Apple Samples Research Articles

NiFe2O4 nanoparticles grafted sulfonated melamine for rapid magnetic dispersive µ-solid phase extraction of pesticides in apple and pear samples: Greenness evaluation

In this research, a facile and rapid magnetic dispersive µ-solid-phase extraction technique based on novel and high-performance sulfonated melamine-modified NiFe2O4 nanoparticles was developed forsimultaneous extraction and separation of fifteen pesticides followed by gas chromatography-mass spectrometry. The characterization of the synthesized nano-adsorbent was carried out using scanning electron microscopy (SEM), vibrating sample magnetometry (VSM), and Fourier-transform infrared spectroscopy (FT-IR) techniques. The substantial factors including pH, the amount of nano-sorbent, ionic strength, sample volume, and desorption conditions (i.e. desorption solvent type and volume, and desorption time) on the extraction efficiencies of the interest pesticides from apple and pear samples were explored using the matrixed match method. Under the optimum conditions, the linear range of 0.2-500µg kg−1, LODs, and LOQs in the range of 0.065–0.077µg kg−1 and 0.22–0.26µg kg−1 for apple and 0.065–0.085µg kg−1 and 0.22–0.29µg kg−1 for pear were acquired. The intra-day and inter-day precisions were evaluated at three spiked concentration levels (10, 50, and 100 μg kg−1 of each analyte) on the same day and five distinct days, respectively. The RSD (%) values were ≤ 3.6 % for intra-day (n = 6) and ≤ 4.3 % for inter-day (5 days and n = 3) precisions. High relative recoveries of 92.5–98.9 % revealed high potential of the presented method for analysis of pesticides in complex matrixes. Moreover, Analytical Greenness metric approach was applied and consequently confirmed the greenness of the method which accompanied with the green analytical aspects.

Gold nanoparticle-based lateral flow immunoassay for the repaid and sensitive detection of pyraclostrobin in wheat, apple, Chinese cabbage, and soil samples

Pyraclostrobin is widely employed for controlling fungal pathogens. Given its potential adverse effects on aquatic organisms, beneficial insects, and mammals, there is an urgent need to develop on-site detection methods for monitoring pyraclostrobin residues. In this study, monoclonal antibodies (mAbs) targeting pyraclostrobin were developed, and a reliable structure of the mAb 4B4C3 was predicted using AlphaFold 3. The structure showed high predicted local distance difference test (pLDDT) values for both the complementarity-determining regions (CDRs) and framework regions (FRs). Molecular docking was employed to investigate its binding pattern with pyraclostrobin. Subsequently, a highly sensitive lateral flow immunoassay (LFIA) based on gold nanoparticles (AuNPs) for detecting pyraclostrobin was established. The AuNP-LFIA method exhibited a visual limit of detection (vLOD) of 1.25 ng/mL and a completely inhibitory concentration of 5 ng/mL, surpassing the sensitivity of previously described methods. The accuracy of the established method was confirmed through spiked-recovery tests, exhibiting a sensitivity of 30 ng/g in wheat, apple, and soil samples, and 60 ng/g in Chinese cabbage samples. The reliability of the method was validated using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). This study presents a sensitive and cost-effective approach for rapidly detecting pyraclostrobin residues, demonstrating the significant potential of AlphaFold 3 in antibody engineering and small molecule on-site detection.

Multianalytical Approach to Understand Polyphenol-Mal d 1 Interactions to Predict Their Impact on the Allergenic Potential of Apples.

Interactions between phenolic compounds and the allergen Mal d 1 are discussed to be the reason for better tolerance of apple cultivars, which are rich in polyphenols. Because Mal d 1 is susceptible to proteolytic digestion and allergenic symptoms are usually restricted to the mouth and throat area, the release of native Mal d 1 during the oral phase is of particular interest. Therefore, we studied the release of Mal d 1 under different in vitro oral digestion conditions and revealed that only 6-15% of the total Mal d 1 present in apples is released. To investigate proposed polyphenol-Mal d 1 interactions, various analytical methods, e.g., isothermal titration calorimetry, 1H-15N-HSQC NMR, and untargeted mass spectrometry, were applied. For monomeric polyphenols, only limited noncovalent interactions were observed, whereas oligomeric polyphenols and browning products caused aggregation. While covalent modifications were not detectable in apple samples, a Michael addition of epicatechin at cysteine 107 in r-Mal d 1.01 was observed.

