利用農藝性狀評估糯稻種原之遺傳歧異性Genetic Diversity Evaluation for Glutinous Rice Germplasm Based on Agronomic Traits

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(1)ፓРߴ‫ن‬ਞ‫ݏ‬ϟः‫ف‬. 11. ւңၼ᛻‫ޒܓ‬ຠզ᝴ጎᆎ঩ϟᒹ༉‫ݣ‬౵‫ܓ‬ ຫᄭঊ Ε‫ޕ‬९ު Ε႓༡ୠ Ε១ጜ۹ Εࣥႉ壂 1. 2. 3. 1. ୾ҴᇄᢋτᏱၼ᛻Ᏹ‫ق‬ ՘࢈ଲၼཿ‫ې‬সཽၼཿၑᡜ‫ܛ‬ၼ᛻ಣ ՘࢈ଲၼཿ‫ې‬সཽ୞ෛ‫ޑ‬٪࣬ᔯ࣬‫׌‬. 1. *. 1. 2 3. ᄣ्. зࣩ᝴ጎϟः‫ࣦف‬ЎȂйᇄᢋ᝴ጎϟ‫ي‬ ᆎᐤѭ‫ܗ‬೤ዂְሊϛІ ጎ‫ުܗ‬ጎȂЏ‫ڐ‬Ӷ ᝴ጎᆎ঩ϟຠզІւңР८ۧࡠђ஽Ȅ࣐௥ ଇ᝴ጎᆎ঩ϟᒹ༉‫ݣ‬౵‫ܓ‬ȂҐः‫ف‬пᇕ໲Ս ঐ୾ঢ়‫ ޠ‬ঐ᝴ጎ єࢃ ঐު᝴ȃ ঐ ᝴І ঐഛ᝴ ࠣᆎᇅ ঐߩ᝴ጎ Ȟᄈྲࠣᆎȟ࣐؆ਠȂܼ ԒΚ෉ІΡ ෉ձӶᇄϜӵୣ።ࢦ ঐ፵‫ޒܓޠ‬І ঐ ኶໕‫ޒܓ‬Ȅၦਠϸ‫ݚ‬๗‫ึݏ‬౫Ȃ ঐ኶໕‫ܓ‬ ‫ޒ‬Ӷ‫෉ڎ‬ձ໣ϟৰ౵ࣲႁ྄ᡘ຀ЬྦȂйഌ ϸ‫ޒܓ‬໣Ӷ‫෉ڎ‬ձϟࣻᜱᡘ຀‫ܓ‬ᔯۢ๗‫ݏ‬ ϛΚयȄпၼ᛻‫ໍޒܓ‬՘‫ݣ‬౵‫ܓ‬ϸထϸ‫ݚ‬๗ ‫ݏ‬ȂӶ‫෉ڎ‬ձְณ݃ᡘτϸထя౫ȂҼณ‫ݳ‬ ୣϸ ᝴ȃު᝴Іഛ᝴ጎᆎ঩Ȅկ࢑‫ٿ‬Սࣻ Ӥ୾ঢ়‫ޠ‬ᆎ঩ࠍԥ໲Ϝܼϊထϟᗎ༗Ȅၼ᛻ ‫ޒܓ‬ϟлԚϸϸ‫ݚ‬๗‫ݏ‬ᡘұȂ‫ܛ‬።ࢦϟ኶໕ ‫ޒܓ‬ၷ፵‫ڏޒܓޠ‬ԥၷ‫ٺ‬ϟᆎ঩ୣϸਞ ‫ݏ‬Ȃ‫ڐ‬Ϝੂାᇅဩߞ‫ޒܓڎ‬ӶಒΚ෉ձӔѠ ၍ម ᡑ౵ȂӶಒΡ෉ձӔѠ၍ម ᡑ౵Ȃ‫ٸ‬ԫ‫ޒܓڎ‬Ѡ஡ ᝴Іު᝴ᆎ ঩ϸထȂՅު᝴ጎၷ ᝴ጎᆎ঩ԥၷτϟᒹ 10. 135. 53. 28. (. 64. ). 5. 2000. 27. 7. 7. 87.5%. 90.7%. ೾߭ձ޲ , [email protected] ‫׺‬ጉС෉Ȉ 2003 Ԓ 10 У 1 С ௦‫ڨ‬С෉Ȉ 2004 Ԓ 9 У 6 С ձ‫ޑ‬ȃᕘძᇅҢ‫ޑ‬ၦଊ 2:11-30 (2005) *. Crop, Environment & Bioinformatics 2:11-30 (2005) 189 Chung-Cheng Rd., Wufeng, Taichung Hsien 41301, Taiwan (ROC). ༉‫ݣ‬౵‫ܓ‬Ȃկ࢑ഛ᝴ጎࠍϸයܼު᝴І ᝴ ጎᆎ঩ထϟϜȄ ᜱᗥມȋᒹ༉‫ݣ‬౵‫ܓ‬ȃ᝴ጎȃᆎ঩Ȅ Genetic Diversity Evaluation for Glutinous Rice Germplasm Based on Agronomic Traits Yuan-Jan. Chen 1 ,. Huei-Jiuan Huang 3 , and Shun-Fu Lin 1 * 1. 2. 3. Charng-Pei Jen-You. Li 2 ,. Jian 1. Department of Agronomy, National Taiwan University, Taipei 106, Taiwan (ROC) Agronomy Division, Taiwan Agricultural Research Institue, Taichung Hsien 413, Taiwan (ROC) Bureau of Animal and Plant Health Inspection and Quarantine, Council of Agriculture, Taipei 100, Taiwan (ROC). ABSTRACT There have been very few researches on glutinous rices in all over the world. In contrast to indica or japonica type, the breeding history and activities of glutinous rices are far behind in Taiwan. Studies specifically focus on the evaluation and utilization of germplasm for glutinous rices are necessary. To evaluate the genetic diversity of glutinous rice germplasm, 135 glutinous rices (including 64 indica, 53 japonica and 28 upland types) collected from 10 countries and 5 non-glutinous varieties were used in this study. Twenty-seven qualitative and 7 quantitative traits were investigated at Taichung, Taiwan during the first and second cropping.

