臺灣博碩士論文加值系統

本研究之目的為建立白米內部品質在近紅外光譜短波段(750-1100nm)之檢測模式，並探討應用於快速檢測動態單粒白米之內部品質之可行性。本研究之白米內部品質以水分為指標。
本研究以連續波段之近紅外光譜儀進行靜態單粒白米含水率之檢測，並應用小型光纖光譜儀(S1024DW，Ocean)和實驗室型分光光譜儀(FOSS NIRS 6500)兩種儀器進行光譜量測工作。小型光纖光譜儀反射式實驗中(642-1217nm)，利用部份最小平方差迴歸(PLSR)所得之迴歸式之判定係數R2 = 0.966，標準校正誤差(SEC) = 0.899。實驗室型分光光譜儀反射式實驗中(全波段400-2500nm)，以原始光譜進行部分最小平方差迴歸(PLSR)所得到之檢量線判定係數R2 = 0.981，標準校正誤差(SEC) = 0.543。小型光纖光譜儀穿透式實驗中(部份波段642-1217nm)以部分最小平方差迴歸(PLSR)所得到之含水率檢量線判定係數R2 = 0.968，標準校正誤差(SEC) = 0.878。
單粒白米動態檢測系統係應用近紅外光多光譜影像系統在910、960和1014nmn三個波長之組合來檢測移動中單粒白米樣本之含水率。本系統以部分最小平方差迴歸(PLSR)所得之含水率檢量線之判定係數R2 = 0.651，標準校正誤差(SEC) = 2.518。
應用近紅外光光譜預測單粒白米含水率之效果以靜態方式以全波段反射式光纖所得到之效果為較佳。近紅外光多光譜影像系統在動態檢測含水率之結果還有改善空間，但確具有運用於生產線上檢測動態單粒白米內部品質之可行性。

The objective of this study was to evaluate the feasibility of applying near infrared technology for establishing regression model to detect internal qualities of single rice kernels. The short near infrared wavelength range from 750 nm to 1100 nm was used to develop an on-line moisture content detecting system for single rice kernels.
NIR spectrophotometers of S1024DW (Ocean Optics) and FOSS NIRS 6500 (Foss NIRSystems) with specially designed fiber-optics were used to measure the NIR spectra of stationary rice kernels. The partial least squares regression (PLSR) was adopted for predicting rice moisture content by analyzing reflectance spectra and transmittance spectra. The coefficient of determination (R2) and standard error of calibration (SEC) for S1024DW reflectance spectra, FOSS NIRS 6500 reflectance spectra and S1024DW transmittance spectra were respectively 0.966 & 0.899, 0.981& 0.543, and 0.968 & 0.878.
The near infrared multi-spectral imaging system with detection wavelength range at 910 nm, 960 nm and 1014 nm was adopted for on-line moisture content measurement of running single rice kernels. The coefficient of determination (R2) and standard error of calibration (SEC) obtained by PLSR were respectively 0.651 and 2.518.
The predictions of moisture content of stationary single rice kernels are better in the system as the reflection spectra were adopted instead of transmittance spectra at near infrared wavelength range from 750nm to 2500nm. Further improvement of the near infrared multi-spectral imaging system developed in this study is required for future implementing this system in the on-line rice milling industry.

誌 謝 i
摘 要 ii
Abstract iii
目錄 iv
圖目錄 vii
表目錄 ix
第一章 前言 1
1.1前言 1
1.2 研究目的 2
第二章 文獻探討 3
2.1 稻米之介紹 3
2.2 近紅外光吸收光譜之理論基礎 4
2.2.1 吸收光譜的基本原理 4
2.2.2近紅外光譜的定量分析 11
2.2.3 近紅外光光譜校正線之建立流程 14
2.2.4 近紅外光譜資料之迴歸模式 16
2.2.5 校正線性能評估之相關定義 19
2.2.6 各成分對近紅外光之特徵波長 21
2.3 近紅外光之應用與研究 23
2.3.1 應用近紅外光光譜分析穀物成分的研究 23
2.3.2 應用近紅外光多光譜影像的研究 27
第三章 實驗設備與方法 29
3.1 實驗樣本 30
3.2儀器設備 31
3.2.1靜態單粒白米品質檢測儀器設備 31
3.2.2 動態單粒白米之品質檢測儀器設備 36
3.3實驗流程 41
3.3.1 靜態單粒白米品質檢測實驗流程 41
3.3.2 動態單粒白米品質檢測實驗流程 42
3.4化學分析 46
第四章 結果與討論 47
4.1 靜態單粒白米含水率檢測實驗結果 48
4.1.1小型光纖光譜儀(S1024DW)反射式實驗 48
4.1.2 實驗室型分光光譜儀(FOSS NIRS 6500)反射式實驗 53
4.1.3 小型光纖光譜儀(S1024DW)穿透式實驗 56
4.2 動態單粒白米之含水率檢測實驗結果 63
4.2.1 動態近紅外光多光譜影像系統 63
4.3靜態單粒白米與動態單粒米含水率實驗結果之比較 73
第五章 結論與建議 76
5.1 結論 76
5.2 建議 77
參考文獻 80

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