First report of apple hammerhead viroid infecting apple trees in Montenegro.

Apple hammerhead viroid (AHVd, Pelamoviroid, Avsunviroidae) is one of the five viroids infecting apples. It has been identified on all continents except Australia since its viroid nature was confirmed (DiSerio et al. 2018; CABI and EPPO 2022). AHVd has been found in apple trees showing leaf mosaic, ringspot and dieback (Hamdi et al., 2021). Apple (Malus domestica Borkh.) and its wild relatives are traditionally grown in Montenegro. With an annual production of 7767 tons on 216 ha, it is the second most important fruit tree (after plum) in the country (Anonymous 2022). In a 2020-2022 survey, 29 apple trees exhibiting virus-like symptoms (e.g. mosaic, necrosis) were sampled throughout Montenegro, including 16 locations in eight municipalities (Podgorica, Danilovgrad, Niksic, Mojkovac, Bijelo Polje, Berane, Pljevlja and Savnik). Small RNAs were isolated using the mirVana miRNA Isolation Kit (Ambion, Life Technologies) and pooled into three bulk samples. Each bulk contained 9 to 10 samples. Libraries of sRNAs were constructed using the Ion Total RNA-Seq Kit v2 and barcoded using the Xpress RNA-Seq Barcode 1-16 Kit (Ion Torrent) according to the manufacturer's instructions. Small RNA library sequencing was performed on Illumina platform (Novogene Europe) yielding 9.9, 9.8 and 18.6 million reads in the three libraries. The CLC Genomics Workbench software was used to demultiplex the reads into pools using the 'Demultiplex Reads' tool. The online program VirusDetect (Zheng et al. 2017) was used for virus/viroid detection and identification. Besides viruses known to infect apple (apple stem grooving virus, apple stem pitting virus, apple mosaic virus), contigs mapping to AHVd were identified in all three bulks enabling full AHVd genomes reconstruction. To verify AHVd presence, all 29 apple samples were tested by reverse transcription-polymerase chain reaction (RT-PCR) using the AHVd PG13f/PG12r primers (Messmer et al. 2017). AHVd amplicons were obtained in three samples (30/21, 32/21 and 38/21) from bulk 1 and two samples (47/21 and 55/21) from bulk 2, while all samples from bulk 3 tested negative potentially due to the low titer of the pathogen or nucleotide mismatches at the 3' end of the primers. The three amplicons from bulk 1 were Sanger sequenced and partial AHVd genomes over 200 nts were obtained from two of them (30/21 and 32/21) (GenBank acc. nos. OQ863319 and OR020603). Furthermore, three full consensus AHVd genomes were assembled in Geneious Prime by mapping Sanger sequences onto contigs from Virus Detect and named 30/21, 32/21 and 38/21 (acc. nos. PP133245, -46, and -47, respectively). All three genomes exhibited conserved hammerhead motifs (Messmer et al. 2017). In BLASTn analysis, the isolate 30/21 from Montenegro shared the highest nt identity (98.8%) with the isolate SA-36 (ON564299) from Czechia, while 32/21 and 38/21 showed the highest identities (95.4% and 92.3%) with isolates SD17_2-3 (MK188691) from Canada and JF2 (ON564298) from Czechia, respectively. To the best of our knowledge, this is the first report of AHVd infecting Malus domestica in Montenegro. The AHVd-positive samples 30/21 and 32/21 originated from at least two-decade-old apple trees from Niksic, whilst 38/21 came from a 40-year-old tree from Mojkovac district, suggesting that this viroid has long been present in different parts of the country. The AHVd discovery in Montenegro should be considered in any phytosanitary regulations and pome fruit certification program in the country.