(2) 12. Crop, Environment & Bioinformatics, Vol. 2, March 2005. seasons of 2000. There were significant differences between two cropping seasons in the investigated quantitative traits. However, in corresponding comparison with the significant test results of correlation between traits in different years, some inconsistent results were found. No distinct group was identified from clustering analysis based on agronomic traits, and 3 types of glutinous germplasm were unable to be differentiated. The germplasm originated from different countries were separately gathered in a few small groups. The quantitative traits had better categorization effectiveness than qualitative traits in principal component analysis (PCA). Different subspecies of glutinous germplasm were separated by using culm length and leaf length as decisive factors, which accounted for 87.5% and 90.7% variation in the first and second cropping seasons, respectively. Compared to japonica type germplasm, the indica type had wider genetic diversity. And the upland glutinous germplasms were distributed diversely in japonica or indica group. Genetic diversity, Glutinous rice, Germplasm. Key words:. ࠊّ. ጎ঩࣐ዦழ঩ۗձ‫ޑ‬ȂࡤစҦߞ෉‫਼ޠ‬ ஊІ΢࣐‫ޠ‬ᒶ‫ܧ‬Ȃഃᅛᅌᡑ૗ᎍᔗөᆎϛӤ ੊঑ࠣᆎȂ‫ܛ‬п౫ϭጎϛ༊਼ஊܼዦழȂྤ ழіഌҼԥᎍᔗ‫ࠣޠ‬ᆎȄҭࠊ਼ஊጎєࢃ Oryza sativa І Oryza glaberrima ‫ڎ‬ঐ‫ޑ‬ ᆎȂ‫ࢹٴ‬ӵୣ਼ஊᆎ឵ܼ Oryza sativaȂѠ ϸ࣐ުጎ (indica) ȃ ጎ (japonica) ІЮࠟ ጎ (Javanica)ή᜹ထ (Chang 1976)ȄጎԾ‫ޠ‬ थ‫ٱ‬ϜᐧલҦМᜧᐧલ (amylopectin) І‫ޣ‬ ᜧᐧલ (amylose) ಣԚȂՅߩ᝴‫ޠܓ‬Ծตዤ ࡤϟԾ໼ၷ᝴‫ޠܓ‬Ծ໼ୂᚭȄ᝴ጎ (glutinous rice; waxy rice) ‫ٸ‬ጋಗ‫ޒם‬ୣ ϸȂєࢃ༬᝴ ( ᝴ )Іߞ᝴ (ު᝴ )Ȃ‫ڐ‬थ‫ٱ‬ ϜᐧલτӼҦМᜧᐧલಣԚȂ‫ޣڐ‬ᜧᐧલ֥ ໕ΚૢӶ 1~12%(COA et al. 1987)Ȅ਴ᐄጎ ձ‫ً׾‬Ԓൣ (2000) пІᇄᢋӵୣᙑॶҢ౱. ௒‫ޠם‬ၦਠᡘұȂ 2000 Ԓᇄᢋӵୣ‫ޠ‬Ьጎ ਼ஊ८ᑗङ 32.9 ࿳ϵധȂпΚૢңഋ‫ٿ‬ᇴȂ Ծ࣐ΚૢॶԾȂުԾпᇨձᡏፀᑥȃԾ લȃ‫މ‬໼࣐лȄ᝴ԾϜȂ ᝴Ծпᡷ଩ȃԾ ᑥ࣐ңȂު᝴ԾпΥ᝙๕ȃᆠφ࣐л्ңഋ (COA 1996)Ȅ ൸ᆎ঩ւңՅّȂ‫ي‬ᆎঢ়‫ܛ‬ᜱЗ‫࢑ޠ‬Ԅ եԥਞ౦ӵᑣᒶя‫ܛ‬ሰ‫يޠ‬ᆎ؆ਠȇՅᄈܼ ᆎ঩ᆔ౪޲ՅّȂ‫ܛ‬ᜱЗ‫࢑ࠍޠ‬Ԅեւңഷ စᔽ‫ޠ‬ၦྜ‫ߴٿ‬ԇ೼‫ٳ‬ᆎ঩Ȃ‫ٯ‬ණЁᆎ঩Ԟ ໲‫ߴڸ‬ԇ‫ޠ‬ਞ౦ (Chen et al. 1997)Ȅᆎ঩‫ޠ‬ ߴԇ֊Ӷᆱࡼᡑ౵Ȃ‫ܛ‬пᆱࡼ‫ޑ‬ᆎ‫ޠ‬Ӽኻ‫ܓ‬ ஡Ѡණ‫يٽ‬ᆎঢ়ᄈܼ‫ي‬ᆎ؆ਠαᒶᐆȄः‫ف‬ ᆎ঩ᡑ౵‫ޠ‬Р‫࡟ݳ‬ӼȂ‫ڐ‬Ϝпѵߓ࠯ᄙ੬‫ܓ‬ ‫ޠ‬ᢏᄇ࣐ഷР߰ϟР‫ݳ‬Ȃഷԟೞᔗңܼᆎ঩ ᡑ౵‫ޠ‬።ࢦȄ Holcomb et al. (1977)Ҧᆎ঩ ৳Ϝഈᐡᒶ‫ ڦ‬1,407 ঐ ጎІ 488 ঐުጎᆎ ঩Ȃ‫ٯ‬й።ࢦ 14 ঐ኶໕‫ޒܓ‬І 27 ঐ፵໕‫ܓ‬ ‫ޒ‬Ȃดࡤໍ՘Ӽᡑঅϸ‫ݚ‬Ȃึ౫ުጎᆎ঩ၷ ጎᆎ঩‫ڏ‬ԥၷτϟᒹ༉‫ݣ‬౵Ȅ Mackill and Lei (1997) ።ࢦ 117 ঐ਼ஊጎϟҢ‫ي‬ ෉ȃ҃ᕭࣁΩȃϸ៌኶Іဤဩ‫ޒܓ๊ܓ‬Ȃໍ ՘ᒹ༉‫ݣ‬౵‫ܓ‬ϸ‫ݚ‬Ȃ๗‫֖ݏ‬౫ഀ៊‫ܓ‬ϟϸ ҁȂ‫ڐ‬Ϝዦழϟ ࠯ጎࠣᆎϸҁϮܼྤழϟ ࠯ጎࠣᆎᇅު࠯ጎࠣᆎϟ໣ȂՅϛӤထ໣ ࠍϛܿಡϸȄ ߗԒ‫ٿ‬Ҧܼ DNA ϸφዀᇭኅ‫ހ‬ӵᔗң ܼөᆎҢ‫ޑ‬ᒹ༉ः‫ف‬І‫ي‬ᆎȂηᔗңӶЬጎ ϟᅌϾᇅᒹ༉ၦྜຠզ (Second 1991) Ȅ Zhang et al. (1992) ‫ ٻ‬ң 95 ঐ RFLP. (restriction fragment length polymorphism)ϸφዀᇭϸ‫ ݚ‬12 ঐ indica І 14 ঐ japonica ࠣᆎȂึ౫ indica ࠯ϲϟࠣᆎᡑ ౵ τ ܼ japonica ࠯ ϲ Ȃ ԫ Κ ๗ ‫ ݏ‬ᇅ Holcomb et al. (1977)ϸ‫ݚ‬л्‫ם‬ᄙІҢ౪. ‫ޒܓ‬ϟ๗‫ࣻݏ‬ಓӬȄѫѵпᆺӬሖષഀᚈЇ ᔗ (polymerase chain reaction, PCR)࣐ஆ.

