Masateru Nagata

NIR Hyperspectral Imaging for Measurement of Internal Quality in Strawberries

Non-destructive estimation of internal quality of fruits for on-line grading for higher product consistency and enhanced safety will greatly benefit the consumer and the fruit industry as a whole. This research was aimed to develop prediction models for firmness (MPa) and soluble solids content (SSC, %Brix) in strawberries using NIR hyperspectral imaging. From freshly harvested “Akihime” variety strawberries, NIR hyperspectral images (650-1000nm at 5 nm interval) were taken and calibration models were developed for firmness and SSC using stepwise multiple linear regression. The three-wavelength prediction model for firmness had a correlation of 0.786 and SEP of 0.350 (50% to Full-ripe group). It confirmed the importance of chlorophyll absorbance peak at around 675 nm and water at 980 nm. While for SSC, the five-wavelength prediction model yielded a correlation of 0.87 and SEP of 0.53 (70% to Fullripe group). It included NIR wavelengths above 800 nm where absorptions due to carbohydrate and sugar exist.

Judgment on level of maturity for tomato quality using L*a*b* color image processing

This paper was described the judgment of Maturity for Tomato quality using color image processing. The image analysis were used for the RGB and L*a*b* color system. In the analyzes, the pixels count of G(36) showed the highest correlation coefficient from tomato maturity. But, the average value of a* of the tomato upper surface was more accurate maturity index than the radical regression curve of G(36).

Predicting Maturity Quality Parameters of Strawberries Using Hyperspectral Imaging

Non-destructive measurement of some internal properties of fruits for quality and safety is becoming important to the consumers and the industry in whole. The main goal of this research is to develop prediction models that can estimate firmness and soluble solids content (SSC) in ‘Akihime’ strawberries using hyperspectral imaging in the visible range. A spectral imaging system was developed based on a liquid crystal tunable filter to take images from 450 nm to 650 nm at 2 nm interval. Using the technically ripe sample sets, the five-predictor firmness model (510, 650, 644, 628, and 598 nm) had an SEP of 0.364 and a correlation coefficient r of 0.784. The SSC calibration models, however, require individual maturity level analysis for more reliable predictions.

Detection of Bruises in Strawberies By Hyperspectral Imaging

Latent damages such as bruises in fruits reduce their quality, incur economic losses, and make an important concern for safety and confidence for the consumers. With a general aim at developing techniques for detection of bruises in strawberries (Fragaria x ananassa Duch.) using NIR hyperspectral imaging, this study seeks to identify specific important wavelengths. From some 120 pieces of ‘Akihime’ variety at 70-80% ripe and full-ripe levels of maturity that had received six levels of bruising force (0 N, 0.5 N, 1.0 N, 1.5 N, 2.0 N and 3.0 N), spectral images were taken from 650 to 1000 nm at 5 nm- intervals. Optimal wavebands of 825 nm and 980 nm were determined using stepwise linear discriminant analysis. Three judgment methods (linear discriminant analysis, normalized difference and artificial neural network) were found to perform equally well, while the normalized difference method seemed to be more useful.

Quality Evaluation of Plant Products

Hyperspectral imaging or imaging spectrometry combines the strengths of computer vision technology with optical spectroscopy. It is primarily suited for measurement of parameters that vary spatially both at the external surface of samples and internally within the samples. The parameters may be physical features such as incipient bruises or surface contamination, or chemical constituents such as sugar and acidity. While the acquisition of images generally follows the procedures of machine vision, adding a spectral dimension would require the rigor of multivariate statistics, also known as chemometrics, to find functional relationships between the measured values and target parameters. Its application to agriculture, particularly to post-harvest processing, has recently been explored by university research laboratories in order to develop new techniques for non-destructive measurement of quality.

