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Europ. J. Agronomy 72 (2016) 70–79

Contents lists available at ScienceDirect

European Journal of Agronomy

journa l homepage: www.e lsev ier .com/ locate /e ja

lanting density and sowing proportions of maize–soybean intercropsffected competitive interactions and water-use efficiencies on theoess Plateau, China

uanyuan Ren a,b, Jiajia Liu c, Zhiliang Wang d, Suiqi Zhang a,d,∗

State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences andinistry of Water Resources, Yangling, Shaanxi 712100, PR ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, PR ChinaMinistry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of life Sciences, Fudan University, Shanghai 200433, PRhinaNorthwest A&F University, Yangling, Shaanxi 712100, PR China

r t i c l e i n f o

rticle history:eceived 8 April 2014eceived in revised form0 September 2015ccepted 1 October 2015

eywords:ompetition dynamics

ntercroppingater equivalent ratio

a b s t r a c t

In field trials on the Loess Plateau, China, in 2012–13, maize (Zea mays L.) and soybean (Glycine max L.)were sole cropped and intercropped at three densities and with three sowing proportions. Maize wasgenerally more growth efficient for biomass accumulation than soybean during the entire growth interval,as assessed using the relative efficiency index (REIc). However, most of sowing proportion at each densitydisplayed a trend of decreased growth with development. Throughout the growth period, the dry matterproduction and leaf area index (LAI) of maize increased as the plant density increased irrespective ofwhether it was grown as a sole crop or as an intercrop. However, the effect of increasing cropping densitywas less obvious for soybean. The LAI values of the sole crop treatment for both maize and soybean weregreater than that of the intercropping system, indicating that the presence of maize and soybean together

eaf area indexelative growth efficiency

suppressed the respective growth of the two crops. At the final harvest, land equivalent ratios (LER) of0.84–1.35 indicated resource complementarity in most of the studied intercrops. Complementarity wasdirectly affected by changes in plant densities; the greatest LER were observed in 2 rows maize and 2 rowssoybean intercrops at low density. The water equivalent ratio (WER), which characterized the efficiencyof water resource use in intercropping, ranged from 0.84 to 1.68, indicating variability in the effect of

se ef

intercropping on water-u

. Introduction

Intercropping is the simultaneous cultivation of two (or more)rops together on the same piece of land. Intercropping results inreater yield and less variation in yield compared to sole cropsWilley, 1979). This increased yield, particularly under low inputonditions, is frequently attributed to resource complementarity,n which component crops use limiting resources more efficiently

ue to different temporal, spatial, or phenological characteristicsLi et al., 2013). Inter- and intraspecific competition, the avail-bility of environmental resources and the sowing proportionnd density of the component crops influenced the degree of

∗ Corresponding author at: State Key Laboratory of Soil Erosion and Dryland Farm-ng on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academyf Sciences and Ministry of Water Resources, Yangling, Shaanxi 712100, PR China.ax: +86 29 87012210.

E-mail address: sqzhang@ms.iswc.ac.cn (S. Zhang).

ttp://dx.doi.org/10.1016/j.eja.2015.10.001161-0301/© 2015 Elsevier B.V. All rights reserved.

ficiency (WUE).© 2015 Elsevier B.V. All rights reserved.

resource complementarity, the total yield, the relative contribu-tion of the individual components (Hauggaard-Nielsen et al., 2006;Vanermeer, 1989). For example, Umar (2006) reported that inter-crops of grain sorghum (Sorghum bicolor L. Moench) and groundnut(Arachis hypogaea L.) achieved larger relative yield advantageswhen grown under drought than they did when kept well-watered.Determination of the optimum plant population density necessaryfor optimal yield is a major agronomic goal. Compared with solecrops, intercrop components may utilize resources more efficiently.Therefore, the optimum plant density in intercrops outweigh theoptimum density in sole crop (Willey and Osiru, 1972). At the meantime, the optimum plant density and sowing proportion at one sitemay not be applicable to other locations because of regional vari-ations in weather (precipitation, solar radiation, temperature, etc.)

and soil properties (organic matter, nitrogen, phosphorus, potas-sium, soil water hold capacity, etc.). The sowing proportions ofintercrop components are sown may be of great significance indetermining yield of cereal–legume intercrops (Mao et al., 2012;

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fori and Stern, 1987). Therefore, plant density and sowing propor-ions are commonly used to achieve potential yield of intercrops inry land production (Ijoyah and Fanen, 2012).

