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Search Results (944)

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20 pages, 1722 KiB  
Article
Andean Pistacia vera L. Crops: Phytochemical Update and Influence of Soil-Growing Elemental Composition on Nutritional Properties of Nuts
by Daniela Zalazar-García, Mario J. Simirgiotis, Jessica Gómez, Alejandro Tapia and María Paula Fabani
Horticulturae 2025, 11(8), 925; https://doi.org/10.3390/horticulturae11080925 (registering DOI) - 5 Aug 2025
Abstract
Pistachio nuts are among the 50 best foods with the highest antioxidant potential. They have a balanced content of mono- (~70%) and polyunsaturated (~20%) fatty acids, minerals, and bioactive compounds such as tocopherols, phytosterols, and phenolic compounds, which have shown rapid accessibility in [...] Read more.
Pistachio nuts are among the 50 best foods with the highest antioxidant potential. They have a balanced content of mono- (~70%) and polyunsaturated (~20%) fatty acids, minerals, and bioactive compounds such as tocopherols, phytosterols, and phenolic compounds, which have shown rapid accessibility in the stomach. Pistachio consumption provides several health benefits, primarily due to its antioxidant properties and high content of essential nutrients. In this study, we analyzed the mineral composition, total phenolic content (TP), antioxidant activity (AA), and UHPLC/MS-MS polyphenolic profile of three Argentinian pistachio crops. Additionally, the physicochemical parameters and the elemental profiles of the growing soils were determined, as they influence mineral uptake and the synthesis of bioactive compounds in pistachio kernels. The TP was not significantly modified by the growing soils, with Crop3 presenting the highest TP content (276 ± 14 mg GA/100 g DW). Crop3 exhibited 18% higher TP content compared to Crop2. Similarly, FRAP values ranged from 28.0 to 36.5 mmol TE/100 g DW, with Crop1 showing a 30% increase compared to Crop2. DPPH values varied from 19.0 to 24.3 mmol TE/100 g DW, with Crop1 displaying 28% higher activity than Crop2. However, the polyphenolic profile was similar for all crops analyzed. Thirty compounds were identified; only Crop 1 contained the flavanone eriodyctiol and the isoflavone genistein, while the flavanone naringenin and the flavone luteolin were identified in Crop1 and Crop3. Regarding mineral content, the pistachio kernels mainly contained K, Ca, and Mg. Multivariate analyses revealed distinct elemental and antioxidant profiles among crops. LDA achieved classification accuracies of 77.7% for soils and 74.4% for kernels, with Pb, Zn, Cu, Rb, Sr, and Mn as key discriminants. CCA confirmed strong soil–kernel mineral correlations (r = 1), while GPA showed higher congruence between antioxidant traits and kernel composition than with soil geochemistry. These findings underscore the importance of soil composition in determining the nutritional quality of pistachio kernels, thereby supporting the beneficial health effects associated with pistachio consumption. Full article
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12 pages, 2107 KiB  
Article
The Impact of Harvest Season on Oolong Tea Aroma Profile and Quality
by Chao Zheng, Shuilian Gao, Xiaxia Wang, Zhenbiao Yang, Junling Zhou and Ying Liu
Plants 2025, 14(15), 2378; https://doi.org/10.3390/plants14152378 - 1 Aug 2025
Viewed by 113
Abstract
The impact of seasonality on the aroma quality of tea has been documented in various tea types, but not specifically in oolong tea. This study is the first to explore the complex relationships between seasonality, volatile compounds, and aroma quality in oolong tea. [...] Read more.
