Monitoring complex monosaccharide mixtures derived from macroalgae biomass by combined optical and microelectromechanical techniques

Determining the shelf life and quality changes of potatoes (Solanum tuberosum) during storage using electronic nose and machine learning

The activities of alpha-amylase, beta-amylase, sucrose synthase, and invertase enzymes are under the influence of storage conditions and can affect the structure of starch, as well as the sugar content of potatoes, hence altering their quality. Storage in a warehouse is one of the most common and effective methods of storage to maintain the quality of potatoes after their harvest, while preserving their freshness and sweetness. Smart monitoring and evaluation of the quality of potatoes during the storage period could be an effective approach to improve their freshness. This study is aimed at assessing the changes in the potato quality by an electronic nose (e-nose) in terms of the sugar and carbohydrate contents. Three potato cultivars (Agria, Santé, and Sprite) were analyzed and their quality variations were separately assessed. Quality parameters (i.e. sugar and carbohydrate contents) were evaluated in six 15-day periods. The e-nose data were analyzed by means of chemometric methods, including principal component analysis (PCA), linear data analysis (LDA), support vector machine (SVM), and artificial neural network (ANN). Quadratic discriminant analysis (QDA) and multivariate discrimination analysis (MDA) offer the highest accuracy and sensitivity in the classification of data. The accuracy of all methods was higher than 90%. These results could be applied to present a new approach for the assessment of the quality of stored potatoes.

Analysis of the chemical composition of natural carbohydrates - An overview of methods

Natural carbohydrates are gaining importance over a wide spectrum of human activity due to their versatile functionalities. The properties of carbohydrates are currently used in many branches of industry and new possibilities of their utilization, like in medicine or materials science, are demonstrated systematically. The attractive properties of carbohydrates result from their chemical structure and ability to form macromolecules and derivatives. Each application of carbohydrate requires a knowledge of their chemical composition, which due to the number and differentiation of monosaccharides and their spatial forms is often challenging. This review presents an overview on sample preparation and the methods used for the determination of the fine chemical structure of natural carbohydrates. Most popular and reliable colorimetric, chromatographic and spectroscopic methods are presented with an emphasis on their pros and cons.

Sustainability of multifaceted usage of biomass: A review

The paper focuses on collection of information on recent multifaceted usage of biomass materials with critical examination on its sustainability. The use of biomass is becoming popular, with wide global acceptance as it is considered as green technology. The use of biomass products across industrial parallels, the material combination and production processes were elucidated in this paper. Biomass materials are seen as affordable alternative to conventional materials for domestic and industrial applications. The multifaceted use of biomass, which includes, energy generation, metallurgical applications, construction purposes, reinforcement in metal matrix composite, microelectromechanical system, biochemical and traditional medicine were discussed. This underscores the need to develop a sustainable plan to meet with its diverse usage to be beyond laboratory efforts. This paper examined whether the availability of biomass can sustain its multifaceted usage or not. It also examined the modalities to ensure sustainable use of biomass. Different policies were highlighted and discussed in line with continuous multifaceted use of biomass.

Spatial and Temporal Monitoring of Pasture Ecological Quality: Sentinel-2-Based Estimation of Crude Protein and Neutral Detergent Fiber Contents

Frequent, region-wide monitoring of changes in pasture quality due to human disturbances or climatic conditions is impossible by field measurements or traditional ecological surveying methods. Remote sensing imagery offers distinctive advantages for monitoring spatial and temporal patterns. The chemical parameters that are widely used as indicators of ecological quality are crude protein (CP) content and neutral detergent fiber (NDF) content. In this study, we investigated the relationship between CP, NDF, and reflectance in the visible–near-infrared–shortwave infrared (VIS–NIR–SWIR) spectral range, using field, laboratory measurements, and satellite imagery (Sentinel-2). Statistical models were developed using different calibration and validation data sample sets: (1) a mix of laboratory and field measurements (e.g., fresh and dry vegetation) and (2) random selection. In addition, we used three vegetation indices (Normalized Difference Vegetative Index (NDVI), Soil-adjusted Vegetation Index (SAVI) and Wide Dynamic Range Vegetation Index (WDRVI)) as proxies to CP and NDF estimation. The best models found for predicting CP and NDF contents were based on reflectance measurements (R2 = 0.71, RMSEP = 2.1% for CP; and R2 = 0.78, RMSEP = 5.5% for NDF). These models contained fresh and dry vegetation samples in calibration and validation data sets. Random sample selection in a model generated similar accuracy estimations. Our results also indicate that vegetation indices provide poor accuracy. Eight Sentinel-2 images (December 2015–April 2017) were examined in order to better understand the variability of vegetation quality over spatial and temporal scales. The spatial and temporal patterns of CP and NDF contents exhibit strong seasonal dependence, influenced by climatological (precipitation) and topographical (northern vs. southern hillslopes) conditions. The total CP/NDF content increases/decrease (respectively) from December to March, when the concentrations reach their maximum/minimum values, followed by a decline/incline that begins in April, reaching minimum values in July.

Highly Responsive and Ultrasensitive Glucose Sensor Based on Au Foam

Glucose concentration is an important physiological index, therefore methods for sensitive detection of glucose are important. In this study, Au foam was prepared by electrodeposition with a dynamic gas template on an Au nanoparticle/Si substrate. The Au foam showed ultrasensitivity, high selectivity, and long-term stability in the quantitative detection of glucose. The foam was used as an electrode, and the amperometric response indicated excellent catalytic activity in glucose oxidation, with a linear response across the concentration range 0.5 μM to 12 mM, and a limit of detection of 0.14 μM. High selectivity for interfering molecules at six times the normal level and long-term stability for 30 days were obtained. The results for electrochemical detection with Au foam of glucose in human serum were consistent with those obtained with a sensor based on surface-enhanced Raman spectroscopy and a commercial sensor. This proves that this method can be used with real samples. These results show that Au foam has great potential for use as a non-enzymatic glucose sensor.

Scanning MEMS Mirror for High Definition and High Frame Rate Lissajous Patterns

Scanning MEMS (micro-electro-mechanical system) mirrors are attractive given their potential use in a diverse array of laser scanning display and imaging applications. Here we report on an electrostatic MEMS mirror for high definition and high frame rate (HDHF) Lissajous scanning. The MEMS mirror comprised a low Q-factor inner mirror and frame mirror, which provided two-dimensional scanning at two similar resonant scanning frequencies with high mechanical stability. The low Q inner mirror enabled a broad frequency selection range. The high definition and high frame rate (HDHF) Lissajous scanning of the MEMS mirror was achieved by selecting a set of scanning frequencies near its resonance with a high greatest common divisor (GCD) and a high total lobe number. The MEMS mirror had resonant scanning frequencies at 5402 Hz and 6702 Hz in x and y directions, respectively. The selected pseudo-resonant frequencies of 5450 Hz and 6700 Hz for HDHF scanning provided 50 frames per second with 94% fill factor in 256 × 256 pixels. This Lissajous MEMS mirror could be utilized for assorted HDHF laser scanning imaging and display applications.