Search Results (10)

This study examines the chemical composition and antioxidant properties of iron walnut oil (IWO) from different Chinese regions, using ultra-high-performance liquid chromatography–quadrupole time-of-flight mass spectrometry for the analysis of phenolic compounds. Regional variations were identified in fatty acid profiles, with elevated α-linolenic acid levels observed in samples from cooler climates (e.g., Liaoning, sample 1) that were 60% higher than in samples from warmer regions (e.g., Sichuan, sample 2). Antioxidant properties, quantified using 1,1-diphenylpicryl phenyl hydrazine (DPPH), 2,2-azinobis-3-ethylbenzothiazoline-6-sulfonate (ABTS), and Ferric ion reducing antioxidant power (FRAP) assays, corresponded to both oil polyphenol content (up to 62.91 mg/kg) and γ-tocopherol concentrations (268.68–525.05 mg/kg). Nineteen phenolic acids and flavonoids were identified, including ellagic acid, gallic acid, p-hydroxybenzoic acid, syringic acid, vanillic acid, quercetin, caffeic acid, ferulic acid, p-coumaric acid, coniferol, and pinoresinol. This comprehensive analysis underscores the nutritional and therapeutic potential of IWO, and delineates the impact of geographic and environmental factors on its quality, providing a scientific foundation for further research and development aimed at enhancing food industry standards and exploring natural product chemistry. Full article

Walnut is one of four major nuts in the world. China has abundant walnut germplasm resources, but there are still shortcomings in the identification of germplasm resources. This study used different walnut varieties as materials and developed 14 high-quality SSR molecular markers from 60 pairs of primers based on genome re-sequencing results. This study analyzed the genetic diversity of Chinese walnut genetic resources using 14 selected SSR markers. A total of 64 alleles were detected in 47 walnut resources, with an average of 4.571 alleles per locus. The variation range of polymorphism information content was 0.096~0.711, with an average value of 0.422. Cluster analysis, population genetic structure, and principal coordinate analysis divided 47 walnut resources into ordinary walnuts, Juglans hopeiensis, and Liaoyi 1. In addition, core SSR markers (Jr45, Jr40, Jr29, Jr35, and Jr11) were selected from 14 SSR markers, which were sufficient to distinguish 47 walnut resources. At the same time, 47 unique molecular fingerprints of walnuts were constructed using these core SSR markers. This study provides strong scientific support for rapid and efficient identification, germplasm innovation, and a variety of property protection of walnut germplasm. Full article

The United States is a principal producer of tree nuts (almonds, pistachios, and walnuts), resulting in the generation of excess of tree-nutshell by-products each year, with few market outlets. A nutshell is an essential, lignocellulosic layer that protects a kernel (seed) from the environment during cultivation. The objective of this study was to develop nutshell by-products as herbicide delivery systems, which would not only enable sustainable weed control in fields but also increases nutshell value and reduce the cost of waste disposal. We recently identified a natural salicylaldehyde (SA) that emits volatiles with both herbicidal and antifungal properties. In this study, walnut shell particles saturated with 0.8 to 1.6 M SA were developed as delivery vehicles for SA to soil, which allowed for the controlled release of an SA fumigant for weed control. The pre- and post-emergent herbicidal efficacy of SA was investigated using model monocot (Lolium arundinaceum (Schreb.) Darbysh; turfgrass) and dicot (Brassica rapa var. pekinensis; Chinese cabbage) plants. We compared (1) the effects of different types of solvents for dissolving SA (dimethyl sulfoxide (DMSO) and ethanol (60%, v/v)), and (2) the effect of covering soil with plastic layers (i.e., soil pasteurization) or not covering soil during SA fumigation using nutshells. Results: In the pre-emergent herbicidal testing with the soil covered, the dicot plants exhibited levels of higher susceptibility to SA in DMSO emitted from nutshells when compared to the monocot plants. The seed germination frequencies in the dicots were 15% and 1% with 0.8 and 1.6 M SA, respectively, while those in the monocots were 32% and 18%, respectively, under the same test conditions. In the post-emergent herbicidal testing with the soil covered, the growth of both the monocot and dicot plants was completely prevented after 5 to 7 days of SA fumigation, resulting in the deaths of entire plants. It was noteworthy that in the post-emergent herbicidal testing, SA dissolved in ethanol (60%, v/v) completely disrupted the growth of the monocot and dicot plants as early as 3 days after SA emission from the nutshells, even without the soil being covered. Tree-nutshell particles could serve as effective SA delivery vehicles with controlled release capabilities for SA. The SA exhibited pre- and post-emergent herbicidal activities against the monocot and dicot plants at most growth stages. SA (0.8 and 1.6 M) dissolved in ethanol (60%, v/v) might exert a synergism for higher herbicidal activity after emission from nutshells. Since tree nuts capture/store a substantial amount of carbon over their life-cycles, the new and sustainable utility of using nutshells not only reduces carbon emissions but also valorizes tree-nut by-products, thus benefitting the tree-nut industry. Full article

