iVOD / 168946

Field Value
IVOD_ID 168946
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/168946
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 2026-04-29T11:31:18+08:00
結束時間 2026-04-29T11:36:44+08:00
影片長度 00:05:26
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/6301273cb2dfee843b8bdebc557527744294381b535652e618096c5e05de57c6eb30719eee88c9bd5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 賴士葆
委員發言時間 11:31:18 - 11:36:44
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 0.04784375
transcript.pyannote[0].end 0.82409375
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 1.24596875
transcript.pyannote[1].end 2.24159375
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 10.27409375
transcript.pyannote[2].end 12.77159375
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 13.04159375
transcript.pyannote[3].end 14.25659375
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 20.33159375
transcript.pyannote[4].end 20.71971875
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 20.71971875
transcript.pyannote[5].end 20.73659375
transcript.pyannote[6].speaker SPEAKER_00
transcript.pyannote[6].start 21.02346875
transcript.pyannote[6].end 21.79971875
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 22.69409375
transcript.pyannote[7].end 25.36034375
transcript.pyannote[8].speaker SPEAKER_00
transcript.pyannote[8].start 26.23784375
transcript.pyannote[8].end 28.16159375
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 28.87034375
transcript.pyannote[9].end 31.70534375
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 32.05971875
transcript.pyannote[10].end 33.30846875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 34.05096875
transcript.pyannote[11].end 35.14784375
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 36.24471875
transcript.pyannote[12].end 36.27846875
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 36.27846875
transcript.pyannote[13].end 38.65784375
transcript.pyannote[14].speaker SPEAKER_01
transcript.pyannote[14].start 39.24846875
transcript.pyannote[14].end 46.50471875
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 46.82534375
transcript.pyannote[15].end 47.21346875
transcript.pyannote[16].speaker SPEAKER_01
transcript.pyannote[16].start 47.21346875
transcript.pyannote[16].end 47.65221875
transcript.pyannote[17].speaker SPEAKER_01
transcript.pyannote[17].start 47.93909375
transcript.pyannote[17].end 52.19159375
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 52.19159375
transcript.pyannote[18].end 52.22534375
transcript.pyannote[19].speaker SPEAKER_01
transcript.pyannote[19].start 52.22534375
transcript.pyannote[19].end 52.24221875
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 52.24221875
transcript.pyannote[20].end 52.27596875
transcript.pyannote[21].speaker SPEAKER_01
transcript.pyannote[21].start 53.11971875
transcript.pyannote[21].end 58.51971875
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 58.03034375
transcript.pyannote[22].end 83.89971875
transcript.pyannote[23].speaker SPEAKER_01
transcript.pyannote[23].start 58.67159375
transcript.pyannote[23].end 58.94159375
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 84.33846875
transcript.pyannote[24].end 94.91909375
transcript.pyannote[25].speaker SPEAKER_00
transcript.pyannote[25].start 95.59409375
transcript.pyannote[25].end 97.97346875
transcript.pyannote[26].speaker SPEAKER_01
transcript.pyannote[26].start 97.12971875
transcript.pyannote[26].end 97.66971875
transcript.pyannote[27].speaker SPEAKER_01
transcript.pyannote[27].start 97.97346875
transcript.pyannote[27].end 113.29596875
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 98.73284375
transcript.pyannote[28].end 100.26846875
