紅薯收獲機(jī)的設(shè)計(jì)與仿真【說(shuō)明書+CAD+PROE+仿真】

紅薯收獲機(jī)的設(shè)計(jì)與仿真【說(shuō)明書+CAD+PROE+仿真】,說(shuō)明書+CAD+PROE+仿真,紅薯,收獲,收成,設(shè)計(jì),仿真,說(shuō)明書,仿單,cad,proe 畢業(yè)設(shè)計(jì)附本紅薯收獲機(jī)的設(shè)計(jì)與仿真DESIGN AND SIMULATION OF SWEET POTATO HARVESTER學(xué)生姓名班 級(jí)學(xué) 號(hào)學(xué)院名稱專業(yè)名稱指導(dǎo)教師 年5月30日目 錄畢業(yè)設(shè)計(jì)（論文）課題申報(bào)表1畢 業(yè) 設(shè) 計(jì)（論 文） 任 務(wù) 書 2畢業(yè)設(shè)計(jì)（論文）開題報(bào)告5畢業(yè)設(shè)計(jì)（論文）指導(dǎo)手冊(cè)10學(xué)生畢業(yè)設(shè)計(jì)（論文）中期匯報(bào)表15學(xué)生畢業(yè)設(shè)計(jì)（論文）中期情況檢查表16畢業(yè)設(shè)計(jì)（論文）指導(dǎo)教師評(píng)閱表17畢業(yè)設(shè)計(jì)（論文）評(píng)閱教師評(píng)閱表18畢業(yè)設(shè)計(jì)（論文）答辯及綜合成績(jī)?cè)u(píng)定表19外文翻譯20畢業(yè)設(shè)計(jì)（論文）課題申報(bào)表指導(dǎo)教師職稱講師教研室機(jī)械基礎(chǔ)教研室申報(bào)課題名稱紅薯收獲機(jī)的設(shè)計(jì)與仿真課題類型工程設(shè)計(jì)類課題來(lái)源B.社會(huì)生產(chǎn)實(shí)踐課題簡(jiǎn)介傳統(tǒng)的紅薯、土豆等根莖類農(nóng)作物收獲一直是靠人工刨土收獲，這是農(nóng)業(yè)生產(chǎn)領(lǐng)域中一項(xiàng)重體力勞動(dòng)，人工收獲勞動(dòng)強(qiáng)度大，生產(chǎn)效率低。雖然市面上也有一些機(jī)械化收獲設(shè)備，但由于價(jià)格、性能，尤其是收凈率等各方面原因，始終未能大范圍應(yīng)用。課題要求（包括所具備的條件）要求完成紅薯收獲的小型機(jī)械化設(shè)備一臺(tái)，包括動(dòng)力源、傳動(dòng)系統(tǒng)、挖土機(jī)構(gòu)、振動(dòng)篩、薯塊收集等結(jié)構(gòu)，并且要適應(yīng)山區(qū)、丘陵等小地塊作業(yè)要求，并且保證收凈率在95%以上。課題工作量要求1、裝配圖1張；自選零件圖若干，要求圖紙總量不少于2張0號(hào)圖；2、采用proe完成三維建模，并進(jìn)行動(dòng)畫仿真；3、翻譯英文資料5000字； 4、不少于15000字的設(shè)計(jì)說(shuō)明書一份。教研室審定意見 同意教研室主任簽字：學(xué) 院審定意見同意 教學(xué)院長(zhǎng)簽字： 畢 業(yè) 設(shè) 計(jì)（論 文） 任 務(wù) 書 學(xué)院（系）：機(jī)電工程學(xué)院專 業(yè)：機(jī)械設(shè)計(jì)制造及其自動(dòng)化學(xué)生姓名：學(xué) 號(hào)：設(shè)計(jì)(論文)題目：紅薯收獲機(jī)的設(shè)計(jì)與仿真紅薯收獲機(jī)的設(shè)計(jì)與仿真起 迄 日 期:2018年2 月26 日 2018年5 月 26日指 導(dǎo) 教 師:教研室主任: 發(fā)任務(wù)書日期: 年 3 月 4 日 畢 業(yè) 設(shè) 計(jì)（論 文）任 務(wù) 書 1畢業(yè)設(shè)計(jì)的背景：傳統(tǒng)的紅薯、土豆等根莖類農(nóng)作物收獲一直是靠人工刨土收獲，這是農(nóng)業(yè)生產(chǎn)領(lǐng)域中一項(xiàng)重體力勞動(dòng)，人工收獲勞動(dòng)強(qiáng)度大，生產(chǎn)效率低。雖然市面上也有一些機(jī)械化收獲設(shè)備，但由于價(jià)格、性能，尤其是收凈率等各方面原因，始終未能大范圍應(yīng)用。2畢業(yè)設(shè)計(jì)(論文)的內(nèi)容和要求：要求完成紅薯收獲的小型機(jī)械化設(shè)備一臺(tái)，包括動(dòng)力源、傳動(dòng)系統(tǒng)、挖土機(jī)構(gòu)、振動(dòng)篩、薯塊收集等結(jié)構(gòu)，并且要適應(yīng)山區(qū)、丘陵等小地塊作業(yè)要求，并且保證收凈率在95%以上。1、裝配圖1張；自選零件圖若干，要求圖紙總量不少于2張0號(hào)圖；2、采用proe完成三維建模，并進(jìn)行動(dòng)畫仿真；3、翻譯英文資料5000字； 4、不少于15000字的設(shè)計(jì)說(shuō)明書一份。3主要參考文獻(xiàn)：1李建東,楊薇,杜永琪,賈晶霞,李洋.4UL-1型多功能根莖類作物挖掘機(jī)的設(shè)計(jì).農(nóng)業(yè)工程.2015.052甘方地.紅薯種植與機(jī)械化作業(yè).湖南農(nóng)機(jī).2014.013宋龍鎮(zhèn).HX-85A多功能收獲機(jī).農(nóng)村新技術(shù).2015.104雙驅(qū)動(dòng)薯類收獲機(jī)的研發(fā)應(yīng)用.馬世文,黃桂紅.農(nóng)機(jī)質(zhì)量與監(jiān)督.2017.105夏陽(yáng).紅薯機(jī)械化收獲機(jī)具的試驗(yàn)研究.河南農(nóng)業(yè)大學(xué)碩士論文.2009年4畢業(yè)設(shè)計(jì)(論文)進(jìn)度計(jì)劃(以周為單位)：1周：布置畢業(yè)設(shè)計(jì)題目，進(jìn)行畢業(yè)設(shè)計(jì)實(shí)習(xí)。2周：收集相關(guān)資料。完成并提交開題報(bào)告。3周：翻譯英文資料。4-5周：初步構(gòu)設(shè)并確定設(shè)計(jì)方案。