高光譜影像技術應用於葉片水潛勢量測及可視化之研究

高光譜影像技術屬於非破壞性檢測技術，已被廣泛使用在各產業領域，農業上之應用包括精準農業、作物栽培管理、農產品品質檢測等。本研究自行開發的移動式台車線上型高光譜影像檢測系統，使用了銦鎵砷（InGaAs）材質的高光譜影像相機，檢測波段範圍為900～1700 nm，並利用LabVIEW與MATLAB兩套程式進行系統軟硬體的整合。系統的使用前校準，應用了波長、平場、空間等校正，確保系統穩定的運作。系統可以放置於台車上，在番茄作物的實際栽培場域移動。以線上水平方向拍攝的方式擷取光譜及影像的資訊，以檢測葉片活體的水潛勢。水潛勢的實驗，採用露點微伏水潛勢測定儀HR-33T，並使用了10個樣本室進行分時檢測實驗，以NaCl標準檢測液建立0～−2.971 MPa範圍的水潛勢標準檢量線，作為樣本檢測計算葉片水潛勢的依據。番茄葉片169個樣本進行的水潛勢的量測結果介於−0.446～−1.911 MPa，標準差為0.284 MPa，均落在標準檢量線可檢測的範圍內。葉片水潛勢的預測模式採用修正部分最小平方迴歸法（MPLSR）來建立，其分析結果為決定係數r_c^2 = 0.779、標準校正誤差SEC = 0.129。本研究亦經由所建立的MPLSR葉片水潛勢預測模式，計算出所拍攝的葉片影像各像素點上的水潛勢值，以假彩色方式呈現葉片的水潛勢分佈圖，透過清晰易懂的可視化方式提供葉片水潛勢分佈的直觀判別。本研究建立快速、簡易、非破壞性的葉片水潛勢量測系統及技術。

關鍵字

非破壞檢測；高光譜影像；番茄；葉片水潛勢；可視化

並列摘要

Hyperspectral imaging technology is a non-destructive detection technology, and it has been widely used in various industrial fields. Agricultural applications include precision agriculture, crop cultivation management and quality evaluation of agricultural products. This study developed a mobile-carrier online type hyperspectral imaging system, in which a hyperspectral imaging camera made of indium gallium arsenide (InGaAs) with a detection wavelength range of 900~1700 nm was used, and programs using LabVIEW and MATLAB were adopted to integrate the systems. System pre-calibrations including wavelength correction, flat field correction and spatial correction are applied to ensure the stable operation of the system. The system can be easily installed on a carrier and moved to the actual cultivation field of the tomato crops. The spectra and image information are captured by horizontally online shooting of images of tomato crops, and the water potentials of the living body of leaves can be directly measured. Regarding the water potential experiments, DewPoint Microvoltmeter HR-33T was used and 10 sample chambers were also used for timesharing purpose. NaCl standard test solution was used to establish a water potential standard calibration equations in the range of 0 ~ -2.971 MPa as the reference basis for calculating leaf water potentials. The measurement results of water potential for 169 tomato leaf samples ranged from -0.446 to -1.911 MPa with a standard deviation of 0.284 MPa, all falling within the detectable range of the standard calibration equations. The MPLSR (Modified Partial Least Square Regression) prediction model for tomato water potential was established, and the regression results were r_c^2 (coefficient of determination of calibration) = 0.779 and SEC (Standard Error of Calibration) = 0.129. The water potential values at each pixel of the leaf images can be calculated through MPLSR model. The distribution of the water potential over the entire leaf area could be presented in a pseudo-color graph, in which intuitive judgment of leaf water potential distribution through clear and easy-to-understand visualization can be provided. In this research, a fast, easy and non-destructive leaf water potential measurement system and techniques have been developed.