Shell eggs with microcracks are often undetected during egg grading processes. In the past, a modified pressure imaging system was developed to detect eggs with microcracks without adversely affecting the quality of normal intact eggs. The basic idea of the modified pressure imaging system was to apply a short burst of vacuum within a transparent chamber in order to cause a momentary and forced opening in the egg shell with a crack and thus to utilize the changes in image intensities during this process. The intensity changes from dark to bright in the shell surface were recorded by a high-resolution digital camera and processed by an image ratio technique. However, the performance of the imaging system was compromised by both false readings due to motion of intact eggs relative to the camera and an improper selection of parameter values for the detection algorithm. First, a machine vision technique based on motion estimation of individual eggs was developed to compensate any motion errors present on images and thus reduce false crack-detection readings. The simulation results of the developed motion estimation and compensation technique with 3,000 eggs showed no false errors. Second, the receiver operating characteristic (ROC) curve was used to evaluate and compare the performance of the crack-detection algorithm under varying parameters (ratio and detection-tolerance thresholds) and to find the optimal parameter values. The area under the ROC curve (AUC) was used to compare the performance under varying parameter values. The minimum distance and Youden index criteria were used to find the optimal values from the ROC curve. The minimum distance criterion found the optimal parameters at 1.11 and 20 (or 1.1 and 25) for the ratio and detection-tolerance thresholds, respectively. The true positive and false positive rates at the optimal conditions were 98.91 and 0.14 %, respectively.

Hyperspectral imaging techniques, combining the advantages of spectroscopy and imaging, have found wider use in food quality and safety evaluation applications during the past decade. In light of the prevalent use of hyperspectral imaging techniques in the visible to near-infrared (VNIR: 400–1,000 nm) for agro-food evaluations, seldom reported are the instrument artifacts that may affect the quality of image data. Furthermore, hyperspectral-based research has focused on the development of image processing and detection aspects with minimal attention given to illustrating the underlying value of imaging with sufficient spatial resolution in the regions spanning from the visible to short-wavelength infrared (SWIR: 1,000–1,700). We have developed multiple generations of line-scan based hyperspectral imaging systems and expanded the imaging capabilities in the SWIR. With the use of our most recently developed VNIR and SWIR hyperspectral imaging systems, spectral and spatial attributes of apples with defects from 400 to 1,700 nm are presented. In addition, we characterize the second-order effect in the 800–1,000 nm range that emanates from the use of a diffraction grating in the VNIR hyperspectral imaging system. We have devised methods to perform SWIR spectral calibration and to remove the bad pixels inherent to the SWIR InGaAs focal plane array used in the imaging system. We envision that hyperspectral imaging techniques will continue to play a significant role in the agro-food sector as critical research tools, and in further applications for rapid inspection of produce safety and quality.

Because of the high demand for aromatic rice cultivars that command a premium, it is important to have efficient methods for determining 2-acetyl-1-pyrroline (2-AP), the aromatic compound found in rice, that can be used in breeding efforts and to detect aromatic/non-aromatic blended rice in the marketplace. Solid-phase microextraction (SPME) in conjunction with GC/MS was used to distinguish non-aromatic rice (Oryzasativa, L.) kernels from aromatic rice kernels. In this method, single kernels along with 10 μl of 0.1 ng μl−1 2,4,6-Trimethylpyridine were placed in sealed vials and heated to 80 °C for 18 min. During the heating stage volatile compounds, which include 2-AP, were adsorbed onto a SPME fiber. Volatiles were desorbed from the fiber and separated using gas chromatography. 2-AP was quantitated by mass spectrometry using the 111, 83 and 68 m/z ions. The method detected 2-AP in milled rice and brown rice; however, its detection in paddy rice was less successful. In a mixture of aromatic and non-aromatic rice, the aromatic rice kernels were differentiated from the non-aromatic rice kernels using the described method. Therefore, this method can be used to identify segregating from non-segregating progeny during early generations in an aromatic rice breeding program when quantities of seed are very limited and can determine if aromatic rice has been adulterated with non-aromatic rice either through inadvertent mixtures, outcrosses or prepared blends.

Oxytetracycline residue in shrimp muscle was determined using a portable time-resolved analyzer. After extraction in EDTA-metaphosphoric acid and filtration, the analyte was cleaned up using hydrophilic-lipophilic balance cartridges. Europium-sensitized luminescence (ESL) was measured at λex = 385 nm and λem = 620 nm. Recoveries were 80.3 and 79.7% at 100 ng g−1 and 2 μg g−1, respectively. The signal intensity was linear (r2 ≥ 0.996) in each decade in the 5–5,000 ng g−1 range. Averaged relative standard deviation was ~2% and limit of detection was 8.3 ng g−1. This instrument-method combination enabled sensitive in-situ quantification of OTC residue in shrimp. The ESL results were validated by HPLC–MS/MS.

