干秸稈、鮮豆稈混合厭氧發(fā)酵條件優(yōu)化設(shè)計(jì)

鄧媛方,許家興,劉曉燕,戴本林,徐繼明

(1.淮陰師范學(xué)院 江蘇省生物質(zhì)能與酶技術(shù)重點(diǎn)實(shí)驗(yàn)室,江蘇淮安　223300;2.淮陰師范學(xué)院 江蘇省區(qū)域現(xiàn)代農(nóng)業(yè)與環(huán)境保護(hù)協(xié)同創(chuàng)新中心,江蘇淮安　223300)

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干秸稈、鮮豆稈混合厭氧發(fā)酵條件優(yōu)化設(shè)計(jì)

鄧媛方1,2,許家興1,2,劉曉燕1,2,戴本林1,2,徐繼明1,2

(1.淮陰師范學(xué)院 江蘇省生物質(zhì)能與酶技術(shù)重點(diǎn)實(shí)驗(yàn)室,江蘇淮安223300;2.淮陰師范學(xué)院 江蘇省區(qū)域現(xiàn)代農(nóng)業(yè)與環(huán)境保護(hù)協(xié)同創(chuàng)新中心,江蘇淮安223300)

摘要：以鮮豆稈和風(fēng)干稻秸作為發(fā)酵原料,在前期單因素實(shí)驗(yàn)基礎(chǔ)上,采用3因素5水平二次回歸正交旋轉(zhuǎn)組合設(shè)計(jì),以累計(jì)沼氣產(chǎn)量作為響應(yīng)值,探討溫度、干鮮比(鮮豆稈與風(fēng)干稻秸干物質(zhì)的質(zhì)量比)、接種物質(zhì)量分?jǐn)?shù)3因素對(duì)沼氣產(chǎn)量的影響,并建立數(shù)學(xué)模型,進(jìn)行模型擬合,確定最佳條件.結(jié)果表明：二次項(xiàng)模型擬合效果最佳,3因素對(duì)干鮮秸稈混合厭氧發(fā)酵產(chǎn)氣量影響的大小依次為接種物質(zhì)量分?jǐn)?shù)、溫度、干鮮比.最佳工藝條件為溫度28.97 ℃,干鮮比2.23∶1,接種物質(zhì)量分?jǐn)?shù)30.11%,預(yù)測(cè)TS產(chǎn)氣率279.789 L/kg.模型預(yù)測(cè)值與驗(yàn)證實(shí)驗(yàn)值之間相對(duì)偏差為0.23%(F<0.01),差異不顯著,該多元回歸模型擬合較好,為提高干鮮秸稈混合厭氧發(fā)酵產(chǎn)氣效率提供理論參考.

關(guān)鍵詞：沼氣；秸稈；厭氧發(fā)酵；模型優(yōu)化

隨著農(nóng)村分散養(yǎng)殖日益減少,及規(guī)?；B(yǎng)殖的快速推進(jìn),戶用沼氣面臨原料供給不足的困境.中國(guó)作為一個(gè)農(nóng)業(yè)大國(guó),生物資源豐富,其中半數(shù)以上為農(nóng)作物秸稈,其年產(chǎn)量超過(guò)7.5×108t[1],解決對(duì)農(nóng)作物秸桿的利用轉(zhuǎn)換意義重大.中國(guó)秸稈資源中水稻、小麥、玉米秸稈主要以風(fēng)干狀態(tài)存在,水分含量低,纖維素含量高,作為沼氣發(fā)酵原料具有碳氮比高、原料不易降解、發(fā)酵周期長(zhǎng)等特點(diǎn)[2],而豆稈、紅薯藤葉、蔬菜剩余物等鮮青秸稈具有碳氮比低、含水量高、易腐爛降解、發(fā)酵周期短等特點(diǎn)[3-5].本文以鮮豆稈和風(fēng)干稻秸為原料,采用二次回歸正交旋轉(zhuǎn)組合設(shè)計(jì)[6],研究發(fā)酵溫度、干鮮比(鮮豆稈與風(fēng)干稻秸干物質(zhì)的質(zhì)量比)、接種物質(zhì)量分?jǐn)?shù)3因素對(duì)干鮮秸稈原料混合厭氧消化的影響,為提高秸稈類原料厭氧消化產(chǎn)沼效率提供理論和實(shí)踐依據(jù).