The impact of seasonality on the aroma quality of tea has been documented in various tea types, but not specifically in oolong tea. This study is the first to explore the complex relationships between seasonality, volatile compounds, and aroma quality in oolong tea. Using Headspace Solid-Phase Microextraction Gas Chromatography–Mass Spectrometry (HS-SPME-GC-MS)-based untargeted metabolomics, we analyzed 266 samples of Tieguanyin oolong tea. The data identified linalool, linalool oxides (trans-linalool oxide (furanoid) and trans-linalool oxide (pyranoid)), and their metabolites (diendiol I; hotrienol) as key seasonal discriminants. Four out of the top ten key differential compounds for distinguishing aroma scores were metabolites from fatty acid degradation, namely trans-3-hexenyl butyrate, trans-2-hexenyl hexanoate, hexyl hexanoate, and hexyl 2-methyl butyrate. Approximately one-fifth of the seasonal discriminant volatile compounds were significant in influencing aroma quality. Overall, the impact of seasonality on the aroma quality of finished Tieguanyin oolong tea is marginal. These findings enhance our understanding of the interplay between seasonal variations, volatile composition, and aroma quality in oolong tea. Full article
(This article belongs to the Special Issue Production, Quality and Function of Tea)
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41 pages, 7932 KiB  
Article
Element Mobility in a Metasomatic System with IOCG Mineralization Metamorphosed at Granulite Facies: The Bondy Gneiss Complex, Grenville Province, Canada
by Olivier Blein and Louise Corriveau
Minerals 2025, 15(8), 803; https://doi.org/10.3390/min15080803 - 30 Jul 2025
Viewed by 155
Abstract
In the absence of appropriate tools and a knowledge base for exploring high-grade metamorphic terrains, felsic gneiss complexes at granulite facies have long been considered barren and have remained undermapped and understudied. This was the case of the Bondy gneiss complex in the [...] Read more.
In the absence of appropriate tools and a knowledge base for exploring high-grade metamorphic terrains, felsic gneiss complexes at granulite facies have long been considered barren and have remained undermapped and understudied. This was the case of the Bondy gneiss complex in the southwestern Grenville Province of Canada which consists of 1.39–1.35 Ga volcanic and plutonic rocks metamorphosed under granulite facies conditions at 1.19 Ga. Iron oxide–apatite and Cu-Ag-Au mineral occurrences occur among gneisses rich in biotite, cordierite, garnet, K-feldspar, orthopyroxene and/or sillimanite-rich gneisses, plagioclase-cordierite-orthopyroxene white gneisses, magnetite-garnet-rich gneisses, garnetites, hyperaluminous sillimanite-pyrite-quartz gneisses, phlogopite-sillimanite gneisses, and tourmalinites. Petrological and geochemical studies indicate that the precursors of these gneisses are altered volcanic and volcaniclastic rocks with attributes of pre-metamorphic Na, Ca-Fe, K-Fe, K, chloritic, argillic, phyllic, advanced argillic and skarn alteration. The nature of these hydrothermal rocks and the ore deposit model that best represents them are further investigated herein through lithogeochemistry. The lithofacies mineralized in Cu (±Au, Ag, Zn) are distinguished by the presence of garnet, magnetite and zircon, and exhibit pronounced enrichment in Fe, Mg, HREE and Zr relative to the least-altered rocks. In discrimination diagrams, the metamorphosed mineral system is demonstrated to exhibit the diagnostic attributes of, and is interpreted as, a metasomatic iron and alkali-calcic (MIAC) mineral system with iron oxide–apatite (IOA) and iron oxide copper–gold (IOCG) mineralization that evolves toward an epithermal cap. This contribution demonstrates that alteration facies diagnostic of MIAC systems and their IOCG and IOA mineralization remain diagnostic even after high-grade metamorphism. Exploration strategies can thus use the lithogeochemical footprint and the distribution and types of alteration facies observed as pathfinders for the facies-specific deposit types of MIAC systems. Full article
(This article belongs to the Section Mineral Deposits)
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21 pages, 727 KiB  
Article
Seasonal and Cultivar-Dependent Phenolic Dynamics in Tuscan Olive Leaves: A Two-Year Study by HPLC-DAD-MS for Food By-Product Valorization
by Tommaso Ugolini, Lorenzo Cecchi, Graziano Sani, Irene Digiglio, Barbara Adinolfi, Leonardo Ciaccheri, Bruno Zanoni, Fabrizio Melani and Nadia Mulinacci
Separations 2025, 12(8), 192; https://doi.org/10.3390/separations12080192 - 24 Jul 2025
Viewed by 188
Abstract
Olive tree leaf is a phenol-rich, high-potential-value biomass that can be used to formulate food additives and supplements. Leaf phenolic content varies depending on numerous factors, like cultivar, geographical origin, year, and season of harvest. The aim of this research was to evaluate [...] Read more.
