Scientia Agricultura Sinica ›› 2020, Vol. 53 ›› Issue (13): 2691-2702.doi: 10.3864/j.issn.0578-1752.2020.13.017

• TECHNOLOGY AND MECHANISM FOR RECOVERY OF ABANDONED CROPLAND • Previous Articles     Next Articles

Coupling Mechanism of Herbage-Water-Nitrogen Fertilizer in Abandoned Farmland in Meadow Steppe

LI Da1,FANG HuaJun2,WANG Di1,XU LiJun3(),TANG XueJuan3,XIN XiaoPing3,NIE YingYing3,Wuren qiqige4   

  1. 1Institute of Animal Husbandry Science of Baicheng/Hulunber Grassland Ecosystem Observation and Research Station/National Forage Industry Technology System Baicheng Station, Baicheng 137000, Jilin
    2 Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101
    3Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/Hulunber Grassland Ecosystem Observation and Research Station, Beijing 100081
    4 Hulunber University/Key Laboratory of Meadow Grassland Ecosystem and Global Change in Inner Mongolia Autonomous Region, Hulunber 021800, Inner Mongolia
  • Received:2019-09-22 Accepted:2019-12-26 Online:2020-07-01 Published:2020-07-16
  • Contact: LiJun XU E-mail:xulijun@caas.cn

Abstract:

【Objective】 The study was to investigate the effects of three factors, including water replenishment, nitrogen application, and pasture type, on the biomass, plant nutrient composition and soil quality of artificial grassland communities by planting artificial grassland with different planting patterns of Hulunber, and to reveal the retreat of Hulunbuir area and the water-fertilizer coupling mechanisms of cultivated land artificial grassland, so as to optimize the mode of planting management. 【Method】 The experiment was carried out at the Hulunber Grassland Ecosystem Observation and Research Station. On June 6, 2016, the experiment began with four blocks, each of which included three test factors pasture types (P) and nitrogen application level (N) and Irrigation (I); forage types included three treatments: alfalfa (P1), awnless brome (P2), and alfalfa and awnless brome 1:1 mixed sowing (P3); nitrogen application levels included no nitrogen (N0), low nitrogen (N1: 75 kgN·hm-2·a-1) and high nitrogen (N2: 150 kgN·hm-2·a-1). The hydration included two levels (I0: no water, I1: hydration). There were 72 test plots, each of which was 7 m×10 m, and the row spacing was 1 m; it replenished the water 3 times every year in June, July and August, and the water per unit area was 20 mm. The nitrogen application (chemical pure urea) was twice in the seedling (returning) and tillering stages, respectively. Grassland biomass, nutrients (plant crude protein, neutral detergent fiber and acid detergent fiber) and soil nutrients (soil total nitrogen, soil organic carbon and soil pH) were measured in 2016 and 2017. 【Result】 (1) The response of (N), (I), (P) and (P×I) to yield in the year of planting (2016) reached a significant level (P<0.05), and two measurements in 2017. The total yield of the production reached a significant level (P<0.05) in response to test factors such as (N), (P), (P×I), (P×N), (N×I×P), and mixed (P3). Under low water (I0) conditions, the yield of low nitrogen (N1) was significantly higher than that of the other treatment groups (P<0.05), with an average of 17 801.19 kg·hm-2. (2) The crude protein content in 2016 and 2017 were P1 treatment>P3 treatment>P2 treatment, in 2016. P1, P2 and P3 treatment showed that the CP content increased with the increase of nitrogen level when the hydration (I) conditions were the same, and P1 was not replenished under water (I0) conditions. The crude protein content under P1N2I0 was significantly higher than that under P1N0I0, P1N1I0, and P1N1I1 (P<0.05), reaching a maximum value of 19.08%; in 2017, under P3 at I0 conditions, the CP content of the lower N1 level (15.12%) was significantly higher than that of N0 (P<0.05). (3) Both nitrogen application and water addition promoted the negative growth of soil SOC content, positive TN content, and negative pH growth. The SOC growth of the topsoil and the bromegrass were significantly higher than that of the mixed seeding (P<0.05), and the TN growth of the topsoil was significantly higher than that of the bromegrass and mixed seeding (P<0.05); under the surface and subsurface of 2016, the ratio of soil carbon to nitrogen (C/N) was higher than that of 2017, the average surface layer was 17.39% higher, and the subsurface layer was 15.18% higher. The carbon and nitrogen ratio of surface soil was more obvious. The surface soil carbon and nitrogen ratio was P1N0I1 in 2016, with the highest value of 8.15; in 2017, the highest value under P1N2I0 was 5.67. The carbon and nitrogen in the subsurface soil was 6.36 higher than that under P1N2I1 in 2016, and the highest under P3N2I1 in 2017 was 5.67. 【Conclusion】 In the second year of planting in Hulunber, the coupling effect of herbage, water and nitrogen fertilizer had a significant effect on the biomass of the grass. The coupling effect of water and nitrogen fertilizer had a synergistic effect on the nutrient accumulation of the grass. The construction of artificial grassland plant could reduce a C/N and soil quality to drop, and adding in different kinds of grass, and water and nitrogen levels all showed the 0-20 cm soil SOC content and pH value were lower and soil TN content increased, indicating that soil acidification occurs, bean-grain mixed soil pH lower amplitude was less than unicast, and high nitrogen and filling water could be reduced to a significantly increased the soil pH value.

