Untargeted metabolomics with multivariate analysis to discriminate hazelnut (Corylus avellana L.) cultivars and their geographical origin.

BACKGROUND: In the present study a metabolomics-based approach was used to discriminate among different hazelnut cultivars and to trace their geographical origins. Ultra-high-pressure liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UHPLC-ESI/QTOF-MS) was used to profile phenolic and sterolic compounds. RESULTS: Compounds were identified against an in-house database using accurate monoisotopic mass and isotopic patterns. The screening approach was designed to discern 15 hazelnut cultivars and to discriminate among the geographical origins of six cultivars from the four main growing regions (Chile, Georgia, Italy, and Turkey). This approach allowed more than 1000 polyphenols and sterols to be annotated. The metabolomics data were elaborated with both unsupervised (hierarchical clustering) and supervised (orthogonal projections to latent structures discriminant analysis, OPLS-DA) statistics. These multivariate statistical tools allowed hazelnut samples to be discriminated, considering both 'cultivar type' and 'geographical origin'. Flavonoids (anthocyanins, flavanols and flavonols - VIP scores 1.34-1.49), phenolic acids (mainly hydroxycinnamics - VIP scores 1.35-1.55) together with cholesterol, ergosterol, and stigmasterol derivatives (VIP scores 1.34-1.49) were the best markers to discriminate samples according to geographical origin. CONCLUSIONS: This work illustrates the potential of untargeted profiling of phenolics and sterols based on UHPLC-ESI/QTOF mass spectrometry to discriminate hazelnut and support authenticity and origin. © 2019 Society of Chemical Industry.

Functional and sensory properties of pistachio nuts as affected by cultivar.

BACKGROUND: Modern agriculture allows farmers to choose among different cultivars of the same fruit to fulfill their agronomic needs and consumers' demands; however, there are only a few studies that describe and compare key functional and sensory properties of different pistachio cultivars. The main objective of this study was to compare eight pistachio cultivars by analyzing key functional properties (phenolic compounds, polymeric procyanidins, antioxidant activity, and inhibition of α-amylase and ß-glucosidase), aromatic compounds with gas chromatography-mass spectrometry (GC-MS), and by examining their sensory properties with a trained panel. RESULTS: A combination of LC-PDA-MS-QTof (liquid chromatography photodiode array quadrupole time-off flight mass spectrometry) and electrospray ionization was used to determine two phenolic acids, nine flavonols, one anthocyanin, and three flavan-3-ols in pistachio cultivars, with a total concentration ranging from 500 to 6065 mg 100 g-1 dry weight (dw). The total polymeric procyanidins concentrations oscillated between 348 and 5919 mg 100 g-1 dw, (-)-epicatechin being the major monomer contributor. Pinene was the most abundant volatile compound (∼200 mg kg-1 dw), and, in the sensory analysis of samples, 23 sensory attributes were found to differ significantly among the cultivars. CONCLUSION: The cultivar 'Larnaka' stood out as having the best functional profile (high polyphenolic content, high antioxidant activity, and high values of α-amylase and ß-glucosidase inhibition), and the cultivars 'Kastel' and 'Kerman' showed the most attractive sensory properties, mainly the most intense flavor. © 2019 Society of Chemical Industry.

Cumulative risk assessment of pesticide residues in different Iranian pistachio cultivars: Applying the source specific HQS and adversity specific HIA approaches in Real Life Risk Simulations (RLRS).

Iran is a major supplier of the world pistachio market. In this study, we collected five pistachio cultivars from four main pistachio-producing zones in August and September 2016, and determined the residues of 18 organophosphorus, carbamate, pyrethroid and nicotinoid pesticide in these samples using Gas Chromatography-Mass Spectrometry, as an efficient method for determination of pesticides' residues. Next, single-chemical and chronic cumulative risk assessment was done based on the new approaches of the food specific Hazard Quotient and adversity specific Hazard Index. Fifteen from eighteen food-specific Hazard Quotients were above 1 even in cases when the respective contamination was bellow MRLs. The adversity specific Hazard Indexes values were above 1 for five from six adversities indicating various risks in the resulted levels of pistachios' contamination from the pesticides' mixture. However, no risk for carcinogenicity was found. Our results indicate the necessity of taking appropriate measures to control/standardize pesticides practice in pistachio cultivation in Iran and the need to re-establish the MRLs based on cumulative exposure.

