Study of the Evolution of Pigments from Freshly Pressed to 'On-the-Shelf' Extra-Virgin Olive Oils by Means of Near-UV Visible Spectroscopy

Machine learning-enabled high-throughput industry screening of edible oils

Long-term consumption of mixed fraudulent edible oils increases the risk of developing of chronic diseases which has been a threat to the public health globally. The complicated global supply-chain is making the industry malpractices had often gone undetected. In order to restore the confidence of consumers, traceability (and accountability) of every level in the supply chain is vital. In this work, we shown that machine learning (ML) assisted windowed spectroscopy (e.g., visible-band, infra-red band) produces high-throughput, non-destructive, and label-free authentication of edible oils (e.g., olive oils, sunflower oils), offers the feasibility for rapid analysis of large-scale industrial screening. We report achieving high-level of discriminant (AUC > 0.96) in the large-scale (n ≈ 11,500) of adulteration in olive oils. Notably, high clustering fidelity of 'spectral fingerprints' achieved created opportunity for (hypothesis-free) self-sustaining large database compilation which was never possible without machine learning. (137 words).

Application, challenges and future prospects of recent nondestructive techniques based on the electromagnetic spectrum in food quality and safety

Safety and quality aspects of food products have always been critical issues for the food production and processing industries. Since conventional quality measurements are laborious, time-consuming, and expensive, it is vital to develop new, fast, non-invasive, cost-effective, and direct techniques to eliminate those challenges. Recently, non-destructive techniques have been applied in the food sector to improve the quality and safety of foodstuffs. The aim of this review is an effort to list non-destructive techniques (X-ray, computer tomography, ultraviolet-visible spectroscopy, hyperspectral imaging, infrared, Raman, terahertz, nuclear magnetic resonance, magnetic resonance imaging, and ultrasound imaging) based on the electromagnetic spectrum and discuss their principle and application in the food sector. This review provides an in-depth assessment of the different non-destructive techniques used for the quality and safety analysis of foodstuffs. We also discussed comprehensively about advantages, disadvantages, challenges, and opportunities for the application of each technique and recommended some solutions and developments for future trends.

In Situ Visible Spectroscopic Daily Monitoring of Senescence of Japanese Maple (Acer palmatum) Leaves

The degradation of green leaves in autumn after their photosynthetic activities is associated with decreases in chlorophylls and increases in anthocyanins. However, the sequential orders of these processes are not well understood because of a lack of continuous monitoring of leaves in the same positions. Therefore, the senescence processes of Japanese maple (Acer palmatum) leaves were followed daily in the same positions for approximately 60 days using visible spectroscopy with an original handheld visible-near-infrared spectrometer. The obtained reflection spectra were converted to absorption spectra and band areas of chlorophyll a and anthocyanins were determined. Decreases in the chlorophyll a band area with time show two-step exponential decreases corresponding to slow and fast first-order decrease rates. A rapid decrease in chlorophyll a started after an increase in anthocyanin. Therefore, the leaf senescence started through a slow decrease in chlorophyll a (20-30 days), followed by a rapid increase in anthocyanins (~20 days), followed by a rapid decrease in chlorophyll a (10-20 days). The formation of anthocyanins has been proposed to protect leaf cells from losing chlorophylls through solar radiation damage. The obtained sequential changes of pigments support this light screen hypothesis. (199 words < 200 words).

Rhodotorula mucilaginosa-alternative sources of natural carotenoids, lipids, and enzymes for industrial use

Biotechnologically useful yeast strains have been receiving important attention worldwide for the demand of a wide range of industries. Rhodotorula mucilaginosa is recognized as a biotechnologically important yeast that has gained great interest as a promising platform strain, owing to the diverse substrate appetites, robust stress resistance, and other gratifying features. Due to its attractive properties, R. mucilaginosa has been regarded as an excellent candidate for the biorefinery of carotenoids, lipids, enzymes, and other functional bioproducts by utilizing low-cost agricultural waste materials as substrates. These compounds have aroused great interest as the potential alternative sources of health-promoting food products, substrates for so-called third-generation biodiesel, and dyes or functional ingredients for cosmetics. Furthermore, the use of R. mucilaginosa has rapidly increased as a result of advancements in fermentation for enhanced production of these valuable bioactive compounds. This review focuses on R. mucilaginosa in these advancements and summarizes its potential prospects as alternative sources of natural bioproducts.