Effects of cultivation patterns on winter wheat root growth parameters and grain yield

Field Crops Research 156 (2014) 208–218

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Field Crops Research journal homepage: www.elsevier.com/locate/fcr

Effects of cultivation patterns on winter wheat root growth parameters and grain yield Yonghua Wang a,b,∗ , Weili Hu a , Xuelin Zhang a , Liuxia Li a , Guozhang Kang b , Wei Feng b , Yunji Zhu a , Chenyang Wang a,b , Tiancai Guo a,b,∗ a b

Collaborative Innovation Center of Henan Grain Crops, Agronomy College of Henan Agricultural University, #63 Nongye Road, Zhengzhou 450002, China National Engineering Research Center for Wheat, Henan Agricultural University, #62 Nongye Road, Zhengzhou 450002, China

a r t i c l e

i n f o

Article history: Received 1 September 2013 Received in revised form 25 November 2013 Accepted 26 November 2013 Keywords: Winter wheat Cultivation pattern Root growth parameter Yield

a b s t r a c t Grain yields of winter wheat are greatly affected by different cultivation patterns through regulating root growth and development. In this study, we established four cultivation patterns, i.e. farmers’ traditional cultivation pattern (T1), optimized T1 cultivation pattern (T2), super high yield cultivation pattern (T3) and optimized T3 cultivation pattern (T4). The variations of wheat root growth parameters were analyzed in two growth years (2008–2009 and 2009–2010). The results indicated that there were significant differences in yield factors among four patterns. Temporal variations of total root dry weight (TRDW), total root length (TRL) and average root diameter (ARD) in four patterns exhibited a single peak curve. The maximum of TRDW and TRL in T1 appeared at the heading stage, whereas those in T2, T3 and T4 were postponed to anthesis. The peak appearance time (te ) and the maximum growth rate (tm ) of TRDW and TRL in T2, T3 and T4 were retarded. The maximum values (wmax ), average growth rate (¯c ) and maximum growth rage (cm ) of TRDW, TRL and ARD in T2, T3 and T4 were significantly higher than those in T1. In comparison with T1, the mean values of RDWD and RLD in T2 in upper soil layers (0–20 cm) reduced remarkably. Similarly, the mean values of RDWD and RLD in T4 were also markedly lower than those in T3. In the middle and lower soil layers (40–100 cm), however, the mean values of RDWD and RLD in T2 were significantly higher than those in T1, and these parameters in T4 had also significant difference with T3. In the 20–100 cm soil layers, the gray correlation coefficients among grain yield, RDWD, RLD and ARD in T2 were higher than T1. Above 60 cm soil layers, these coefficients in T3 were higher than in T4. In deep soil layers (60–100 cm), however, these coefficients in T3 were lower in T4. These results suggested that optimized cultivation patterns may enhance wheat grain yield by changing the root distribution among soil layers, prolonging the root growth duration, increasing root growth rate and enhancing the absorption ability to water and nutrition in deep soil layers. © 2013 Published by Elsevier B.V.

1. Introduction Root is an important absorption and metabolism organ, as well as an important contributor to grain yields. The size, quantity, distribution, metabolism and activity variation of root system influence directly the growth, development of the upper ground tissues, and eventually grain yields (Liu et al., 1993; Chen et al., 2003; Zhang et al., 2009). The research on the underground root system growth, distribution characteristics and the underlying regulatory measures have become a focus in the field of crop science.

∗ Corresponding authors at: National Engineering Research Center for Wheat, #62 Nongye Road, Zhengzhou, Henan 450002, China. Tel.: +86 371 63558205; fax: +86 371 63558202. E-mail addresses: [email protected] (Y. Wang), [email protected] (T. Guo). 0378-4290/$ – see front matter © 2013 Published by Elsevier B.V. http://dx.doi.org/10.1016/j.fcr.2013.11.017

Variations of winter wheat root temporal and spatial distribution is affected by many factors such as cultivars, soil properties, timing and the amount of irrigation and fertilizing, and tillage management, etc., have been intensively studied (Qin et al., 2004; Aggarwal et al., 2006; Zuo et al., 2006; Herrera et al., 2007; Martínez et al., 2008; Kubo et al., 2008; Outoukarte et al., 2010; Verónica et al., 2010; Huang et al., 2012). Root growth and root distribution along the soil profile are greatly affected by soil moisture condition and genetic background (Benjamin and Nielsen, 2006). Schulze et al. (1996) demonstrated that frequent irrigation encouraged root growth in the upper soil layers and that dry soil conditions stimulated deep root growth. Soil management practices including tillage, sowing and organic matter incorporation into soil enhanced root proliferation as evident from increase in root length density (Aggarwal and Sharma, 2002; Aggarwal and Goswami, 2003), and close connections between root density, soil moisture content and root water uptake have already been

209

30

2008-2009

25

2009-2010

20

normal years

15 10 5

100

First 10 days in june

May

April

March

February

January

December

November

October

0 -5

Precipitation(mm)

2008-2009

80

2009-2010

60

normal years

40 20

March

April

May

First 10 days in june

March

April

May

First 10 days in june

February

January

December

November

0 October

demonstrated (Angadi and Entz, 2002; Zhang et al., 2009). Rotation using “break crops” and deep tillage to break soil pan represent effective methods to encourage deep root growth of crops under dry conditions (Barraclough and Weir, 1988). Under the condition when the total amount of water supplied was maintained at 120 mm, irrigation during the later part of the winter wheat growth season and increase in irrigation frequency decreased the available soil water; this result was mainly due to the changes in the vertical distribution of root length density (Li et al., 2010). To promote the root system growth in the middle and lower soil layer helps to efficiently enhance root system’s absorption to water and fertilizers, resulting in the increased grain yields (Wu et al., 2005). These imply that the root systems in the middle and lower soil layers play vital roles in determining wheat grain yields. Crop roots do not grow independently, they are greatly influenced not only by climate, soil and growth conditions, but also by agronomic cultivation measures, such as tillage, water, fertilizer, etc. (Wang et al., 2012). However, one or two of the above factors were conducted in previous literatures (Lampurlanés et al., 2001; Chen et al., 2003; Lv et al., 2010; Huang et al., 2012), and, to our knowledge, effects of multiple cultivation technique systems on wheat root growth and development have been less reported as so far. In this study, thus, multiple cultivation technique systems including field operations, fertilizer applications, planting density, and irrigation schemes were designed in four cultivation patterns to explore effects of cultivation patterns on winter wheat root growth parameters and grain yields. The results of this study could provide valuable information for improving water and fertilizer efficiency, and grain yield, and for determining future strategies for field management practices in China and elsewhere.

