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  • ISSN 1008-505X
  • CN 11-3996/S

鱼蛋白作为激发剂促进还田秸秆腐解和有机碳在土壤中积累

刘心雨, 黄程鹏, 姜培坤, 陈瑾, 徐秋芳

刘心雨, 黄程鹏, 姜培坤, 陈瑾, 徐秋芳. 鱼蛋白作为激发剂促进还田秸秆腐解和有机碳在土壤中积累[J]. 植物营养与肥料学报, 2024, 30(1): 74-86. DOI: 10.11674/zwyf.2023201
引用本文: 刘心雨, 黄程鹏, 姜培坤, 陈瑾, 徐秋芳. 鱼蛋白作为激发剂促进还田秸秆腐解和有机碳在土壤中积累[J]. 植物营养与肥料学报, 2024, 30(1): 74-86. DOI: 10.11674/zwyf.2023201
LIU Xin-yu, HUANG Cheng-peng, JIANG Pei-kun, CHEN Jin, XU Qiu-fang. Using fish protein as activator to stimulate straw decomposition and enhance organic carbon accumulation in soil[J]. Journal of Plant Nutrition and Fertilizers, 2024, 30(1): 74-86. DOI: 10.11674/zwyf.2023201
Citation: LIU Xin-yu, HUANG Cheng-peng, JIANG Pei-kun, CHEN Jin, XU Qiu-fang. Using fish protein as activator to stimulate straw decomposition and enhance organic carbon accumulation in soil[J]. Journal of Plant Nutrition and Fertilizers, 2024, 30(1): 74-86. DOI: 10.11674/zwyf.2023201

鱼蛋白作为激发剂促进还田秸秆腐解和有机碳在土壤中积累

基金项目: 浙江省“尖兵”“领雁”研发攻关计划(2022C02036)。
详细信息
    作者简介:

    刘心雨 E-mail: m15957139713_1@163.com

    通讯作者:

    徐秋芳 E-mail: xuqiufang@zafu.edu.cn

Using fish protein as activator to stimulate straw decomposition and enhance organic carbon accumulation in soil

  • 摘要:
    目的 

    秸秆还田量影响秸秆腐解、后茬作物生长和温室气体排放。研究不同秸秆还田量下,利用鱼蛋白作为激发剂促进秸秆分解、提高土壤有机碳积累的效果,为秸秆和鱼蛋白资源的合理高效利用提供理论依据。

    方法 

    采用室内培养试验方法,设置秸秆还田量、有机激发剂种类及其在总激发剂中的占比3个因素。秸秆还田量包括适量 (7500 kg/hm2)和高量 (10500 kg/hm2) 两个水平;供试有机激发剂包括猪粪、鱼蛋白;猪粪、鱼蛋白激发剂添加量占尿素氮量的比例分别为50%、100% (分别记为P50、F50、P100、F100),以两个秸秆还田量不添加激发剂处理为对照,共10个处理。激发剂总量按照调节投入秸秆碳氮比为35∶1所需要的氮量计算,其中50%和100%的氮量由猪粪、鱼蛋白提供,培养期为60天。培养期间测定CO2和N2O排放速率及累计排放量。培养结束时,测定土壤养分含量、细菌和真菌丰度以及酶活性。

    结果 

    高量秸秆还田虽然可增加土壤中有机碳的积累,但土壤CO2排放量以及单位输入碳的排放量均高于适量秸秆还田土壤。培养前13天,高量和适量秸秆还田的累计CO2排放量占总排放量的40%以上,以F50处理排放量最高。P50和F50处理适量和高量秸秆还田土壤CO2排放总量低于P100和F100处理,而N2O排放正好相反,P50和F50处理土壤有机碳积累也高于P100和F100处理。适量秸秆还田条件下,F50处理的CO2排放速率和N2O排放总量均高于P50;而CO2排放总量显著低于P50,土壤中有机碳积累量显著高于P50处理。适量秸秆还田土壤细菌和真菌丰度总体高于高量秸秆还田土壤;P50和F50处理土壤酶活性总体高于激发剂100%添加处理,F50处理的效果优于P50处理。

    结论 

    高量秸秆还田显著增加CO2排放总量,降低单位碳投入量的土壤有机碳积累量。适量秸秆还田(7500 kg/hm2)条件下,以鱼蛋白提供调节碳氮比所需氮量的50%处理较传统猪粪处理可显著提高早期CO2排放速率,降低CO2排放总量,提升土壤有机碳积累量,因此,可作为提高还田秸秆腐解的有效措施。

    Abstract:
    Objectives 

    Straw returning amount to field affects the decomposition, greenhouse gas emission and the growth of following crops. We studied the suitable returning amount of rice straws and the effect of fish protein as activator to promote straw decomposition, from the points of greenhouse gas emission and organic carbon accumulation.

    Methods 

    An indoor incubation experiment was conducted, three variables were included, as: straw returning with high and low amount (7500 and 10500 kg/hm2), organic activator source (fish protein and pig manure), and the percentage of organic activators (50% and 100%) in the total N required for rapid straw decomposition (regulating C/N ratio to 35∶1), and not regulating C/N ratio as the control for each returning amount, composing a total of 10 treatments, and the incubation lasted 60 days in total. During the incubation, the CO2 and N2O emission and cumulative emissions were monitored. At the end of incubation, soil nutrients, bacterial and fungal abundance and enzyme activities were measured.

    Results 

    High straw returning amount resulted in higher total CO2 emissions and unit carbon input CO2 emissions than the moderate straw retuning, although the total organic carbon accumulation in soil was still high. The cumulative emissions during the first 13 days accounted for more than 40% of the total emission, F50 treatments (fish protein replacing 50% of the total activator N) resulted in the highest CO2 emissions under both straw retuning amount. Both F50 and P50 (pig manure replacing 50% of the total activator N) treatments were observed lower CO2 emissions than F100 and P100 (fish protein and pig manure provide 100% of the total activator N), but higher N2O emissions than F100 and P100. F50 and P50 treatment resulted in higher organic carbon accumulation in soil than F100 and P100 did. F50 was monitored higher CO2 emissions at early period of incubation, lower cumulative CO2 emissions at the end of incubation, and significantly higher organic carbon accumulation in soil than P50, while P50 resulted in higher soil nutrient contents, inducing higher nutrient availability of soil. High straw returning resulted in lower abundance of soil bacteria and fungi than moderate returning amount, and both F50 and P50 were recorded higher soil enzyme activities than the other treatments under the same straw returning amount.

    Conclusions 

    Suitable straw returning amount is beneficial to the organic carbon accumulation per unit carbon input. Replacing 50% of N required for regulation of straw C/N ratio with fish protein could increase early decomposition of straws, decrease the total CO2 emissions, and enhance the organic carbon accumulation in soil, so is recommended for efficient straw returning practice.

  • 随着我国粮食产量持续增长,副产品秸秆量也不断升高,从1980年的4.1亿t[1]到2019年超过10亿t[2],仅水稻秸秆产量就高达21210.43万t[3],年均增量约0.14亿t。秸秆焚烧是处理大量秸秆最简便的方式,但焚烧过程破坏土壤结构,产生的烟雾还污染生态环境[45],目前已被严令禁止[5]。秸秆含有丰富的碳和植物生长所需的矿质元素[6],是宝贵的可再生自然资源。早在20世纪开始,秸秆粉碎还田方式已在国内外广泛应用[7]。还田秸秆通过提高微生物活性,增加土壤有机碳(SOC)积累[8],改善土壤结构,提高土壤细菌和真菌的活性及数量[9],有利于农业可持续发展[10]

    由于农作物秸秆C/N较高[11],直接还田后降解困难,同时微生物分解秸秆时与作物争氮,严重影响后茬作物生长[12]。长期大量还田因秸秆分解不彻底而形成半腐烂层,影响植物根系固定[13],因此,秸秆还田需要调节C/N值以加快分解。秸秆还田时施用适量氮肥可以促进秸秆分解,提高养分释放速率[14],是调节C/N值的简便方法。然而,化肥长期施用会造成土壤板结肥力降低,如果利用资源丰富且含氮量高的农林牧副渔废弃有机物,既达到废弃物资源化利用目的,又能调节秸秆C/N,起到一举两得的效果。猪粪含有较丰富的氮以及可被微生物利用的有机物[15],施用猪粪可促进土壤肥力以及碳矿化能力的提升[16],猪粪替代不同比例化肥与单施化肥相比均提高了土壤有机质含量[17]

    2020年我国淡水鱼产量已超过3.0×107 t[18],提供了巨大的鱼蛋白资源。鱼蛋白含有丰富的氨基酸以及小分子活性有机物质,是微生物极易吸收利用的碳氮资源[19],可能是秸秆分解的理想潜在激发剂。为探明鱼蛋白对秸秆还田的激发效果,本研究以猪粪为参照,比较猪粪和鱼蛋白不同添加比例对秸秆矿化分解、土壤有机碳积累、土壤酶活性以及微生物丰富度和多样性的影响效果。

