Eunsoo Park

Non-Destructive Sorting Techniques for Viable Pepper (Capsicum annuum L.) Seeds Using Fourier Transform Near-Infrared and Raman Spectroscopy

Purpose: This study examined the performance of two spectroscopy methods and multivariate classification methods to discriminate viable pepper seeds from their non-viable counterparts. Methods: A classification model for viable seeds was developed using partial least square discrimination analysis (PLS-DA) with Fourier transform near-infrared (FT-NIR) and Raman spectroscopic data in the range of (1400-2400 nm) and , respectively. The datasets were divided into 70% to calibration and 30% to validation. To reduce noise from the spectra and compare the classification results, preprocessing methods, such as mean, maximum, and range normalization, multivariate scattering correction, standard normal variate, and and derivatives with the Savitzky-Golay algorithm were used. Results: The classification accuracies for calibration using FT-NIR and Raman spectroscopy were both 99% with first derivative, whereas the validation accuracies were 90.5% with both multivariate scattering correction and standard normal variate, and 96.4% with the raw data (non-preprocessed data). Conclusions: These results indicate that FT-NIR and Raman spectroscopy are valuable tools for a feasible classification and evaluation of viable pepper seeds by providing useful information based on PLS-DA and the threshold value.

Visual Analysis for Detection and Quantification of Pseudomonas cichorii Disease Severity in Tomato Plants

Pathogen infection in plants induces complex responses ranging from gene expression to metabolic processes in infected plants. In spite of many studies on biotic stress-related changes in host plants, little is known about the metabolic and phenotypic responses of the host plants to Pseudomonas cichorii infection based on image-based analysis. To investigate alterations in tomato plants according to disease severity, we inoculated plants with different cell densities of P. cichorii using dipping and syringe infiltration methods. High-dose inocula (≥ 106 cfu/ml) induced evident necrotic lesions within one day that corresponded to bacterial growth in the infected tissues. Among the chlorophyll fluorescence parameters analyzed, changes in quantum yield of PSII (ΦPSII) and non-photochemical quenching (NPQ) preceded the appearance of visible symptoms, but maximum quantum efficiency of PSII (Fv/Fm) was altered well after symptom development. Visible/near infrared and chlorophyll fluorescence hyperspectral images detected changes before symptom appearance at low-density inoculation. The results of this study indicate that the P. cichorii infection severity can be detected by chlorophyll fluorescence assay and hyperspectral images prior to the onset of visible symptoms, indicating the feasibility of early detection of diseases. However, to detect disease development by hyperspectral imaging, more detailed protocols and analyses are necessary. Taken together, change in chlorophyll fluorescence is a good parameter for early detection of P. cichorii infection in tomato plants. In addition, image-based visualization of infection severity before visual damage appearance will contribute to effective management of plant diseases.

Spectroscopic Techniques for Nondestructive Quality Inspection of Pharmaceutical Products: A Review

, 2015Spectroscopy is an emerging technology for the quality assessment of pharmaceutical samples, from tablet manufacturing to final quality assurance. The traditional methods for the quality management of pharmaceutical tablets are time consuming and destructive, while spectroscopic techniques allow rapid analysis in a non-destructive manner. The advantage of spectroscopy is that it collects both spatial and spectral information (called hyperspectral imaging), which is useful for the chemical imaging of pharmaceutical samples. These chemical images provide both qualitative and quantitative information on tablet samples. In the pharmaceutics, spectroscopic techniques are used for a variety of applications, such as analysis of the homogeneity of powder samples as well as determination of particle size, product composition, and the concentration, uniformity, and distribution of the active pharmaceutical ingredient in solid tablets. This review paper presents an introduction to the applications of various spectroscopic techniques such as hyperspectroscopy and vibrational spectroscopies (Raman spectroscopy, FT-NIR, and IR spectroscopy) for the quality and safety assessment of pharmaceutical solid dosage forms. In addition, various chemometric techniques that are highly essential for analyzing the spectroscopic data of pharmaceutical samples are also reviewed.Keywords: Applications, Chemometrics, Hyperspectroscopy, Pharmaceutical, Vibrational spectroscopy

Raman Hyperspectral Imaging for Detection of Watermelon Seeds Infected with Acidovorax citrulli

The bacterial infection of seeds is one of the most important quality factors affecting yield. Conventional detection methods for bacteria-infected seeds, such as biological, serological, and molecular tests, are not feasible since they require expensive equipment, and furthermore, the testing processes are also time-consuming. In this study, we use the Raman hyperspectral imaging technique to distinguish bacteria-infected seeds from healthy seeds as a rapid, accurate, and non-destructive detection tool. We utilize Raman hyperspectral imaging data in the spectral range of 400–1800 cm−1 to determine the optimal band-ratio for the discrimination of watermelon seeds infected by the bacteria Acidovorax citrulli using ANOVA. Two bands at 1076.8 cm−1 and 437 cm−1 are selected as the optimal Raman peaks for the detection of bacteria-infected seeds. The results demonstrate that the Raman hyperspectral imaging technique has a good potential for the detection of bacteria-infected watermelon seeds and that it could form a suitable alternative to conventional methods.