Defining the Sensory Profiles of Raw Almond ( Prunus dulcis) Varieties and the Contribution of Key Chemical Compounds and Physical Properties.

This study describes the sensory composition of commercial sweet almond varieties across two California growing seasons. It also discusses the relationship between sensory attributes and chemical and physical measures. Raw, whole almonds (43 samples each of 13 varieties in 2015 and 40 samples each of 10 varieties in 2016) were evaluated for their sensory profiles using descriptive sensory analysis. The 2016 samples were also analyzed for macro- and micronutrients, amygdalin, volatile composition (using gas chromatography-mass spectrometry), and physical properties, and the results were modeled with the sensory data. Independence, Sonora, and Wood Colony were harder, more fracturable, and crunchy, whereas Fritz and Monterey were more moist and chewy, reflecting their moisture contents. Aldrich and Fritz were higher in marzipan/benzaldehyde flavor, which is related to amygdalin, benzaldehyde, phenylethyl alcohol, and benzyl alcohol. New insights are provided into sweet-almond composition and the sensorial contribution of headspace volatiles. This assists almond growers and processors in describing and marketing almond varieties.

1H NMR Spectroscopy for Determination of the Geographical Origin of Hazelnuts.

A total of 262 authentic samples was analyzed by 1H NMR spectroscopy for the geographical discrimination of hazelnuts ( Corylus avellana L.) covering samples from five countries (Germany, France, Georgia, Italy, and Turkey) and the harvest years 2013-2016. This article describes method development starting with an extraction protocol suitable for separation of polar and nonpolar metabolites in addition to reduction of macromolecular components. Using the polar fraction for data analysis, principle component analysis was applied and used to monitor sample preparation and measurement. Several machine learning algorithms were tested to build a classification model. The best results were obtained by a linear discrimination analysis applying a random subspace algorithm. The division of the samples in a trainings set and a test set yielded a cross validation accuracy of 91% for the training set and an accuracy of 96% for the test set. The identification of key features was carried out by Kruskal-Wallis test and t test. A feature assigned to betaine exhibits a significant level for the classification of all five countries and is considered a possible candidate for the development of targeted approaches. Further, the results were compared to a previously published study based on LC-MS analysis of nonpolar metabolites. In summary, this study shows the robustness and high accuracy of a discrimination model based on NMR analysis of polar metabolites.

Simultaneous detection of eight species of tree nut in foods using two tetraplex polymerase chain reaction assays.

Tree nuts comprise a category of food allergens that must be included in the food labels in several countries. We developed a polymerase chain reaction (PCR) method using eight specific primer pairs to detect eight representative tree nuts (almond, Brazil nut, cashew, hazelnut, macadamia nut, pecan, pistachio, and walnut) under the same experimental conditions. The specificity of the eight primer pairs was confirmed by PCR testing against a variety of plant and animal samples. The detection limit of the method ranged from 1 fg to 1 pg DNA of individual tree nuts. The method detected tree nut DNA in processed and unprocessed food. In addition, the primer pairs could be combined into two sets of tetraplex PCR system. The developed method is specific, sensitive, and efficient, making it useful for detecting trace amounts of eight species of tree nut in foods.

Characterization of virgin walnut oils and their residual cakes produced from different varieties.