1材料與方法

1.1材料與裝置

自然風(fēng)干水稻秸稈和新鮮大豆秸稈取自淮陰區(qū)郊區(qū)農(nóng)田,經(jīng)粉碎機(jī)粉碎至長(zhǎng)度1 cm.接種物取自江蘇省生物質(zhì)能與酶技術(shù)重點(diǎn)實(shí)驗(yàn)室自行馴化的厭氧發(fā)酵污泥,實(shí)驗(yàn)原料理化特性見(jiàn)表1.實(shí)驗(yàn)裝置為水壓式厭氧發(fā)酵裝置[7].

1.2實(shí)驗(yàn)設(shè)計(jì)

實(shí)驗(yàn)前期分別對(duì)可能影響厭氧發(fā)酵產(chǎn)氣效果的溫度條件、干鮮比和接種物質(zhì)量進(jìn)行單因素實(shí)驗(yàn),初步了解其在厭氧發(fā)酵過(guò)程中產(chǎn)氣量及甲烷含量變化情況.在此基礎(chǔ)上選擇合適的因素水平范圍進(jìn)行編碼,探討水稻、大豆秸稈原料混合厭氧消化的最佳工藝條件[8-10].因素水平編碼見(jiàn)表2.

利用Design-expet.V8.0.6數(shù)據(jù)處理軟件進(jìn)行二次正交旋轉(zhuǎn)組合實(shí)驗(yàn)方案設(shè)計(jì),單純考慮沼氣產(chǎn)量作為響應(yīng)值,并對(duì)回歸方程進(jìn)行檢驗(yàn),分析單因素(溫度、干鮮比及接種物質(zhì)量分?jǐn)?shù))的變化對(duì)大豆、水稻秸稈混合厭氧消化累計(jì)沼氣產(chǎn)量變化的影響及其主次效應(yīng)[11]和不同因素間交互作用對(duì)干鮮秸稈混合厭氧發(fā)酵產(chǎn)氣量的影響,最終確定最優(yōu)工藝條件.

表1　水稻、大豆秸稈原料及接種物理化特性

表2　水平編碼表

干鮮比指鮮豆稈與風(fēng)干稻秸干物質(zhì)的質(zhì)量比，下同.

1.3檢測(cè)方法

總碳(TOC)：總有機(jī)碳分析儀(島津TOC儀)；總氮(TN)：凱氏定氮法；干物質(zhì)(TS)測(cè)定：在(105±1) ℃的干燥箱中干燥至質(zhì)量恒定；產(chǎn)氣量：排水法收集氣體,量筒測(cè)定其體積[12].

2結(jié)果與分析

2.1模型構(gòu)建

通過(guò)Design-expet.V8.0.6實(shí)驗(yàn)設(shè)計(jì)軟件,對(duì)實(shí)際沼氣產(chǎn)率的結(jié)構(gòu)矩陣進(jìn)行排列并對(duì)其實(shí)驗(yàn)結(jié)果進(jìn)行預(yù)測(cè)建模,結(jié)果見(jiàn)表3.

表3　三元二次回歸正交旋轉(zhuǎn)組合設(shè)計(jì)實(shí)驗(yàn)結(jié)果

2.2擬合模型選擇

使用Design-expert.V8.0.6實(shí)驗(yàn)設(shè)計(jì)軟件選擇CCD實(shí)驗(yàn)[13],對(duì)表3實(shí)驗(yàn)結(jié)果中產(chǎn)氣量進(jìn)行數(shù)據(jù)分析,結(jié)果見(jiàn)表4.分別采用線性、二次和三次回歸模型對(duì)干鮮秸稈混合厭氧發(fā)酵實(shí)驗(yàn)中的沼氣產(chǎn)率進(jìn)行模型擬合,選擇最優(yōu)的擬合模型.可知二次模型擬合效果極顯著(P<0.000 1).

