Crops ›› 2024, Vol. 40 ›› Issue (2): 148-157.doi: 10.16035/j.issn.1001-7283.2024.02.018

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Effects of Water Deficit in Soybean Seedling Stage on Soil Enzyme Activity and Microbial Diversity

Li Duo1(), Wang Chen1, Zhang Mingcong2, Cao Liang1, Jin Xijun1, Zhang Yuxian1, Wang Mengxue1()   

  1. 1College of Agronomy, Heilongjiang Bayi Agricultural University, Daqing 163000, Heilongjiang, China
    2Key Laboratory of Low-Carbon Green Agriculture in Northeastern China, Ministry of Agriculture and Rural Affairs, Daqing 163000, Heilongjiang, China
  • Received:2022-09-27 Revised:2023-11-02 Online:2024-04-15 Published:2024-04-15

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Abstract:

In order to study the effects of different degrees of water deficit on soil enzyme activities and soil microbial diversity of soybean, a pot experiment was conducted with drought sensitive soybean Suinong 26. At seedling stage, soil water content was set at 70% (normal water supply, CK), 60% (mild water deficit, T1), 50% (moderate water deficit, T2) and 40% (severe water deficit, T3) of field capacity treatments, the soil enzyme activity was determined, and the high-throughput sequencing technique was used to study the community composition and diversity of soil microorganisms. The results showed that soil urease activity in T1 treatment was the highest in all growth stages except mature stage. Compared with CK, soil sucrase activity in different water deficit treatments decreased by 13.89% to 21.94%. After rehydration, soil catalase activity was the highest with T2 treatment, while soil phosphatase activity reached the highest with T1 treatment. Water deficit could lead to changes in the number of soil microorganisms, increase in richness, and there was a certain correlation with enzyme activities. The yield per plant of soybean reached the maximum with T1 treatment, which was significantly higher than that of CK by 9.55%. To sum up, moderate water deficit could promote soil enzyme activity to a certain extent, and further affected soil microenvironment, so as to achieve the purpose of saving water and increasing production.

Key words: Soybean, Water deficit, Soil enzymes, Soil microorganisms

Fig.1

Effects of different degrees of water deficiency at seedling stage on urease activities Different letters indicate significant difference at P < 0.05 level, the same below."

Fig.2

Effects of different degrees of water deficiency at seedling stage on sucrase activities"

Fig.3

Effects of different degrees of water deficiency at seedling stage on catalase activities"

Fig.4

Effects of different degrees of water deficiency at seedling stage on phosphatase activities"

Fig.5

Venn diagram of soil bacteria with different degrees of water deficit and rehydration treatment at seedling stage (a): Water deficit treatment, (b) After rehydration."

Fig.6

Venn diagram of soil fungi with different degrees of water deficit and rehydration treatments at seedling stage (a): Water deficit, (b) After rehydration."

Table 1

Alpha diversity index of soil bacteria with different degrees of water deficit and rehydration treatment at seedling stage"

时期
Stage		 处理
Treatment		 Chao1指数
Chao1 index		 ACE指数
ACE index		 Simpson指数
Simpson index		 Shannon指数
Shannon index		 覆盖率
Coverage (%)
控水后
After water deficit
 CK 2132.48±21.47b 2102.97±32.01b 0.9973±0.0003a 9.65±0.06a 99.71
T1 2149.28±28.03b 2108.51±24.70b 0.9971±0.0001a 9.58±0.01a 99.68
T2 2172.92±33.32b 2149.11±45.74b 0.9971±0.0003a 9.64±0.17a 99.70
T3 2257.39±28.20a 2240.09±31.32a 0.9972±0.0004a 9.72±0.17a 99.71
复水后
After rehydration
 CK 2255.41±66.58a 2252.51±53.45a 0.9969±0.0003b 9.61±0.04a 99.65
T1 2186.41±108.55a 2166.79±110.05a 0.9971±0.0003ab 9.67±0.03a 99.67
T2 2284.27±45.35a 2264.62±58.90a 0.9975±0.0003a 9.80±0.19a 99.74
T3 2295.40±15.72a 2282.64±21.95a 0.9973±0.0002ab 9.69±0.07a 99.74

Table 2

Alpha diversity indexes of soil fungi with different degrees of water deficit and rehydration treatments at seedling stage"

