Search

The suitability of adult male the navel orangeworm, Amyelois transitella (Walker) for Sterile Insect Technique (SIT) has been reported for both high energy gamma (>1 MeV) and low energy x-ray (90 keV) sterilization. However, research regarding sterilization of NOW larvae and pupae by gamma irradiation indicated nonsuitability due to high mortality. Here, NOW larvae and pupae were irradiated to doses up to 50 Gy with 90 keV x-rays, then paired with nonirradiated colony mates. Sterility of surviving insects was determined by the presence or absence of hatched neonates. While presence of offspring does not guarantee viability, the absence does guarantee sterility (as is appropriate for SIT) and was thus the measure used here. Early stage larvae experienced 77% mortality at a dose of 30 Gy, versus 20% for nonirradiated control. At 40 Gy, mortality reached 98%. Of surviving early stage larvae at 30 Gy, 29% of moth pairs produced offspring. For late stage larvae, no offspring were produced at 40 Gy, but mortality was 73%. For pupae, mortality reached 53% at 30 Gy with 13% still producing neonates, while mortality reached 98% at 40 Gy. These results are consistent with reported results for gamma irradiation of NOW larvae where sterility was observed somewhere between the 30 Gy and 60 Gy data points, but mortality was high. This further confirms the lack of suitability of NOW irradiated in the larval stage, whether by gamma or x-ray, and supports the hypothesis that x-ray and gamma treatments are biologically equivalent at equal doses.

Pollination-variant persimmon (Diospyros kaki) fruit exhibits two distinct phenotypes based upon pollination status. Pollinated fruit are seeded and develop flesh that is brown in color, nonastringent, delectable in taste and highly desirable, whereas non-pollinated fruit retain unseeded orange-color flesh that is astringent and virtually unpalatable. Growers face the problem that both types of flesh may be present in the same persimmon fruit, and external skin color is uniformly orange, regardless of the extent of astringency. Thus, in this work, the nondestructive measurement modalities of nuclear magnetic resonance (NMR) relaxometry and near-infrared (NIR) spectroscopy were investigated for their ability to screen pollination-variant persimmons for extent of nonastringent flesh. Fruit from a diverse sample set – including six cultivars stored for varying lengths of time and exhibiting an array of astringency levels – was subjected to the two nondestructive measurements and then evaluated destructively for astringency using a sequential blotting and visual sensory analysis approach. The sensory astringency score was then used as the response variable to construct partial least squares – discriminant analysis (PLS-DA) models from spectra from each modality on its own as well as for concatenated spectra, which combined the information from both modalities. These PLS-DA models performed well, showing a maximum misclassification rate of 33%. When the most market-relevant astringency threshold was used, NIR slightly outperformed NMR. When different astringency screening thresholds were considered, combining the two modalities did not consistently improve PLS-DA model performance. Thus, both modalities show promise for nondestructive characterization of the flesh of pollination-variant persimmons.

Near-Infrared (NIR) spectroscopy (900–2600 nm) was evaluated as a rapid, non-destructive method for detection of zebra chip disease (ZC) in potatoes. Two models were tested; one that directly correlated spectra with ZC and one that measured sugar concentrations which in turn are known to be correlated with ZC. Applying stepwise regression in conjunction with canonical discriminant analysis to raw spectra, total classification accuracy of 98.35% was achieved in discriminating infected potatoes from control, with 2% false negative and 1% false positive error rates. The same analysis applied to 2nd derivative spectra yielded 97.25% accuracy with equal false negative and false positive error rates. Canonical discriminant analysis applied to sucrose, glucose, and fructose concentrations previously determined by high-performance liquid chromatography yielded 96.7% classification accuracy, with 4.3% false positive and 2.3% false negative rates. Accuracy did not significantly differ when fructose was excluded from the model. Partial least squares regression models built to predict sugar concentrations from the 2nd derivative NIR spectra resulted in R2 for actual vs. predicted concentrations of 0.7 and 0.72 respectively for sucrose and glucose, 0.63 for fructose, and 0.81 for total sugars. Given the relatively low R2 values in measuring sugar concentrations directly from the spectra it was concluded that classification accuracy is highest for models that directly correlate spectral features to ZC without considering sugar concentrations. Furthermore, this indicates that although NIR can detect infection, it may not be effective for evaluating severity of ZC in fresh potatoes.