Evaluating the Susceptibility of Different Crops to Smoke Taint

The potential for grapes and wine to be tainted following vineyard exposure to wildfire smoke is well established, with recent studies suggesting hops and apples (and thus beer and cider) can be similarly affected. However, the susceptibility of other crops to ‘smoke taint’ has not yet been investigated. Smoke was applied to a selection of fruits and vegetables, as well as potted lavender plants, and their volatile phenol composition determined by gas chromatography–mass spectrometry to evaluate their susceptibility to contamination by smoke. Volatile phenols were observed in control (unsmoked) capsicum, cherry, lavender, lemon, spinach and tomato samples, typically at ≤18 µg/kg, but 52 µg/kg of guaiacol and 83–416 µg/kg of o- and m-cresol and 4-methylsyringol were detected in tomato and lavender samples, respectively. However, significant increases in volatile phenol concentrations were observed as a consequence of smoke exposure; with the highest volatile phenol levels occurring in smoke-exposed strawberry and lavender samples. Variation in the uptake of volatile phenols by different crops was attributed to differences in their physical properties, i.e., their surface area, texture and/or cuticle composition, while the peel of banana, lemon, and to a lesser extent apple samples, mitigated the permeation of smoke-derived volatile phenols into pulp. Results provide valuable insight into the susceptibility of different crops to smoke contamination.

The impact of pre-drying and different infrared powers on some quality parameters of apple chips fried by vacuum-combined infrared radiation

In this study, the use of vacuum-combined infrared radiation (VCIR) as a frying technique for the production of apple chips was investigated. The effects of a pre-drying treatment before frying on the quality parameters of apple chips were also evaluated. While the frying time of apple slices decreased by increasing the infrared power, the browning index value, 5-hydroxymethylfurfural (HMF) content, and oxidation ratio were raised. The frying times, oil contents, browning, and oxidation rates of apple chips were decreased with the pre-drying treatment. The sensory analyzes showed that the samples fried by vacuum-combined infrared radiation had the highest scores in all sensory characteristics than deep-fat fried samples. Pre-dried apple samples (41% moisture) fried at 350W infrared power under 400 mmHg vacuum pressure had the highest score for general acceptance. The results showed that VCIR would be an alternative frying method for producing healthier apple chips with less oil content and higher quality.

A novel, intelligent and computer-assisted electrochemical sensor for extraction and simultaneous determination of patulin and citrinin in apple and pear fruit samples

In this work, a novel electrochemical sensor was fabricated for simultaneous determination of patulin (PT) and citrinin (CT) in apple and pear fruit samples. A glassy carbon electrode (GCE) was modified with graphene-multiwalled carbon nanotubes-ionic liquid (Gr-MWCNTs-IL) which was used as a platform to electrochemical synthesis of molecularly imprinted polymers (MIPs) by using PT and CT as templates, maleic acid as a functional monomer, and ethylene glycol dimethacrylate as a cross linker with the aim of preconcentration and simultaneous determination of the PT and CT. Experimental variables affecting fabrication of the structure of the sensor and hydrodynamic differential pulse voltammetric (HDPV) response of the sensor were optimized by a small central composite design and desirability function. After optimization, the HDPV responses of the sensor were calibrated by multivariate calibration methods in the ranges of 0.5–13 fM and 1.5–18 fM for PT and CT, respectively, with the help of PLS-1, RBF-PLS, rPLS, LS-SVM, and RBF-ANN with the aim of selecting the best algorithm to assist the sensor. Our results confirmed the best performance was observed from RBF-ANN which was used for the analysis of apple and pear fruit samples. Limit of detections of the sensor assisted by RBF-ANN for determination of PT and CT were 0.08 and 0.61 fM, respectively. Several commercial brands were analyzed by the use of sensor assisted by RBF-ANN and HPLC-UV, and the results confirmed performance of the sensor was admirable and comparable with the reference method with lower cost, faster response, and easier procedure which made it to be a reliable alternative method for simultaneous determination of PT and CT in real matrices.

Natural and polyanionic heparin polysaccharide functionalized upconversion nanoparticles for highly sensitive and selective ratiometric detection of pesticide

Pesticide contamination is a global concern, threatening human health and food safety. Herein, we developed heparin (HEP) functionalized upconversion nanoparticles (UCNPs)-based ratiometric nanosensor for the sensitive detection of 2,6-dichloro-4-nitroaniline (DCN) pesticide via inner filter effect. The strategy for HEP functionalization of UCNPs is based on adjusting the surface potentials of UCNPs with polyanionic HEP through the electrostatic interaction. UCNPs (NaYbF4:Gd/Y/Tm@NaYbF4@NaYF4) was designed with core-shell-shell structure and extra sensitizer layer for efficient and strong upconversion luminescence (UCL) in the range of UV to NIR. After incorporation of DCN, the upconverted UV emission of UCNPs-HEP ratiometric nanosensor was considerably quenched with the NIR UCL at 800 nm remaining unchanged as internal standard. The UCNPs-HEP ratiometric nanosensor can achieve outstandingly selective and sensitive detection of DCN at the wide linear range of 5–300 μM with a detection limit of 0.41 μM. The remarkable applicability of the UCNPs-HEP ratiometric nanosensor was verified in apple, cucumber and grapes samples. The developed UCNPs-HEP ratiometric nanosensor with excellent biocompatibility and water dispersion capability, is promising for convenient, selective and sensitive sensing of DCN towards food and aqueous samples.

