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.

Mycotoxins such as aflatoxins (AFs), ochratoxin A (OTA) fumonisins (FMN), deoxynivalenol (DON), zearalenone (ZEN), and patulin are stable at regular food process practices. Ozone (O ₃ ) is a strong oxidizer and generally considered as a safe antimicrobial agent in food industries. Ozone disrupts fungal cells through oxidizing sulfhydryl and amino acid groups of enzymes or attacks the polyunsaturated fatty acids of the cell wall. Fusarium is the most sensitive mycotoxigenic fungi to ozonation followed by Aspergillus and Penicillium . Studies have shown complete inactivation of Fusarium and Aspergillus by O ₃ gas. Spore germination and toxin production have also been reduced after ozone fumigation. Both naturally and artificially, mycotoxin‐contaminated samples have shown significant mycotoxin reduction after ozonation. Although the mechanism of detoxification is not very clear for some mycotoxins, it is believed that ozone reacts with the functional groups in the mycotoxin molecules, changes their molecular structures, and forms products with lower molecular weight, less double bonds, and less toxicity. Although some minor physicochemical changes were observed in some ozone‐treated foods, these changes may or may not affect the use of the ozonated product depending on the further application of it. The effectiveness of the ozonation process depends on the exposure time, ozone concentration, temperature, moisture content of the product, and relative humidity. Due to its strong oxidizing property and corrosiveness, there are strict limits for O ₃ gas exposure. O ₃ gas has limited penetration and decomposes quickly. However, ozone treatment can be used as a safe and green technology for food preservation and control of contaminants.

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,targetandbacterial 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 aK-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.

Citrus Huanglongbing (HLB), also known as greening, is a destructive disease caused by the fastidious, phloem-colonizing bacteria Candidatus Liberibacter spp.; ‘Ca. Liberibacter asiaticus’ (Las) is the most prevalent of the species causing HLB. The Asian citrus psyllid (ACP, Diaphorina citri) transmits Las. HLB is threatening citrus production worldwide, and there is no cure for infected trees. Management strategies targeting diseased trees at different stages of colonization by Las are needed for sustainable citrus production in HLB-endemic regions. We evaluated the effect of the combinations of plant defense elicitors, nitrogen (N) fertilizer, and compost on mildly diseased trees. We tested thermotherapy on severely diseased trees and assessed tree protectors to prevent feeding by ACP, thus preventing Las from being transmitted to new plantings that replaced HLB-moribund trees. After four applications over two consecutive growing seasons we found that the combination of compost, urea, and plant defense elicitors β-aminobutyric acid, plus ascorbic acid and potassium phosphite with or without salicylic acid, slowed down the progression of HLB and reduced disease severity by approximately 18%, compared with the untreated control. Our data showed no decline in fruit yield, indeed treatment resulted in a higher yield compared with the untreated control. Thermotherapy treatment (55°C for 2 min) exhibited a suppressive effect on growth of Las and progress of HLB in severely diseased trees for 2 to 3 months after treatment. The tree protectors prevented feeding by ACP, and therefore young replant trees remained healthy and free from infection by Las over the 2-year duration of the experiment. Taken together, these results may contribute to a basis for developing a targeted approach to control HLB based on stage of host colonization, application of plant defense elicitors, N fertilizer, compost, thermotherapy, and tree protectors. There is potential to implement these strategies in conjunction with other disease control measures to contribute to sustainable citrus production in HLB-endemic regions.

Airborne multispectral and hyperspectral imaging can be used to detect potentially diseased trees rapidly over a large area using unique spectral signatures. Ground inspection and management can be focused on these detected zones, rather than an entire grove, making it less labor-intensive and time-consuming. We propose a method to detect the areas of citrus groves infected with citrus greening disease [Huanglongbing (HLB)] using airborne hyperspectral and multispectral imaging. This would prevent further spread of infection with efficient management plans of infected areas. Two sets of hyperspectral images were acquired in 2007 and 2009, from different citrus groves in Florida. Multispectral images were acquired only in 2009. A comprehensive ground truthing based on ground measurements and visual check of the citrus trees was used for validating the results using 2007 images. In 2009, a more accurate polymerase chain reaction test for selected trees from ground truthing was carried out. With a handheld spectrometer, ground spectral measurements were obtained along with their degrees of infection. A hyperspectral imaging software (ENVI, ITT VIS) was used for the analysis. HLB infected areas were identified using image-derived spectral library, mixture tuned matched filtering (MTMF), spectral angle mapping (SAM), and linear spectral unmixing. The accuracy of the MTMF method was greater than the other methods. The accuracy of SAM using multispectral images (87%) was comparable to the results of the MTMF and also yielded higher accuracy when compared to SAM analysis on hyperspectral images. A possible inaccurate ground truthing for the grove in 2007 generated more false positives.