Walnut shell–kernel separation is an essential step in the deep processing of walnut. It is a crucial factor that prevents the increase in the added value and industrial development of walnuts. This study proposes a walnut shell–kernel detection method based on YOLOX deep learning using machine vision and deep-learning technology to address common issues, such as incomplete shell–kernel separation in the current airflow screening, high costs and the low efficiency of manually assisted screening. A dataset was produced using Labelme by acquiring walnut shell and kernel images following shellshock. This dataset was transformed into the COCO dataset format. Next, 110 epochs of training were performed on the network. When the intersection over the union threshold was 0.5, the average precision (AP), the average recall rate (AR), the model size, and floating point operations per second were 96.3%, 84.7%, 99 MB, and 351.9, respectively. Compared with YOLOv3, Faster Region-based Convolutional Neural Network (Faster R-CNN), and Single Shot MultiBox Detector algorithms (SSD), the AP value of the proposed algorithm was increased by 2.1%, 1.3%, and 3.4%, respectively. Similarly, the AR was increased by 10%, 2.3%, and 9%, respectively. Meanwhile, walnut shell–kernel detection was performed under different situations, such as distinct species, supplementary lighting, or shielding conditions. This model exhibits high recognition and positioning precision under different walnut species, supplementary lighting, and shielding conditions. It has high robustness. Moreover, the small size of this model is beneficial for migration applications. This study’s results can provide some technological references to develop faster walnut shell–kernel separation methods. Full article

China is the world’s largest walnut producer. There is still a scarcity of comprehensive information on the nutritional quality of Chinese walnuts and the influence of soil on walnut quality. In this study, 273 samples and the corresponding soils from the main English walnut (Juglans regia L.)-producing areas in China were collected. The results revealed that walnut oil contained a high percentage of linoleic acid and γ-tocopherol, with an average content of 62.36% and 77.70%, respectively. Walnut flour is rich in nutritional elements, with the highest content of macro-element K at 3961.29 mg kg⁻¹. In addition, 12 micro-elements with concentrations ranging from 0.01 to 42.34 mg/kg were discovered in walnut flour. The total amino acid profile of walnut flour contains 27.23% of the seven essential amino acids, with the highest amount allocated to leucine at 2.07 g 100 g⁻¹. The Pearson correlation analysis revealed that almost all amino acids showed a significant positive correlation (p < 0.01, r > 0.70). The soil’s content in terms of three trace elements (Fe, Cu, and Zn) has the greatest influence on the nutritional qualities of walnuts. Furthermore, the pH of the soil played a role in determining the qualities of the walnut. These findings provide fundamental information for the consumer selection and trade of walnuts, as well as guidance for the development of high-quality walnuts in China. Full article

The ageing of materials is an irreversible, in-time occurring complex phenomenon, which affects both wood surfaces and the coating materials. This paper focuses on the light-induced natural ageing of wood-coated surfaces in indoor conditions. Two wood species: European maple (Acer pseudoplatanus) and European walnut (Juglans regia) and two types of waxes: bees wax and Chinese wax were employed in the experiments presented in this paper. Uncoated and coated wood samples were exposed to the natural sunlight filtered by window glass in a simulated indoors natural ageing test for a total period of 7 years. Colour measurements in the CIE-Lab system and FTIR-ATR investigation were employed to evaluate the ageing phenomena. The uncoated wooden samples underwent progressive colour changes perceived as darkening for European maple and lightening for European walnut, corresponding to total colour differences values (ΔE) after 7 years of exposure of 12.54 and 11.66, respectively. Coating of wood samples with the two types of waxes differently influenced the total colour changes for the two wood species: reduced colour changes corresponding to ΔE values of 4.79–6.44 were determined for European maple, whilst increased colour changes corresponding to ΔE values of 13.80–20.83 were determined for European walnut. FTIR analysis highlighted different surface chemistry changes for the uncoated and wax-coated wood samples. Full article

Forests are an important part of the ecological environment, and changes in forests not only affect the ecological environment of the region but are also an important factor causing landslide disasters. In order to correctly evaluate the impact of forest cover on landslide susceptibility, in this paper, we build an evaluation model for the contribution of forests to the landslide susceptibility of different grades based on survey data for forest land change in Bijie City and landslide susceptibility data, and discuss the effects of forest land type, origin, age group, and dominant tree species on landslide susceptibility. We find that forests play a certain role in regulating landslide susceptibility: compared with woodland, the landslide protection ability of shrubland is stronger. Furthermore, natural forests have a greater inhibitory effect on landslides than artificial forests, and compared with young forest, mature forest and over-mature forest, middle-aged forest and near-mature forest have stronger landslide protection abilities. In addition, the dominant tree species in different regions have different impacts on landslides. Coniferous forests such as Chinese fir and Cryptomeria fortunei in Qixingguan and Dafang County have a low ability to prevent landslides. Moreover, the soft broad tree species found in Qianxi County, Zhijin County, Nayong County and Jinsha County are likely to cause landslides and deserve further research attention. Additionally, a greater focus should be placed on the landslide protection of walnut economic forests in Hezhang County and Weining County. Simultaneously, greater attention should be paid to the Cyclobalanopsis glauca tree species in Weining County because the area where this tree species is located is prone to landslides. Aiming at addressing the landslide susceptibility existing in different forests, we propose forest management strategies for the ecological prevention and control of landslides in Bijie City, which can be used as a reference for landslide susceptibility prevention and control. Full article