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(6) 14. Crop, Environment & Bioinformatics, Vol. 2, March 2005. Table 1. Codes, names, types and origins of 135 glutinous and 5 non-glutinous rice germplasm. Code Variety. Type glutinous, GW1 Ta-Li-Huang-Chan Indica glutinous, GW2 Shang-Chi-Tsao-Tao Japonica glutinous, GW3 Tsao-Chiu-Ku Japonica glutinous, GW4 Lao-To-Hsu Japonica glutinous, GW5 Chin-Se-No Japonica glutinous, GW6 Hung-No Indica glutinous, GW7 Hung-Ko-No Japonica glutinous, GW8 Yen-No Indica glutinous, GW9 Wu-No-Tao Indica glutinous, GW10 O-Nung No.3 Japonica glutinous, GW11 Shuang-Ton-Chu Indica glutinous, GW12 Chien-Tzu-Chu Indica glutinous, GW13 Mang-Hua-Chu Indica glutinous, GW14 Chih-Chueh-Chu Indica glutinous, GW15 Hung-Chueh-Chu Indica glutinous, GW16 Fan-Tzu-Chu Indica glutinous, GW17 Shuang-Tung-Juan Indica glutinous, GW18 O-Loan-Chu Indica glutinous, GW19 Chu-His-Chu No.1 Indica glutinous, GW20 Hung-Chueh-Chu Indica GW21 Taichung-Hsien-No No.1 glutinous, Indica GW22 Tainung-Hsien-No No.2 glutinous, Indica glutinous, GW23 Tai-Hsien-No No.2 Indica glutinous, GW24 Shichimancheue-No Japonica glutinous, GW25 Hassen-No Japonica glutinous, GW26 Taisheyuo-No Japonica glutinous, GW27 Miro-No-Toku No.1 Indica. Country. Code. China. GW71. China. GW72. China. GW73. China. GW74. China. GW75. China. GW76. China. GW77. China. GW78. China. GW79. China. GW80. Taiwan. GW81. Taiwan. GW82. Taiwan. GW83. Taiwan. GW84. Taiwan. GW85. Taiwan. GW86. Taiwan. GW87. Taiwan. GW88. Taiwan. GW89. Taiwan. GW90. Taiwan. GW91. Taiwan. GW92. Taiwan. GW93. Japan. GW94. Japan. GW95. Japan. GW96. Japan. GW97. Variety. Type glutinous, Pai-Fu-Go-Ya upland glutinous, Pai-Au-Re-Gu upland glutinous, Lu-No-Daw upland glutinous, Hung-Ye-Lu-Daw upland Wan-No-Tao No. 240 glutinous, upland glutinous, Tuan-Li-No upland glutinous, Tan-Yang-No upland glutinous, Chung-Kuo-No No.130 Japonica glutinous, Kagura-Mochi Japonica glutinous, Chien-Nung No.55 Indica glutinous, Pai-Jih-Tung-Chan Indica glutinous, Hung-Chan Indica glutinous, Wu-Chan-Tao Indica Chin-Men-Tou-Men-Wu glutinous, c Indica glutinous, Ju-Ku Indica glutinous, Hsiao-Chia-Ku Indica glutinous, Bai-Ke-Muo Indica glutinous, Ye-Ji-Hwe Indica glutinous, Chen-Chien-Nvo Indica glutinous, Kaksi-Zum-Yo Japonica glutinous, Kang-Lung-Ido Japonica glutinous, Naeng-Do Japonica glutinous, No-In-Do Japonica glutinous, Nockdu Byc Japonica glutinous, Daehwal-Do Japonica glutinous, Do-Li Japonica glutinous, Chilseongbyeo Japonica. Country Taiwan Taiwan Taiwan Taiwan China China China Japan Japan China China China China China China China China China China Korea Korea Korea Korea Korea Korea Korea Korea.

(7) ၼ᛻‫ޒܓ‬ຠզ᝴ጎᆎ঩ᒹ༉‫ݣ‬౵‫ܓ‬ (continued) Code Variety GW28 Kintoki-No GW29 Miyuoshin-No GW30 Kilien-No GW31 Shiasher-No GW32 Kuroo-No No.22 GW33 Aehegomiz-No GW34 Tosou-No GW35 Kirosheta-No GW36 Shiroga-No GW37 Mirozaki-No No.1 GW38 Fujiura-No No.16 GW39 Tokyofhujra-No GW40 Yuronoyuki-No GW41 Roku-U-No No.22 GW42 Kunimiz-No GW43 Gaisen-No GW44 Tainung-No No.8 GW45 Nung-Yu-No No.3 GW46 Nung-Yu-No No.11 GW47 Nung-Yu-No No.13 GW48 Nung-Yu-No No.20 GW49 Nung-Yu-No No.24 GW50 Nung-Yu-No No.25 GW51 Nung-Yu-No No.30 GW52 Nung-Yu-No No.35 GW53 Nung-Yu-No No.54 GW54 Taichung-No No.46 GW55 Hsinchu-No No.4. Type glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica. Country. Code. Variety. Japan. GW98. Suweon 290. Japan. GW99. Rinoldo-Bersoni. Japan. GW100 Kinan-Kuda. Japan. GW101 Lin-Leng. Japan. GW102 Legage-In. Japan. GW103 IR 29. Japan. GW104 Perurufong Nba. Japan. GW105 Inaway. Japan. GW106 IR3941-9-2. Japan. GW107 TD 52. Japan. GW108 KU 81. Japan. GW109 Hawm. Japan. GW110 Ja-Ma-Bau-Jah. Japan. GW111 Ja-No-Nug. Japan. GW112 K-17044. Japan. GW113 K-17054. Taiwan. GW114 K-17049. Taiwan. GW115 K-17057. Taiwan. GW116 India 16. Taiwan. GW117 India 18. Taiwan. GW118 ARC 12886. Taiwan. GW119 Jhum-Paddy 7. Taiwan. GW120 WRC 4. Taiwan. GW121 KU 16. Taiwan. GW122 Land-Bauw. Taiwan. GW123 Umbang-Sampahiring. Taiwan. GW124 Glutinous-Lebonnent. Taiwan. GW125 Khao-Kieng. 15. Type glutinous, Indica glutinous, Indica glutinous, Japonica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Indica glutinous, Japonica glutinous, Indica glutinous, Indica. Country Korea Italy Philippine Philippine Philippine Philippine Philippine Philippine Philippine Thailand Thailand Thailand Thailand Thailand Thailand Thailand Thailand Thailand India India India India India India Indonesia Indonesia U.S.A. Loas.