完成裝配圖草圖的繪制。6周：計(jì)算確定各零件基本尺寸。7-8周：繪制總裝配圖。9周：編寫設(shè)計(jì)說(shuō)明書。10周：繪制零件圖。11周：修訂初稿。12周：完成答辯。教研室審查意見： 教研室主任簽名： 年 月 日學(xué)院審查意見： 教學(xué)院長(zhǎng)簽名： 年 月 日 畢業(yè)設(shè)計(jì)（論文）開題報(bào)告 課題名稱：紅薯收獲機(jī)的設(shè)計(jì)與仿真學(xué)生姓名：學(xué)號(hào)：指導(dǎo)教師：職稱：講師所在學(xué)院：機(jī)電工程學(xué)院專業(yè)名稱：機(jī)械設(shè)計(jì)制造及其自動(dòng)化 日期：2018 年 3 月 16 日 說(shuō) 明1根據(jù)畢業(yè)設(shè)計(jì)(論文)管理規(guī)定，學(xué)生必須撰寫畢業(yè)設(shè)計(jì)（論文）開題報(bào)告，由指導(dǎo)教師簽署意見、教研室審查，學(xué)院教學(xué)院長(zhǎng)批準(zhǔn)后實(shí)施。2開題報(bào)告是畢業(yè)設(shè)計(jì)（論文）答辯委員會(huì)對(duì)學(xué)生答辯資格審查的依據(jù)材料之一。學(xué)生應(yīng)當(dāng)在畢業(yè)設(shè)計(jì)（論文）工作前期內(nèi)完成，開題報(bào)告不合格者不得參加答辯。3畢業(yè)設(shè)計(jì)開題報(bào)告各項(xiàng)內(nèi)容要實(shí)事求是，逐條認(rèn)真填寫。其中的文字表達(dá)要明確、嚴(yán)謹(jǐn)，語(yǔ)言通順，外來(lái)語(yǔ)要同時(shí)用原文和中文表達(dá)。第一次出現(xiàn)縮寫詞，須注出全稱。4本報(bào)告中，由學(xué)生本人撰寫的對(duì)課題和研究工作的分析及描述，沒(méi)有經(jīng)過(guò)整理歸納，缺乏個(gè)人見解僅僅從網(wǎng)上下載材料拼湊而成的開題報(bào)告按不合格論。 5課題類型填：工程設(shè)計(jì)類；理論研究類；應(yīng)用（實(shí)驗(yàn)）研究類；軟件設(shè)計(jì)類；其它。6課題來(lái)源填：教師科研；社會(huì)生產(chǎn)實(shí)踐；教學(xué)；其它 畢業(yè)設(shè)計(jì)（論文）開題報(bào)告課題名稱 紅薯收獲機(jī)的設(shè)計(jì)與仿真課題來(lái)源B.社會(huì)生產(chǎn)實(shí)踐課題類型工程設(shè)計(jì)類1選題的背景及意義：傳統(tǒng)的紅薯、土豆等根莖類農(nóng)作物收獲一直是靠人工刨土收獲，這是農(nóng)業(yè)生產(chǎn)領(lǐng)域中一項(xiàng)重體力勞動(dòng)，人工收獲勞動(dòng)強(qiáng)度大，生產(chǎn)效率低。雖然市面上也有一些機(jī)械化收獲設(shè)備，但由于價(jià)格、性能，尤其是收凈率等各方面原因，始終未能大范圍應(yīng)用。紅薯收獲機(jī)從目前國(guó)際經(jīng)濟(jì)全球化發(fā)展來(lái)看我國(guó)農(nóng)業(yè)機(jī)械方面面臨著嚴(yán)峻考驗(yàn)和新的機(jī)遇。因此為了了解國(guó)內(nèi)紅薯生產(chǎn)機(jī)械化和發(fā)展動(dòng)態(tài)對(duì)于大力發(fā)展，以促進(jìn)我國(guó)紅薯收獲機(jī)對(duì)農(nóng)民財(cái)富收入問(wèn)題展開了針對(duì)性調(diào)查，盡快普及紅薯收獲機(jī)的機(jī)械化創(chuàng)造更多的財(cái)富。 開發(fā)一種能適應(yīng)我國(guó)農(nóng)業(yè)生產(chǎn)體制的紅薯收獲機(jī)及時(shí)在必行這樣有效的降低勞動(dòng)強(qiáng)度，解放了勞動(dòng)生產(chǎn)力使農(nóng)民在有限的時(shí)間內(nèi)創(chuàng)造更多的財(cái)富收入，因此開發(fā)技術(shù)對(duì)于提高紅薯種植效益，降低生產(chǎn)成本增加農(nóng)民財(cái)富收入具有重大的意義。2研究?jī)?nèi)容擬解決的主要問(wèn)題：研究的內(nèi)容:l.紅薯收獲機(jī)的總體方案設(shè)計(jì)。 2.挖掘機(jī)構(gòu)的設(shè)計(jì)與分析計(jì)算。 3.薯士及薯秧分離機(jī)構(gòu)的設(shè)計(jì)與分析計(jì)算。解決的主要問(wèn)題，對(duì)挖掘鏟的要求: l.挖出所有薯塊，盡可能不漏薯(即明薯率高);2.盡可能使進(jìn)入機(jī)器的土壤少; 3.能將掘起的紅薯輸送到分離裝置，并且盡可能細(xì)化土壤，減少負(fù)荷; 挖掘鏟的任務(wù)是在克服各種阻力時(shí)消耗的能量最少的情況下將紅薯挖出。3研究方法技術(shù)路線：畢業(yè)設(shè)計(jì)分為紅薯收獲機(jī)的設(shè)計(jì)與仿真的傳動(dòng)系統(tǒng)、挖土機(jī)構(gòu)、振動(dòng)篩、薯塊收集等結(jié)構(gòu)設(shè)計(jì)，裝配圖和主要零件圖及論文。研究并完成基本傳動(dòng)計(jì)算、帶傳動(dòng)、機(jī)架部分的設(shè)計(jì)，減速器的選擇，聯(lián)軸器的選擇挖掘鏟的設(shè)計(jì)，鏈輪設(shè)計(jì)以及地輪設(shè)計(jì)。 4研究的總體安排和進(jìn)度計(jì)劃：1周：布置畢業(yè)設(shè)計(jì)題目，進(jìn)行畢業(yè)設(shè)計(jì)實(shí)習(xí)。2周：收集相關(guān)資料。完成并提交開題報(bào)告。 3周：翻譯英文資料。 4-5周：初步構(gòu)設(shè)并確定設(shè)計(jì)方案。完成裝配圖草圖的繪制。 6周：計(jì)算確定各零件基本尺寸。 7-8周：繪制總裝配圖。 9周：編寫設(shè)計(jì)說(shuō)明書。 10周：繪制零件圖。 11周：修訂初稿。 12周：完成答辯。