一種便攜式蘋果糖度無損檢測儀的研制

郭亞 程亮 秦斌

摘要糖度是判斷蘋果質量好壞的一個重要參考標準，針對蘋果糖度的檢測問題，設計了一種以Cortex-A9為內核、以自研發的可見-近紅外光譜儀（波長范圍400～1 000 nm）作為光譜檢測裝置、以Linux為操作系統的便攜式蘋果糖度無損檢測儀。以山東煙臺的100個紅富士蘋果為材料，采集了漫透射檢測方式下基于自收發光機構的蘋果漫透射光譜曲線，結合化學計量學方法，對樣本的全光譜曲線使用了平均法和Savitzky-Golay卷積平滑光譜預處理方法，將預處理后的光譜數據按波峰位置劃分區間，并分別按照全光譜范圍和所劃分區間的波段范圍建立PLS模型來預測蘋果的糖度含量。結果表明，經預處理后的全光譜數據所建立的PLS模型預測效果最好，優于按波峰劃分區間所建立的PLS模型，其校正相關系數為0.96、預測相關系數為0.87，校正均方根誤差為0.31、預測均方根誤差為0.34。同時對儀器工作時的預測穩定性進行了測試，測試結果得出檢測精度可控制在±0.2 Brix以內，模型預測精度滿足現場快速檢測應用要求。

關鍵詞糖度；蘋果；近紅外光譜；便攜式；無損檢測；嵌入式系統

中圖分類號TP23文獻標識碼A文章編號0517-6611（2017）14-0191-08

AbstractSugar content is an important reference standard to judge the quality of apple，a portable apple soluble solids content spectrometer was designed with CortexA9 as controller，selfdeveloped nearinfrared spectrometer（the wavelength range of 400 to 1 000 nm） as spectrum detector，Linux as embedded operating system.The total number of 100 apple samples from Yantai，Shandong Province were used as the test objects.Collecting optical transceiver diffuse transmission spectral curves，combined with the method of chemometrics，the full spectrum of the sample was processed by averaging method and SavitzkyGolay convolution smoothing spectral pretreatment method，and the spectral data of pretreatment were divided according to the wave peak position，then PLS model was established to predict the sugar content of apple.Experimental results showed that the full spectrum of PLS models set up in average and smooth pretreatment way were better than that of divided by wave peak position.The correlation coefficient of Rc=0.96，the Rp=0.87，root mean square error RMSEC=0.31，RMSEP=0.34.Meanwhile，work to predict the stability of the instrument were tested，the test results obtained detection accuracy could be controlled within ± 0.2Brix，the prediction accuracy of the model met the requirements of onsite inspection applications.

Key wordsSugar content；Apple；Near infrared spectrum；Portable；Nondestructive inspection；Embedded system

隨著人們生活水平的提高，消費者對蘋果的品質有了更高的要求。從過去單一的追求外觀形狀、色澤、有無蟲眼等發展到酸度、甜度、有無農藥殘留等內部品質的要求。但傳統的蘋果分選只能依賴于人眼通過經驗辨別它的外部特征進行分級，蘋果的外觀質量并不能反映其內在的品質，且人工分選容易受到外界光線、個人工作狀態等影響，準確性和效率較低。……