(8) 16. Crop, Environment & Bioinformatics, Vol. 2, March 2005. (continued) Code Variety GW56 Taichung-No No.70 GW57 Taikeng-No No.1 GW58 Taikeng-No No.3 GW59 Taikeng-No No.5 GW60 Paerizu-Mochi GW61 Tarunatsu-Mochi GW62 Warisan-Mochi No.1 GW63 Warisan-Mochi No.2 GW64 Komapatai GW65 Pagaitsuitaiyaru GW66 Airaromu GW67 Pazumataharu GW68 Nakara No.2 GW69 Nakabo GW70 Ya-A-Bi. Type glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, Japonica glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland glutinous, upland. Country. Code. Taiwan. GW126. Taiwan. GW127. Taiwan. GW128. Taiwan. GW129. Taiwan. GW130. Taiwan. GW131. Taiwan. GW132. Taiwan. GW133. Taiwan. GW134. Taiwan. GW135. Taiwan. GW136. Taiwan. GW137. Taiwan. GW138. Taiwan. GW139. Taiwan. GW140. T=àÄ=#qI =àT=à =àTä[Q=[Q=== ==üÂ=üÂT = ¡=¡

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(13) 1.P. Z[Q]T QFC SAS ¬T CORR Procedure ¢ik"Ö×Q]ïTÂÃÄ m. Variety. Type glutinous, Kap-Nhay Indica glutinous, Mack-Hing-Hoom Indica glutinous, Khao-Kam Indica glutinous, Khao-Chao-Hom Indica glutinous, Khao-Khane Indica glutinous, Khao-Lay-Nhay Indica glutinous, Khao-Nane-Noi Indica glutinous, Houei-Deng Indica glutinous, Khao-Konhdam Indica glutinous, Pheip Indica non-glutino Tainung No.67 us, Japonica non-glutino Taichung No.65 us, Japonica non-glutino Taikeng No.9 us, Japonica Taichung-Shien No.10 non-glutino us, Indica Tai-Chung-Native No. 1 non-glutino us, Indica. Country Loas Loas Loas Loas Loas Loas Loas Loas Loas Loas Taiwan Taiwan Taiwan Taiwan Taiwan. Ó;Ù®Ö× mÓTv®Q¯l (SAS Institute 1993) . 2.P Z[Q]Ö×;B;Ù ghik"Z[Q]°±² ³´ (Euclidean distance) µik" TÜÝÞ³´¶ m. dij2=Σλp(yip-yjp)2 p=1. yip ³ yjp ;· i ³ j f% p (p=1, 2, 3, …, m) » % ; Ó (component scores) ¡ λp p 4 % T Æ ¸ g (eigenvalue) .$ SAS ¬ (SAS Institute 1993) . µ M Ü Ý ³ ´ ¹ º (genetic distance matrix) ®» NT-SYS ¬.

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(22) 18. Crop, Environment & Bioinformatics, Vol. 2, March 2005. Table 2. The clssifications and frequencies (in parentheses) of qualitative traits of 140 glutinous rice germplasm. Trait Leaf blade pubescence Color of leaf blade Leaf angle Flag leaf angle Ligule color Ligule shape Collar color Auricle color Basal leaf sheath color Culm angle Internode color Culm strength Panicle type Secondary branching of panicles Panicle exsertion Panicle axis Shattering habit Panicle threshability Awning Awn color Apiculus color Stigma color Lemma and palea color Lemma and palea pubescence Sterile lemma color Sterile lemma length Seed coat color. Classification and frequency Glabrous (1), Intermediate (32), Pubescent (107) Light green (0), Green (125), Dark green (12), Purple tips (0), Purple margins (3), Purple blotch (0), Purple (0) Erect (42), Horizontal (78), Droopy (20) Erect (39), Intermediate (32), Horizental (41), Descending (28) White (126), Purple lines (12), Purple (2) Acute (4), Cleft (136), Truncate (0) Light green (127), Green (1), Purple (12) Light green (127), Purple (13) Green (123), Purple lines (8), Light purple (2), Purple (7) Erect (3), Intermediate(93), Open (44), Spreading (0), Procumbent (0) Green (4), Gold (119), Purple lines (7), Purple (10) Strong (8), Moderately strong (52), Intermediate (47), Weak (21), Very weak (12) Compact (0), Intermediate (137), Open (3) Abscent (98), Light (42), Heavy (0), Clustered (0) Well exserted (35), Moderately well exserted (99), Just exserted (3) Partly exserted (3), Enclosed(0) Straight (0), Droopy (140) Very low (1), Low (9), Intermediate (50), Moderately high (51), High (29) Difficult (1), Moderately difficult (58), Easy (81) Absent (87), Short and partly awned (27) Short and fully awned (7), Long and fully awned (19) Straw (13), Gold (9), Brown (13), Red (2), Purple (11), Black (5) White (1), Straw (85), Brown (28), Red (3), Red tip (4) Purple (9), Purple tip (10) White (3), Light green (94), Yellow (25), Light purple (17), Purple (1) Straw (1), Gold (30), Brown spots (8), Brown furrows (57), Brown (17) Reddish to light purple (5), Purple spots (0), Purple furrows (21), Purple (1), Black (0) Glabrous (19), Hair on lemma keel (36), Hair on upper portion (32), Short hairs (51), Long hairs (2) Yellow (59), Gold (53), Red (3), Purple (25) Short (0), Medium (128), Long (12), Extra long (0), Asymmetrical (0) White (96), Light brown (22), Speckled brown (2), Brown (1), Red (13) Variable purple (0), Purple (6).

(23) ၼ᛻‫ޒܓ‬ຠզ᝴ጎᆎ঩ᒹ༉‫ݣ‬౵‫ܓ‬. 19. Table 3. Testing on mean and variance of quantitative traits of glutinous rice germplasm grown in the spring and fall of 2000. Trait Season Range Mean SE t-test Leaf length (cm) C891 26.0 - 72.0 46.2 0.9 ** C892 18.7 - 65.6 40.6 0.9 Leaf width (mm) 12.6 0.2 C891 8.0 - 19.0 ** C892 5.2 - 18.8 11.6 0.2 ** C891 7.6 - 41.7 Ligule length (mm) 16.7 0.2 5.9 0.5 C892 2.0 - 14.2 C891 87.6 - 175.7 ** Culm length (cm) 125.7 2.0 112.7 1.8 C892 65.2 - 166.6 3.9 - 16.0 Culm number (No. pl ) C891 8.7 0.2 ** C892 2.4 - 14.6 6.5 0.2 Culm diameter (mm) 4.3 - 8.9 6.3 0.1 ** C891 C892 2.2 - 5.7 4.0 0.9 ** C891 17.1 - 38.9 Panicle length (cm) 24.0 0.3 22.7 0.3 C892 15.0 - 30.2 **: Significantly different at 1% level. -1. Table 4. Significant tests of correlation coefficients among quantitative traits of glutinous rice germplasm grown in the spring and fall of 2000. Leaf Leaf Ligule Culm Culm Culm Season ! Trait length width length length number diameter Leaf width C891 0.30** C892 0.48** C891 Ligule length 0.67** 0.02 C892 0.75** 0.39** C891 Culm length 0.70** 0.15 0.46** C892 0.83** 0.44** 0.59** C891 -0.37** -0.57** -0.06 -0.19* Culm number C892 0.17* -0.29** 0.33** 0.12 C891 Culm diameter 0.58** 0.64** 0.34** 0.23** -0.69** C892 0.47** 0.58** 0.37** 0.38** -0.26** C891 Panicle length 0.75** 0.37** 0.56** 0.55** -0.51** 0.66** C892 0.62** 0.57** 0.47** 0.65** -0.22* 0.56** *,** : Significant at 5% and 1% levels, respectively.. d¥å£îå

