iVOD / 168893

Field Value
IVOD_ID 168893
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/168893
日期 2026-04-29
會議資料.會議代碼 委員會-11-5-19-11
會議資料.會議代碼:str 第11屆第5會期經濟委員會第11次全體委員會議
會議資料.屆 11
會議資料.會期 5
會議資料.會次 11
會議資料.種類 委員會
會議資料.委員會代碼[0] 19
會議資料.委員會代碼:str[0] 經濟委員會
會議資料.標題 第11屆第5會期經濟委員會第11次全體委員會議
影片種類 Clip
開始時間 2026-04-29T09:29:01+08:00
結束時間 2026-04-29T09:41:35+08:00
影片長度 00:12:34
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/6301273cb2dfee84b51e3f735c3de96e4294381b535652e636c9d108d903c183f0c0b32b082070385ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 張嘉郡
委員發言時間 09:29:01 - 09:41:35
會議時間 2026-04-29T09:00:00+08:00
會議名稱 立法院第11屆第5會期經濟委員會第11次全體委員會議(事由:一、 審查115年度中央政府總預算案關於農業部及所屬單位預算部分。 二、 審查115年度中央政府總預算案有關第27款直轄市及縣市政府第7項一般性補助款—農業部主管第1目農業部、第2目林業及自然保育署及所屬、第3目農村發展及水土保持署及所屬、第4目漁業署及所屬、第5目動植物防疫檢疫署及所屬、第6目農糧署及所屬、第7目農田水利署部分預算。 三、 審查115年度中央政府總預算案附屬單位預算非營業部分關於農業部主管:農業作業基金、農田水利事業作業基金、農業特別收入基金及農民退休基金。(詢答) 【4月29日及4月30日二天一次會】)
transcript.pyannote[0].speaker SPEAKER_01
transcript.pyannote[0].start 0.03096875
transcript.pyannote[0].end 2.79846875
transcript.pyannote[1].speaker SPEAKER_02
transcript.pyannote[1].start 10.47659375
transcript.pyannote[1].end 11.53971875
transcript.pyannote[2].speaker SPEAKER_02
transcript.pyannote[2].start 11.77596875
transcript.pyannote[2].end 12.88971875
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 13.32846875
transcript.pyannote[3].end 14.40846875
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 21.36096875
transcript.pyannote[4].end 21.78284375
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 22.20471875
transcript.pyannote[5].end 35.65409375
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 36.44721875
transcript.pyannote[6].end 37.74659375
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 39.78846875
transcript.pyannote[7].end 42.85971875
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 44.09159375
transcript.pyannote[8].end 47.04471875
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 47.28096875
transcript.pyannote[9].end 48.19221875
transcript.pyannote[10].speaker SPEAKER_02
transcript.pyannote[10].start 48.76596875
transcript.pyannote[10].end 53.45721875
transcript.pyannote[11].speaker SPEAKER_02
transcript.pyannote[11].start 53.89596875
transcript.pyannote[11].end 54.89159375
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 55.65096875
transcript.pyannote[12].end 56.56221875
transcript.pyannote[13].speaker SPEAKER_02
transcript.pyannote[13].start 58.40159375
transcript.pyannote[13].end 59.83596875
transcript.pyannote[14].speaker SPEAKER_02
transcript.pyannote[14].start 60.89909375
transcript.pyannote[14].end 62.02971875
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 62.48534375
transcript.pyannote[15].end 63.14346875
transcript.pyannote[16].speaker SPEAKER_02
transcript.pyannote[16].start 64.25721875
transcript.pyannote[16].end 65.57346875
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 66.06284375
transcript.pyannote[17].end 68.61096875
transcript.pyannote[18].speaker SPEAKER_02
transcript.pyannote[18].start 68.91471875
transcript.pyannote[18].end 69.75846875
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 70.97346875
transcript.pyannote[19].end 87.46034375
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 86.05971875
transcript.pyannote[20].end 86.51534375
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 87.22409375
transcript.pyannote[21].end 89.63721875
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 90.09284375
transcript.pyannote[22].end 93.36659375
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 94.26096875
transcript.pyannote[23].end 101.93909375
transcript.pyannote[24].speaker SPEAKER_01
transcript.pyannote[24].start 102.15846875
transcript.pyannote[24].end 105.73596875
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 106.36034375