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 109.22909375
transcript.pyannote[29].end 110.54534375
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 111.67596875
transcript.pyannote[30].end 116.28284375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 116.60346875
transcript.pyannote[31].end 122.03721875
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 122.13846875
transcript.pyannote[32].end 126.98159375
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 126.30659375
transcript.pyannote[33].end 145.86471875
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 132.12846875
transcript.pyannote[34].end 132.38159375
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 140.83596875
transcript.pyannote[35].end 141.96659375
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 142.43909375
transcript.pyannote[36].end 142.75971875
transcript.pyannote[37].speaker SPEAKER_00
transcript.pyannote[37].start 143.02971875
transcript.pyannote[37].end 143.23221875
transcript.pyannote[38].speaker SPEAKER_00
transcript.pyannote[38].start 143.26596875
transcript.pyannote[38].end 152.85096875
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 146.08409375
transcript.pyannote[39].end 146.80971875
transcript.pyannote[40].speaker SPEAKER_01
transcript.pyannote[40].start 152.85096875
transcript.pyannote[40].end 152.90159375
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 152.90159375
transcript.pyannote[41].end 152.96909375
transcript.pyannote[42].speaker SPEAKER_01
transcript.pyannote[42].start 152.96909375
transcript.pyannote[42].end 153.62721875
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 153.03659375
transcript.pyannote[43].end 153.05346875
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 153.08721875
transcript.pyannote[44].end 153.10409375
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 153.12096875
transcript.pyannote[45].end 153.23909375
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 153.25596875
transcript.pyannote[46].end 153.37409375
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 153.62721875
transcript.pyannote[47].end 154.65659375
transcript.pyannote[48].speaker SPEAKER_01
transcript.pyannote[48].start 153.69471875
transcript.pyannote[48].end 158.94284375
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 157.64346875
transcript.pyannote[49].end 158.95971875
transcript.pyannote[50].speaker SPEAKER_01
transcript.pyannote[50].start 158.95971875
transcript.pyannote[50].end 158.97659375
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 158.97659375
transcript.pyannote[51].end 159.14534375
transcript.pyannote[52].speaker SPEAKER_01
transcript.pyannote[52].start 159.14534375
transcript.pyannote[52].end 173.40471875
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 171.97034375
transcript.pyannote[53].end 173.43846875
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 173.43846875
transcript.pyannote[54].end 173.65784375
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 173.65784375
transcript.pyannote[55].end 173.69159375
transcript.pyannote[56].speaker SPEAKER_00
transcript.pyannote[56].start 173.77596875
transcript.pyannote[56].end 173.97846875
transcript.pyannote[57].speaker SPEAKER_01
transcript.pyannote[57].start 173.97846875
transcript.pyannote[57].end 174.02909375
transcript.pyannote[58].speaker SPEAKER_00
transcript.pyannote[58].start 174.02909375
transcript.pyannote[58].end 174.09659375
transcript.pyannote[59].speaker SPEAKER_01
transcript.pyannote[59].start 174.09659375
transcript.pyannote[59].end 174.50159375
transcript.pyannote[60].speaker SPEAKER_00
transcript.pyannote[60].start 174.50159375
transcript.pyannote[60].end 174.82221875