(24) =å£î¤&= å

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(27) 05 20 hc ar M 2., ol V, csi at mr o nfi o Bi &t ne m n or vi En po, Cr. 20. 02. .0002 fo nosaes gnipporc tsrif eht ni detagitsev ni msalpmreg ecir suonitulg-non 5 dna suonitulg 531 fo scitsiretcarahc ymonorga no desab sisylana retsulc fo margordneD .1 .giF. 5002 hcraM ,2 .loV ,scitamrofnioiB & tnemnorivnE ,porC.

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(29) 05 20 hc ar M 2., ol V, csi at mr o nfi o Bi &t ne m n or vi En po, Cr. 22. 22. .0002 fo nosaes gnipporc dnoces eht ni detagitsevn i msalpmreg ecir suonitulg-non 5 dna suonitulg 531 fo scitsiretcarahc ymonorga no desab sisylana retsulc fo margordneD .2 .giF. 5002 hcraM ,2 .loV ,scitamrofnioiB & tnemnorivnE ,porC.

(30) 3 2. ‫ܓ‬ ౵ ‫ݣ‬ ༉ ᒹ ঩ ᆎ ጎ ᝴ զ ຠ ‫ޒ‬ ‫ܓ‬ ᛻ ၼ. 32. .)deunitnoc(. .2 .giF. ‫ܓ‬౵‫ݣ‬༉ᒹ঩ᆎጎ᝴զຠ‫ܓޒ‬᛻ၼ.