Olive tree leaf is a phenol-rich, high-potential-value biomass that can be used to formulate food additives and supplements. Leaf phenolic content varies depending on numerous factors, like cultivar, geographical origin, year, and season of harvest. The aim of this research was to evaluate the variations in phenolic profile of four major Tuscan cultivars (Frantoio, Leccio del Corno, Leccino, and Moraiolo) over four different phenological phases and across two years. All 96 olive leaf samples were harvested from trees grown in the same orchard located in Florence. After drying, their phenolic profile was characterized using HPLC-DAD-MS, and the obtained data were processed by ANOVA, GA-LDA, and RF methods. A total of 25 phenolic derivatives were analyzed, with total contents ranging 16,674.0–50,594.3 mg/kg and oleuropein (4570.0–27,547.7 mg/kg) being the predominant compound regardless of cultivar, year, and season of harvest. Oleuropein and hydroxytyrosol glucoside showed inverse proportionality and similar behavior across years in all cultivars, and therefore were highlighted as main phenolic compounds correlated with the seasonal variability in studied cultivars. Interesting behavior was also pointed out for apigenin rutinoside. Application of GA-LDA and RF methods allowed pointing out the excellent performance of leaf phenols in discriminating samples based on cultivar, harvest year, and harvesting season. Full article
(This article belongs to the Special Issue Extraction and Isolation of Nutraceuticals from Plant Foods)
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14 pages, 1840 KiB  
Article
Volatilomic Fingerprint of Tomatoes by HS-SPME/GC-MS as a Suitable Analytical Platform for Authenticity Assessment Purposes
by Gonçalo Jasmins, Tânia Azevedo, José S. Câmara and Rosa Perestrelo
Separations 2025, 12(8), 188; https://doi.org/10.3390/separations12080188 - 22 Jul 2025
Viewed by 194
Abstract
Tomatoes are globally esteemed not only for their nutritional value but also for their complex and appealing aroma, a key determinant of consumer preference. The present study aimed to comprehensively characterise the volatilomic fingerprints of three tomato species—Solanum lycopersicum L., S. lycopersicum [...] Read more.
Tomatoes are globally esteemed not only for their nutritional value but also for their complex and appealing aroma, a key determinant of consumer preference. The present study aimed to comprehensively characterise the volatilomic fingerprints of three tomato species—Solanum lycopersicum L., S. lycopersicum var. cerasiforme, and S. betaceum—encompassing six distinct varieties, through the application of headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC-MS). A total of 55 volatile organic compounds (VOCs) spanning multiple chemical classes were identified, of which only 28 were ubiquitously present across all varieties examined. Carbonyl compounds constituted the predominant chemical family, with hexanal and (E)-2-hexenal emerging as putative key contributors to the characteristic green and fresh olfactory notes. Notably, esters were found to dominate the unique volatile fingerprint of cherry tomatoes, particularly methyl 2-hydroxybenzoate, while Kumato and Roma varieties exhibited elevated levels of furanic compounds. Multivariate statistical analyses, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), demonstrated clear varietal discrimination and identified potential aroma-associated biomarkers such as phenylethyl alcohol, 3-methyl-1-butanol, hexanal, (E)-2-octenal, (E)-2-nonenal, and heptanal. Collectively, these findings underscore the utility of volatilomic fingerprint as a robust tool for varietal identification and quality control within the food industry. Full article
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19 pages, 5003 KiB  
Article
Coffees Brewed from Standard Capsules Help to Compare Different Aroma Fingerprinting Technologies—A Comparison of an Electronic Tongue and Electronic Noses
by Biborka Gillay, Zoltan Gillay, Zoltan Kovacs, Viktoria Eles, Tamas Toth, Haruna Gado Yakubu, Iyas Aldib and George Bazar
Chemosensors 2025, 13(7), 261; https://doi.org/10.3390/chemosensors13070261 - 18 Jul 2025
Viewed by 797
Abstract
With the development of various new types of instrumental aroma sensing technologies, there is a need for methodologies that help developers and users evaluate the performance of the different devices. This study introduces a simple method that uses standard coffee beverages, reproducible worldwide, [...] Read more.
