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This study investigated the pretreatment of rice straw using different soaking solvents (deionized water, nanobubble water, biogas slurry, and nanobubble water coupled with biogas slurry) for 5 days. The study explored the changes in volatile fatty acid content, lignocellulose content, and methane production in different treatments after soaking pretreatment. The results indicated that the treatment of soaking with nanobubble water and the treatment of combing soaking of nanobubble water with biogas slurry both enhanced the pretreatment effectiveness of the rice straw. The treatment of combing soaking of nanobubble water with biogas slurry showed the optimal pretreatment performance, with the volatile fatty acid content reaching 6 470 mg/L. The cellulose degradation rate and hemicellulose degradation rate reached at 12.1% and 23.7% , respectively, and the maximum cumulative methane yield increased by 19.5%.

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文章以水稻秸秆为研究对象,采用4种浸泡溶剂(去离子水、纳米气泡水、沼液、纳米气泡水联合沼液)对水稻秸秆进行5d厌氧预处理,研究了不同浸泡预处理对挥发性脂肪酸含量、木质纤维素含量以及甲烷产率的影响。结果表明:纳米气泡水和沼液浸泡均促进了水稻秸秆的水解过程;纳米气泡水联合沼液组的处理效果最为突出,挥发性脂肪酸含量达到了6470mg/L,纤维素和半纤维素降解率分别达到了12.1%和23.7%,最大累积甲烷产率提高了19.5%。

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郭建斌(1982-),男,博士,副教授,研究方向为农业废弃物资源化与高值化利用。E-mail:
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特性 水稻秸秆 浸泡沼液 接种物
TS 含量 ${94.1} \pm {0.3}$ ${18.0} \pm {1.2}$ ${5.4} \pm {0.2}$
VS 含量 ${81.5} \pm {0.2}$ ${7.8} \pm {0.2}$ ${3.0} \pm {0.1}$
纤维素含量 ${35.6} \pm {0.6}$ ${3.1} \pm {0.2}$ -
半纤维素含量 ${31.3} \pm {0.5}$ ${15.8} \pm {0.9}$ -
木质素含量 ${4.3} \pm {0.6}$ ${2.4} \pm {0.4}$ -
), ArticleFig(id=1154430676171477298, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154430657406161088, language=CN, label=表 1, caption=水稻秸秆、浸泡沼液和接种物的物化性质, figureFileSmall=null, figureFileBig=null, tableContent=
特性 水稻秸秆 浸泡沼液 接种物
TS 含量 ${94.1} \pm {0.3}$ ${18.0} \pm {1.2}$ ${5.4} \pm {0.2}$
VS 含量 ${81.5} \pm {0.2}$ ${7.8} \pm {0.2}$ ${3.0} \pm {0.1}$
纤维素含量 ${35.6} \pm {0.6}$ ${3.1} \pm {0.2}$ -
半纤维素含量 ${31.3} \pm {0.5}$ ${15.8} \pm {0.9}$ -
木质素含量 ${4.3} \pm {0.6}$ ${2.4} \pm {0.4}$ -
), ArticleFig(id=1154430676242780467, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154430657406161088, language=EN, label=Table 2, caption=Settings of each experimental group, figureFileSmall=null, figureFileBig=null, tableContent=
组别 浸泡水 秸秆与浸泡 水的质量比 沼液 秸秆与沼液 的 VS 含量比
DW 组 DW 1:10 不添加 -
NBW 组 NBW 1:10 不添加 -
BS 组 DW 1:10 添加 4:1
NBW-BS 组 NBW 1:10 添加 4:1
), ArticleFig(id=1154430676343443764, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154430657406161088, language=CN, label=表 2, caption=各试验组的设置, figureFileSmall=null, figureFileBig=null, tableContent=
组别 浸泡水 秸秆与浸泡 水的质量比 沼液 秸秆与沼液 的 VS 含量比
DW 组 DW 1:10 不添加 -
NBW 组 NBW 1:10 不添加 -
BS 组 DW 1:10 添加 4:1
NBW-BS 组 NBW 1:10 添加 4:1
), ArticleFig(id=1154430676410552629, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154430657406161088, language=EN, label=Table 3, caption=Modified Gompertz model parameters after different soaking pretreatment, figureFileSmall=null, figureFileBig=null, tableContent=
