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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 陳世銘(Suming Chen) | |
dc.contributor.author | Yi-Tzu Shen | en |
dc.contributor.author | 沈怡慈 | zh_TW |
dc.date.accessioned | 2021-06-16T09:45:31Z | - |
dc.date.available | 2025-08-17 | |
dc.date.copyright | 2020-09-17 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-08-17 | |
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Hughes, K. Yabumoto and W.G. Jennings. 1977. Quality of cantaloupe muskmelons : variability and attributes. Scientia Horticulturae. 6: 59-70. Yin, S., G. Wang and X. Yang. 2014. Robust PLS approach for KPI-related prediction and diagnosis against outliers and missing data. International Journal of Systems Science. 45(7): 1375-1382. Yang, Y. and C. Yu. 2015. Prediction models based on multivariate statistical methods and their applications for predicting railway freight volume. Neurocomputing. 158: 210-215. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/59927 | - |
dc.description.abstract | 近紅外光光譜是一種非破壞性的檢測方式,其操作簡易、能快速的檢測水果,並保有水果完整的外表,適合應用於農產品內部品質之檢測。本研究以果皮構造複雜的鳳梨和厚果皮的網紋洋香瓜為量測對象,並使用不同量測方法檢測鳳梨及洋香瓜。將研究大致分為三類,在鳳梨的部分,將現有的光譜量測果皮的方式,改為量測果柄的光譜與果肉的糖酸度建立檢測模型;在洋香瓜的部分,使用小型、重量輕、價格低和操作容易的手持式光譜儀檢測洋香瓜,使近紅外光技術能夠更廣泛應用於農業上,並掌握洋香瓜最佳採收時機。除此之外,本研究還使用近紅外光二維的影像技術-高光譜影像系統,應用於建立洋香瓜及鳳梨可視化糖度與酸度的分佈資訊,使其能更有效的取得平面的資訊。實驗用到的儀器有實驗室型分光光度計 (FOSS),波長為400-1800 nm;手持式光譜儀(DLP),波長為900-1700 nm;高光譜影像系統(HSIS),波長為900-1700 nm。三部儀器量測的光譜資訊以MPLSR及數學處理分析建立模型。使用FOSS建立鳳梨果柄檢量線結果表示其可以有效預測糖度,rc(校正相關係數)為0.95、SEC(校正標準誤差)為0.71 °Brix,其結果高於過去研究的結果,且可以應用在分級選別鳳梨。在洋香瓜研究結果中,使用FOSS及DLP建立洋香瓜外層果肉檢量線與內層果肉檢量線,在外層果肉檢量線的結果較好,其中DLP的結果相近於FOSS,DLP量測的結果rc為0.88、SEC為0.74 °Brix,其具有預測洋香瓜糖度的能力,而DLP的便利使它可以應用在農業檢測。使用HSIS能有效預測洋香瓜果肉糖度,其rc為0.98,由外層果肉至內層果肉的糖度會有上升的趨勢,其中外層果肉中靠近瓜臍的果肉糖度比較高。由洋香瓜可視化糖度影像中,將果肉分為外、中與內層果肉進行相關性分析,其外層果肉與外至內層果肉的糖度相關性高(r=0.95),此外,瓜臍果肉與剖面洋香瓜糖度相關性有0.87。使用HSIS建立鳳梨可視化糖酸度分布影像的結果,糖度的rc為0.95、SEC為1.14 °Brix,酸度的rc為0.89、SEC為0.10 %,其結果表示越接近鳳梨果柄的果肉糖度越高且酸度越低,從果皮到果心,糖度越低且酸度也越低。 | zh_TW |
dc.description.abstract | Near-infrared spectroscopy (NIRS) is a non-destructive detection method. It is easy-to-use, allows rapid measurement of fruit quality and retains the intact appearance of fruits, making the NIRS a suitable tool for measuring the internal quality of agricultural products. In this study, the pineapples with the complex skin texture and cantaloupes with a thick skin are used as the study objects. The research is divided into three parts. For the pineapples, the current spectral measurement is changed from peel to pedicel, and subsequently correlated to the sugar content and acidity of the pulp based on the calibration curve. For the cantaloupes, the small, light-weight, low-cost and easy-to-operate portable spectrometer is used to detect the internal quality of cantaloupes, such that the NIRS technology can be more widely used in agriculture, and the best time of harvesting can be determined. In addition, this research also uses the two-dimensional near-infrared imaging technology - the hyperspectral spectrometer imaging system (HSIS), to visualize the sugar content and acidity distribution map of cantaloupe and pineapple pulp, such that the planar information can be obtained more effectively. The instruments used in the experiment were laboratory-scale spectrophotometer (FOSS) with the wavelength range of 400-1800 nm, the portable spectrometer (DLP) with the wavelength range of 900-1700 nm; the HSIS with a wavelength of 900-1700 nm. The spectral information measured by these three instruments was pretreated and modeled by modified partial least squares regression. The obtained calibration curve for the pineapple pedicel using FOSS indicated that it can effectively