Assessment of apple soluble sugar content by hyperspectral vegetation indexes

Soluble sugar content in apple fruit is a crucial internal quality factor. Rapid and accurate estimation of soluble sugar content in apple fruit is helpful to predicting maturity. However, few studies have used an approach of hyperspectral vegetation indexes for monitoring apple soluble sugar content from ground-based handheld hyperspectral data. This study systematically analyzed the performance of hyperspectral vegetation indexes of apple in estimating the soluble sugar content. The visible and near infrared spectral of apple samples were measured by using a hyperspectral equipment, with the wavelength of 350–2500 nm. Eleven early-ripening apple varieties were collected from orchards located in five provinces of China, and the sugar content of each apple fruit sample was measured using laboratory methods. Two-band combination method was used to identify the effective spectral index. Results showed that the newly developed two-band ratio spectral index R833/R834 (Rλ is the reflectance value at wavelength λ) was recommended as the optimal index for monitoring early-ripening apple soluble sugar content, generated the coefficients of determination, root mean square error (RMSE) and residual prediction deviation (RPD) values between the measured and predicted values of 0.73%, 0.72%, and 1.38%, respectively. Result indicated that the newly developed two-band index R833/R834 can be used to nondestructively determine apple fruit soluble sugar content. The findings can provide insight into the relationship between the optical properties of apple fruit at different wavelengths and soluble sugar content.

Molecular and chemical evaluation of patulin production of Aspergillus and Penicillium-like species isolated from Hungarian apples

Mycotoxins are secondary fungal metabolites harmful to humans and animals. Patulin (PAT) is a toxin found in different food products but especially in apples and their derivative products. The most common fungi producers of this compound are Aspergillus clavatus and Penicillium expansum. The production of patulin, as other mycotoxins, can be impacted by diverse phenomena such as water and nutrient availability, UV exposure, and the presence of antagonistic organisms. Consequently, gaining a comprehensive understanding of climate and environmental conditions is a crucial step in combating patulin contamination. In this study, moulds were isolated from 40 apple samples collected from seven locations across Hungary: Csenger, Damak, Pallag, Lövőpetri, Nagykálló, and Újfehértó. A total of 183 moulds were morphologically identified, with 67 isolates belonging to the Alternaria, 45 to the Aspergillus, and 13 to the Penicillium groups. The location possessed a higher influence than farming method on the distribution of mould genera. Despite the requirement of higher temperature, Aspergillus species dominated only for the region of Újfehértó with approximately 50% of the isolates belonging to the genus. Four of the seven locations assessed: Csenger, Debrecen-Pallag, Nyírtass and Nagykálló, were dominated by Alternaria species. All isolates belonging to the genera Aspergillus and Penicillium were tested for the presence of the isoepoxidone dehydrogenase (idh) gene, a key player in the patulin metabolic pathway. To guarantee patulin production, this ability was confirmed with TLC assays. The only Aspergillus strain that presented a positive result was the strain Aspergillus clavatus B9/6, originated from the apple cultivar Golden Reinders grown in Debrecen-Pallag by integrated farming. Of the Penicillium isolates only one strain, B10/6, presented a band of the right size (500-600 bp) for the idh gene. Further sequencing of the ITS gene showed that this strain should be classified as Talaromyces pinophilus. The TLC tests confirmed this microorganism as the only patulin producer under the studied conditions for its cluster.