组别
DW 组 ${250.7} \pm {3.4}$ ${17.2} \pm {0.5}$ ${0.4} \pm {0.2}$ 0.996
NBW 组 ${261.2} \pm {3.9}$ ${18.7} \pm {0.7}$ ${0.4} \pm {0.2}$ 0.994
BS 组 ${282.0} \pm {3.3}$ ${21.9} \pm {0.6}$ ${1.5} \pm {0.2}$ 0.996
NBW-BS 组 296.4±3.3 ${22.4} \pm {0.6}$ ${1.5} \pm {0.2}$ 0.997
), ArticleFig(id=1154430676460884278, tenantId=1146029695717560320, journalId=1146119893612605453, articleId=1154430657406161088, language=CN, label=表 3, caption=不同浸泡预处理后的修正 Gompertz 模型参数, figureFileSmall=null, figureFileBig=null, tableContent=
组别
DW 组 ${250.7} \pm {3.4}$ ${17.2} \pm {0.5}$ ${0.4} \pm {0.2}$ 0.996
NBW 组 ${261.2} \pm {3.9}$ ${18.7} \pm {0.7}$ ${0.4} \pm {0.2}$ 0.994
BS 组 ${282.0} \pm {3.3}$ ${21.9} \pm {0.6}$ ${1.5} \pm {0.2}$ 0.996
NBW-BS 组 296.4±3.3 ${22.4} \pm {0.6}$ ${1.5} \pm {0.2}$ 0.997
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纳米气泡水与沼液联合浸泡对水稻秸秆厌氧产气性能的影响
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邢帆 1 , 王恩振 2 , 吴兴国 2 , 李玉蓉 2 , 马雪杨 2 , 王晓 1 , 徐吉磊 1 , 董仁杰 2 , 郭建斌 2
可再生能源 | 2024,42(5): 587-591
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可再生能源 | 2024, 42(5): 587-591
纳米气泡水与沼液联合浸泡对水稻秸秆厌氧产气性能的影响
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邢帆1, 王恩振2, 吴兴国2, 李玉蓉2, 马雪杨2, 王晓1, 徐吉磊1, 董仁杰2, 郭建斌2
作者信息
  • 1 青岛汇君环境能源工程有限公司 山东 青岛 266100
  • 2 中国农业大学 工学院 北京 100083

通讯作者:

郭建斌(1982-),男,博士,副教授,研究方向为农业废弃物资源化与高值化利用。E-mail:
Effect of combined soaking with nanobubble water and biogas slurry on the biogas production performance of rice straw
Fan Xing1, Enzhen Wang2, Xingguo Wu2, Yurong Li2, Xueyang Ma2, Xiao Wang1, Jilei Xu1, Renjie Dong2, Jianbin Guo2
Affiliations
  • 1 Qingdao Huijun Environmental Energy Engineering Co. Ltd. Qingdao 266100 China
  • 2 College of Engineering China Agricultural University Beijing 100083 China
出版时间: 2024-05-20
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文章以水稻秸秆为研究对象,采用4种浸泡溶剂(去离子水、纳米气泡水、沼液、纳米气泡水联合沼液)对水稻秸秆进行5d厌氧预处理,研究了不同浸泡预处理对挥发性脂肪酸含量、木质纤维素含量以及甲烷产率的影响。结果表明:纳米气泡水和沼液浸泡均促进了水稻秸秆的水解过程;纳米气泡水联合沼液组的处理效果最为突出,挥发性脂肪酸含量达到了6470mg/L,纤维素和半纤维素降解率分别达到了12.1%和23.7%,最大累积甲烷产率提高了19.5%。

水稻秸秆  /  厌氧消化  /  纳米气泡水  /  浸泡预处理

This study investigated the pretreatment of rice straw using different soaking solvents (deionized water, nanobubble water, biogas slurry, and nanobubble water coupled with biogas slurry) for 5 days. The study explored the changes in volatile fatty acid content, lignocellulose content, and methane production in different treatments after soaking pretreatment. The results indicated that the treatment of soaking with nanobubble water and the treatment of combing soaking of nanobubble water with biogas slurry both enhanced the pretreatment effectiveness of the rice straw. The treatment of combing soaking of nanobubble water with biogas slurry showed the optimal pretreatment performance, with the volatile fatty acid content reaching 6 470 mg/L. The cellulose degradation rate and hemicellulose degradation rate reached at 12.1% and 23.7% , respectively, and the maximum cumulative methane yield increased by 19.5%.

