Fruit variability impacts puree quality: Assessment on individually processed apples using the visible and near infrared spectroscopy.

This study was designed to have the absolute definition of 'one apple to one puree', which gave a first insight into the impacts of fruit inter-variability (between varieties) and intra-variability (between individual fruits) on the quality of processed purees. Both the inter-variability of apple varieties and the intra-variability of single apples induced intensive changes of appearance, chemical and textural properties of their corresponding microwave-cooked purees. The intra-variability of cooked purees was different according to apple cultivars. Some strong correlations of visible-near infrared (VIS-NIR) spectra were observed between fresh and cooked apples, particularly in the regions 665-685 nm and 1125-1400 nm. These correlations allowed then the indirect predictions of puree color (a* and b*, RPD ≧ 2.1), viscosity (RPD ≧ 2.3), soluble solids content (SSC, RPD = 2.1), titratable acidity (RPD = 2.8), and pH (RPD = 2.5) from the non-destructive acquired VIS-NIR spectra of raw apples.

Revisiting the contribution of ATR-FTIR spectroscopy to characterize plant cell wall polysaccharides.

The contribution of ATR-FTIR spectroscopy to study cell wall polysaccharides (CWPs) was carefully investigated. The region 1800-800 cm-1 was exploited using principal component analysis and hierarchical clustering on a large range of different powders of CWPs based on their precise chemical characterization. Relevant wavenumbers were highlighted for each CWP: 1035 cm-1 was attributed to xylose-containing hemicelluloses, 1065 and 807 cm-1 to mannose-containing hemicelluloses, 988 cm-1 to cellulose, 1740 and 1600 cm-1 to homogalacturonans according to the degree of methylation. Some band positions were affected by macromolecular arrangements (especially hemicellulose-cellulose interactions). However, as arabinan and galactan did not reveal distinctive absorption bands, ATR-FTIR spectroscopy did not allow the discrimination of cell walls differing by the abundance of these polysaccharides, e.g., those extracted from apple and beet. Therefore, the application of ATR-FTIR could remain sometimes limited due to the complexity of overlapping spectra bands and vibrational coupling from the large diversity of CWP chemical bonds.

Mid-infrared technique to forecast cooked puree properties from raw apples: A potential strategy towards sustainability and precision processing.

The potential of MIRS was investigated to: i) differentiate cooked purees issued from different apples and process conditions, and ii) predict the puree quality characteristics from the spectra of homogenized raw apples. Partial least squares (PLS) regression was tested both, on the real spectra of cooked purees and their reconstructed spectra calculated from the spectra of homogenized raw apples by direct standardization. The cooked purees were well-classified according to apple thinning practices and cold storage durations, and to different heating and grinding conditions. PLS models using the spectra of homogenized raw apples can anticipate the titratable acidity (the residual predictive deviation (RPD) = 2.9), soluble solid content (RPD = 2.8), particle averaged size (RPD = 2.6) and viscosity (RPD ≥ 2.5) of cooked purees. MIR technique can provide sustainable evaluations of puree quality, and even forecast texture and taste of purees based on the prior information of raw materials.

Adoption and Optimization of Genomic Selection To Sustain Breeding for Apricot Fruit Quality.

Genomic selection (GS) is a breeding approach which exploits genome-wide information and whose unprecedented success has shaped several animal and plant breeding schemes through delivering their genetic progress. This is the first study assessing the potential of GS in apricot (Prunus armeniaca) to enhance postharvest fruit quality attributes. Genomic predictions were based on a F1 pseudo-testcross population, comprising 153 individuals with contrasting fruit quality traits. They were phenotyped for physical and biochemical fruit metrics in contrasting climatic conditions over two years. Prediction accuracy (PA) varied from 0.31 for glucose content with the Bayesian LASSO (BL) to 0.78 for ethylene production with RR-BLUP, which yielded the most accurate predictions in comparison to Bayesian models and only 10% out of 61,030 SNPs were sufficient to reach accurate predictions. Useful insights were provided on the genetic architecture of apricot fruit quality whose integration in prediction models improved their performance, notably for traits governed by major QTL. Furthermore, multivariate modeling yielded promising outcomes in terms of PA within training partitions partially phenotyped for target traits. This provides a useful framework for the implementation of indirect selection based on easy-to-measure traits. Thus, we highlighted the main levers to take into account for the implementation of GS for fruit quality in apricot, but also to improve the genetic gain in perennial species.