    试验土壤采于浙江省桐乡市屠甸镇。供试土壤为青紫泥水稻土,风干后过2 mm筛,土壤基本理化性质为:有机碳含量10.8 g/kg,全氮含量1.09 g/kg,速效钾含量80.8 mg/kg,有效磷含量20.5 mg/kg,铵态氮含量14.4 mg/kg,硝态氮含量1.85 mg/kg,可溶性碳含量135 mg/kg,pH 6.72。供试水稻秸秆有机碳含量为39.8 mg/kg,全氮含量为7.80 g/kg,秸秆粉碎后过10 mm筛备用。猪粪 (含水率15.3%) 有机碳含量为13.3 mg/kg,全氮含量为12.1 g/kg。液体鱼蛋白 (深海鲜鱼酶解提取,连云港伟诺生物科技有限公司) 总氮含量24.8 g/L,有机质含量259 g/L。

    我国水稻秸秆的适宜还田量为4500~9000 kg/hm2[20],高还田量为9000~13500 kg/hm2[21]。因此,试验设置两个秸秆还田量 (S):7500 kg/hm2 (适量) 和10500 kg/hm2 (高量)。激发剂为猪粪 (P) 和鱼蛋白 (F),按照C/N控制在35∶1[22]需要的尿素量,设置激发剂添加量为尿素氮的50%和100%,以不添加激发剂为空白对照,共计10个处理,每个处理3个重复。试验采用室内培养法进行。在每个培养瓶中加入600 g土壤,按照试验设计计算各处理每瓶中秸秆、激发剂用量(表1),将土壤与秸秆、激发剂置于干净塑料布上充分混匀后,用去离子水均匀喷洒混合至达到土壤田间持水量的70%,装入1000 mL培养瓶中,插入一个通气管,置于恒温27℃培养箱中培养,计时采样。

    表  1  各处理每个培养瓶中的秸秆和激发剂添加量
    Table  1.  Adding amount of rice straw and activator in each bottle of a treatment
    水稻秸秆还田量
    Rice straw returning amount
    激发剂添加比例
    Activator addition rate
    处理代号
    Treatment code
    秸秆
    Straw
    (g/bottle)
    尿素
    Urea
    (g/bottle)
    猪粪
    Pig manure
    (g/bottle)
    鱼蛋白
    Fish protein
    (mL/bottle)
    适量 Moderate
    7500 kg/hm2
    0 M 1.8 0.0 0.0 0.0
    50%猪粪 50% pig manure MP50 1.8 0.0074 0.4 0.0
    100%猪粪 100% pig manure MP100 1.8 0.0 0.8 0.0
    50%鱼蛋白 50% fish protein MF50 1.8 0.0074 0.0 0.13
    100%鱼蛋白 100%fish protein MF100 1.8 0.0 0.0 0.26
    高量 High
    10500 kg/hm2
    0 H 2.5 0.0 0.0 0.0
    50%猪粪 50% pig manure HP50 2.5 0.01 0.5 0.0
    100%猪粪 100% pig manure HP100 2.5 0.0 1.0 0.0
    50%鱼蛋白 50% fish protein HF50 2.5 0.01 0.0 0.18
    100%鱼蛋白 100%fish protein HF100 2.5 0.0 0.0 0.36
    下载: 导出CSV 
    | 显示表格

    在培养期间,每天通气30 min,用土壤重量法(差重法)加水保持土壤田间持水量的70%,每间隔7天用30 mL注射器进行气体采集,采气前用封口膜密封培养瓶2 h[23],采集后的气体1天内应用气相色谱仪(GC-2010AF,日本)完成测定。测定CO2和N2O两种温室气体浓度,利用土壤容重与孔隙度计算培养瓶中的体积,最终得出单位时间内气体的排放总量,计算公式如下:

    V=V1m/ρ(1+f)

    Q=(培养瓶内CO2或N2O气体浓度−环境中气体浓度)×V÷2

    式中:V为培养瓶中空气体积 (mL);V1为培养瓶容积 (L);m为培养瓶中土壤质量 (g),ρ为供试土壤密度,f为土壤孔隙度 (g/cm3),Q为气体排放量 (mg/h)。

    培养第60天时进行土壤采集,采集前拿出通气管,充分混匀共采样100 g,分为三部分,一部分风干过筛后进行理化性质测定,一部分冻干后放置于−70℃冰箱储存,用于土壤DNA提取以及定量分析,剩余新鲜土样用于酶活性分析。

    pH采用pH计测定,土水质量比1∶2.5;速效钾采用乙酸铵浸提,火焰光度计测定;有效磷采用0.05 mol/LHCl−0.025 mol/L H2SO4方法浸提,间断分析仪(SMARTCHEM 200) 测定;土壤全氮和有机碳用元素分析仪 (Vario EL Ⅲ,Elementar,德国)测定;可溶性有机碳采用去离子水浸提,有机碳分析仪 (TOC-L-CPN,日本岛津公司) 测定;硝态氮 (NO3-N) 和铵态氮 (NH4+-N) 用2 mol/L KCl浸提后,间断分析仪测定NO3-N含量,紫外分光光度计测定NH4+-N含量。

    α-葡萄糖苷酶 (AG)、β-葡萄糖苷酶 (BG)、纤维二糖水解酶 (CB)、木聚糖苷酶(XYL)、亮氨酸氨基肽酶 (LAP) 和β-N-乙酰氨基葡萄糖酶 (NAG) 对应的底物分别为4-MUB-α-D-葡萄糖苷、4-MUB-β-D-葡萄糖苷、4-MUB-纤维二糖苷、4-MUB-β-D-木糖苷、L-亮氨酸-7-氨基-4-甲基香豆素盐酸和4-MUB-β-D-乙酰基氨基葡萄糖苷。土壤荧光酶活性测定参考吴涛等[24]报道的方法,将含有酶和底物混合液的微孔板于25℃培养箱中黑暗培养3h,使用多功能酶标仪 (Synergy H4,BioTek) 测定,酶活性单位为 nmol/(g·h)。

    称取冻干土壤0.5 g,用土壤DNA提取试剂盒 (DNeasy PowerSoil Pro Kit®,美国)按说明书提取土壤DNA,利用紫外分光光度计 (NanoDrop One,Thermo) 测定DNA的OD值,保存于−40℃。土壤细菌16S rDNA V3+V4区片段、真菌ITS2区片段采用的引物分别为338F和518R、NS1-F和Fung-R,引物碱基序列分别为338F: ACTCCTACGGGAGGCAGCAG,518R: ATTACCGCGGCTGCTGG;NS1-F: GTAGTCATATGCTTGTCTC,Fung-R: ATTCCCCGTTACCCGTTG。定量反应体系为:10 μL SYBR Premix Ex Taq,引物 (20 μmol/L) 各0.4 μL,模板DNA 1.0 μL,加无菌蒸馏水至20 μL。质粒稀释10倍为1个梯度,共5个梯度,重复3次,按照吴涛等[24]的方法进行标准曲线的制作,利用荧光定量PCR仪器 (CFX96TM Real-Time System,Bio-Rad) 进行土壤中细菌16S以及真菌ITS的定量分析。

    数据采用Microsoft Excel进行整理分析,用SPSS 26.0单因素进行方差分析,LSD法和邓肯法 (Duncan) 检验处理间的差异显著性 (P<0.05),用Origin和Canoco5.0进行绘图。采用冗余分析 (RDA)评估不同处理下土壤环境因子与酶活性之间的关系。

    各处理CO2排放动态见图1。在60天培养过程中,第1~7天排放最高,之后总体表现为下降趋势(图1)。培养第1天,MF50和HF50处理分别为秸秆适量还田与高量还田最高排放量,其次为MP50和HP50,而最低排放量分别为 MF100和H处理。从第1天到第7天,两个秸秆还田量水平下P50与F50处理的排放量均陡降,而MP100与HF100分别陡升至第一,M与H处理则排列第二。培养25天后, MF50、HF50处理排放量均最低。适量与高量秸秆还田平均CO2排放速率分别为112.4~2341.3和134.6~2955.8 mg/h。

    图  1  不同处理下土壤CO2排放速率动态变化
    注:M与H分别代表秸秆适量(7500 kg/hm2)与高量(10500 kg/hm2)还田对照,P50、P100分别表示激发剂中含50%、100%猪粪处理,F50、F100 分别表示激发剂中含50%、100%鱼蛋白处理。
    Figure  1.  Dynamics of soil CO2 emission rate under different treatments
    Note: M and H represent moderate (7500 kg/hm2) and high (10500 kg/hm2) straw returning amount controls; P50 and P100 represent treatment using 50% and 100% swine manure as activator; F50 and F100 refer to treatments using 50% and 100% fish protein as activator, respectively.