rice straw  /  anaerobic digestion  /  nanobubble water  /  soaking pretreatment
邢帆, 王恩振, 吴兴国, 李玉蓉, 马雪杨, 王晓, 徐吉磊, 董仁杰, 郭建斌. 纳米气泡水与沼液联合浸泡对水稻秸秆厌氧产气性能的影响. 可再生能源, 2024 , 42 (5) : 587 -591 .
Fan Xing, Enzhen Wang, Xingguo Wu, Yurong Li, Xueyang Ma, Xiao Wang, Jilei Xu, Renjie Dong, Jianbin Guo. Effect of combined soaking with nanobubble water and biogas slurry on the biogas production performance of rice straw[J]. Renewable Energy Resources, 2024 , 42 (5) : 587 -591 .
作为粮食生产大国,我国拥有丰富的农作物秸秆资源,秸秆年产量约为 9.7 亿 $\mathrm{t}$ ,其中以玉米秸秆、水稻秸秆和小麦秸秆为主 [ 1 ] 。近年来,由于秸秆禁烧政策的提出,合理利用农业主产区的秸秆成为农村绿色发展中亟待解决的问题。厌氧消化是一种利用厌氧微生物将秸秆等有机物分解转化为沼气的生化过程, 是秸秆能源化利用的重要方式之一。但是, 秸秆的木质纤维素结构和表层蜡质层等因素严重制约了厌氧消化的水解效率 [ 2 ] 。因此,需要对秸秆进行预处理,以提高秸秆生物可及性,进而实现高效的厌氧消化 [ 3 ]
纳米气泡水 (Nanobubble Water, NBW) 是一种含有大量直径小于 ${1000}\mathrm{\;{nm}}$ 气泡的水溶液 [ 4 ] 。 NBW 具有比表面积大、水力停留时间长、能产生羟基自由基等特点, 被广泛应用于污水处理、水产养殖、农田灌溉等领域 [ 5 , 6 ] 。近年来,研究人员将 NBW 引入到厌氧消化体系中,发现 NBW 具有促进农业废弃物沼气生产的作用 [ 7 , 8 ] 。这是因为 $\mathrm{{NBW}}$ 的加入改变了厌氧体系, 创造了微氧环境, 提高了兼性细菌的活性,加快了复杂有机物的水解,最终实现沼气产率的提高 [ 9 ] 。秸秆预处理是秸秆厌氧消化必不可少的步骤, 但目前仍缺少 NBW 对秸秆预水解效果影响的研究。
沼液浸泡处理既能降低生物预处理成本,又能降低沼液废物的处理难度, 因此被广泛应用于大型秸秆沼气工程。沼液中含有丰富的微生物和营养物质 $\left({\mathrm{{NH}}}_{4}^{+ }\right.$ ,氨基酸等),具有加速秸秆水解和克服高碳氮比抑制的潜力 [ 10 ] 。李杨 [ 11 ] 利用沼液将油菜秸秆浸泡预处理 ${18}\mathrm{\;d}$ ,结果表明,浸泡处理 5 $\mathrm{d}$ 的油菜秸秆甲烷产率达到 ${154.0}\mathrm{{mL}}/\mathrm{g}$ ,较未浸泡油菜秸秆的甲烷产率提高了 28.9%。兰艳艳 [ 12 ] 的研究表明,使用含水率为 85%的猪粪沼液浸泡处理小麦秸秆 $1\mathrm{\;d}$ 后,小麦秸秆的甲烷产率比对照组提高了 43.2%。由此可见,沼液浸泡预处理能够有效改善秸秆的水解酸化效果。
在沼液浸泡处理过程中添加 NBW 会稀释沼液浓度, 导致浸泡反应器的单位体积利用率降低。 因此, 如何优化和改进 NBW 对秸秆沼液浸泡水解的影响仍需更进一步的研究。本研究以水稻秸秆为底物, 探究 NBW 和高浓度沼液浸泡对于秸秆联合预处理的效果以及预处理后产气潜力的影响, 从而提出一种适用于秸秆沼气工程的绿色、高效的原料预处理手段。