Detection of myclobutanil and tebuconazole in apple using magnetic molecularly imprinted polymer surface-enhanced Raman spectroscopy

The main challenge in Raman detection of pesticide residues in agricultural products is matrix interference, which hinders accurate identification of trace compounds in complicated agricultural samples. In this study, a novel surface-enhanced Raman spectroscopy approach based on magnetic molecularly imprinted polymers (MMIP-SERS) was introduced for the rapid analysis of myclobutanil and tebuconazole in apples. The synthesized magnetic molecularly imprinted polymer selectively adsorbed triazole pesticides, effectively eliminating matrix interference in real samples. The saturation adsorption time for MMIPs was only 10 min. In addition, the synthesized colloidal gold served as an excellent substrate for enhancing the specific signals for myclobutanil and tebuconazole. We successfully identified the characteristic peak of tebuconazole at 1089 cm−1, while myclobutanil showed its characteristic peak at 632 cm−1. The series of experiments and recovery tests confirmed the high sensitivity of the developed MMIP-SERS method using colloidal gold as an enhanced substrate for fungicide analysis in apple samples. The linear detection ranges for myclobutanil and tebuconazole in apples were determined to be 0.2–10 mg/kg and 0.5–10 mg/kg, respectively. The limit of detection was 0.09 mg/kg for tebuconazole and 0.05 mg/kg for myclobutanil. This study provides a rapid and simple method for detecting myclobutanil and tebuconazole based on the synergistic effect of the imprinted polymer and SERS with good separation and detection performance.

Electrochemical detection of carbendazim using molecularly imprinted poly(3,4-ethylenedioxythiophene) on Co,N co-doped hollow carbon nanocage@CNTs-modified electrode

Precisely detecting trace pesticides and their residues in food products is crucial for ensuring food safety. Herein, a high-performance electrochemical sensing platform was developed for the detection of carbendazim (CBZ) using Co,N co-doped hollow carbon nanocage@carbon nanotubes (Co,N-HC@CNTs) obtained from core–shell ZIF-8@ZIF-67 combined with a poly(3,4-ethylenedioxythiophene) (PEDOT) molecularly imprinted polymer (MIP). The Co,N-HC@CNTs exhibited excellent electrocatalytic performance, benefitting from the synergistic effect of CNTs that provide a large specific surface area and excellent electrical conductivity, Co,N co-doped carbon nanocages that offer high electrocatalytic activity and hollow nanocage structures that ensure rapid diffusion kinetics. The conductive PEDOT-MIP provided specific binding sites for CBZ detection and significantly amplified the detection signal. The sensor showed superior selectivity for CBZ with an extremely low detection limit of 1.67 pmol L−1. Moreover, the method was successfully applied to detect CBZ in tomato, orange and apple samples, achieving satisfactory recovery and accuracy, thus demonstrating its practical feasibility.

Optimization of metal–organic framework nanozyme activity via histidine modification for simultaneous pesticide detection

Biosensors provide simple, rapid and sensitive detection of a wide range of analytes. Recently, they have been widely used for the rapid detection of pesticides, which makes up for the shortcomings of traditional detection methods. However, the catalytic activity of some nanozymes is not satisfactory in practical applications, limiting the performance of biosensors. Further development of highly active and stable nanozymes is conducive to improving the sensitivity of the sensors and expanding their application in practical detection. Herein we simulated the amino acid microenvironment of natural enzymes and synthesized His-MIL-101(Fe)-X with different histidine (His) modification amounts (X = 0, 25%, 50%, 75%) by regulating the ratio of histidine and terephthalic acid ligands using a one-step solvothermal method. With increasing histidine doping, the peroxidase-like activity of His-MIL-101(Fe)-X was gradually enhanced, and the sensing performance of the sensor arrays constructed by combining His-MIL-101(Fe)-X with three peroxidase substrates was also gradually improved, with a 25-fold increase in detection limit. The His-MIL-101(Fe)-75% sensor array was not only able to accurately discriminate five pesticides in the range of 2-100 μM, but also to quantitatively identify different concentrations of pesticides. Moreover, the His-MIL-101(Fe)-75% sensor array showed good anti-interference capability and was able to discriminate five pesticides at only 2 μM in soil, lake water, seawater, and apple samples, as well as quantitatively detecting diafenthiuron, which has great potential for practical application.

