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Podolian cattle is an autochthonous breed well adapted to the harsh semi-arid environments of the Southern Italy regions; the extensive rearing system used for these indigenous animals is based on grazing on spontaneous pastures, such as grasslands or wood pastures These grazing systems respect animal welfare and enrich animal products with characteristics closely related to the feeding system and the farming environment. The aim of the present study was to characterize the nutritional value of a forage crop and a wood-pasture and to evaluate the effects of grazing by Podolian young bulls on the performances and meat quality in relation to the age at slaughter (14 or 18 months) and to the ageing time of meat (3, 9 or 14 days). The metabolizable energy and the gas production were greater in April and June for both pasture systems. Young bulls raised on the grassland showed greater slaughter weights ( p  < 0.05) as compared to those fed on the woodland system, at both the slaughtering ages. The Warner Bratzler Shear (WBS) force values for raw and cooked meat were not influenced by the pasture system but they significantly ( p  < 0.01) decreased in relation to the ageing time in all the groups. Ageing markedly ( p  < 0.05) increased the malondialdehyde (MDA) concentration from 3 to 14 days of storage, regardless of the pasture system and the slaughtering age. The n-6/n-3 polyunsaturated fatty acid ratio of meat was markedly lower in grassland animals, regardless of the age of slaughter. In conclusion, 18 months old grassland beef showed better performances and yield of meat cuts. Ageing for 9 days positively affected meat WBS without increasing MDA concentration.

Hemp seed cake (HSC) ( Cannabis sativa L.) is a rich source of polyunsaturated fatty acids, high-quality proteins and essential amino acids. The aim of this study was to evaluate the effects of dietary inclusion of HSC on growth performance, meat quality traits, fatty acids profile and oxidative status, and intestinal morphology in slow-growing broilers. A total of 180 male slow-growing broilers were randomly assigned to one of three dietary treatments containing different levels of HSC: 0 (HSC0), 5 (HSC5) or 10% (HSC10). Birds were slaughtered at 49 days of age: breast and thigh muscles were analysed and duodenum mucosa histomorphological features were evaluated. Regardless the level of HSC inclusion, no differences among groups were found for performance and meat quality traits. The thigh and breast fatty acid profile were significantly improved in both HSC groups, with an increase of the long chain fatty acids of n-3 series and decrease of n-6/n-3 ratio. The HSC diets lowered the MDA concentration and lipid hydroperoxides in breast meat. Histomorphometrical analysis revealed a significant increase in villus height, surface area and villus/crypt ratio, with a decrease of crypt depth, suggesting that dietary supplementation with HSC may boost intestinal health status in poultry. In conclusion, dietary HSC did not affect performance, carcass traits and meat quality, while it positively influenced the lipid profile of meat, and improved the oxidative status and gut health, thus representing a valuable and sustainable alternative ingredient in broiler diet.

This paper proposes the use of modified biochar, derived from Sawdust (SD) biomass using sonication (SSDB) and Ozonation (OSDB) processes, as an additive for biogas production from green algae Cheatomorpha linum (C. linum) either individually or co-digested with natural diet for rotifer culture (S. parkel). Brunauer-Emmett-Teller (BET), Fourier-Transform Infrared (FTIR), thermal-gravimetric (TGA), and X-ray diffraction (XRD) analyses were used to characterize the generated biochar. Ultrasound (US) specific energy, dose, intensity and dissolved ozone (O 3 ) concentration were also calculated. FTIR analyses proved the capability of US and ozonation treatment of biochar to enhance the biogas production process. The kinetic model proposed fits successfully with the data of the experimental work and the modified Gompertz models that had the maximum R 2 value of 0.993 for 150 mg/L of OSDB. The results of this work confirmed the significant impact of US and ozonation processes on the use of biochar as an additive in biogas production. The highest biogas outputs 1059 mL/g VS and 1054 mL/g VS) were achieved when 50 mg of SSDB and 150 mg of OSDB were added to C. linum co-digested with S. parkle., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

