Monitoring small-scale alcoholic fermentations using a portable FTIR-ATR spectrometer and multivariate analysis

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Biostimulants and biofertilizers are considered environmentally friendly and cost-effective alternatives to synthetic fertilizers, plant growth regulators and crop improvement products. Broadly, plant biostimulants are expected to improve nutrient use efficiency, tolerance to abiotic stress, quality traits and availability of nutrients in the soil or rhizosphere. Currently, seaweed extracts account for more than 33% of the total plant biostimulant market. Within this category, Ascophyllum nodosum (AN), is the most widely studied and applied in biostimulant formulations.

The use of new fungus disease-tolerant grapevine varieties is a long-term and promising solution to reduce chemical input in viticulture. However, little is known about the effects of water deficit (WD) on the thiol aromatic potential of new varieties coming up from breeding programs. Varietal thiols such as 3-sulfanylhexan-ol (3SH), 4-methyl-4-sulfanylpentan-2-one (4MSP) and their derivatives are powerful aromatic compounds present in wines coming from odorless precursors in grapes, and could contribute to the wine typicity of such varieties.

Chardonnay is the world’s most planted white grape variety and has met a great commercial success for decades.

Knowledge on the reflectance spectrum of soil is potentially useful since it carries information on soil chemical composition that can be used to the planning of agricultural practices. If compared with analytical methods such as conventional chemical analysis, reflectance measurement provides non-destructive, economic, near real-time data. This paper reports results from reflectance measurements performed by spectroradiometry on soils from two vineyards in south Brazil. The vineyards are close to each other, are on different geological formations, but were subjected to the same management. The objective was to detect spectral differences between the two areas, correlating these differences to variations in their chemical composition, to assess the technique’s potential to predict soil attributes from reflectance data.To that end, soil samples were collected from ten selected vine parcels. Chemical analysis yield data on concentration of twenty-one soil attributes, and spectroradiometry was performed on samples. Chemical differences significant to a 95% confidence level between the two studied areas were found for six soil attributes, and the average reflectance spectra were separated by this same level along most of the observed spectral domain. Correlations between soil reflectance and concentrations of soil attributes were looked for, and for ten soil traits it was possible to define wavelength domains were reflectance and concentrations are correlated to confidence levels from 95% to 99%. Partial Least Squares Regression (PLSR) analyses were performed comparing measured and predicted concentrations, and for fifteen out of 21 soil traits we found Pearson correlation coefficients r > 0.8. These preliminary results, which have to be validated, suggest that variations of concentration in the investigated soil attributes induce differences in reflectance that can be detected by spectroradiometry. Applications of these observations include the assessment of the chemical content of soils by spectroradiometry as a fast, low-cost alternative to chemical analytical methods.