High selectivity molecularly imprinted polymer based on short amylose as bio-based functional monomers for selective extraction of λ-cyhalothrin

Nowadays, the development of sustainable molecularly imprinted polymers (MIPs) with high selectivity is still challenging due to the limitations of bio-based functional monomers. In this study, the highly selective and porous MIPs (LC-TMIPs) were designed and prepared on short amylose (SAM) as bio-based functional monomers, λ-cyhalothrin (LC) as a template molecule, and tetrafluoroterephthalonitrile as a rigid crosslinking agent. Static, dynamic, and selective adsorption experiments were conducted to investigate the adsorption performance. The results indicated that, compared to MIPs prepared using epichlorohydrin as flexible crosslinking agents, LC-TMIPs exhibited higher imprinting factor (3.93), selectivity (5.78), and adsorption capacity (35.79 mg g−1), as well as faster adsorption/desorption kinetics. The LC-TMIPs were used as sorbents for the selective determination of LC in both apple and cucumber samples by high-performance liquid chromatography. Under the optimal extraction conditions, the recoveries of the method reached 92.1–106.1 %, with a linear range of 1.5–30 ng g−1 and a detection limit of 0.5 ng g−1. The proposed preparation method of LC-TMIPs is expected to open a new way to prepare highly selective and sustainable MIPs for hydrophobic compounds.

Senna auriculata extract-assisted biogenic synthesis of yellow emissive gold nanoclusters for quantitative detection of glyphosate in food and environmental samples

The green chemistry approach was unitized for the development of fluorescent nanomaterial. The objective of this study is to develop plant-based fluorescence nanomaterials via environment-friendly and biocompatible approach. Here, water-soluble yellow emissive gold nanoclusters were synthesized by using extract of Senna auriculata leaves and 1.25 mM of HAuCl4·xH2O via microwave-assisted method. Senna auriculata-AuNCs (S. auriculata-AuNCs) exhibit excellent solubility, good quantum yield (QY), stability, and biocompatibility. The ultra-small (<5 nm) size of S. auriculata-AuNCs displayed yellow emission and were characterized by using fluorescence, UV–visible, FT-IR, HR-TEM, zeta potential, DLS, XPS, and XRD techniques. S. auriculata-AuNCs display an intense emission of 620 nm when excited at 500 nm. The as-synthesized S. auriculata-AuNCs act as an effective sensor for sensing glyphosate pesticide via the “turn-off” mechanism. Moreover, S. auriculata-AuNCs showed a good performance in detecting glyphosate with a wider linear range from 0.05 to 100 µM, offering the detection limit of 32.0 nM for glyphosate. Additionally, S. auriculata-AuNCs are also able to visualize Saccharomyces cerevisiae cells, and successfully applied in assaying glyphosate pesticide in apple, rice, river, and canal water samples.

A comparative study of distinguishing apple cultivars and a clone based on features of selected fruit parts and leaves using image processing and artificial intelligence

This study aimed to identify the most useful white-fleshed apple samples to distinguish apple cultivars and a clone. Whole apples, apple slices, seeds, and leaves belonging to ‘Free Redstar’, clone 118, ‘Ligolina’, ‘Pink Braeburn’, and ‘Pinokio’ were imaged using a digital camera. The texture parameters were extracted from images in color channels L, a, b, R, G, B, X, Y, Z, U, V, and S. The classification models were built using traditional machine learning algorithms. Models developed using selected image seed textures allowed the classification of apple cultivars and a clone with the highest average accuracy of up to 97.4%. The apple seeds ‘Free Redstar’ were distinguished with the highest accuracy, equal to 100%. Machine learning models built based on the textures of apple skin allowed for the clone and cultivar classification with slightly lower correctness, reaching 94%. Meanwhile, the average accuracies for models involving selected flesh and leave textures reached 86.4% and 88.8%, respectively. All the most efficient models for classifying individual apple fruit parts and leaves were developed using Multilayer Perceptron. However, models combining selected image textures of apple skin, slices (flesh), seeds, and leaves produced the highest average accuracy of up to 99.6% in the case of Bayes Net. Thus, it was found that including features of different parts of apple fruit and apple leaves in one model can allow for the correct distinguishing of apples in terms of cultivar and clone.