A non-destructive method based on visible and near- infrared spectroscopy was investigated for determining the dry matter and soluble solids contents of dehydrator onions (485 samples) at the base, equatorial, and shoulder locations and of garlic cloves (270 samples) at the equatorial location. The interactance spectrum (400–1000 nm) of each sample was measured non-destructively within a 5 s period using a handheld spectrometer that employed an optical design of 0° angle between the incident illumination and the detection view. The spectral data were used to develop partial least square regression models to predict the dry matter and soluble solids contents. The results showed that the predictive performance of the onion model with optical measurements taken at the equator and shoulder locations were superior to the performance at the base location. For dry matter and soluble solids contents, the onion model performance had coefficient of determination (R2) values of 0.96 and 0.97, with RMSECV values of 1.29 and 1.23, respectively. Similarly, for garlic models, the R2 values were 0.87 and 0.72, with RMSECV values of 1.14 and 1.09, for dry matter and soluble solids contents respectively. These results suggested that the handheld instrument has excellent potential to aid in onion and garlic production processing as a rapid, non-destructive technique to identify the dry matter and soluble solids contents in the field or in an industrial setting.

Near infrared spectroscopy in the wavelength region from 800 to 2600 nm was evaluated as the basis for a rapid, nondestructive method for the detection of pits and pit fragments in fresh cherries. Partial least squares discriminant analysis following various spectral pretreatments was applied to spectra of cherries with either no pit, a whole pit, a half pit, or a quarter pit to test various classification schemes. An iterative algorithm tested all combinations of pretreatments and parameters as input to the partial least squares discriminant analysis. In addition, a step forward feature selection algorithm was used to identify the most significant wavebands in order to isolate small sets (

NIR spectroscopy and physical properties derived from image analysis were evaluated as potential features for the classification of seed kernels from two pine nut species (P. pinea L. and P. sibirica Du Tour) using Partial Least Squares Discriminant Analysis (PLS-DA). Model performances were evaluated in terms of specificity, sensitivity and accuracy. Data pre-treatments were essential for achieving excellent performances (accuracy rate > 95%) in all tests. The interval PLS-DA highlighted that the most important features for (1) the NIR method were the absorption bands at 1640–1658, 1720–1738 and 1880–1998 nm, while for (2) the image analysis were kernel eccentricity, kernel major axis length, kernel lightness (L*) and kernel perimeter. The results demonstrate potential of both techniques for discriminating the two pine nut species.

Two natural compounds (quercetin and curcumin) were tested as sensitizing or protecting agents for Navel Orangeworm (NOW) larvae under x-ray sterilization, with the aim to reduce required doses and thus facilitate the substitution of x-ray for radioisotopes. The compounds were added to NOW diet at concentrations between 0 and 1.0 mmol kg−1 and subsequent reared male larvae were subjected to x-ray irradiation (90 keV, 9 mA) to doses up to 15 Gy. Upon emergence as adults, surviving male NOW were paired with colony virgin females and placed in isolation for observation of deformity, mortality, and fertility. Treatments included rearing larvae on infused diet before irradiation, after irradiation, and both. Results were tabulated as percentage of insects that were dead/deformed, infertile, or fertile and subjected to chi-squared analysis. While insect populations subjected to quercetin treatments were not found to be significantly different from control at any x-ray dose, all curcumin treatments yielded significant differences at an absorbed dose of 10 Gy, both in terms of decreased mortality and fertility. While none of the treatments resulted in acceptable mortality/deformity rates, the observed effects strongly support the need for continued testing of natural compounds for their efficacy to reduce required dose levels for sterilization.