Willey and Osiru (1972) determined that a higher density ofomponent crops in intercropping resulted in greater intercropdvantages in a maize–bean intercrop. Crop density significantlyffects the competitive dynamics between intercrop componentrops because dominance is always enhanced by increasing inter-rop density. The variables involved (e.g., proportion of the legumer cereal species) may alter the competitive dynamics betweenomponent species and indicated their variations (positive effect)n determining yield and production efficiency (Ijoyah and Fanen,012). For instance, one stand of maize (Zea mays L.) alternated withne stand of soybean (Glycine max L.) gave the greatest intercropield in maize–soybean intercrop. Intercrop competition studiesased on a single, final harvest of crops have hypothesized thatompetitive strength or the measures of performance are constanthroughout most of the growing season (Andersen et al., 2007).owever, species interactions are a complex process involving vari-ble nutrient environments, space and time.

However, the reported effects of plant density, row spacing, theistance between plants and crop proportion on water-use effi-iency (WUE) have been inconsistent. A number of studies haveeported that WUE was reduced under intercrops by crop propor-ion (Gao et al., 2009). Mao et al. (2012) discovered that the sowingroportions had a significant effect on water use in intercroppingnd that WUE varied from 0.87 to 1.16, indicating variability in theffect of intercropping on WUE. However, these studies primar-ly involved full irrigation. Research studies on the effects of plantensity and crop proportion on WUE in rain-fed dryland agriculturere scarce. It is essential to understand how intercropping to offsetater limitations influences crop growth and water utilization to

ptimize water management in arid regions.Maize and soybean are the most common grain crops on the

oess Plateau, which has a typical semi-arid monsoon climate (But al., 2013). Despite the potential for irrigation, most of the avail-ble water for crop growth in semi-arid regions originates fromimited precipitation. Therefore, limited water resources are the

ajor constraint on crop production (Rockström et al., 2007).The aim of this study was to determine the effects of the sowing

roportions of maize and soybean and the population density inaize–soybean intercrops on (1) the temporal dynamics of com-

etitive interactions, (2) the potential yield advantages and WUE,nd (3) the final yield in intercrops compared to sole crops.

. Materials and methods

.1. Study area

The study was conducted during the 2012 and 2013 grow-ng seasons at the Changwu experimental station in the Loesslateau agricultural center (35.12 N, 107.40 E, 1200 m above sea

evel). This location is within the dry farming zone with 582 mmf mean annual rainfall from 1957 to 2013 (73% rainfall dur-

ng May–September). The annual mean temperature is 9.7◦ C.he soils are Cumuli-Ustic Isohumosols according to Chinese Soilaxonomy (Gong et al., 2007). The soil physic-chemical charac-eristics (average) of the sites were as follows for the 2012 and013 growing seasons: organic matter 11.8 g kg−1, total nitro-

en 0.87 g kg−1, available phosphorus 14.4 mg kg−1, exchangeableotassium 144.6 mg kg−1, and inorganic nitrogen 3.15 mg kg−1. Thelimatic data for the two growing seasons of the experiment arerovided in Fig. 1. Precipitation during the growth period wasecorded at the research station.

omy 72 (2016) 70–79 71

2.2. Experimental design and field management

The experimental plots were arranged factorially in a random-ized complete block design with three blocks. The experimentaltreatments: there were three planting densities (maize (Z. mays L.cv. Zhengdan 958) densities of 45,000, 90,000 and 135,000 plantsha−1 for low, medium and high density; soybean (G. max L. cv.Zhonghuang 24) densities of 90,000, 210,000 and 330,000 plantsha−1 for low, medium and high density), each density included fivesowing proportions: sole-cropped maize (M) and soybean (S), threemaize–soybean intercrop treatments included (1/2) maize + (1/2)soybean (M2S2, 2 rows of maize and 2 rows of soybean), (1/3)maize + (2/3) soybean (M2S4, 2 rows of maize and 4 rows of soy-bean) and (2/3) maize + (1/3) soybean (M4S2, 4 rows of maize and2 rows of soybean) (only for 2013). Each block included a total of12 and 15 crop treatments for 2012 and 2013, respectively (Fig. 2).

The land was manually cleared and ridged. Each plot was6 m × 4 m and contained four ridges. The gross land area(17 × 147 m) was 0.25 ha with 1 m between blocks.

The sowing season for the experiment was late April. Maize andsoybean were sowed on 25th April in 2012; maize and soybeanwere sowed on 20th April in 2013. Two seeds each were sown formaize and were thinned to one plant per stand at 28 and 24 daysafter planting (DAP) in 2012 and 2013, respectively. Four seeds eachwere sown for soybean and were thinned to two plants per standat 17 and 24 DAP in 2012 and 2013, respectively.

