Eat, but Verify: Low-Cost Portable Devices for Food Safety Analysis

Masna, Naren Vikram Raj; Paul, Shubhra Deb; Chen, Cheng; Mandal, Soumyajit; Bhunia, Swarup

doi:10.1109/mce.2018.2867969

Cited by 8 publications

(5 citation statements)

References 10 publications

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“…Resulting delays in procurement can lead to produce contamination due to inadequate storage [ 47 , 48 ]. In line with the international committee for food value and safety [ 3 , 10 , 56 – 58 ], we argue that the current procurement process could be streamlined using novel portable technologies [ 18 , 40 , 41 ]. Therefore, we tested the relevance of X-ray-based technology for the prediction of the key indicators of peanut produce price, kernel and shell mass.…”

Section: Discussionmentioning

confidence: 86%

X-ray driven peanut trait estimation: computer vision aided agri-system transformation

et al. 2022

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Background In India, raw peanuts are obtained by aggregators from smallholder farms in the form of whole pods and the price is based on a manual estimation of basic peanut pod and kernel characteristics. These methods of raw produce evaluation are slow and can result in procurement irregularities. The procurement delays combined with the lack of storage facilities lead to fungal contaminations and pose a serious threat to food safety in many regions. To address this gap, we investigated whether X-ray technology could be used for the rapid assessment of the key peanut qualities that are important for price estimation. Results We generated 1752 individual peanut pod 2D X-ray projections using a computed tomography (CT) system (CTportable160.90). Out of these projections we predicted the kernel weight and shell weight, which are important indicators of the produce price. Two methods for the feature prediction were tested: (i) X-ray image transformation (XRT) and (ii) a trained convolutional neural network (CNN). The prediction power of these methods was tested against the gravimetric measurements of kernel weight and shell weight in diverse peanut pod varieties1. Both methods predicted the kernel mass with R2 > 0.93 (XRT: R2 = 0.93 and mean error estimate (MAE) = 0.17, CNN: R2 = 0.95 and MAE = 0.14). While the shell weight was predicted more accurately by CNN (R2 = 0.91, MAE = 0.09) compared to XRT (R2 = 0.78; MAE = 0.08). Conclusion Our study demonstrated that the X-ray based system is a relevant technology option for the estimation of key peanut produce indicators (Figure 1). The obtained results justify further research to adapt the existing X-ray system for the rapid, accurate and objective peanut procurement process. Fast and accurate estimates of produce value are a necessary pre-requisite to avoid post-harvest losses due to fungal contamination and, at the same time, allow the fair payment to farmers. Additionally, the same technology could also assist crop improvement programs in selecting and developing peanut cultivars with enhanced economic value in a high-throughput manner by skipping the shelling of the pods completely. This study demonstrated the technical feasibility of the approach and is a first step to realize a technology-driven peanut production system transformation of the future.

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Section: Discussionmentioning

confidence: 86%

X-ray driven peanut trait estimation: computer vision aided agri-system transformation

et al. 2022

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“…Within this range lie signals from the vibration of organic chemical bonds such as oxygenhydrogen (O-H), carbon-hydrogen (C-H), nitrogen-hydrogen (N-H), and sulfurhydrogen (S-H), as well as their overtones [13]. Instrument cost and robustness is generally better for NIR than for MIR [14]. However, NIR spectral peaks tend to be weak and broad with significant overlapping of absorption peaks because of a combination of vibrational spectra from multiple chemical bonds, making straightforward interpretation difficult, if not impossible [15].…”

Section: Near-infrared Spectroscopy (Nirs)mentioning

confidence: 99%

“…Spectra in this range are very sensitive to chemical composition, leading to high specificity. Furthermore, organic functional groups produce well-delineated absorption bands in this region, a feature that can be exploited to individually separate different components present in a mixture by their unique fingerprints in the absorption spectrum [14]. Given the high cost of InGaAs detectors and the need for cooling to lower noise to a manageable level, MIR spectrometers generally feature single-element detector designs.…”

