Texture Prediction in Intact Green Asparagus by Near Infrared (NIR) Spectroscopy,Assaying Linear and Non-linear Regression Strategies

Texture-related parameters were assessed in intact green asparagus at harvest and during postharvest storage using near-infrared spectroscopy combined with MPLS and LOCAL algorithms. Three spectrophotometers were evaluated for this purpose: a monochromator (range, 400–2,500 nm), a diode-array Vis–NIR spectrophotometer (range, 400–1,700 nm), and a handheld micro-electro-mechanical system (MEMS) spectrophotometer (range, 1,600–2,400 nm). Three hundred green asparagus spears (cv. “Grande”) were used to obtain calibration models based on reference data and NIR data. Results for maximum shear force showed that LOCAL algorithm improved the predictive capacity of models constructed using all three NIRS instruments, increasing r ² by 24, 16, and 56 % and reducing the SEP(c) values by 11, 8, and 14 %, respectively. For cutting energy, the LOCAL also improved the predictive capacity of the models (r ² increased by 3 % for the monochromator and the diode-array instrument and by 6 % for the MEMS device; and the SEP(c) decreased by 3 % in the three instruments). It is worth noting that while the monochromator and diode-array instruments displayed similar predictive capacity for the parameters tested, the MEMS instrument achieved slightly poorer results but has clear advantages for the measurement of texture in intact asparagus, being economical, portable, and easy to use in situ.     

Technological Implications of Modifying the Extent of Cell Wall-Proanthocyanidin Interactions Using Enzymes

The transference and reactivity of proanthocyanidins is an important issue that affects the technological processing of some fruits, such as grapes and apples. These processes are affected by proanthocyanidins bound to cell wall polysaccharides, which are present in high concentrations during the processing of the fruits. Therefore, the effective extraction of proanthocyanidins from fruits to their juices or derived products will depend on the ability to manage these associations, and, in this respect, enzymes that degrade these polysaccharides could play an important role. The main objective of this work was to test the role of pure hydrolytic enzymes (polygalacturonase and cellulose) and a commercial enzyme containing these two activities on the extent of proanthocyanidin-cell wall interactions. The results showed that the modification promoted by enzymes reduced the amount of proanthocyanidins adsorbed to cell walls since they contributed to the degradation and release of the cell wall polysaccharides, which diffused into the model solution. Some of these released polysaccharides also presented some reactivity towards the proanthocyanidins present in a model solution.     

Validation of SeaWiFS-derived chlorophyll for the Rio de la Plata Estuary and adjacent waters

The South Atlantic Ocean near the Río de la Plata Estuary is a highly dynamic region that encompasses four different water bodies: the Río de la Plata, the continental shelf and the Brazil and Malvinas currents. Bio-optical measurements obtained during 6–11 November 1999 provided the initial field data for validating Sea viewing Wide Field of view Sensor (SeaWiFS)-derived chlorophyll imagery for this region. The turbid waters of the Río de la Plata Estuary showed the highest variability and complexity in water optical properties, while the offshore waters of the Brazil Current had the lowest. In most cases, the estimates of chlorophyll using the SeaWiFS algorithm were higher than in situ measured values.     

Production of Methyl Oleate in Reactive‐Separation Systems

The esterification of oleic acid and methanol using sulfuric acid as a homogeneous catalyst is studied in reactive‐separation systems. The conversion of the free fatty acid was investigated in two different experiments with the molar ratio of methanol/oleic acid, amount of catalyst, temperature, and reaction time as variables. The conversion of the free fatty acid was found to depend strongly on the molar ratio of methanol/oleic acid. The reaction time had a direct effect on the conversion of the free fatty acid, and this conversion decreased with higher temperature. These results were valuable for a preliminary study on biodiesel production, using an acid homogeneous catalyst in a reactive dividing‐wall distillation column.     