(31) Crop, Environment & Bioinformatics, Vol. 2, March 2005. 24. ȃ ІϜ୾τഛ᝴ጎ ȃ ȃ ȃ ȃ ๊ϸր໲Ϝ ܼΚϊထȄԫѵȂҼѠึ౫ቶ୾ȃ੏୾‫ڸ‬Ӡ ࡚ ঐ‫ྜٿ‬ӵୣ‫ޠ‬᝴ጎᆎ঩Ӽᘫ឵ܼӤΚထ ᆺȂ‫ڐ‬Ꮈ‫ྜٿ‬ӵୣ‫ޠ‬᝴ጎᆎ঩ηԥထᆺ‫ޠ‬౫ ຬȂϛႇӱ࣐ထᆺႮයȂϛԄࠊ८‫ޠྜٿ‬ထ ᆺ౫ຬ݃ᡘȄӶΡ෉ձϜଷΠᇄϜ ဵ пѵȂ ঐߩ᝴ጎᄈྲࠣᆎᘫ឵ܼӤ ΚထᆺȇСҐഛ᝴ ȃ ȃ ȃ ȃ ȃ ȃϜ୾τഛ᝴ጎ ȃ ȃ ȃ ȃ ȃ ቶ୾ު᝴ጎ ȃ ȃ ȃ ‫ޠ‬᝴ጎᆎ঩ηөրԥထᆺ౫ຬȂՅ‫ڐ‬ Ꮈ‫ྜٿ‬ӵୣ‫ޠ‬᝴ጎᆎ঩ϟထᆺࠍၷႮයȄҦ GW33. GW80. GW36). GW81. (GW4. GW87. GW88). 3. 65. (GW137). 4. (GW34. GW38. GW39. (GW75. GW77. GW36. GW37. GW43). GW85. (GW129. GW87. GW130. GW88). GW131. GW134). ԫѠُȂпϛӤ෉ձϟ኶໕‫ޒܓ‬ϟϸထ๗‫ݏ‬ ᡘұӶ‫෉ڎ‬ձґԥ݃ᡘτϸထя౫ȂՅࣻӤ ‫୾ྜٿ‬ঢ়ᆎ঩ԥ໲Ϝܼϊထϟᗎ༗Ȃկ‫෉ڎ‬ ձϸထ๗‫ٯݏ‬ϛΚयȄ пުȃ ࠯ጎᆎІഛ᝴ጎϸ᜹ᢏᄇᐚ‫ޒ‬ ϸထშȂܼΚ෉ձϜ ᝴ȃު᝴Іഛ᝴ጎ҂ ְϸոܼөϊထȇܼΡ෉ձϟ๗‫ݏ‬ҼࣻծȄ ࢉ‫۠ڎ‬ϸထ๗‫ࣲݏ‬ґԥ݃ᡘϟ ᝴ȃު᝴І ഛ᝴ጎϟϸထȄ. ѳȃпϛӤ۠࿾ၼ᛻‫ໍޒܓ‬՘᝴ጎᆎ঩ ᒹ༉຾ᚕϟлԚϸϸ‫ݚ‬. пө୥ၑᆎ঩ϟၼ᛻‫ޒܓ‬ϟ҂ְঅໍ ՘лԚϸϸ‫ݚ‬ȂؒூөࠣᆎዀྦϾϟлԚϸ. Table 5. Eigenvalues and proportions of the first 25 principle components among 60 markers on 33 traits of 140 rice germplasm in the first and second cropping seasons of 2000. Component. Eigenvalue. First cropping season, 2000 Difference Proportion Cumulative. Second cropping season, 2000 Eigenvalue Difference Proportion Cumulative. ˄ʳ. ˈ˃˅ˁˉ˃˄ʳ. ˇˇ˄ˁ˄˅ˋʳ. ˃ˁˊˋ˃ʳ. ˃ˁˊˋ˃ʳ. ˉˆˇˁˊ˃ˈʳ. ˉ˃˄ˁ˃ˇˇʳ. ˃ˁˋˉ˅ʳ. ˃ˁˋˉ˅ʳ. ˅ʳ. ˉ˄ˁˇˊ˅ʳ. ˆˋˁ˅ˉˇʳ. ˃ˁ˃ˌˈʳ. ˃ˁˋˊˈʳ. ˆˆˁˉˉ˄ʳ. ˄ˊˁˈˌ˅ʳ. ˃ˁ˃ˇˉʳ. ˃ˁˌ˃ˊʳ. ˆʳ. ˅ˆˁ˅˃ˋʳ. ˄˃ˁˇˆˌʳ. ˃ˁ˃ˆˉʳ. ˃ˁˌ˄˄ʳ. ˄ˉˁ˃ˉˌʳ. ˈˁ˅ˇˌʳ. ˃ˁ˃˅˅ʳ. ˃ˁˌ˅ˌʳ. ˇʳ. ˄˅ˁˊˉˌʳ. ˅ˁˋ˄ˆʳ. ˃ˁ˃˅˃ʳ. ˃ˁˌˆ˄ʳ. ˄˃ˁˋ˄ˌʳ. ˅ˁˌˋˌʳ. ˃ˁ˃˄ˈʳ. ˃ˁˌˇˇʳ. ˈʳ. ˌˁˌˈˉʳ. ˄ˁˋˊˋʳ. ˃ˁ˃˄ˉʳ. ˃ˁˌˇˊʳ. ˊˁˋˆ˄ʳ. ˅ˁˆˈˆʳ. ˃ˁ˃˄˄ʳ. ˃ˁˌˈˈʳ. ˉʳ. ˋˁ˃ˊˋʳ. ˆˁˋ˃ˌʳ. ˃ˁ˃˄ˆʳ. ˃ˁˌˈˌʳ. ˈˁˇˊˋʳ. ˄ˁˇˇˋʳ. ˃ˁ˃˃ˊʳ. ˃ˁˌˉ˅ʳ. ˊʳ. ˇˁ˅ˉˌʳ. ˃ˁ˄ˌ˅ʳ. ˃ˁ˃˃ˊʳ. ˃ˁˌˉˉʳ. ˇˁ˃ˆ˃ʳ. ˃ˁˈˆˋʳ. ˃ˁ˃˃ˉʳ. ˃ˁˌˉˋʳ. ˋʳ. ˇˁ˃ˊˊʳ. ˄ˁ˃ˆˉʳ. ˃ˁ˃˃ˉʳ. ˃ˁˌˊ˅ʳ. ˆˁˇˌ˅ʳ. ˃ˁ˅ˇ˅ʳ. ˃ˁ˃˃ˈʳ. ˃ˁˌˊ˅ʳ. ˌʳ. ˆˁ˃ˇ˄ʳ. ˃ˁˈˉˇʳ. ˃ˁ˃˃ˈʳ. ˃ˁˌˊˊʳ. ˆˁ˅ˈ˃ʳ. ˃ˁˆˋˊʳ. ˃ˁ˃˃ˇʳ. ˃ˁˌˊˊʳ. ˄˃ʳ. ˅ˁˇˊˊʳ. ˃ˁˆˉˆʳ. ˃ˁ˃˃ˇʳ. ˃ˁˌˋ˄ʳ. ˅ˁˋˉˆʳ. ˃ˁˆ˃ˇʳ. ˃ˁ˃˃ˇʳ. ˃ˁˌˋ˄ʳ. ˄˄ʳ. ˅ˁ˄˄ˇʳ. ˃ˁˇˆˉʳ. ˃ˁ˃˃ˆʳ. ˃ˁˌˋˇʳ. ˅ˁˈˈˌʳ. ˃ˁ˅˃˃ʳ. ˃ˁ˃˃ˇʳ. ˃ˁˌˋˇʳ. ˄˅ʳ. ˄ˁˉˊˋʳ. ˃ˁˆ˅˃ʳ. ˃ˁ˃˃ˆʳ. ˃ˁˌˋˊʳ. ˅ˁˆˈˌʳ. ˃ˁˉˋ˄ʳ. ˃ˁ˃˃ˆʳ. ˃ˁˌˋˊʳ. ˄ˆʳ. ˄ˁˆˈˋʳ. ˃ˁ˅ˆˌʳ. ˃ˁ˃˃˅ʳ. ˃ˁˌˋˌʳ. ˄ˁˉˊˌʳ. ˃ˁ˄˃ˊʳ. ˃ˁ˃˃˅ʳ. ˃ˁˌˌ˃ʳ. ˄ˇʳ. ˄ˁ˄˄ˌʳ. ˃ˁ˃ˌ˄ʳ. ˃ˁ˃˃˅ʳ. ˃ˁˌˌ˄ʳ. ˄ˁˈˊ˅ʳ. ˃ˁˉ˅ˉʳ. ˃ˁ˃˃˅ʳ. ˃ˁˌˌ˅ʳ. ˄ˈʳ. ˄ˁ˃˅ˊʳ. ˃ˁ˅ˇˇʳ. ˃ˁ˃˃˅ʳ. ˃ˁˌˌ˅ʳ. ˃ˁˌˇˉʳ. ˃ˁ˃ˌˉʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˆʳ. ˄ˉʳ. ˃ˁˊˋˇʳ. ˃ˁ˃ˌ˅ʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˆʳ. ˃ˁˋˈ˃ʳ. ˃ˁ˄˅ˆʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˇʳ. ˄ˊʳ. ˃ˁˉˌ˅ʳ. ˃ˁ˃ˆˇʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˇʳ. ˃ˁˊ˅ˊʳ. ˃ˁ˃ˊˉʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˈʳ. ˄ˋʳ. ˃ˁˉˈˋʳ. ˃ˁ˃ˊ˄ʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˈʳ. ˃ˁˉˈ˄ʳ. ˃ˁ˄˃˄ʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˉʳ. ˄ˌʳ. ˃ˁˈˋˊʳ. ˃ˁ˄˃ˌʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˉʳ. ˃ˁˈˈ˃ʳ. ˃ˁ˄˃˅ʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˊʳ. ˅˃ʳ. ˃ˁˇˊˋʳ. ˃ˁ˃ˋˉʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˊʳ. ˃ˁˇˇˋʳ. ˃ˁ˃ˌ˃ʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˊʳ. ˅˄ʳ. ˃ˁˆˌ˅ʳ. ˃ˁ˃ˆˉʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˋʳ. ˃ˁˆˈˋʳ. ˃ˁ˃ˇˋʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˋʳ. ˅˅ʳ. ˃ˁˆˈˉʳ. ˃ˁ˄ˆˉʳ. ˃ˁ˃˃˄ʳ. ˃ˁˌˌˋʳ. ˃ˁˆ˄˃ʳ. ˃ˁ˃ˉˊʳ. ˃ˁ˃˃˃ʳ. ˃ˁˌˌˋʳ. ˅ˆʳ. ˃ˁ˅˅˃ʳ. ˃ˁ˃˄˃ʳ. ˃ˁ˃˃˃ʳ. ˃ˁˌˌˌʳ. ˃ˁ˅ˇˆʳ. ˃ˁ˃˃ˋʳ. ˃ˁ˃˃˃ʳ. ˃ˁˌˌˌʳ. ˅ˇʳ. ˃ˁ˅˄˃ʳ. ˃ˁ˃ˈˆʳ. ˃ˁ˃˃˃ʳ. ˃ˁˌˌˌʳ. ˃ˁ˅ˆˈʳ. ˃ˁ˃ˆˆʳ. ˃ˁ˃˃˃ʳ. ˃ˁˌˌˌʳ. ˅ˈʳ. ˃ˁ˄ˈˋʳ. ˃ˁ˃˃ˋʳ. ˃ˁ˃˃˃ʳ. ˃ˁˌˌˌʳ. ˃ˁ˅˃˅ʳ. ˃ˁ˃ˇˇʳ. ˃ˁ˃˃˃ʳ. ˃ˁˌˌˌʳ.

