Search Results (11)

This work successfully synthesized green zinc oxide nanoparticles using extracts from strawberry guava leaves (Psidium cattleianum Sabine). Additionally, the reducing effect of the antioxidant extracts obtained through traditional techniques, such as infusion and maceration, was studied and compared against an emerging unconventional technology like ultrasound assisted extraction. Regarding the physical and chemical characteristics, it was found that all three systems were confined within a wavelength range of 357 to 370 nm (UV-vis) and sizes from 60 to 140 nm for the ultrasound-assisted nanoparticles (SEM), corroborated with DLS (134 ± 60 nm). Through X-ray diffraction, the hexagonal wurtzite structure was elucidated, and it was observed that ultrasound favored a higher percentage of crystallinity (98%) compared to the infusion (84%) and maceration (72%). This could be correlated with different functional groups via FTIR and with thermal events associated with thermogravimetric curves, where the total biomass weight loss was lower for nanoparticles using ultrasound extract (6.25%), followed by maceration (15.55%) and infusion (18.01%) extracts. Furthermore, these nanostructures were evaluated against clinically relevant pathogens, including Salmonella enteritidis, Staphylococcus aureus, Escherichia coli O157:H7, and Pseudomonas aeruginosa, assessing bacterial growth inhibition using the microdilution technique, and achieving inhibitions of 75%. Biofilm activity was evaluated through Congo red and crystal violet assays, where ultrasound-derived NPs proved to be good inhibitors for all pathogens. Finally, the toxicity of the nanoparticles was analyzed against peripheral blood leukocytes from goats as well as on the 3 T3-L1 cell line used in anti-obesity assays; the nanoparticles proved to be suitable in all concentrations reaching around 100% cell viability, positioning them as good candidates for diverse industrial applications that align with the principles of green chemistry towards a circular economy. Full article

This study investigated the potential of endophytic microorganisms in fermentative processes using agro-industrial residues as substrates. The aim was to explore sustainable biotechnological methods for producing valuable compounds from waste. Endophytic microorganisms were isolated from strawberry, lychee, and tangerine and used in fermentative processes with passion fruit, guava, and pineapple residues. Key methods included isolating and screening potent aroma-producing microorganisms, identifying them using MALDI-TOF MS, and analyzing volatile compounds by GC-MS. The results identified 37 endophytic microorganisms, with Kloeckera apiculata presenting the greatest aromatic potential. Fermentation with agro-industrial residues produced significant volatile compounds, identifying 27, 23, and 22 compounds from passion fruit, pineapple, and guava residues, respectively. The main conclusions highlighted the high production of ethyl acetate and 2-phenylethyl acetate, which contributed to fruity and floral aromas. The novelty of this study lies in the use of endophytic microorganisms isolated from tropical fruits to biotransform agro-industrial waste into high-value aromatic compounds, offering economic and environmental benefits. This research is significant, as it proposes a sustainable approach to valorize waste and produce natural aroma compounds through biotechnological processes. Full article

Strawberry guava is the fruit of Psidium littorale, which grows in tropical regions. Few studies have examined the hydrophobic compounds and biological activities of this fruit. Therefore, we purified lipophilic compounds of strawberry guava and examined their effects on epidermal and blood vessel barrier functions as well as their anti-melanogenic activity. Lipophilic compounds were isolated by silica gel column chromatography followed by reversed-phase HPLC with MeOH from an EtOH extract of the fruit. Isolated compounds were identified by comparing NMR and MS spectra with those of reference values. The effects of these compounds on epidermal barrier function were evaluated by measuring transepidermal water loss (TEWL) using reconstructed human epidermal keratinocytes (RHEKs). Blood vessel barrier function was examined using dye permeability through human umbilical vein endothelial cell (HUVEC) layers. Anti-melanogenic activity was assessed by theophylline-induced melanogenesis in B16 melanoma cells. We isolated six glucosylceramides (GlcCers) and three digalactosyldiacylglycerols (DGDGs). Only GlcCer[t18:1(8Z)/23:0] significantly lowered TEWL in RHEKs, while GlcCer[t18:1(8Z)/24:0] induced a slight reduction. Regarding the permeability of the HUVEC layer, GlcCer[d18:2(4E,8Z)/16:0] and DGDG (1,2-dilinolenoyl-3-digalactosylglycerol) significantly suppressed dye permeability and this effect was accompanied by the expression of VE-cadherin, which facilitates cell-to-cell adhesion. GlcCers and DGDGs did not exhibit anti-melanogenic activity. Therefore, strawberry guava containing specific GlcCers and DGDGs may promote epidermal and blood vessel barrier functions. Full article