Stability of the antimicrobial activity of acetogenins from avocado seed,under common food processing conditions,against Clostridium sporogenes vegetative cell growth and endospore germination

Anticlostridial activity of acetogenins from avocado seed was further characterised, and their stability and effectiveness under food processing conditions, and in a model food system, studied for the first time. Isolated AcO‐avocadenyne (1) and AcO‐avocadene (2) showed anticlostridial potential, particularly the latter molecule. Enriched acetogenins extracts, obtained at laboratory scale (EAE) and semi‐commercially (Avosafe^®), presented similar MIC values (3.9–9.8 ppm) and a bacteriostatic effect. Extracts bioactivity showed resistance to heat (≤120 °C), high hydrostatic pressure (HHP; 300–600 MPa, 3–6 min, 25 °C) and salt (≤3% w/v). In addition, the extract was most stable at pH ≥ 7.0 and potency against endospores increased after HHP treatment and exposure to pH 9.5, suggesting a positive effect on solubility or structure of particular acetogenins. In a model food system processed by HHP, acetogenins were retained; however, initial quantities gradually declined by 63% and 32% at 25 and 4 °C, respectively, at the end of the storage period (42 days). Most stable molecules (persediene (4) > persenones > AcO‐avocadene (2)) possess a keto or trans‐enone group at C‐4 in the aliphatic chain, which could support hydrogen donation to surrounding carbon atoms and confer antioxidant activity. Active endospores were completely inhibited by 5000 ppm Avosafe^® in the model food system (37 °C, 72 h) and lower concentrations (500–1000 ppm) resulted in 1–2 log reduction of a 3 log inoculum target. Efficacy information generated in the present work is considered crucial to improve scientific knowledge on spore inhibition properties of avocado acetogenins.     

Grading and color evolution of apples using RGB and hyperspectral imaging vision cameras

The potential of RGB digital imaging and hyperspectral imaging (900–1700 nm) was evaluated for discriminating maturity level in apples under different storage conditions along the shelf-life. Segmentation, preprocessing and partial least squares-discriminant analysis (PLS-DA) were used for hyperspectral data analysis, while illumination correction, dimensionality reduction and linear discriminant analysis (LDA) were used for RGB data analysis. The results showed that hyperspectral discrimination classified different storage regimes better than RGB, with an overall success rate of 95.83%. In addition, color evolution of apples during shelf-life under different storage regimes was modeled using RGB zero and first order regression models, fitting better to a first order kinetic model.     

Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction

The task of breast density quantification is becoming increasingly relevant due to its association with breast cancer risk. In this work, a semi-automated and a fully automated tools to assess breast density from full-field digitized mammograms are presented. The first tool is based on a supervised interactive thresholding procedure for segmenting dense from fatty tissue and is used with a twofold goal: for assessing mammographic density (MD) in a more objective and accurate way than via visual-based methods and for labeling the mammograms that are later employed to train the fully automated tool. Although most automated methods rely on supervised approaches based on a global labeling of the mammogram, the proposed method relies on pixel-level labeling, allowing better tissue classification and density measurement on a continuous scale. The fully automated method presented combines a classification scheme based on local features and thresholding operations that improve the performance of the classifier. A dataset of 655 mammograms was used to test the concordance of both approaches in measuring MD. Three expert radiologists measured MD in each of the mammograms using the semi-automated tool (DM-Scan). It was then measured by the fully automated system and the correlation between both methods was computed. The relation between MD and breast cancer was then analyzed using a case–control dataset consisting of 230 mammograms. The Intraclass Correlation Coefficient (ICC) was used to compute reliability among raters and between techniques. The results obtained showed an average ICC = 0.922 among raters when using the semi-automated tool, whilst the average correlation between the semi-automated and automated measures was ICC = 0.838. In the case–control study, the results obtained showed Odds Ratios (OR) of 1.38 and 1.50 per 10% increase in MD when using the semi-automated and fully automated approaches respectively. It can therefore be concluded that the automated and semi-automated MD assessments present a good correlation. Both the methods also found an association between MD and breast cancer risk, which warrants the proposed tools for breast cancer risk prediction and clinical decision making. A full version of the DM-Scan is freely available.