5主要參考文獻(xiàn)：1李建東,楊薇,杜永琪,賈晶霞,李洋.4UL-1型多功能根莖類作物挖掘機(jī)的設(shè)計(jì).農(nóng)業(yè)工程.2015.052甘方地.紅薯種植與機(jī)械化作業(yè).湖南農(nóng)機(jī).2014.013宋龍鎮(zhèn).HX-85A多功能收獲機(jī).農(nóng)村新技術(shù).2015.10 4雙驅(qū)動(dòng)薯類收獲機(jī)的研發(fā)應(yīng)用.馬世文,黃桂紅.農(nóng)機(jī)質(zhì)量與監(jiān)督.2017.105夏陽(yáng).紅薯機(jī)械化收獲機(jī)具的試驗(yàn)研究.河南農(nóng)業(yè)大學(xué)碩士論文.2009 6呂金慶.紅薯收獲機(jī)的設(shè)計(jì)M.農(nóng)業(yè)機(jī)械出版社:1576 7上海市大專院校機(jī)械制造工藝學(xué)協(xié)作組.機(jī)械制造工藝學(xué):97125 8農(nóng)業(yè)部農(nóng)機(jī)化技術(shù)開發(fā)推廣總站編.農(nóng)機(jī)化適用新技術(shù)讀本M。兵器工業(yè)出版社,2000:45103 9沈再春.農(nóng)產(chǎn)品機(jī)械與設(shè)備M.農(nóng)業(yè)出版社,1993:1266 10李自華.農(nóng)業(yè)機(jī)械學(xué)M.農(nóng)業(yè)出版社:122 11張耀宸主編.機(jī)械加工工藝設(shè)計(jì)手冊(cè)M.航空業(yè)出版社，1987；102180 12戴曙.金屬切削機(jī)床M.北京：機(jī)械工業(yè)出版社，2001：6584 13濮良貴，紀(jì)名剛.機(jī)械設(shè)計(jì)（第七版）M.高等教育出版社7799 14劉鴻文.材料力學(xué)M.北京：高等教育出版社,6688 15中國(guó)機(jī)械工程學(xué)會(huì).中國(guó)機(jī)械設(shè)計(jì)大典M.南昌:江西科學(xué)技術(shù)出版社，2002：903912 16崔洪斌，方憶湘，張嘉任等.計(jì)算機(jī)輔助設(shè)計(jì)基礎(chǔ)及應(yīng)用M.北京:清華大學(xué)出版社，2002:7188指導(dǎo)教師意見：對(duì)“文獻(xiàn)綜述”的評(píng)語(yǔ)：文獻(xiàn)查閱完整，兼顧中文與外文文獻(xiàn)，能夠滿足設(shè)計(jì)基本需求。 對(duì)總體安排和進(jìn)度計(jì)劃的評(píng)語(yǔ)：研究的總體安排和進(jìn)度計(jì)劃合理，同意開題。 指導(dǎo)教師簽名： 年 月 日教研室意見： 通過(guò)，同意開題 教研室主任簽名： 年 月 日學(xué)院意見： 教學(xué)院長(zhǎng)簽名： 年 月 日畢業(yè)設(shè)計(jì)（論文）指導(dǎo)手冊(cè)設(shè)計(jì)（論文）題目： 紅薯收獲機(jī)的設(shè)計(jì)與仿真 學(xué)生姓名 學(xué)號(hào) 年 級(jí) 專業(yè)（全稱）機(jī)械設(shè)計(jì)制造及其自動(dòng)化指導(dǎo)教師 所在學(xué)院 機(jī)電工程學(xué)院 畢業(yè)設(shè)計(jì)（論文）指導(dǎo)記錄第一次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日第二次指導(dǎo)記錄：指導(dǎo)地點(diǎn) 年 月 日第三次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日第四次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日 第五次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日第六次指導(dǎo)記錄：指導(dǎo)地點(diǎn) 年 月 日第七次指導(dǎo)記錄：指導(dǎo)地點(diǎn) 年 月 日第八次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日 第九次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日 第十次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日 第十一次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日 第十二次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日 第十三次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日 第十四次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日 第十五次指導(dǎo)記錄： 指導(dǎo)地點(diǎn) 年 月 日 學(xué)生畢業(yè)設(shè)計(jì)（論文）中期匯報(bào)表學(xué)生姓名專 業(yè)機(jī)械設(shè)計(jì)制造及其自動(dòng)化學(xué) 號(hào)設(shè)計(jì)（論文）題目紅薯收獲機(jī)的設(shè)計(jì)與仿真畢業(yè)設(shè)計(jì)（論文）前期工作小結(jié)現(xiàn)已完成的：1.根據(jù)課題收集并查閱了相關(guān)資料，對(duì)所需知識(shí)進(jìn)行了復(fù)習(xí)。2.完成了開題報(bào)告。3.查找了相關(guān)的外文文獻(xiàn)并進(jìn)行了翻譯。4.在劉老師的指導(dǎo)下完成了對(duì)紅薯收獲機(jī)的設(shè)計(jì)計(jì)算。主要的問(wèn)題：1.論文的大綱有些不完善并沒(méi)有針對(duì)性。2.對(duì)圖紙的繪制思路不夠明晰，還需繼續(xù)細(xì)化。3. 對(duì)于三維軟件的使用也不是很得心應(yīng)手。