Development of Non-Destructive Sorting Technique for Viability of Watermelon Seed by Using Hyperspectral Image Processing

Abstract Seed viability is one of the most important parameters that is directly related with seed germination performance and seedling emergence. In this study, a hyperspectral imaging (HSI) system having a range of 1000–2500 nm was used to classify viable watermelon seeds from nonviable seeds. In order to obtain nonviable watermelon seeds, a total of 96 seeds were artificially aged by immersing the seeds in hot water (25°C) for 15 days. Further, hyperspectral images for 192 seeds (96 normal and 96 aged) were acquired using the developed HSI system. A germination test was performed for all the 192 seeds in order to confirm their viability. Spectral data from the hyperspectral images of the seeds were extracted by selecting pixels from the region of interest. Each seed spectrum was averaged and preprocessed to develop a classification model of partial least square discriminant analysis (PLS-DA). The developed PLS-DA model showed a classification accuracy of 94.7% for the calibration set, and 84.2% for the validation set. The results demonstrate that the proposed technique can classify viable and nonviable watermelon seeds with a reasonable accuracy, and can be further converted into an online sorting system for rapid and nondestructive classification of watermelon seeds with regard to viability.

Development of Drought Stress Measurement Method for Red Pepper Leaves using Hyperspectral Short Wave Infrared Imaging Technique

This study was conducted to investigate the responses of red pepper (Hongjinju) leaves under water stress. Hyperspectral short wave infrared (SWIR, 1000~1800 nm) reflectance imaging techniques were used to acquire the spectral images for the red pepper leaves with and without water stress. The acquired spectral data were analyzed with a multivariate analysis method of ANOVA (analysis of variance). The ANOVA model suggested that 1449 nm wavebands was the most effective to determine the stress responses of the red pepper leaves exposed to the water deficiency. The waveband of 1449 nm was closely related to the water absorption band. The processed spectral image of 1449 nm could separate the non-stress, moderate stress (−20 kPa), and severe stress (−50 kPa) groups of red pepper leaves distinctively. Results demonstrated that hyperspectral imaging technique can be applied to monitoring the stress responses of red pepper leaves which are an indicator of physiological and biochemical changes under water deficiency. Additional key words : red pepper, phenotyping, water stress, infrared, hyperspectral imaging

Real-time sorting of melon seed using hyperspectral shortwave infrared imaging (Conference Presentation)

Despite the complexity of the factors that lead to loss of seed viability, conventional methods like germination tests, tetrazolium tests are commonly employed to determine it. However, these methods have downsides like being destructive, time consuming and non-representative. Therefore, there is a need to develop a fast, non-destructive and real-time measurement and sorting system of seeds based on viability for industrial purpose. In this study, we seek to utilize HSI and multivariate data analysis techniques to classify viable seeds from non-viable ones and later use it basis to develop an online real-time detection system for sorting these seeds based on viability. For this cause, Data from melon and watermelon seeds were collected using a SWIR HSI system. The performance of the classification models achieved both during calibration and real-time tests were quite impressive and a proof that HSI can be effectively applied to an industrial real-time sorting system.

Machine Vision Technique for Rapid Measurement of Soybean Seed Vigor

Improving crop yield and production stability is important in satisfying the rising demand of human consumption due to the current increasing world population and rapid economic growth of developing countries. Seed quality is one of the most important factors in crop production and should be considered at the first stage of crop cultivation. Germination testing, which is defined by the International Seed Testing Association (ISTA), is one of the primary means of evaluating seed quality and reflects a seed’s ability to produce normal seedlings. A germination test is a common method of determining the percent germination, dormancy, and overall viability of seeds. It is the most consistent way to assess viability. It is important to monitor viability, since non-viable seeds may not be apparent at other stages of processing. The seed germination rate of a specific seed lot is a key indicator as to how that seed will perform in the field. The vigor test is an important step of seed quality testing. Seed vigor directly determines the emergence Machine Vision Technique for Rapid Measurement of Soybean Seed Vigor