    图2可以看出,激发剂、激发剂添加量、秸秆还田量对CO2排放有极显著影响(P<0.001)。秸秆高量还田各处理CO2累计排放总量的平均值比秸秆适量还田高39.13%。秸秆适量还田处理CO2累计排放总量由高到低为MP100>M>MP50>MF100>MF50,MF50和MF100排放总量分别显著低于M,最大、最小排放速率分别为955、592 g/d,相差1.61倍。高量还田处理CO2排放总量顺序为HP100>HF100>H>HP50>HF50,HF50排放总量显著低于H,而HF100显著高于H,最大、最小排放速率分别为1180、869 g/d,相差1.36倍。综上可知,在适量和高量秸秆还田下,激发剂中添加50%的鱼蛋白可以最大限度地降低CO2排放速率和总排放量,而猪粪作为100%的激发剂会增加CO2排放速率和总排放量。

    图  2  不同处理下土壤CO2累计排放总量以及排放碳占输入总碳百分比
    注:CK分别代表秸秆适量和高量还田处理对照M和H,P50、P100分别表示激发剂为50%、100%的猪粪,F50、F100 分别表示激发剂为50%、100%的鱼蛋白。柱上不同小写字母代表同一还田量下处理间差异显著 (P<0.05);**、***分别表示两个处理间差异达到0.01、0.001显著水平。
    Figure  2.  Cumulative CO2 emissions and the percentage of emitted carbon to total carbon input under different treatments
    Note: CK refers to the control M and H for moderate and high straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. Different small letters above the bars indicate significant difference among treatments in the same straw returning amount; and **, *** indicate the difference between two treatments reaching 0.01 and 0.001 significant levels, respectively.

    土壤有机碳积累与否取决于碳的输入与排放平衡,单位输入碳的排放量可衡量土壤碳积累效率。计算每个处理CO2排放总量与输入碳总量比值可知,秸秆高量还田各处理该比值总体高于适量还田,说明高量还田不利于有机碳积累,而适量还田配合含50%鱼蛋白的激发剂最利于有机碳积累。

    图3显示,两个还田量、两种有机激发剂处理土壤N2O排放规律一致,激发剂50%添加处理培养第1天的排放量最大,培养第7天时陡降,培养7~13天期间下降幅度减小,培养13天之后呈稳定态势,培养25天之前P50与F50处理N2O排放速率均高于其他处理。其他处理则始终处于较低排放平稳态势,且它们之间差异不明显。

    图  3  不同处理下土壤N2O排放速率动态变化
    注:M与H分别代表秸秆适量(7500 kg/hm2)与高量(10500 kg/hm2)还田对照,P50、P100分别表示激发剂含有50%、100%的猪粪,F50、F100 分别表示激发剂含有50%、100%的鱼蛋白。
    Figure  3.  Dynamics of soil N2O emission rate under different treatments
    Note: M and H represent moderate (7500 kg/hm2) and high (10500 kg/hm2) straw returning amount controls, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein.

    对各处理N2O排放总量进行多因素分析(图4)表明,秸秆还田量与激发剂添加比例对N2O排放量有极显著影响(P<0.01)。适量秸秆还田平均N2O累计排放量是高量秸秆还田的1.05倍;同一秸秆还田量,F50处理的N2O累计排放量显著高于F100、对照,P50处理与P100、CK的差异分别达到显著与极显著水平;除HF100的N2O累计排放量显著高于HP100外,同一秸秆还田量、相同添加比例的两个激发剂处理之间没有显著差异。综上所述,高秸秆还田量可显著降低N2O排放,在秸秆适量还田条件下,激发剂中添加50%的鱼蛋白较添加50%的猪粪增加N2O排放的风险有所降低。

    图  4  不同处理下土壤N2O累计排放量
    注:CK分别代表秸秆适量和高量还田处理对照M和H,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%的鱼蛋白。柱上不同小写字母表示同一秸秆还田量下处理间差异显著,**表示两处理间差异达到0.01显著水平。方差分析中,D—秸秆还田量,P—有机激发剂比例,***表示变量效应达到0.001显著水平。
    Figure  4.  Cumulative soil N2O emissions under different treatments
    Note: CK represents the two control M and H for moderate and high straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. Different small letters above the bars indicate significant differences among treatments in the straw returning amount, and the ** indicate the difference between the two treatments at 0.01 levels. In the ANOVA, D—Straw return amount, P—Activator adding rate. *** indicates the variable effect at 0.001 significant level.

    表2可知,秸秆还田量对土壤有机碳与可溶性有机碳含量有极显著影响;激发剂与添加比例对土壤有机碳含量有显著影响,3个变量间对土壤有机碳含量无显著交互作用。

    表  2  秸秆还田量、激发剂及添加比例对土壤有机碳含量影响的多因素方差分析
    Table  2.  Multiple-factor analysis of traw return dose, activator, and additive percentage on soil organic carbon content
    养分
    Nutrient
    还田量
    Dose
    (D)
    激发剂
    Activator
    (A)
    添加比例
    Percentage
    (P)
    D×A D×P A×P
    有机碳
    Organic C
    *** *** ** ns ns ns
    可溶性有机碳
    Soluble
    organic C
    ** ns ns ns ns ns
    注:**、***分别表示变量效应在0.01、0.001水平显著,ns表示变量效应不显著。
    Note: **, *** indicate the variable effect at 0.01 and 0.001 significant level, respectively; ns indicates the variable effect is not significant.
    下载: 导出CSV 
    | 显示表格

    培养60天后,从各处理土壤的化学性状(表3)可以看出,秸秆适量还田土壤有机碳含量高于高量秸秆还田,F50处理高于F100,使用有机激发剂显著降低了土壤有机碳积累量。适量秸秆还田条件下,激发剂及其添加比例对土壤有机碳和水溶性有机碳积累量,及对铵态氮和速效钾含量的影响无显著差异;MP50显著增加了硝态氮含量但降低了有效磷含量;MF100显著降低了全氮和硝态氮含量且硝态氮含量最低。秸秆高量还田条件下,HP50处理的土壤有机碳、全氮、NO3-N含量显著高于其他3个激发剂处理,HF50的硝态氮含量显著高于HP100和HF100。总的来讲,猪粪在提高有机碳、氮积累,提升养分有效性的效果好于鱼蛋白,添加比例50%的激发效果好于添加100%。

    表  3  不同处理土壤化学性质
    Table  3.  Soil chemical properties as affected by treatments
    处理
    Treatment
    pH 有机碳
    Organic C
    (g/kg)
    可溶性有机碳
    Soluble organic C
    (mg/kg)
    全氮
    Total N
    (g/kg)
    硝态氮
    NO3-N
    (mg/kg)
    铵态氮
    NH4+-N
    (mg/kg)
    有效磷
    Available P
    (mg/kg)
    速效钾
    Available K
    (mg/kg)
    M 6.55±0.07 a 14.94±0.85 a 187.8±90.2 a 1.17±0.16 a 15.48±4.81 b 46.57±5.56 a 19.08±0.42 a 88.83±4.17 a
    MP50 6.11±0.03 c 13.26±0.44 b 163.7±14.4 b 1.31±0.11 a 38.74±3.09 a 45.78±8.33 a 16.44±0.42 b 87.23±19.35 a
    MP100 6.27±0.02 b 13.22±0.35 b 163.1±28.0 b 1.30±0.16 a 18.47±1.59 b 34.00±2.52 a 18.25±1.56 a 79.46±11.28 a
    MF50 6.12±0.07 c 12.86±0.16 b 178.2±20.6 b 1.23±0.10 a 41.35±3.11 a 42.06±10.86 a 19.41±0.19 a 85.17±17.58 a
    MF100 6.24±0.04 b 12.61±0.50 b 179.8±8.9 b 1.18±0.12 b 16.55±2.17 c 48.89±24.04 a 19.05±0.32 a 84.78±22.57 a
    平均 Mean 6.25±0.16 13.38±0.95** 174.5±17.8** 1.24±0.13* 24.12±14.34 41.89±12.87 18.44±1.28 83.10±15.55
    H 6.37±0.05 a 13.73±0.28 a 175.6±17.6 a 1.09±0.04 a 7.95±1.07 d 37.93±14.26 ab 20.51±1.05 a 93.97±21.38 a
    HP50 6.11±0.08 c 13.56±0.10 b 148.3±15.0 ab 1.41±0.08 a 53.14±3.23 a 44.38±12.79 ab 19.09±0.69 ab 96.55±9.12 a
    HP100 6.24±0.05 b 11.11±1.49 c 144.0±20.1 b 1.06±0.12 b 15.18±2.03 c 32.71±4.96 b 19.46±0.38 ab 108.43±28.99 a
    HF50 6.11±0.04 c 11.04±0.89 c 148.0±9.6 ab 0.95±0.17 b 45.71±1.59 b 57.92±8.48 a 17.70±1.91 b 81.43±15.01 a
    HF100 6.35±0.04 ab 10.53±0.20 c 164.0±10.5 ab 0.99±0.06 b 16.32±0.76 c 36.37±4.43 b 9.87±0.43 c 90.21±12.97 a
    平均 Mean 6.23±0.13 11.993±1.56** 156.0±17.8** 1.10±0.19* 27.66±18.86 43.43±11.47 17.32±4.07 87.38±16.73
    注:M与H分别为秸秆适量(7500 kg/hm2)与高量(10500 kg/hm2)还田对照,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%鱼蛋白。同列数据后不同小写字母表示同一秸秆还田量下处理间差异显著,*、**分别表示两秸秆还田量间差异达到0.05、0.01显著水平。
    Note: M and H are control for moderate (7500 kg/hm2) and high (10500 kg/hm2) straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. Different lowercase letters indicate significant difference among treatments at the same straw return rate, the * and ** indicate the difference between two straw return rates reaching 0.05 and 0.01 significant levels, respectively.
    下载: 导出CSV 
    | 显示表格

