Near-Infrared Spectral Imaging for the Visualization of Moisture Distribution inside Soybean Seeds

Transcription

1 1/ 31 Near-Infrared Spectral Imaging for the Visualization of Moisture Distribution inside Soybean Seeds M. Tsuta 1, Y. Ogawa 2, Y. Sagara 3, G. Do 4 and J. Sugiyama 1 1 National Food Research Institute, 2 Chiba University, 3 The University of Tokyo, 4 Nihon University

2 2/ 31 Outline Background and Objective Instrumentation Preliminary Experiment Measurement and Visualization of Moisture Distribution inside Soybean Seeds Conclusion and Future Studies

3 3/ 31 Outline Background and Objective Instrumentation Preliminary Experiment Measurement and Visualization of Moisture Distribution inside Soybean Seeds Conclusion and Future Studies

4 4/ 31 Importance of Moisture Distribution Moisture distribution inside foods affect; Qualities Processing characteristics etc. Moisture distribution is an important factor. Needs for measurement of moisture distribution.

5 5/ 31 Studies of NIR Imaging Brix % Foreign Substance Sugar Distribution of Melon 0 Foreign Substance Detection for Blueberry Fruits NIR imaging is effective in visualization of constituent distribution and can be applied to moisture distribution.

6 6/ 31 Objectives In order to develop a visualization technique for moisture distribution using NIR imaging, Develop an imaging apparatus, Identify the absorption band of ice, Sample would be frozen materials. Choose soybean seed as a sample, One of the most important food materials. Research project to visualize morphological and physiological properties of seeds. Measure and visualize the moisture distribution inside a soybean seed.

7 7/ 31 Outline Background and Objective Instrumentation Preliminary Experiment Measurement and Visualization of Moisture Distribution inside Soybean Seeds Conclusion and Future Studies

8 8/ 31 Imaging Apparatus Spectral Imager Takes the image of the sample surface at nearinfrared range Micro-slicer Pushes up the sample and slices the sample surface repeatedly Spectral Illuminator Illuminates the sample surface at any wavelength.

9 9/ 31 Spectral Illuminator Wavelength 1500 nm Halogen Lamp Grating Monochromater Wavelength Selector Germanium-Doped Light Guide with a Condensing Lens Range 400-1,600 nm Custom-Made by Somaopt., Japan Bandwidth: Approx. 10 nm Sample surface can be illuminated at the selected wavelength.

10 10/ 31 Microslicer Sample Holder for Frozen Sample Rotating Microtome Custom-Made by Toshiba Machine Inc., Japan Stepping Motor Sample Freezing Temperature: Approx. -10 C Slicing Thickness: 1-30 µm Surfaces at different depth of the frozen sample can be exposed.

11 11/ 31 Spectral Imager NIR Camera (XEVA-FPA , Xenics NV, Belgium) Fluorescence Microscope (BX-FM, Olympus Corp., Japan) Objective Lens for NIR Region (M Plan NIR 5x, Mitsutoyo Corp., Japan) Sensitivity: 900-1,600 nm Pixels: 320 x 256 A/ D Gradation: 12 bits (4,096 Steps) Images of the sample surface can be acquired at Near-Infrared region

12 12/ 31 Outline Background and Objective Instrumentation Preliminary Experiment Measurement and Visualization of Moisture Distribution inside Soybean Seeds Conclusion and Future Studies

13 13/ 31 Preliminary Experiment Micro-slicer 1. White Reference Board 2. Water Droplet 3. Frozen Droplet A water droplet was added on the white reference board. The droplet was frozen by the cooler of Microslicer. Acquisition of spectral images at stages 1 and 3.

14 14/ 31 Taking Spectral Images 1,400 nm 1,401 nm 1,402 nm Frozen Droplet 1,597 nm 1,598 nm 1,599 nm 1,400-1,599 nm, 1 nm intervals (Total 200 images)

15 15/ 31 Conversion: Image into Absorbance Definition of Absorbance Absorbance = log Intensity( Sample) Intensity( Reference) Applied to each pixel Droplet image at 1,400 nm = -log Absorbance image at 1,400 nm Reference image at 1,400 nm (All image processing was carried out by Image Pro Plus 5.0, Media Cybernetics Inc., USA)

16 16/ 31 False Colorization of Absorbance Image 1.5 Absorbance Original Image Colorized Image 0

17 17/ 31 Absorbance Images 1,400 1,449 nm 1.5 1,450 1,499 nm 1,500 1,549 nm Absorbance 1,550 1,599 nm 0 Absorbance peak seemed to exist around 1,500 nm

18 18/ 31 Absorbance Spectra Absorption peaks of ice 1,484 nm 1,500 nm Calculation of average absorbance within at each wavelength

19 19/ 31 Outline Background and Objective Instrumentation Preliminary Experiment Measurement and Visualization of Moisture Distribution inside Soybean Seeds Conclusion and Future Studies

20 20/ 31 Measurement of Soybean Seeds Soybean Seed Freeze Embedding Agent Soaked in Pure Water (0, 30, 60, 120, 240 min and 24 h) Frozen/ Embedded Set in Microslicer/ Cut into Halves Spectral Analysis Conversion into Absorbance Images Acquisition of Spectral Images (Same as in the case of the frozen droplet)

21 21/ 31 Raw Spectra Periphery Center Calculation of average absorbance within and of each soybean seed at each wavelength Some peaks found around 1,500 nm, but no specific trend.

22 22/ 31 Second Derivative Spectra 2D absorbance at 1,484 nm was getting smaller with soaking time increased at periphery.

23 Development of second derivative absorbance image. 23/ 31 Second Derivative Spectra Indicated increase in moisture content at periphery.

24 24/ 31 Image Arithmetic = 2D Absorbance Image at 1,484 nm - 2 x + (1,504 nm) (1,484 nm) (1,464 nm) Absorbance Images with gap of 20 nm

25 25/ 31 2D Absorbance Images at 1,484 nm 0 30 min 60 min 5 mm 2D Absorbance 0 min min 240 min 24 h Pixels with low 2D absorbance spread toward center part from periphery as soaking time increased.

26 26/ 31 2D Absorbance Images at 1,484 nm 0 30 min 60 min 5 mm 2D Absorbance 0 min min 240 min 24 h Which indicated that water penetrated more deeper inside soybean seeds as the soaking time became longer.

27 27/ 31 2D Absorbance Images at 1,484 nm 0 30 min 2D Absorbance 0 min 60 min 5 mm min 240 min 24 h These 2D absorbance images seemed to reflect actual moisture distribution.

28 28/ 31 Outline Background and Objective Instrumentation Preliminary Experiment Measurement and Visualization of Moisture Distribution inside Soybean Seeds Conclusion and Future Studies

29 29/ 31 Conclusion The absorption peaks of ice was found around 1,500 nm in raw spectra and 1,484 nm in second derivative spectra. Absorbance images of half-cut soybean seeds with different water soaking time were acquired using NIR imaging technique. Second derivative absorbance images at 1,484 nm were considered to reflect actual moisture distribution. NIR Imaging could be applicable to visualization of moisture distribution in food.

30 30/ 31 Future Studies Three-dimensional visualization of moisture distribution Application of longer wavelength region (1,700-2,500 nm) using the latest NIR camera Strong absorption band of protein, starch etc. Simultaneous visualization of moisture and other constituent distribution More precise analysis concerning complex structure of food

31 31/ 31 Introduction of Our Poster Other applications of NIR Imaging? Please come to see the poster C:02! Spectral Imaging Application on Foods in Japan by Dr. Sugiyama