transcript.pyannote[25].end 112.40159375
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 112.62096875
transcript.pyannote[26].end 115.30409375
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 112.63784375
transcript.pyannote[27].end 113.21159375
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 113.93721875
transcript.pyannote[28].end 115.01721875
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 115.47284375
transcript.pyannote[29].end 117.68346875
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 118.17284375
transcript.pyannote[30].end 122.35784375
transcript.pyannote[31].speaker SPEAKER_02
transcript.pyannote[31].start 123.18471875
transcript.pyannote[31].end 124.63596875
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 125.10846875
transcript.pyannote[32].end 127.45409375
transcript.pyannote[33].speaker SPEAKER_02
transcript.pyannote[33].start 127.84221875
transcript.pyannote[33].end 128.48346875
transcript.pyannote[34].speaker SPEAKER_02
transcript.pyannote[34].start 129.09096875
transcript.pyannote[34].end 130.49159375
transcript.pyannote[35].speaker SPEAKER_02
transcript.pyannote[35].start 130.69409375
transcript.pyannote[35].end 131.70659375
transcript.pyannote[36].speaker SPEAKER_02
transcript.pyannote[36].start 132.19596875
transcript.pyannote[36].end 140.97096875
transcript.pyannote[37].speaker SPEAKER_01
transcript.pyannote[37].start 140.97096875
transcript.pyannote[37].end 149.96534375
transcript.pyannote[38].speaker SPEAKER_02
transcript.pyannote[38].start 140.98784375
transcript.pyannote[38].end 141.34221875
transcript.pyannote[39].speaker SPEAKER_02
transcript.pyannote[39].start 150.20159375
transcript.pyannote[39].end 153.08721875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 153.86346875
transcript.pyannote[40].end 155.07846875
transcript.pyannote[41].speaker SPEAKER_02
transcript.pyannote[41].start 155.85471875
transcript.pyannote[41].end 160.93409375
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 161.67659375
transcript.pyannote[42].end 162.79034375
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 163.09409375
transcript.pyannote[43].end 167.70096875
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 167.70096875
transcript.pyannote[44].end 176.34096875
transcript.pyannote[45].speaker SPEAKER_02
transcript.pyannote[45].start 171.02534375
transcript.pyannote[45].end 172.18971875
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 172.39221875
transcript.pyannote[46].end 173.67471875
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 176.34096875
transcript.pyannote[47].end 189.11534375
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 189.40221875
transcript.pyannote[48].end 190.39784375
transcript.pyannote[49].speaker SPEAKER_02
transcript.pyannote[49].start 190.90409375
transcript.pyannote[49].end 193.30034375
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 193.33409375
transcript.pyannote[50].end 202.41284375
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 201.61971875
transcript.pyannote[51].end 206.14221875
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 205.46721875
transcript.pyannote[52].end 205.97346875
transcript.pyannote[53].speaker SPEAKER_01
transcript.pyannote[53].start 206.14221875
transcript.pyannote[53].end 206.26034375
transcript.pyannote[54].speaker SPEAKER_02
transcript.pyannote[54].start 206.58096875
transcript.pyannote[54].end 211.82909375
transcript.pyannote[55].speaker SPEAKER_01
transcript.pyannote[55].start 206.83409375
transcript.pyannote[55].end 207.54284375
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 208.01534375
transcript.pyannote[56].end 208.85909375
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 209.38221875
transcript.pyannote[57].end 221.78534375