本文中所使用的水稻秸秆来自湖北襄阳农田,收获并晾晒一段时间后运输至实验室粉碎,过 20 目筛后备用。浸泡沼液和接种物取自北京某污水处理厂长期运行的厌氧发酵罐。浸泡沼液使用离心机离心 (转速为 ${1500}\mathrm{r}/\mathrm{{min}}$ ,离心时间为 50 min)后弃去上清液,储存备用。接种物放置在(37± 2)℃的厌氧环境下,存放至不产气后备用。水稻秸秆、浸泡沼液和接种物的物化性质见 表 1
$\mathrm{{NBW}}$ 是采用纳米气泡快速发生装置 $\left({\mathrm{O}}_{2}\right.$ 流量设为 $1\mathrm{\;L}/\mathrm{{min}}$ ,水箱内去离子水体积为 ${20}\mathrm{\;L}$ ,运行时间为 ${15}\mathrm{\;{min}}$ )制备的,该装置利用了水力空化法的原理。制备完成后,放置 $3 \sim 5\mathrm{\;{min}}$ ,在此期间, 纳米气泡水逐渐由乳白色变为透明,大部分宏观气泡和微米气泡从水中逸出。
本文共设计 4 个试验组进行浸泡预处理: 对照组 (DW 组),仅添加去离子水 (DW) 作为浸泡溶剂;单一 NBW 组 (NBW 组), 仅添加 NBW 作为浸泡溶剂;沼液浸泡组(BS 组),添加 DW 和沼液作为浸泡溶剂;NBW 与沼液联合浸泡组(NBW-BS 组), 添加 NBW 和沼液作为浸泡溶剂。各试验组的设置见 表 2
为避免空气中的氧气对浸泡过程的影响, 在加入试验物料后用 ${\mathrm{N}}_{2}$ 冲洗玻璃瓶以排空氧气,然后用丁腈橡胶塞密封。所有的玻璃瓶都放在 $({37}\pm$ 2 ) ${}^{\circ }\mathrm{C}$ 的恒温水浴箱中浸泡 $5\mathrm{\;d}$ ,每天定时摇晃,保证浸泡的均匀性。
浸泡 $5\mathrm{\;d}$ 后,进行水稻秸秆产气潜力试验。按照水稻秸秆和接种物的 VS 含量之比为 $1 :{1.5}$ 直接加入接种物,用 ${\mathrm{N}}_{2}$ 冲洗玻璃瓶以排空氧气,然后用丁腈橡胶塞密封。所有的玻璃瓶都放在(37± 2)℃的恒温水浴箱中发酵 ${30}\mathrm{\;d}$ ,定期记录沼气产量和甲烷含量。
浸泡前后秸秆的 TS 和 VS 含量采用差重法进行测试。浸泡液中的挥发性脂肪酸(VFAs)含量采用岛津 GC-2010 Plus 型气相色谱仪进行测定。 定期使用玻璃注射器测量各组的沼气产量, 并以单位质量 VS 记录累积甲烷产率和日均甲烷产率。同时使用岛津 GC-8A 型气相色谱仪测定沼气成分。纤维素、半纤维素和木质素含量采用范式洗涤法进行测定。纤维素和半纤维素降解率的计算式为
$\eta =\frac{{W}_{0}- {W}_{1}}{{W}_{0}}\times {100}\%$
式中: $\eta$ 为(半)纤维素降解率, $\%;{W}_{0}$ 为浸泡前 (半)纤维素质量, $\mathrm{g};{W}_{1}$ 为浸泡后(半)纤维素质量, g。
使用修正的 Gompertz 模型对水稻秸秆的甲烷产率进行动力学特性分析 [ 2 ]
$ P\left( t\right)= {P}_{\max }\times \exp \left\{{-\exp \left\lbrack {\frac{{R}_{\max }\mathrm{e}}{{P}_{\max }}\left({\lambda - t}\right)+ 1}\right\rbrack }\right\}$
式中: $P\left( t\right)$ 为累积甲烷产率(以单位质量的 VS 计, 下同), $\mathrm{{mL}}/\mathrm{g};{P}_{\max }$ 为最大累积甲烷产率, $\mathrm{{mL}}/\mathrm{g};{R}_{\max }$ 为最大产甲烷速率, $\mathrm{{mL}}/\left({\mathrm{g}\cdot \mathrm{d}}\right);\lambda$ 为迟滞期, $\mathrm{d};t$ 为实验时间, d。
经过 $5\mathrm{\;d}$ 浸泡后,各组浸泡液中的 VFAs 含量如 图 1 所示。