    图5可知,秸秆还田量与添加比例对细菌丰度具有极显著影响;秸秆还田量分别和激发剂及其添加比例对细菌丰度有极显著的交互作用。秸秆适量还田细菌丰度总体高于高量还田,且不同处理之间存在明显差异,MP100与MF100处理细菌丰度显著高于MP50、MF50与M,MP100和MF100处理细菌拷贝数分别比M、MP50和MF50的平均值高出57.26%、40.30%和15.94%、62.60%。HF50显著高于HP100,HF (50%和100%)处理高于HP (50%和100%)。综上所知,培养60天后,秸秆适量还田土壤细菌处于较高水平,特别是MP100与MF100高于其他处理;而秸秆适量还田激发剂处理土壤细菌丰度明显高于高量还田。

    图  5  不同处理下土壤微生物数量
    注:CK代表秸秆适量和高量还田对照M和H,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%鱼蛋白。方差分析中,D—秸秆还田量,A—激发剂,P—激发剂比例;*、**、***分别表示变量效应达到0.05、0.01、0.001显著水平。
    Figure  5.  Soil microbial population under different treatments
    Note: CK represents the control M for moderate and H for high straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. In ANOVA, D—Straw return amount, A—Activator, P—Percentage of pigmanure or fish protein in activator; *, **, and ** indicate variable effects reaching 0.05, 0.01, and 0.001 significance levels, respectively.

    图5可知,秸秆还田量对真菌丰度具有极显著影响;秸秆还田量分别和激发剂及其添加比例对真菌丰度有显著的交互作用。与细菌情况相似,真菌丰度也是秸秆适量还田高于高量还田,但两者之间的差距小于细菌。差异分析发现,秸秆适量还田不同处理之间无显著差异,MP100、MF100、MF50与MP50处理分别较M低12.82%、16.55%、20.33%和25.98%。而秸秆高量还田下,HP100处理真菌丰度低于其他处理。综上所知,培养60天后,秸秆适量还田土壤真菌丰度总体高于高量还田。

    多因素方差分析(图6)发现,秸秆还田量对土壤6种酶活性无显著影响;添加激发剂比例对BG和NAG活性影响达P<0.001水平,对CB和XYL活性的影响达P<0.01水平。

    图  6  不同处理下土壤酶活性
    注: CK分别代表秸秆适量和高量还田对照M和H,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%鱼蛋白。AG—α-葡萄糖苷酶;BG—β-葡萄糖苷酶;CB—纤维二糖水解酶;XYL—β-木聚糖苷酶;NAG—β-N-乙酰氨基葡萄糖苷酶;LAP—亮氨酸氨基肽酶。方差分析中,D—秸秆还田量,A—激发剂,P—激发剂比例;*、**、***分别表示变量效应达到0.05、0.01、0.001显著水平。
    Figure  6.  Soil enzyme activity under different treatments
    Note: CK represents the control M for moderate and H for high straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. AG—α-Glucomutase; BG—β-Glucomutase; CB—Cellobiose hydrolase; XYL—β-Xyloglucomutase; NAG—β-N-Acetylglucosaminoglycans; LAP—Leucine aminopeptidase. In ANOVA, D—Straw return amount, A—Activator, P—Percentage of activator; *, **, and *** indicate variable effects reaching 0.05, 0.01, and 0.001 significance levels, respectively.

    相同秸秆添加量下, 50%有机激发剂添加处理土壤6种酶活性增加的比例总体高于对应的100%添加比例和对照,不同酶最低活性值出现于不同处理,适量秸秆还田下,BG、NAG、LAP最低活性出现在MP100处理,AG、CB、XYL 最低活性出现在M处理;高量秸秆还田下,BG、NAG最低活性值均出现在HP100,AG、CB、XYL出现在 HF100,LAP出现在 H处理。除LAP外,其他5种酶活性的共性特征是,MF50与MP100比显著提高土壤酶活性;不加激发剂对照(M、H)和猪粪(P50、P100)处理土壤上,高量秸秆还田高于适量秸秆还田;鱼蛋白两个添加比例处理则正好相反,秸秆适量还田>高量还田。MF50与M相比,显著提高了土壤AG、BG、CB、XYL和NAG活性,提高幅度分别为118.42%、133.05%、90.09%、122.57%和122.34%;MP50与M、MP100相比,提高了土壤NAG活性;HF50处理土壤BG活性显著高于HP100与HF100。

    以6种酶活性为因变量,土壤化学性质与环境因子的RDA结果(图7)表明,两个秸秆还田量的土壤酶活性均与第一主轴呈正相关关系。秸秆适量还田第一、第二主轴分别解释了土壤环境因子与酶活性数据方差变化的56.40%和5.25%,秸秆高量还田第一、第二主轴对应的数值分别为32.13%和23.45%,两个秸秆还田量第一、第二主轴解释率分别为61.65%和55.58%。分析土壤化学性质与酶的关系发现共性规律,硝态氮对所测土壤酶总体积极作用最大,其次是有效磷,而土壤pH和可溶性有机碳则是负相关;不同秸秆还田量的情况是:秸秆适量还田时,全氮正相关、土壤有机碳负相关;秸秆高量还田时,土壤有机碳和NH4+-N正相关、全氮负相关。

    图  7  不同秸秆还田量下土壤酶活性与环境因子之间冗余分析
    注:M与H分别为秸秆适量(7500 kg/hm2)与高量(10500 kg/hm2)还田对照,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%鱼蛋白。AG—α-葡萄糖苷酶;BG—β-葡萄糖苷酶;CB—纤维二糖水解酶;XYL—β-木聚糖苷酶;NAG—β-N-乙酰氨基葡萄糖苷酶;LAP—亮氨酸氨基肽酶。SOC、WSOC、TN、AK、AP、NO3-N、NH4+-N分别代表土壤有机碳、可溶性有机碳、全氮、速效钾、有效磷、硝态氮、铵态氮。
    Figure  7.  Redundancy analysis between enzyme activities of soil and environmental factors underdifferent returning amount of straw
    Note: M and H are control for moderate (7500 kg/hm2) and high (10500 kg/hm2) straw returning amount treatments, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. AG—α-Glucomutase; BG—β-Glucomutase; CB—Cellobiose hydrolase; XYL—β-Xyloglucomutase; NAG—β-N-Acetylglucosaminoglycans; LAP—Leucine aminopeptidase. SOC, WSOC, TN, AK, AP, NO3-N, and NH4+-N represent soil organic carbon, water-soluble organic carbon, total nitrogen, available potassium, available phosphorus, ammonium nitrogen, and nitrate nitrogen, respectively.