This study addresses the composition and properties of different walnut varieties (Chandler, Hartley and Lara), in particular their virgin oils and residual cakes obtained by screw pressing employing different cultivars. Among nuts, walnut (Juglans regia L.) exhibits interesting nutritional value, mainly due to their high content in linoleic acid, phenolic and tocopherol compounds, which show antioxidant and other healthy properties. Valuable results related to fatty acid profile and minor components were observed. Virgin walnut oil is a rich source in linoleic acid (60-62%) and γ-tocopherol (517-554 mg/kg). Moreover, walnuts show a very high content in total phenolic compounds (10,045-12,474 mg/kg; as gallic acid), which contribute to a great antioxidant activity (105-170 mmol/kg for DPPH, and 260-393 mmol/kg for ORAC), being the hydrolysable tannins (2132-4204 mg/kg) and flavanols (796-2433 mg/kg) their main phenolic groups. Aldehydes account for the highest contribution to aromatic volatiles in virgin walnut oil (about 35% of total). As expected, polar phenolic compounds concentrate in the residual cake, after the separation of the oily phase, reaching a content of up to 19,869 mg/kg, leading to potential added value and applications as source of bioactive compounds to this by-product.

Evaluation of the chemical and nutritional characteristics of almonds (Prunus dulcis (Mill). D.A. Webb) as influenced by harvest time and cultivar.

BACKGROUND: Several workers have studied the effect of harvest time on chemical and nutritional composition of almonds, but the results are partly conflicting, probably due to differences in the cultivars considered and to different agronomic and climatic conditions in the growing areas. In this paper, the influence of harvest time and cultivar on the chemical and nutritional composition of almonds (Prunus dulcis (Mill). D.A. Webb) were evaluated. Ten cultivars were considered, grown in the same orchard and subjected to the same agronomical regime. Almonds were collected at two different harvest times: (i) when the fruits were unripe, but already edible, and showed green and moist hull; and (ii) when the fruits were ripe, with dry brown hull. The analyses of proximate composition, fatty acid profile, total phenolic compounds, and antioxidant activity were carried out. RESULTS: Lipid content increased (P < 0.001) during ripening, while both protein and carbohydrate content decreased (P < 0.01). Fatty acid composition showed a not univocal behavior during ripening and was highly influenced by cultivar. Total phenolic compounds and antioxidant activity varied among cultivars but increased during ripening with the exception of cv Marcona. The 'Genco' and 'Francolì' cultivars were found to be phenolic rich. CONCLUSION: Harvest time and cultivar significantly influenced the chemical and nutritional composition of almonds. Genotype strongly influenced fatty acid composition and total phenolic compounds. The changes of bioactive compounds and antioxidant activity suggest that the synthesis of antioxidants also occurs in the last stage of ripening. Unripe almonds, a valuable niche product, showed interesting nutritional value. © 2018 Society of Chemical Industry.

Tree nut allergies: Allergen homology, cross-reactivity, and implications for therapy.

Tree nut allergy is a potentially life-threatening disease that is increasing in prevalence, now affecting 1% of the general population in the United States. While other food allergies often resolve spontaneously, tree nut allergies are outgrown in less than 10% of cases. Due to the likelihood of cross-sensitization to multiple tree nut allergens, the current treatment guideline is strict avoidance of all nuts once one tree nut allergy has been diagnosed. For example, walnut and pecan are highly cross-reactive, along with cashew and pistachio, but the extent of clinical, IgE-mediated cross-reactivity among other tree nuts remains unclear, therefore making avoidance of all tree nuts a safe approach. There have been recent advances in immunotherapy for food allergies. For instance, there are investigational immunotherapies for milk, egg and peanut allergies, specifically oral immunotherapy, sublingual immunotherapy and epicutaneous immunotherapy. However, there are no large randomized controlled clinical trials for tree nut allergies. Even though there has been less research into tree nut allergy immunotherapies, the evidence of T-cell cross-reactivity among tree nuts exists in animal models and in T cells from allergic patients indicates that immunotherapeutic interventions may be possible. Here, we review the literature regarding epidemiology, allergen homology and cross-reactivity among tree nuts, and explore how current findings can be employed for effective therapy.

Authentication of an Italian PDO hazelnut ("Nocciola Romana") by NIR spectroscopy.

