Identification and verification of seed development related miRNAs in kernel almond by small RNA sequencing and qPCR.

Many studies have investigated the role of miRNAs on the yield of various plants, but so far, no report is available on the identification and role of miRNAs in fruit and seed development of almonds. In this study, preliminary analysis by high-throughput sequencing of short RNAs of kernels from the crosses between almond cultivars 'Sefid' × 'Mamaee' (with small and large kernels, respectively) and 'Sefid' × 'P. orientalis' (with small kernels) showed that the expressions of several miRNAs such as Pdu-miR395a-3p, Pdu-miR8123-5p, Pdu-miR482f, Pdu-miR6285, and Pdu-miR396a were significantly different. These miRNAs targeted genes encoding different proteins such as NYFB-3, SPX1, PGSIP3 (GUX2), GH3.9, and BEN1. The result of RT-qPCR revealed that the expression of these genes showed significant differences between the crosses and developmental stages of the seeds, suggesting that these genes might be involved in controlling kernel size because the presence of these miRNAs had a negative effect on their target genes. Pollen source can influence kernel size by affecting hormonal signaling and metabolic pathways through related miRNAs, a phenomenon known as xenia.

Comparative and Phylogenetic Analyses of the Complete Chloroplast Genomes of Six Almond Species (Prunus spp. L.).

As a source of genetic variation, almond germplasm resources are of great significance in breeding. To better reveal the mutation characteristics and evolution patterns of the almond chloroplast (cp) genome, the complete cp genomes from six almond species were analyzed. The lengths of the chloroplast genome of the six almond species ranged from 157,783 bp to 158,073 bp. For repeat sequence analysis, 53 pairs of repeats (30 bp or longer) were identified. A total of 117 SSR loci were observed, including 96 polymorphic SSR loci. Nine highly variable regions with a nucleotide variability (Pi) higher than 0.08, including rps16, rps16-psbK, atpF-atpH, rpoB, ycf3-rps4, rps4-ndhJ, accD-psaI and rps7-orf42 (two highly variable regions) were located. Based on the chloroplast genome evolution analysis, three species (P. tenella, P. pedunculata and P. triloba) and wild cherry (P. tomentosa) were grouped into clade I. Clade II consisted of two species (P. mongolica and P. tangutica) and wild peach (P. davidiana). Clade III included the common almond (P. dulcis), cultivated peach (P. persica) and GanSu peach (P. kansuensis). This result expands the researchers' vision of almond plant diversity and promotes an understanding of the evolutionary relationship among almond species. In brief, this study provides abundant resources for the study of the almond chloroplast genome, and has an important reference value for study of the evolution and species identification of almond.

Chemometric comparison of almond oxidation rates using kinetic parameters obtained by infrared spectroscopy.

BACKGROUND: The study of almond fat stability is essential from a quality control perspective meanly because, in most of the cases, almonds are sold skinned and thermally treated. In this work an alternative method to Rancimat test based on attenuated total reflectance-Fourier-transform infrared (ATR-FTIR) spectrometry was adapted for checking the induced degradation at 75 °C of seven almond oil cultivars, three of the top Californian producing varieties, and, four traditional cultivars harvested in Spain. RESULTS: The thermal oil degradation evolution was followed by measuring the changes in the absorbance of the selected FTIR spectra bands (3470, 3006, 1730, 1630, 988 and 970 cm-1 ). A first-order kinetic behaviour was observed, after an induction time in all bands. CONCLUSIONS: Kinetic coefficients and induction times were easily obtained as the absorbance values (from difference spectra) fitted to pseudo-first-order kinetics after the induction time. Principal component analysis was applied to the kinetic parameters to visualize which variables could be useful to classify the almond cultivars based on their resistance to thermal oxidation processes. It was found that selecting only the induction times corresponding to the bands 3470, 3006, 1630 and 970 cm-1 a separate classification of the Californian cultivars from the Spanish ones was possible. Finally, a linear discriminant analysis was assayed using only the four induction times previously selected. Validated classification and correct in 100% of the cases was obtained for all the samples based on their Spanish or Californian origin. © 2020 Society of Chemical Industry.

Multivariate Classification of Prunus Dulcis Varieties using Leaves of Nursery Plants and Near Infrared Spectroscopy.