Fresh, freeze-dried or cell wall samples: Which is the most appropriate to determine chemical, structural and rheological variations during apple processing using ATR-FTIR spectroscopy?

Attenuated total reflectance Fourier transform spectroscopy (ATR-FTIR) was applied on fresh (NF), freeze-dried (FD) and cell wall materials (AIS) of raw and processed apples. These samples prepared from 36 apple sets and the corresponding 72 purees, issued from different varieties, agricultural practices, storage periods and processing conditions, were used to build models including exploratory analysis, supervised classification and multivariate calibration. Fresh and freeze-dried samples presented similar fingerprint spectral variations due to processing. ATR-FTIR directly on fresh purees satisfactorily predicted textural properties such as particle average size and volume (RPD > 3.0), while freeze-drying improved assessment of chemical (RPD > 3.2) and rheological (RPD > 3.1) parameters using partial least-squares regression. The assessment of texture and macrocomponents of purees can be obtained with a limited sample preparation. For research applications because of a need of sample preparation, changes of cell wall composition during fruit processing could be assessed in relationship with pectin degradation.

A new application of NIR spectroscopy to describe and predict purees quality from the non-destructive apple measurements.

The potential of NIRS was investigated on both apples and purees to (i) examine factors involving quality variability (variety, agricultural practice, cold storage, puree mechanical refining level) and (ii) establish the link between quality traits before and after processing in order to predict the quality characteristics of purees from spectral information of raw apples. Apples and purees were well-classified at over 82% and 88% according to varieties and storage times respectively. The PLS models showed a good ability to estimate puree characteristics from spectra acquired on corresponding apples such as viscosity (R2 > 0.82), cell wall content (R2 > 0.81) and also dry matter (R2 > 0.83), soluble solids content (R2 > 0.80) and titratable acidity (R2 > 0.80). NIR technique should be a useful tool for industry insofar as it can give a reliable assessment of texture and taste of the final products based on the non-destructive fresh materials evaluation.

Use of Machine Learning and Infrared Spectra for Rheological Characterization and Application to the Apricot.

Fast advancement of machine learning methods and constant growth of the areas of application open up new horizons for large data management and processing. Among the various types of data available for analysis, the Fourier Transform InfraRed (FTIR) spectroscopy spectra are very challenging datasets to consider. In this study, machine learning is used to analyze and predict a rheological parameter: firmness. Various statistics have been gathered including both chemistry (such as ethylene, titrable acidity or sugars) and spectra values to visualize and analyze a dataset of 731 biological samples. Two-dimensional (2D) and three-dimensional (3D) principal component analyses (PCA) are used to evaluate their ability to discriminate for one parameter: firmness. Partial least squared regression (PLSR) modeling has been carried out to predict the rheological parameter using either sixteen physicochemical parameters or only the infrared spectra. We show that (i) the spectra alone allows good discrimination of the samples based on rheology, (ii) 3D-PCA allows comprehensive and informative visualization of the data, and (iii) that the rheological parameters are predicted accurately using a regression method such as PLSR; instead of using chemical parameters which are laborious to obtain, Mid-FTIR spectra gathering all physicochemical information could be used for efficient prediction of firmness. As a conclusion, rheological and chemical parameters allow good discrimination of the samples according to their firmness. However, using only the IR spectra leads to better results. A good predictive model was built for the prediction of the firmness of the fruit, and we reached a coefficient of determination R2 value of 0.90. This method outperforms a model based on physicochemical descriptors only. Such an approach could be very helpful to technologists and farmers.