With the development of various new types of instrumental aroma sensing technologies, there is a need for methodologies that help developers and users evaluate the performance of the different devices. This study introduces a simple method that uses standard coffee beverages, reproducible worldwide, thus allowing users to compare aroma sensing devices and technologies globally. Eight different variations of commercial coffee capsules were used to brew espresso coffees (40 mL), consisting of either Arabica coffee or a blend of Robusta and Arabica coffee, covering a wide range of sensory attributes. The AlphaMOS Astree electronic tongue (equipped with sensors based on chemically modified field-effect transistor technology) and the AlphaMOS Heracles NEO and the Volatile Scout3 electronic noses (both using separation technology based on gas chromatography) were used to describe the taste and odor profiles of the freshly brewed coffee samples and also to compare them to the various sensory characteristics declared on the original packaging, such as intensity, roasting, acidity, bitterness, and body. Linear discriminant analysis (LDA) results showed that these technologies were able to classify the samples similarly to the pattern of the coffees based on the human sensory characteristics. In general, the arrangement of the different coffee types in the LDA results—i.e., the similarities and dissimilarities in the types based on their taste or smell—was the same in the case of the Astree electronic tongue and the Heracles electronic nose, while slightly different arrangements were found for the Scout3 electronic nose. The results of the Astree electronic tongue and those of the Heracles electronic nose showed the taste and smell profiles of the decaffeinated coffees to be different from their caffeinated counterparts. The Heracles and Scout3 electronic noses provided high accuracies in classifying the samples based on their odor into the sensory classes presented on the coffee capsules’ packaging. Despite the technological differences in the investigated devices, the introduced coffee test could assess the similarities in the taste and odor profiling capacities of the aroma fingerprinting technologies. Since the coffee capsules used for the test can be purchased all over the world in the same quality, these coffees can be used as global standard samples during the comparison of different devices applying different measurement technologies. The test can be used to evaluate instrumentational and data analytical developments worldwide and to assess the potential of novel, cost-effective, accurate, and rapid solutions for quality assessments in the food and beverage industry. Full article
(This article belongs to the Special Issue Electronic Nose and Electronic Tongue for Substance Analysis)
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26 pages, 7178 KiB  
Article
Super-Resolution Reconstruction of Formation MicroScanner Images Based on the SRGAN Algorithm
by Changqiang Ma, Xinghua Qi, Liangyu Chen, Yonggui Li, Jianwei Fu and Zejun Liu
Processes 2025, 13(7), 2284; https://doi.org/10.3390/pr13072284 - 17 Jul 2025
Viewed by 333
Abstract
Formation MicroScanner Image (FMI) technology is a key method for identifying fractured reservoirs and optimizing oil and gas exploration, but its inherent insufficient resolution severely constrains the fine characterization of geological features. This study innovatively applies a Super-Resolution Generative Adversarial Network (SRGAN) to [...] Read more.
Formation MicroScanner Image (FMI) technology is a key method for identifying fractured reservoirs and optimizing oil and gas exploration, but its inherent insufficient resolution severely constrains the fine characterization of geological features. This study innovatively applies a Super-Resolution Generative Adversarial Network (SRGAN) to the super-resolution reconstruction of FMI logging image to address this bottleneck problem. By collecting FMI logging image of glutenite from a well in Xinjiang, a training set containing 24,275 images was constructed, and preprocessing strategies such as grayscale conversion and binarization were employed to optimize input features. Leveraging SRGAN’s generator-discriminator adversarial mechanism and perceptual loss function, high-quality mapping from low-resolution FMI logging image to high-resolution images was achieved. This study yields significant results: in RGB image reconstruction, SRGAN achieved a Peak Signal-to-Noise Ratio (PSNR) of 41.39 dB, surpassing the optimal traditional method (bicubic interpolation) by 61.6%; its Structural Similarity Index (SSIM) reached 0.992, representing a 34.1% improvement; in grayscale image processing, SRGAN effectively eliminated edge blurring, with the PSNR (40.15 dB) and SSIM (0.990) exceeding the suboptimal method (bilinear interpolation) by 36.6% and 9.9%, respectively. These results fully confirm that SRGAN can significantly restore edge contours and structural details in FMI logging image, with performance far exceeding traditional interpolation methods. This study not only systematically verifies, for the first time, SRGAN’s exceptional capability in enhancing FMI resolution, but also provides a high-precision data foundation for reservoir parameter inversion and geological modeling, holding significant application value for advancing the intelligent exploration of complex hydrocarbon reservoirs. Full article
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19 pages, 3806 KiB  
Article
Electroactive Poly(amic acid) Films Grafted with Pendant Aniline Tetramer for Hydrogen Sulfide Gas Sensing Applications
by Kun-Hao Luo, Yun-Ting Chen, Hsuan-Yu Wu, Zong-Kai Ni and Jui-Ming Yeh
Polymers 2025, 17(14), 1915; https://doi.org/10.3390/polym17141915 - 11 Jul 2025
Viewed by 376
Abstract
Hydrogen sulfide (H2S) is a highly toxic and corrosive gas generated in numerous industrial and environmental processes; rapid, sensitive detection at low ppm levels is therefore crucial for ensuring occupational safety and protecting public health. This work explores the effect of [...] Read more.