predict the sugar content, with corrected correlation coefficient (rc) of 0.95 and corrected standard error (SEC) of 0.71 °Brix. The obtained results were higher than that of previous studies, and thus suggesting the feasibility to apply this technique to determine the sugar content of pineapples. For cantaloupe, the obtained calibration curve of the cantaloupe outer pulp was better than the cantaloupe inner pulp. The results of the DLP were similar to FOSS. The rc of 0.88 and SEC of 0.74 °Brix were obtained by the DLP measuring method, indicating its ability to predict the sugar content of cantaloupes. Moreover, the easy portability of DLP makes it applicable to agricultural testing. The HSIS can effectively predict the sugar content of cantaloupe pulp, with the result of rc = 0.98 was obtained. The sugar content from the outer pulp to the inner pulp showed an increasing trend. The pulp near the umbilicus of cantaloupe had a higher sugar content. For the visualization of the sugar content of cantaloupe using a distribution map, the flesh was divided into the regions of outer, middle and inner flesh for correlation analysis. The sugar content of the outer flesh and outer to inner flesh was highly correlated (r = 0.95). Also, there was a correlation of 0.87 between the pulp near the umbilicus of a cantaloupe and the sugar content of the whole cantaloupe. From the results of using HSIS to visualize the distribution map of sugar content and acidity of pineapple, rc = 0.95, SEC = 1.14 °Brix, and rc = 0.89, SEC = 0.10 %, were obtained for sugar content and acidity, respectively. The results indicated that the pineapple pulp closer to the pedicel has higher sugar content and lower acidity. From the peel to the core of the pulp in pineapple, the lower the sugar content, the lower the acidity was. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T09:45:31Z (GMT). No. of bitstreams: 1 U0001-1308202015413400.pdf: 5407135 bytes, checksum: 751b41ca15d3e0c7c184ed9b195fa2b7 (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 論文口試委員審定書 i 誌 謝 ii 摘 要 iii Abstract v 目錄 vii 圖目錄 ix 表目錄 xiii 第一章 前 言 1 1.1 研究背景 1 1.2 研究目的 2 第二章 文獻探討 3 2.1 近紅外光檢測原理 3 2.2 近紅外光譜分析方法 5 2.3 近紅外光技術應用於農業 7 2.3.1 光譜技術應用於鳳梨 10 2.3.2 光譜技術應用於洋香瓜 11 第三章 材料與方法 14 3.1 實驗儀器設備 14 3.1.1 實驗室型分光光度計 14 3.1.2 手持式光譜儀 16 3.1.3 高光譜影像系統(HSIS) 17 3.1.4 糖度計 18 3.1.5 糖酸度計 18 3.1.6 果肉切割固定平台 19 3.2 光譜分析軟體 20 3.2.1 光譜處理分析軟體(WinISI) 20 3.2.2 MATLAB 20 3.3 鳳梨實驗方法 21 3.3.1 實驗樣本 21 3.3.2 光譜量測 22 3.3.3 糖酸度成分量測 23 3.4 洋香瓜實驗方法 25 3.4.1 實驗樣本 25 3.4.2 光譜掃描洋香瓜果皮 27 3.4.3 糖度成分量測 29 3.5 高光譜影像系統可視化果肉糖酸度實驗方法 30 3.5.1 實驗樣本前處理 30 3.5.2 高光譜影像系統影像掃描 33 3.6 光譜處理及分析方法 34 第四章 結果與討論 37 4.1 鳳梨實驗的分析結果 37 4.1.1 果目檢量線之分析結果 39 4.1.2 果柄檢量線之分析結果 41 4.1.3 不同方法之量測結果比較 42 4.2 洋香瓜實驗分析結果 51 4.2.1 手持式光譜儀掃描洋香瓜果皮預測果肉糖度分析結果 51 4.2.2 不同儀器量測之結果比較 54 4.3 高光譜影像系統實驗分析結果 57 4.3.1 高光譜影像系統掃描次數比較 57 4.3.2 洋香瓜縱剖面可視化糖度分析結果 58 4.3.3 鳳梨縱剖面可視化糖酸度分析結果 63 第五章 結論與建議 67 參考文獻 69 | |
dc.language.iso | zh-TW | |
dc.title | 以近紅外光檢測鳳梨及洋香瓜內部品質之研究 | zh_TW |
dc.title | Internal Quality Evaluations of Pineapple and Cantaloupe Using NIR Spectroscopy | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 莊永坤(Yung-Kun Chuang),王豐政(Feng-Jehng Wang),林連雄(Lian-hsiung Lin),艾群(Chyung Ay) | |
dc.subject.keyword | 近紅外光,高光譜影像,手持式,洋香瓜,鳳梨,糖度,酸度,修正型部分最小平方迴歸, | zh_TW |
dc.subject.keyword | near infrared,hyperspectral imaging,portable spectrometer,cantaloupe,pineapple,sugar content,acidity,MPLSR, | en |
dc.relation.page | 71 | |
dc.identifier.doi | 10.6342/NTU202003277 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2020-08-18 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物機電工程學系 | zh_TW |
顯示於系所單位: | 生物機電工程學系 |
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