Soil Photosynthetic Microbial Communities Mediate Aggregate Stability: Influence of Cropping Systems and Herbicide Use in an Agricultural Soil.

Edaphic cyanobacteria and algae have been extensively studied in dryland soils because they play key roles in the formation of biological soil crusts and the stabilization of soil surfaces. Yet, in temperate agricultural crop soils, little is understood about the functional significance of indigenous photosynthetic microbial communities for various soil processes. This study investigated how indigenous soil algae and cyanobacteria affected topsoil aggregate stability in cereal cropping systems. Topsoil aggregates from conventional and organic cropping systems were incubated in microcosms under dark or photoperiodic conditions with or without a treatment with an herbicide (isoproturon). Physicochemical parameters (bound exopolysaccharides, organic carbon) and microbial parameters (esterase activity, chlorophyll a biomass, and pigment profiles) were measured for incubated aggregates. Aggregate stability were analyzed on the basis of aggregate size distribution and the mean weight diameter (MWD) index, resulting from disaggregation tests. Soil photosynthetic microbial biomass (chl a) was strongly and positively correlated with aggregate stability indicators. The development of microalgae crusts in photoperiodic conditions induced a strong increase of the largest aggregates (>2 mm), as compared to dark conditions (up to 10.6 fold and 27.1 fold, in soil from organic and conventional cropping systems, respectively). Concomitantly, the MWD significantly increased by 2.4 fold and 4.2 fold, for soil from organic and conventional cropping systems. Soil microalgae may have operated directly via biochemical mechanisms, by producing exopolymeric matrices surrounding soil aggregates (bound exopolysaccharides: 0.39-0.45 µg C g-1 soil), and via biophysical mechanisms, where filamentous living microbiota enmeshed soil aggregates. In addition, they may have acted indirectly by stimulating heterotrophic microbial communities, as revealed by the positive effect of microalgal growth on total microbial activity. The herbicide treatment negatively impacted soil microalgal community, resulting in significant decreases of the MWD of the conventional soil aggregates (up to -42% of the value in light treatment). This study underscores that indigenous edaphic algae and cyanobacteria can promote aggregate formation, by forming photosynthetic microbiotic crusts, thus improving the structural stability of topsoil, in temperate croplands. However, the herbicide uses can impair the functional abilities of algal and cyanobacterial communities in agricultural soils. ORIGINALITY/SIGNIFICANCE: Edaphic algal and cyanobacterial communities are known to form photosynthetic microbial crusts in arid soils, where they drive key ecosystem functions. Although less well characterized, such communities are also transiently abundant in temperate and mesic cropped soils. This microcosm study investigated the communities' functional significance in topsoil aggregate formation and stabilization in two temperate cropping systems. Overall, our results showed that the development of indigenous microalgal communities under our experimental conditions drove higher structural stability in topsoil aggregates in temperate cropland soils. Also, herbicide use affected photosynthetic microbial communities and consequently impaired soil aggregation.

ATR-FTIR spectroscopy to determine cell wall composition: Application on a large diversity of fruits and vegetables.

Infrared spectroscopy coupled with multivariate analyses such as linear regressions was applied to assess the main cell wall components of a huge diversity of fruits and vegetables belonging to 29 plant species. The methodology was tested on the raw freeze-dried powders and on their corresponding AIS (Alcohol Insoluble Solids) dried by solvent exchanges. The most informative spectral region was 1750-1035 cm-1. Excellent predictions (determination coefficient R2 ≥ 0.9 and residual predictive deviation RPD ≥ 3.0) were obtained for AIS yields and for arabinose, total glucose, non-cellulosic glucose, total neutral sugars, methanol and starch contents in the AIS samples. The key wavenumbers were: 1740 cm-1 for total neutral sugars; 1075, 1440-1450, 1616 and 1740 cm-1 for pectins; 895, 1035-1041 and 1160-1163 cm-1 for cellulose and 1035-1041 cm-1 for lignin. Limitations of the reference methods to analyze cell wall components (biochemical assays, spectrophotometry, chromatography) affecting the prediction accuracy were also discussed.