transcript.pyannote[58].speaker SPEAKER_01
transcript.pyannote[58].start 222.46034375
transcript.pyannote[58].end 237.61409375
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 236.90534375
transcript.pyannote[59].end 238.25534375
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 237.76596875
transcript.pyannote[60].end 238.08659375
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 239.52096875
transcript.pyannote[61].end 240.31409375
transcript.pyannote[62].speaker SPEAKER_02
transcript.pyannote[62].start 240.31409375
transcript.pyannote[62].end 241.17471875
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 240.34784375
transcript.pyannote[63].end 240.90471875
transcript.pyannote[64].speaker SPEAKER_02
transcript.pyannote[64].start 242.11971875
transcript.pyannote[64].end 252.61596875
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 252.61596875
transcript.pyannote[65].end 252.90284375
transcript.pyannote[66].speaker SPEAKER_02
transcript.pyannote[66].start 252.90284375
transcript.pyannote[66].end 254.03346875
transcript.pyannote[67].speaker SPEAKER_01
transcript.pyannote[67].start 252.91971875
transcript.pyannote[67].end 270.41909375
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 267.61784375
transcript.pyannote[68].end 269.38971875
transcript.pyannote[69].speaker SPEAKER_02
transcript.pyannote[69].start 269.81159375
transcript.pyannote[69].end 274.87409375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 275.61659375
transcript.pyannote[70].end 279.39659375
transcript.pyannote[71].speaker SPEAKER_02
transcript.pyannote[71].start 279.39659375
transcript.pyannote[71].end 281.50596875
transcript.pyannote[72].speaker SPEAKER_02
transcript.pyannote[72].start 281.70846875
transcript.pyannote[72].end 283.09221875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 283.95284375
transcript.pyannote[73].end 284.71221875
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 285.52221875
transcript.pyannote[74].end 286.06221875
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 286.93971875
transcript.pyannote[75].end 288.30659375
transcript.pyannote[76].speaker SPEAKER_02
transcript.pyannote[76].start 288.49221875
transcript.pyannote[76].end 289.40346875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 288.71159375
transcript.pyannote[77].end 290.66909375
transcript.pyannote[78].speaker SPEAKER_02
transcript.pyannote[78].start 290.66909375
transcript.pyannote[78].end 296.67659375
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 296.76096875
transcript.pyannote[79].end 298.19534375
transcript.pyannote[80].speaker SPEAKER_01
transcript.pyannote[80].start 299.57909375
transcript.pyannote[80].end 302.41409375
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 301.89096875
transcript.pyannote[81].end 304.84409375
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 305.46846875
transcript.pyannote[82].end 309.24846875
transcript.pyannote[83].speaker SPEAKER_01
transcript.pyannote[83].start 307.02096875
transcript.pyannote[83].end 319.28909375
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 319.33971875
transcript.pyannote[84].end 319.59284375
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 319.87971875
transcript.pyannote[85].end 324.01409375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 324.01409375
transcript.pyannote[86].end 328.55346875
transcript.pyannote[87].speaker SPEAKER_02
transcript.pyannote[87].start 327.96284375
transcript.pyannote[87].end 330.17346875
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 329.73471875
transcript.pyannote[88].end 329.97096875
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 331.37159375
transcript.pyannote[89].end 331.99596875
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 333.37971875
transcript.pyannote[90].end 350.23784375