Average temperature (˚c )

Y. Wang et al. / Field Crops Research 156 (2014) 208–218

2008-2009

250

2009-2010

2. Materials and methods

normal years

150 100 50

February

January

December

November

0 October

Field experiments were conducted from October 2008 to June 2010 in Xiangyun town, Wenxian county, Henan Province, China (112◦ 99 E, 34◦ 92 N). The area has a warm temperate semi-humid continental monsoon climate, annual average temperature of 14.4 ◦ C, annual accumulated sunshine hours of 2251.0 h, annual precipitation ranging from 281.5 to 932.8 mm, annual average precipitation of 556.5 mm (Meteorological data of 1962–2006, Provided by Wenxian Meteorological Bureau). The preceding crops of this experiment were maize in two growth years. The soil was fluvo-aquic clay soil. Other properties of the plough layer soil were shown in Table 1. Wheat cultivar Ping’an 8 was used in this experiment, and sowing was conducted on October 15, in two growth years. Wheat grains were harvested on June 7, 2009 and June 11, 2010, respectively. Four cultivation patterns were designed, i.e. Farmers’ traditional cultivation pattern (T1), optimized cultivation pattern 1 in comparison with T1 (T2), super high yield cultivation pattern (T3) and optimized cultivation pattern 2 in comparison with T3 (T4). For T1, the rotary tillage (about 15 cm) was adopted before wheat sowing and rolling was not conducted after seeding, the water irrigation was applied after sowing, 20 cm equal row spacing was adopted, and the sowing quantity (187.5 kg ha−1 ) of wheat seeds was used. For T2, T3 and T4, the mechanical deep ploughing (over 25 cm deep) was adopted, and rotary harrow multiple times, and rolling after seeding was conducted. Equal row spacing (20 cm) was adopted in T2, while alternating wide and narrow row spacing (15 cm × 23 cm) was adopted in T3 and T4. The sowing quantity of wheat seeds in T2 was 150 kg ha−1 , and 120 kg ha−1 for both T3 and T4. Organic fertilizers, microelement fertilizers and phosphate and potassium fertilizers were applied before sowing (Table 2). As the base

Sunshine time(h)

2.1. Study site and cultivation treatment

200

Fig. 1. Temporal variations of mean daily air temperature, precipitation and sunshine during the periods of wheat growth (October to First 10-days of June) in 2008–2009, 2009–2010 and normal years (from 1962 to 2006). Note: Meteorological data of normal years for the average of 1962–2006 over the past 45 years.

fertilizers, all of nitrogen (N) fertilizers in T1 were applied before sowing, whereas in T2, T3 and T4, 50% N fertilizers were applied before sowing, and at the jointing stage the remaining 50% N fertilizers were applied with irrigation. Four treatments were randomly laid out with four replications, and each plot area was 200 m2 . 2.2. Climate variations during winter wheat growth periods The climate conditions during the wheat growing periods in 2008–2009 and 2009–2010 were different (Fig. 1). In 2008–2009, a serious drought appeared in this region during the early stage of wheat growth. From October 2008 to the end of January 2009, rainfall was merely 32, 43.76 mm less than average rainfall in normal years. From December 2008 to January 2009, rainfall was merely 0.2, 15.48 mm less than average rainfall in normal years.

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Y. Wang et al. / Field Crops Research 156 (2014) 208–218

Table 1 Basic physicochemical property of the tested soil. Year

Soil layer (cm)

0–20 20–40 0–20 20–40

2008–2009 2009–2010

Organic matter (g kg−1 )

15.50 12.80 16.07 13.10

Total N (g kg−1 )

1.11 0.93 1.04 0.89

Available nutrient (mg kg−1 )

Bulk density (g cm−3 )

Alkaline – extractable N

Olsen – extractable P

NH4 OAc – extractable K (mg kg−1 )

140.00 113.50 135.60 112.00

26.43 21.30 23.29 20.50

129.90 101.50 130.00 97.40

In 2009–2010, a severe winter and spring seasons occurred. During the early spring, the temperature was low and the sunshine was weak. The average temperature in November was 4.90 ◦ C, 3.22 ◦ C less than that in normal years. From November 2009 to the end of April 2010, the monthly average temperature was also 0.87 ◦ C lower than that in normal years. During the whole growth seasons, the totally accumulated temperature was 106.90 ◦ C lower than that in normal years. The illumination hours decreased by 268.0 h, mainly because a decreased 117.5 h illumination hours in February and March, 2010.

1.28 1.35 1.26 1.32

Root dry weight (root length) per unit area refers to the root dry weight (root length) in unit area of soil. It is determined by Eqs. (1) and (2): RDW = M/S × 104

(1)

RL = L/S

(2)

RDW is the root dry weight (g m−2 ), RL is the root length (cm cm−2 ), M is the root dry weight (g), L is the root length (cm) and S is the soil area (cm2 ). The soil area is determined by Eq. (3): S = 3r 2

2.3. Contents of determinations and methods 2.3.1. Root system sampling and analyses In each plot, the sampling areas with uniform growing wheat plants were selected and signed, and wheat root samples were harvested with a root auger at the wintering, jointing, heading, flowering, filling and maturity stages, and the sampling dates were designed at the 66 d, 163 d, 181 d, 195 d, 215 d, 233 d and 69 d, 159 d, 187 d, 201 d, 221 d, 240 d after seedling. The diameter and length of drilling bit of root augers were 10 cm and 15 cm, respectively. The sampling method was as follows: 3 sampling points were randomly selected in the fixed sampling zone of each plot. In every sampling point, the drilling was carried out for three times. The sampling positions were described as follows: (l) within the row, (2) between the rows and (3) in an intermediate position, i.e. with one edge of the core touching the row (Bolinder et al., 1997). Samples of the three drillings were combined and used as one for the same soil layer. Every 20 cm of depth was considered as one soil layer, with 1 m depth. The obtained mixtures of root and soil were transferred into a nylon bag of 100 mesh and then submerged in water for 0.5 h. Subsequently, the samples were washed with tap water and removed the impurities. The cleaned root samples were placed on the glass plate of the root system scanner for the gray-scale scanning (Epson perfection V700 photo). The analysis of the files was conducted using the root system analysis software (WinRHIZO 2008) to obtain the growth parameters such as root length (RL) and average root diameter (ARD). Finally, the root samples were dried at 105 ◦ C for 20 min, and then dried at the constant temperature of 85 ◦ C to constant dry weight. The samples were weighed for the root dry weight.

