Evaluation of spontaneous fermentation impact on the physicochemical properties and sensory profile of green and roasted arabica coffee by digital technologies.

There is a growing demand for specialty coffee with more pleasant and uniform sensory perception. Wet fermentation could modulate and confer additional aroma notes to final roasted coffee brew. This study aimed to assess differences in volatile compounds and the intensities of sensory descriptors between unfermented and spontaneously fermented coffee using digital technologies. Fermented (F) and unfermented (UF) coffee samples, harvested from two Australia local farms Mountain Top Estate (T) and Kahawa Estate (K), with four roasting levels (green, light-, medium-, and dark-) were analysed using near-infrared spectrometry (NIR), and a low-cost electronic nose (e-nose) along with some ground truth measurements such as headspace/gas chromatography-mass spectrometry (HS-SPME-GC-MS), and quantitative descriptive analysis (QDA ®). Regression machine learning (ML) modelling based on artificial neural networks (ANN) was conducted to predict volatile aromatic compounds and intensity of sensory descriptors using NIR and e-nose data as inputs. Green fermented coffee had significant perception of hay aroma and flavor. Roasted fermented coffee had higher intensities of coffee liquid color, crema height and color, aftertaste, aroma and flavor of dark chocolate and roasted, and butter flavor (p < 0.05). According to GC-MS detection, volatile aromatic compounds, including methylpyrazine, 2-ethyl-5-methylpyrazine, and 2-ethyl-6-methylpyrazine, were observed to discriminate fermented and unfermented roasted coffee. The four ML models developed using the NIR absorbance values and e-nose measurements as inputs were highly accurate in predicting (i) the peak area of volatile aromatic compounds (Model 1, R = 0.98; Model 3, R = 0.87) and (ii) intensities of sensory descriptors (Model 2 and Model 4; R = 0.91), respectively. The proposed efficient, reliable, and affordable method may potentially be used in the coffee industry and smallholders in the differentiation and development of specialty coffee, as well as in process monitoring and sensory quality assurance.

Novel insights into the mechanism(s) of silicon-induced drought stress tolerance in lentil plants revealed by RNA sequencing analysis.

BACKGROUND: Lentil is an essential cool-season food legume that offers several benefits in human nutrition and cropping systems. Drought stress is the major environmental constraint affecting lentil plants' growth and productivity by altering various morphological, physiological, and biochemical traits. Our previous research provided physiological and biochemical evidence showing the role of silicon (Si) in alleviating drought stress in lentil plants, while the molecular mechanisms are still unidentified. Understanding the molecular mechanisms of Si-mediated drought stress tolerance can provide fundamental information to enhance our knowledge of essential gene functions and pathways modulated by Si during drought stress in plants. Thus, the present study compared the transcriptomic characteristics of two lentil genotypes (drought tolerant-ILL6002; drought sensitive-ILL7537) under drought stress and investigated the gene expression in response to Si supplementation using high-throughput RNA sequencing. RESULTS: This study identified 7164 and 5576 differentially expressed genes (DEGs) from drought-stressed lentil genotypes (ILL 6002 and ILL 7537, respectively), with Si treatment. RNA sequencing results showed that Si supplementation could alter the expression of genes related to photosynthesis, osmoprotection, antioxidant systems and signal transduction in both genotypes under drought stress. Furthermore, these DEGs from both genotypes were found to be associated with the metabolism of carbohydrates, lipids and proteins. The identified DEGs were also linked to cell wall biosynthesis and vasculature development. Results suggested that Si modulated the dynamics of biosynthesis of alkaloids and flavonoids and their metabolism in drought-stressed lentil genotypes. Drought-recovery-related DEGs identified from both genotypes validated the role of Si as a drought stress alleviator. This study identified different possible defense-related responses mediated by Si in response to drought stress in lentil plants including cellular redox homeostasis by reactive oxygen species (ROS), cell wall reinforcement by the deposition of cellulose, lignin, xyloglucan, chitin and xylan, secondary metabolites production, osmotic adjustment and stomatal closure. CONCLUSION: Overall, the results suggested that a coordinated interplay between various metabolic pathways is required for Si to induce drought tolerance. This study identified potential genes and different defence mechanisms involved in Si-induced drought stress tolerance in lentil plants. Si supplementation altered various metabolic functions like photosynthesis, antioxidant defence system, osmotic balance, hormonal biosynthesis, signalling, amino acid biosynthesis and metabolism of carbohydrates and lipids under drought stress. These novel findings validated the role of Si in drought stress mitigation and have also provided an opportunity to enhance our understanding at the genomic level of Si's role in alleviating drought stress in plants.