在繪制二維圖時(shí)，對(duì)一些制圖標(biāo)準(zhǔn)也很模糊。4.對(duì)一些知識(shí)掌握程度不足，不能較靈活的運(yùn)用以掌握的知識(shí)，需多向老師請(qǐng)教。下階段工作：根據(jù)目前檢查的結(jié)果，我將在后期對(duì)論文的每個(gè)章節(jié)進(jìn)行細(xì)化，對(duì)內(nèi)容做進(jìn)一步的修改，對(duì)專題研究部分進(jìn)行深入的研究。配合論文對(duì)圖紙進(jìn)行繪制，修改圖紙格式，同時(shí)找老師幫忙檢查論文與圖紙上的不足并修改，保證論文與圖紙質(zhì)量的條件下完成畢設(shè)終稿，制作畢設(shè)論文副本與答辯PPT，準(zhǔn)備參加畢業(yè)答辯。指導(dǎo)教師意見同學(xué)的設(shè)計(jì)按照設(shè)計(jì)進(jìn)度以及設(shè)計(jì)工作量的要求完成了預(yù)定的設(shè)計(jì)任務(wù)，情況屬實(shí)！簽名： 年 月 日學(xué)生畢業(yè)設(shè)計(jì)（論文）中期情況檢查表 學(xué)院名稱：機(jī)電工程學(xué)院 檢查日期：2018年 4 月 24 日學(xué)生姓名專 業(yè)機(jī)械設(shè)計(jì)制造及其自動(dòng)化指導(dǎo)教師設(shè)計(jì)（論文）題目紅薯收獲機(jī)的設(shè)計(jì)與仿真工作進(jìn)度情況基本按照設(shè)計(jì)進(jìn)度要求完成了預(yù)定的設(shè)計(jì)任務(wù)。 是否符合任務(wù)書要求進(jìn)度是 能否按期完成任務(wù)能 工作態(tài)度情況(態(tài)度、紀(jì)律、出勤、主動(dòng)接受指導(dǎo)等)工作態(tài)度較端正，出勤情況稍差，與指導(dǎo)老師的溝通偏少！主動(dòng)性稍差！ 質(zhì)量評(píng)價(jià)(針對(duì)已完成的部分)對(duì)紅薯收獲的背景及現(xiàn)狀有了基礎(chǔ)性的認(rèn)識(shí)，具體技術(shù)細(xì)節(jié)還有待進(jìn)一步完善。 存在問(wèn)題和解決辦法設(shè)計(jì)計(jì)算過(guò)程要詳盡，制圖還需進(jìn)一步規(guī)范 檢查人簽名 教學(xué)院長(zhǎng)簽名 畢業(yè)設(shè)計(jì)（論文）指導(dǎo)教師評(píng)閱表學(xué)院：機(jī)電工程學(xué)院 專業(yè)：機(jī)械設(shè)計(jì)制造及其自動(dòng)化 學(xué)生： 學(xué)號(hào)： 題目： 紅薯收獲機(jī)的設(shè)計(jì)與仿真 評(píng)價(jià)項(xiàng)目評(píng)價(jià)要素成績(jī)?cè)u(píng)定優(yōu)良中及格不及格工作態(tài)度工作態(tài)度認(rèn)真，按時(shí)出勤能按規(guī)定進(jìn)度完成設(shè)計(jì)任務(wù)選題質(zhì)量選題方向和范圍選題難易度選題理論意義和實(shí)際應(yīng)用價(jià)值能力水平查閱和應(yīng)用文獻(xiàn)資料能力綜合運(yùn)用知識(shí)能力研究方法與手段實(shí)驗(yàn)技能和實(shí)踐能力創(chuàng)新意識(shí)設(shè)計(jì)論文質(zhì)量?jī)?nèi)容與寫作結(jié)構(gòu)與水平規(guī)范化程度成果與成效指導(dǎo)教師意見建議成績(jī)是否同意參加答辯評(píng)語(yǔ)： 指導(dǎo)教師簽名：年 月 日 畢業(yè)設(shè)計(jì)（論文）評(píng)閱教師評(píng)閱表學(xué)院：機(jī)電工程學(xué)院 專業(yè)：機(jī)械設(shè)計(jì)制造及其自動(dòng)化 學(xué)生： 學(xué)號(hào)：題目： 紅薯收獲機(jī)的設(shè)計(jì)與仿真 評(píng)價(jià)項(xiàng)目評(píng)價(jià)要素成績(jī)?cè)u(píng)定優(yōu)良中及格不及格選題質(zhì)量選題方向和范圍選題難易度選題理論意義和實(shí)際應(yīng)用價(jià)值能力水平查閱和應(yīng)用文獻(xiàn)資料能力綜合運(yùn)用知識(shí)能力研究方法與手段實(shí)驗(yàn)技能和實(shí)踐能力創(chuàng)新意識(shí)設(shè)計(jì)論文質(zhì)量?jī)?nèi)容與寫作結(jié)構(gòu)與水平規(guī)范化程度成果與成效評(píng)閱教師意見建議成績(jī) 是否同意參加答辯 評(píng)語(yǔ)： 評(píng)閱教師簽名：年 月 日 畢業(yè)設(shè)計(jì)（論文）答辯及綜合成績(jī)?cè)u(píng)定表學(xué) 院機(jī)電工程學(xué)院 專 業(yè)機(jī)械設(shè)計(jì)制造及其自動(dòng)化 學(xué)生姓名 學(xué) 號(hào) 指導(dǎo)教師 設(shè)計(jì)論文題 目紅薯收獲機(jī)的設(shè)計(jì)與仿真 答辯時(shí)間 年 月 日 時(shí) 分至 時(shí) 分答辯地點(diǎn)敬本樓C502 答辯小組成 員姓名陸興華秦錄芳楊麗娟馬西良黃傳輝職稱副教授副教授副教授副教授教授答辯記錄提問(wèn)人提問(wèn)主要內(nèi)容學(xué)生回答摘要 答辯記錄人簽名：答辯小組意見答辯評(píng)語(yǔ)： 答辯成績(jī)： 答辯小組組長(zhǎng)簽名：綜合成績(jī)?cè)u(píng)定指導(dǎo)教師評(píng)定成績(jī)?cè)u(píng)閱教師評(píng)定成績(jī)答辯成績(jī)綜合評(píng)定成績(jī)答辯委員會(huì)主任簽名： 年 月 日 畢業(yè)設(shè)計(jì)（論文）外文翻譯學(xué)生姓名班 級(jí) 14機(jī)械單學(xué) 號(hào)學(xué)院名稱 機(jī)電工程學(xué)院專業(yè)名稱機(jī)械設(shè)計(jì)制造及其自動(dòng)化指導(dǎo)教師 年5月26日Characterization