(3)

r is the radius of the drilling bit (r = 5 cm). Total root length (root dry weight) refers to the sum of root length (root dry weight) which is unit soil area of different soil layer. Root dry weight (root length) density refers to the root dry weight (root length) in unit volume of soil. It is determined by Eqs. (4) and (5): RDWD = M/V × 106

(4)

RLD = L/V

(5)

RDWD is the root dry weight density (g m−3 ), RLD is the root length density (cm cm−3 ), M and L refer to the same of (1) and (2) type and V is the soil volume (cm3 ). The soil volume is determined by Eq. (6): V = Sh

(6)

S is the soil area and h is the sampling depth (h = 20 cm). 2.3.2. Yield calculation of harvest and variety test The spike number of the fixed sampling points for 1 m’s double row of each treatment was investigated at the maturity stage. The wheat plants with the roots in all the sampling points were harvested to laboratory and measured the spike number and grain weight. The harvest of an area of 10 m2 was carried out and the harvested samples were threshed and dried for the calculation of the grain yield (kg ha−1 ). 2.4. Statistical analyses 2.4.1. Quantitative analysis based on Beta model Rate and duration of root growth were quantified by fitting the data for the time course of the root growth parameters (Yin et al.,

Table 2 Irrigation and fertilization management of wheat under different cultivation patterns. Treatment

T1 T2 T3 T4

Rate of fertilizer application (kg ha−1 )

Irrigation stage and amount (m3 ha−1 )

N

P2 O5

K2 O

ZnSO4

Organic fertilizer

Soil moisture water

Green rose water

Jointing water

Blossom filling water

225 180 300 240

75 75 150 90

60 60 150 90

0 0 15 15

0 0 3000 3000

900 600 600 600

900 0 0 0

0 900 900 600

900 900 900 600

Y. Wang et al. / Field Crops Research 156 (2014) 208–218

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Table 3 Grain yields and yield components of winter wheat among four cultivation patterns in two growth years. Year

2008–2009

2009–2010

Treatment

Spikes (104 ha−1 )

T1 T2 T3 T4 T1 T2 T3 T4

552.6 566.7 571.20 600.60 643.50 621.30 598.20 599.33

± ± ± ± ± ± ± ±

Grains per spike

39.31aA 38.98aA 42.03aA 57.38aA 12.57aA 13.09bAB 14.16cB 2.54cB

41.33 43.86 44.52 46.23 30.75 33.08 37.48 36.73

± ± ± ± ± ± ± ±

1000-grain weight (g)

1.72cC 0.82bBC 1.63abA 1.12aA 1.56cB 1.63bB 1.17aA 1.34aA

42.38 43.33 47.57 43.55 45.04 46.79 47.90 47.14

± ± ± ± ± ± ± ±

1.06cB 0.26bcB 0.35aA 0.65bB 0.07cC 0.41bB 0.14aA 0.14aA

Grain yield (kg ha−1 ) 8136.49 8747.44 9573.79 9229.79 7566.18 8452.56 9519.90 9416.04

± ± ± ± ± ± ± ±

95.24bB 411.18abAB 829.77aA 779.79aAB 107.59cC 78.90bB 64.10aA 34.71aA

Note: The data are the average value ± standard deviation (±SD), n = 4. Date with capital and small letter in the same column indicate significant difference at 1% and 5% levels, respectively.

2003)



w = wmax 1 + < 2te − tm

  t te /(te −tm ) te − t te − tm and

te

with 0 ≤ t

0 < tm < te

(7)

w is the characteristic parameter of the root system (TDRW, TRL, ARD), t is days after seeding, wmax is the maximum value of w, which is reached at time te , and tm is the time at which the maximum root growth rate is achieved (so 0 < tm < te ). Eq. (7) obeys the constraints that w = 0 at the start of root growth (i.e. t = 0), and w = wmax when growth is terminated (i.e. t = te ). Eq. (7) produces an asymmetrical unimodal curve if te is exceeded, and described the course of a increasing growth process from t = 0 until te , and the attenuating growth process beyond te until time (2te − tm ). With this model, the average rate of root growth (¯c ) during the growth period will be calculated simply as: c¯ =

wmax te

(8)

The maximum root growth rate (cm ), which is calculated at time tm , is given by Yin et al. (2003) cm =

2te − tm te (te − tm )

 t tm /(te −tm ) m

te

wmax

(9)

2.4.2. Gray correlation analysis The gray correlation analysis was evaluated according to the method of Deng (2010): Step 1: Equalization is used for the original data transformation xij =

xij

(10)

x¯ j

xij is the equalized transformation value, xij is the tested value of the index, x¯ j is the average value of index j. Step 2: Correlation coefficient calculation. The grain yield of the mature period was used as the basic sequence x0 (t), the root characteristic parameters including root dry weight density, root length density and average root diameter of different test periods in different soil layer were set as the sub sequence of xi (t), i = 1, 2, . . ., m. The correlation coefficient calculation equation is written as follows: L0i (K) =

min + max 0i (K) + max

(11)

0i (K) is the absolute difference between the two comparison sequences at moment k; max and min are the maximum and minimum values of the absolute differences of all the sequences at any moment.  is the resolution ratio, with the value set as 0.5.