时期
Stage		 处理
Treatment		 Chao1指数
Chao1 index		 ACE指数
ACE index		 Simpson指数
Simpson index		 Shannon指数
Shannon index		 覆盖率
Coverage (%)
控水后
After water deficit
 CK 591.47±20.69c 599.23±24.48c 0.9710±0.0291a 6.80±0.36a 99.91
T1 788.53±16.93a 823.62±46.77a 0.9696±0.0206a 6.96±0.21a 99.85
T2 694.36±29.35b 704.69±24.29b 0.9563±0.0396a 6.80±0.33a 99.89
T3 637.46±33.89c 638.80±32.29c 0.9686±0.0159a 6.51±0.27a 99.87
复水后
After rehydration
 CK 543.33±24.50c 594.31±29.67c 0.9211±0.0412b 5.82±0.30c 99.89
T1 757.29±23.45a 872.20±29.58ab 0.9339±0.0419ab 6.75±0.34b 99.85
T2 675.13±34.01b 894.08±11.97a 0.9608±0.0230ab 6.41±0.26b 99.84
T3 732.85±37.43a 827.30±49.88b 0.9854±0.0068a 7.45±0.31a 99.86

Fig.7

Community structure and relative abundance of soil bacteria at phylum classification level in different degrees of water deficit (a) and rehydration treatments (b) at seedling stage The length of the color block indicates the relative content of the species, the figure only indicates the top ten major phyla with abundance greater than 0.1%, the same below."

Fig.8

Community structure and relative abundance of soil fungi at phylum classification level in different degrees of water deficit (a) and rehydration treatments (b) at seedling stage"

Table 3

Correlations between soil enzyme activities and Alpha diversity indexes of soil microorganisms with different degrees of water deficit and rehydration treatments"

分类
Classify		 多样性指数
Diversity index		 脲酶活性
Urease activity		 蔗糖酶活性
Sucrase activity		 过氧化氢酶活性
Catalase activity		 磷酸酶活性
Phosphatase activity
细菌Bacteria Chao1 -0.431* -0.207 0.359 -0.116
ACE -0.444* -0.229 0.314 -0.094
Simpson -0.167 0.126 0.420* -0.024
Shannon -0.192 -0.080 0.471* 0.027
真菌Fungi Chao1 0.537** -0.217 0.091 -0.034
ACE 0.520** -0.077 0.267 0.290
Simpson -0.148 0.166 0.094 -0.332
Shannon -0.015 0.072 -0.161 -0.204

Table 4

Effects of different degrees of water deficiency on soybean yield and its components"