    土壤有机质增减取决于有机碳的输入和输出平衡,在同一生态系统中,一般输入量高则积累也多。刘东海等[25]持续12年长期定位试验结果表明,随着秸秆还田量增加土壤有机碳与全氮含量随之上升。然而,秸秆还田在提高有机质的同时,排出CO2、N2O等温室气体[26]。同理,秸秆还田量越高CO2排放越多。本研究表明,秸秆还田量对CO2排放、土壤有机碳和可溶性有机碳含量均有显著影响,秸秆高量还田所有处理的排放总量高于适量还田,动态排放每次检测的CO2排放速率均高于适量还田,由此导致高量还田处理土壤有机碳反而低于适量还田。当然60天培养时间内输入的秸秆可能没有充分分解,因此测得的土壤有机质中可能包含秸秆粉末。秸秆高量还田的排放总量及其占单位输入碳比例均高于适量还田 (图2),可能是大量秸秆粉末中的可溶性有机碳输入对土壤微生物产生强烈激发效应所致[27]。孙昭安等[28]研究发现土壤有机碳分解的激发效应(PE)随秸秆添加量增加从负 (抑制土壤有机碳矿化) 到正 (促进土壤有机碳矿化) 的变化,解释秸秆高量还田可能被促进分解而适量还田则被抑制。2个秸秆还田量的对照处理土壤有机碳最高,可能是没有添加激发剂致微生物活动减弱、分解程度低,土壤中残留未分解和半分解的秸秆粉末使有机碳分析结果偏高。

    60天的培养动态显示,前13天CO2累计排放量占总排放量40%以上,说明前期是秸秆快速分解期,因为秸秆粉末与土壤充分接触后微生物快速繁殖[29];F50为所有处理中CO2累计排放量占总排放量比例最高,秸秆适量和高量还田处理分别达到45.28%和47.09%,说明尿素加鱼蛋白的综合激发效果最好;然而,F50处理后期的CO2排放量均处于最低水平,最终,F50处理60天CO2累计排放总量最低 (图2)。F50处理前期CO2排放占比大的原因是,鱼蛋白有机降解液含有丰富的氨基酸和小分子有机物质,氨基酸中25%的碳被呼吸作用散失,剩余75%能为土壤微生物提供能源促进其生长繁殖[30],前期微生物活动加强,呼吸速率升高,而培养后期则由于易降解的有机物被消耗使土壤微生物数量减少、分解减慢。

    不同处理N2O排放的规律是秸秆适量还田处理略高于高量还田,而激发剂50%添加比例显著高于对照和100%添加比例,不同激发剂之间没有明显差异,说明激发剂50%添加比例中无机氮是决定N2O排放的主要因素。这与侯苗苗[31]研究结果一致,因为激发剂50%添加比例处理一半的氮素来源是尿素,在理想的温度和湿度条件下,土壤中尿素很快水解形成铵,从而进行硝化作用产生硝酸根,同时释放N2O和N2,由于秸秆分解消耗大量氧气,还可能进行反硝化作用释放N2O与N2[3233],这是激发剂50%添加比例土壤N2O排放高于100%添加比例的主要原因。激发剂50%添加处理土壤硝态氮含量高是硝化作用的结果,但铵态氮仍然高于100%添加处理,一方面可能是由于铵态氮没有被完全消化掉;另一方面是50%添加处理激发的微生物活动使部分有机态氮矿化为铵态氮[3435] 。鱼蛋白有机液肥含有的氨基酸对土壤氮循环起着重要作用,微生物会产生脱氨酶,使氨基酸分解成铵根离子与α-酮酸,有助于氮素矿化;而鱼蛋白用量的增加导致微生物对氮素固定时间延长,有利于对氮的保护[36]。因为碳氮循环是耦合过程,N2O排放可能影响CO2排放,这些过程与土壤微生物及酶活性有关。下面分析不同处理土壤微生物及酶活性情况,以及它们与CO2排放和有机碳积累的关系。

    土壤碳氮循环主要由微生物分泌的各种酶所介导,培养60天时土壤微生物和酶活性反映的是当下状态,而气体排放是动态过程,有机碳含量是过程的结果。首先分析土壤微生物及酶活性,如从当下情况分析,土壤微生物生物量高、活性越强,则分泌的胞外酶越多,但土壤酶受到保护时具有累积效应。翟修彩等[37]开展90天水稻秸秆还田的培养试验发现,土壤酶活性随着培养时间延长先增后降,60天达到峰值;然而,他们发现土壤微生物量碳(MBC)的峰值时间是30天,早于酶活性峰值时间。基于60天内土壤酶活性随着培养时间增加而增加的背景知识,本研究没有分析土壤微生物及酶活性动态变化,直接测定培养60天的结果发现,秸秆高量还田土壤酶活性总体高于适量还田,而土壤细菌和真菌丰度正好相反,秸秆高量和适量还田处理之间土壤微生物丰度和酶活性的高低不一致,可以从不同秸秆还田量对土壤酶活性的影响来解释,高量还田前期微生物活动强,分泌积累了较多的胞外酶,但由于前期消耗大量土壤碳,微生物活动后劲不足,数量减少。综合本研究秸秆高量还田CO2排放量大于适量还田、而土壤有机碳低,很好地解释了酶活性高—CO2排放多—有机碳残留少的结果。激发剂50%添加处理土壤酶活性高,而细菌和真菌数量低,该结果的原因与秸秆高量还田处理相同。

    基于同一秸秆还田量和相同激发剂的比较发现,激发剂50%添加处理累计CO2排放少于其他处理,土壤有机碳高于100%添加处理,特别是秸秆高量还田时差异更明显(表3),结果符合CO2排放少、土壤有机碳积累多的逻辑。然而,激发剂50%添加处理土壤酶活性总体高于其他处理,高酶活性没有导致高排放,可能是微生物对于碳的利用效率 (CUE) 高。微生物在分解秸秆释放CO2的同时把部分碳同化为自身生物量存留,许多研究证明,微生物残体碳是稳定性高的土壤碳组分[38]。Li等[39]采用H218O示踪剂方法,进行温带森林长期氮素添加试验发现,尿素低氮添加显著增加微生物CUE。本研究激发剂50%添加处理、特别是F50处理CUE高的原因,一方面是少量尿素的作用,另一方面可能是鱼蛋白中氨基酸有利于微生物繁殖,积累残体碳[40]

    高秸秆还田量显著提升了CO2排放量,降低N2O排放量。因此,秸秆还田应以适量为宜。在激发剂中用50%的鱼蛋白替代无机氮,可以显著加快早期秸秆在土壤中的腐解速率,提高CO2排放速率但减少CO2排放总量,提高土壤中有机碳的积累量。如果激发剂改为100%鱼蛋白,会促进秸秆CO2排放速率和排放总量,不能有效地将有机碳保留在土壤中。因此,以50%鱼蛋白作为激发剂是促进还田秸秆腐解,降低CO2排放量,提高土壤有机碳积累的可行技术措施。

  • 图  1   不同处理下土壤CO2排放速率动态变化

    注:M与H分别代表秸秆适量(7500 kg/hm2)与高量(10500 kg/hm2)还田对照,P50、P100分别表示激发剂中含50%、100%猪粪处理,F50、F100 分别表示激发剂中含50%、100%鱼蛋白处理。

    Figure  1.   Dynamics of soil CO2 emission rate under different treatments

    Note: M and H represent moderate (7500 kg/hm2) and high (10500 kg/hm2) straw returning amount controls; P50 and P100 represent treatment using 50% and 100% swine manure as activator; F50 and F100 refer to treatments using 50% and 100% fish protein as activator, respectively.

    图  2   不同处理下土壤CO2累计排放总量以及排放碳占输入总碳百分比

    注:CK分别代表秸秆适量和高量还田处理对照M和H,P50、P100分别表示激发剂为50%、100%的猪粪,F50、F100 分别表示激发剂为50%、100%的鱼蛋白。柱上不同小写字母代表同一还田量下处理间差异显著 (P<0.05);**、***分别表示两个处理间差异达到0.01、0.001显著水平。

    Figure  2.   Cumulative CO2 emissions and the percentage of emitted carbon to total carbon input under different treatments

    Note: CK refers to the control M and H for moderate and high straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. Different small letters above the bars indicate significant difference among treatments in the same straw returning amount; and **, *** indicate the difference between two treatments reaching 0.01 and 0.001 significant levels, respectively.

    图  3   不同处理下土壤N2O排放速率动态变化

    注:M与H分别代表秸秆适量(7500 kg/hm2)与高量(10500 kg/hm2)还田对照,P50、P100分别表示激发剂含有50%、100%的猪粪,F50、F100 分别表示激发剂含有50%、100%的鱼蛋白。

    Figure  3.   Dynamics of soil N2O emission rate under different treatments

    Note: M and H represent moderate (7500 kg/hm2) and high (10500 kg/hm2) straw returning amount controls, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein.

    图  4   不同处理下土壤N2O累计排放量

    注:CK分别代表秸秆适量和高量还田处理对照M和H,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%的鱼蛋白。柱上不同小写字母表示同一秸秆还田量下处理间差异显著,**表示两处理间差异达到0.01显著水平。方差分析中,D—秸秆还田量,P—有机激发剂比例,***表示变量效应达到0.001显著水平。

    Figure  4.   Cumulative soil N2O emissions under different treatments

    Note: CK represents the two control M and H for moderate and high straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. Different small letters above the bars indicate significant differences among treatments in the straw returning amount, and the ** indicate the difference between the two treatments at 0.01 levels. In the ANOVA, D—Straw return amount, P—Activator adding rate. *** indicates the variable effect at 0.001 significant level.