Table 4 Changes of root growth parameters on different days after seedling under four cultivation patterns measured in two growth years. Year

Root parameters

Total root dry weight per unit area (g m−2 )

2008–2009

Total root length per unit area (cm cm−2 )

Average root diameter (mm)

Total root dry weight per unit area (g m−2 )

2009–2010

Total root length per unit area (cm cm−2 )

Average root diameter (mm)

Treatments

T1 T2 T3 T4 T1 T2 T3 T4 T1 T2 T3 T4

T1 T2 T3 T4 T1 T2 T3 T4 T1 T2 T3 T4

Growth period/Days after seedling (d) Wintering/66d

Jointing/163 d

Heading/181 d

Anthesis/195 d

Filling/215 d

Maturity/233 d

9.79bcAB 9.59cB 10.19aA 10.08abAB 43.30aA 36.93dD 41.65bB 38.75cC 0.41dB 0.43cB 0.44bA 0.46aA

54.22bB 47.65dD 59.30aA 51.08cC 77.82bB 69.29dD 79.86aA 73.57cC 0.56dD 0.59cC 0.61bB 0.64aA

93.51bB 73.34cC 102.04aA 94.14bB 132.82bB 110.15dD 136.60aA 120.08cC 0.65cC 0.61dD 0.70aA 0.68bB

91.01cC 80.23dD 117.00aA 102.82bB 127.80cC 119.35dD 151.12aA 133.11bB 0.61cC 0.58dD 0.67aA 0.63bB

78.07cC 71.45dD 98.84aA 95.26bB 118.01cB 108.89dC 136.40aA 120.17bB 0.51cC 0.51dD 0.57aA 0.56bB

69.85cC 65.91dD 87.79aA 86.14bB 106.24cC 92.76dD 121.05aA 111.44bB 0.47cB 0.47cB 0.50aA 0.50bA

Wintering/69d

Jointing/159 d

Heading/187 d

Anthesis/201 d

Filling/221 d

Maturity/240 d

6.70aA 5.63bB 4.87cC 4.85cC 38.72aA 36.18bA 30.40cB 29.46cB 0.37cB 0.36dB 0.41aA 0.40bA

49.98aA 27.45dD 34.56bB 30.30cC 85.97aA 75.49cC 85.85aA 80.71bB 0.45cC 0.46dC 0.49bB 0.53aA

94.64aA 69.47dD 92.76bB 78.66cC 127.29aA 102.29cC 128.78aA 118.18bB 0.51cC 0.51cC 0.65aA 0.59bB

89.43cC 84.98dD 112.49aA 97.36bB 121.28cC 110.67dD 156.35aA 132.67bB 0.49cC 0.50cC 0.57aA 0.55bB

79.77cC 75.36dD 92.32aA 89.54bB 103.11cC 96.93dD 123.28aA 113.09bB 0.42bB 0.42bB 0.47aA 0.47aA

70.20cC 68.84cC 84.93aA 82.57bB 92.57cC 88.75dC 110.90aA 102.98bB 0.39cB 0.39cB 0.41bA 0.43aA

Note: Date with capital and small letter in the same column indicate significant difference at 1% and 5% levels, respectively.

212

Y. Wang et al. / Field Crops Research 156 (2014) 208–218

Fig. 2. Beta equation model diagram of the variation of the growth parameter of the root system of the winter wheat under different cultivation patterns. Note: T1, T2, T3, T4 represented the measured values in different growth period of winter wheat, t1, t2, t3, t4 represented the Beta equation fitting curve of different cultivation patterns.

Step 3: Correlation calculation r0i =

N 1

N

L0i (k)

t=

r0i



2 1 − r0i

×



n−2

(13)

(12)

k=1

r0i is the correlation between the subsequence i and the basic sequence 0. N is the length of the comparison sequences. Step 4: Testing the significance of the correlation coefficient. Eq. (13) is used to calculate the t value to test significance of a correlation coefficient:

n − 2 is the degree of freedom. t < t0.05 , an insignificant relationship; t ≥ t0.05 and t < t0.01 , the significant relationship at 0.05 level; t > t0.01 , the significant relationship at 0.01 level. All data were statistically analyzed as a completely randomized design with four replications using analysis of variance (ANOVA) to examine differences among four cultivation patterns (Clewer and Scarisbrick, 2001). Least significant differences (LSD) at a

0-20cm

350 300

300

250

250

200

200

150

150

T1

100

T3

50

T2 T4

0

100 50

140

120

120

100

100

80

80

60

60

40

40

20

20

0

0 66

163 181 195 215 233

69

30

20

20

10

10

0

-3

163 181 195 215 233

40 30

30

25

25

20

20

15

15

10

10

5

5 66 16 3 18 1 19 5 21 5 23 3

80-100cm

30

30

25

25

20

20

15

15

10

10

5

5

0 163 181 195 215 233

Day s after see dling (d)

2008–2009

20-40cm

Days after seedling (d)

2009–2010

20-40cm

1.4

0.8 0.6

0.4

0.4

0.2

0.2 0.0

0.0

40-60 cm

-3

69

163 181 195 215 233

159 187 201 221 240

1.0 40-60 cm

0.8

0.8

0.6

0.6

0.4

0.4

0.2

0.2 0.0 66

69

16 3 18 1 19 5 21 5 233

15 9 18 7 20 1 22 1 240

0.5

60-80cm

60-80cm

0.4

0.4

0.3

0.3

0.2

0.2

0.1

0.1

0.0

0.0

66

16 3 18 1 19 5 21 5 233

69

159 187 201 221 240

0.5

0.5

15 9 187 20 1 221 24 0

159 187 201 221 240

1.6

0.6

80-100cm

69

69

1.0

159 187 20 1 22 1 24 0

0 66

163 181 195 215 233

0.5

60-80 cm

69

35

0.0

66

80-100 cm -3

35

1.0

0.8

40

40

T4

159 187 20 1 22 1 24 0

0

0

T3

0.0 69

35

2.0

1.2

40 60-80 cm

35

T2

1.0

0 66

T1

1.0

1.2

Root length density (cm.cm )

30

2.0

1.0

50 40

3.0

159 18 7 20 1 221 24 0

40-60 cm

40

3.0

1.4

60 40-60cm

50

4.0

-3

Root dry weight density (g.m -3 )

60

4.0

1.6

20-40cm

160

140

0-20cm 5.0

66

Root length density (cm.cm -3 )

20-40cm

6.0

0-20cm

5.0

159 187 201 221 240

180

160

213

0.0 69

Root length density(cm.cm )

Root dry weight density (g,m -3 )

180

Root dry weight density (g,m )

6.0

0

66 163 181 195 215 233

Root dry weight density (g,m - 3 )

0-20cm

350

Root length density (cm.cm -3 )

400

400

Root length density(cm.cm )

Root dry weight density (g.m -3 )

Y. Wang et al. / Field Crops Research 156 (2014) 208–218

80-10 0cm

0.4

0.4

0.3

0.3

0.2

0.2

0.1

0.1 0.0

0.0 66

163 181 19 5 21 5 23 3

Days after seedling (d)

2008–2009

69

159 18 7 20 1 221 240

Days after seedling (d)

2009–2010

Fig. 3. Changes of dry root weight density and root length density of the winter wheat in the different soil layer under different cultivation patterns.