of the genetic diversity of Ugandas sweet potato (Ipomoea batatas) germplasm using microsatellites markersBarbara M. Zawedde Marc Ghislain Eric Magembe Geovani B. Amaro Rebecca Grumet Jim HancockReceived: 7 April 2014/Accepted: 1 September 2014/Published online: 17September 2014 Springer Science+Business Media Dordrecht 2014Abstract Knowledge about the genetic diversity and structure of crop cultivars can help make better conservation decisions, and guide crop improvement efforts. Diversity analysis using microsatellite markers was performed to assess the level of genetic diversity in sweet potato in Uganda, and evaluate the genetic relationship between the Ugandas germplasm and some genotypes obtained from Kenya, Tanzania, Ghana, Brazil and Peru. A total of 260 sweet potato cultivarswerecharacterizedusing93microsatelliteloci. The Ugandan collection showed a large number ofDistinct genetic diversitybetweengenotypesobtainedfromthedifferent agro-ecological zones. There was low (6 %) levels of genetic diversity observed between the East African genotypes; however unique alleles were present in collections from the various sources. Pairwise comparisons germplasmwassignicantlydifferent(P0.001)from cultivars from Tanzania, Ghana, Brazil and Peru. The presence of unique alleles in populations from various Ugandas agro-ecological zones and suggestthateffortsshouldbemadetofurthercollectand characterize the germplasm in more depth.Keywords Characterization Crop breeding Ipomoea batatas Molecular markers SSRA germplasm collection of crop cultivars with varying environmental adaptive capacity can be both a source of genes for future crop improvement, as well as a critical resource for farmers. The highest levels of genetic diversity for the majority of the important global food crops is in the South, where crop centers of origins are commonly found, and centers of diversity emerged due to prolonged periods of farmer selection (FAO 2008).B. M. Zawedde R. Grumet J. Hancock (&) Graduate Program in Plant Breeding, Genetics and Biotechnology, Michigan State University, Plant and Soil Science Building, 1066 Bogue Street, East Lansing, MI 48824, USA e-mail: hancockmsu.eduB. M. Zawedde e-mail: zaweddemsu.eduPresent Address: B. M. Zawedde Uganda Biosciences Information Center (UBIC), National Crop Resources Research Institute, 27 km Kampala Zirobwe Road, Namulonge, Kampala, UgandaM. Ghislain E. Magembe CIP Sub-Saharan Africa, International Potato Center, P.O. Box 25171, Nairobi, KenyaG. B. Amaro Embrapa Vegetable Crops, P.O. Box 218, Bras lia, DF CEP 70359-970, Brazil Sweet potato, Ipomoea batatas (L.) Lam., is the fth most important food crop in terms of weight harvested in Eastern