图 1 可以看出:DW 组、NBW 组、BS 组和 NBW-BS 组的 VFAs 含量分别达到 1484.6, ${3370.8},{6100.2},{6470.0}\mathrm{{mg}}/\mathrm{L}$ ;与 DW 组相比,其余三组的 VFAs 含量均显著提高; 各组浸泡液中的 VFAs 均以乙酸为主,乙酸含量分别达到 655.5, 2393.8,3466.2,3693.1 mg/L,与 DW 组相比, NBW 组、BS 组和 NBW-BS 组的乙酸含量分别提高了 265.2%,428.8% 和 463.4%。
浸泡液体中的 VFAs 含量是衡量秸秆水解效果的最直接的指标之一, 尤其是乙酸可被后续古菌直接利用,加快沼气生产速率。与 DW 组相比, NBW 组的 VFAs 含量显著增加, 这说明 NBW 的添加有利于微生物利用有机物生产 VFAs。Wang $\mathrm{X}$ 研究发现,在高负荷纤维素厌氧反应器中添加 Air-NBW 后, VFAs 含量提高了 ${30.3}\%$ [ 13 ] 。这可能与 Air-NBW 添加后创造的微氧环境有关,引入的少量外源氧气提高了兼性细菌的活性, 从而促进了微生物分解有机物的速率。此外, NBW 具有更高的传质效率, 可以加速微生物与外界环境的营养物质交换和传递, 提高微生物活性和促进水解酶的释放 [ 7 , 9 , 14 ] 。由于 DW 组和 NBW 组未引入外源微生物, 其浸泡液中的 VFAs 含量比添加沼液组 (BS 组和 NBW-BS 组)低。通过添加沼液, 可以利用沼液本身含有的水解微生物加速秸秆的降解。 同时, 沼液中含有的氨氮和其他有机物可以为微生物提供养分, 从而加速水解过程中 VFAs 的产生。NBW 与沼液联合浸泡预处理水稻秸秆 (NBW-BS 组)可以实现最高的 VFAs 含量, 这说明 NBW 的添加进一步促进了沼液浸泡秸秆的水解效率。
浸泡 $5\mathrm{\;d}$ 后,各组的纤维素和半纤维素降解率见 图 2 。从 图 2 可以看出, DW 组、NBW 组、BS 组和 NBW-BS 组的纤维素降解率分别为 ${3.2}\%$ , ${4.8}\%,{8.3}\%$${12.1}\%$ ,半纤维素降解率分别为 ${15.5}\%,{16.9}\%,{23.6}\%$${23.7}\%$ 。以上结果表明,与 DW 组相比,其余三组的纤维素和半纤维素降解率均显著提高。
纤维素和半纤维素降解率是衡量秸秆水解效果的关键指标。秸秆主要由纤维素、半纤维素和木质素组成, 三者组成的致密复杂的木质纤维素结构是制约秸秆厌氧消化产沼气的主要因素 [ 15 , 16 ] 。 在秸秆浸泡预处理过程中, 部分木质纤维素被水解微生物降解为单糖等小分子物质后进一步被转化为 ${\mathrm{{VFAs}}}_{0}$ 与纤维素相比,半纤维素更易被降解, 这是由于大部分纤维素以结晶形态为主要形式, 其酶解难度更高 [ 17 ] 。这可能是造成浸泡过程中纤维素降解率低的原因,特别是没有添加外源水解微生物的 DW 组和 NBW 组。这也与本研究中半纤维素的降解率明显高于纤维素降解率的结果相符。另外, 有研究表明, 浸泡前后秸秆的微观结构发生了显著变化, 原有的光滑平整表面出现了沟壑、孔洞,这说明浸泡预处理可以增加微生物和相关水解酶与秸秆的接触面积, 从而有利于后续微生物的降解利用 [ 2 , 18 ]
不同浸泡预处理后的秸秆累积甲烷产率和日均甲烷产率见 图 3 。从 图 3(a)可以看出,经过 30 $\mathrm{d}$ 发酵后, DW 组、NBW 组、BS 组和 NBW-BS 组的累积甲烷产率分别达到了 251.8,264.1,286.7, ${300.9}\mathrm{\;{mL}}/\mathrm{g}$ (以单位质量的 VS 计)。与 DW 组相比, 其余三组的累积甲烷产率提高了 4.9%~19.5%。这可能是由于 NBW 为体系中引入了氧气, 促进了兼性水解细菌水解酶的释放, 促进了更多大分子有机物降解为乙酸等易降解的小分子物质, 同时破坏了秸秆本身的致密结构,增加了厌氧消化过程微生物对秸秆的利用和转化。然而, NBW 组没有额外补充水解微生物, 而秸秆自身携带的细菌又相对较少, 导致 NBW 组的累积甲烷产率提高效果相对有限。沼液不仅为浸泡过程提供了水解菌,同时提供了大量的营养物质,从而提高了预水解的效率和处理效果 [ 11 , 12 ] 。因此, NBW-BS 组具有最大的累积甲烷产率,即 NBW 和沼液联合预处理的效果最优。