Common hazelnuts are widely present in human diet all over the world, and their beneficial effects on the health have been extensively investigated and demonstrated. Different in-depth researches have highlighted that the harvesting area can define small variations in the chemical composition of the fruits, affecting their quality. As a consequence, it has become relevant to develop methodologies which would allow authenticating and tracing hazelnuts. In the light of this, the present work aims to develop a non-destructive method for the authentication of a specific high-quality Italian hazelnut, "Nocciola Romana," registered with a protected designation of origin (PDO). Thus, different samples of this fruit have been analyzed by near-infrared (NIR) spectroscopy and then classification models have been built, in order to distinguish between the PDO fruits and the hazelnuts not coming from the designated region. In particular, two different classification approaches have been tested, a discriminant one, partial least squares-discriminant analysis, and a class-modeling one, soft independent modeling of class analogies. Both methods led to very high prediction capability in external validation on a test set (classification accuracy in one case, and sensitivity and specificity in the other, all higher than 92%), suggesting that the proposed methodologies are suitable for a rapid and non-destructive authentication of the product.

Quality Evaluation of Shelled and Unshelled Macadamia Nuts by Means of Near-Infrared Spectroscopy (NIR).

The quality of shelled and unshelled macadamia nuts was assessed by means of Fourier transformed near-infrared (FT-NIR) spectroscopy. Shelled macadamia nuts were sorted as sound nuts; nuts infected by Ecdytolopha aurantiana and Leucopteara coffeella; and cracked nuts caused by germination. Unshelled nuts were sorted as intact nuts (<10% half nuts, 2014); half nuts (March, 2013; November, 2013); and crushed nuts (2014). Peroxide value (PV) and acidity index (AI) were determined according to AOAC. PCA-LDA shelled macadamia nuts classification resulted in 93.2% accurate classification. PLS PV prediction model resulted in a square error of prediction (SEP) of 3.45 meq/kg, and a prediction coefficient determination value (Rp (2) ) of 0.72. The AI PLS prediction model was better (SEP = 0.14%, Rp (2) = 0.80). Although adequate classification was possible (93.2%), shelled nuts must not contain live insects, therefore the classification accuracy was not satisfactory. FT-NIR spectroscopy can be successfully used to predict PV and AI in unshelled macadamia nuts, though.

Modeling the survival kinetics of Salmonella in tree nuts for use in risk assessment.

Salmonella has been shown to survive in tree nuts over long periods of time. This survival capacity and its variability are key elements for risk assessment of Salmonella in tree nuts. The aim of this study was to develop a mathematical model to predict survival of Salmonella in tree nuts at ambient storage temperatures that considers variability and uncertainty separately and can easily be incorporated into a risk assessment model. Data on Salmonella survival on raw almonds, pecans, pistachios and walnuts were collected from the peer reviewed literature. The Weibull model was chosen as the baseline model and various fixed effect and mixed effect models were fit to the data. The best model identified through statistical analysis testing was then used to develop a hierarchical Bayesian model. Salmonella in tree nuts showed slow declines at temperatures ranging from 21°C to 24°C. A high degree of variability in survival was observed across tree nut studies reported in the literature. Statistical analysis results indicated that the best applicable model was a mixed effect model that included a fixed and random variation of δ per tree nut (which is the time it takes for the first log10 reduction) and a fixed variation of ρ per tree nut (parameter which defines the shape of the curve). Higher estimated survival rates (δ) were obtained for Salmonella on pistachios, followed in decreasing order by pecans, almonds and walnuts. The posterior distributions obtained from Bayesian inference were used to estimate the variability in the log10 decrease levels in survival for each tree nut, and the uncertainty of these estimates. These modeled uncertainty and variability distributions of the estimates can be used to obtain a complete exposure assessment of Salmonella in tree nuts when including time-temperature parameters for storage and consumption data. The statistical approach presented in this study may be applied to any studies that aim to develop predictive models to be implemented in a probabilistic exposure assessment or a quantitative microbial risk assessment.