The development of chemical sensors and biosensors over several decades has been investigated resulting in novel and very interesting sensor devices with great promise for many areas of applications including food technology. The incorporation of such sensors into the food packaging technology has resulted what we call smart or intelligent packaging. These are truly integrated and interdisciplinary systems that invoke expertise from the fields of chemistry, biochemistry, physics and electronics as well as food science and technology. Smart packaging utilises chemical sensor or biosensor to monitor the quality & safety of food from the producers to the costumers. This technology can result in a variety of sensor designs that are suitable for monitoring of food quality and safety, such as freshness, pathogens, leakage, carbon dioxide, oxygen, pH, time or temperature. Thus, this technology is needed as on-line quality control and safety in term of consumers, authorities and food producers, and has great potential in the development of new sensing systems integrated in the food packaging, which are beyond the existing conventional technologies, like control of weight, volume, colour and appearance.

Early detection of contamination in food items is the current interest of research. Changes in concentration of volatile organic compounds emitted by the food items can provide valuable information about its contamination. Hence, a polypyrrole based gas sensor is developed for the detection and monitoring the organic volatiles produced from wheat bread during storage. Gas chromatography–mass spectroscopy results show that 1-heptanol, 1-pentanol, 1-octanol are the predominant volatiles produced from wheat bread during storage. Multifrequency impedance measurement technique is used to monitor the changes in electrical properties, mainly capacitance of the developed sensor over a frequency range 10 Hz–2 MHz upon exposure to the above organic volatiles produced from the bread during storage of 120 h. Electrical property data show that the quantitative change in the above volatiles has influence on the change in capacitance of the developed sensor.

Grain quality is assessed based on different grain features like appearance, shape, color, smell, flavour, moisture content, infections, presence of impurities, etc. The main indexes for the quality of grain samples are related to the color characteristics and the shape of the grain sample elements. Most of these characteristics are assessed visually by an expert. In this paper, an approach for an objective estimation of some basic grain quality characteristics is presented. It is based on a complex analysis of color images of the investigated objects. Due to the conceptual difference in presenting the objects’ color and shape characteristics, their assessment was performed separately. After that the results form these two assessments were combined and the final decision about the object’s classification to one of the quality groups defined by the standard regulations was made. Methods and tools for feature extraction and for object description, as well as for classification of the objects into predetermined groups were proposed. Three classifiers, based on radial basis elements, which were used for grain color and shape class recognition, were analyzed. Two different approaches for fusing the results from object color and object shape analyses were investigated. The training and testing errors of the developed procedures were evaluated.

A method is described for construction of an amperometric biosensor for specific determination of tyramine, using black gram tyramine oxidase immobilized covalently on an epoxy resin membrane. The biosensor had optimum response within 10 s at pH 8.5 and 35 °C. A linear relationship was observed between tyramine concentrations and current (mA) in the range of 0.24 to 3.47 mg/dL. The biosensor was employed for determination of tyramine in beer and sauce. The detection limit of sensor was 0.24 mg/dL. The mean analytical recovery of added tyramine (0.5 and 1.0 mg/dL) was 97.3 ± 2.3 and 95.9 ± 3.4%. Within and between batch coefficient of variation were 5.1 and 5.34%, respectively. Enzyme electrode showed 35% loss in its initial activity after its regular use over a period of 2 months. The biosensor has the advantage that it does not suffer from leaching of enzyme and measures tyramine specifically.

This study reports the effect of microwaving on the chemical composition [pH, total soluble solids (TSS), dry matter (DM) and total anthocyanins extraction], and the visible (VIS) and (NIR) spectra of red grape homogenates. It was observed that microwaving red grape homogenates prior to analysis improved the NIR calibrations for total anthocyanins (SECV: 0.21–0.13 mg g−1) and TSS (SECV: 0.89–0.54 °Brix), however no improvements in the NIR calibrations for DM were observed. Microwaving red grape samples prior to NIR scanning also caused an increased in absorbance for samples heated for up to 3 min, particularly in those wavelengths associated with water (1400 nm and 1930 nm). The practical implication of this study is that microwaving of red grape samples prior to scanning did not improve the NIR calibration statistics for the most common chemical parameters measured in red grapes.

The presence of sulfonamide residues in muscle foods is an important concern for consumers and regulatory agencies since these residues may pose potential health risks and result in an increase of drug-resistant bacteria. Surface enhanced Raman spectroscopy (SERS) was applied to analyze three sulfa drugs including sulfamerazine, sulfamethazine and sulfamethoxazole with concentrations ranging from 10 ng mL−1 to 5 μg mL−1. Partial least squares regression (PLS) and principal component analysis (PCA) were used for the spectral data analyses. The three sulfa drugs could be detected at concentration levels as low as 10 ng mL−1. For the quantitative analyses, the R 2 values of actual sulfa drug concentrations versus their concentrations predicted by the PLS models ranged from 0.8149 to 0.9009. Plotting of principal components based upon PCA showed clear, separated clusters between different sulfonamides. This study indicated potential for detection and determination of trace amounts of prohibited or restricted drugs with SERS technology.