Aspergillus flavus and Aspergillus parasiticus are ubiquitous in natural environments and have the potential to produce aflatoxins that can cause both chronic and acute diseases in humans and animals. The near-infrared (800–2500 nm) reflectance spectra of almonds from the 2012 and 2013 harvest seasons inoculated with one selected isolate of either A. flavus or A. parasiticus were analysed to determine if the spectra could be used to distinguish infected almonds from uninfected control almonds. A canonical classifier was developed that could discriminate infected almonds from the uninfected control kernels with a total cross-validation error rate of 0.26% and zero false negative errors. Additionally, a follow-up canonical classifier was developed to evaluate the potential to discriminate between infections by the two Aspergillus species, once infection was detected. Spectral analysis indicated that the NIR wavebands associated with lipid content were the most indicative factors in both identifying the infected almonds as well as discriminating between almonds infected by the A. flavus or the A. parasiticus isolate. Further comparison of the canonical discriminant analysis results from the 2nd derivative spectra and the original spectra also suggested that the chemical differences caused by the fungal metabolism had a much greater contribution to the discriminant function than the structural changes caused by the fungal invasion. The wavelengths identified in this study could be helpful in developing non-destructive multispectral sensing systems to effectively scan and detect almonds with fungal infection.

The multidisciplinary and versatile characteristics of biosensors make them very attractive topics to introduce science and engineering concepts into a secondary education classroom. Some of the techniques used in biosensors are easy to demonstrate and can be intriguing to students. We evaluated which application areas and techniques were most intriguing to students through a survey and then developed a 60 to 90 min introductory lesson plan with hands-on experience. The survey was conducted to determine students’ greatest interests and motivations among four biosensor applications (medical diagnostics, food safety, biosecurity, and environmental monitoring) as well as seven techniques used in biosensors: genetic engineering, nanotechnology, circuit building, microfabrication, 3D printing, smartphone utilization, and computer programming. For the application, the middle school students showed the most interest in food safety, followed by environmental monitoring and medical diagnostics. The high school students showed the most interest in medical diagnostics. For the techniques used in biosensors, the middle school students showed the most interest in 3D printing, followed by circuit building and smartphone utilization, while the high school students showed the most interest in genetic engineering and nanotechnology. To capture the most interest early in the students’ education, we designed a 60 to 90 min lesson plan for middle school students using the application areas of food safety and environmental monitoring, as well as the techniques of 3D printing, circuit building, and smartphone utilization. Simplified sampling protocols were introduced for monitoring E. coli from lettuce, Salmonella from chicken packaging, and influenza A from aerosols. As an example of a biosensor, a commercial glucose assay kit was demonstrated using a simple photometric circuit (including an LED and a photodiode) as an optical transducer. As a second example, a commercial pregnancy test strip was demonstrated using a smartphone camera as an optical transducer. Finally, a plastic attachment to a smartphone, made with a 3D printer, was demonstrated to improve the sensitivity and reproducibility of the same pregnancy test. This lesson was carried out in a classroom, and the results exemplify the potential benefit of using biosensor research in a middle school classroom as well as the possibility of inspiring students toward science and engineering fields of study or careers.

The worldwide consumption of dried carrot (Daucus carota L.) is on a growing trend. Conventional methods for drying carrots include hot-water blanching followed by hot-air drying, which is usually uncontrolled and therefore prone to product quality deterioration. Thus, there is a need for innovative drying systems that yield high-value end products. In this study, the efficacy of NIR spectroscopy for the non-destructive monitoring of physicochemical changes and drying behaviour in organic carrot slices during 8-h hot-air drying at 40 °C was demonstrated using Partial least squares (PLS) regression and PLS discriminant analysis (PLS-DA). The impact of hot-water blanching pre-treatment (at 95 °C for 1.45 min) for enzyme inactivation on performances of both regression and classification models was also evaluated. PLS regression models were successfully developed to monitor changes in water activity (R2 = 0.91–0.96), moisture content (R2 = 0.97–0.98), total carotenoids content (R2 = 0.92–0.96), lightness for unblanched carrots (R2 = 0.80–0.83) and hue angle for blanched samples (R2 = 0.85–0.87). Soluble solids content prediction was poor for both treatments (RMSEP = 3.43–4.40). Classification models were developed to recognise dehydration phases of carrot slices on the basis of their NIR spectral profile using K-means and PLS-DA algorithms in sequence. The performance of each PLS-DA model was defined based on its accuracy, sensitivity and specificity rates. All of the selected models provided from good (> 0.85) to excellent (> 0.95) sensitivity and specificity for the predefined drying phases. Feature selection procedures yielded both regression and classification models with performances very similar to models computed from the full spectrum. Moscetti, R., Haff, R.P., Ferri, S.et al.Real-Time Monitoring of Organic Carrot (var. Romance) During Hot-Air Drying Using Near-Infrared Spectroscopy.Food Bioprocess Technol10,2046–2059 (2017). https://doi.org/10.1007/s11947-017-1975-3 &nbsp