Africa (FAO 2012). Sweet potato was introduced to the East African borders from South America by Portuguese explorers during the 16th century (Zhang et al. 2004). The oldest remains of sweet potato have been found in the caves of the Chilca Canyon in Peru and dated as 8,000 years old (Lebot 2010). However, based on morphological relationships among related species, the center of origin appears to be between the Yucatan Peninsula in Mexico and the Orinoco River in Venezuela (Austin 1977). It is also in that region that the wild species of the section Batatas, considered as putative ancestors and wild relatives of the cultivated sweet potato, are found (Andersson and de Vicente 2010). Evaluations of genetic diversity patterns among germplasm from different parts of the world have resulted in the suggestion that China, Southeast Asia, New Guinea and East Africa are secondary centers of diversity (Yen 1982; Austin 1983). Uganda has the highest production per capita in Sub-Saharan Africa and numerous, diverse sweet potato landraces are grown. In 2005, the national sweet potato program collected over 1,300 landraces, which were characterized using morphological methodologies to determine the level of genetic diversity and 946 of these were found to be morphologically distinct genotypes (Yada et al. 2010a). This high level of diversity can be attributed primarily to the allogamous and hexaploidy nature of sweet potato (Lebot 2010), as well as variations in farmers preferences (Veasey et al. 2008). The method of propagation by vine cuttings contributes also indirectly by maintaining cultivar diversity. Knowledge about the genetic diversity and structure of existing crop cultivars can aid in making better conservation decisions, and help direct breeding programs. Characterization of crop diversity can be achieved through morphological and molecular tools. Morphological characterization is an important rst step in assessment of diversity; however there are major limitations in relying only on morphological characterization including low levels of polymorphism, low repeatability, late expression for certain traits; phenotypic plasticity and parallel evolution (Karuri et al. 2010; Yada et al. 2010b). A number of molecular markers including random amplied polymorphic DNAs (RAPDs), restriction fragment lengthgenetic diversity for each population included number of polymorphic loci (P), percentage of polymorphic loci (%P) and Neis (1973) gene diversity (D), estimated from binary data using GenAlex 6.4 (Peakall and Smouse 2006). Analysisofmolecularvariance(AMOVA)was also performed using GenAlEx version 6.4 to estimate the total variance and distribution of diversity within and between