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 350.76096875
transcript.pyannote[91].end 351.30096875
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 351.30096875
transcript.pyannote[92].end 351.35159375
transcript.pyannote[93].speaker SPEAKER_02
transcript.pyannote[93].start 351.35159375
transcript.pyannote[93].end 352.60034375
transcript.pyannote[94].speaker SPEAKER_01
transcript.pyannote[94].start 352.60034375
transcript.pyannote[94].end 352.61721875
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 352.61721875
transcript.pyannote[95].end 352.65096875
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 352.65096875
transcript.pyannote[96].end 353.27534375
transcript.pyannote[97].speaker SPEAKER_02
transcript.pyannote[97].start 353.27534375
transcript.pyannote[97].end 353.34284375
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 353.34284375
transcript.pyannote[98].end 353.95034375
transcript.pyannote[99].speaker SPEAKER_01
transcript.pyannote[99].start 354.32159375
transcript.pyannote[99].end 361.52721875
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 360.10971875
transcript.pyannote[100].end 375.97221875
transcript.pyannote[101].speaker SPEAKER_01
transcript.pyannote[101].start 375.97221875
transcript.pyannote[101].end 379.80284375
transcript.pyannote[102].speaker SPEAKER_00
transcript.pyannote[102].start 380.00534375
transcript.pyannote[102].end 380.02221875
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 380.02221875
transcript.pyannote[103].end 384.59534375
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 380.35971875
transcript.pyannote[104].end 381.57471875
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 384.93284375
transcript.pyannote[105].end 395.56409375
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 395.68221875
transcript.pyannote[106].end 399.86721875
transcript.pyannote[107].speaker SPEAKER_01
transcript.pyannote[107].start 397.58909375
transcript.pyannote[107].end 405.67221875
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 405.89159375
transcript.pyannote[108].end 426.49596875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 426.05721875
transcript.pyannote[109].end 427.47471875
transcript.pyannote[110].speaker SPEAKER_02
transcript.pyannote[110].start 427.57596875
transcript.pyannote[110].end 428.87534375
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 429.11159375
transcript.pyannote[111].end 439.62471875
transcript.pyannote[112].speaker SPEAKER_01
transcript.pyannote[112].start 440.26596875
transcript.pyannote[112].end 451.62284375
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 451.74096875
transcript.pyannote[113].end 453.29346875
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 453.83346875
transcript.pyannote[114].end 458.67659375
transcript.pyannote[115].speaker SPEAKER_02
transcript.pyannote[115].start 457.41096875
transcript.pyannote[115].end 465.30846875
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 465.47721875
transcript.pyannote[116].end 466.23659375
transcript.pyannote[117].speaker SPEAKER_02
transcript.pyannote[117].start 466.77659375
transcript.pyannote[117].end 469.62846875
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 470.03346875
transcript.pyannote[118].end 472.21034375
transcript.pyannote[119].speaker SPEAKER_02
transcript.pyannote[119].start 473.29034375
transcript.pyannote[119].end 476.73284375
transcript.pyannote[120].speaker SPEAKER_01
transcript.pyannote[120].start 477.54284375
transcript.pyannote[120].end 479.98971875
transcript.pyannote[121].speaker SPEAKER_01
transcript.pyannote[121].start 480.17534375
transcript.pyannote[121].end 481.39034375
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 481.99784375
transcript.pyannote[122].end 483.24659375