This work demonstrates the preparation of high-surface-area activated carbon (AC) from Pisum sativum pods using ZnCl 2 and KOH as activating agents. The influence of CO 2 and N 2 gases during the carbonization process on the porosity of AC were studied. The highest specific surface area of AC was estimated at 1300 to 1500 m 2 /g, which presented characteristics of microporous materials. SEM micrographs revealed that chemical activation using an impregnation reagent ZnCl 2 increases the porosity of the AC, which in turn leads to an increase in the surface area, and the SEM image showed that particle size diameter ranged between 48.88 and 69.95 nm. The performance of prepared AC for adsorption of Acid Orange 7 (AO7) dye was tested. The results showed that the adsorption percentage by AC (2.5 g/L) was equal to 94.76% after just 15 min, and the percentage of removal increased to be ~100% after 60 min. The maximum adsorption capacity was 473.93 mg g -1 . A Langmuir model (LM) shows the best-fitted equilibrium isotherm, and the kinetic data fitted better to the pseudo-second-order and Film diffusion models. The removal of AO7 dye using AC from Pisum sativum pods was optimized using a response factor model (RSM), and the results were reported.

For the estimation of the soil organic carbon stocks, bulk density (BD) is a fundamental parameter but measured data are usually not available especially when dealing with legacy soil data. It is possible to estimate BD by applying pedotransfer function (PTF). We applied different estimation methods with the aim to define a suitable PTF for BD of arable land for the Mediterranean Basin, which has peculiar climate features that may influence the soil carbon sequestration. To improve the existing BD estimation methods, we used a set of public climatic and topographic data along with the soil texture and organic carbon data. The present work consisted of the following steps: i) development of three PTFs models separately for top (0-0.4 m) and subsoil (0.4-1.2 m), ii) a 10-fold cross-validation, iii) model transferability using an external dataset derived from published data. The development of the new PTFs was based on the training dataset consisting of World Soil Information Service (WoSIS) soil profile data, climatic data from WorldClim at 1 km spatial resolution and Shuttle Radar Topography Mission (SRTM) digital elevation model at 30 m spatial resolution. The three PTFs models were developed using: Multiple Linear Regression stepwise (MLR-S), Multiple Linear Regression backward stepwise (MLR-BS), and Artificial Neural Network (ANN). The predictions of the newly developed PTFs were compared with the BD calculated using the PTF proposed by Manrique and Jones (MJ) and the modelled BD derived from the global SoilGrids dataset. For the topsoil training dataset (N = 129), MLR-S, MLR-BS and ANN had a R 2 0.35, 0.58 and 0.86, respectively. For the model transferability, the three PTFs applied to the external topsoil dataset (N = 59), achieved R 2 values of 0.06, 0.03 and 0.41. For the subsoil training dataset (N = 180), MLR-S, MLR-BS and ANN the R 2 values were 0.36, 0.46 and 0.83, respectively. When applied to the external subsoil dataset (N = 29), the R 2 values were 0.05, 0.06 and 0.41. The cross-validation for both top and subsoil dataset, resulted in an intermediate performance compared to calibration and validation with the external dataset. The new ANN PTF outperformed MLR-S, MLR-BS, MJ and SoilGrids approaches for estimating BD. Further improvements may be achieved by additionally considering the time of sampling, agricultural soil management and cultivation practices in predictive models., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021. Published by Elsevier B.V.)