populations. Wrights F-Statistic (FST, xation index) was also computed, using GenAlEx software, to estimate the amount of genetic variance that can be explained by population structure (Holsinger and Bruce 2009). Fixation index; FST HT HI HTwhere HI is the mean observed heterozygosity per individual within subpopulations and HT is the expected heterozygosity in a random mating total population. FST can range from 0.0 (no differentiation) to 1.0 (complete differentiation, that is, subpopulations xed for different alleles). The phylogenetic relationship among populations was assessed using DARwin version 5 (Perrier and Jacquemoud-Collet 2006). Similarity matrices were constructed from the binary data with Jaccards coefcients (Jaccard 1908). Jaccards coefcient = Nab/(Na ? Nb), where Nab is the number of alleles shared by two individuals a and b, Na is total number of alleles in sample a, and Nb is total number of alleles in sample b. Genetic distances between populations were obtained by computing the usual Euclidian distance matrix based on haplotype frequencies. From this matrix, a dendrogram was constructed using the neighbor joining method (NJ) from Saitou and Nei (1987). The signicance of each node was evaluated by bootstrappingdataovera locusfor 5,000 replications of the original matrix. We examined hierarchical genetic variation between individuals using the un-weighted pair group method analysis (UPGMA), as suggested by Sneath and Sokal (1973). Clustering patterns of individuals and populations were examined using STRUCTURE version 2.3.3 (Pritchard et al. 2000), which is reported to have the capability to generate population structuring (Pritchard et al. 2009). Using the allele dosage (MAC-PR) data for each individual, individuals were assigned probabilistically to genetic clusters (K). The STRUCTURE program was run using no prior assumptions of population structure withan admixture ancestrymodel and the recommended methods for recessive alleles, and allele frequencies correlated. The analysis was used to determine whether biologically relevant clusters could be determined among the plants sampled, and establish the proportion of an individuals genome (Q) that originated from each cluster. For all analyses, the Markov chain Monte Carlo (MCMC) parameters were set to a burn-in period of 50,000 with 50,000 iterations. The optimum K, indicating the number of true clusters in the data, was determined from 20 replicate runs for each value of K (K set to 10) using the method described by Evanno et al. (2005) and the adhocQuantityDeltaK,based ontherateofchangein the log probability of the data between successive K values. Parameters of the method of Evanno et al. (2005) were