Hydrogen sulfide (H2S) is a highly toxic and corrosive gas generated in numerous industrial and environmental processes; rapid, sensitive detection at low ppm levels is therefore crucial for ensuring occupational safety and protecting public health. This work explores the effect of grafting various loadings of pendant aniline tetramer pendants (PEDA) onto electroactive poly(amic acid) (EPAA) films and evaluates their performance as H2S gas sensors. Comprehensive characterization including ion trap mass spectrometry (Ion trap MS), Fourier-transform infrared spectroscopy (FTIR), cyclic voltammetry (CV), and four-probe conductivity measurements, confirmed successful PEDA incorporation and revealed enhanced electrical conductivity with increasing PEDA content. Gas sensing tests revealed that EPAA3 (3 wt% PEDA) achieved the best overall performance toward 10 ppm H2S, producing a 591% response with a rapid 108 s response time. Selectivity studies showed that the response of EPAA3 to H2S exceeded those for SO2, NO2, NH3, and CO by factors of five to twelve, underscoring its excellent discrimination against common interferents. Repeatability tests over five successive cycles gave a relative standard deviation of just 7.4% for EPAA3, and long-term stability measurements over 16 days in ambient air demonstrated that EPAA3 retained over 80%. These findings establish that PEDA-grafted PAA films combine the processability of poly(amic acid) with the sharp, reversible redox behavior of pendant aniline tetramers, delivering reproducible, selective, and stable H2S sensing. EPAA3, in particular, represents a balanced composition that maximizes sensitivity and durability, offering a promising platform for practical environmental monitoring and industrial safety applications. Full article
(This article belongs to the Special Issue Development of Applications of Polymer-Based Sensors and Actuators)
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11 pages, 403 KiB  
Article
Modeling the Frequency–Amplitude Characteristics of a Tunable SAW Oscillator
by Ionut Nicolae and Cristian Viespe
Chemosensors 2025, 13(7), 240; https://doi.org/10.3390/chemosensors13070240 - 6 Jul 2025
Viewed by 334
Abstract
The resonant frequency of an SAW oscillator can be modulated by varying the signal amplitude, due to non-linear acoustic interactions within the chemoselective layer. In this study, we developed an explicit model to describe the amplitude–frequency behavior of a tunable SAW oscillator. A [...] Read more.
The resonant frequency of an SAW oscillator can be modulated by varying the signal amplitude, due to non-linear acoustic interactions within the chemoselective layer. In this study, we developed an explicit model to describe the amplitude–frequency behavior of a tunable SAW oscillator. A polymeric layer of variable thickness was deposited in a circular area (radius 1.1 mm) at the center of the piezoactive surface. Increasing the oscillator loop attenuation resulted in a continuous increase in the resonant frequency by up to 1.8 MHz. The layer was modeled as a succession of non-interacting sub-layers of varying thicknesses. As a result, the function model consists of a superposition of terms, each corresponding to a layer region of distinct length and thickness. The maximum difference between the experimental data and function model (also known as residual of the fit) was below 1% (13.02 kHz) of the resonant frequency variation, thus supporting the validity of our approach. While our model proved successful, the results suggest that some interactions are unaccounted for, as evidenced by the periodicity of the residuals of fit and unrealistically large variation in acoustic wave velocity. Full article
(This article belongs to the Special Issue Advanced Chemical Sensors for Gas Detection)
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20 pages, 6441 KiB  
Article
Tissue-Based Metabolomic Profiling of Endometrial Cancer and Hyperplasia
by Khalid Akkour, Afshan Masood, Maha Al Mogren, Reem H. AlMalki, Assim A. Alfadda, Salini Scaria Joy, Ali Bassi, Hani Alhalal, Maria Arafah, Othman Mahmoud Othman, Hadeel Mohammad Awwad, Anas M. Abdel Rahman and Hicham Benabdelkamel
Metabolites 2025, 15(7), 458; https://doi.org/10.3390/metabo15070458 - 5 Jul 2025
Viewed by 677
Abstract
Background: Endometrial cancer (EC) is the sixth most common cancer among women globally, with an estimated 420,000 new cases diagnosed annually. Methods: This study comprised patients with endometrial cancer (EC) (n = 17), hyperplasia (HY) (n = 17), and controls (CO) [...] Read more.