处理
Treatment		 株高
Plant height
(cm)		 茎粗
Stem diameter
(mm)		 节数
Pitch
number		 单株荚数
Number of pods
per plant		 单株荚重
Pod weight
per plant (g)		 单株粒数
Grains per
plant		 单株产量
Yield per
plant (g)
CK 82.37±1.46a 9.10±0.20a 16.67±0.87ab 32.22±1.20a 8.71±0.14a 67.89±2.93b 13.40±0.20b
T1 79.16±0.98b 7.97±0.07b 17.11±0.93a 33.44±2.07a 7.24±0.17b 71.33±3.28a 14.68±0.20a
T2 75.95±0.98c 7.75±0.04c 16.00±1.12ab 28.67±1.22b 6.76±0.18c 65.89±2.32bc 12.84±0.17c
T3 72.74±0.98d 7.54±0.07d 15.78±0.97b 27.78±1.79b 5.90±0.16d 64.33±2.65c 12.75±0.30c
[1] 陈亚宁, 李玉朋, 李稚, 等. 全球气候变化对干旱区影响分析. 地球科学进展, 2022, 37(2):111-119.
doi: 10.11867/j.issn.1001-8166.2022.006
[2] 袁仁文, 刘琳, 张蕊, 等. 植物根际分泌物与土壤微生物互作关系的机制研究进展. 中国农学通报, 2020, 36(2):26-35.
doi: 10.11924/j.issn.1000-6850.casb18090023
[3] 陆宁海, 杨蕊, 郎剑锋, 等. 秸秆还田对土壤微生物种群数量及小麦茎基腐病的影响. 中国农学通报, 2019, 35(34):102-108.
doi: 10.11924/j.issn.1000-6850.casb18070071
[4] 刘亚军, 王文静, 王红刚, 等. 作物轮作对甘薯田土壤微生物群落的影响. 作物杂志, 2021(6):122-128.
[5] 韩冰. 灌水控制下限对设施土壤N2O排放及微生物功能多样性的影响. 沈阳: 沈阳农业大学, 2017.
[6] 刘奎, 葛壮, 徐英德, 等. 不同耕作方式下黑土微生物群落对干湿交替的响应. 土壤学报, 2020, 57(1):206-216.
[7] Ochoa-Hueso R, Collins S L, Delgado-Baquerizo M, et al. Drought consistently alters the composition of soil fungal and bacterial communities in grasslands from two continents. Global Change Biology, 2018, 24:2818-2827.
doi: 10.1111/gcb.14113 pmid: 29505170
[8] 景宇鹏, 李跃进, 姚一萍, 等. 盐渍化土壤酶活性及其与微生物、理化因子的关系. 中国农业科技导报, 2016, 18(2):128-138.
doi: 10.13304/j.nykjdb.2015.407
[9] 仙旋旋, 孔范龙, 朱梅珂, 等. 水盐梯度对滨海湿地土壤养分指标和酶活性的影响. 水土保持通报, 2019, 39(1):65-71.
[10] 田幼华, 吕光辉, 杨晓东, 等. 水盐胁迫对干旱区植物根际土壤酶活性的影响. 干旱区资源与环境, 2012, 26(3):158-163.
[11] 邱丽丽, 张佳宝, 赵炳梓. 土壤干旱对两品种小麦根际土壤微生物群落组成和酶活性的影响. 干旱区资源与环境, 2022, 36(2):116-122.
[12] 李旺霞, 陈彦云, 陈科元, 等. 不同降雨量对雨养农业区土壤酶活性和土壤微生物的影响. 南方农业学报, 2015, 46(9):1579-1583.
[13] 闫春娟, 宋书宏, 王文斌, 等. 不同基因型大豆生理特性和产量对不同降雨条件的响应. 节水灌溉, 2021(5):8-14.
[14] 李盛有, 孙旭刚, 王昌陵, 等. 不同嫁接方式下大豆对干旱胁迫的响应. 中国油料作物学报, 2020, 42(4):632-639.
[15] 邹京南, 曹亮, 王梦雪, 等. 外源褪黑素对干旱胁迫下大豆结荚期光合及生理的影响. 生态学杂志, 2019, 38(9):2709-2718.
[16] 关松荫. 土壤酶及其研究方法. 北京: 农业出版社, 1986.
[17] 杨兰芳, 曾巧, 李海波, 等. 紫外分光光度法测定土壤过氧化氢酶活性. 土壤通报, 2011, 42(1):207-210.
[18] 王理德, 王方琳, 郭春秀, 等. 土壤酶学硏究进展. 土壤, 2016, 48(1):12-21.
[19] 姜佰文, 马晓东, 周宝库, 等. 有机无机肥料配施对土壤酶活性、微生物量及玉米产量影响. 东北农业大学学报, 2016, 47(5):23-28,43.
[20] 肖新, 朱伟, 肖靓, 等. 适宜的水氮处理提高稻基农田土壤酶活性和土壤微生物量碳氮. 农业工程学报, 2013, 29(21):91-98.
[21] 陶佳. 断根与干旱对苹果幼树生长发育及根际环境的影响. 杨凌: 西北农林科技大学, 2015.
[22] 周芙蓉, 王进鑫, 杨楠, 等. 水分和铅胁迫对土壤酶活性的影响. 草地学报, 2013, 21(3):479-484.
doi: 10.11733/j.issn.1007-0435.2013.03.011
[23] Kivlin S N, Treseder K K. Soil extracellular enzyme activities correspond with abiotic factors more than fungal community composition. Biogeochemistry, 2014, 117(1):23-37.
doi: 10.1007/s10533-013-9852-2
[24] 玛伊努尔·依克木, 张丙昌, 买买提明·苏来曼. 古尔班通古特沙漠生物结皮中微生物量与土壤酶活性的季节变化. 中国沙漠, 2013, 33(4):1091-1097.
doi: 10.7522/j.issn.1000-694X.2013.00154
[25] 朱琳, 李玉玺, 王寅, 等. 苗期干旱胁迫下施氮对玉米氮素吸收和土壤生物化学性质的影响. 水土保持学报, 2021, 35(4):267-274.
[26] Seo J, Jang I, Jung J Y, et al. Warming and increased precipitation enhance phenol oxidase activity in soil while warming induces drought stress in vegetation of an Arctic ecosystem. Geoderma, 2015, 259/260:347-353.
doi: 10.1016/j.geoderma.2015.03.017
[27] 方静. 耐旱春小麦根际微生物对干旱胁迫的响应机制. 呼和浩特: 内蒙古大学, 2021.
[28] Xu L, Naylor D, Dong Z B, et al. Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria. Proceedings of the National Academy of Sciences of the United States of America, 2018, 115(18):4284-4293.
[29] Hartmann M, Brunner I, Hagedorn F, et al. A decade of irrigation transforms the soil microbiome of a semi-arid pine forest. Molecular Ecology, 2017, 26(4):1190-1206.
doi: 10.1111/mec.13995 pmid: 28028891
[30] 岳丹丹, 韩贝, Abid Ullah, 等. 干旱条件下棉花根际真菌多样性分析. 作物学报, 2021, 47(9):1806-1815.
doi: 10.3724/SP.J.1006.2021.04162
[31] 杨司睿, 范井伟, 孙永强, 等. 罗布泊腹地人工植被梭梭的光学特性及其对干旱胁迫的响应. 干旱区研究, 2018, 35(2):379-386.
[32] 唐梅, 李伏生, 张富仓, 等. 不同磷钾条件下苗期适度水分亏缺对大豆生长及干物质积累的影响. 干旱地区农业研究, 2006(5):109-114.
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