An optofluidic lab-on-a-chip system and subsequent sampling procedure were developed for detecting bacteria from soil samples utilizing light scattering detection of immunoagglutination assay. This system and protocol detected the presence of Escherichia coli K12 from soil particles in near real-time (10 min) with a detection limit down to 1 CFU mL-1, which is superior to the conventional methods, such as plate counting or polymerase chain reaction (PCR) assays. E. coli solutions were applied to the surface of a mock soil system and incubated overnight. The light scattering immunoagglutination assays using the optofluidic lab-on-a-chip showed two E. coli peaks over the soil depth, one at 1 cm and the other at 4 cm. Comparison with bacterial viability assay and Bradford protein assay revealed that smaller E. coli colonies were found at 1 cm depth and larger colonies at 4 cm, while free antigens adsorbed and desorbed more reversibly at both locations. The two peaks were explained by the two-step process of protein-surface interaction and gravitational force. The target molecules with small sizes (free antigens and single cells) arrived at the soil particle surface faster according to the diffusion model, and the larger E. coli colonies arrived later where the soil surface was already occupied. Because the free antigens adsorbed and desorbed in a more reversible manner, they could be found throughout the depth of the mock-up soil system, whereas the larger E. coli colonies traveled through the void space within soil particles via gravitational force and accumulated at the bottom of where the liquid reached. This work also demonstrates a device and procedure that could be potentially implemented in field studies. With proper soil sample handling protocol and light scattering detection of immunoagglutination assay in an optofluidic lab-on-a-chip, developing more complete bacteria subsurface transport models with actual field results can be achieved.

Mycotoxins, which are toxins produced by fungi, can pose great danger to human health with their acute and chronic effects when contaminated foods (grains, fruits, meat, or milk) are ingested. Fungal infections in food crops are extremely common and many developed countries have set standards to monitor and control their imported and exported food products. The analytical methods required to quantify the toxin concentrations are accurate and sensitive but often destructive thus rely on sampling to determine the contamination status. Infrared spectroscopy has gained a lot of attention for its ability to non-destructively provide critical information of samples, which can help reduce the uncertainties inherited from the sampling methods. Several successful examples in identifying fungal infection from agricultural commodities provide great hope for a faster and more cost-effective screening method to help eliminate the health threats.

A smartphone-utilized biosensor was developed for detecting microbial spoilage on ground beef, without using antibodies, microbeads or any other reagents, towards a preliminary screening tool for microbial contamination on meat products, and potentially towards wound infection. Escherichia coli K12 solutions (10(1)-10(8) CFU/mL) were added to ground beef products to simulate microbial spoilage. An 880 nm near infrared LED was irradiated perpendicular to the surface of ground beef, and the scatter signals at various angles were evaluated utilizing the gyro sensor and the digital camera of a smartphone. The angle that maximized the Mie scatter varied by the E. coli concentration: 15° for 10(8) CFU/mL, 30° for 10(4) CFU/mL, and 45° for 10 CFU/mL, etc. SEM and fluorescence microscopy experiments revealed that the antigens and cell fragments from E. coli bonded preferably to the fat particles within meat, and the size and morphologies of such aggregates varied by the E. coli concentration.