Section: Mid-infrared Spectroscopymentioning

confidence: 99%

Advanced Optical Technologies in Food Quality and Waste Management

Chauvin¹,

Duran²,

Ng³

et al. 2021

Innovation in the Food Sector Through the Valorization of Food and Agro-Food by-Products

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Food waste is a global problem caused in large part by premature food spoilage. Seafood is especially prone to food waste because it spoils easily. Of the annual 4.7 billion pounds of seafood destined for U.S. markets between 2009 and 2013, 40 to 47 percent ended up as waste. This problem is due in large part to a lack of available technologies to enable rapid, accurate, and reliable valorization of food products from boat or farm to table. Fortunately, recent advancements in spectral sensing technologies and spectroscopic analyses show promise for addressing this problem. Not only could these advancements help to solve hunger issues in impoverished regions of the globe, but they could also benefit the average consumer by enabling intelligent pricing of food products based on projected shelf life. Additional technologies that enforce trust and compliance (e.g., blockchain) could further serve to prevent food fraud by maintaining records of spoilage conditions and other quality validation at all points along the food supply chain and provide improved transparency as regards contract performance and attribution of liability. In this chapter we discuss technologies that have enabled the development of hand-held spectroscopic devices for detecting food spoilage. We also discuss some of the analytical methods used to classify and quantify spoilage based on spectral measurements.

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“…In this context, due to the complexity and vulnerability of the spice supply chain, the portability of the analysis devices is an advantage over tableware (more expensive and difficult to move) because they allow routinely monitoring along the entire supply chain. Ideally, food authentication device would have low cost and easy handling as a consumer‐grade product (Masna, Paul, Chen, Mandal, & Bhunia, ). However, although faster analysis protocols can be developed for more rigorous control, the results obtained with these devices are unrealistic for some applications (Ulusoy & Hecer, ).…”

Section: Portable/handheld Spectrometers For Spice's Authenticationmentioning

confidence: 99%

Nontargeted Analytical Methods as a Powerful Tool for the Authentication of Spices and Herbs: A Review

Oliveira

Cruz-Tirado

Barbin

2019

Comp Rev Food Sci Food Safe

110

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Food fraud in herbs and spices is an important topic, which has led to new technologies being studied as potential tools for fraud identification. Nontargeted technologies have proven to be a useful tool for the authentication of herbs and spices. The present review focuses on the use of near‐infrared, hyperspectral imaging, Fourier‐transform infrared, Raman, nuclear magnetic resonance, and electron spin resonance spectroscopy for the authentication of spices, which includes the determination of origin and irradiated spices and the identification of adulterants. The methods developed based on vibrational spectroscopy combined with chemometric techniques seem to be promising tools for determining the presence of adulterants and contaminants in herbs and spices. On the other hand, nuclear magnetic resonance seems to be the most efficient technology to determine the origin of herbs and spices although, for some cases, studies with near‐infrared spectroscopy can be a viable substitute. Electron spin resonance spectroscopy is the technique par excellence used for the authentication of irradiated herbs and spices, so its use should be expanded to many more spices’ varieties. Portable devices are preferred by those involved in the food industry, due to its manageability and low cost. Data fusion and big data are shown as promising tools for spice fraud control. In conclusion, spectroscopic techniques show a great efficiency to authenticate spices, although their evaluation must be expanded to other spice varieties, to new strategies of data analysis (as data fusion and big data), and to the use of portable devices.

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Eat, but Verify: Low-Cost Portable Devices for Food Safety Analysis

Cited by 8 publications

References 10 publications

X-ray driven peanut trait estimation: computer vision aided agri-system transformation

X-ray driven peanut trait estimation: computer vision aided agri-system transformation

Advanced Optical Technologies in Food Quality and Waste Management

Nontargeted Analytical Methods as a Powerful Tool for the Authentication of Spices and Herbs: A Review

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