Nut crop yield records show that budbreak-based chilling requirements may not reflect yield decline chill thresholds.

Warming winters due to climate change may critically affect temperate tree species. Insufficiently cold winters are thought to result in fewer viable flower buds and the subsequent development of fewer fruits or nuts, decreasing the yield of an orchard or fecundity of a species. The best existing approximation for a threshold of sufficient cold accumulation, the "chilling requirement" of a species or variety, has been quantified by manipulating or modeling the conditions that result in dormant bud breaking. However, the physiological processes that affect budbreak are not the same as those that determine yield. This study sought to test whether budbreak-based chilling thresholds can reasonably approximate the thresholds that affect yield, particularly regarding the potential impacts of climate change on temperate tree crop yields. County-wide yield records for almond (Prunus dulcis), pistachio (Pistacia vera), and walnut (Juglans regia) in the Central Valley of California were compared with 50 years of weather records. Bayesian nonparametric function estimation was used to model yield potentials at varying amounts of chill accumulation. In almonds, average yields occurred when chill accumulation was close to the budbreak-based chilling requirement. However, in the other two crops, pistachios and walnuts, the best previous estimate of the budbreak-based chilling requirements was 19-32 % higher than the chilling accumulations associated with average or above average yields. This research indicates that physiological processes beyond requirements for budbreak should be considered when estimating chill accumulation thresholds of yield decline and potential impacts of climate change.

Near infrared spectroscopy is suitable for the classification of hazelnuts according to Protected Designation of Origin.

BACKGROUND: This study investigates the possibility of using near infrared spectroscopy for the authentication of the 'Nocciola Romana' hazelnut (Corylus avellana L. cvs Tonda Gentile Romana and Nocchione) as a Protected Designation of Origin (PDO) hazelnut from central Italy. Algorithms for the selection of the optimal pretreatments were tested in combination with the following discriminant routines: k-nearest neighbour, soft independent modelling of class analogy, partial least squares discriminant analysis and support vector machine discriminant analysis. RESULTS: The best results were obtained using a support vector machine discriminant analysis routine. Thus, classification performance rates with specificities, sensitivities and accuracies as high as 96.0%, 95.0% and 95.5%, respectively, were achieved. Various pretreatments, such as standard normal variate, mean centring and a Savitzky-Golay filter with seven smoothing points, were used. The optimal wavelengths for classification were mainly correlated with lipids, although some contribution from minor constituents, such as proteins and carbohydrates, was also observed. CONCLUSION: Near infrared spectroscopy could classify hazelnut according to the PDO 'Nocciola Romana' designation. Thus, the experimentation lays the foundations for a rapid, online, authentication system for hazelnut. However, model robustness should be improved taking into account agro-pedo-climatic growing conditions.

Distinguishing Nonpareil marketing group almond cultivars through multivariate analyses.

More than 80% of the world's almonds are grown in California with several dozen almond cultivars available commercially. To facilitate promotion and sale, almond cultivars are categorized into marketing groups based on kernel shape and appearance. Several marketing groups are recognized, with the Nonpareil Marketing Group (NMG) demanding the highest prices. Placement of cultivars into the NMG is historical and no objective standards exist for deciding whether newly developed cultivars belong in the NMG. Principal component analyses (PCA) were used to identify nut and kernel characteristics best separating the 4 NMG cultivars (Nonpareil, Jeffries, Kapareil, and Milow) from a representative of the California Marketing Group (cultivar Carmel) and the Mission Marketing Group (cultivar Padre). In addition, discriminant analyses were used to determine cultivar misclassification rates between and within the marketing groups. All 19 evaluated carpological characters differed significantly among the 6 cultivars and during 2 harvest seasons. A clear distinction of NMG cultivars from representatives of the California and Mission Marketing Groups was evident from a PCA involving the 6 cultivars. Further, NMG kernels were successfully discriminated from kernels representing the California and Mission Marketing Groups with overall kernel misclassification of only 2% using 16 of the 19 evaluated characters. Pellicle luminosity was the most discriminating character, regardless of the character set used in analyses. Results provide an objective classification of NMG almond kernels, clearly distinguishing them from kernels of cultivars representing the California and Mission Marketing Groups.