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Y. Wang et al. / Field Crops Research 156 (2014) 208–218

Table 5 Secondary growth parameters of the root system of winter wheat under different cultivation patterns. Root parameters

Year

2008–2009 Total root dry weight per unit area 2009–2010

2008–2009 Total root length per unit area 2009–2010

2008–2009 Average root diameter 2009–2010

Treatments

Secondary root parameter

T1 T2 T3 T4 T1 T2 T3 T4

T1 T2 T3 T4 T1 T2 T3 T4

T1 T2 T3 T4 T1 T2 T3 T4

wmax (g m−2 )

te (d)

tm (d)

c¯ (g m−2 d−1 )

cm (g m−2 d−1 )

89.31cC 77.98dD 112.32aA 104.50bB 90.86cC 85.12dD 108.58aA 99.88bB

204.17cC 208.18bB 208.49bB 211.07aA 210.29dD 219.01bB 217.45cC 220.36aA

151.82dD 155.39cC 164.27bB 167.71aA 157.54dD 179.59bB 177.74cC 181.85aA

0.44cC 0.37dD 0.54aA 0.50bB 0.43cC 0.39dD 0.50aA 0.45bB

0.91cC 0.78dD 1.27aA 1.19bB 1.03cC 0.91dD 1.31aA 1.23bB

wmax (cm cm−2 )

te (d)

tm (d)

c¯ (cm cm−2 d−1 )

cm (cm cm−2 d−1 )

117.5cB 105.22dC 135.78aA 119.46bB 114.83cC 100.16dD 138.28aA 120.54bB

206.07cC 207.35cBC 212.85bB 224.06aA 195.95cB 204.96bA 208.45aA 208.25aA

85.70dC 94.55cB 107.75aA 97.58bB 91.99dC 100.68cC 145.67aA 130.79bB

0.57bB 0.51cC 0.64aA 0.53cC 0.59bB 0.49cC 0.66aA 0.58bB

0.83bB 0.75cC 0.96aA 0.78cBC 0.88cC 0.73dD 1.25aA 0.97bB

wmax (mm)

te (d)

tm (d)

c¯ (×10−2 mm d−1 )

cm (×10−2 mm d−1 )

0.70dC 0.72cC 0.76bB 0.79aA 0.51cC 0.53bB 0.61aA 0.62aA

163.44aA 156.86bB 163.76aA 155.05bB 187.54aA 183.05bA 177.15cB 173.90cB

108.69aA 105.64bB 108.99aA 105.09bB 118.27aA 117.37aA 114.75bB 114.09bB

7.56cB 8.21bB 8.24bB 9.25aA 4.59dB 4.93cB 5.93bA 6.20aA

4.26cC 4.56bB 4.64bB 5.11aA 2.72cB 2.88bB 3.43aA 3.55aA

Note: Date with capital and small letter in the same column indicate significant difference at 1% and 5% levels, respectively.

probability levels of P = 0.01 and 0.05 were calculated. Drawing figures were conducted by using Microsoft Excel 2003. 3. Results 3.1. Differences of wheat grain yield among cultivation treatments Four cultivation patterns had remarkable effects on wheat grain yields (Table 3), and, in two growth years (2008–2009 and 2009–2010), yields in four patterns showed similar orders: T3 > T4 > T2 > T1. In comparison with T1, grain yields of T2, T3 and T4 increased by 7.6%, 17.7% and 13.4% in 2008–2009, and 11.7%, 25.8% and 24.5% in 2009–2010, respectively. There were significant differences in total spike amounts of four patterns in 2009–2010, as exhibited by T1 > T2 > T4 > T3, whereas, being insignificant in 2008–2009. In comparison with T1, total spike numbers in T2, T3 and T4 in 2009–2010 decreased by 22.2 × 104 ha−1 , 45.3 × 104 ha−1 , and 44.2 × 104 ha−1 , respectively. Grain number per spike and thousand grain weight in T2, T3 and T4 in 2008–2009 increased by 2.5–4.9 grains and 0.9–5.2 g, respectively, and grain number per spike and thousand grain weight in 2009–2010 increased by 2.3–6.7 grains and 1.8–2.9 g, respectively. 3.2. Temporal variations of wheat root characteristics and the mathematical model establishment In two growth years, TRDW, TRL and ARD in four patterns showed similar temporal variations (Table 4). The maximum of both TRDW and TRL in T1 occurred at the heading stage, while in T2, T3 and T4, their maximums were delayed to anthesis. Both TRDW and TRL in four patterns showed similar profiles: T3 > T4 > T1 > T2 from anthesis to maturity, while the maximums of ARD in four patterns occurred at the heading stage. In comparison with T1, the

maximums of TRDW, TRL and ARD in T2 declined by 27.9%, 11.0% and 8.3%, respectively. Compared to T3, these parameters in T4 declined by 36.5%, 21.1% and 14.5%, respectively. The Beta equation was used to fit the variation of the root growth parameters. TRDW, TRL and ARD had the similar pattern with the single peak cure in four patterns in two growth years: slow growth, quick growth, and then gradual decline (Fig. 2). The determination coefficients (R2 ) of the Beta equation on TRDW, TRL and ARD were more than 0.7, and F tests on their R2 were significant (P < 0.05 and 0.01), indicating that the Beta equation model may be suitable to reflect the root growth process of wheat. 3.3. Comparison of secondary wheat root characteristics among cultivation treatments There were significant differences in the secondary growth parameters of TRDW, TRL and ARD in four patterns across the 0–100 cm soil layers (Table 5). In two growth years, wmax , c¯ , cm of TRDW, TRL in four patterns showed similar profiles: T3 > T4 > T1 > T2 or T3 > T1 > T4 > T2, but those of ARD showed T4 > T3 > T2 > T1. In comparison with T1, tm of TRDW and TRL in T2, T3 and T4 were delayed with 3.6–15.9 d and 8.9–53.7 d, respectively. And te of TRDW and TRL in these patterns were also delayed with 7.2–24.3 d and 1.3–18.0 d, respectively. tm and te of ARD in T2, however, appeared more early than those in T1 by 0.9–3.1 d and 4.5–6.6 d, respectively. Similarly, tm and te of ARD in T4 were also more early than T3 by 0.7–3.9 d and 3.3–8.7 d, respectively. 3.4. Dynamic spatiotemporal distributions of RDWD, RLD and ARD of winter wheat in the difference soil layers under different cultivation patterns The spatiotemporal distributions of RDWD and RLD in four cultivation patterns showed similar variation: gradually decreased with

Note: Date with capital and small letter within the same year and growth stage under different soil layer indicate significant difference at 1% and 5% levels, respectively.