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 174.82221875
transcript.pyannote[61].end 174.97409375
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 174.97409375
transcript.pyannote[62].end 175.00784375
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 175.00784375
transcript.pyannote[63].end 175.02471875
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 175.02471875
transcript.pyannote[64].end 175.78409375
transcript.pyannote[65].speaker SPEAKER_00
transcript.pyannote[65].start 176.77971875
transcript.pyannote[65].end 177.96096875
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 178.16346875
transcript.pyannote[66].end 179.76659375
transcript.pyannote[67].speaker SPEAKER_00
transcript.pyannote[67].start 180.34034375
transcript.pyannote[67].end 184.39034375
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 184.96409375
transcript.pyannote[68].end 186.06096875
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 187.69784375
transcript.pyannote[69].end 189.26721875
transcript.pyannote[70].speaker SPEAKER_00
transcript.pyannote[70].start 190.00971875
transcript.pyannote[70].end 190.97159375
transcript.pyannote[71].speaker SPEAKER_00
transcript.pyannote[71].start 191.57909375
transcript.pyannote[71].end 193.11471875
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 193.30034375
transcript.pyannote[72].end 196.55721875
transcript.pyannote[73].speaker SPEAKER_00
transcript.pyannote[73].start 196.84409375
transcript.pyannote[73].end 199.57784375
transcript.pyannote[74].speaker SPEAKER_01
transcript.pyannote[74].start 196.94534375
transcript.pyannote[74].end 197.45159375
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 197.92409375
transcript.pyannote[75].end 208.26846875
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 206.26034375
transcript.pyannote[76].end 212.79096875
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 210.73221875
transcript.pyannote[77].end 213.73596875
transcript.pyannote[78].speaker SPEAKER_00
transcript.pyannote[78].start 213.07784375
transcript.pyannote[78].end 226.44284375
transcript.pyannote[79].speaker SPEAKER_01
transcript.pyannote[79].start 226.44284375
transcript.pyannote[79].end 226.45971875
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 226.96596875
transcript.pyannote[80].end 226.99971875
transcript.pyannote[81].speaker SPEAKER_01
transcript.pyannote[81].start 226.99971875
transcript.pyannote[81].end 235.09971875
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 235.25159375
transcript.pyannote[82].end 244.02659375
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 244.02659375
transcript.pyannote[83].end 245.27534375
transcript.pyannote[84].speaker SPEAKER_00
transcript.pyannote[84].start 245.57909375
transcript.pyannote[84].end 245.61284375
transcript.pyannote[85].speaker SPEAKER_01
transcript.pyannote[85].start 245.61284375
transcript.pyannote[85].end 245.62971875
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 245.62971875
transcript.pyannote[86].end 249.96659375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 249.96659375
transcript.pyannote[87].end 257.74596875
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 258.38721875
transcript.pyannote[88].end 263.50034375
transcript.pyannote[89].speaker SPEAKER_01
transcript.pyannote[89].start 263.68596875
transcript.pyannote[89].end 267.93846875
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 268.24221875
transcript.pyannote[90].end 270.38534375
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 271.29659375
transcript.pyannote[91].end 272.03909375
transcript.pyannote[92].speaker SPEAKER_00
transcript.pyannote[92].start 272.03909375
transcript.pyannote[92].end 273.30471875
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 274.18221875