All crops were sown at a spacing of 50 cm (inter-row) apart.Maize was sown 44, 22 and 15 cm apart (intra-row spacing) toachieve population densities of 45,000, 90,000 and 135,000 plantsha−1, respectively. Soybean was sown 44, 19 and 12 cm apart (intra-row spacing) to achieve population densities of 90,000, 210,000 and330,000 plants ha−1, respectively.

Mixed-base fertilizer NP was applied to soybean and maize byspreading the fertilizer 5 days before planting to supply 90 kg N and150 kg P2O5/ha; this was achieved by mixing 196 kg urea + 266 kgCa(H2PO4)2·H2O/ha. In addition, 67.5 kg/ha N was applied to maizestands twice by drilling at 60 DAP and 80 DAP to supply 147 kg/haurea, as recommended for local cultivation. The water supply foreach treatment came solely from natural rainfall. Manual weedingwas conducted at five and eleven weeks after planting, respectively.

2.3. Sampling and measurements

The standard developmental stage system was used to identifythe vegetative stage (VS, from seedling emergence to silking formaize and to flowering for soybean) and the reproductive stage (RS,from silking and flowering for maize and soybean to physiologicalmaturity) of the entire growing season (Ritchie et al., 1993). Threeharvests were conducted during the experimental period, and theplants were cut just above the soil surface. The first harvest wasperformed at the V6 growth stage in maize (44 days after sowing)and the corresponding V3 stage in soybean. The second harvest (90days after sowing) was performed close to the silking growth stagein maize (stage R1), which corresponds to R4 in soybean. The lastharvest (155 days after sowing) was performed at physiologicalmaturity (stage R6) in maize and soybean (stage R8).

Four measurements for leaf area index (LAI) were conductedduring the experimental period. The first measurement was per-formed at the V6 growth stage in maize and the corresponding V3stage in soybean. The second measurement was performed at V12growth stage in maize and the corresponding V6 stage in soybean.

The third measurement was performed at R1 stage in maize and thecorresponding R4 stage in soybean. The fourth measurement wasperformed at the R3 growth stage in maize and the correspondingR6 stage in soybean. The LAI was measured using a Plant CanopyAnalyzer (Li-2200, LiCor Inc., Lincoln, NE, USA).

72 Y. Ren et al. / Europ. J. Agronomy 72 (2016) 70–79

easons in 2012 and 2013 at the Changwu experimental station.

mtfifad

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Fig. 2. Layout of the experiments of sole crop and intercrops in three plant densities

Fig. 1. Daily meteorological data during the two growing s

At each stage, six adjacent plants were sampled for each treat-ent. The sampled plants were heated at 105◦ C for 30 min and

hen dried at 75◦ C to a constant weight before weighing. At thenal harvest, the grain dry matter (DM) for 6 m2 was determined

or both maize and soybean after threshing. The samples were driedt 75◦ C to a constant weight, and the biomass and grain yield wasetermined based on the average of three plot replicates.

.4. Determination of soil moisture and evapotranspiration (ET)

The soil water content was measured gravimetrically at 10 cmntervals within 0–100 cm and at 20 cm intervals within the00–200 cm profile for each plot, and it was sampled at physiologi-al maturity. The soil moisture in the 0–200 cm soil profile for eachlot was then calculated as the total soil water storage. Seasonalvapotranspiration (ET, mm) in the individual plots was deter-ined according to the following equation: ET = P + �SWS (Hillel,

998), where P is the total precipitation (mm) and �SWS is thehange in soil water storage (SWS, mm) between the planting andarvest stages; WUE was calculated as the grain yield (kg ha−1)ivided by the total ET (mm) over the growing season. For the solerops, we used the measurements taken in the middle of two rowso calculate the change in soil water contents in the water balancequation. For the intercrops, we used the measurements taken inhe middle of the maize and soybean rows to calculate the changen soil water contents in the water balance equation.

.5. Data analysis

The cumulative relative efficiency index (REIc), which compareshe proportional change in total dry matter (K) in a given time inter-al (t1–t2) of one species relative to another, was used to evaluatehe relative performance of maize compared to soybean (Connolly,

(low, medium and high) and five sowing proportions. Each line showed that M (sole-cropped maize), M4S2 (4 rows of maize and 2 rows of soybean, only for 2013), M2S2(2 rows of maize and 2 rows of soybean), M2S4 (2 rows of maize and 4 rows ofsoybean) and S (sole-cropped soybean) from left to right.

1987). For the maize–soybean intercrops, REIc was calculated asfollows:

REIc = Kmaize

Ksoybean

Ksoybean =DMsoybeanICt2

DMsoybeanICt1

Kmaize = DMmaizeICt2

DMmaizeICt1

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EIc values corresponding to three growth interval were calculated,rom sowing to the first harvest, from the first to the second har-est and from the second to the third harvest at maturity. Ksoybeannd Kmaize are proportion in total dry matter in a given time inter-al (t1–t2) for soybean and maize. DMmaizeIC

and DMsoybeanICare

ry matter under intercrops for maize and soybean. The total seedeight at sowing was taken as the total biomass for the first growth

nterval. A REIc value of one indicates that both species had sym-etrical growth efficiencies over a period of time.