Mycotoxin patulin contamination in various fruits and estimating its dietary impact on the consumers: From orchard to table

The present research examined patulin's presence across the whole supply chain of selected fruits. A comprehensive analysis was conducted on 442 samples of fruits (oranges, apples, apricots, lemons, and guava) to determine the presence of patulin contamination. This analysis used Liquid Chromatography (HPLC) with a UV detector. The findings indicate that 17, 23, and 28 % of selected fruit samples tested positive for patulin levels in farm, transportation, and market samples. However, the sample collected during the transportation step showed that 56 % (percentage of positive samples) of fruits have patulin levels greater than 50 μg/kg, and 41 % (percentage of positive samples) have greater levels than 50 μg/kg in market samples. The findings of the one-way analysis of variance indicated that no statistically significant variation existed between the amounts of patulin across the various stages of the food supply chain system (p > 0.05). Nevertheless, the analysis of the correlation study, namely Kendall's tau_b and Spearman's rho, denote a robust association between the levels of patulin and the food supply system. The apple samples exhibited the most significant average dietary intake of patulin, with an average value of 0.11 μg/kg bw/day. The maximum mean hazard quotient (HQ) of 0.28 was also recorded. The prevalence and incidence of patulin in specific fruits were found to be relatively high, and it was observed that market samples had elevated levels of patulin in the selected fruits.

Metabolomics on Apple (Malus domestica) Cuticle-Search for Authenticity Markers.

The profile of secondary metabolites present in the apple cuticular layer is not only characteristic of a particular apple cultivar; it also dynamically reflects various external factors in the growing environment. In this study, the possibility of authenticating apple samples by analyzing their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. A total of 274 authentic apple samples from four cultivars harvested in the Czech Republic and Poland between 2020 and 2022 were analyzed. The complex data generated, processed using univariate and multivariate statistical methods, enabled the building of classification models to distinguish apple cultivars as well as their geographical origin. The models showed very good performance in discriminating Czech and Polish samples for three out of four cultivars: "Gala", "Golden Delicious" and "Idared". Moreover, the validity of the models was tested over several harvest seasons. In addition to metabolites of the triterpene biosynthetic pathway, the diagnostic markers were mainly wax esters. "Jonagold", which is known to be susceptible to mutations, was the only cultivar for which an unambiguous classification of geographical origin was not possible.

Farm to fork strategy for evaluating the qualitative and quantitative health risks to the Nepalese population associated with pesticide residues in apple and banana

Studies of pesticide use on commercial fruits are limited in Nepal. We surveyed the experiences and opinions of banana farmers in Nepal and monitored pesticide residues in apples and bananas. We monitored the residual status and associated health risks of 51 multi-group pesticides using Liquid Chromatography Triple Quadrupole Mass Spectrometry. Apple and banana samples were collected from different districts, farms, markets, and seller categories (our farm to fork survey). We found a significant bivariate positive correlation between farmers’ knowledge of pesticide negative effects and safety-promoting behavior among farmers. Residues of tebuconazole, difenoconazole, propargite and imidacloprid were most frequently detected. Of all the detected pesticides, propargite showed the highest concentration in apples, exceeding regulatory maximum residue limits (MRLs) in 24% of the samples. Epoxiconazole, tebuconazole, imidacloprid, quinalphos, fenpropathrin and bifenthrin in apples, and metalaxyl and imidacloprid in bananas also crossed their MRLs. Dietary exposure to pesticides among children and adults was estimated based on a hazard quotient and hazard index by using lower-bound and upper-bound approaches. Our results indicated that children consuming apples with residues of propargite are exposed to the greatest pesticide hazard.

Designing a size exclusion-based hapten and the development of a quantitative and visual time-resolved fluorescence immunochromatography assay strip for detecting dimethomorph and flumorph in a group-specific manner

Based on the size and surface properties of dimethomorph and flumorph, we used a computer simulation-assisted size exclusion hapten design strategy to develop group-specific monoclonal antibodies that can simultaneously recognize dimethomorph and flumorph. For this, we performed quantitative and visual semi-quantitative time-resolved fluorescence immunochromatography (TRFICA) to simultaneously detect dimethomorph and flumorph in potatoes and apples. In potato samples, the visual limit of detection (vLOD) for dimethomorph and flumorph was 4 ng/mL and 8 ng/mL, respectively, whereas the quantitative limit of detection (qLOD) for dimethomorph and flumorph was 0.26 and 0.33 ng/mL, respectively. The vLOD of dimethomorph and flumorph in apple samples was 8 ng/mL, whereas the qLOD of dimethomorph and flumorph was 0.17 and 0.38 ng/mL, respectively. The average recovery of potato and apple samples ranged from 77.5% to 121.7%, which indicated that the method can be used to rapidly detect dimethomorph and flumorph in food samples.