Background: Endometrial cancer (EC) is the sixth most common cancer among women globally, with an estimated 420,000 new cases diagnosed annually. Methods: This study comprised patients with endometrial cancer (EC) (n = 17), hyperplasia (HY) (n = 17), and controls (CO) (n = 20). Tissue was collected from the endometrium of all 54 patients, including patients with HY, EC, and CO, who underwent total hysterectomy. EC and HY diagnoses were confirmed based on histological examination. Untargeted metabolomics profiling was conducted using LC-HRMS. The partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models were used for univariate and multivariate statistical analysis. The fitness of the model (R2Y) and predictive ability (Q2) were used to create OPLS-DA models. ROC analysis was carried out, followed by network analysis using Ingenuity Pathway Analysis. Results: The top metabolites that can discriminate EC and HY from CO were identified. This revealed a decrease in the levels of the lipid species, specifically phosphatidic acid (PA) (PA (14:1/14:0), PA(10:0/17:0), PA(18:1-O(12,13)/12:0)), PG(a-13:0/a-13:0), ganglioside GA1 (d18:1/18:1), PS(14:1/14:0), TG(20:0/18:4/14:1), and CDP-DG(PGF2alpha/18:2), while the levels of 3-Dehydro-L-gulonate, Uridine diphosphate-N-acetylglucosamine, ganglioside GT2 (d18:1/14:0), gamma-glutamyl glutamic acid and oxidized glutathione were increased in cases of EC and HY as compared to CO. Bioinformatics analysis, specifically using Ingenuity Pathway Analysis (IPA), revealed distinct pathway enrichments for EC and HY. For EC, the most highly scored pathways were associated with cell-to-cell signaling and interaction, skeletal and muscular system development and function, and small-molecule biochemistry. In contrast, HY cases showed the highest scoring pathways related to inflammatory disease, inflammatory response, and organismal injury and abnormalities. Conclusions: Developing sensitive biomarkers could improve diagnosis and guide treatment decisions, particularly in identifying which patients with HY may safely avoid hysterectomy and be managed with hormonal therapy. Full article
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14 pages, 3332 KiB  
Article
Physiological Responses of Olive Cultivars Under Water Deficit
by Lorenzo León, Willem Goossens, Helena Clauw, Olivier Leroux and Kathy Steppe
Horticulturae 2025, 11(7), 745; https://doi.org/10.3390/horticulturae11070745 - 27 Jun 2025
Viewed by 294
Abstract
Olive trees are generally considered a species well-adapted to drought, but the impact of water shortage is of critical importance on olive production. For this reason, developing tolerant cultivars could be an effective strategy to mitigate the impact of drought in the future. [...] Read more.
Olive trees are generally considered a species well-adapted to drought, but the impact of water shortage is of critical importance on olive production. For this reason, developing tolerant cultivars could be an effective strategy to mitigate the impact of drought in the future. Characterizing drought stress tolerance in olive is a complex task due to the numerous traits involved in this response. In this study, plant growth, pressure–volume curves, gas-exchange and chlorophyll fluorescence traits, and stomata characteristics were monitored in nine cultivars to assess the effects of mild and severe drought stress conditions induced by withholding water for 7 and 21 days, respectively, and were compared to a well-watered control treatment. The plant materials evaluated included traditional cultivars, as well as new developed cultivars suited for high-density hedgerow olive orchards or resistant to verticillium wilt. Significant differences between cultivars were observed for most evaluated traits, with more pronounced differences under severe drought conditions. A multivariate analysis of the complete dataset recorded throughout the evaluation period allowed for the identification of promising cultivars under stress conditions (‘Sikitita’, ‘Sikitita-2’, and ‘Martina’) as well as highly discriminative traits that could serve as key selection parameters in future breeding programs. Full article
(This article belongs to the Special Issue Strategies of Producing Horticultural Crops Under Climate Change)
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21 pages, 1885 KiB  
Article
Understanding the Aroma Profiles of Hui Li Red Sichuan Pepper (Zanthoxylum bungeanum Maxim) Across Harvesting Periods Using Sensory Evaluation, E-Nose and GC-IMS Techniques
by Lian He, Sook Wah Chan, Sze Ying Leong, Mingyi Guo, Zhiyong Hou, Xiangbo Xu, Nallammai Singaram, Dan Lin, Xing Qiao, Lin Wang, Huachang Wu and Zongyuan Lu
Foods 2025, 14(13), 2285; https://doi.org/10.3390/foods14132285 - 27 Jun 2025
Viewed by 455
Abstract
This study investigated aroma changes in Hui Li red Sichuan pepper across five different harvesting times within their typical optimum period based on 24 traditional solar terms, employing sensory evaluation, electronic nose (E-nose), gas chromatography-ion mobility spectrometry (GC-IMS) combined with relative odour activity [...] Read more.