We calculated the LER to measure the land use advantage ofntercropping (Rao and Willey, 1980). The LER for a maize–soybeanntercrop based on dry matter and grain yield was calculated asollows:

LERmaize = maizeIC

maizeSC

LERsoybean = soybeanIC

soybeanSC

LER = LERmaize + LERsoybean

here maizeIC, soybeanIC, maizeSC and soybeanSC are the dry mat-er and grain yield for intercropped and sole cropped maize andoybean, respectively. LERmaize and LERsoybean are partial LER ofaize and soybean in the intercrops. LER values >1 indicate a land

se advantage for intercropping.We calculated the water equivalent ratio (WER) (Mao et al.,

012) to measure the water use advantage of intercropping usinghe following equation:

ER = WERmaize+WERsoybean =maizeIC

ETmaizeICmaizeSC

ETmaizeSC

+

soybeanICETsoybeanICsoybeanSC

ETsoybeanSC

= WUEmaizeIC

WUEmaizeSC

+WUEsoybeanIC

WUEsoybeanSC

he WER for a maize–soybean intercrop was the sum of the par-ial WER values for maize (WERmaize) and soybean (WERsoybean),alculated based on grain yield. ETmaizeSC

, ETmaizeIC,ETsoybeanSC

ndETsoybeanICare evapotranspiration of maize and soybean in

ole crops and intercrops, respectively. WUEmaizeSC, WUEmaizeIC

,UEsoybeanSC

and WUEsoybeanICare the water-use efficiencies of

aize and soybean in sole crops and intercrops, respectively. TheER quantifies the amount of water that would be needed in sole

rops to achieve the same yield as produced with one unit of watern intercrops. A WER >1 indicates an advantage from intercroppingn terms of the use of environmental water for plant growth.

All data were statistically treated by analysis of varianceANOVA) for the randomized complete block design, and the leastignificant difference (LSD) test was used for mean separation fol-owing the procedure of Steel and Torrie (1980).

. Results

.1. Total dry matter production

For all harvests and cropping densities, the total dry matter pro-uction of the soybean sole crop was the lowest except at lowensity of the first harvest (Fig. 3). For the second (P < < 0.05) andhird (P < 0.01) harvest and all cropping densities, the total dry mat-er of M2S2 outyielded that of M2S4 in 2012. Furthermore, theotal dry matter of M4S2 outperformed the other two intercrops

t all three harvests and cropping densities in 2013. For the secondP < 0.01) and third (P < 0.05) harvest and all cropping densities, theotal dry matter of M4S2 outyielded that of M2S4 in 2013. Withhe exception of the dry matter production of the V6 growth stagef the two crops grown at medium and high densities in 2013 and

omy 72 (2016) 70–79 73

low density in 2012, the intercrops did not result in greater drymatter production than those of the higher producing maize solecrop at any of the harvest and cropping densities. Both sole croppedand intercropped maize dry matter production increased with plantdensity, with the exception of the third harvest in 2012. Increasingsoybean density also had a positive effect on dry matter produc-tion of sole cropped and intercropped soybean at all three harvests.However, at the third harvest in both 2012 and 2013, increasingthe density from low to high did not significantly affect the inter-cropped soybean production. At all three harvests and croppingdensities, sowing proportions significantly affected the dry matterproduction of intercropped maize, with the exception of the firstharvest in 2012 at low and medium densities.

3.2. Interspecies dynamics

The REIc value was calculated to estimate the relative efficiencyof the two crops in terms of biomass accumulation in each of thethree growth intervals (Table 1). The REIc value was greater thanone, which shown that relative efficiency of maize for biomassaccumulation was higher than that of soybean over a period oftime, indicating that maize had the growth advantage over soybean.The treatments including M2S2 from R1 to R6 in 2012 (P < 0.01),M2S2 from sowing to V6 in 2013 (P < 0.05) shown that the growthadvantage increased as cropping density increased. The treatmentsincluding M2S4 from sowing to V6 in 2012 (P < 0.05) and M4S2from R1 to R6 (P < 0.05) in 2013 shown that the growth advantagedecreased as cropping density increased. As expected the temper-ature from sowing to silking in 2012 was higher than that of in2013, in all intercrop treatments, the maize component grew ata relatively greater rate from sowing to V6 and during the sec-ond growth interval (V6–R1) in 2012 compared to 2013 (P < 0.001).However, there was no significant difference in the last growthinterval (R1–R6) between the two years. In both years, the mostgrowth-efficient period in all treatments was from sowing to V6,followed by the second growth interval (P < 0.001 in 2012 andP < 0.01 in 2013). The maize component grew at a faster rate in inter-crop M2S4 than in M2S2 from sowing to V6 in 2012 (P < 0.01). Withthe exception of the first growth interval and high sowing density ofthe second growth interval in 2013, the relative efficiency of M2S4was always the greatest of the three intercrops. With the exceptionof M2S4 at a medium density from R1 to R6 in 2012 and M4S2 ata high density in the same interval in 2013, the maize componentalways grew more efficiently in all treatments.