    图  5   不同处理下土壤微生物数量

    注:CK代表秸秆适量和高量还田对照M和H,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%鱼蛋白。方差分析中,D—秸秆还田量,A—激发剂,P—激发剂比例;*、**、***分别表示变量效应达到0.05、0.01、0.001显著水平。

    Figure  5.   Soil microbial population under different treatments

    Note: CK represents the control M for moderate and H for high straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. In ANOVA, D—Straw return amount, A—Activator, P—Percentage of pigmanure or fish protein in activator; *, **, and ** indicate variable effects reaching 0.05, 0.01, and 0.001 significance levels, respectively.

    图  6   不同处理下土壤酶活性

    注: CK分别代表秸秆适量和高量还田对照M和H,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%鱼蛋白。AG—α-葡萄糖苷酶;BG—β-葡萄糖苷酶;CB—纤维二糖水解酶;XYL—β-木聚糖苷酶;NAG—β-N-乙酰氨基葡萄糖苷酶;LAP—亮氨酸氨基肽酶。方差分析中,D—秸秆还田量,A—激发剂,P—激发剂比例;*、**、***分别表示变量效应达到0.05、0.01、0.001显著水平。

    Figure  6.   Soil enzyme activity under different treatments

    Note: CK represents the control M for moderate and H for high straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. AG—α-Glucomutase; BG—β-Glucomutase; CB—Cellobiose hydrolase; XYL—β-Xyloglucomutase; NAG—β-N-Acetylglucosaminoglycans; LAP—Leucine aminopeptidase. In ANOVA, D—Straw return amount, A—Activator, P—Percentage of activator; *, **, and *** indicate variable effects reaching 0.05, 0.01, and 0.001 significance levels, respectively.

    图  7   不同秸秆还田量下土壤酶活性与环境因子之间冗余分析

    注:M与H分别为秸秆适量(7500 kg/hm2)与高量(10500 kg/hm2)还田对照,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%鱼蛋白。AG—α-葡萄糖苷酶;BG—β-葡萄糖苷酶;CB—纤维二糖水解酶;XYL—β-木聚糖苷酶;NAG—β-N-乙酰氨基葡萄糖苷酶;LAP—亮氨酸氨基肽酶。SOC、WSOC、TN、AK、AP、NO3-N、NH4+-N分别代表土壤有机碳、可溶性有机碳、全氮、速效钾、有效磷、硝态氮、铵态氮。

    Figure  7.   Redundancy analysis between enzyme activities of soil and environmental factors underdifferent returning amount of straw

    Note: M and H are control for moderate (7500 kg/hm2) and high (10500 kg/hm2) straw returning amount treatments, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. AG—α-Glucomutase; BG—β-Glucomutase; CB—Cellobiose hydrolase; XYL—β-Xyloglucomutase; NAG—β-N-Acetylglucosaminoglycans; LAP—Leucine aminopeptidase. SOC, WSOC, TN, AK, AP, NO3-N, and NH4+-N represent soil organic carbon, water-soluble organic carbon, total nitrogen, available potassium, available phosphorus, ammonium nitrogen, and nitrate nitrogen, respectively.

    表  1   各处理每个培养瓶中的秸秆和激发剂添加量

    Table  1   Adding amount of rice straw and activator in each bottle of a treatment

    水稻秸秆还田量
    Rice straw returning amount
    激发剂添加比例
    Activator addition rate
    处理代号
    Treatment code
    秸秆
    Straw
    (g/bottle)
    尿素
    Urea
    (g/bottle)
    猪粪
    Pig manure
    (g/bottle)
    鱼蛋白
    Fish protein
    (mL/bottle)
    适量 Moderate
    7500 kg/hm2
    0 M 1.8 0.0 0.0 0.0
    50%猪粪 50% pig manure MP50 1.8 0.0074 0.4 0.0
    100%猪粪 100% pig manure MP100 1.8 0.0 0.8 0.0
    50%鱼蛋白 50% fish protein MF50 1.8 0.0074 0.0 0.13
    100%鱼蛋白 100%fish protein MF100 1.8 0.0 0.0 0.26
    高量 High
    10500 kg/hm2
    0 H 2.5 0.0 0.0 0.0
    50%猪粪 50% pig manure HP50 2.5 0.01 0.5 0.0
    100%猪粪 100% pig manure HP100 2.5 0.0 1.0 0.0
    50%鱼蛋白 50% fish protein HF50 2.5 0.01 0.0 0.18
    100%鱼蛋白 100%fish protein HF100 2.5 0.0 0.0 0.36
    下载: 导出CSV

    表  2   秸秆还田量、激发剂及添加比例对土壤有机碳含量影响的多因素方差分析

    Table  2   Multiple-factor analysis of traw return dose, activator, and additive percentage on soil organic carbon content

    养分
    Nutrient
    还田量
    Dose
    (D)
    激发剂
    Activator
    (A)
    添加比例
    Percentage
    (P)
    D×A D×P A×P
    有机碳
    Organic C
    *** *** ** ns ns ns
    可溶性有机碳
    Soluble
    organic C
    ** ns ns ns ns ns
    注:**、***分别表示变量效应在0.01、0.001水平显著,ns表示变量效应不显著。
    Note: **, *** indicate the variable effect at 0.01 and 0.001 significant level, respectively; ns indicates the variable effect is not significant.
    下载: 导出CSV

    表  3   不同处理土壤化学性质

    Table  3   Soil chemical properties as affected by treatments

    处理
    Treatment
    pH 有机碳
    Organic C
    (g/kg)
    可溶性有机碳
    Soluble organic C
    (mg/kg)
    全氮
    Total N
    (g/kg)
    硝态氮
    NO3-N
    (mg/kg)
    铵态氮
    NH4+-N
    (mg/kg)
    有效磷
    Available P
    (mg/kg)
    速效钾
    Available K
    (mg/kg)
    M 6.55±0.07 a 14.94±0.85 a 187.8±90.2 a 1.17±0.16 a 15.48±4.81 b 46.57±5.56 a 19.08±0.42 a 88.83±4.17 a
    MP50 6.11±0.03 c 13.26±0.44 b 163.7±14.4 b 1.31±0.11 a 38.74±3.09 a 45.78±8.33 a 16.44±0.42 b 87.23±19.35 a
    MP100 6.27±0.02 b 13.22±0.35 b 163.1±28.0 b 1.30±0.16 a 18.47±1.59 b 34.00±2.52 a 18.25±1.56 a 79.46±11.28 a
    MF50 6.12±0.07 c 12.86±0.16 b 178.2±20.6 b 1.23±0.10 a 41.35±3.11 a 42.06±10.86 a 19.41±0.19 a 85.17±17.58 a
    MF100 6.24±0.04 b 12.61±0.50 b 179.8±8.9 b 1.18±0.12 b 16.55±2.17 c 48.89±24.04 a 19.05±0.32 a 84.78±22.57 a
    平均 Mean 6.25±0.16 13.38±0.95** 174.5±17.8** 1.24±0.13* 24.12±14.34 41.89±12.87 18.44±1.28 83.10±15.55
    H 6.37±0.05 a 13.73±0.28 a 175.6±17.6 a 1.09±0.04 a 7.95±1.07 d 37.93±14.26 ab 20.51±1.05 a 93.97±21.38 a
    HP50 6.11±0.08 c 13.56±0.10 b 148.3±15.0 ab 1.41±0.08 a 53.14±3.23 a 44.38±12.79 ab 19.09±0.69 ab 96.55±9.12 a
    HP100 6.24±0.05 b 11.11±1.49 c 144.0±20.1 b 1.06±0.12 b 15.18±2.03 c 32.71±4.96 b 19.46±0.38 ab 108.43±28.99 a
    HF50 6.11±0.04 c 11.04±0.89 c 148.0±9.6 ab 0.95±0.17 b 45.71±1.59 b 57.92±8.48 a 17.70±1.91 b 81.43±15.01 a
    HF100 6.35±0.04 ab 10.53±0.20 c 164.0±10.5 ab 0.99±0.06 b 16.32±0.76 c 36.37±4.43 b 9.87±0.43 c 90.21±12.97 a
    平均 Mean 6.23±0.13 11.993±1.56** 156.0±17.8** 1.10±0.19* 27.66±18.86 43.43±11.47 17.32±4.07 87.38±16.73
    注:M与H分别为秸秆适量(7500 kg/hm2)与高量(10500 kg/hm2)还田对照,P50、P100分别表示激发剂含50%、100%猪粪,F50、F100 分别表示激发剂含50%、100%鱼蛋白。同列数据后不同小写字母表示同一秸秆还田量下处理间差异显著,*、**分别表示两秸秆还田量间差异达到0.05、0.01显著水平。
    Note: M and H are control for moderate (7500 kg/hm2) and high (10500 kg/hm2) straw returning amount, respectively. P50 and P100 represent treatments adding activator containing 50% and 100% pig manure, and F50 and F100 indicate treatments adding activator containing 50% and 100% fish protein. Different lowercase letters indicate significant difference among treatments at the same straw return rate, the * and ** indicate the difference between two straw return rates reaching 0.05 and 0.01 significant levels, respectively.
    下载: 导出CSV
  • [1] 贾凤伶, 陈琼, 秦静. 农业生产用能结构变化特点及消费弹性分析[J]. 天津农业科学, 2019, 25(2): 49−55. DOI: 10.3969/j.issn.1006-6500.2019.02.011

    Jia F L, Chen Q, Qin J. Energy consumption structure change characteristics and consumption elasticity analysis of agricultural production[J]. Tianjin Agricultural Sciences, 2019, 25(2): 49−55. DOI: 10.3969/j.issn.1006-6500.2019.02.011

    [2] 牛立亭. 人大代表为农业绿色与持续发展建言[N]. 中国农资, 2019-03-08(3).