Fruits are considered among the most nutrient-dense cash crops around the globe. Since fruits come in different types, sizes, shapes, colors, and textures, the manual classification and disease identification of a large quantity of fruit is time-consuming and sluggish, requiring massive human intervention. We propose a multilevel fusion method for fruit disease identification and fruit classification that includes intensive fruit image pre-processing, customized image kernels for feature extraction with state-of-the-art (SOTA) deep methods, Gini-index-based controlled feature selection, and a hybrid ensemble method for identification and classification. We noticed certain limitations in the existing literature of adopting a single data source, in terms of limited data sizes, variability in fruit types, variability in quality, and variability in disease type. Therefore, we extensively aggregated and pre-processed multi-fruit data to simulate our proposed ensemble model on comprehensive datasets to cover both fruit classification and disease identification aspects. The multi-fruit imagery data contained regular and augmented images of fruits including apple, apricot, avocado, banana, cherry, fig, grape, guava, kiwi, mango, orange, peach, pear, pineapple, and strawberry. Similarly, we considered normal and augmented images of rotten fruits including beans (two categories), strawberries (seven categories), and tomatoes (three categories). For consistency, we normalized the images and designed an auto-labeling mechanism based on the existing image clusters to label inconsistent data to appropriate classes. Finally, we verified the auto-labeled data with a complete inspection to correctly assign it to the relevant classes. The proposed ensemble classifier outperforms all other classification methods, achieving 100% and 99% accuracy for fruit classification and disease identification. Further, we performed the analysis of variance (ANOVA) test to validate the statistical significance of the classifiers’ outcomes at α = 0.05. We achieved F-values of 32.41 and 11.42 against F-critical values of 2.62 and 2.86, resulting in p-values of 0.00 (<0.05) for fruit classification and disease identification. Full article

Many tropical invasive species have allelopathic effects that contribute to their success in native plant communities. Pyrolyzed biomass (“biochar”) can sorb toxic compounds, including allelochemicals produced by invasive plants, potentially reducing their inhibitory effects on native species. Strawberry guava (Psidium cattleianum) is among the most important allelopathic invasive species on tropical islands and recognized as the most serious threat among invasive species in the global biodiversity hotspot of Mauritius. We investigated the effects of additions of locally produced biochar on native tree species in a field experiment conducted in areas invaded by strawberry guava within Mauritius’ largest national park. Growth and survivorship of native tree species were monitored over 2.5 years in plots subjected to four treatments: non-weeded, weeded, weeded + 25 t/ha biochar, and weeded + 50 t/ha biochar. Native tree growth and survivorship were strongly suppressed by strawberry guava. Biochar treatments dramatically increased native tree performance, with more than a doubling in growth, and substantially increased native tree survivorship and species diversity, while suppressing strawberry guava regeneration, consistent with growth-promoting properties and sorption of allelochemicals. We conclude that biochars, including “sustainable biochars” produced from locally accessible biomass using low-tech pyrolysis systems, have considerable potential to counteract effects of allelopathic invaders and increase the capacity for native species regeneration in tropical island ecosystems. Full article