At the first two harvests, the LER values of the intercrop aver-aged 1.07 and 0.98 for maize/soybean intercrops in 2012 and 0.96and 0.94 for maize/soybean intercrops in 2013, demonstrating thatgrowth resources were used 2–6% less efficiently in the intercropthan in the sole crops, except at the first harvest in 2012 (Fig. 4). Bythe last harvest, the intercrops outyielded the sole crops, with LERvalues averaging 1.08 and 1.04 for 2012 and 2013, respectively,indicating a slight land use advantage in maize/soybean inter-crops. The partial LER values of maize during the two years wereaffected by density (P < 0.05); the three harvests with medium den-sity attained the greatest LER values, but there was no significanteffect of density on the calculated partial LER values of soybean. Atall harvests and cropping densities, the sowing proportion exertedopposite effects on the calculated partial LER values of maize andsoybean. That is, the partial LER values of maize were increased byincreased intercropping with soybean (P < 0.001 in 2012 and 2013).

The partial LER values of maize and soybean changed very little overtime in 2013; however, at the first harvest in 2012, the partial LERvalues of maize in all intercrops were significantly lower than thoseof the other two harvests, with the opposite tendency observed insoybean.

74 Y. Ren et al. / Europ. J. Agronomy 72 (2016) 70–79

F five sT

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ig. 3. Total aboveground crop dry matter production in three plant densities andhe values are the mean (n = 3) ± S.E.

.3. Grain yield

In both the sole crops and intercrops in both years, except M2S4n 2012, the maize grain yield increased with density (P < 0.001).oybean grain yield was affected by density only in the croppingreatments in 2013, with yield increasing with density (Table 2).

The total grain yield of the M2S4 cropping treatment in 2012as not significantly different from those of the low- to high-

ensity treatments. Increasing density significantly increased theotal grain yield of the other sole crops and intercropping in both

owing proportions measured during the V6, R1, and R6 periods in 2012 and 2013.

years. The land equivalent ratio (LER) based on grain yield in theintercropping systems averaged 1.14 (P < 0.01) and 1.05 (P < 0.05)for 2012 and 2013, respectively indicating a substantial land useadvantage of intercropping in maize/soybean intercrops. There wasno significant effect of sowing proportions on LER. The LER wasnot significantly different at any densities. However, in the inter-

cropping in 2013, the LER of the intercrops at low (P < 0.01) andhigh (P < 0.01) densities were significantly higher than those of theintercrops at a medium density.

Y. Ren et al. / Europ. J. Agronomy 72 (2016) 70–79 75

Table 1The relative efficiency index (REIc) at three densities and three sowing proportions in 2012 and 2013.

Density Sowing proportion Period

2012 2013

V6 R1 R6 V6 R1 R6

Low M4S2 3.2 ± 0.23aA 1.37 ± 0.07bB 1.12 ± 0.04aBM2S2 4.28 ± 0.56aA 3.15 ± 0.67aA 1.11 ± 0.06bA 1.94 ± 0.1bB 1.64 ± 0.09aAB 1.21 ± 0.07bBM2S4 5.95 ± 0.32aA 1.66 ± 0.27bA 1.50 ± 0.16aA 1.62 ± 0.25aB 2.37 ± 0.40aA 1.60 ± 0.07aA

Medium M4S2 3.23 ± 0.11aA 1.36 ± 0.06bB 1.01 ± 0.09abBM2S2 3.77 ± 0.14aB 2.87 ± 0.02aA 2.33 ± 0.12aA 2.88 ± 0.07aA 1.55 ± 0.19aB 1.84 ± 0.17aAM2S4 5.04 ± 0.22bA 3.08 ± 0.16aA 0.94 ± 0.03bB 2.02 ± 0.17aB 2.17 ± 0.09aA 2.08 ± 0.14aA