    Niu L T. NPC Deputies advise on green and sustainable development of agriculture[N]. China Agri-Production News, 2019-03-08(3).

    [3] 马兰, 李晓波, 马舒坦. 双氰胺减少铵态氮肥施用后潮土N2O排放的机制[J]. 农业环境科学学报, 2021, 40(12): 2801−2808.

    Ma L, Li X B, Ma S T, Mechanisms of underpinning the dicyandiamide-induced N2O emissions reduction in a fluvo-aquic soil after ammonium nitrogen fertilization[J]. Journal of Agro-Environment Science, 2021, 40(12): 2801−2808.

    [4]

    Singh G, Gupta M K, Chaurasiya S, et al. Rice straw burning: A review on its global prevalence and the sustainable alternatives for its effective mitigation[J]. Environmental Science and Pollution Research, 2021, 28: 32125−32155. DOI: 10.1007/s11356-021-14163-3

    [5] 李珍珍. 基层政府治理秸秆焚烧的法律对策研究[J]. 农村经济与科技, 2022, 33(4): 24−26.

    Li Z Z. A study on grassroots government's legal defenses against straw burning[J]. Rural Economy and Science-Technology, 2022, 33(4): 24−26.

    [6] 赵婉宁. 秸秆打捆机粉碎部件的设计与试验研究[D]. 吉林长春: 吉林农业大学硕士学位论文, 2016.

    Zhao W N. Design and experimental study on straw baler crushing parts[D]. Changchun, Jilin: MS Thesis of Jilin Agricultural University, 2016.

    [7] 盘礼东, 李瑞. 有机覆盖措施对土壤肥力的影响研究现状及展望[J]. 贵州师范大学学报(自然科学版), 2021, 39(6): 91−101.

    Pan L D, Li R. Research status and prospect of effects of organic mulching on soil fertility[J]. Journal of Guizhou Normal University (Natural Sciences), 2021, 39(6): 91−101.

    [8] 罗雪婷. 污染土壤水分散性胶体态重金属释放的主要影响因素研究[D]. 江苏南京: 南京信息工程大学硕士学位论文, 2022.

    Luo X T. Study on the main factors influencing the release of heavy metals in water-dispersible colloidal state from contaminated soil[D]. Nanjing, Jiangsu: MS Thesis of Nanjing University of Information Science and Technology, 2022.

    [9] 王学霞, 张磊, 梁丽娜, 等. 秸秆还田对麦玉系统土壤有机碳稳定性的影响[J]. 农业环境科学学报, 2020, 39(8): 1774−1782.

    Wang X X, Zhang L, Liang L N, et al. Effects of straw returning on the stability of soil organic carbon in wheat-maize rotation systems[J]. Journal of Agro-Environment Science, 2020, 39(8): 1774−1782.

    [10] 杨希, 于济菘, 王冰, 等. 秸秆还田对土壤养分供应及微生物群落的影响[J]. 智慧农业导刊, 2022, 2(18): 50−52.

    Yang X, Yu J S, Wang B, et al. Effects of straw return on soil nutrient supply and microbial community[J]. Journal of Smart Agriculture, 2022, 2(18): 50−52.

    [11] 魏伟业. 农作物秸秆还田技术应用及前景[J]. 种子科技, 2021, 39(16): 42−43.

    Wei W Y. Application and prospects of crop straw returning technology[J]. Seed Science & Technology, 2021, 39(16): 42−43.

    [12] 余坤, 李国建, 李百凤, 等. 不同秸秆还田方式对土壤质量改良效应的综合评价[J]. 干旱地区农业研究, 2020, 38(3): 213−221. DOI: 10.7606/j.issn81000-7601.2020.03.27

    Yu K, Li G J, Li B F, et al. Comprehensive evaluation of soil quality under different straw incorporation approaches[J]. Agricultural Research in the Arid Areas, 2020, 38(3): 213−221. DOI: 10.7606/j.issn81000-7601.2020.03.27

    [13] 朱晓晴, 安晶, 马玲, 等. 秸秆还田深度对土壤温室气体排放及玉米产量的影响[J]. 中国农业科学, 2020, 53(5): 977−989. DOI: 10.3864/j.issn.0578-1752.2020.05.010

    Zhu X Q, An J, Ma L, et al. Effects of different straw returning depths on soil greenhouse gas emission and maize yield[J]. Scientia Agricultura Sinica, 2020, 53(5): 977−989. DOI: 10.3864/j.issn.0578-1752.2020.05.010

    [14] 徐宁泽, 王英伟. 秸秆“过火还田”方舱模式的应用探讨[A]. 中国环境科学学会环境工程分会. 中国环境科学学会2019年科学技术年会: 环境工程技术创新与应用分论坛论文集(四)[C]. 2019.

    Xu N Z, Wang Y W. Discussion on the application of the mode of“returning straw to the field over fire” shelter[A]. Environmental Engineering Branch, Chinese Society for Environmnetal Sciences. 2019 Annual Science and Technology Conference of the Chinese Society of Environmental Science: Environmental engineering technology innovation and application sub-forum[C]. 2019.

    [15] 何治逢, 王时聪, 尹众, 等. 秸秆还田配施腐秆剂下不同氮肥运筹对土壤养分及活性有机碳库的影响[J]. 安徽农业大学学报, 2022, 49(3): 462−468.

    He Z F, Wang S C, Yin Z, et al. Effects of different nitrogen application methods on soil nutrients and labile organic carbon pool under the condition of straw returning with straw-decomposing microbial inoculant[J]. Journal of Anhui Agricultural University, 2022, 49(3): 462−468.

    [16] 郑凤君, 王雪, 李景, 等. 免耕条件下施用有机肥对冬小麦土壤酶及活性有机碳的影响[J]. 中国农业科学, 2020, 53(6): 1202−1213. DOI: 10.3864/j.issn.0578-1752.2020.06.012

    Zheng F J, Wang X, Li J, et al. Effect of no-tillage with manure on soil enzyme activities and soil active organic carbon[J]. Scientia Agricultura Sinica, 2020, 53(6): 1202−1213. DOI: 10.3864/j.issn.0578-1752.2020.06.012

    [17] 周芸, 李永梅, 范茂攀, 等. 不同基肥处理对山原红壤土壤理化特性、酶活性及作物产量的影响[J]. 应用与环境生物学报, 2020, 26(3): 603−611.

    Zhou Y, Li Y M, Fan M P, et al. Effects of different base fertilizer treatments on mountain red earth soil nutrition, enzyme activity, and crop yield[J]. Chinese Journal of Applied and Environmental Biology, 2020, 26(3): 603−611.

    [18] 冯建新, 杨治国, 莫海珍, 等. 2020年河南省大宗淡水鱼产业技术发展报告[J]. 河南水产, 2021, (5): 1−3.

    Feng J X, Yang Z G, Mo H Z, et al. Technical development report on bulk freshwater fish industry in Henan Province in 2020[J]. Henan Fisheries, 2021, (5): 1−3.

    [19] 周雄, 黄吉人. 鱼蛋白氨基酸水溶肥料的制备及应用研究[J]. 肥料与健康, 2021, 48(3): 52−55. DOI: 10.3969/j.issn.2096-7047.2021.03.014

    Zhou X, Huang J R. Preparation and application research of the water-soluble fertilizer containing fish protein amino acids[J]. Fertilizer & Health, 2021, 48(3): 52−55. DOI: 10.3969/j.issn.2096-7047.2021.03.014

    [20] 张晓庆, 王梓凡, 参木友, 等. 中国农作物秸秆产量及综合利用现状分析[J]. 中国农业大学学报, 2021, 26(9): 30−41. DOI: 10.11841/j.issn.1007-4333.2021.09.04

    Zhang X Q, Wang Z F, Shen M Y, et al. Analysis of yield and current comprehensive utilization of crop straws in China[J]. Journal of China Agricultural University, 2021, 26(9): 30−41. DOI: 10.11841/j.issn.1007-4333.2021.09.04

    [21] 吴红艳, 于淼, 高晓梅. 玉米秸秆添加量对温室土壤氨挥发及辣椒氮素吸收的影响[J]. 农业环境科学学报, 2022, 41(10): 2307−2314.