Basic Study on Strawberry Harvesting Robot (Part II)

Abstract These papers describe a strawberry harvesting robot where by robot vision and a 4 DOF’s Cartesian coordinate manipulator were used. This first part presents the development of a robot vision system and the algorithm for locating and feature extracting of strawberry fruits. The robot vision system employs the use of two color CCD cameras. The first camera is used to capture the whole area image under focus within the harvesting range, and the second camera captures only the image of the strawberry fruit to be plucked. The algorithm converts the captured images from RGB to L*a*b and extracts recognized position, orientation and shape of strawberry from a gray image of the L*a*b color model. Experimental results show that the robot vision system can extract position, orientation and shape of various strawberries in ordinary lighting condition. The Part II presents the design and development of the robot frame, the plucking hand, 4 DOF’s Cartesian coordinate manipulator and the Control System.

Judging of Tomato Maturity by Utilizing a Lowresolution RGB Color System

On the image processing of personal computer, the RGB color system has the most closely index color map (16.77 million index, 24bit) compared to the other (L*a*b* or HSV etc.) color system. Therefore RGB index values are used in the other color system formula. This study determines a method for higher accuracy judgment by the RGB color system for the index color of tomato maturity. The correlation coefficient between the relationship of tomato maturity and the histogram in 24bit color index map in RGB color system was 0.6202, when it was showed under the index of R=141, G=60 and B=50. The judgment accuracy for using this linear formula was about 50%. Then, when the percentile of histogram of tomato area was used, the correlation coefficient was increased to 0.6225. This reason was affected by the size of tomato. Moreover, we thought that the RGB 24bit color map was too much, thus a lower bit color map was used this analysis. The highest correlation coefficient was obtained 0.9202 in 64 colors(12bit). This result was clearly showed that the group color is better than mono color. Therefore, other color system which has lower color map, were compared to a 15bit color index map on the RGB color system.

Study on Precision Seeding System Using Urethane Mat for Hydroponic Seedling Production of Leaf Vegetables. (Part 1). Development of a Punching Mechanism for Seeding.

A punching mechanism was developed for placing seeds of leaf vegetables directly into precut cells of urethane mat in hydroponic seedling production of leaf vegetables. The mechanism has twelve punchers, which are in the form of a hollow cone to penetrate into urethane mat for seed placement. The mechanism was attached and synchronized to the conventional vacuum seeder. When punchers penetrate the urethane mat, seeds are discharged from nozzles and delivered to punchers through tubes. Seeds of mustard spinach were used for the performance test. Punchers with outer diameter of 3.0 mm and cone index angle of 10 degrees could successfully penetrate into pre-cut cells of urethane mat. The punchers accurately placed the seeds at pre-determined punching depth of 3.0 mm with seeding efficiency of 96.5%.

Study on Quality Estimation for Strawberry using Color and NIR Image Processing

Abstract This study was carried out to detect bruises on the surface of strawberry using color and NIR image processing. The bruises in this study were caused in controlled manner on the freshly harvested fruits. Firstly, the bruises were detected by analyzing L*a*b* color model. The a* level has indicated their characteristics. Secondly, the particular wavelengths critical for bruise detection were determined and spectral images were acquired with suitable filters of 860 and 960nm. Two methods of image subtractions, one between the same samples and next between the test and standard image, has confirmed the possibilities of bruise detection by using NIR image processing for online sorting.

Basic Study on Strawberry Harvesting Robot (Part II): Design and Development of Harvesting Mechanism

Abstract The aim of the study was to develop an automatic harvesting robot for strawberry. The algorithm for recognition of fruit and its location, and the design concept of the robot vision system were reported in Part I of this study. This part describes the design and development of the robot frame, the plucking hand, 4 DOF’s Cartesian coordinate manipulator and the control system. The plucking hand and its position geometry are very important for any harvesting robot. The developed plucking hand is a non-touch fruit type as it specifically grips the stem to be cut. The experiment results show that the optimum air pressure supplied to the harvesting hand was from 0.09 to 0.17 MPa during the plucking process, and more than 0.23 MPa during the cutting off process. A high harvest accuracy of nearly 100 % was confirmed. And since the plucking process is a method accomplished by grasping the stem of the strawberry, it was demonstrated that strawberry can be harvested without touching the delicate fruits.