High M4S2 2.07 ± 0.07bB 2.82 ± 0.28aA 0.85 ± 0.03bBM2S2 4.19 ± 0.25aA 3.88 ± 0.51aA 2.48 ± 0.24aA 2.92 ± 0.28aA 1.92 ± 0.24aB 1.23 ± 0.05bBM2S4 4.52 ± 0.05bA 2.47 ± 0.04aA 1.79 ± 0.06aA 1.77 ± 0.06aB 2.25 ± 0.23aAB 1.96 ± 0.28aA

Calculated on the basis of total crop dry matter production (see Fig. 3) from sowing to V6the seed thousand-grain weight for maize and soybean was set to 370 and 230 g, respectiThe values are the mean (n = 3) ± S.E. For each column, different letters denote significant(lower case), and among different sowing proportions at the same density (capital letters

Table 2Grain yield at three densities and five sowing proportions in 2012 and 2013.

Density Sowing proportion Grain yield (g m−2)

2012 2013

Maize Soybean Total Maize Soybean Total

Low M 740aA 740aA 481bA 481bAM4S2 366bB 60bC 426bBM2S2 416bB 89aB 505bB 278cC 87bBC 364cCM2S4 324bC 109aB 432aC 184cD 110bB 293cDS 152aA 152aD 168bA 168bE

Medium M 787aA 787aA 985aA 985aAM4S2 698aB 69bC 767aBM2S2 646aA 80aB 726aA 487bC 85bC 572bCM2S4 415aB 113aB 529aB 305bD 143abB 448bDS 214aA 214aC 216aA 216aE

High M 1010aA 1010aA 1088aA 1088aAM4S2 733aB 84aD 817aBM2S2 696aA 90aB 786aA 595aC 120aC 714aBCM2S4 410aB 110aB 521aB 431aD 178aB 609aCS 199aA 199aC 233aA 233aD

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sities. A significant part of this advantage can be attributed to the

or each column, different letters denote significant difference at P < 0.05 among dif-erent plant density at the same sowing proportion (lower case), and among differentowing proportions at the same density (capital letters).

.4. Leaf area index (LAI)

There were substantial variations between planting density inhe LAI values in the different development stages in both yearsFig. 5). Based on averaged LAI values from low to high density inoth years, both sole cropped and intercropped maize LAI values

ncreased with increasing plant density, whereas increasing plantensity had only a slight effect on the soybean LAI values of bothole cropped and intercropped soybean, with a trend of increasingAI values as the density of soybean increased. The LAI values ofhe sole crop treatments for both maize and soybean were greaterhan that of the intercropping system, indicating that maize andoybean suppressed the LAI values of the competing crop whenntercropped. However, the LAI values did not differ significantlyetween the different intercropping treatments.

.5. Water use advantage of intercropping

The WER indices were used to determine if a given intercropield was associated with greater (WER >1) or lower (WER <1)ater use compared to sole crops. WER is a measure for water-

se efficiency when the objective is to produce the crop yield in

(0–44 days), R1 (44–90 days) and R6 (90–155 days). In the sowing-V6 calculation,vely, and multiplied by plant density ha−1 to estimate the crop dry matter sowing.

difference at P < 0.05 among different plant density at the same sowing proportion).

the ratio achieved in intercrop. It is here used to assess whetherwater is used more efficiently in intercrop than in sole crop.

The partial WER of maize, WERmaize, was not always higher thanWERsoybean, indicating that the competitive advantage of maize forwater depended on both density and sowing proportion (Fig. 6). Thepartial WER (0.54) of intercropped maize was as high as the partialLER of intercropped maize (0.56). The LERmaize and WERmaize valuesdemonstrated that the competitive advantage of maize is similar interms of land capture and water capture. The partial WER of inter-cropped soybean ranged from 0.25 to 0.89, similar to the partialLER of intercropped soybean (0.28–0.92), demonstrating the rela-tive competitive disadvantage of soybean compared with maize inthe acquisition of water. The averaged results of 2012 demonstratedthat all intercropping systems in 2012 consumed significantly morewater (+13.0%) than would be expected on the basis of the wateruse efficiencies and yield for sole cropping (P < 0.01); however, theaveraged results of 2013, there was no significant difference in WERbetween sole cropping and intercropping at any density in 2013. Noeffect of density on the calculated partial WER values was observedfor either year. However, the partial WER values of maize (P < 0.001)and soybean (P < 0.001) in 2013 both showed a tendency to increaseas the proportion of maize or soybean in the crop increased.

4. Discussion

4.1. Interspecies dynamics

Compared to single measurements of final yield, sequentialmeasurements of crop growth provide more detailed informationon competitive interactions (Hauggaard-Nielsen et al., 2006). In thisstudy, we used three harvests over the course of the growing seasonand investigated interspecies dynamics in three periods: sowing to44 days, 44–90 DAP and 90–155 DAP.