Kombucha is a traditional beverage of sweetened black tea fermented with a symbiotic association of acetic acid bacteria and yeasts. In this study, kombucha fermented beverage (KFB) appeared to include nine chemical groups (alcohols, acids, lactones, condensed heterocyclic compounds, antibiotics, esters, aldehydes, fatty acids, and alkaloids) of many bioactive metabolites, as elucidated by gas chromatography–mass spectrometry (GC-MS) and IR spectra. The fermented metabolic components of KFB seem collectively to act in a synergistic action giving rise to the antimicrobial activity. Four types of kombucha preparations (fermented, neutralized, heat-treated and unfermented) were demonstrated with respect to their antimicrobial activity against some pathogenic bacterial and fungal strains using agar well diffusion assay. KFB exerted the strongest antimicrobial activities when compared with neutralized and heat-treated kombucha beverages (NKB and HKB). Staphylococcus aureus ATCC6538 (S. aureus) and Escherichia coli ATCC11229 (E. coli) were the organisms most susceptible to the antimicrobial activity of kombucha beverage preparations. Finally, the KFB preparation showed remarkable inhibitory activity against S. aureus and E. coli bacteria in a brain heart infusion broth and in some Egyptian fruit juices (apple, guava, strawberry, and tomato). These data reveal that kombucha is not only a prophylactic agent, but also appears to be promising as a safe alternative biopreservative, offering protection against pathogenic bacteria and fungi. Full article

Kefir beverage (KB) is a fermented milk initiated by kefir grains rich with starter probiotics. The KB produced in this study seemed to contain many chemical compounds elucidated by gas chromatography–mass spectrometry (GC-MS) and IR spectra. These compounds could be classified into different chemical groups such as alcohols, phenols, esters, fatty esters, unsaturated fatty esters, steroids, polyalkenes, heterocyclic compounds and aromatic aldehydes. Both KB and neutralized kefir beverage (NKB) inhibited some pathogenic bacteria including Escherichia coli ATCC11229 (E. coli), Listeria monocytogenes ATCC 4957 (L. monocytogenes), Bacillus cereus ATCC 14579 (B. cereus), Salmonella typhimurium ATCC 14028 (Sal. typhimurium) as well as some tested fungal strains such as Aspergillus flavus ATCC 16872 (A. flavus) and Aspergillus niger ATCC 20611 (A. niger), but the inhibitory activity of KB was more powerful than that obtained by NKB. It also appeared to contain four lactic acid bacteria species, one acetic acid bacterium and two yeast species. Finally, the KB inhibited distinctively both S. aureus and Sal. typhimurium bacteria in a brain heart infusion broth and in some Egyptian fruit juices, including those made with apples, guava, strawberries and tomatoes. Full article

Nowadays, there are few options of low or no added sugar drinks offering health benefits and oriented to consumers with a special health condition, such as overweight and obesity. The objective of this work was to develop and characterize a low-calorie antioxidant beverage made from aqueous extracts of medicinal plants (Melissa and lemon verbena), flowers (chamomile and bougainvillea), and fruits (guava, pineapple, strawberry, orange, and tangerine) as an alternative for people with overweight and obesity. Four formulations were developed from medicinal plants, flowers, and fruits. For this, a solid-liquid conventional extraction was carried out (at 90 °C during 5 min) followed by a cold shock in ice. The developed beverages were characterized in a microbiological and physicochemical way according to official analysis methods. The sensory evaluation was carried out through liking and buying intention tests. The population under study was integrated by 400 adults divided into two groups (with and without overweight or obesity). The beverages developed were low-calorie (≤40 kcal per portion), very low in sodium (<34 mg per portion), rich in antioxidants (>1.6 g GAE portion), and with an attractive color. The results indicate that these beverages could be an alternative to the consumption of common industrialized drinks conferring additional benefits for the prevention of chronic diseases. Full article

Fruits provide humans with multiple kinds of nutrients and protect humans against worldwide nutritional deficiency. Therefore, it is essential to understand the nutrient composition of various fruits in depth. In this study, we performed LC-MS-based non-targeted metabolomic analyses with ten kinds of fruit, including passion fruit, mango, starfruit, mangosteen, guava, mandarin orange, grape, apple, blueberry, and strawberry. In total, we detected over 2500 compounds and identified more than 300 nutrients. Although the ten fruits shared 909 common-detected compounds, each species accumulated a variety of species-specific metabolites. Additionally, metabolic profiling analyses revealed a constant variation in each metabolite’s content across the ten fruits. Moreover, we constructed a neighbor-joining tree using metabolomic data, which resembles the single-copy protein-based phylogenetic tree. This indicates that metabolome data could reflect the genetic relationship between different species. In conclusion, our work enriches knowledge on the metabolomics of fruits, and provides metabolic evidence for the genetic relationships among these fruits. Full article