图 3(b) 可以看出:与 DW 组相比,添加 NBW 可以提高日均甲烷产率, 这可能是因为 $\mathrm{{NBW}}$ 可促进 $\mathrm{{VFAs}}$ 的产量,从而使 $\mathrm{{NBW}}$ 组的最大日均甲烷产率高于 DW 组;与未添加沼液组相比,添加沼液组的最大日均甲烷产率出现滞后,这可能与预处理过程中产生的大量丙酸有关。据报道, 在丙酸浓度较高的情况下, 产甲烷古菌会由嗜乙酸甲烷菌主导向嗜氢甲烷菌转变, 从而降低甲烷生产速率,使沼气产量出现滞后性 [ 19 ]
不同浸泡预处理后的秸秆产甲烷动力学分析见 表 3 。由 表 3 可知: 各组的相关系数 ${R}^{2}$ 均大于 0.994, 表明修正的 Gompertz 模型拟合效果良好; $\mathrm{{NBW}}- \mathrm{{BS}}$ 组的 ${P}_{\max }$ 达到了 ${296.4}\mathrm{\;{mL}}/\mathrm{g}$ ,分别比 $\mathrm{{DW}}$ 组、NBW 组和 BS 组提高了 18.2%, 13.4% 和 5.1%; NBW 和沼液浸泡均提高了水稻秸秆的 ${R}_{\max }$
本文通过采用不同浸泡溶剂 $(\mathrm{{DW}},\mathrm{{NBW}},\mathrm{{BS}}$ 和 NBW-BS)对水稻秸秆浸泡处理 $5\mathrm{\;d}$ 后发现, NBW 和沼液浸泡均能促进秸秆预水解。其中, NBW-BS 组的处理效果最为突出, NBW-BS 组的 VFAs 含量达到了 ${6470}\mathrm{{mg}}/\mathrm{L}$ ,纤维素和半纤维素降解率分别为 12.1% 和 23.7%,最高累积甲烷产率提高了 19.5%。使用修正的 Gompertz 模型进行动力学拟合分析后发现,通过 NBW 和沼液浸泡均提高了水稻秸秆的最大累积甲烷产率和最大产甲烷速率。
  • 国家自然科学基金项目(U20A2086)
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2024年第42卷第5期
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  • 接收时间:2023-12-16
  • 首发时间:2025-07-22
  • 出版时间:2024-05-20
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  • 收稿日期:2023-12-16
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国家自然科学基金项目(U20A2086)
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    1 青岛汇君环境能源工程有限公司 山东 青岛 266100
    2 中国农业大学 工学院 北京 100083

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郭建斌(1982-),男,博士,副教授,研究方向为农业废弃物资源化与高值化利用。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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