Comparison of visible-near infrared and mid-infrared spectroscopy for classification of Huanglongbing and citrus canker infected leaves

In this study, visible-near infrared spectroscopy and mid-infrared spectroscopy were compared to evaluate their applicability in classifying citrus leaves infected with canker and HLB from healthy citrus leaves.  The visible-near infrared spectra in the range 350-2,500 nm and mid-infrared spectra in the range of 5.15-10.72 µm were collected from healthy and diseased (canker, HLB) leaves.  Following the spectral data collection, the data were preprocessed and classification was performed using two classifiers, quadratic discriminant analysis (QDA) and k-nearest neighbor (kNN).  The classifiers (QDA, kNN) resulted in an average overall and individual class classification accuracy of about 90% or more.  Mid-infrared spectroscopy provided high classification accuracy especially in identifying HLB-infected leaves; while, visible-near infrared spectroscopy was better suited for canker detection.  Both methods have their own merits such as visible-near infrared spectroscopy offers non-invasive disease detection; while mid-infrared spectroscopy represents the chemical profile of the leaf structure, which may allow potential detection in asymptomatic stages.   Keywords: disease detection, classification, quadratic discriminant analysis, k-nearest neighbo

A Comprehensive Review on Food Applications of Terahertz Spectroscopy and Imaging.

Food product safety is a public health concern. Most of the food safety analytical and detection methods are expensive, labor intensive, and time consuming. A safe, rapid, reliable, and nondestructive detection method is needed to assure consumers that food products are safe to consume. Terahertz (THz) radiation, which has properties of both microwave and infrared, can penetrate and interact with many commonly used materials. Owing to the technological developments in sources and detectors, THz spectroscopic imaging has transitioned from a laboratory-scale technique into a versatile imaging tool with many practical applications. In recent years, THz imaging has been shown to have great potential as an emerging nondestructive tool for food inspection. THz spectroscopy provides qualitative and quantitative information about food samples. The main applications of THz in food industries include detection of moisture, foreign bodies, inspection, and quality control. Other applications of THz technology in the food industry include detection of harmful compounds, antibiotics, and microorganisms. THz spectroscopy is a great tool for characterization of carbohydrates, amino acids, fatty acids, and vitamins. Despite its potential applications, THz technology has some limitations, such as limited penetration, scattering effect, limited sensitivity, and low limit of detection. THz technology is still expensive, and there is no available THz database library for food compounds. The scanning speed needs to be improved in the future generations of THz systems. Although many technological aspects need to be improved, THz technology has already been established in the food industry as a powerful tool with great detection and quantification ability. This paper reviews various applications of THz spectroscopy and imaging in the food industry

Detection of multi-tomato leaf diseases (late blight, target and bacterial spots) in different stages by using a spectral-based sensor.

Several diseases have threatened tomato production in Florida, resulting in large losses, especially in fresh markets. In this study, a high-resolution portable spectral sensor was used to investigate the feasibility of detecting multi-diseased tomato leaves in different stages, including early or asymptomatic stages. One healthy leaf and three diseased tomato leaves (late blight, target and bacterial spots) were defined into four stages (healthy, asymptomatic, early stage and late stage) and collected from a field. Fifty-seven spectral vegetation indices (SVIs) were calculated in accordance with methods published in previous studies and established in this study. Principal component analysis was conducted to evaluate SVIs. Results revealed six principal components (PCs) whose eigenvalues were greater than 1. SVIs with weight coefficients ranking from 1 to 30 in each selected PC were applied to a K-nearest neighbour for classification. Amongst the examined leaves, the healthy ones had the highest accuracy (100%) and the lowest error rate (0) because of their uniform tissues. Late stage leaves could be distinguished more easily than the two other disease categories caused by similar symptoms on the multi-diseased leaves. Further work may incorporate the proposed technique into an image system that can be operated to monitor multi-diseased tomato plants in fields

Nanoporous Polyether Sulfone Membrane, Preparation and Characterization: Effect of Porosity and Mean Pore Size on Performance