2009–2010

T4

0.67aAB 0.50aA 0.41aA 0.27aA 0.28aA 0.68aA 0.47bB 0.38bB 0.26aA 0.28aA

T3 T2

0.62cC 0.47bB 0.37bB 0.25bB 0.26bB 0.65bBC 0.44cB 0.35cC 0.25bB 0.25bB

T1 T4

0.79abA 0.53aA 0.43aA 0.31aA 0.32aA 0.80aA 0.52abA 0.41bB 0.29bB 0.30bA

T3 T2

0.68cB 0.50bA 0.38cBC 0.28cC 0.28cB 0.77bA 0.46cB 0.37dC 0.26dD 0.27cB

T1 T4

0.83bB 0.60bB 0.54aA 0.35aA 0.42aA 0.93aA 0.71aA 0.50bB 0.34bAB 0.35bB

T3 T2

0.78cC 0.56cC 0.47cC 0.33bB 0.33cB 0.94aA 0.49dD 0.42dD 0.29cC 0.31dC

T1 T4

1.00bB 0.73bB 0.52aA 0.34aA 0.37aA 1.22aA 0.85aA 0.48bB 0.33aA 0.34bB

T3 T2

0.90cB 0.58cC 0.46cBC 0.31bB 0.32cC 0.99bB 0.52dD 0.45cC 0.29cC 0.30dD

T1 T4

0.80bA 0.63aA 0.52aA 0.34aA 0.36aA 0.82aA 0.53bB 0.44bB 0.32bAB 0.33bB

T3 T2

0.77cB 0.52bB 0.40cC 0.31bB 0.31cC 0.83aA 0.47cC 0.37dD 0.28cC 0.29dD

T1 T4

0.54bB 0.42aA 0.23aA 0.61aA 0.42aA 0.21bB

T3 T2

0.53bB 0.35bB 0.20cB

T1

0.59aA 0.33bB 0.19dC

Maturity/240 d Filling/221 d Anthesis/201 d Jointing/159 d Wintering/69 d Soil depths (cm) Year

T3

0.60aAB 0.53aA 0.44bAB 0.32bB 0.32bB 2008–2009

0–20 20–40 40–60 60–80 80–100

0.75bBC 0.62aA 0.47aA 0.33aA 0.34aA Heading/187 d

T3

0.80aA 0.62aA 0.45bA 0.32aAB 0.32bB 0.72cC 0.57bB 0.42cB 0.30bB 0.32bcB

T2 T1

0.78abAB 0.56bB 0.40dB 0.28cC 0.31cB 0.83bB 0.71aA 0.52aA 0.35aA 0.36aA 0.93aA 0.71aA 0.50bA 0.34bAB 0.35abA 0.76cC 0.69aA 0.44cB 0.33bB 0.35abA 0.82bB 0.63bB 0.43cB 0.33bB 0.34bA 0.95cB 0.82bB 0.65aA 0.41aA 0.42aA 1.10bA 0.88aA 0.62bB 0.38bB 0.40bAB 0.88dC 0.74cC 0.60cC 0.39bB 0.41bAB 1.15aA 0.73cC 0.46dD 0.38bB 0.39cB 1.27bB 0.88bB 0.60aA 0.38aA 0.38aA 1.34aA 0.97aA 0.55bB 0.37bA 0.38aA 1.03cC 0.88bB 0.57bAB 0.34cB 0.35bB 1.38aA 0.77cC 0.50cC 0.34cB 0.35bB 0.92bB 0.82aA 0.52aA 0.36aA 0.37aA 0.98aA 0.73bB 0.51bA 0.34bB 0.35bA 0.59aAB 0.52aA 0.46aA 0.36aA 0.36aA

0.93bB 0.66cC 0.45dC 0.31dC 0.31dC 0.57bB 0.53aA 0.42bcBC 0.30cC 0.31bB 0.61aA 0.48bB 0.40cC 0.29cC 0.28cC 0–20 20–40 40–60 60–80 80–100

0.86cC 0.72bB 0.48cB 0.33cB 0.33cB

Maturity/233 d

T4 T3 T2 T1

Filling/215 d

T4 T3 T2 T1

Anthesis/195 d

T4 T3 T2 T1

Heading/181 d

T4 T3 T1 T4

T2

Jointing/163 d

T2 T1

Soil environments and planting technologies have great effects on the root growth of winter wheat, and their variations may regulate the adaptability of root system (Aggarwal et al., 2006; ˜ and Wade, 2012). Different plantation patterns, Botwright Acuna sowing date and quantity, irrigation and fertilization management and tillage directly or indirectly influence the growth of wheat

Wintering/66 d

4.1. Effect of cultivation patterns on root growth

Growth period/days after seedling (d)

4. Discussion

Soil depths (cm)

The minimum coefficients (r0i ) between grain yield, and RDWD as well as RLD in four patterns appeared in supper soil layer (0–20 cm) (Table 7). In T1 and T3 patterns, the maximum coefficients between grain yield, and RDWD as well as RLD appeared in middle soil layer (40–60 cm). However, these variants in T2 and T4 gradually increased with the increased soil depths until maturity. The gray correlation coefficients between ARD and grain yield in four patterns in the 40–100 cm soil layers were higher than those of in the 0–40 cm soil layers. In the 0–20 cm soil layer, the gray correlation coefficient between grain yield and ARD in T1 was higher than that in T2, and in the 20–100 cm soil layer, this parameter in T1 was lower than T2 pattern. Above 60 cm soil layer, the coefficients in T3 were higher than those in T4, but lower in deep soil layers (60–100 cm).