transcript.pyannote[123].speaker SPEAKER_02
transcript.pyannote[123].start 483.95534375
transcript.pyannote[123].end 485.11971875
transcript.pyannote[124].speaker SPEAKER_02
transcript.pyannote[124].start 485.71034375
transcript.pyannote[124].end 487.87034375
transcript.pyannote[125].speaker SPEAKER_02
transcript.pyannote[125].start 489.11909375
transcript.pyannote[125].end 499.75034375
transcript.pyannote[126].speaker SPEAKER_01
transcript.pyannote[126].start 499.93596875
transcript.pyannote[126].end 503.26034375
transcript.pyannote[127].speaker SPEAKER_02
transcript.pyannote[127].start 503.34471875
transcript.pyannote[127].end 505.04909375
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 506.21346875
transcript.pyannote[128].end 510.31409375
transcript.pyannote[129].speaker SPEAKER_02
transcript.pyannote[129].start 509.79096875
transcript.pyannote[129].end 512.55846875
transcript.pyannote[130].speaker SPEAKER_01
transcript.pyannote[130].start 511.25909375
transcript.pyannote[130].end 511.44471875
transcript.pyannote[131].speaker SPEAKER_01
transcript.pyannote[131].start 512.13659375
transcript.pyannote[131].end 515.68034375
transcript.pyannote[132].speaker SPEAKER_02
transcript.pyannote[132].start 512.59221875
transcript.pyannote[132].end 512.77784375
transcript.pyannote[133].speaker SPEAKER_02
transcript.pyannote[133].start 515.68034375
transcript.pyannote[133].end 534.36096875
transcript.pyannote[134].speaker SPEAKER_02
transcript.pyannote[134].start 534.64784375
transcript.pyannote[134].end 535.96409375
transcript.pyannote[135].speaker SPEAKER_02
transcript.pyannote[135].start 536.16659375
transcript.pyannote[135].end 536.97659375
transcript.pyannote[136].speaker SPEAKER_02
transcript.pyannote[136].start 538.91721875
transcript.pyannote[136].end 539.69346875
transcript.pyannote[137].speaker SPEAKER_02
transcript.pyannote[137].start 539.86221875
transcript.pyannote[137].end 541.41471875
transcript.pyannote[138].speaker SPEAKER_02
transcript.pyannote[138].start 541.61721875
transcript.pyannote[138].end 552.06284375
transcript.pyannote[139].speaker SPEAKER_01
transcript.pyannote[139].start 553.10909375
transcript.pyannote[139].end 554.88096875
transcript.pyannote[140].speaker SPEAKER_02
transcript.pyannote[140].start 554.02034375
transcript.pyannote[140].end 558.37409375
transcript.pyannote[141].speaker SPEAKER_02
transcript.pyannote[141].start 558.42471875
transcript.pyannote[141].end 558.45846875
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 558.45846875
transcript.pyannote[142].end 558.94784375
transcript.pyannote[143].speaker SPEAKER_02
transcript.pyannote[143].start 558.89721875
transcript.pyannote[143].end 564.19596875
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 564.71909375
transcript.pyannote[144].end 568.66784375
transcript.pyannote[145].speaker SPEAKER_02
transcript.pyannote[145].start 569.05596875
transcript.pyannote[145].end 583.51784375
transcript.pyannote[146].speaker SPEAKER_02
transcript.pyannote[146].start 583.72034375
transcript.pyannote[146].end 584.34471875
transcript.pyannote[147].speaker SPEAKER_00
transcript.pyannote[147].start 583.88909375
transcript.pyannote[147].end 584.07471875
transcript.pyannote[148].speaker SPEAKER_01
transcript.pyannote[148].start 584.07471875
transcript.pyannote[148].end 584.17596875
transcript.pyannote[149].speaker SPEAKER_00
transcript.pyannote[149].start 584.17596875
transcript.pyannote[149].end 584.19284375
transcript.pyannote[150].speaker SPEAKER_01
transcript.pyannote[150].start 584.19284375
transcript.pyannote[150].end 607.49721875
transcript.pyannote[151].speaker SPEAKER_00
transcript.pyannote[151].start 584.34471875
transcript.pyannote[151].end 584.37846875
transcript.pyannote[152].speaker SPEAKER_02
transcript.pyannote[152].start 584.37846875