Non-native plant species have become serious pests in Hawaii’s delicate island ecosystems. It is necessary to control invasive plants. The herbicides hexazinone and tebuthiuron were evaluated for defoliation efficacy to control several major invasive plants and for non-target effects on native plants at Site I in a rainforest at 1200 m elevation and Site II in a mesic area at 640 m elevation on the island of Kauai, Hawaii. The invasive weed species in the sites included daisy fleabane (Erigeron karvinskianus DC.), faya tree (Myrica faya Ait.), strawberry guava (Psidium cattleyanum Sabine), banana passion fruit (Passiflora mollissima Bailey), vaseygrass (Paspalum urvillei Steud.), and highbush blackberry (Rubus argutus Link. 1822). Native plants included ohia lehua (Metrosideros polymorpha Gaudich.), naupaka (Scaevola cerasifolia Labill.), pilo (Hedyotis mannii), hona (Urera glabra (Hook. & Arn.)), aalii (Dodonaea viscosa Jacq.), and amau (Sadleria sp.). The results showed that broadcast applications of hexazinone granules and tebuthiuron pellets were effective on some of those invasive species. Herbicidal tolerance varied among the native species. For example, D. viscosa showed high tolerance to hexazinone. S. cerasifolia was susceptible to hexazinone, but not to tebuthiuron. The inconsistent defoliation of Sadleria sp. occurred among different applications rates of the two herbicides. M. polymorpha, particularly when it was small, could tolerate hexazinone and tebuthiuron. U. glabra was severely injured by the two herbicides. H. mannii was moderately tolerant to hexazinone, but fairly sensitive to tebuthiuron. The invasive loblolly pine (Pinus taeda L.) was highly tolerant to hexazinone, but was very sensitive to tebuthiuron. M. faya was very sensitive to hexazinone, but very tolerant to tebuthiuron. P. cattleyanum was sensitive to both herbicides. Six and nine months after hexazinone and tebuthiuron treatment, respectively, native plants were transplanted into the Sites to observe injury from residual herbicides. Approximately less than 10% mortality was observed for the out-planted native species three months after planting (MAP), indicating that the native species showed less injury in the early period of transplant. The mortality of the three endangered species Kauai hau kuahiwi (Hibiscadelphis distans), Kauai delissea (Delissea rhytidosperma H.Mann) and kawawaenohu (Alsinidendron lynchnoides), however, increased as the MAP increased. Overall, broadcast treatments of hexazinone and tebuthiuron at rates higher than 1 kg active ingredient per hectare would be problematic. The dissipation half-life values of hexazinone and tebuthiuron in the 1–15 cm layer of soils at the two sites were approximately 7 days and greater than 180 days, respectively. Full article

High-resolution airborne imaging spectroscopy represents a promising avenue for mapping the spread of invasive tree species through native forests, but for this technology to be useful to forest managers there are two main technical challenges that must be addressed: (1) mapping a single focal species amongst a diverse array of other tree species; and (2) detecting early outbreaks of invasive plant species that are often hidden beneath the forest canopy. To address these challenges, we investigated the performance of two single-class classification frameworks—Biased Support Vector Machine (BSVM) and Mixture Tuned Matched Filtering (MTMF)—to estimate the degree of Psidium cattleianum incidence over a range of forest vertical strata (relative canopy density). We demonstrate that both BSVM and MTMF have the ability to detect relative canopy density of a single focal plant species in a vertically stratified forest, but they differ in the degree of user input required. Our results suggest BSVM as a promising method to disentangle spectrally-mixed classifications, as this approach generates decision values from a similarity function (kernel), which optimizes complex comparisons between classes using a dynamic machine learning process. Full article