This study investigated aroma changes in Hui Li red Sichuan pepper across five different harvesting times within their typical optimum period based on 24 traditional solar terms, employing sensory evaluation, electronic nose (E-nose), gas chromatography-ion mobility spectrometry (GC-IMS) combined with relative odour activity value (ROAV) and partial least squares discriminant analysis (PLS-DA). Sensory analysis indicated that peppers were characterised by green, citrus, minty, sweet, woody, and peppery numbing aroma attributes. E-nose revealed the greatest aroma difference in peppers occurred between the early and late optimum harvest stages. GC-IMS identified 71 volatile compounds, with esters being the most abundant. Six key compounds identified were crucial for distinguishing peppers harvested at different times. Findings provided a valuable contribution to decide the optimal harvest window for Hui Li red Sichuan peppers, maximising their applications in the seasoning industry. Full article
(This article belongs to the Section Food Analytical Methods)
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14 pages, 2626 KiB  
Article
Aroma-Driven Differentiation of Wuyi Shuixian Tea Grades: The Pivotal Role of Linalool Revealed by OAV and Multivariate Analysis
by Mengzhen Zhang, Ying Zhang, Yeyun Lin, Yuhua Wang, Jishuang Zou, Miaoen Qiu, Qingxu Zhang, Jianghua Ye, Xiaoli Jia, Haibin He, Haibin Wang and Qi Zhang
Foods 2025, 14(13), 2169; https://doi.org/10.3390/foods14132169 - 21 Jun 2025
Viewed by 344
Abstract
Wuyi Shuixian tea, a premium oolong tea known for its complex floral-fruity aroma, exhibits significant quality variations across different grades. This study systematically analyzed the aroma characteristics and key fragrant compounds of four grades (Grand Prize SA, First Prize SB, Outstanding Award SC, [...] Read more.
Wuyi Shuixian tea, a premium oolong tea known for its complex floral-fruity aroma, exhibits significant quality variations across different grades. This study systematically analyzed the aroma characteristics and key fragrant compounds of four grades (Grand Prize SA, First Prize SB, Outstanding Award SC, and Non-award SD) using headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS), odor activity value (OAV) analysis, and multivariate statistical methods. A total of 159 volatile compounds were identified, with similar compound categories but distinct concentration gradients between grades. OAV-splitting analysis (based on OAV ≥ 1 as the threshold for aroma activity) identified β-ionone (fruity), octanal (fatty), and linalool (floral) as core aroma-active contributors, as their OAV values significantly exceeded 10 in awarded grades (SA, SB, SC), indicating dominant roles in sensory perception. Notably, linalool, a floral marker, showed a concentration gradient (SA > SB > SC) and was absent in SD, serving as a critical determinant of grade differentiation. Orthogonal partial least squares-discriminant analysis (OPLS-DA) further distinguished awarded grades (SA, SB, SC) by balanced fruity, floral, and woody notes, while SD lacked floral traits and exhibited burnt aromas. This classification was supported by hierarchical clustering analysis (HCA) of volatile profiles and principal component analysis (PCA). Electronic nose data validated these findings, showing strong correlations between sensor responses (W5S/W2W) and key compounds like hexanal and β-ionone. This study elucidates the molecular basis of aroma-driven quality grading in Wuyi Shuixian tea, providing a scientific framework for optimizing processing techniques and enhancing quality evaluation standards. The integration of chemical profiling with sensory attributes advances precision in tea industry practices, bridging traditional grading with objective analytical metrics. Full article
(This article belongs to the Special Issue Tea Technology and Resource Utilization)
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24 pages, 1964 KiB  
Article
Metabolomic Profiling Reveals PGPR-Driven Drought Tolerance in Contrasting Brassica juncea Genotypes
by Asha Rani Sheoran, Nita Lakra, Baljeet Singh Saharan, Annu Luhach, Yogesh K. Ahlawat, Rosa Porcel, Jose M. Mulet and Prabhakar Singh
Metabolites 2025, 15(6), 416; https://doi.org/10.3390/metabo15060416 - 19 Jun 2025
Viewed by 636
Abstract
Background: Drought stress is a major abiotic factor limiting Brassica juncea productivity, resulting in significant yield reductions. Plant Growth-Promoting Rhizobacteria (PGPR) have shown potential in enhancing drought tolerance; however, the metabolomic changes associated with their effects remain largely unexplored. This study examines the [...] Read more.