(32) ၼ᛻‫ޒܓ‬ຠզ᝴ጎᆎ঩ᒹ༉‫ݣ‬౵‫ܓ‬. RtY<=VW5 Table 5Pwx yVW: 2000 <={" (eigen value)P Table 5 6 wx "S 91.14%P Table 6 wx S(eigen vectors)B2w"1; wx B2w"1 w wx B2w1P

(33) ;x MS 87.5%mPKF#B ;wx 2. 25. |=F#M 2D 4kh5 Fig. 3. Br 20 AF M ( ij¡ 121.8 cm) 2 ¢£B¤¥¦ F Kinankuda M (ij2 45.8 cm)2 ¢£B ! y¡B 2 A B Y§ HI HI @¨ © (ª 1 #$ ) «¬ (ª 1 #$ ) 5 CDE F#w

(34) A GL @¨J . Table 6. Eigenvectors of the 32 traits on the first to the 5th principal components on 140 rice accessions the first and second cropping seasons of 2000.. Trait Leaf length (cm) Leaf width (mm) Leaf pubescence Leaf color Leaf sheath color Leaf angle Flag leaf angle Ligule length (mm) Ligule color Ligule shape Collar color Auricle color Plant height (cm) Tilling number Culm angle Culm diameter (mm) Internode color Culm strength Panicle length (cm) Panicle type! Secondary panicles! Panicle exsertion! Shattering habit Panicle threshability Awning! Awn color! Apiculus color! Stigma color! Lemma and palea color! Lemma and palea pubescence! Sterile lemma color! Sterile lemma length! Seed coat color!. Prin1 0.361 0.018 0.000 0.001 0.007 0.020 0.030 0.141 0.004 -0.002 0.006 0.003 0.912 -0.027 0.013 0.014 0.005 0.031 0.109 0.005 -0.003 -0.008 -0.006 -0.002 0.017 0.018 0.015 0.006 0.006 -0.014 -0.002 0.001 0.020. First cropping season Prin2 Prin3 Prin4 0.740 0.170 -0.354 0.067 0.191 -0.085 -0.017 -0.026 -0.021 0.007 -0.022 0.015 0.002 -0.023 0.030 0.049 0.302 0.293 0.016 0.272 0.244 0.416 -0.577 0.579 0.002 -0.010 0.016 -0.003 0.000 -0.001 0.002 -0.019 0.013 0.001 -0.009 0.007 -0.388 -0.043 -0.006 -0.097 -0.336 -0.072 -0.027 -0.065 0.038 0.074 0.074 -0.017 -0.003 -0.015 0.021 -0.123 -0.137 0.115 0.246 0.201 0.176 0.006 -0.002 0.001 0.000 -0.001 -0.039 0.033 -0.050 -0.025 -0.011 -0.064 0.199 0.016 -0.044 0.215 -0.131 0.367 0.322 -0.044 0.204 0.200 0.048 0.140 0.143 0.010 0.067 0.079 0.034 0.166 0.225 -0.073 -0.015 -0.035 0.023 0.108 0.093 0.012 0.037 0.036 0.016 0.027 0.114. Prin5 0.063 0.048 -0.046 0.005 0.029 0.454 0.296 -0.198 0.015 0.011 0.031 0.017 0.020 0.061 0.015 -0.027 0.030 0.102 -0.180 0.028 -0.036 0.010 0.381 0.418 -0.471 -0.198 -0.037 0.003 -0.069 -0.122 -0.056 0.024 0.004. Prin1 0.363 0.045 0.003 -0.001 0.010 0.001 -0.007 0.057 0.007 0.001 0.011 0.005 0.923 0.013 0.006 0.011 0.013 0.034 0.088 0.002 -0.001 -0.002 0.007 0.017 -0.003 0.005 0.011 0.012 0.011 -0.004 -0.004 0.004 0.008. Second cropping season Prin2 Prin3 Prin4 0.855 0.097 0.261 0.088 0.249 -0.245 -0.005 -0.064 0.088 -0.002 -0.003 0.003 -0.007 0.071 -0.048 -0.025 0.358 -0.180 -0.020 0.305 -0.155 0.183 -0.089 -0.037 -0.007 0.050 -0.038 0.000 0.002 0.003 0.002 0.075 -0.083 -0.003 0.051 -0.039 -0.355 -0.074 -0.069 0.070 -0.439 0.126 -0.028 0.022 0.077 0.031 0.044 -0.016 -0.030 0.038 -0.027 -0.076 -0.053 0.059 0.063 0.314 -0.154 -0.003 -0.010 -0.012 0.013 -0.013 0.000 0.101 0.003 -0.091 0.005 -0.071 -0.119 -0.009 -0.149 -0.250 -0.235 0.262 0.709 -0.116 0.171 0.348 -0.015 0.290 -0.009 -0.024 0.150 -0.024 0.001 0.320 -0.061 -0.039 -0.011 0.157 0.000 0.178 0.010 -0.010 0.011 -0.026 -0.042 0.093 0.002. Prin5 0.087 -0.301 -0.046 -0.007 0.079 0.463 0.316 -0.017 0.046 0.010 0.054 0.027 0.021 0.341 0.073 -0.107 0.075 -0.049 -0.533 0.013 -0.015 -0.056 0.106 0.165 -0.017 -0.011 0.109 0.076 0.273 0.049 0.088 0.012 -0.045.

(35) 26. Crop, Environment & Bioinformatics, Vol. 2, March 2005. Nw

(36) B L @¨® ¤¥¦¯ (ª 2 # $ )"N

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(41) A 2O µ¶·2wL B N¸ OP¶»o- k#^_ <=\l`*@¨J:;<=ª k:¹ºL: <=N:µ ¹ºj- k. Fig. 3. Plot of the first two principal components from the covariance matrix of the trait frequencies in the 135 glutinous and 5 non-glutinous rice germplasm in the first cropping season of 2000..