The emergence of new almond tree (Prunus dulcis) varieties with agricultural interest is forcing the nursery plant industry to establish quality systems to keep varietal purity in the production stage. The aim of this study is to assess the capability of near-infrared spectroscopy (NIRS) to classify different Prunus dulcis varieties as an alternative to more expensive methods. Fresh and dried-powdered leaves of six different varieties of almond trees of commercial interest (Avijor, Guara, Isabelona, Marta, Pentacebas and Soleta) were used. The most important variables to discriminate between these varieties were studied through of three scientifically accepted indicators (Variable importance in projection¸ selectivity ratio and vector of the regression coefficients). The results showed that the 7000 to 4000 cm-1 range contains the most useful variables, which allowed to decrease the complexity of the data set. Concerning to the classification models, a high percentage of correct classifications (90-100%) was obtained, where dried-powdered leaves showed better results than fresh leaves. However, the classification rate of both kinds of leaves evidences the capacity of the near-infrared spectroscopy to discriminate Prunus dulcis varieties. We demonstrate with these results the capability of the NIRS technology as a quality control tool in nursery plant industry.

Development of a methodology to analyze leaves from Prunus dulcis varieties using near infrared spectroscopy.

Near-infrared spectroscopy (NIRS) can be a faster and more economical alternative to traditional methods for screening varietal mixtures of nursery plants during the propagation process to ensure varietal purity and to avoid errors in the dispatch batches. The global objective of this work was to develop and optimize a NIR spectral collection method for construction of robust multivariate discrimination models. Three different varieties of Prunus dulcis (Avijor, Guara, and Pentacebas) of agricultural interest were used for this study. Sources of variation were investigated, including the position of the leaves on the trees, differences among trees of the same variety, and differences at the varietal level. Three types of processed samples were investigated. Fresh leaves, dried leaves, and dried leaves in powder form were included in each analysis. A study of spectral pre-treatment methods was also performed, and multivariate methods were applied to analyze the influence of different factors on classification. These included principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and ANOVA simultaneous component analysis (ASCA). The results indicated that variety was the most important factor for classification. The spectral pre-treatment that provided the best results was a combination of standard normal variate (SNV), Savitzky-Golay first derivative, and mean-centering methods. With regard to the type of processed sample, the highest percentages of correct classifications were obtained with fresh and dried powdered leaves at both the training set and test set validation levels. This study represents the first step towards the consolidation of NIRS as a method to identify Prunus dulcis varieties.

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.

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.

The classification of almonds (Prunus dulcis) by country and variety using UHPLC-HRMS-based untargeted metabolomics.

The aim of this study was to use an untargeted UHPLC-HRMS-based metabolomics approach allowing discrimination between almonds based on their origin and variety. Samples were homogenised, extracted with ACN:H2O (80:20) containing 0.1% HCOOH and injected in a UHPLC-QTOF instrument in both positive and negative ionisation modes. Principal component analysis (PCA) was performed to ensure the absence of outliers. Partial least squares - discriminant analysis (PLS-DA) was employed to create and validate the models for country (with five different compounds) and variety (with 20 features), showing more than 95% accuracy. Additional samples were injected and the model was evaluated with blind samples, with more than 95% of samples being correctly classified using both models. MS/MS experiments were carried out to tentatively elucidate the highlighted marker compounds (pyranosides, peptides or amino acids, among others). This study has shown the potential of high-resolution mass spectrometry to perform and validate classification models, also providing information concerning the identification of the unexpected biomarkers which showed the highest discriminant power.

Almond supplementation reduces serum uric acid in coronary artery disease patients: a randomized controlled trial.

OBJECTIVE: Elevated serum uric acid (UA), a biomarker of renal insufficiency, is also an independent prognostic marker for morbidity in coronary artery disease (CAD) and poses serious health risks. This study reports the effect of almond consumption on UA in CAD patients. STUDY DESIGN: A randomized controlled clinical trial was conducted with three groups: no-intervention (NI), Pakistani almonds (PA) or American almonds (AA). Patients were recruited from the Cardiology Clinics, Aga Khan University Hospital. Two follow-ups were scheduled at week-6 and week-12. 150 patients were randomly divided in three groups (50 per group). NI was not given almonds, whereas the PA and AA were given Pakistani and American almond varieties (10 g/day), respectively; with instruction to soak overnight and eat before breakfast. RESULTS: Almonds supplementation significantly reduced (p < 0.05) serum UA among groups, and over time. At week-6, UA concentrations were -13 to -16 % less in PA and AA; at week-12 the concentrations were -14 to -18 % less, compared to NI. Systolic and diastolic blood pressure and body weights of the participants remained fairly constant among all the groups. CONCLUSION: Almonds (10 g/day), eaten before breakfast, reduces serum UA in CAD patients. Prevention of hyperuricemia can confer protection from kidney and vascular damage and if extrapolated for general population, dietary almonds can offer grander health benefit. Trial is registered at Australian New Zealand Clinical trial registry as ACTRN12614000036617.