transcript.pyannote[93].end 277.13534375
transcript.pyannote[94].speaker SPEAKER_00
transcript.pyannote[94].start 277.92846875
transcript.pyannote[94].end 282.67034375
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 284.03721875
transcript.pyannote[95].end 295.96784375
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 295.96784375
transcript.pyannote[96].end 296.84534375
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 296.84534375
transcript.pyannote[97].end 296.89596875
transcript.pyannote[98].speaker SPEAKER_01
transcript.pyannote[98].start 297.11534375
transcript.pyannote[98].end 323.10284375
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 303.56159375
transcript.pyannote[99].end 303.69659375
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 323.99721875
transcript.pyannote[100].end 325.97159375
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 325.65096875
transcript.pyannote[101].end 325.87034375
transcript.whisperx[0].start 0.069
transcript.whisperx[0].end 1.31
transcript.whisperx[0].text 有關於花生的零關稅
transcript.whisperx[1].start 26.451
transcript.whisperx[1].end 51.58
transcript.whisperx[1].text 為什麼這個新聞最近才出來當初行政院跟立法院報告ART的時候都沒講咧我們在公告的時候我們當初開記者會的時候就已經有提到零關稅的部分這個是有提到的零關稅 花生還有部分的乳製品那為什麼最近才講這個題目呢
transcript.whisperx[2].start 53.367
transcript.whisperx[2].end 61.49
transcript.whisperx[2].text 我也不清楚為什麼最近突然被特定的一些媒體去報導這樣的問題不是特定的啦 因為大家的關係 說按照脫刀雖然美國這占1% 但是不要忘了配額內 它是25%的關稅配額外 每公斤64塊這個東西 難怪雲林縣它最大化身產地它這個縣長 大家起來放炮啊那我現在
transcript.whisperx[3].start 76.095
transcript.whisperx[3].end 94.74
transcript.whisperx[3].text 就問你 你知不知道世貿組織叫WTO是允許各國進行農業的保護而且允許不扭曲的貿易或者對貿易扭曲的一些措施這裡面有綠鄉的政策有藍鄉的政策等等的 就是
transcript.whisperx[4].start 95.66
transcript.whisperx[4].end 118.864
transcript.whisperx[4].text 你知不知道這個事我了解這個所謂的農業可以保護啊我們可以部分的項目我們可以允許所謂的關稅內的配額TRQ的部分也可以啟動就是特別關稅特別防疫SSG的部分這個我了解 非常了解為什麼廁所呢 為什麼花式去把它廁所掉呢老實講世界各國對農產品幾乎都很少零關稅的啦
transcript.whisperx[5].start 122.945
transcript.whisperx[5].end 127.207
transcript.whisperx[5].text 怎麼會這麼大方就零關稅我想大部分我想委員是一個非常明理的委員我們零關稅不一定說就不好有一些產品是當作我們的原料的部分零關稅反而是對我們有幫助像黃豆玉米小麥我剛剛說零關稅因為我實際上有些人在問你
transcript.whisperx[6].start 147.293
transcript.whisperx[6].end 173.046
transcript.whisperx[6].text 你對這個花生零關稅已經雲林縣這樣大聲起舞你到底有什麼因應的措施我想我們的產業的部分我剛才說的我們不會放任你有沒有來問你喔你有沒有編預算對於這些零關稅的農產品保護有沒有對 農安基金300億就是在處理這些我們必須長期關切對產業影響的這些而且我們要讓這個產業做生意300億 張俊雄你知道這個人吧
transcript.whisperx[7].start 177.084
transcript.whisperx[7].end 183.897
transcript.whisperx[7].text 張俊雄以前的行政院長他那時候為了因為台灣要加入WTO就拚了一千億因應
transcript.whisperx[8].start 187.885
transcript.whisperx[8].end 213.246
transcript.whisperx[8].text 市貿 加入市貿所產生的特別是農業方面的這種補助基金就變成一千億啦你現在講三百億 那是一千億啦在當時的WTO農業的這些競爭力跟現在的競爭力是不可同日而語我們也會積極的去跟產業協調 你好好面對這個問題啦這個大家要對這個很好 我想我們一起來努力我們要看到發芽的馬鈴薯啊 你現在是交給
transcript.whisperx[9].start 216.168
transcript.whisperx[9].end 242.065
transcript.whisperx[9].text 檢驗一顆一顆檢驗是交給個別工廠加工廠目前加工廠只有兩家耶然後你針對這個要屬科檢驗誰來確定它可以做到屬科檢驗我跟委員報告第一個部分齁這個加工廠並不是只有兩家這個就是說其實我們有看到我們看到發芽但是它還是農會檢沒有超標喔超標也是餘地退貴喔
transcript.whisperx[10].start 242.745
transcript.whisperx[10].end 269.154
transcript.whisperx[10].text 我先問你 你怎麼確定他們有沒有驗你怎麼確定這家紅茶 不管幾家你怎麼確定他有檢驗因為我們的 我們是整櫃封簽運到指定的地點以後由檢疫人員督導之下開櫃然後他們做就是輸用帶的自動選別選別完合格的我們才發檢疫合格證他的正式的入關所以這個過程都還在邊境檢疫
transcript.whisperx[11].start 271.345
transcript.whisperx[11].end 282.495
transcript.whisperx[11].text 第三個 最後一個小問題ART3.3條第四段他要加速MIL就是溶液殘留的容量
transcript.whisperx[12].start 284.697
transcript.whisperx[12].end 304.394
transcript.whisperx[12].text 簡單來講就是幫美國的藥商 如孟山都、丹麥爾、量身病照的打造到人家講話好不好你可以跟我們講一下台灣被迫用美國的標準USBA或者是FDA不過我想這是不正確的訊息第一個齁 這個我要存你版本是食藥組在訂第二個部位...USBA的標準...翻譯給我來
transcript.whisperx[13].start 305.635
transcript.whisperx[13].end 322.725
transcript.whisperx[13].text MIL是食藥組在訂的第二個就是說農藥殘留標準是跟我們的實用的攝取量是有關係的就是ADI整個的ADI的概念它跟不同的國家都不一樣所以我們是參考國際標準但是我們也會參考我們的實用的一個習慣好 謝謝賴世寶