Year

3.5. Correlations between wheat grain yield and wheat root growth parameters

Table 6 Changes of average root diameter of winter wheat in the different soil layers under different cultivation patterns (mm).

the increased soil depths (Fig. 3). In above soil layers (<40 cm) in T1, RDWD and RLD peaked at the heading stage, whereas the peak of RDWD and RLD in T2, T3 and T4 were postponed to anthesis and the highest value appeared in T3. In middle soil layer (40–60 cm), RDWD and RLD increased to peak at anthesis, being markedly (P < 0.05 and 0.01) higher in T3 and T4 than those in T1 and T2. In deeper soil layers (60–100 cm), however, RDWD and RLD in four patterns gradually increased onward with the development process. In comparison with T1, the mean values of RDWD and RLD in T2 in upper soil layer (0–20 cm) reduced by 18.9% and 20.2%, respectively. Similarly, the mean values of RDWD and RLD in T4 were lower than those in T3 by 4.9% and 11.7%, respectively. In the 40–100 cm soil layers, however, the mean value of RDWD in T2 was higher than that in T1 by 36.5%, and this parameter in T4 was higher than in T3 by 5.9%. In the 20–100 cm soil layers, the mean value of RLD in T2 was markedly higher than that in T1 by 3.9–45.2% and the differences became more as the development stages proceeded onward. Compared to T3, in the 20–60 cm soil layers, the mean value of RLD in T4 remarkably declined by 6.6–7.4%, while this parameter in T4 in deeper soil layer (>60 cm) increased by more than 15.0%. In two growth years, ARD in four patterns showed similarly spatiotemporal change profiles: ARD increased at the beginning stage of wheat development, then decreased thereafter. Furthermore, this parameter also gradually decreased with the increased soil depths, and ARD in the 80–100 cm soil layer was higher than that in the 60–80 cm soil layer (Table 6). In the 0–40 cm soil layer, ARD in four patterns peaked at the heading stage in the two sampling years. In the 40–60 cm soil layer, the peak of ARD appeared in T1 at the heading stage, whereas it was postponed to anthesis in T2, T3 and T4. In deeper soil layers (60–100 cm), the peak of ARD in four patterns was also postponed to anthesis. In both middle and deep soil layers, ARD in T2 at maturity was higher than that in T1 by 4.1%, and this parameter in T4 was also higher than that in T3 by 4.0%.

215

T4

Y. Wang et al. / Field Crops Research 156 (2014) 208–218

216

Y. Wang et al. / Field Crops Research 156 (2014) 208–218

Table 7 Gray correlations numerical (r0i ) among root parameters of different soil layer with wheat yield. Items

Year

2008–2009 Root dry weight density (g m−3 ) 2009–2010

2008–2009 Root length density (cm cm−3 ) 2009–2010

2008–2009 Average root diameter (mm) 2009–2010

Treatments

Soil depth (cm) 0–20

20–40

40–60

60–80

80–100

T1 T2 T3 T4 T1 T2 T3 T4

0.6663ns 0.6569ns 0.6681ns 0.6593ns 0.6767ns 0.6689ns 0.6881ns 0.6850ns

0.6802ns 0.6815ns 0.6933ns 0.6659ns 0.6890ns 0.7080ns 0.6978ns 0.6911ns

0.7267ns 0.6851ns 0.7391ns 0.7173ns 0.7895* 0.7235ns 0.7494ns 0.7168ns

0.7188ns 0.6871ns 0.7125ns 0.6895ns 0.7007ns 0.7546ns 0.7004ns 0.6961ns

0.6925ns 0.7345ns 0.7309ns 0.7204ns 0.6960 ns 0.7918* 0.7141ns 0.7390 ns

T1 T2 T3 T4 T1 T2 T3 T4

0.6970ns 0.6871ns 0.6782ns 0.6795ns 0.6886ns 0.6582ns 0.6847ns 0.6854ns

0.7173ns 0.7003ns 0.7398ns 0.6840ns 0.7327ns 0.6883ns 0.7538ns 0.6882ns

0.7766ns 0.7005ns 0.7496ns 0.7087ns 0.7562ns 0.6906ns 0.7746ns 0.7130ns

0.7153ns 0.7309ns 0.7274ns 0.7262ns 0.7289ns 0.7459ns 0.7445ns 0.8013*

0.7162ns 0.7585ns 0.7121ns 0.7512ns 0.7269ns 0.7567ns 0.7006ns 0.8231*

T1 T2 T3 T4 T1 T2 T3 T4

0.7978* 0.7548 ns 0.8084 ns 0.7717 ns 0.6722ns 0.6634 ns 0.7682ns 0.7546 ns

0.7386 ns 0.8108* 0.7881ns 0.7229ns 0.6692ns 0.6790ns 0.8272* 0.6577ns

0.8804* 0.8982** 0.8653* 0.8703* 0.8704* 0.7687 ns 0.8464* 0.7824 ns

0.8656* 0.9285** 0.8794* 0.9130** 0.7999* 0.9133** 0.8901* 0.9018**

0.8182* 0.9141** 0.8721* 0.9638** 0.7806 ns 0.8274* 0.8588* 0.9061**

Note: ns indicate non-significant. * and ** indicate significant differences at p-levels of 0.05 and 0.01, respectively. P(t0.05 ) = 2.571, P(t0.01 ) = 4.032.