Ylang-ylang (YY) essential oil (EO) is distilled from the fresh-mature flowers of the Annonaceae family tropical tree Cananga odorata [Lam.] Hook. f. & Thomson, and is widely used in perfume and cosmetic industries for its fragrant character. Herein, two different metabolomic profiles obtained using high-performance thin-layer chromatography (HPTLC), applying different stains, namely 2,2-diphenyl-1-picrylhydrazyl (DPPH·) and p-anisaldehyde, were used for discrimination of 52 YY samples across geographical origins and distillation grades. The first profile is developed using the DPPH· stain based on the radical scavenging activity (RSA) of YY EOs. Results of the HPTLC-DPPH· assay confirmed that RSA of YY EOs is in proportion to the length of distillation times. Major components contributing to the RSA of YY EOs were tentatively identified as germacrene D and α-farnesene, eugenol and linalool, by gas chromatography-mass spectrometry (GC-MS) and GC-flame ionisation detector (GC-FID). The second profile was developed using the general-purpose p-anisaldehyde stain based on the general chemical composition of YY EOs. Untargeted metabolomic discrimination of YY EOs from different geographical origins was performed based on the HPTLC-p-anisaldehyde profiles, followed by principal component analysis (PCA). A discrimination and prediction model for identification of YY distillation grade was developed using PCA and partial least squares regression (PLS) based on binned HPTLC-ultraviolet (254 nm) profiles, which was successfully applied to distillation grade determination of blended YY Complete EOs., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The research studied the effects of dietary supplementation with Camelina sativa fresh forage on the chemical and fatty acid composition of milk and Caciotta cheese, and its sensory properties. Twenty Ionica goats were randomly assigned to the following two groups ( n = 10): the control received a traditional forage mixture ( Avena sativa , 70%; Vicia sativa , 20%; Trifolium spp., 10%), while the experimental group was given Camelina sativa fresh forage (CAM). All of the dams grazed on pasture and received a commercial feed (500 g/head/day) at housing. The milk from the CAM group showed a higher ( p < 0.05) content of dry matter, fat, lactose and concentrations of C6:0, C11:0, C14:0, C18:2 n -6, CLA and PUFA, while lower ( p < 0.05) amounts of C12:0, C18:0 and saturated long chain FA (SLCFA). The Caciotta cheese from the CAM group showed a greater ( p < 0.05) content of n -6 FA and n -6/ n -3 ratio, although close to four, thus resulting adequate under the nutritional point of view. The overall liking, odour, taste, hardness, solubility and "goaty" flavour were better ( p < 0.05) in the CAM cheeses. Further investigation would be advisable in order to evaluate the effect of feeding Camelina forage obtained from different phenological stages, and the application of ensiling techniques.

Quality control of essential oil blends and the discovery of potential adulterations and product fraud is a significant challenge within the natural oil and perfume industry. In this research, total chromatogram average mass spectra (TCAMS), created from the GC-MS three-way raw data, were employed for the characterisation of complex samples of perfumes and essential oil blends. A multivariate approach for curve resolution was used to resolve the TCAMS of pure essential oils within such perfume and essential oil blends. Resolved TCAMS, in combination with unsupervised pattern recognition approaches revealed the distillation grade and origin of used ylang-ylang oils in perfume mixtures. TCAMS resolved from the essential oil blends were used with a supervised machine learning classification model to identify oils, used in creating the blends. Quantification was performed using a multivariate curve resolution approach, resulting in relative errors of prediction lower than 17.84% with root mean square errors of prediction smaller than 3.43., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Analyses of the complex essential oil samples using gas chromatography hyphenated with mass spectrometry (GC-MS) generate large three-way data arrays. Processing such large data sets and extracting meaningful information in the metabolic studies of natural products requires application of multivariate statistical techniques (MSTs). From the GC-MS raw data several different input data sets for the MSTs can be created, including total chromatogram average mass spectra (TCAMS), segmented average mass spectra (SAMS) and chemical composition. Herein, we compared the performance of MSTs on average mass spectrum based data sets, TCAMS and SAMS, against chemical composition and attenuated total reflectance - Fourier transformation infrared (ATR-FTIR) spectroscopy in the evaluation of quality of ylang-ylang essential oils, based on their grade, geographical origin and chemical composition, using principal component analysis (PCA), partial least squares regression (PLS) and discriminatory analysis (PLS-DA). PCA based on TCAMS, SAMS and chemical composition showed clear trends amongst the samples based on increase in grade (distillation time). PLS-DA applied to TCAMS, SAMS and ATR-FTIR discriminated between all geographical origins. Predicted relative abundances of the 18 most important compounds, using PLS regression models on TCAMS, SAMS and ATR-FTIR, were successfully applied to ylang-ylang essential oil quality assessment based on comparison with the ISO 3063:2004 standard, where the SAMS data set showed superior performance, compared to other data sets., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier B.V.)