transcript.pyannote[152].end 584.39534375
transcript.pyannote[153].speaker SPEAKER_00
transcript.pyannote[153].start 584.39534375
transcript.pyannote[153].end 584.49659375
transcript.pyannote[154].speaker SPEAKER_02
transcript.pyannote[154].start 584.49659375
transcript.pyannote[154].end 584.51346875
transcript.pyannote[155].speaker SPEAKER_00
transcript.pyannote[155].start 584.51346875
transcript.pyannote[155].end 585.40784375
transcript.pyannote[156].speaker SPEAKER_00
transcript.pyannote[156].start 605.75909375
transcript.pyannote[156].end 606.46784375
transcript.pyannote[157].speaker SPEAKER_01
transcript.pyannote[157].start 607.86846875
transcript.pyannote[157].end 627.64596875
transcript.pyannote[158].speaker SPEAKER_02
transcript.pyannote[158].start 625.99221875
transcript.pyannote[158].end 630.43034375
transcript.pyannote[159].speaker SPEAKER_02
transcript.pyannote[159].start 630.68346875
transcript.pyannote[159].end 639.03659375
transcript.pyannote[160].speaker SPEAKER_01
transcript.pyannote[160].start 639.03659375
transcript.pyannote[160].end 639.13784375
transcript.pyannote[161].speaker SPEAKER_01
transcript.pyannote[161].start 640.28534375
transcript.pyannote[161].end 654.19034375
transcript.pyannote[162].speaker SPEAKER_02
transcript.pyannote[162].start 640.48784375
transcript.pyannote[162].end 640.90971875
transcript.pyannote[163].speaker SPEAKER_02
transcript.pyannote[163].start 653.26221875
transcript.pyannote[163].end 656.35034375
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 654.20721875
transcript.pyannote[164].end 654.22409375
transcript.pyannote[165].speaker SPEAKER_02
transcript.pyannote[165].start 657.17721875
transcript.pyannote[165].end 670.33971875
transcript.pyannote[166].speaker SPEAKER_01
transcript.pyannote[166].start 669.46221875
transcript.pyannote[166].end 674.54159375
transcript.pyannote[167].speaker SPEAKER_02
transcript.pyannote[167].start 670.91346875
transcript.pyannote[167].end 678.20346875
transcript.pyannote[168].speaker SPEAKER_01
transcript.pyannote[168].start 678.20346875
transcript.pyannote[168].end 691.55159375
transcript.pyannote[169].speaker SPEAKER_02
transcript.pyannote[169].start 691.21409375
transcript.pyannote[169].end 711.68346875
transcript.pyannote[170].speaker SPEAKER_01
transcript.pyannote[170].start 693.61034375
transcript.pyannote[170].end 693.99846875
transcript.pyannote[171].speaker SPEAKER_00
transcript.pyannote[171].start 693.99846875
transcript.pyannote[171].end 694.21784375
transcript.pyannote[172].speaker SPEAKER_00
transcript.pyannote[172].start 697.77846875
transcript.pyannote[172].end 697.96409375
transcript.pyannote[173].speaker SPEAKER_00
transcript.pyannote[173].start 698.04846875
transcript.pyannote[173].end 698.48721875
transcript.pyannote[174].speaker SPEAKER_00
transcript.pyannote[174].start 698.53784375
transcript.pyannote[174].end 698.68971875
transcript.pyannote[175].speaker SPEAKER_01
transcript.pyannote[175].start 709.75971875
transcript.pyannote[175].end 729.70596875
transcript.pyannote[176].speaker SPEAKER_00
transcript.pyannote[176].start 715.14284375
transcript.pyannote[176].end 715.19346875
transcript.pyannote[177].speaker SPEAKER_02
transcript.pyannote[177].start 715.19346875
transcript.pyannote[177].end 717.80909375
transcript.pyannote[178].speaker SPEAKER_00
transcript.pyannote[178].start 717.80909375
transcript.pyannote[178].end 718.97346875
transcript.pyannote[179].speaker SPEAKER_02
transcript.pyannote[179].start 718.97346875
transcript.pyannote[179].end 719.02409375
transcript.pyannote[180].speaker SPEAKER_00
transcript.pyannote[180].start 719.02409375
transcript.pyannote[180].end 719.53034375
transcript.pyannote[181].speaker SPEAKER_02
transcript.pyannote[181].start 729.30096875
transcript.pyannote[181].end 734.68409375
