陳世銘Chen, Suming臺灣大學:生物產業機電工程學研究所廖信凱Liao, Hsin-KaiHsin-KaiLiao2010-05-052018-07-102010-05-052018-07-102009U0001-1808200910285900http://ntur.lib.ntu.edu.tw//handle/246246/180283水果採摘的考量，不外乎是判斷水果是否成熟、遭受病蟲害的破壞或感染。傳統判斷水果是否採摘是靠果農的經驗，而判斷的主要依據就是水果的外觀及直覺。近年來利用近紅外光在水果內部品質的檢測研究甚多，其是一種非破壞性且快速的檢測方式，並可獲得完整的檢測資訊。本研究利用近紅外光光譜來檢測桃太郎番茄 (Lycopericon esculentum) 中茄紅素之含量，作為預測番茄成熟度的指標，未來可結合水果採收機器人，在採摘番茄時，除了以影像處理方式判斷外觀外，還可利用茄紅素成份作為判斷成熟的指標，增加判定採摘之正確性。本研究以機械視覺拍攝番茄底部之彩色影像，將影像中之RGB色彩系統經計算後，轉換為L*a*b*色彩系統，利用a*/b*指標來取代果農主觀判定之番茄成熟度，以降低其成熟度判斷之誤差。在量測茄紅素含量部分，利用FOSS NIRS 6500 RCA快速成份分析儀 (rapid content analyzer) 進行番茄茄紅素萃取液之量測，取490 nm之吸收度建立茄紅素檢量線，其SEE (standard error of estimate)及r (coefficient of correlation)可達0.216及0.999。本研究利用不同的分光光度計量測番茄完整果，分別為實驗室型分光光度計搭配光纖模組(FOSS NIRS 6500)，實驗室型分光光度計搭配快速成份分析儀(FOSS NIRS 6500 RCA) ，以及線上型分光光度計(FOSS On-Line NIRS 6500)，其分別量測A, B, C三項不同的定義區域。在番茄完整果茄紅素之MPLSR分析中，以FOSS On-Line NIRS 6500量測C區域之光譜，在可見光一次微分光譜，可得最佳模式，其rc可達0.960、SEC (standard error of calibration) = 0.53 ppm；在近紅外光特徵波段部分，以光纖模組(FOSS NIRS 6500)量測A區域之光譜可得最佳模式，其rc為0.918、SEC = 0.76 ppm。此成果提供了快速、非破壞、預測能力佳的檢測方式，可應用於採收時輔助判斷未採摘番茄之成熟度。The criterion for the fruit harvesting depends on the maturity of the fruit, blight and infection. The experiences of farmers based on the appearance of the fruit and the intuition of them are usually employed to evaluate the harvesting time for fruits. Near infrared spectroscopy, a non-destructive and rapid measurement, was used to inspect the fruit internal quality with complete spectrum information in recent years. The lycopene content of tomato (Lycopericon esculentum) was measured using near infrared spectroscopy to serve as an index of the degree of tomato maturity. Therefore, both the lycopene content and the appearance images of tomatoes can be integrated as the indices to evaluate the degree of tomato maturity for the automatic fruit harvesting system to assure the accuracy of the determination for the maturity. The color images of tomatoes were acquired by the machine vision and converted the RGB values to L*a*b* color system. The subjective judgement by farmers could be improved using the index, a*/b*, to evaluate the degree of tomato maturity. The lycopene content of the tomato was determined by measuring the extraction of tomato juice using FOSS NIRS 6500 RCA (rapid content analyzer). The calibration of lycopene content was established by the absorption of 490 nm. The standard error of estimate (SEE) was 0.216, and the coefficient of correlation (r) was 0.999. Different spectrophotometers (FOSS NIRS 6500 with fiber optics, FOSS On-Line NIRS 6500, and FOSS NIRS 6500 RCA) were used to obtain the spectra from the bottoms of intact tomatoes at the areas A, B, and C defined for different instrument attachments. The best MPLSR (multiple partial least square regression) result of the intact tomato fruit was measured using FOSS On-Line NIRS 6500 (Region C) with the first derivative pre-treatment in visible region, and rc = 0.960, SEC (standard error of calibration) = 0.53 ppm. The best MPLSR result of the spectra measured by FOSS NIRS 6500 with fiber optics (Region A) was rc = 0.918 and SEC = 0.76 ppm in the near infrared region. In summary, the rapid, non-destructive inspection with excellent prediction was successfully established in determining of the degree of maturity during the fruit harvesting.口試委員會審定書 i 謝 ii 要 ivbstract v 錄 vii目錄 ix目錄 xi一章 前言 1.1 前言 1.2 研究目的 2二章 文獻探討 3.1 番茄成熟度之探討 3.1.1 生理現象 3.1.2 番茄成熟度與內部成份關係探討 4.2 近紅外光技術之應用 8.2.1 近紅外光光譜理論 8.2.2近紅外光光譜於農產品檢測 14.3 近紅外光於番茄茄紅素之檢測 15三章 材料與方法 17.1 分光光度計設備 17.1.1實驗室型分光光度計（FOSS NIRS 6500） 17.1.2 快速成份分析儀（FOSS NIRS 6500 RCA） 18.1.3 線上型分光光度計（FOSS On-Line NIRS 6500） 19.2 化學分析儀器 20.2.1 高效液相層析儀（HPLC） 20.2.2 超音波洗淨器 21.2.3 磁石攪拌器 21.3 實驗步驟 21.3.1實驗材料準備 21.3.2 實驗步驟流程 22.3.2.1 萃取溶液中茄紅素檢量線之建立 22.3.2.2 番茄成熟度之影像量測與分析 23.3.2.3 番茄完整果及果泥光譜量測 26.3.2.4 番茄萃取溶液之光譜量測 28.4 光譜處理 29.4.1 光譜平滑化處理 29.4.2 光譜微分處理 30.4.3 交叉驗證模式 31.4.4 樣本分組 31.4.5 最佳波段之選擇 32.5光譜分析模式及判斷 32.5.1 MLR分析模式 34.5.2 MPLSR分析模式 34四章 結果與討論 35.1 以影像處理分析番茄成熟度與茄紅素之關係 35.2 茄紅素光譜檢測分析結果 37.2.1 建立茄紅素萃取溶液檢量線之分析結果 38.2.2 番茄萃取溶液茄紅素之量測 43.3 光譜分析之樣本分組及前處理 44.4 番茄果泥吸收光譜分析結果 46.4.1 B量測區域分析結果 46.4.2 C量測區域分析結果 52.5 番茄完整果吸收光譜分析結果 58.5.1 A量測區分析結果 58.5.2 B量測區分析結果 64.5.3 C量測區分析結果 70.6 番茄成熟度預測之分析結果 75五章 結論與建議 77.1 結論 77.2 建議 78考文獻 79application/pdf2038493 bytesapplication/pdfen-US近紅外光光譜番茄成熟度茄紅素Near InfraredSpectraTomatoDegree of MaturityLycopenethesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/180283/1/ntu-98-R95631001-1.pdf