Identification of peanuts and tree nuts: are allergists smarter than their patients?

BACKGROUND: It has been reported that peanut- or tree nut-allergic individuals and their guardians are poorly capable of differentiating various tree nuts and peanuts. No information exists on the ability of allergists to differentiate peanuts and tree nuts. OBJECTIVE: To measure the ability of allergists and other specialists within the allergy and immunology field to identify various types of tree nuts and peanuts. METHODS: A nut box with a clear cover was constructed and contained various tree nuts and peanuts in shelled and unshelled forms. Attendees at the 2012 national meeting of the American Academy of Allergy, Asthma, and Immunology were offered participation by viewing the nut box and filling in their responses to a questionnaire. A similar procedure was conducted in the Food Allergy Center at Children's Medical Center (Dallas, TX) for guardians of children with and without peanut or tree nut allergies. RESULTS: Allergists were better able to identify and differentiate tree nuts and peanuts than guardians of peanut- or tree nut-allergic children, guardians of children without food allergies, and allergy and immunology fellows in training. CONCLUSION: It is important for allergists to educate peanut- and tree nut-allergic individuals and their guardians on the proper avoidance of peanuts and tree nuts. This includes education in the ability to identify peanuts and tree nuts. In addition, allergy and immunology fellows in training may benefit from education in proper peanut and tree nut identification.

Descriptive analysis of flavor characteristics for black walnut cultivars.

Seven black walnut cultivars, Brown Nugget, Davidson, Emma K, Football, Sparks 127, Sparrow, and Tomboy, were evaluated by descriptive sensory analysis. Seven trained panelists developed a lexicon for the black walnuts and scored the intensities of the samples for 22 flavor attributes. Results showed that the 7 samples differed significantly (P ≤ 0.05) on 13 of the attributes. For the majority of the attributes, only Emma K differed from the rest of the cultivars by being characterized with lower scores for black walnut ID, overall nutty, nutty-grain-like, nutty-buttery, floral/fruity, oily, and overall sweet. That sample also was higher in acrid, burnt, fruity-dark, musty/earthy, rancid, and bitter attributes. The remaining 6 cultivars showed few differences in individual attribute ratings, but did show some differences when mapped using multivariate techniques. Future studies should include descriptive analysis of other black walnut varieties, both wild and commercial, that could be grown and harvested for production.

The ability of adults and children to visually identify peanuts and tree nuts.

BACKGROUND: Peanuts and tree nuts are common food allergens and are the leading cause of fatalities from food-induced anaphylaxis. Dietary avoidance is the primary management of these allergies and requires the ability to identify peanuts or tree nuts. OBJECTIVES: To investigate the ability of adults and children to visually identify peanuts and tree nuts. METHODS: A nut display was assembled that held peanuts and 9 tree nuts in a total of 19 different forms. Persons 6 years or older completed a worksheet to name the items. RESULTS: One-thousand one-hundred five subjects completed the study. The mean number of peanuts and tree nuts identified by all subjects was 8.4 (44.2%) out of a possible 19. The mean for children ages 6 to 18 was 4.6 (24.2%), compared with 11.1 (58.4%) for adults older than 18 (P < .001). The most commonly identified items were peanut in the shell and without the shell. The least identified was hazelnut (filbert) in the shell and without the shell. No difference was seen in the performance of peanut- or tree nut-allergic subjects compared with nonallergic subjects. Fifty percent of subjects with a peanut or tree nut allergy correctly identified all forms of peanuts or tree nuts to which they are allergic. Parents of peanut- or tree nut-allergic children did no better than parents of children without such allergy. CONCLUSIONS: Overall, both children and adults are unreliable at visually identifying most nuts. Treatment of nut allergies with dietary avoidance should include education for both adults and children on identification of peanuts and tree nuts.