transcript.pyannote[182].speaker SPEAKER_01
transcript.pyannote[182].start 734.86971875
transcript.pyannote[182].end 743.37471875
transcript.pyannote[183].speaker SPEAKER_02
transcript.pyannote[183].start 740.97846875
transcript.pyannote[183].end 741.63659375
transcript.pyannote[184].speaker SPEAKER_02
transcript.pyannote[184].start 741.85596875
transcript.pyannote[184].end 747.66096875
transcript.pyannote[185].speaker SPEAKER_01
transcript.pyannote[185].start 744.85971875
transcript.pyannote[185].end 747.88034375
transcript.pyannote[186].speaker SPEAKER_02
transcript.pyannote[186].start 747.94784375
transcript.pyannote[186].end 750.32721875
transcript.pyannote[187].speaker SPEAKER_01
transcript.pyannote[187].start 749.17971875
transcript.pyannote[187].end 751.57596875
transcript.pyannote[188].speaker SPEAKER_02
transcript.pyannote[188].start 751.57596875
transcript.pyannote[188].end 752.30159375
transcript.whisperx[0].start 1.73
transcript.whisperx[0].end 12.755
transcript.whisperx[0].text 為質詢請張家俊委員謝謝主席我想請部長請農業部陳部長委員好
transcript.whisperx[1].start 22.233
transcript.whisperx[1].end 37.458
transcript.whisperx[1].text 部長早其實這一個禮拜以來我一直等著一定要今天來詢問部長因為馬鈴薯的事情引起大家非常非常的關注我現在手上有兩顆馬鈴薯部長你知道哪一顆是美國的哪一顆是台灣的嗎
transcript.whisperx[2].start 44.124
transcript.whisperx[2].end 56.027
transcript.whisperx[2].text 我沒辦法判斷啊看不清楚就是說部長都沒有辦法判斷了更何況是我們一般的民眾那現在呢我還有一顆發芽的馬鈴薯我想要請問部長現在有在呼籲說這個發芽的馬鈴薯也能吃是真的嗎
transcript.whisperx[3].start 71.021
transcript.whisperx[3].end 92.936
transcript.whisperx[3].text 至少我從來沒有說過這樣的話那我也跟委員報告就是馬鈴薯它是一個活的生物體所以在市面上看它發芽的可能就是它的儲存不適當所造成的但是不能影射是進口那本席先問一下部長您覺得發芽的馬鈴薯能吃嗎
transcript.whisperx[4].start 94.315
transcript.whisperx[4].end 121.13
transcript.whisperx[4].text 我想這要看它的條件因為相關的龍奎鹼它的形成是在發芽以後又綠化遇到光所以它會做累積但是芽體的長度跟它的龍奎鹼的濃度它是不是有非常正面的正相關因為假設假設我是一般的民眾我聽到部長這樣說聽起來好像是只有長一點點沒關係
transcript.whisperx[5].start 123.231
transcript.whisperx[5].end 147.181
transcript.whisperx[5].text 我覺得這一定要很小心不能夠誤導民眾因為如果假設他吃了他不斷的吸收說吃發芽的馬鈴薯沒關係這件事情他吃了他中毒了到底誰要負責我想我們也不應該去傳言說發芽馬鈴薯能吃我剛才說的我從來沒有說過這句話然後相對的因為龍奎減
transcript.whisperx[6].start 150.242
transcript.whisperx[6].end 160.733
transcript.whisperx[6].text 你應該知道龍奎簡是一種神經毒素它是不會經由高溫烹煮跟經由油炸它是不會消失的
transcript.whisperx[7].start 161.755
transcript.whisperx[7].end 182.065
transcript.whisperx[7].text 所以假設我們政府告訴大家說吃發芽的馬鈴薯沒有關係我想也不是政府說的喔但我絕對沒有說這樣說我想政府不會這樣說所以不能說政府說的我那天其實有看到部長也有吃馬鈴薯我現在擔憂的是說既然政府都知道
transcript.whisperx[8].start 182.825
transcript.whisperx[8].end 187.249
transcript.whisperx[8].text 有毒的馬鈴薯不能吃發芽的馬鈴薯可能有龍葵檢那為什麼還要開放就是不要這麼嚴格的檢測呢我跟委員報告我們所有的檢驗標準是沒有變的只要是發芽的馬鈴薯是絕對不能進關但是過去是只要有一個發芽馬鈴薯你就是要整櫃退啊
transcript.whisperx[9].start 206.664
transcript.whisperx[9].end 221.512
transcript.whisperx[9].text 但是你現在不是啊差別在哪裡你直接告訴我我給你一個釐清的機會我可以很清楚的講過去我們是遇到一顆巴亞的省櫃退那現在因為我們發現到過去的一些資料裡面
transcript.whisperx[10].start 222.532
transcript.whisperx[10].end 237.188
transcript.whisperx[10].text 整櫃裡面可能只有幾棵非常少數的發芽那我們讓業者可以有一個改善的機會如果他提改善計畫然後在指定的加工的地點他都發芽了他怎麼改善沒有 挑掉啊
transcript.whisperx[11].start 242.162
transcript.whisperx[11].end 265.65
transcript.whisperx[11].text 那其實這就更令人擔心了你剛才就告訴我說這個是有機物體所以一顆發芽可能其他還沒開始發芽了它已經被感染了但是肉眼看不出來發芽不是感染的不過我要跟委員報告馬鈴薯是活體的植物它本身你放在那邊你可能三天五天就發芽了所以你儲存不當就會發芽
transcript.whisperx[12].start 268.011
transcript.whisperx[12].end 282.929
transcript.whisperx[12].text 跟通關與否是無關的所以現在農業部是要變成進口商的挑菜小幫手的意思嗎不要用這種語言去處理我再問一下部長我們一年進口多少
transcript.whisperx[13].start 283.993
transcript.whisperx[13].end 297.678
transcript.whisperx[13].text 大概10應該美國的話是7萬噸差不多那全部的話是15萬噸那我就先問部長說假設是7萬噸一顆差不多150克你知道有多少顆嗎你要看一個貨櫃20萬噸差不多假設7萬噸來說至少有5億顆
transcript.whisperx[14].start 305.549
transcript.whisperx[14].end 329.975
transcript.whisperx[14].text 怎麼逐科檢查嘛 你怎麼檢查七萬噸裡面有非常多的是相關的是冷凍的調製的真正的生鮮蝕的部分是兩萬七千多噸好啦 就算兩萬七千多噸你現在告訴我有沒有可能逐科檢查那我剛才說過了在過往的紀錄裡面它是百分之零點六那接下來呢 接下來我再問今天
transcript.whisperx[15].start 333.504
transcript.whisperx[15].end 349.917
transcript.whisperx[15].text 所有的報紙頭版頭都是說美國花生要零關稅進口我想要先問一下部長到底美國花生現在ART還沒有正式生效已經開始無限量的進口了嗎