root (Holanda et al., 1998; Lampurlanés et al., 2001; Miao et al., 2002; Xue et al., 2003; Huang et al., 2012). The cultivation patterns are important methods to regulate the spatial construction and distribution of the root system (Liu et al., 1993; Wu et al., 2005; Wang et al., 2012). Zhang and Liu, (1993) and Liu et al. (2008) have explored the effects of irrigation, fertilization, nitrogen, phosphates and water deficit on the growth of wheat root system. In these studies, winter wheat root systems in the Northern China Plain grew fast before winter, continued to grow during the winter, quickened since the jointing stage, peaked at the heading stage, and then declined. The growths of root length and root weight were consistent with the Logistic model. The spatial distribution patterns varied with the depths of the soil. The root length and root weight decreased from top to bottom soil layers. The root growth conformed to the exponential decline model. Our results were similar to the data of these experiments. Combined with tillage and fertilizer and water management, TRDW, TRL and ARD in four patterns showed similar temporal changes: first increased and then decreased as the root system grew onward (Table 4). The peak of root growth in T1 appeared earlier and decreased faster, and te and tm of TRDW and TRL in this pattern also occurred earlier while these parameters in T2, T3 and T4 appeared later. The wmax of TDRW, TRL, ARD, as well as the c¯ and cm in T2, T3 and T4 were significantly higher than those of T1, whereas the tm and te of ARD in T2 appeared earlier than those in T1, those of ARD in T4 also earlier than those in T3 (Table 5). These may due to larger seed quantity, more amounts seedling community, and more fierce growth competitions among plants in T1. In addition, in T1 pattern, application of all fertilizers before the sowing period provided the sufficient nutrition during the early stage of growth, while resulting in the shortage of nutrition after heading stage. In the other three cultivation patterns, the community structures were optimized by maintaining with high biomasses of root system in the late growth period, postponing the deterioration process of the root, supplying water and nutrition for the growth, grain formation and filling of the upper ground plant parts. These three cultivation patterns favored the dry biomass production and final grain yield formation (Table 3).

Previous studies on root system growth models focused on the static models between root system and water and fertilizer, which merely reflected the adaptive variations among the root system, water and fertilizers (Lecompte et al., 2001; Pages et al., 2004). Our experiments quantitatively explored the dynamic variations of the winter wheat growth under different cultivation patterns using the Beta model. The determination coefficients (R2 ) of the Beta equation on TRDW, TRL and ARD were more than 0.7, and F tests on their R2 were significant (P < 0.05 and 0.01), indicating that Beta equation model may be suitable to reflect the root growth process of wheat (Fig. 2).

4.2. Effect of cultivation patterns on grain yield Grain products of wheat plants and their rooting pattern modifications are greatly affected by many factors including field operations, climate, soil types, fertilizer applications, planting density, and irrigation schemes. Our previous results also confirmed the interactions of these ecological factors (Wang et al., 2012). These should be the major factors to determine the grain yields. This study showed that, in T1, the growths between ground and underground organs were inharmonious, competitions among plants were aggravated, and nutrition supply and plant growth were also inharmonious. These resulted in the reduced numbers of grains per spike, unfilled grains, and the lowed kernel weights (Table 3). The yields of T3 were more 17.7–25.8% than T1, whereas the risk inT3 became higher possibly because of the large amounts of used fertilizers and serious disease and insects. Thus, it is difficult to use this pattern in large field areas due to high cost and intensive field managements (Table 2). In comparison with T1, T2, T3 and T4 had more harmonious yield factors. Especially, in T4, amounts of the sowed seeds were reduced, the application ways (amounts, proportions, applied dates, etc.) of N were optimized, and thus the yields in this pattern were more than T1 by 13.4% and 24.5% in 2008–2009 and 2009–2010, respectively (Table 2). Therefore, T4 should be suitable in fields and likely be accepted by farmers.

Y. Wang et al. / Field Crops Research 156 (2014) 208–218

4.3. Relationships between root growth and grain yields of winter wheat The root systems in deep soil functioned in the grain yields of wheat (Zhang et al., 2004). Soil water and nutrients absorbed by root systems were mainly dependent on the spatial arrangement of the roots (Liu et al., 2003). The increased distribution proportions of the root system in the deep soil helped to enhance water and nutrition absorption and grain yields (Manschadi et al., 2010; Li et al., 2010; Shi et al., 2012). In comparison with traditional irrigation methods, the water-saving cultivation pattern significantly increased the proportions of root systems in deep soil layer, and thus the well developed deep soil root systems further enhanced the nitrogen utilization of deep soil (Wu et al., 2005). Traditional fertilizer application significantly reduced the root dry weight in the deep soil layers, weakened the stress resistance in the late growth period, and was not helpful to the formation of grain yields. Optimized fertilizer application prohibited the growth of root system and decreased root dry weight in the 0–60 cm soil layers, whereas significantly increased the root dry weight in the 60–120 cm soil layers and total root dry weight in all soil layers, and resulted in the enhanced grain yields (Li et al., 2008). The RLD in the upper soil profile was usually great, but a larger root system in the top soil layer might not be necessary and did not affect root water uptake (Zhang et al., 2009). Root pruning significantly improved WUE of winter wheat by lowering the root biomass in the upper soil layer (Ma et al., 2008). Smaller RLD in the deep soil profile restricted crop water use, however, larger RLD in a deep soil profile might be captured and water and nutrient were used efficiently, and grain yields can be greatly boosted under dry conditions (Lecompte et al., 2001). Our results were similar with these studies. Compared to T1, T2 and T4 achieved higher yields and characterized with larger amounts of root systems in deep soil layers, as indicated by higher RDWD, RLD and ARD (Table 6 and Fig. 3) and gray correlation coefficients among grain yield, RDWD, RLD and ARD (Table 7). These suggested that rich roots in the middle and lower soil layer could play important roles in improving grain yields. Although T3 also attained higher grain yields and had plentiful roots in the middle and lower soil layers (Table 6 and Fig. 3), it was seldom used in fields because of the high risk and cost. Therefore, to promote the growth of root system and increase the root system number and quality in deep soil may be considered as the major technology to further enhance grain yields.

5. Conclusions TRDW, TRL and ARD had the similar pattern with the single peak cure in four patterns in two growth years: slow growth, quick growth, and then gradual decline. te and tm of TRDW and TRL in T1 occurred more early, whereas those in T2, T3 and T4 patterns delayed. The wmax , c¯ and cm of TRDW, TRL and ARD in T2, T3 and T4 were significantly higher than those of T1. In the middle and lower soil layer (20–100 cm), the gray correlation coefficients among grain yield, RDWD, RLD and ARD in T2 were remarkably higher than those in T1. Compared to T4, these coefficients in T3 above 60 cm soil layer were markedly higher, whereas these coefficients in deep soil layers (60–100 cm) were lower. In both middle or lower soil layers (40–100 cm), the increased RDWD, RLD and ARD in T2 and T4 may help to expand the growing space of the root system, enhance the absorption ability to water and nutrition in deep soil layers, reason the synchronized and concerted growths of root and canopy, and thus alleviate the adverse effects of abnormal climate on the growth and yield of wheat.

217

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