Background: Drought stress is a major abiotic factor limiting Brassica juncea productivity, resulting in significant yield reductions. Plant Growth-Promoting Rhizobacteria (PGPR) have shown potential in enhancing drought tolerance; however, the metabolomic changes associated with their effects remain largely unexplored. This study examines the metabolic changes induced by a PGPR consortium (Enterobacter hormaechei, Pantoea dispersa, and Acinetobacter sp.) in two contrasting genotypes B. juncea (L.) Czern. ‘RH 725’ (drought tolerant) and B. juncea (L.) Czern. ‘RH-749’ (drought sensitive for drought tolerance, under both control and drought conditions. Methods: Metabolite profiling was conducted using gas chromatography-mass spectrometry (GC-MS) to identify compounds that accumulated differentially across treatments. We applied multivariate statistical methods, such as Partial Least Squares Discriminant Analysis (PLS-DA), hierarchical clustering, and pathway enrichment analysis, to explore metabolic reprogramming. Results: Drought stress induced significant changes in metabolite profile, particularly increasing the levels of osmoprotectants such as trehalose, glucose, sucrose, proline, and valine. Additionally, alterations in organic acids (malic acid and citric acid) and fatty acids (oleic acid and linoleic acid) were observed. PGPR inoculation further amplified these metabolic responses to enhance the osmotic regulation, reactive oxygen species (ROS) detoxification, and carbon-nitrogen metabolism, with RH-725 displaying a stronger adaptive response. Pathway enrichment analysis revealed that PGPR treatment significantly influenced metabolic pathways related to starch and sucrose metabolism, galactose metabolism, and amino acid biosynthesis, which play critical roles in drought adaptation. Conclusion: These findings provide insights into how PGPR contributes to stress resilience in B. juncea by modulating key biochemical pathways. This study provides new molecular insights into the known effect of PGPR for mitigating drought stress in oilseed crops. Full article
(This article belongs to the Section Plant Metabolism)
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20 pages, 2346 KiB  
Article
A Novel Approach to Pine Nut Classification: Combining Near-Infrared Spectroscopy and Image Shape Features with Soft Voting-Based Ensemble Learning
by Yueyun Yu, Xin Huang, Danjv Lv, Benjamin K. Ng and Chan-Tong Lam
Mathematics 2025, 13(12), 2009; https://doi.org/10.3390/math13122009 - 18 Jun 2025
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Abstract
Pine nuts hold significant economic value due to their rich plant protein and healthy fats, yet precise variety classification has long been hindered by limitations of traditional techniques such as chemical analysis and machine vision. This study proposes a novel near-infrared (NIR) spectral [...] Read more.
Pine nuts hold significant economic value due to their rich plant protein and healthy fats, yet precise variety classification has long been hindered by limitations of traditional techniques such as chemical analysis and machine vision. This study proposes a novel near-infrared (NIR) spectral feature selection algorithm, termed the improved binary equilibrium optimizer with selection probability (IBiEO-SP), which incorporates a dynamic probability adjustment mechanism to achieve efficient feature dimensionality reduction. Experimental validation on a dataset comprising seven pine nut varieties demonstrated that, compared to particle swarm optimization (PSO) and the genetic algorithm (GA), the IBiEO-SP algorithm improved average classification accuracy by 5.7% (p < 0.01, Student’s t-test) under four spectral preprocessing methods (MSC, SNV, SG1, and SG2). Remarkably, only 2–3 features were required to achieve optimal performance (MSC + random forest: 99.05% accuracy, 100% F1/precision; SNV + KNN: 97.14% accuracy, 100% F1/precision). Furthermore, a multimodal data synergy strategy integrating NIR spectroscopy with morphological features was proposed, and a classification model was constructed using a soft voting ensemble. The final classification accuracy reached 99.95%, representing a 2.9% improvement over single-spectral-mode analysis. The results indicate that the IBiEO-SP algorithm effectively balances feature discriminative power and model generalization needs, overcoming the contradiction between high-dimensional data redundancy and low-dimensional information loss. This work provides a high-precision, low-complexity solution for rapid quality detection of pine nuts, with broad implications for agricultural product inspection and food safety. Full article
(This article belongs to the Special Issue Mathematical Modelling in Agriculture)
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