transcript.whisperx[16].start 350.799
transcript.whisperx[16].end 364.584
transcript.whisperx[16].text 沒有啊所以什麼時候會開始進口我想我們所有的所有的花生的進口有一定它的一定的期節一定的季節現在還是我先問嘛就是ART都還沒有生效為什麼要提前棄手呢有沒有什麼時候要進口因為大家擔憂的不得了就是我們ART還沒有生效前應該要繼續維持關稅配額一年五二三五嘛我們一直維持的啊那是媒體在操作的啊
transcript.whisperx[17].start 380.149
transcript.whisperx[17].end 395.077
transcript.whisperx[17].text 所以你們預計是什麼時候我想現在目前我們整個ART的簽署的內容是我們是確定的但是整個ART本身它的一個法律的框架架構上面美方正在尋求新的一個法律架構
transcript.whisperx[18].start 395.717
transcript.whisperx[18].end 419.937
transcript.whisperx[18].text 所以他還不會正式實施在台灣不會正式實施也會進到立院去做相關的一個確認跟審查才會正式的實施現在所有的花生農都非常擔心本來你告訴本席我記得3月的時候我在總諮詢也問過你說花生進口要三次啊那你告訴本席說美國花生進來
transcript.whisperx[19].start 421.878
transcript.whisperx[19].end 438.708
transcript.whisperx[19].text 競爭的是阿根廷跟印度的花生你是不是有這樣告訴過印度阿根廷跟巴西跟巴西是那你覺得美國花生進來他會乖乖的只跟阿根廷印度巴西的花生競爭不跟台灣的花生競爭嗎
transcript.whisperx[20].start 440.725
transcript.whisperx[20].end 464.24
transcript.whisperx[20].text 所以我要跟委員說明我們要看總需求量當你一個產品進口的時候那原來的進口是印度阿根廷巴西佔的96%然後美國才不到1%所以它進來一定會先取代或者是更競爭但是它的價格優勢是我們台灣的三倍啊它的價格優勢是我們台灣的三倍我再問一個重點假設
transcript.whisperx[21].start 466.921
transcript.whisperx[21].end 487.818
transcript.whisperx[21].text 食品加工廠他進口了美國的花生他做出來的這個食品加工是Made in Taiwan還是會標示是美國花生做我相信產地一定會標示產地一定會標示產地這標籤是規定的本席去查了他說他會寫Made in Taiwan
transcript.whisperx[22].start 489.21
transcript.whisperx[22].end 503.483
transcript.whisperx[22].text 所以呢這是現在的使館法規定的他進口來之後他在台灣加工他就變成Made in Taiwan這才是真正的息產地我告訴你那個叫做實質轉型那這個部分我想我們也實質轉型是不是息產地
transcript.whisperx[23].start 506.4
transcript.whisperx[23].end 516.324
transcript.whisperx[23].text 我想不能用這樣的角度去看這個問題所以這個才是你要重視的我要提醒的我們會重視整個台灣的花生我今天不是要檢討你我是希望你要看到問題在哪裡是不是能夠標示假設是美國來的你就不能寫Made in Taiwan你就要寫美國產甚至台灣本地的花生你要本地產然後當初3月5問你的時候你告訴我說
transcript.whisperx[24].start 534.77
transcript.whisperx[24].end 536.933
transcript.whisperx[24].text 轉做價格會提高現在那時候我就提醒你我就提醒你說既然美國花生的優勢是我們價格是我們的三倍我們花生轉做現在轉做金額是多少
transcript.whisperx[25].start 553.354
transcript.whisperx[25].end 570.935
transcript.whisperx[25].text 我告訴你我們現在花生轉作金額是一公頃三萬五我知道那那個時候我就說我們如果要跟美國有競爭的這個空間我們至少轉作金要提高三倍吧那三萬五乘以三倍是多少
transcript.whisperx[26].start 571.856
transcript.whisperx[26].end 591.308
transcript.whisperx[26].text 10到5千這樣才有辦法穩定軍心嘛你穩定所有花生農的心你昨天農業部出來說可能會有三成的農民三成的農民影響你再去三成去種麻豆去種對不起喔委員我必須要再澄清一次齁我們昨天胡市長講的兩成到三成是
transcript.whisperx[27].start 592.508
transcript.whisperx[27].end 607.202
transcript.whisperx[27].text 純粹用價格的角度而且沒有政府的支持之下可能會有這樣的影響但是農業部絕對不會沒有作為所以我們有非常多的配套措施會去啟動來支持我們的花式博量產業那你告訴我是什麼配套措施
transcript.whisperx[28].start 607.942
transcript.whisperx[28].end 618.31
transcript.whisperx[28].text 好我第一個部分我想我們整個配料因為我們台灣我本身的仙甲的部分是以這個產品為主所以我們會啟動所謂的仙甲的一個收購那另外我們會啟動區域型的烘乾的中心讓農民免疫這樣的一個烘乾還有相關的基礎產品你這個問題就是沒有辦法解決問題嘛
transcript.whisperx[29].start 630.76
transcript.whisperx[29].end 654.58
transcript.whisperx[29].text 它已經冒不出去了你還在幫它烘乾它的價格就已經沒有競爭力了怎麼烘乾烘乾了要賣誰我覺得你如果這樣講的話其實台灣的農業沒有那麼脆弱台灣農業是有韌性的部分透過我們的引導我們可以讓台灣的花生維持一定的品牌我們市佔率是75%我知道 你知道市佔率75%
transcript.whisperx[30].start 657.282
transcript.whisperx[30].end 664.05
transcript.whisperx[30].text 是我們多少農民 多少農民努力出來的才有75% 結果你現在要無...這是台灣花生的一個特色這是台灣花生的一個特色所以我們希望別人...我們絕對會...
transcript.whisperx[31].start 677.205
transcript.whisperx[31].end 699.3
transcript.whisperx[31].text 那怎麼辦呢我想我們會針對台灣花生做一個特殊的一個台灣花生的一個品牌然後我們也會去爭取所有的國外進口的花生它的原產地一定要標它的原產地不能標台灣這是你在這裡承諾本席的喔我是真的期待你一定要做到因為這個不落實影響的是很多家庭我想我們會跟昨天那個
transcript.whisperx[32].start 700.66
transcript.whisperx[32].end 711.686
transcript.whisperx[32].text 農業部表示說要輔導他們轉型種別的作物你知道嗎所有老農他種了一輩子他種土豆他種花生他就只會種花生我想不要動不動就說我們的老農我們所有農業不是只有老農在做我知道但是老農比較脆弱我們也會來協助我們一定
transcript.whisperx[33].start 720.791
transcript.whisperx[33].end 745.57
transcript.whisperx[33].text 我希望說委員在地方跟我們在農業部這邊一起來合作讓我們的產業能夠繼續往前走這才是重點是你自己說要合作的呀那你要下來啊你不下來你至少要派署長下來吧我想我們很樂意跟地方一起努力去做這樣的事情但是也不要透過任何的政治操作去做這樣的一個問題我跟你說我最不想要這個政治操作我只想要他們能夠安全
transcript.whisperx[34].start 748.033
transcript.whisperx[34].end 750.685
transcript.whisperx[34].text 然後可以把這個產業保護住我們可以一起努力把這個產業做到好 謝謝