表4　模型參數(shù)擬合表

對(duì)總產(chǎn)氣量數(shù)據(jù)進(jìn)行失擬檢驗(yàn),由數(shù)據(jù)分析可知,線性模型(P<0.000 1)和三次模型(P=0.131 0)的損失度均大于二次模型(P=0.373 1),因此,確定二次模型的擬合程度更優(yōu).

對(duì)累計(jì)產(chǎn)氣量數(shù)據(jù)進(jìn)行R2綜合分析,線性、二次、三次模型R2依次為0.191 6、0.996 2、0.995 8,由表4可知,二次模型殘差平方和最小(1 476.340),據(jù)此推測(cè)二次模型預(yù)測(cè)值可信度更高.

綜上所述,通過(guò)對(duì)建立的線性、二次項(xiàng)、三次項(xiàng)模型進(jìn)行方差分析、失擬檢驗(yàn)和R2綜合分析可知,選擇二次項(xiàng)模型對(duì)本實(shí)驗(yàn)數(shù)據(jù)進(jìn)行擬合是理想的方式.

2.3TS產(chǎn)氣率模型的建立

采用Design-expet.V8.0.6數(shù)據(jù)分析軟件對(duì)表3數(shù)據(jù)進(jìn)行方差分析及系數(shù)估計(jì),結(jié)果見(jiàn)表5,沼氣產(chǎn)率為y值,得出以溫度(x1)、干鮮比(x2)、接種物質(zhì)量分?jǐn)?shù)(x3)3因素編碼值為自變量的三元二次回歸方程,見(jiàn)式1.

y=286.99+35.15x1-8.03x2-47.58x3+11.25x1x2-9.00x1x3+

6.75x2x3-55.22x12-48.32x22-40.55x32.

(1)

對(duì)各項(xiàng)回歸系數(shù)進(jìn)行顯著性檢驗(yàn)(P<0.01),回歸方差顯著,失擬方差不顯著(P=0.373 1),說(shuō)明該方程的擬合良好.實(shí)驗(yàn)采用數(shù)據(jù)與建立二次數(shù)學(xué)模型相符,不需要改變回歸模型.

表5　回歸方程的方差分析

2.4單因素效應(yīng)分析

根據(jù)回歸模型(式 1),依次將3因素中的2個(gè)固定在零水平上，建立溫度、干鮮比和接種物質(zhì)量分?jǐn)?shù)分別對(duì)產(chǎn)氣量影響的單因素回歸模型,見(jiàn)式(2)、(3)、(4).以編碼值為橫坐標(biāo),產(chǎn)氣量為縱坐標(biāo),繪制出溫度、干鮮比、接種物質(zhì)量分?jǐn)?shù)對(duì)產(chǎn)氣量的影響曲線,并對(duì)其進(jìn)行擬合,如圖1所示.

圖1　單因素與產(chǎn)氣量的關(guān)系　Fig.1　Relationship between single factor andbiogas yield

由圖1可知,3因素水平變化對(duì)產(chǎn)氣量的影響趨勢(shì)均呈現(xiàn)出開(kāi)口向下的拋物線形態(tài),通過(guò)拋物線的坡度緩急程度以及式(1)中一次項(xiàng)系數(shù)絕對(duì)值大小可以判斷出對(duì)產(chǎn)氣量影響的主次效應(yīng),3因素對(duì)總產(chǎn)氣量的影響順序依次是：接種物質(zhì)量分?jǐn)?shù)>溫度>干鮮比.

y=286.99+35.15x1-55.22x12，

(2)

y=286.99-8.03x2-48.32x22，

(3)

y=286.99-47.58x3-40.55x32.

(4)

2.5交互因素效應(yīng)分析

采用Design-expet.V8.0.6數(shù)據(jù)分析軟件對(duì)3個(gè)因素兩兩之間的交互作用進(jìn)行分析,得到因素之間的響應(yīng)面及等高線圖(圖2).

由圖2可知,發(fā)酵溫度與干鮮比之間交互效應(yīng)顯著.固定干鮮比,產(chǎn)氣量隨溫度增加呈現(xiàn)出先增大后減少的趨勢(shì).實(shí)驗(yàn)選取上水平條件時(shí)產(chǎn)氣量減少可能與實(shí)驗(yàn)所用馴化接種物有關(guān),發(fā)酵罐中所用微生物菌群在30 ℃條件下馴化,進(jìn)入溫度相似環(huán)境能很快適應(yīng),甲烷菌活性大.溫度的驟變給產(chǎn)甲烷微生物活性帶來(lái)顯著影響[14-15].