Effect of cultivar and season on the robustness of PLS models for soluble solid content prediction in apricots using FT-NIRS.

FT-NIR models were developed for the non-destructive prediction of soluble solid content (SSC), titratable acidity (TA), firmness and weight of two commercially important apricot cultivars, "Hacihaliloglu" and "Kabaasi" from Turkey. The models constructed for SSC prediction gave good results. We could also establish a model which can be used for rough estimation of the apricot weight. However, it could not be possible to predict accurately TA and firmness of the apricots with FT-NIR spectroscopy. The study was further extended over 3 years for the SSC prediction. Validation of the both mono and multi-cultivar models showed that model performances may exhibit important variations across different harvest seasons. The robustness of the models was improved when the data of two or three seasons were used. It was concluded that in order to developed reliable SSC prediction models for apricots the spectral data should be collected over several harvest seasons.

Pear ripeness and tissue type impact procyanidin-cell wall interactions.

Procyanidins and cell walls were extracted from pear at ripe and overripe stages in order to investigate the impact of ripening stage on their association. Procyanidin composition and structure remained stable at the overripe stage. Mid Infrared Spectroscopy (MIR) discriminated cell wall-procyanidin complex from initial purified cell wall material (CWM). Interactions between procyanidins and CWM isolated from the whole flesh (FL), parenchyma cells (PC), stone cells (ST) and skin (SK) at ripe and overripe stage were characterized using UV-Vis spectrometry using Langmuir isotherm formulation and Isothermal Titration Microcalorimetry (ITC). The affinity between procyanidins and CWM decreased as follows: PC > FL > ST > SK. The proportion of bound procyanidins increased at the overripe stage for all CWM and the maximal saturation level was obtained for overripe FL and ST. ITC indicated that associations between pear cell walls and procyanidins involved hydrogen bonds and mainly hydrophobic interactions for overripe PC.

Impact of canning and storage on apricot carotenoids and polyphenols.

Apricot polyphenols and carotenoids were monitored after industrial and domestic cooking, and after 2months of storage for industrial processing. The main apricot polyphenols were flavan-3-ols, flavan-3-ol monomers and oligomers, with an average degree of polymerization between 4.7 and 10.7 and caffeoylquinic acids. Flavonols and anthocyanins were minor phenolic compounds. Upon processing procyanidins were retained in apricot tissue. Hydroxycinnamic acids, flavan-3-ol monomers, flavonols and anthocyanins leached in the syrup. Flavonol concentrations on per-can basis were significantly increased after processing. Industrial processing effects were higher than domestic cooking probably due to higher temperature and longer duration. After 2months of storage, among polyphenols only hydroxycinnamic acids, flavan-3-ol monomers and anthocyanins were reduced. Whichever the processing method, no significant reductions of total carotenoids were observed after processing. The cis-ß-carotene isomer was significantly increased after processing but with a lower extent in domestic cooking. Significant decreased in total carotenoid compounds occurred during storage.

Characterization of pectins extracted from pomegranate peel and their gelling properties.

The composition of pomegranate peel, the main by-product during pomegranate processing, and some of the characteristics of the water-soluble pectins were investigated. Four tunisian pomegranate peels were subjected to hot aqueous extractions (86°C, 80min, 20mM nitric acid). Pomegranate peels yielded between 6.8% and 10.1% pectins. The extracted pectins were low methylated and were characterized by the predominance of homogalacturonan regions. Principal component analysis applied on FT-IR spectral data in the region between 4000 and 650cm(-1) differentiated the samples according to their degree of methylation. At pH 3, in the presence of 0.7% pectin, all solutions showed a rapid gel formation with G'>G″. With decreasing temperature from 90°C to 10°C, G' increased to reach a plateau at 10°C. The variation in the pectin gel formation between varieties was attributed to difference in pectin characteristics particularly the hydrodynamic volume and the neutral sugar content.