Silicon modulates nitro-oxidative homeostasis along with the antioxidant metabolism to promote drought stress tolerance in lentil plants.

Lentil is the fifth most important grain legume growing in arid/semi-arid regions of the world. Drought is one of the major constraints leading up to 50% of production losses just in lentil. Application of silicon (Si) has been shown to be a promising solution to improve drought tolerance; however, the biochemical mechanisms and interactions involved are not fully understood, especially in legumes. This study was designed to evaluate the effects of Si on drought stress tolerance of lentil genotypes. Seven lentil genotypes with different drought tolerance levels (tolerant, moderately tolerant and sensitive) were subjected to moderate and severe drought stress at the onset of the reproductive stage. Results showed that different drought stress treatments significantly decreased the above ground biomass, water status and the concentration of chlorophyll pigments, whereas Si supplementation of drought stressed lentil genotypes significantly improved the same traits, irrespective of their drought tolerant levels. On the other hand, Si effect on osmoregulation leads to a decline in the membrane damage and osmolytes (proline and glycine betaine) concentration in drought-stressed lentil. Application of Si to drought-stressed lentil plants significantly maintained the nitro-oxidative homeostasis by balancing the concentrations of reactive oxygen/nitrogen species, superoxide anion, hydrogen peroxide and nitrous oxide, thereby reducing the oxidative damage caused due to drought stress. Furthermore, Si supplementation also stimulated the efficiency of the glutathione (GSH)-ascorbate (ASC) cycle by increasing the concentrations of GSH and ASC as well as the activities of antioxidant enzymes like ascorbate peroxidase, guaiacol peroxidase, catalase, superoxide dismutase, glutathione reductase, dehydro-ascorbate reductase and nitrate reductase for better protection of cell membranes from reactive oxygen species. Although Si showed the same regulatory mechanisms in all the studied genotypes to protect lentil plants from moderate and severe drought stress, the defensive role of Si against drought stress was more conspicuous in drought sensitive genotypes than in the tolerant ones. Thus, this study suggests the protective role of Si on drought-stressed lentil genotypes through the modulation of nitro-oxidative homeostasis and antioxidant defence responses.

Silicon supplementation improves the nutritional and sensory characteristics of lentil seeds obtained from drought-stressed plants.

BACKGROUND: Lentil is an important nutritionally rich pulse crop in the world. Despite having a prominent role in human health and nutrition, it is very unfortunate that global lentil production is adversely limited by drought stress, causing a huge decline in yield and productivity. Drought stress can also affect the nutritional profile of seeds. Silicon (Si) is an essential element for plants and a general component of the human diet found mainly in plant-based foods. This study investigated the effects of Si on nutritional and sensory properties of seeds obtained from lentil plants grown in an Si-supplied drought-stressed environment. RESULTS: Significant enhancements in the concentration of nutrients (protein, carbohydrate, dietary fibre, Si) and antioxidants (ascorbate, phenol, flavonoids, total antioxidants) were found in seeds. Significant reductions in antinutrients (trypsin inhibitor, phytic acid, tannin) were also recorded. A novel sensory analysis was implemented in this study to evaluate the unconscious and conscious responses of consumers. Biometrics were integrated with a traditional sensory questionnaire to gather consumers responses. Significant positive correlations (R = 0.6-1) were observed between sensory responses and nutritional properties of seeds. Seeds from Si-treated drought-stressed plants showed higher acceptability scores among consumers. CONCLUSION: The results demonstrated that Si supplementation can improve the nutritional and sensory properties of seeds. This study offers an innovative approach in sensory analysis coupled with biometrics to accurately assess a consumer's preference towards tested samples. In the future, the results of this study will help in making a predictive model for sensory traits and nutritional components in seeds using machine-learning modelling techniques. © 2020 Society of Chemical Industry.

Integration of non-invasive biometrics with sensory analysis techniques to assess acceptability of beer by consumers.

