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研究生:杰包伯
研究生(外文):Robert Israel Jere
論文名稱:馬拉威Rumphi和Mzimba地區小規模吳郭魚養殖之經濟分析
論文名稱(外文):An Economic Analysis of Small Scale Tilapia Farming in Rumphi and Mzimba Districts in Malawi.
指導教授:繆峽繆峽引用關係
指導教授(外文):Sha, Miao
學位類別:碩士
校院名稱:國立臺灣海洋大學
系所名稱:水產養殖學系
學門:農業科學學門
學類:漁業學類
論文種類:學術論文
畢業學年度:94
語文別:英文
論文頁數:127
中文關鍵詞:小型養殖吳郭魚馬拉威生產力效益
外文關鍵詞:Small scale farmingTilapiaMalawiproductivityprofitability
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摘 要
馬拉威小規模水產養殖經濟吳郭魚分析於2005年9月完成。此分析包含四項變異, 有種苗成本、飼料成本、池塘建造成本、和肥料成本。針對Nchenachena、 Mphompha (Rumphi District) 和 Mapila 、Chizani/Kabiza、 Mankhangala (Inkosi Khosolo Jere, Mzimba District)
的養殖戶做隨機的資料收集。
藉多變量分析, 使得資料分析上更趨周全, 並減少常態下造成微小偏差的敏感度。區隔函數分析能將資料分為兩大項; 放養密度、
總產出(TPP)、總收入(TR)、淨收益(NR), 和根據 種苗、飼料、池塘建造、肥料成本所得到的成本效益。典型相關分析則在探討成本效益變異和物理變異量二者間的關連性。
馬氏距離指出不同地區間的產量、放養密度、成本效益各方面的差異性。在Nchenachena 的產量上相較於其他地區(包含Mphompha)有顯著差異(α<0.0001)。另一方面Mzimba的各地區間無顯著差異。
然而, 在產量方面, 尤其總產出(TPP)在之前的論文都顯示, 此五地區的產量都偏低(>900kg/ha/yr)。
結果顯示在Mphompha 的種苗成本效益, 影響著TPP、TR、NR的物理變異, 而Chizani、Mankhangala的池塘建造成本是較重要的變異量。
Abstract
An economic analysis on small scale Tilapia (Oreochromis shiranus) farming in Malawi was carried out in September 2005. Information on four important input cost variables of seed, feed, initial capital required for pond construction, and Manure/fertilizer costs was collected from randomly selected farmers of Nchenachena, Mphompha (Rumphi District) and Mapila, Chizani/Kabiza Mankhangala (Inkosi Khosolo Jere, Mzimba District).
A multivariate statistical approach to data analysis was applied as it is considered robust enough to be insensitive to minor deviations in normality. Canonical discriminant functions were able to separate data into two distinct categories: the physical quantifiable variables of stocking density, total physical product (TPP), total revenue (TR) and net revenue (NR) and the input efficiency use based on the input costs of seed, feed, initial capital and manure/fertilizer used. A canonical correlation analysis was later used to investigate the relationship between these two groups of variables: input use efficiency variables and the quantifiable physical variables.
Mahalanobis squared distances helped to show the differences that existed between the different locations in terms of both production, stocking densities and the input use efficiencies. Production in Nchenachena was significantly different from all the other locations including that of Mphompha (α<0.0001). On the other hand results for locations in Mzimba were not significantly different from each other.
However, production levels, especially TPP in all the five locations studied showed to be quite low although within the range reported previously by other authors (>900kg/ha/yr).
Input use efficiency for seed showed a better influence to physical variables TPP, TR, NR in Mphompha, where as initial capital was an important variable in Chizani and Mankhangala.
Key words: Small scale fish farming, Malawi, productivity, profitability.
CONTENTS
Dedication………………………………………………………………….....i
Acknowledgement……………………………………………….…………...ii
Chinese abstract………………………………………………………...……iv
English abstract………………………………………………………...…….v
Acronyms……………………………………… ……………… …….…....vii
Contents……………………………………………………………………...ix
List of tables……………………………………………………………....xii
List of figures……………………………………………………………xvii
1.INTRODUCTION……………………………………………...………...1
1.1 Importance of aquaculture…………………………………………1
1.2 Fish farming history in Malawi….…………………………..…….3
1.3 Role of development projects in Malawi……………………….….6 1.4.Marketing…………………………………………………………..8
1.5 Impact indicators………………………………….......……….......8
1.6 Description of the study area…………………… …………….......9
1.6.1 Rumphi District……………………………...………….....10
1.6.1.1 Phoka Hills…………………………………………..11
1.6.1.2 Viphya North in Rumphi District………...……........11
1.6.2 South East Mzimba (Khosolo)…………………………..…12
1.7 Fish species farmed………………………………………...……...14
1.7.1 General biology………………………………………...…...14
1.8 Small scale fish farmers in Malawi………………………………..15
2. OBJECTIVES………………………………………………………...….17
3. MATERIALS AND METHODS…………………………………....…...19
3.1 Social structure of respondents…………………………………….20
3.2 Multivariate statistical analysis……………………………...…….21
3.3 The Cobb Douglas production function……………………………22
4. RESULTS…………………………………………………………...…..23
4.1 Canonical discriminant function analysis …………………………23
4.2 Canonical correlation analysis for productivity……………...……27
4.2.1 Rumphi District………………………………………...…...27
4.2.1.1 Nchenachena……………………………………...….27
4.2.1.2 Mphompha………………………………………...…31
4.2.2 Mzimba District……………………………………….........33
4.2.2.1 Mapila……………………………………………......33
4.2.2.2 Chizani/Kabiza…………………………………........36
4.2.2.3 Mankhangala………………………………………...37
4.3 Canonical correlation analysis for profitability………………..….38
4.3.1 Rumphi District…………………………………………......38
4.3.1.1 Nchenachena………………………………………....38
4.3.1.2 Mphompha………………………………………...…39
4.3.2 Mzimba District……………………………………….........41
4.3.2.1 Mapila..........................................................................41
4.3.2.2 Chizani/Kabiza.............................................................43
4.3.2.3 Mankhangala................................................................44
4.4 Production function analysis………………………………………45
5. DISCUSSION………………………………………………………...….46
6. CONCLUSION…………………………………………………………..50
7. REFERENCES…………………………………………………………...53
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