    Wu H Y , Yu M, Gao X M. Effects of maize straw addition on soil ammonia volatilization and nitrogen absorption of pepper in greenhouse[J]. Journal of Agro-Environment Science, 2022, 41(10): 2307−2314.

    [22] 游宏建, 张美君, 安明远, 等. 不同堆肥材料及其碳氮比对餐厨废弃物堆肥进程中养分及微生物的影响[J]. 西南农业学报, 2022, 35(7): 1631−1639.

    You H J, Zhang M J, An M Y, et al. Effects of different composting materials and their carbon to nitrogen ratios on nutrients and microorganisms in the composting process of food waste[J]. Southwest China Journal of Agricultural Sciences, 2022, 35(7): 1631−1639.

    [23] 马兰, 李晓波, 马舒坦. 双氰胺减少铵态氮肥施用后潮土N2O排放的机制[J]. 农业环境科学学报, 2021, 40(12): 2801−2808.

    Ma L, Li X B, Ma S T. Mechanisms of underpinning the dicyandiamide-induced N2O emissions reduction in a fluvo-aquic soil after ammonium nitrogen fertilization[J]. Journal of Agro-Environment Science, 2021, 40(12): 2801−2808.

    [24] 吴涛, 冯歌林, 曾珍, 等. 生物质炭对盆栽黑麦草生长的影响及机理[J]. 土壤学报, 2017, 54(2): 525−534.

    Wu T, Feng G L, Zeng Z, et al. Effect of biomass charcoal on the growth of potted ryegrass and its mechanism[J]. Acta Pedologica Sinica, 2017, 54(2): 525−534.

    [25] 刘东海, 乔艳, 李晓, 等. 紫色土区不同秸秆还田量对土壤酶活性的影响[J]. 中国土壤与肥料, 2022, (7): 107−113. DOI: 10.11838/sfsc.1673-6257.21252

    Liu D H, Qiao Y, Li Y, et al. Effects of different amounts of straw returning on soil enzyme activity in purple soil[J]. Soil and Fertilizer Sciences in China, 2022, (7): 107−113. DOI: 10.11838/sfsc.1673-6257.21252

    [26] 刘杰云, 邱虎森, 张文正, 等. 节水灌溉对农田土壤温室气体排放的影响[J]. 灌溉排水学报, 2019, 38(6): 1−7.

    Liu J Y, Qiu H S, Zhang W Z, et al. Response of greenhouse gas emissions to water-saving irrigation in croplands: A review[J]. Journal of Irrigation and Drainage, 2019, 38(6): 1−7.

    [27] 花可可, 张睿, 王童语, 等. 长期施肥对砂姜黑土可溶性碳淋溶的影响[J]. 农业工程学报, 2022, 38(1): 80−88. DOI: 10.11975/j.issn.1002-6819.2022.01.009

    Hua K K, Zhang R, Wang T Y, et al. Effects of long-term fertilization on dissolved carbon leaching in lime concretion black soils[J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(1): 80−88. DOI: 10.11975/j.issn.1002-6819.2022.01.009

    [28] 孙昭安, 王方, 张珊, 等. 秸秆添加对石灰性土壤有机与无机碳释放的影响[J]. 土壤学报, 2021, 58(6): 1520−1529.

    Sun Z A, Wang F, Zhang S, et al. The effect of straw addition on organic and inorganic carbon release from calcareous soils[J]. Acta Pedologica Sinica, 2021, 58(6): 1520−1529.

    [29] 陈绍荣. 玉米秸秆生物炭及其老化对石灰性农田土壤氨氧化和氨挥发的影响[D]. 山西太原: 太原理工大学硕士学位论文, 2018.

    Chen S R. Effects of fresh and aged maize straw-derived biochars on ammonia oxidation and volatilization in a calcareous farmland soil[D]. Taiyuan, Shanxi: MS Thesis of Taiyuan University of Technology, 2018.

    [30] 魏修利, 雷平, 石伟勇. 鱼蛋白有机液肥对小粉土酶活性和微生物生物量碳、氮的影响[J]. 应用生态学报, 2010, 21(8): 2086−2091.

    Wei X L, Lei P, Shi W Y. Effect of organic fish protein liquid fertilizer on enzyme activities and microbial biomass C and N in a silt soil[J]. Chinese Journal of Applied Ecology, 2010, 21(8): 2086−2091.

    [31] 侯苗苗. 有机氮替代比例对冬小麦/夏玉米轮作体系产量以及氮磷效率的影响[D]. 陕西杨凌: 西北农林科技大学硕士学位论文, 2018.

    Hou M M. Responses of crop yield and nitrogen and phosphorus use efficiency to chemical nitrogen substitution by manure under a winter wheat-summer maize rotation system on lou soil[D]. Yangling, Shaanxi: MS Thesis of Northwest Agriculture and Forestry University, 2018.

    [32] 刘楚桐, 陈松岭, 邹洪涛, 等. 生物基包膜抑制型尿素对土壤温室气体排放及小青菜产量的影响[J]. 农业环境科学学报, 2021, 40(3): 677−684. DOI: 10.11654/jaes.2020-0658

    Liu C T, Chen S L, Zou H T, et al. Effects of coated urea inhibitor encapsulated by bio-based film on soil greenhouse gas emission and Brassica chinensis yield[J]. Journal of Agro-Environment Science, 2021, 40(3): 677−684. DOI: 10.11654/jaes.2020-0658

    [33] 朱静平, 邓秋宏. 尿素深施后模拟水田系统中氮素的迁移转化途径[J]. 中国农学通报, 2022, 38(27): 66−73. DOI: 10.11924/j.issn.1000-6850.casb2021-1017

    Zhu J P, Deng Q H. Migration and transformation pathways of nitrogen in simulated paddy field system with deep application of urea[J]. Chinese Agricultural Science Bulletin, 2022, 38(27): 66−73. DOI: 10.11924/j.issn.1000-6850.casb2021-1017

    [34] 武亚楠, 喻理飞, 张丽敏, 等. 喀斯特高原区植被恢复过程中土壤碳特征及其影响因素[J]. 生态环境学报, 2020, 29(10): 1935−1942.

    Wu Y N, Yu L F, Zhang L M, et al. Characteristics and influencing factors of soil carbon pool during vegetation restoration in Karst Plateau[J]. Ecology and Environmental Sciences, 2020, 29(10): 1935−1942.

    [35] 曹明, 朱启林, 赵伶茹, 等. 抑制剂对海南土壤中硝化作用及N2O排放的影响[J]. 土壤通报, 2021, 52(1): 68−74.

    Cao M, Zhu Q L, Zhao L R, et al. Effect of inhibitor on soil nitrification and N2O emission in Hainan[J]. Chinese Journal of Soil Science, 2021, 52(1): 68−74.

    [36]

    Jones D L, Kemmitt S J, Wright D. Rapid intrinsic rates of amino acid biodegradation in soils are unaffected by agricultural management strategy[J]. Soil Biology & Biochemistry, 2005, 37(7): 1267−1275.

    [37] 翟修彩, 刘明, 李忠佩, 徐阳春. 不同添加剂处理秸秆腐解物对红壤性质的影响[J]. 土壤, 2013, 45(5): 868−874.

    Zhai X C, Liu M, Li Z P, Xu Y C. Effects of different additives promoted straw decomposition on red soil property[J]. Soils, 2013, 45(5): 868−874.

    [38] 马南, 安婷婷, 张久明, 汪景宽. 添加玉米秸秆和根茬对不同肥力黑土微生物残体碳氮的影响[J]. 中国农业科学, 2023, 56(4): 686−696. DOI: 10.3864/j.issn.0578-1752.2023.04.008

    Ma N, An T T, Zhang J M, Wang J K. Effects of maize shoot and root residues added on microbial residue carbon and nitrogen in different fertility levels of black soil[J]. Scientia Agricultura Sinica, 2023, 56(4): 686−696. DOI: 10.3864/j.issn.0578-1752.2023.04.008

    [39]

    Li J, Sang C, Yang J, et al. Stoichiometric imbalance and microbial community regulate microbial elements use efficiencies under nitrogen addition[J]. Soil Biology and Biochemistry, 2021, 156: 108207. DOI: 10.1016/j.soilbio.2021.108207

    [40]

    He H B, Zhang W, Zhang X D, et al. Temporal responses of soil microorganisms to substrate addition as indicated by amino sugar differentiation[J]. Soil Biology and Biochemistry, 2011, 43(6): 1155−1161. DOI: 10.1016/j.soilbio.2011.02.002

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  • 收稿日期:  2023-05-09
  • 录用日期:  2023-07-13
  • 网络出版日期:  2024-01-09
  • 刊出日期:  2024-01-24

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