蔬果的分級制度在產銷上提供一套標準，使消費者在選擇優良產品的同時，給予生產者更高的收入。目前市場上普遍的採用一較不客觀且略帶模糊的分級標準，且該標準僅止於外觀與口味上的分類，並未針對蔬果的營養成分、口感或是新鮮度等層面進行分級。本研究希望利用蔬果的光學參數，討論建立此一分級制度的可能性，本研究選擇市面上較具經濟價值的蘋果為主要研究目標。目前針對蘋果的分級，多以外觀大小、色澤等級與缺陷檢測為主，除去一般目測的方法，多以光學方法進行檢測分類，如CCD進行影像分析、高光譜影像分析或是穩態光對蘋果的反射光譜分析，配合統計挑選出蘋果缺陷的部位，但上述仍限於透過蘋果外表及缺陷進行分類，沒有深入討論蘋果的營養價值。本研究採頻域光子遷移系統(Frequency Domain Photon Migration, FDPM)量測蘋果，偵測架構分為長距離與短距離量測，長距離量測以擴散理論做為正向模型；短距離量測則以蒙地卡羅法結合人工類神經網路建立正向模型以計算光學參數。此外，也整合侵入式與非侵入式量測，討論蘋果在不同的生理性質下，其光學參數的變化。本研究也搭配積分球與逆疊加運算系統(inverse adding doubling method, IAD)量測蘋果切片樣本，配合FDPM系統的測試結果一併討論。比起大多數以穩態光漫反射光譜對量測蘋果，僅討論反射光譜與穿透光譜的變化，本研究能同時提供蘋果的吸收係數與縮減散射係數，更準確的反應蘋果生理特性的變化。針對已知光學參數之仿體的光學參數計算，設定一誤差10%作為標準，計算誤差必須小於10%才可將系統視為可用，而本研究中FDPM系統於仿體的光學參數計算上，誤差最高不超過10%。本研究中，蘋果區分為兩大類個別討論其生理性質─空間上與時間上的變化。隨著空間與時間的變化，分別透過不同區域的組織在結構與發色團含量的變化，以及同一組織隨時間不同產生的結構與發色團含量的變化，討論光學參數如何反應出蘋果生理特性的差異，進而理解營養價值的不同與新鮮度的變化對光學參數的影響。實驗針對分組後的蘋果，結合非侵入式與侵入式FDPM量測，並輔以IAD系統，討論結構與發色團含量的改變對光學參數產生的影響。另外，透過短距離FDPM量測，利用蘋果於不同組織的性質差異，提供新鮮度的參考。不同生理性質對光學參數產生不同的影響，本研究透過分析光學參數的變化，以判斷蘋果的營養價值、口感與新鮮度的變化，並期望以此技術建立篩選機制。

Currently, grading of fruits and vegetables use less objective grading standards. In our study, we hope that using an optical properties, which is absorption coefficients and reduce scattering coefficients, of apple fruits establish the new grading system. This system can grade apple fruits according to nutrition and freshness. Compared with measurement of steady state, we measure an apple fruits by Frequency Domain Photon Migration system (FDPM), the FDPM system provide an optical properties of apple fruits which accurately reflect the physiological characteristics of apple fruits. The calculation error of optical properties of FDPM system is less than 10% which is set as the standard. We discuss an influences on optical properties when apple’s structure and chromophore content changed. Therefore, the nutrition and freshness of apple fruits can be judged by analyzing an optical properties.

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