(42) ၼ᛻‫ޒܓ‬ຠզ᝴ጎᆎ঩ᒹ༉‫ݣ‬౵‫ܓ‬. 27. Fig. 4. Plot of the first two principal components from the covariance matrix of the trait frequencies in the 135 glutinous and 5 non-glutinous rice germplasm in the second cropping season of 2000.. ÊËYn {Ì"wx BÍ#$ Mw ÎÏBTUj! JÐ Ñ]M#$1ÒÓ

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(44) B . ଇ፤. ßT à2#]áâ#$ " Ú Î Ï ã Chen . 1998, Bhargava . 1966äIáâåæ"TU - 33 * 27 2ç"TU7 2R STUef"TUè"K#TU Md 89¸éßcê *#$! ×W`´DëR#$Lìí et. et al. al. -îMßc2ïðñéò³#$M óô"õö|÷\DLìøùTUMd. N kO2jú>?ûj2àüc Þ 26 ç"TUýBՔᐪ2 dÎÏ޲-Ք èஆՔ Ք ᕘՔ ՇՔ ࿾໣Ք ٌՔ ┃ԍՔ ࢙ᓟՔ °ᑘՔᐪ ៗᑘՔᐪ#ҫՔ 12 G Beîcᄙ2 d޲-Ъ ቕ c ‫ם‬U èఝِ ûc ԪҢМ M-ณ ûMի û ûMဤùT ٌM-ณ °ᑘM೻Ъ ៗᑘ 12 GÞÀ- 2 TሰPΩขé ޲5ఝM஽ ûMÈùT( TUᓝ OMßc‫ٽ‬é#$M! Lí -/(ßcйᓝ\ߗTUNOᎍË

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(47) 28. Crop, Environment & Bioinformatics, Vol. 2, March 2005. -O/Mßuv\0T1é,, TUMM\02RÄÅ) M\0 ¼RM\09ÕT :Y<=-/ b".ßXò³RST U<=í-34×56:*+TUN \02RM bTÆ-"7 /ª7 RSTUMß8 TUM\0T Iáâ¬9: ;<=Mpq#$ "rsTUuv yVWY<=D

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(50) ;<= ; w x w1 2 ¼ R6 wx SN 92.93% Y<=6Ywx Mw 1´\("#"MS. Ì 87.5% 90.7%;TUCÒÜ åæO%Ë@A59#í-óô#$! ×Wê;TUOLí-O/ #$y×W±1J IBPCD !MEFØ #1YTUDGHEI5J4 m/(M#$KÜI5:;TUM. õöØ½¾Y<=MLM/(` ´w M1/ßX´ B=2 <=;<=#$w MÎÏ½¾IáâåæM 23 ç"T UDS#$! Zí-Oñ × W`1*NOåæ#/PQR- Dé#$! Ù-59Stwx y VWT9 UPGMA NUuv) yV W/ bw:

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(54) #$! ,BÌK !"#$KÁ")( !#dMrsTU ?/LZ" JD ECF#-.L A ). O B 899X MrsTU? JMrsTU?O NêÄ[ JYdc Holcomb (1977) P#$\]^_ ` 1,407 488 J#$a#å æ 14 RSTU 27 çSTUJ O í-OMõö?VWI @aB#$2bY{"VW b ¬9*rsTUuvJ ´ v"½¾

(55) RSTUÜP-" L7Ìáâuv"( !/(n M y"VW\$#jB 2w ÎÏýc¬9

(56) õö\lT OM#$ Öñ é#$def¬ 9rsßTU"gé´/h"1-i ¬9 DNA |÷Ýju k"lm y ÏnD

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(58) ၼ᛻‫ޒܓ‬ຠզ᝴ጎᆎ঩ᒹ༉‫ݣ‬౵‫ܓ‬. pqê"o BB¬9F# 4 khMVWr"_spqêF# Mpt Iáâ¬9rsTUBD#$ = y`´rsTURSTUÜP -"uL7P < ;<Y= {" yVWUD !=-8v " `D

(59) BJ M Bw! r"#$¬9Mpt (Yoshida. and. Li. et. 1991). al. 1972, Chang 2D. ЖңНᝧ. Chen S, C Chen, MJ Fan (1997) Core collection of germplasm. (in Chinese) Scientific Agric. 45:299-306. Chen S, C Chen, MJ Fan, S Tsou (1998) Geographic distribution and genetic diversity for morphological characters in a world germplasm collection of mungbean (Vigna radiate (L.) Wilczek). (in Chinese) J. Agric. Res. China 47(2):108-124. Taichung DAIS (2000) Annual Report of Rice Improvement. (in Chinese) p.299-310. Taichung DAIS, Changhua, Taiwan. Bhargava PD, JN Johri, SK Sharma, BN Bhatt (1966) Morphological and genetic variability in green gram. Indian J. Genet. Plant Breed. 26:370-373. Blair MW, O Panaud, SR McCouch (1999) Inter-simple sequence repeat (ISSR) amplification for analysis of microsatellite motif frequency and fingerprinting in rice (Oryza sativa L.). Theor. Appl. Genet. 98: 780-792. Chang TT, CC Li (1991) Genetics and breeding. p.23-101. In: Rice. vol. 1. Production, 2nd ed. B. S. Luh (ed.) AVI-Van Nostrand Reinhold, New York. Chang, TZ (1976) The origin, evolution, cultivation, dissemination, and diversifiction of Asian and African rices. Euphytica 25: 425-441. COA (1996) Brochure of Rice Grain Quality. COA, Taiwan. 2pp.. 29. COA, DAF, and FFTC (1987) Rice Variety in Taiwan. (in Chinese) COA, DAF, and FFTC, Taiwan. 306pp. Davierwala AP, W Ramakrishna, PK Ranjekar, VS Gupta (2000) Sequence variations at a complex microsatellite locus in rice and its conservation in cereals. Theor. Appl. Genet. 101:1291-1298. Gaines TP, GA Mitchell (1979) Chemical methods for soil and plant analysis. p.79-82. In: Agronomy Handbook No. 1. University of Georgia Coastal Plain Experiment Station, Georgia, USA. Holcomb JD, M Tolbert, SK Jain (1977) A diversity analysis of genetic resources in rice. Euphytica 26:441-450. IRRI (1996) Standard Evaluation System for Rice. 4th ed. Manila, Philippines. Juliano BO (1971) A simplified assay for milled-rice amylose. Cereal Sci. 16:334-338. Mackill D (1995) Classifying japonica rice cultivars with RAPD markers. Crop Sci. 35:889-894. Mackill D, X Lei (1997) Genetic variation for traits related to temperate adaptation of rice cultivars. Crop Sci. 37:1340-1346. Rohlf FJ (1989) NTSYS-PC Numerical Taxonomy and Multivariate Analysis System. Version 1.5. Exeter Publ., Setauket, NY, USA. SAS Institute Inc. (1993) SAS Companion for the Microsoft Windows Environment. (Version 6.1). Cary, NC, USA. Second G (1991) Molecular Markers in Rice Systematics and the Evaluation of Genetic Resources. p.469-494. In: Biotechnology in Agriculture and Forestry. Vol.14. Rice. YPS. Bajaj (ed.) Springer-Verlag, Berlin. Virk PS, BV Ford-Lloyd, MT Jackson, HJ Newbury (1995) Use of RAPD for the study of diversity within plant germplasm collections. Heredity 74:170-179. Yang GP, MAS Maroof, CG Xu, Q Zhang, RM Biyashev (1994) Comparative analysis of microsatellite DNA polymorphism in landraces and cultivars of rice. Mol. Gen. Genet. 245:187-194..

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