Chinese walnuts have extraordinary nutritional and organoleptic qualities, and counterfeit Chinese walnut products are pervasive in the market. The aim of this study was to investigate the feasibility of hyperspectral imaging (HSI) technique to accurately identify and visualize Chinese walnut varieties. Hyperspectral images of 400 Chinese walnuts including 200 samples of Ningguo variety and 200 samples of Lin’an variety were acquired in range of 400–1000 nm. Spectra were extracted from representative regions of interest (ROIs), and principal component analysis (PCA) of spectra showed that the characteristic second principal component (PC₂) was potentially effective in variety identification. The PC transformation was also conducted to hyperspectral images to make an exploratory visualization according to pixel-wise PC scores. Three different modeling methods including partial least squares-discriminant analysis (PLS-DA), k-nearest neighbor (KNN), and support vector machine (SVM) were individually employed to develop classification models. Results indicated that raw full spectra constructed PLS-DA model performed best with correct classification rates (CCRs) of 97.33%, 95.33%, and 92.00% in calibration, cross-validation, and prediction sets, respectively. Successful projects algorithm (SPA), competitive adaptive reweighted sampling (CARS), and PC loadings were individually used for effective wavelengths selection. Subsequently, simplified PLS-DA model based on wavelengths selected by CARS yielded the best 96.33%, 95.67% and 91.00% CCRs in the three sets. This optimal CARS-PLS-DA model acquired a sensitivity of 93.62%, a specificity of 88.68%, the area under the receiver operating characteristic curve (AUC) value of 0.91, and Kappa coefficient of 0.82 in prediction set. Classification maps were finally generated by classifying the varieties of each pixel in multispectral images at CARS-selected wavelengths, and the general variety was then readily discernible. These results demonstrated that features extracted from HSI had outstanding ability, and could be applied as a reliable tool for the further development of an on-line identification system for Chinese walnut variety. Full article

The prices of walnuts vary according to their geographical origin and, therefore, offer a financial incentive for adulteration. A reliable analysis method is required to quickly detect possible misdeclarations and thus prevent food fraud. In this study, a method to distinguish between seven geographical origins of walnuts using Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics as a fast, versatile, and easy to handle analytical tool was developed. NIR spectra of 212 ground and afterwards freeze-dried walnut samples, harvested in three consecutive years (2017–2019), were collected. We optimized the data pre-processing by applying and evaluating 50,545 different pre-processing combinations, followed by linear discriminant analysis (LDA) which was confirmed by nested cross-validation. The results show that in the scope of our research minimal pre-processing led to the best results: By applying just multiplicative scatter correction (MSC) and median centering, a classification accuracy of 77.00% ± 1.60% was achieved. Consequently, this complex model can be used to answer economically relevant questions e.g., to distinguish between European and Chinese walnuts. Furthermore, the great influence of the applied pre-processing methods, e.g., the selected wavenumber range, on the achieved classification accuracy is shown which underlines the importance of optimization of the pre-processing strategy. Full article

Gene introgression usually results from natural hybridization occurring among closely related species in sympatric populations. In this study, we discussed two rare and frequent gene flow phenomena between three species of Juglans plants and analyzed the possible causes for the difference. We collected 656 individuals from 40 populations of Persian walnut (Juglans regia L.), Chinese walnut (J. cathayensis Dode), and Iron walnut (J. sigillata Dode) that were genotyped at 17 expressed sequence tag simple sequence repeat (EST-SSR) loci to analyze the introgressions between J. regia and J. cathayensis, and J. regia and J. sigillata. Our study compared the spatial patterns of expected heterozygosity (H_E), allelic richness (Rs), and private allele richness (P_AR) so as to vividly infer the biogeographic history of related species of Juglans in the two regions. The results of the PCoA, UPGMA, and STRUCTURE analyses showed that all J. regia and J. sigillata populations clustered into one group, and the J. cathayensis populations clustered into the other group. The results of the historical gene flow analysis indicated that J. regia and J. sigillata have no genetic barriers, and the directional gene flow is mainly from J. regia to J. sigillata. For the three species of Juglans, all the above results indicated that gene flow was common among the same group of Juglans, and only rare and low-level gene flow appeared in distinct groups. Therefore, our study revealed multiple phenomena of gene flow and introgression among closely related species in sympatric populations, thereby providing a theoretical basis for the genetic evolution of the genus Juglans. Full article