068 0)0205 0)5138 0)0139 0)0003 0)6490 0)2061 0)9152 0)0279 0)0486

PN3

versus PN3W 0)0256 0)2213 0)3316 0)6679 0)6144 0)7024 0)0468 0)0561 0)2159 0)7756 0)7039 0)5056

B vs PTOT

0)0124 0)1922 0)7210 0)8563 0)0738 0)1126 0)0300 0)0009 0)6498 0)2673 0)0067 0)1646

Note: s.d., sampling date: 1 in January, 2 in February, 3 in March, 4 in April; B, burning; P, ploughing in without N and water;N, all nitrogen treatment; N

1, N

2and N

3, nitrogen levels; W, water application; P

TOT, all treatments using ploughing in.

Fig. 1. Temporal pattern of the mean values for the xrst and thesecond principal components over the three crop seasons:

, component 1, , component 2

M. MAIORANA E¹ A¸ .236

horizontal position. Such a procedure might be su$cientfor measurements of cone penetration resistance in veryhomogenous soil conditions. This study has then shownthat the inclusion of position is fundamental when soilproperties may be altered by crop residue managementas a function of location. Not recognizing this importantposition e!ect means that the penetration data were notused e$ciently, i.e. without drawing the full informationfrom them. In the past the practise usually was to takeseveral random samples, without speci"c regard to loca-tion, in an attempt to overcome the variability ofmeasured values. This study has proved that sometimessplitting the "eld in large blocks cannot be su$cient toassess the e!ect of horizontal position on soil strength.

A more e$cient way to record soil impedance wouldthen require that each measure is to be georeferred: inthis case, other techniques of spatial data processing,such as geostatistics, which take into account spatialcorrelation, should be preferred.

Even if this study has not showed a clear, directe!ect of straw burning on soil impedance, however,we feel to promote alternative methods to that technique,largely spread in Italy, as it is the cheapest way ofclearing the "eld after wheat harvesting and before themain soil tillage. But crop residue burning and repeateddeep-plough tillage have led to a progressive deteriora-tion of soil fertility, above all in south Italy. Therefore,we suggest the application of more conservative manage-ment systems, such as no or minimum tillage, as theydid not cause signi"cant yield loss in previous trials atthe same site (De Giorgio et al., 1994). Moreover,leaving crop residues on soil surface, it is possibleto reduce the impact of rain drops and then preservethe continuity of water conducting pores (Pagliaiet al., 2000), improving water availability to thecrops.

4. Conclusions

Statistically signi"cant di!erences in mechanical impe-dance, as measured by a cone penetrometer, were foundas functions of crop residue management, crop seasonand date of measurement within each season.

Nevertheless, trend analysis and multiple comparisonsamong the experimental treatments did not disclose thesuperiority of someone of the examined crop residuemanagement practices and then it is di$cult to give clear,practical advice to farmers on the ground of only theimprovement of soil physical conditions. In this caseother considerations, more properly of environmentaltype, could induce one to prefer ploughing crop residuesinto the soil; "rst of all as it avoids the use of "re andminimizes the loss of organic matter. Moreover, cropresidue is a major renewable resource, which has animportant impact also on the global carbon cycle: crop

237SOIL MECHANICAL IMPEDANCE

residue conservation, in fact, is a fundamental tool forenhancing carbon sequestration in soil.

Among the possible reasons of the confounding e!ectin the data interpretation, there could be the few yearsconsidered and the intrinsic soil variability. In fact, soilconditions vary locally as well as by depth and cropresidue management. This made it di$cult to unambigu-ously interpret cone penetration resistance data. There-fore, measurement and description of soil impedance insoil management studies, importing heterogeneity to soil,must account for localization in addition to depth andmanagement e!ects. To allow a more complete and clearinterpretation of the results of penetrometer measure-ments, future studies should be then designed so as toinclude location e!ects and data should be processed bygeostatistical techniques.

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