calculated using the program Structure Harvester version 0.6.92 (Earl and vonHoldt 2012). Similarity among different runs was calculated by the method of Jakobsson and Rosenberg (2007) as used in their computer program CLUMPP 1.1.2. This method calculates a similarity coefcient h0, which allows the assessment of the similarity of individual runs of the program STRUCTURE. The optimal alignment of 20 replicates of K values was determined using the computer program CLUMPP 1.1.2 (Jakobsson and Rosenberg 2007) and clusters were visualized using the program DISTRUCT 1.1 (Rosenberg 2004).ResultsSSR markers amplicationA total of 107 alleles were scored for the 19 SSR markers (Table 2). The number of alleles per locus ranged from 3 to 9. Three markers had very low PIC; IB-S07(0.22),JB1809(0.19)andIBSSR09(0.31) thus were excluded from further analyses.Determining relatedness between cultivars in UgandaA total of 10 newly improved cultivars released by the national program were compared with 158 Ugandan landraces. The unweighted neighbor joining (NJ) algorithm cluster analysis generated numerous clusters (Fig. 1). Improved cultivars were scattered into many of these clusters together with landraces. Noteworthy (6/10) improved cultivars were grouped together with a Kenyan cultivar Kakamega, which was purposely included in this analysis because it is a known maternal parent for many of these improved cultivars.Genetic relationship between genotypes from Ugandas agro-ecological zones and cultivars collected from other East African countriesAnalysisofMolecularVariance(AMOVA)indicatedthatonly6 %ofthegeneticvariationwasexplainedby differences among the sources (Table 3). Analysis of the sixteen microsatellites yielded a total of 93 presumptive loci in the 228-sweet potato genotypes from the eight predened populations (Table 4). An average of 70 polymorphic loci was observed in each population. The level of genetic diversity variedamong the different populations. Most regions in Uganda had populations with few unique alleles (14), except the south-western region, which had none. Tanzanian cultivars also had few unique alleles (4), but had the highest level of heterozygosity (D). Overall the level of heterozygosity (D) for the collected samples was low. The signicant difference between the cultivars from Tanzania and the populations from Uganda and Kenya is clearly shown in the genetic distance matrix (Fig. 2).Genetic relationship between Ugandan genotypes and cultivars collected from elsewhereAnalysis of Molecular Variance (AMOVA) indicated that only 24 % of the genetic variation was explained by differences among the countries (Table 5). Pairwise comparisons of genetic differe