Flat sheet membranes were prepared by phase inversion technique using polyether sulfone (PES) dissolved in dimethylacetamide (DMAc) with and without adding polyvinylpyrrolidone (PVP) or polyethyleneglycol (PEG). The characteristics of the prepared membranes were evaluated using Scanning Electron Microscope (SEM) images, Atomic Force Microscopy (AFM), and Optical Contact Angle (OCA) measurements, and porosity tests. The porosity test and SEM images show that increasing additives to a certain value increases the porosity of the membrane. Also, as the coagulation bath temperature is increased, the porosity of the membrane is increased. The roughness of the membrane is increased by increasing the additive concentration. The analysis of AFM images confirms the nanoporous structure of the prepared membranes, and that the membranes with appropriate pore size distribution can be prepared by the applied method. Permeability tests using single-layer membranes show that the direct relationship between porosity and the flux of pure water or salt solution is dominated by the effect of applied additive while the salt rejection shows an inverse relationship with the mean pore size regardless of the applied additive. The salt permeation flux is a function of total porosity while the salt rejection is a function of surface porosity. Pervaporation tests show that both permeation flux and enrichment factor depend on the total porosity of the support membrane

Real-time nondestructive citrus fruit quality monitoring system: development and laboratory testing

This study reports on the development and laboratory testing of the This study reports on the development and laboratory testing of the nondestructive citrus fruit quality monitoring system.  Prototype system consists of a light detection and ranging (LIDAR) and visible-near infrared spectroscopy sensors installed on an inclined conveyer for real-time fruit size and total soluble solids (TSS) measurement respectively.  Laboratory test results revealed that the developed system is applicable for instantaneous fruit size (R2 = 0.912) and TSS (R2 = 0.677, standard error of prediction = 0.48 °Brix) determination.  Future applications of such system would be in precision farming for in-field orange quality determination during the harvest and for row specific yield mapping and monitoring.    Keywords: LIDAR sensor, visible-near infrared spectroscopy, fruit size, sugar conten

Detection of multi-tomato leaf diseases (\u3ci\u3elate blight, target and bacterial spots\u3c/i\u3e) in different stages by using a spectral-based sensor

Several diseases have threatened tomato production in Florida, resulting in large losses, especially in fresh markets. In this study, a high-resolution portable spectral sensor was used to investigate the feasibility of detecting multi-diseased tomato leaves in different stages, including early or asymptomatic stages. One healthy leaf and three diseased tomato leaves (late blight, target and bacterial spots) were defined into four stages (healthy, asymptomatic, early stage and late stage) and collected from a field. Fifty-seven spectral vegetation indices (SVIs) were calculated in accordance with methods published in previous studies and established in this study. Principal component analysis was conducted to evaluate SVIs. Results revealed six principal components (PCs) whose eigenvalues were greater than 1. SVIs with weight coefficients ranking from 1 to 30 in each selected PC were applied to a K-nearest neighbor for classification. Amongst the examined leaves, the healthy ones had the highest accuracy (100%) and the lowest error rate (0) because of their uniform tissues. Late stage leaves could be distinguished more easily than the two other disease categories caused by similar symptoms on the multi-diseased leaves. Further work may incorporate the proposed technique into an image system that can be operated to monitor multi-diseased tomato plants in fields

Modelling of proteolysis in Iranian brined cheese using proteinase-loaded nanoliposome

In this study, Flavourzyme was encapsulated in liposomes to accelerate the ripening of Iranian white cheese. Liposomal enzyme was prepared using a modified heating method. The influence of enzyme content, ripening time and curd retention in saturated brine on proteolysis indices and sensory perception was investigated using response surface methodology. The most influential factor on proteolysis indices was ripening time, while the content of liposomal enzyme and retention time were also significant (P < 0.05). The maximum proteolysis indices and highest sensory characteristic scores were achieved by applying 0.3% w/w enzyme, ripening for 30 days and 8-h curd retention in saturated brine