圖3反應(yīng)發(fā)酵溫度與接種物質(zhì)量分?jǐn)?shù)的變化對(duì)累計(jì)產(chǎn)氣量的影響趨勢(shì),當(dāng)接種物質(zhì)量分?jǐn)?shù)處于上水平條件時(shí),產(chǎn)氣量有下降的趨勢(shì),在同樣容積負(fù)荷下,接種量越大,發(fā)酵罐中所添加的原料就越少,發(fā)酵罐的容積利用率越低,這對(duì)于發(fā)酵并不利,會(huì)增加同等質(zhì)量原料消化所需容積,降低發(fā)酵罐的容積利用率,增加投資和運(yùn)行成本[16]；當(dāng)接種物質(zhì)量分?jǐn)?shù)處于下水平條件時(shí),產(chǎn)氣量總體偏高.說(shuō)明接種物質(zhì)量分?jǐn)?shù)在零水平條件時(shí),接種強(qiáng)度已經(jīng)足夠.在評(píng)估最終沼氣產(chǎn)量時(shí),接種量一般以能夠基本消除批量消化的延滯期和保持 pH值穩(wěn)定為佳[17-19].

圖2　溫度(x1)、干鮮比(x2)對(duì)產(chǎn)氣量的影響圖3　溫度(x1)、接種物質(zhì)量分?jǐn)?shù)(x3)對(duì)產(chǎn)氣量的影響Fig.2　Effect of temperature(x1) and dry-fresh(x2) TS ratio on Fig.3　Effect of temperature(x1) and inoculation massbiogas productionfraction(x3) on biogas production

由圖4可知,干鮮比與接種物質(zhì)量分?jǐn)?shù)對(duì)產(chǎn)氣量的影響均呈現(xiàn)開(kāi)口向下的拋物線形,同一接種物質(zhì)量分?jǐn)?shù)水平條件下,不同干鮮比條件對(duì)產(chǎn)氣量有小幅影響,本實(shí)驗(yàn)通過(guò)干鮮比調(diào)配控制碳、氮質(zhì)量比在23∶1～30∶1.一般認(rèn)為發(fā)酵原料的碳、氮質(zhì)量比以(20～30)∶1產(chǎn)氣效果較好[20].

2.6最優(yōu)工藝條件確定

通過(guò)模型尋優(yōu),得到干鮮秸稈混合厭氧發(fā)酵最佳工藝條件為：溫度28.97 ℃,干鮮比為2.23∶1,接種物質(zhì)量分?jǐn)?shù)30.11%,預(yù)測(cè)TS產(chǎn)氣率279.789 L/kg(表6).

為證實(shí)預(yù)測(cè)結(jié)果,采用上述最優(yōu)條件進(jìn)行干鮮秸稈混合厭氧發(fā)酵實(shí)驗(yàn),3次重復(fù),實(shí)測(cè)累計(jì)沼氣產(chǎn)量平均19.63 L(即TS產(chǎn)氣率280.43 L/kg)，較預(yù)測(cè)值相對(duì)偏差為0.23%(F<0.01),差異性不顯著,驗(yàn)證了該多元回歸模型的合理性.

圖4　干鮮比(x2)、接種物質(zhì)量分?jǐn)?shù)(x3)對(duì)產(chǎn)氣量的影響Fig.4　　　　Effect of dry-fresh(x2) TS ratio and inoculation mass　　　fraction(x3) on biogas production

因 子編碼值實(shí)際值x10.668 28.97 x20.391 2.23 x3-0.031 30.11 穩(wěn)定點(diǎn)的TS預(yù)測(cè)值279.789L/kg

3結(jié)論

1)通過(guò)溫度(x1)、干鮮比 (x2)、接種物質(zhì)量分?jǐn)?shù)(x3) 3因素5水平二次旋轉(zhuǎn)正交組合實(shí)驗(yàn),得到累計(jì)沼氣產(chǎn)量(y)的回歸模型為

y=286.99+35.15x1-8.03x2-47.58x3+11.25x1x2-9.00x1x3+

6.75x2x3-55.22x12-48.32x22-40.55x32

方差分析、失擬檢驗(yàn)和R2綜合分析表明,所得模型擬合良好,能夠用于描述累計(jì)沼氣產(chǎn)量隨發(fā)酵溫度、原料干鮮比、接種物質(zhì)量分?jǐn)?shù)的變化規(guī)律.