The competitive dynamics of intercropped maize and soybeanwere significantly affected by plant density and sowing pro-portions. However, maize generally grew more efficiently thansoybean in all the considered periods. The REIc values calculatedfor each of the intercrop treatments in the study clearly demon-strated the superior initial growth of maize compared to soybean.From a lower seed weight, maize grew at a greater relative ratethan soybean within the first 44 DAP at all three cropping den-

faster seedling emergence of maize relative to soybean, particularlygiven the delay in soybean sowing due to low emergence rates in2012. Moreover, the root growth of maize is more rapid than that ofsoybean (Corre-Hellou et al., 2006). In the 44–90 and 90–155 DAP

76 Y. Ren et al. / Europ. J. Agronomy 72 (2016) 70–79

F M4S2b tio (LEa partiab ues ar

gd

fdmai

ig. 4. Partial land equivalent ratio (partial LER) of the maize and soybean intercropsasis of total dry matter production. The diagonal lines show the land equivalent radvantage according to crop dry matter. The two lines (the left and right line indicatealanced use of environmental sources for plant growth by maize and soybean. Val

rowth periods, the sowing proportions showed a tendency towardecreasing REIc values with development (Table 1).

The relative performance of the two species may show that dif-erent phenology play an important role in forming the observed

ynamics. There was an obvious and positive effect of density onaize growth, irrespective of whether it was grown as a sole crop or

s an intercrop throughout the growth season. The effect of increas-ng cropping density was less obvious for soybean. The LAI value

(black symbols), M2S2 (white symbols) and M2S4 (gray symbols) calculated on theR). The above area of diagonal lines of LER = 1(1.2) represent there is intercroppingl LER of maize and soybean) crossing the x–y coordinate 0–0 indicates a 50%-to-50%

e the mean (n = 3) ± S.E.

of maize significantly increased with maize density in both thesole and intercropping systems. Several studies have shown thatchanges in canopy structure (leaf area distribution) have a negativeinfluence on competitive dynamics in pea–barley intercropping

systems (Berntsen et al., 2004).

Y. Ren et al. / Europ. J. Agronomy 72 (2016) 70–79 77

F and

t

4

obpi(

ig. 5. Changes in the leaf area index (LAI) in maize (M) and soybean (S) sole cropshe period V6, V12, R1, and R3 in 2012 (a and b) and 2013 (c and d).

.2. Intercropping advantage

Both complementary resource use and the relative strength

f intra- and interspecific competitive interactions within andetween crops determine the potential advantages of intercrop-ing. The density of the intercrop affected the yield in wheat–cotton

ntercrops (Mao et al., 2015) and peppermint–geranium intercropsVerma et al., 2013). The partial LER values of maize based on dry

intercrops sown in three sowing proportions and three densities measured during

matter production in both years were significantly affected by den-sity; the greatest LER values were observed for the three harvests ofthe medium density treatment, indicating an interaction between

competition and resource complementarity. However, there wasa slight tendency for partial LER values of soybean to decreasewhen the density of soybean increased, indicating that intraspecificcompetition might negate complementarity. Based on the averagedLER values for all densities and the three harvests during the two

78 Y. Ren et al. / Europ. J. Agronomy 72 (2016) 70–79

F crops

o tio (W

ytf

oawivtbtLms(

4

ttdiaq2bsHitfi

cstrttmc

ig. 6. Partial water use equivalent ratio (partial WER) of maize and soybean intern the basis of total grain yield. The oblique lines show the water use equivalent ra

ears, the identical LER values observed among the three plant pat-erns were primarily the result of the opposing effects of relativerequency on the partial LER values of maize and soybean.

The partial LER of maize were significantly greater than thosef soybean in M2S2 and M4S2, whereas the M2S4 intercrop had

higher partial LER for soybean than for maize. Thus, the maizeas dominant in the M2S2 and M4S2 cropping systems. Moreover,

ntercrops at medium and high densities led to greater partial LERalues for maize than for soybean. Density and relative frequencyhus determined the relative yield contributions of maize and soy-ean in the intercrops. Prasad and Brook (2005) determined thathe variation in maize density resulted in a significant effect on theAI of maize itself, which consequently affected the rates of dryatter accumulation. The lower LER for soybean observed in this

tudy would contribute to increased shading with maize densityOfori and Stern, 1987).

.3. Effect of intercropping on grain yield

The grain yield of the three intercrops were significantly greaterhan those of the corresponding sole soybean crops and lowerhan those of the corresponding sole maize crops for all croppingensities in both years. Intercropped maize had a strong compet-

tive effect on the growth of soybean at high cropping density,s evidenced by the low grain yield of soybean, which conse-uently increased the proportion of grain yield due to maize in013. However, stronger competitive effects of intercropped soy-ean on the growth of maize were observed as the proportion ofoybean seed was increased in both years at low cropping density.auggaard-Nielsen et al. (2006) reported similar results; however,

n our study, interspecific competition outperformed the facilita-ion in which one plant species enhances the survival, growth, ortness of another in intercrop systems.

