No abstract

Pasture quality monitoring is a key element in the decision making process of a farm manager. Laboratory reference methods for assessing quality parameters such as crude protein (CP) or fibers (neutral detergent fiber: NDF) require collection and analytical procedures involving technicians, time, and reagents, making them laborious and expensive. The objective of this work was to evaluate two technological and expeditious approaches for estimating and monitoring the evolution of the quality parameters in biodiverse Mediterranean pastures: (i) near infrared spectroscopy (NIRS) combined with multivariate data analysis and (ii) remote sensing (RS) based on Sentinel-2 imagery to calculate the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI). Between February 2018 and March 2019, 21 sampling processes were carried out in nine fields, totaling 398 pasture samples, of which 315 were used during the calibration phase and 83 were used during the validation phase of the NIRS approach. The average reference values of pasture moisture content (PMC), CP, and NDF, obtained in 24 tests carried out between January and May 2019 in eight fields, were used to evaluate the RS accuracy. The results of this study showed significant correlation between NIRS calibration models or spectral indices obtained by remote sensing (NDVIRS and NDWIRS) and reference methods for quantifying pasture quality parameters, both of which open up good prospects for technological-based service providers to develop applications that enable the dynamic management of animal grazing.

A rapid method for the evaluation of fatty acids (FA) of monovarietal Portuguese extra virgin olive oils (EVOOs) (n = 82) from Alentejo, south‐central region of Portugal, is developed based on Fourier‐transform near‐infrared spectroscopy (FT‐NIRS). The contents of FA‐components (previously determined per conventional gas chromatography) are correlated with FT‐NIRS data (independent variable), by means of full cross‐validation partial least squares regression (CVPLSR). CVPLSR is run using standard normal variate (SNV) data pre‐processing and the nonlinear iterative partial least squares (NIPALS) algorithm. Obtained correlation models are characterized with good statistics: high correlation coefficients (R > 0.85) and low root mean square errors (RMSE < 2.04). Obtained values of the residual predictive deviation (RPD) of CVPLSR‐model, higher than 5.0 (C18:1, C18:2, MUFA, PUFA) confirm the FT‐NIRS as a potential method for rapid quality control of EVOO's FA. Practical Applications: In this work for the first time, fatty acid (FA) profile of monovarietal extra virgin olive oil (EVOO) samples of the greatest olive region in Portugal—Alentejo—is analyzed by Fourier‐transform near‐infrared spectroscopy (FT‐NIRS) and chemometrics. Obtained high‐quality results allow one to recommend this technique from monitoring to quality control analysis of FA (in particular, of representative unsaturated FA), in a great number of olive oil samples, in near‐real time. Quality of olive oil can be assessed by target or non‐target analysis and it is of mandatory importance. Fourier‐transform near‐infrared spectroscopy (FT‐NIRS), combined with chemometrics, for the analysis of the fatty acid profile of varietal olive oils from Alentejo (Portugal) can be a useful technique for quality control. Furthermore, FT‐NIRS is rapid, non‐destructive, and a more environmental friendly technique.

Red wine grapes require a constant follow-up through analytical chemistry to assure the greatest wine quality. Wet chemical procedures are time-consuming and produce residues that are hard to eliminate. NIR (near infrared radiation) spectroscopy has been referred as an accurate, rapid, and cost-efficient technique to evaluate quality in many fruit species, both in field and in industry. The main objective of this study was to develop predictive models using NIR spectroscopy to quantify important quality attributes in wine grapes. Soluble solids content (SSC), titratable acidity (TA), total phenolic content, total flavonoids, total anthocyanins, and total tannins were quantified in four red wine grape varieties, ‘Aragonês’, ‘Trincadeira’, ‘Touriga Nacional’, and ‘Syrah’. Samples were collected during 2017 and 2018 along véraison. Prediction models were developed using a near-infrared portable device (Brimrose, Luminar 5030), and spectra were collected from entire grapes under near field conditions. Models were built using a partial least square regression (PLSR) algorithm and SSC, TA, total anthocyanins, and total tannins exhibited a determination coefficient of 0.89, 0.90, 0.87, and 0.88, respectively. The Residual Prediction Deviation (RPD) values of these models were higher than 2.3. The prediction models for SSC, TA, total anthocyanins, and total tannins have considerable potential to quantify these attributes in wine grapes. Total flavonoids and total phenolic content were predicted with a slightly lower capacity, with R2 = 0.72 and 0.71, respectively, and both with a RPD of 1.6, indicating a very low to borderline potential for quantitative predictions in flavonoids and phenols models.

At Mediterranean regions and particularly in southern Portugal, it is imperative to identify grape varieties more adapted to warm and dry climates in order to overcome future climatic changes. Two Vitis vinifera genotypes, Aragonez (syn. Tempranillo) and Trincadeira, were selected to assess their physiological responses to soil water stress. Vines were subjected to four irrigation regimes: irrigated during all phenological cycle, non-irrigated during all phenological cycle, non irrigated until veraison, irrigated after veraison. Predawn leaf water potential was much higher in Trincadeira than Aragonez in non-irrigated plants. This result is in accordance with its higher stomatal control efficiency in this variety (Trincadeira). Photosynthetic capacity (A max at saturating light intensity) decreased due to stomatal and biochemical limitations under water stress. However, recovery capacity of leaf water status after irrigation was faster in Trincadeira. Yield and yield x Brix increased when irrigation occurred after veraison, particularly in Trincadeira. These results show that Trincadeira presents a drought adaptation than Aragonez. Ratio of variable to maximum fluorescence F v /F m and total leaf chlorophyll related with leaf water potential for both species. Reflectance Normalized Difference Vegetation Index (NDVI 705 ), Red Edge Inflexion Point Index and Photochemical Reflectance Index were related with irrigation treatment. Relative water content and specific leaf area were similar between varieties. In conclusion, we suggested that there is variation among the genotypes and the main physiological parameters for variety selection, for drought, were leaf water potential, stomatal conductance and reflectance indexes.