Key words: artificial grassland, nitrogen application, adding water, mixed sowing of bean-grass, community biomass, soil nutrients, Hulunber

Fig. 1

Variation trend of meteorological conditions temperature and precipitation in 2016-2017"

Table 1

Experimental design"

处理组
Treatment
牧草类型
Pasture
补水
Irrigation
(mm·m-2)
氮水平
Nitrogen level
(kg N·hm-2·a-1)
P1I0N0 苜蓿单播
Alfalfa
(P1
0 0
P1I0N1 75
P1I0N2 150
P1I1N0 20 0
P1I1N1 75
P1I1N2 150
P2I0N0 无芒雀麦单播
Awnless brome
(P2
0 0
P2I0N1 75
P2I0N2 150
P2I1N0 20 0
P2I1N1 75
P2I1N2 150
P3I0N0 苜蓿+无芒雀麦混播
Alfalfa+ Awnless
brome(P3
0 0
P3I0N1 75
P3I0N2 150
P3I1N0 20 0
P3I1N1 75
P3I1N2 150

Table 2

Summary of ANOVA evaluating the effects of N, I , P, and their interactions on dry weight"

Source of variation 2016 2017
F P F P
氮 Nitrogen 0.200 n.s. 6.281 *(0.034)
水 Irrigation 0.067 n.s. 4.951 n.s.
牧草 Pasture 1.738 n.s. 21.827 **(0.002)
氮×水 Nitrogen×Irrigation 0.090 n.s. 0.875 n.s.
水×牧草 Irrigation×Pasture 0.752 n.s. 19.640 **(<0.01)
牧草×氮 Pasture×Nitrogen 0.438 n.s. 23.888 **(0.001)
水×牧草×氮Irrigation×Pasture×Nitrogen 1.099 n.s. 4.270 *(0.022)

Table 3

Comparison of the biomass of lower pasture between treatments"

处理组
Treatment
产量Dry weight (kg·hm-2)
2016 2017
P1I0N0 1725.00±190.02a 9954.26±756.41a
P1I0N1 2249.63±317.60a 8241.24±389.35a
P1I0N2 1385.93±226.72a 9546.30±1391.84a
P1I1N0 2171.67±263.37a 9356.11±471.86a
P1I1N1 1936.11±370.06a 10184.04±1492.04a
P1I1N2 2150.46±272.86a 10705.19±1653.52a
P2I0N0 2592.69±363.03a 11030.56±292.88a
P2I0N1 1855.28±416.00a 11133.80±173.71a
P2I0N2 2767.69±595.23a 9316.60±1001.31b
P2I1N0 1829.26±316.65a 11894.91±163.28a
P2I1N1 2258.80±505.40a 11562.36±122.73a
P2I1N2 2672.50±675.11a 8542.5±555.63b
P3I0N0 2178.06±511.10a 13253.33±637.41bc
P3I0N1 2214.63±341.56a 17801.19±503.09a
P3I0N2 2594.17±560.39a 13683.80±266.01b
P3I1N0 2313.52±445.38a 12169.26±394.49cd
P3I1N1 2554.63±256.94a 13263.98±396.62bc
P3I1N2 2140.74±573.56a 11027.78±384.61d