Differences in chemical profiles of various essential oils (EOs) come from the fact that each plant species and chemotype has a distinctive secondary metabolism. Therefore, these differences can be used as the chemical markers for EO classification and determination of their quality. Herein, the Random Forests (RF) machine learning algorithm was applied to the classification of 20 different EOs. From three-way raw gas chromatography - mass spectra data, total chromatogram average mass spectra (TCAMS) and segment average mass spectra (SAMS) were created. TCAMS was generated by averaging response of each m/z over the whole chromatogram and SAMS by averaging the response of each fragment across a certain time segment within the chromatogram. The RF model was applied to the two data sets and optimised through the evaluation of pre-processed data, number of trees, and number of variables used in each node split. The performance of the model was evaluated through a cross-validation process, repeated 50 times by dividing the whole sample set into training and validation subsets. The calculated average out-of-bag error (OOBE), over 50 different training TCAMS data sets was 3.22 ± 1.29%, while for SAMS it was found to be 2.28 ± 1.33%. The minimal number of variables necessary for EO classification was determined by a nested cross-validation process. The amount of reduced variables in each step was 10%. It was shown that the TCAMS data set with 6 variables had similar prediction power as the SAMS with 30 variables. OOBE for classification of 20 EOs was 2.89 ± 1.44% and 3.70 ± 1.73%, for TCAMS and SAMS, respectively. Proximity between samples was used to evaluate their qualities. Samples with greater intra-class proximity had good similarity, while the lower ones indicated greater variations in the chemical profiles. The SAMS data set showed superior potential for quality assurance, compared with TCAMS., (Copyright © 2019 Elsevier B.V. All rights reserved.)

This study assesses whether the distinct altitudinal cline in leaf morphology (decreased leaf width and length with increased altitude) in Tasmanian mountain pepper ( Tasmannia lanceolata ) is associated with changes in the leaf chemistry of wild populations from different ecological landscapes and altitudes. The presence of distinct pungent drimane sesquiterpenoid chemotypes was identified: subalpine woodland and wet sclerophyll forest chemotypes. Isolation studies and analysis of extracts revealed that wet sclerophyll forest T. lanceolata populations featured polygodial as the principal terpenoid, with profiles similar to the commercial cultivars sampled. In contrast, the subalpine woodland populations contained the drimane sesquiterpenoids 1β-acetoxy-9-deoxyisomuzigadial and 3β-acetoxydrimenin and the conspicuous absence of the pungent principle polygodial.

Multimaterial 3D printing facilitates the rapid production of complex devices with integrated materials of varying properties and functionality. Herein, multimaterial fused deposition modeling (MM-FDM) 3D printing was applied to the fabrication of low-cost passive sampler devices with integrated porous membranes. Using MM-FDM 3D printing, the device body was produced using black polylactic acid, with Poro-Lay Lay-Felt filament used for the printing of the integrated porous membranes (rubber-elastomeric polymer, porous after removal of a water-soluble poly(vinyl alcohol) component). The resulting device consisted of two interlocking circular frames, each containing the integrated membrane, which could be efficiently sealed together without the need for additional O-rings, and prevented loss of enclosed microparticulate sorbent. Scanning electron microscopy (SEM) analysis of the purified composite filament confirmed the porous properties of the material, an average pore size of ∼30 nm. The printed passive samplers with various membrane thicknesses, including 0.5, 1.0, and 1.5 mm, were evaluated for their ability to facilitate the extraction of atrazine as the model solute onto the internal sorbent, under standard conditions. Gas chromatography-mass spectrometry was used to determine the uptake of atrazine by the device from standard water samples and also to evaluate any chemical leaching from the printed materials. The sampler with 0.5 mm thick membrane showed the best performance with 87% depletion and a sampling rate of 0.19 Ld -1 ( n = 3, % RSD = 0.59). The results obtained using these printed sampling devices with integrated membranes were in close agreement to devices fitted with a standard poly(ether sulfone) membrane.

