Determination of the geographic origin of garlic using the bioelement content and isotope signatures

Optimizing geographical traceability models of Chinese Lycium barbarum: Investigating effects of region, cultivar, and harvest year on nutrients, bioactives, elements and stable isotope composition

Lycium barbarum is a type of "medicine-food homology" whose geographical origin has attracted strong interest from consumers due to different regional quality characteristics. A sophisticated OPLS-DA model to verify Lycium barbarum origin was developed using 266 samples gathered from five cultivars in two regions between 2020 and 2022, which was based on 67 indices, including nutrients, bioactives, elements and stable isotopes. Twelve variables (fructose, δ2H, glucose, tartaric acid, Mo, Na, Sr, His, Phe, Mn, Lys and Rb) were selected to refine models that could distinguish Lycium barbarum origin without being impacted by cultivar or year. The model of training set and testing set samples had discrimination rates of 100 % and 94.71 % to 98.28 %, suggesting an optimized multi-variate analysis strategy using OPLS-DA model could correctly predict the origin of blind Lycium barbarum samples. This study provides new evidence for constructing a reliable traceability model for the geographical origins of Lycium barbarum.

Gas chromatography-stable isotope ratio mass spectrometry prior solid phase microextraction and gas chromatography-tandem mass spectrometry: development and optimization of analytical methods to analyse garlic (Allium sativum L.) volatile fraction

Garlic (Allium sativum L.) is not only appreciated for its flavour and taste, but it is also recognized for various health properties. The European Commission, through the attribution of the Protected Designation of Origin (PDO) certification mark, has officially recognized some specific varieties of garlic. To protect not only the commercial value but also the reputation of this appreciated product, effective tools are therefore required. For the first time, a new compound specific isotope analysis method based on carbon stable isotopic ratio measurement of the three major volatile garlic compounds allyl alcohol (AA), diallyl disulphide (DD) and diallyl trisulphide (DT) through head-space solid phase microextraction (HS-SPME) followed by gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) was developed. A within-day standard deviation (Srwithin-day) of 0.3 ‰, 0.4 ‰ and 0.2 ‰ for δ(13C) and a between-day standard deviation (Srbetween-day) of 0.8 ‰, 1.0 ‰ and 0.6 ‰ of AA, DT and DD was estimated. For the first time, the ranges of isotopic variability for the three volatile compounds of red garlic from two neighbouring Italian regions (Abruzzo and Lazio) were defined analysing 30 samples. The same dataset was also considered in analysing the percentage composition of the previously mentioned three volatile compounds through HS-SPME followed by gas chromatography-tandem mass spectrometry (GC-MS/MS). The two analytical approaches were combined in this explorative study, aiming to provide potential parameters to discriminate garlic samples based on their geographical origin.

Breeding value of non-shooting forms of winter garlic in the conditions of the Right Bank Forest-Steppe of Ukraine

Purpose. To investigate the degree of reduced scape of softneck collection specimens of winter garlic of different ecological and geographical origin in the conditions of the Right Bank Forest-Steppe of Ukraine. Methods. During 2020–2022, nine local and introduced varieties of winter garlic (Nos. 19, 27, 33, 43 and 44 from Cherkasy) were stu­died in field conditions (Uman, 48°46’N, 30°14’E) region, No. 14 from Ternopil region, No. 1 from Spain, No. 16 from France and No. 35 from Azerbaijan). Generally accepted methods of genetico-statistical analysis were used to evaluate the garlic collection. Results. The research revealed that the weight of the bulb decreased by 7.6–31.1%, depending on the sample, and the yield by 6.1–38.6% during the formation of a reduced scape. Among the collection samples, according to the “bulb weight” indicator, Nos. 16 and 44 stood out – 57.22 and 52.24 g, respectively, of the sample. Adap­table for this feature were samples Nos. 16, 19 and 44; intensive – Nos. 16, 27, 33 and 44, and stable samples were Nos. 14, 19, 35 and 43. A significant relationship between the coefficient of genetic and environmental variation (CVG/CVA) for the traits “bulb weight” and “yield” was revealed. However, CVG/CVA ratio ≥ 1 is required to obtain high performance. Samples were selected as the initial material for further breeding based on the “yield” feature: according to adaptability and ecological plasticity – Nos. 16 and 44; according to stability – Nos. 19, 35 and 43 and samples of the intensive type – 16, 27, 33 and 44, which will ensure high yields in optimal cultivation conditions. All studied samples that formed air bulbs were characterized by a very large 1000 bulb weight, on average 1156.76 g. The maximum of 1000 bulb weight was characteristic for samples No. 16 and 27 – 1225.73 and 1638.0 g, respectively. Conclusions. The data obtained in the Right Bank Forest-Steppe of Ukraine will be used to develop a breeding research scheme under the conditions of introduction. As a result of the research, a working collection of raw material was created for the breeding of garlic by the classical method – clonal breeding.