A yield advantage in intercropping is achieved only when theomponent crops do not compete for the same resources in theame time and space. In the present study, the sharing of light byhe component crops was important for improved utilization of

esources, resulting in higher productivity of the intercropping sys-em. Prasad and Brook (2005) reported that intercropping increasedhe total amount of radiation intercepted due to rapid establish-

ent of ground cover by the combined canopies of the componentrops. Maize productivity appeared to be more strongly related to

M4S2 (black symbols), M2S2 (white symbols) and M2S4 (gray symbols) calculatedER). Values are the mean (n = 3) ± S.E.

the temporal distribution of captured resources in different devel-opment stages (Mwale et al., 2007), particularly sunlight captureand assimilation, which were correlated with the LAI (Li et al.,2001). The plant density significantly enhanced the LAI values, lead-ing to greater photosynthetically active radiation (PAR) that theamount of intercepted PAR by plant canopy is computed by solarradiation and LAI (Yang et al., 2004), which was subsequently avail-able to the rapidly growing maize crop during growth (Bu et al.,2013).

The crop yield depends not only on resource capture but alsoon resource use efficiency (Mao et al., 2012). The values of WERfor intercropping indicate the advantage of intercropping for wateruse. The intercropped maize and soybean both displayed an overallpartial WER that was as high as the partial LER.

The comparison of these indices suggests that both maize andsoybean produced slightly greater yield per plant in the intercroptreatment compared to the sole crop treatments (LER = 0.56 and0.52 for maize and soybean, respectively, averaged over all treat-ments and years). However, per unit of available water, the soybeanplants produced less in the intercrop treatment than in the singlecrop treatments (overall average WER = 0.54 and 0.51 for maizeand soybean, respectively), indicating that soybean was equallycompetitive with maize with respect to water acquisition. Thiscompetitive symmetry was confirmed by water capture evidence.Despite this symmetry in the competition for water between maizeand soybean, the system can still be advantageous in terms of landand water use, as indicated by the LER and WER values.

For water use in the maize/soybean intercropping systems, wedetermined that WUE depends on the sowing proportion of theintercropping system. Similarly, Mao et al. (2012) reported thatWUE was affected by the sowing proportion of the intercroppingsystem. In our study, the partial WUE values of maize and soy-bean did not differ at any plant density. However, different plantdensities affected the distribution and depth of roots (Hauggaard-Nielsen et al., 2001; Li et al., 2011; Reddy and Willey, 1981). Inmaize/soybean intercrops, a complementary distribution of rootsmight occur, leading to a significant water use advantage. We found

that the WER, as a measure of WUE in intercropping, was signifi-cantly increased in the M2S2 intercrop in 2012 (P < 0.01), whereasthe other treatments had WER values slightly greater than 1 thatwere not significant.

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Y. Ren et al. / Europ. J.

Maize is a C4 crop with high physiological WUE, while soybeans a drought-tolerant crop (Calderón et al., 2012). These opposingraits can help to increase the WUE of sole crops as well as inter-rops. What is more, a shaded soil surface and a dense canopy wouldead to lower temperature of soil surface and decreased evaporationCooper et al., 1987). Maize/soybean intercropping with a longeregetative cover therefore had reduced soil evaporation. However,n our study, all the available water for crop growth originatedrom limited precipitation. Water limitation might offset the poten-ial competitive advantage of maize for water. Hence, the sowingroportions had a substantial effect on the competition for wateretween maize and soybean; the partial WER of maize was sig-ificantly greater than that of soybean in the M4S2 treatment andmaller than that of soybean in the M2S4 treatment.

. Conclusions

Plant density and sowing proportions significantly affected thenterspecies dynamics of maize–soybean intercrops. The leaf areandex of maize increased as the maize density increased. Maize

as generally more growth efficient for biomass accumulation thanoybean during the growth period. The plant density or sowing pro-ortion had no directly effect on water-use efficiency. 2 rows ofaize and 2 rows of soybean at low density was the highest land

quivalent ratio in maize–soybean intercrop systems to improvehe total crop productivity.

cknowledgements

We thank Y.-J. Zhu for the help with the climatic data. We thank.-L. Chen for helpful criticisms of this paper. This study was finan-ially supported by the National High Technology Research andevelopment Program of China (2011AA100504) and Project 111f the Chinese Education Ministry (B12007).

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