Conservative agriculture includes a range of management strategies with low energy inputs such as no-tillage, minimum tillage, and low application of fertilizers. Weed flora in arable fields is strictly affected by agronomic practices such as tillage and fertilization management. This study was conducted seven years after the beginning of a long-term-durum wheat⁻faba bean-rotation. It analyzes the combined effects on the soil seed bank of three different tillage systems (conservative, reduced, and conventional tillage) and two levels of nitrogen fertilization. The effects were investigated both using stepwise discriminant analysis and analysis of variance in order to find statistical differences among main factors and their interactions. The seed bank of Conyza canadensis , Papaver rhoeas , Solanum nigrum , Fallopia convolvulus , and Fumaria officinalis was higher in conservative or reduced tillage plots. The magnitude of the response to nitrogen supply varied among weed species. Conyza canadensis seemed to be favored by low nitrogen supply, whereas Sinapis arvensis by higher doses of nitrogen. Anagallis arvensis showed the lowest seed bank in conventionally tilled plots, without distinction of nitrogen supply. The results suggest that different tillage systems and, to a lesser extent, different nitrogen supply, produce changes in the seed bank size and composition, along the soil profile.

An investigation of the previously unexamined ancient Tasmanian clone Lomatia tasmanica W. M. Curtis (Proteaceae) and two other endemic species Lomatia tinctoria R. Br. and Lomatia polymorpha (Labill.) R. Br. was undertaken. This represents the first extensive natural products study in which individual phytochemical components have been isolated and identified from these three Lomatia species. Extraction of L. tasmanica leaves provided the naphthoquinone juglone (0.34% w/w), and n-alkanes nonacosane and heptacosane (0.30% w/w combined). L. polymorpha afforded the flavonoid glycosides dihydroquercetin 3-O-β-D-xyloside (0.22% w/w) and quercetin 3-O-β-d-glucose (0.14% w/w), as well as the naphthalene glucoside 1,4,8-trihydroxynaphthalene-1-O-β-d-glucose (0.04% w/w) and 4-O-p-coumaroyl-d-glucose (0.03% w/w). In addition, both L. polymorpha and L. tinctoria contained juglone (0.32% w/w and 0.58% w/w, respectively). L. polymorpha provided tetracosan-1-ol, hexacosan-1-ol and octacosan-1-ol (0.07% w/w combined), while L. tinctoria gave nonacosane (0.13% w/w). Analysis of three individual specimens from each of the three species demonstrated consistency in the respective phytochemical profiles of these populations and tentatively suggests limited intraspecific variation., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Comprehensive two-dimensional gas chromatography with quadrupole accurate mass time-of-flight mass spectrometry (GC×GC-Q-TOFMS) is employed to profile Humulus lupulus L. (hop) essential oils. Comparison of characterised essential oils allows discrimination among chemotypes. Experimental and commercial hop genotypes displayed distinguishable chemotypic patterns among the volatile secondary metabolites making up their essential oils. In total, 210-306 unique compounds were detected (depending on specific genotype), with 99 of these compounds either positively or tentatively identified. Identified volatile secondary metabolites were grouped into esters, monoterpene hydrocarbons, oxygenated monoterpenes, sesquiterpene hydrocarbons, oxygenated sesquiterpenes and ketones. Terpenoids were the dominant chemical families across all hop genotypes analysed, representing between 67% and 90% of the total ion count. The multidimensional chromatographic profiles of hop essential oils are extremely information-rich, making GC×GC-Q-TOFMS useful for fast screening of new hybrid hop genotypes, and therefore informing breeding strategies to derive new commercial hop cultivars for the development of distinctive and desirable beers., (Copyright © 2017 Elsevier B.V. All rights reserved.)

We introduce an information rich analytical approach called parallel comprehensive two-dimensional gas chromatography (2GC×2GC). This parallel chromatography approach splits injected samples into two independent two-dimensional column ensembles and provides two GC×GC separations by using contra-directional thermal modulation. The first-dimension ( 1 D) and second-dimension ( 2 D) columns are connected using planar three-port microchannel devices, which are supplied with supplementary flow via two pressure controller modules. Precise carrier gas flow control at the junction of the 1 D and 2 D columns permits independent control of flow conditions in each separation column. The 2GC×2GC approach provides two entirely independent GC×GC separations for each injection. Analysis of hop (Humulus lupulus L.) essential oils is used to demonstrate the capability of the approach. The analytical performance of each GC×GC separation in the 2GC×2GC experiment is comparable to individual GC×GC separation with matching column configurations. The peak capacity of 2GC×2GC is about 2 times than that of single GC×GC system. The dual 2D chromatograms produced by this single detector system provide complementary separations and additional identification information by harnessing different selectivity provided by the four separation columns., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Through optimization of the printing process and orientation, a suitably developed surface area has been realized upon a 3D printed polymer substrate to facilitate chromatographic separations in a planar configuration. Using an Objet Eden 260VS 3D printer, polymer thin layer chromatography platforms were directly fabricated without any additional surface functionalization and successfully applied to the separation of various dye and protein mixtures. The print material was characterized using gas chromatography coupled to mass spectrometry and spectroscopic techniques such as infrared and Raman. Preliminary studies included the separation of colored dyes, whereby the separation performance could be visualized optically. Subsequent separations were achieved using fluorescent dyes and fluorescently tagged proteins. The separation of proteins was affected by differences in the isoelectric point (pI) and the ion exchange properties of the printed substrate. The simple chromatographic separations are the first achieved using an unmodified 3D printed stationary phase.