Convolutional Neural Network for Object Detection in Garlic Root Cutting Equipment

Traditional manual garlic root cutting is inefficient and can cause food safety problems. To develop food processing equipment, a novel and accurate object detection method for garlic using deep learning—a convolutional neural network—is proposed in this study. The you-only-look-once (YOLO) algorithm, which is based on lightweight and transfer learning, is the most advanced computer vision method for single large object detection. To detect the bulb, the YOLOv2 model was modified using an inverted residual module and residual structure. The modified model was trained based on images of bulbs with varied brightness, surface attachment, and shape, which enabled sufficient learning of the detector. The optimum minibatches and epochs were obtained by comparing the test results of different training parameters. Research shows that IRM-YOLOv2 is superior to the SqueezeNet, ShuffleNet, and YOLOv2 models of classical neural networks, as well as the YOLOv3 and YOLOv4 algorithm models. The confidence score, average accuracy, deviation, standard deviation, detection time, and storage space of IRM-YOLOv2 were 0.98228, 99.2%, 2.819 pixels, 4.153, 0.0356 s, and 24.2 MB, respectively. In addition, this study provides an important reference for the application of the YOLO algorithm in food research.

Chemometric origin classification of Chinese garlic using sulfur-containing compounds, assisted by stable isotopes and bioelements

Geographical origin discrimination of agro-products is essential to guarantee food safety and fair trade. Garlic samples cultivated in six provinces or major production regions in China were characterized for stable isotopes (δ¹³C, δ²H, δ¹⁸O, δ¹⁵N, and δ³⁴S), bioelemental contents (% C, % N and % S), and sulfur-containing compounds (8 organosulfur components and 2 amino acids). Results showed that many of the 18 analyzed garlic variables had significant differences among production regions. Some sulfur-containing compounds found in garlic from different provinces had a strong correlation with sulfur isotopes, suggesting garlic sulfur isotopes were also affected by geographical origin. Two supervised pattern recognition models (PLS-DA and k-NN) were developed using stable isotopes, elemental contents, and sulfur-containing compounds, and had a discrimination accuracy of 93.4 % and 87.8 %, respectively. Chemometric classification models using multi-isotopes, elements and sulfur-containing compounds provides a useful method to authenticate Chinese garlic origins.

Exploration of multifunctional properties of garlic skin derived cellulose nanocrystals and extracts incorporated chitosan biocomposite films for active packaging application

For many years, garlic has been used as a condiment in food and traditional medicine. However, the garlic skin, which accounts for 25% of the garlic bulk, is considered agricultural waste. In this study, cellulose nanocrystals (CNCs) and garlic extract (GE) from garlic skin were isolated and used as fillers to manufacture biocomposite films. The films were characterized in terms of UV barrier, thermal, mechanical, biodegradability, and antimicrobial activity. The chitosan-containing films and CNCs have significantly improved the films' tensile strength, Young's modulus, and elongation but decreased the film transparency compared to chitosan films. The combination of the CNCs and GE, on the other hand, slightly reduced the mechanical properties. The addition of CNCs slightly decreased the film transparency, while the addition of GE significantly improved the UV barrier properties. Thermal studies revealed that the incorporation of CNC and GE had minimal effect on the thermal stability of the chitosan films. The degradability rate of the chitosan composite films was found to be higher than that of the neat chitosan films. The antimicrobial properties of films were studied against Escherichia coli, Streptomyces griseorubens, Streptomyces alboviridis, and Staphylococcus aureus, observing that their growth was considerably inhibited by the addition of GE in composite films. Films incorporating both CNCs and GE from garlic skin hold more promise for active food packaging applications due to a combination of enhanced physical characteristics and antibacterial activity.

Dietary homogenization and spatial distributions of carbon, nitrogen, and sulfur isotope ratios in human hair in South Korea

Dietary homogenization has progressed worldwide due to westernization and the globalization of food production systems. We investigated dietary heterogeneity in South Korea by examining the spatial distribution of carbon (C), nitrogen (N), and sulfur (S) isotope ratios using 264 human hair samples. Overall, variation in isotope values was small, indicating low dietary heterogeneity. We detected differences in δ13C, δ15N, and δ34S values between administrative provinces and metropolitan cities; inter-regional differences were typically < 1 ‰. Values of δ34S were significantly lower in hair samples from inland regions relative to those from coastal locations, and a similar pattern was observed in δ15N values. Understanding geographic variation in δ34S and δ15N values in human hair is useful for provenancing humans in South Korea.