Characterization of tissue specific differences in cell wall polysaccharides of ripe and overripe pear fruit.

Cell walls from flesh, parenchyma cells, stone cells and skin were isolated from ripe and overripe Pyrus communis L. cv "De Cloche" using the phenol-buffer method. Pear polysaccharides were solubilized from cell walls by sequential extractions with aqueous solutions of ammonium oxalate, Na2CO3, and increasing concentration of NaOH, to explore overripening impact. Cell walls were also differentiated using MIR spectral data. Stone cells contained high levels of xylose and lignin while parenchyma cells had high levels of glucose, uronic acids and arabinose. Sequential extractions revealed that pear pectins had highly branched rhamnogalacturonans and were extremely methylated. Xylans were the main hemicelluloseespecially for stone cells. Cellulose represented about half of all cell walls. This heterogeneous composition of pear affected differently cell wall evolutions and properties. Thus, overripening involved a decrease in arabinose and a loss of pectic side chains mostly from parenchyma cells. Changes in hemicellulose and cellulose were minor.

Cultivar and Year Rather than Agricultural Practices Affect Primary and Secondary Metabolites in Apple Fruit.

Many biotic and abiotic parameters affect the metabolites involved in the organoleptic and health value of fruits. It is therefore important to understand how the growers' decisions for cultivar and orchard management can affect the fruit composition. Practices, cultivars and/or year all might participate to determine fruit composition. To hierarchize these factors, fruit weight, dry matter, soluble solids contents, titratable acidity, individual sugars and organics acids, and phenolics were measured in three apple cultivars ('Ariane', 'Melrose' and 'Smoothee') managed under organic, low-input and conventional management. Apples were harvested at commercial maturity in the orchards of the cropping system experiment BioREco at INRA Gotheron (Drôme, 26) over the course of three years (2011, 2012 and 2013). The main factors affecting primary and secondary metabolites, in both apple skin and flesh, were by far the cultivar and the yearly conditions, while the management system had a very limited effect. When considering the three cultivars and the year 2011 to investigate the effect of the management system per se, only few compounds differed significantly between the three systems and in particular the total phenolic content did not differ significantly between systems. Finally, when considering orchards grown in the same pedoclimatic conditions and of the same age, instead of the usual organic vs. conventional comparison, the effect of the management system on the apple fruit quality (Fruit weight, dry matter, soluble solids content, titratable acidity, individual sugars, organic acids, and phenolics) was very limited to non-significant. The main factors of variation were the cultivar and the year of cropping rather than the cropping system. More generally, as each management system (e.g. conventional, organic…) encompasses a great variability of practices, this highlights the importance of accurately documenting orchard practices and design beside the generic type of management in such studies.

Comparison of NIRS approach for prediction of internal quality traits in three fruit species.

NIR Spectroscopy ability was investigated to assess the fruit structure effect (passion fruit, tomato and apricot) on prediction performance of soluble solids content (SSC) and titratable acidity (TA). Relationships between spectral wavelengths and SSC and TA were evaluated through the application of chemometric techniques based on partial least squares (PLS). Good prediction performance was obtained for apricot with correlation coefficients of 0.93 and 0.95 for SSC and TA and root mean square errors of prediction (RMSEP%) of 3.3% and 14.2%, respectively. For the passion fruit and tomato, the prediction models were not satisfactorily accurate due to the high RMSEP. Results showed that NIR technology can be used to evaluate apricot internal quality, however, it was not appropriate to evaluate internal quality in fruits with thick skin, (passion fruit), and/or heterogeneous internal structure (tomato).