2)3因素對(duì)干鮮秸稈混合厭氧發(fā)酵產(chǎn)氣的影響大小依次為接種物質(zhì)量分?jǐn)?shù)、溫度、干鮮比,且溫度與干鮮比、接種物質(zhì)量分?jǐn)?shù),干鮮比與接種物質(zhì)量分?jǐn)?shù)之間交互作用影響顯著.

3)風(fēng)干水稻秸稈、新鮮大豆秸稈混合厭氧消化最優(yōu)沼氣產(chǎn)量工藝條件為:溫度28.97 ℃,干鮮比2.23∶1,接種物質(zhì)量分?jǐn)?shù)30.11%,預(yù)測(cè)TS產(chǎn)氣率 279.789L/kg.

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(責(zé)任編輯：趙藏賞)

Optimization design of anaerobic fermentation with mixed materials of bean stalk and rice straw

DENG Yuanfang1,2,XU Jiaxing1.2,LIU Xiaoyan1,2,DAI Benlin1,2,XU Jiming1,2

(1.Jiangsu Key Laboratory for Biomass-based Energy and Enzyme Technology,Huaiyin Normal University,Huaian 223300,China;2.Jiangsu Collaborative Innovation Center of Regional Modern Agriculture & Environmental Protection,Huaiyin Normal University,Huaian 223300,China)

Abstract:This experiment use fresh bean stalk and natural withering rice straw as fermentation materials.On the basis of earlier single factor test,three factors five levels quadratic regression orthogonal rotating combination design was adopted in this study,and only the accumulative gas production was involved in the response value.Effects of three factors on anaerobic fermentation were analyzed,including the environment of anaerobic fermentation temperature,dry-fresh TS ratio,inoculation percentage and the mathematical model for anaerobic mixed fermentation of bean stalk and rice straw was developed.The regression equation was optimized and analyzed when the optimum conditions and interactive effects were exposed.The results showed that the quadratic model had the optimal fitting data.The sequence of factors effecting anaerobic fermentation was inoculation percentage,the environment of anaerobic fermentation temperature

and dry-fresh TS ratio.The optimum conditions for dry-fresh mixed-fermentation were determined as follows:the temperature was 28.97 ℃,dry-fresh TS ratio of fresh bean stalk and rice straw was 2.23∶1,inoculation percentage was 30.11% and prediction value of TS production rate was 279.789 L/kg.Through testing with related experimental data,the relative deviation of biogas production between experiment measurement and model prediction was 0.23 %(F<0.01),which proved the multiple regression model had high fitting degree and applicability.This study could provide certain theory reference for materials anaerobic digestion of mixed straw material.

Key words:biogas;straw;anaerobic digestion;model optimization

DOI：10.3969/j.issn.1000-1565.2016.01.010

收稿日期：2015-06-25

基金項(xiàng)目：國(guó)家自然科學(xué)基金青年科學(xué)基金資助項(xiàng)目(21406083);江蘇省生物質(zhì)能與酶技術(shù)重點(diǎn)實(shí)驗(yàn)室資助項(xiàng)目(JSBEET1211)

通信作者:許家興(1986—),男,山東日照人，淮陰師范學(xué)院副教授,博士,主要從事生物質(zhì)能研究.

中圖分類號(hào)：X712

文獻(xiàn)標(biāo)志碼：A

文章編號(hào)：1000-1565(2016)01-0058-07

第一作者:鄧媛方(1985—),女,河南南陽(yáng)人,淮陰師范學(xué)院講師,主要從事生物質(zhì)能研究.E-mail:dengyf@hytc.edu.cn

E-mail：xujiaxing@hytc.edu.cn