Table 4

Effects of different treatments on the change of nutritional composition of grassland from 2016 to 2017"

处理组
Treatment
2016 2017
粗蛋白
CP (%)
中性洗涤纤维
NDF (%)
酸性洗涤纤维
ADF (%)
相对饲喂价值
RFV
粗蛋白
CP (%)
中性洗涤纤维
NDF (%)
酸性洗涤纤维
ADF (%)
相对饲喂价值
RFV
P1I0N0 16.61±0.14b 29.85±1.26a 20.12±1.88a 229.99±13.80a 15.87±0.70a 48.83±0.81a 30.83±1.45a 125.35±3.81a
P1I0N1 17.51±0.41ab 33.49±2.42a 21.23±2.71a 205.41±19.95a 15.51±0.42a 49.84±0.95a 31.87±0.56a 121.17±2.53a
P1I0N2 19.08±0.47a 28.47±1.70a 17.81±1.50a 248.48±17.10a 16.18±1.41a 48.91±1.38a 30.91±1.64a 126.67±7.02a
P1I1N0 16.69±0.74b 32.31±2.12a 21.51±2.76a 211.44±18.30a 15.27±0.68a 49.00±1.08a 30.90±1.39a 124.56±4.55a
P1I1N1 16.62±1.27b 35.32±4.64a 24.48±2.68a 196.45±31.60a 15.30±0.55a 49.95±0.98a 31.89±0.79a 120.19±2.62a
P1I1N2 17.55±0.47ab 31.35±2.61a 22.09±1.86a 218.12±21.46a 15.12±0.66a 49.54±1.88a 32.29±1.65a 122.27±7.52a
P2I0N0 16.37±0.68a 34.27±1.32a 19.71±1.11a 200.74±8.91a 10.21±1.02a 65.08±2.02a 36.99±1.27a 86.53±4.19a
P2I0N1 17.93±0.20a 31.12±1.67a 17.55±1.74a 227.76±17.80a 10.24±0.59a 63.46±1.14a 36.67±0.89a 88.70±2.59a
P2I0N2 18.19±1.21a 33.61±1.48a 17.65±1.88a 209.85±13.62a 12.42±0.47a 63.40±0.99a 34.76±0.99a 90.93±2.53a
P2I1N0 16.59±0.68a 31.07±1.07a 17.33±1.19a 226.77±9.17a 10.04±1.42a 61.77±1.18a 34.51±1.14a 93.74±3.07a
P2I1N1 17.46±1.11a 33.47±0.91a 18.86±1.62a 206.73±8.44a 11.33±0.84a 62.43±1.49a 36.55±1.96a 91.68±4.56a
P2I1N2 17.88±1.56a 32.34±0.97a 18.67±1.83a 214.9±9.80a 11.01±0.61a 64.21±1.47a 36.75±1.24a 87.62±2.96a
P3I0N0 16.79±1.38a 33.65±1.85a 22.24±2.51a 200.61±15.95a 13.15±0.52b 55.33±2.68a 33.72±1.55a 106.87±7.69a
P3I0N1 16.82±1.23a 32.61±1.93a 20.99±2.30a 209.97±16.51a 15.12±0.42a 53.29±0.89a 31.09±1.25a 113.61±3.51a
P3I0N2 17.39±1.88a 33.77±2.77a 21.85±1.42a 202.83±19.54a 14.69±0.39ab 54.22±1.71a 31.20±0.40a 111.50±3.73a
P3I1N0 17.93±1.27a 30.85±1.70a 19.95±2.29a 224.03±16.75a 14.71±0.42ab 54.75±2.49a 33.01±1.44a 109.03±6.42a
P3I1N1 17.62±1.09a 31.96±2.59a 20.27±1.68a 218.49±23.41a 13.77±0.80ab 55.76±0.87a 33.29±1.27a 105.48±3.06a
P3I1N2 18.34±1.05a 31.34±1.69a 18.44±1.89a 223.95±16.67a 14.65±0.46ab 56.37±2.33a 33.56±1.56a 105.02±5.91a

Fig. 2

Changes of SOC, TN and pH in soils under three different treatments from 2016 to 2017 Variation = existing value - original value. The data bars in the figure represent M±SE. The same as below"

Fig. 3

Changes of C/N ratio in different treatment groups from 2016 to 2017"

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