Determination of the composition in sugars and organic acids in peach using mid infrared spectroscopy: comparison of prediction results according to data sets and different reference methods.

The prediction of internal quality properties, such as sweetness and acidity, in peach fruit by mid infrared spectroscopy is of interest for rapid determination. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) was tested here on two populations of peach fruits issued from contrasting genitors providing a large phenotypic variability. Over two successive years, 284 samples in 2006 and 483 samples in 2007 were characterized for soluble solids content (SSC), titratable acidity (TA), glucose, fructose, sucrose, malic acid, and citric acid contents. Sugar and organic acid composition were determined by three methods: colorimetric enzymatic measurements (ENZ), high-performance liquid chromatography (HPLC), or proton NMR spectroscopy ((1)H NMR), depending on the samples. For all samples, fruit homogenates were analyzed in ATR-FTIR using the same methodology and the same spectrometer. The objective here was to evaluate the effect of reference methods on the prediction performance. The best results were generally observed for SSC and TA, the percentage of the root-mean-square error of cross validation (RMSECV%) ranging respectively between 5.8% and 8.7% and between 5.9% and 8.0%, depending on the samples. For individual sugars and organic acids, the best correlations were obtained between ATR-FTIR data and ENZ reference data followed by HPLC and (1)H NMR ones.

Pink discoloration of canned pears: role of procyanidin chemical depolymerization and procyanidin/cell wall interactions.

After canning, pear pieces turn occasionally from whitish-beige to pink. Conditions were set up to obtain this discoloration systematically and investigate its mechanism. Canned pears showed a significantly lower L* coordinate compared with fresh pears, and the L* coordinate of canned pears decreased with decreasing pH. The values of the a* and b* coordinates increased significantly after processing, the increase being greater for the more acidic pH values, with corresponding redder colors. After canning, polyphenol concentrations decreased significantly, mainly due to loss of procyanidins. This supported the hypothesis of conversion of procyanidins to anthocyanin-like compounds. However, no soluble product was detected at 520 nm, the characteristic wavelength of anthocyanins. When purified procyanidins were treated at 95 °C at three different pH values (2.7, 3.3, and 4.0), procyanidin concentrations decreased after treatment, the more so as the pH was lower, and a pinkish color also appeared, attributed to tannin-anthocyanidin pigment. The pink color was bound to cell walls. Extraction of the neoformed pink entities was attempted by successive solvent extractions followed by cell wall degrading enzymes. The pink color persisted in the residues, and canned pears gave significantly higher amounts of residues after solvent and enzyme treatments than fresh pears. Procyanidins were the entities responsible for the appearance of pink discoloration. However, it seems that this pink discoloration also involved the formation of strong, probably covalent, bonds to the cell wall.

Home conservation strategies for tomato (Solanum lycopersicum): storage temperature vs. duration--is there a compromise for better aroma preservation?

Expression of dissatisfaction with tomato aroma prompted us to lead this study on the impact of domestic storage conditions on volatile compounds. Two storage modalities (20 and 4°C) and two cultivars (Levovil and LCx) were used. Volatile compounds were analysed by gas chromatography-mass spectrometry detection after accelerated solvent extraction. Physical characteristics, lipoxygenase activity, hydroperoxide lyase activity; linoleic acid and linolenic acid were monitored. Storing tomatoes at 4°C induced a drastic loss in volatiles, whatever their biosynthetic origin. After 30 days at 4°C, the concentration of volatiles had decreased by 66%. Reconditioning for 24 h at 20°C was able to recover some aroma production after up to 6 days storage at 4°C. Volatile degradation products arising from carotenoids and amino acids increased when tomatoes were kept at 20°C, while lipid degradation products did not vary. Storing tomatoes at fridge temperature, even for short durations, was detrimental for their aroma. This should be taken into account to formulate practical advice for consumers.