Traditional sensory tests rely on conscious and self-reported responses from participants. The integration of non-invasive biometric techniques, such as heart rate, body temperature, brainwaves and facial expressions can gather more information from consumers while tasting a product. The main objectives of this study were i) to assess significant differences between beers for all conscious and unconscious responses, ii) to find significant correlations among the different variables from the conscious and unconscious responses and iii) to develop a model to classify beers according to liking using only the unconscious responses. For this study, an integrated camera system with video and infrared thermal imagery (IRTI), coupled with a novel computer application was used. Videos and IRTI were automatically obtained while tasting nine beers to extract biometrics (heart rate, temperature and facial expressions) using computer vision analysis. Additionally, an EEG mobile headset was used to obtain brainwave signals during beer consumption. Consumers assessed foam, color, aroma, mouthfeel, taste, flavor and overall acceptability of beers using a 9-point hedonic scale with results showing a higher acceptability for beers with higher foamability and lower bitterness. i) There were non-significant differences among beers for the emotional and physiological responses, however, significant differences were found for the cognitive and self-reported responses. ii) Results from principal component analysis explained 65% of total data variability and, along with the covariance matrix (p < 0.05), showed that there are correlations between the sensory responses of participants and the biometric data obtained. There was a negative correlation between body temperature and liking of foam height and stability, and a positive correlation between theta signals and bitterness. iii) Artificial neural networks were used to develop three models with high accuracy to classify beers according to level of liking (low and high) of three sensory descriptors: carbonation mouthfeel (82%), flavor (82%) and overall liking (81%). The integration of both sensory and biometric responses for consumer acceptance tests showed to be a reliable tool to be applied to beer tasting to obtain more information from consumers physiology, behavior and cognitive responses.

Silicon improves seed germination and alleviates drought stress in lentil crops by regulating osmolytes, hydrolytic enzymes and antioxidant defense system.

Silicon (Si) has been widely reported to have beneficial effect on mitigating drought stress in plants. However, the effect of Si on seed germination under drought conditions is still poorly understood. This research was carried out to ascertain the role of Si to abate polyethylene glycol-6000 mediated drought stress on seed germination and seedling growth of lentil. Results showed that drought stress significantly decreased the seed germination traits and increased the concentration of osmolytes (proline, glycine betaine and soluble sugars), reactive oxygen species (hydrogen peroxide and superoxide anion) and lipid peroxides in lentil seedlings. The activities of hydrolytic enzymes and antioxidant enzymes increased significantly under osmotic stress. The application of Si significantly enhanced the plants ability to withstand drought stress conditions through increased Si content, improved antioxidants, hydrolytic enzymes activity, decreased concentration of osmolytes and reactive oxygen species. Multivariate data analysis showed statistically significant correlations among the drought-tolerance traits, whereas cluster analysis categorised the genotypes into distinct groups based on their drought-tolerance levels and improvements in expression of traits due to Si application. Thus, these results showed that Si supplementation of lentil was effective in alleviating the detrimental effects of drought stress on seed germination and increased seedling vigour.

Within-Vineyard, Within-Vine, and Within-Bunch Variability of the Rotundone Concentration in Berries of Vitis vinifera L. cv. Shiraz.

This study characterizes the environmental factors driving rotundone concentrations in grape berries by quantifying rotundone variability and correlating it with viticultural parameters. Dissection of the vineyard into distinct zones (on the basis of vigor, electrical soil conductivity, and slope), vine into orientations to sun (shaded/unshaded), and grape bunches into sectors (upper and lower and front and back) shows the influence of vine vigor, sunlight, and temperature. Occurrence of the highest rotundone concentration was observed in shaded bunch sectors and vines and from higher vigor vines in the southern-facing areas of the vineyard. The highest concentration of rotundone is consistently found at the top and in shaded sectors of bunches, and this correlates to lower grape surface temperatures. Modeling showed that berry temperature exceeding 25 °C negatively affects the rotundone concentration in Shiraz. Both natural and artificial shading modulated the grape surface and air temperature at the bunch zone and increased the rotundone concentration, without affecting other grape berry quality parameters. Thus, temperature and possibly sunlight interception are the main determinants of rotundone in grape berries. Vineyard topography, vine vigor, vine row, and grape bunch orientation influence the level of berry shading and can, therefore, adjust bunch surface and zone temperatures and influence the berry rotundone concentration.