We describe a new process for preparing porous solid phase microextraction (SPME) coatings by the sputtering of silicon onto silica fibers. The microstructure of these coatings is a function of the substrate geometry and mean free path of the silicon atoms, and the coating thickness is controlled by the sputtering time. Sputtered silicon structures on silica fibers were treated with piranha solution (a mixture of concd H2SO4 and 30% H2O2) to increase the concentration of silanol groups on their surfaces, and the nanostructures were silanized with octadecyldimethylmethoxysilane in the gas phase. The attachment of this hydrophobic ligand was confirmed by X-ray photoelectron spectroscopy and contact angle goniometry on model, planar silicon substrates. Sputtered silicon coatings adhered strongly to their surfaces, as they were able to pass the Scotch tape adhesion test. The extraction time and temperature for headspace extraction of mixtures of alkanes and alcohols on the sputtered fibers were optimized (5 min and 40 °C), and the extraction performances of SPME fibers with 1.0 or 2.0 μm of sputtered silicon were compared to those from a commercial 7 μm poly(dimethylsiloxane) (PDMS) fiber. For mixtures of alcohols, aldehydes, amines, and esters, the 2.0 μm sputtered silicon fiber yielded signals that were 3-9, 3-5, 2.5-4.5, and 1.5-2 times higher, respectively, than those of the commercial fiber. For the heavier alkanes (undecane-hexadecane), the 2.0 μm sputtered fiber yielded signals that were approximately 1.0-1.5 times higher than the commercial fiber. The sputtered fibers extracted low molecular weight analytes that were not detectable with the commercial fiber. The selectivity of the sputtered fibers appears to favor analytes that have both a hydrophobic component and hydrogen-bonding capabilities. No detectable carryover between runs was noted for the sputtered fibers. The repeatability (RSD%) for a fiber (n = 3) was less than 10% for all analytes tested, and the between-fiber reproducibility (n = 3) was 0-15%, generally 5-10%, for all analytes tested. The repeatabilities of our sputtered fibers and the commercial 7 μm PDMS fiber are essentially the same. Fibers could be used for at least 300 extractions without loss of performance. More than 50 compounds were identified in a gas chromatography-mass spectrometry headspace analysis of a real world botanical sample with the 2.0 μm fiber.

This study aimed at assessing the dynamics of lactic acid bacteria and other Firmicutes associated with durum wheat organs and processed products. 16S rRNA gene-based high-throughput sequencing showed that Lactobacillus, Streptococcus, Enterococcus, and Lactococcus were the main epiphytic and endophytic genera among lactic acid bacteria. Bacillus, Exiguobacterium, Paenibacillus, and Staphylococcus completed the picture of the core genus microbiome. The relative abundance of each lactic acid bacterium genus was affected by cultivars, phenological stages, other Firmicutes genera, environmental temperature, and water activity (aw) of plant organs. Lactobacilli, showing the highest sensitivity to aw, markedly decreased during milk development (Odisseo) and physiological maturity (Saragolla). At these stages, Lactobacillus was mainly replaced by Streptococcus, Lactococcus, and Enterococcus. However, a key sourdough species, Lactobacillus plantarum, was associated with plant organs during the life cycle of Odisseo and Saragolla wheat. The composition of the sourdough microbiota and the overall quality of leavened baked goods are also determined throughout the phenological stages of wheat cultivation, with variations depending on environmental and agronomic factors., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)