UV-Vis and CIELAB based chemometric characterization of manihot esculenta carotenoid contents

Vitamin A deficiency is a prevalent health problem in many areas of the world, where cassava genotypes with high pro-vitamin A content have been identified as a strategy to address this issue. In this study, we found a positive correlation between the color of the root pulp and the total carotenoid contents and, importantly, showed how CIELAB color measurements can be used as a non-destructive and fast technique to quantify the amount of carotenoids in cassava root samples, as opposed to traditional methods. We trained several machine learning models using UV-visible spectrophotometry data, CIELAB data and a low-level data fusion of the two. Best performance models were obtained for the total carotenoids contents calculated using the UV-visible dataset as input, with R2 values above 90 %. Using CIELAB and fusion data, values around 60 % and above 90 % were found. Importantly, these results demonstrated how data fusion can lead to a better model performance for prediction when comparing to the use of a single data source. Considering all these findings, the use of colorimetric data associated with UV-visible and HPLC data through statistical and machine learning methods is a reliable way of predicting the content of total carotenoids in cassava root samples.To CNPq (National Counsel of Technological and Scientific Development) for financial support (Process n 407323/2013-9), to CAPES (Coordination for the Improvement of Higher Education Personnel (CAPES), and EPAGRI(AgriculturalResearchandRuralExtensionCompanyofSantaCatarina).Theresearchfellowshipfrom CNPqonbehalfofM.Maraschinisacknowledged.TheworkispartiallyfundedbyProjectPropMine,funded bytheagreementbetweenPortugueseFCT(FoundationforScienceandTechnology)andBrazilianCNPq.info:eu-repo/semantics/publishedVersio

Configuració i optimització d’un mètode multi-instrumental integrat per analitzar pols sahariana en filtres d’aerosol atmosfèric de la Sierra Nevada

Treballs Finals de Grau de Química, Facultat de Química, Universitat de Barcelona, Any: 2019, Tutores: Anna De Juan Capdevila, Laura TosittiThis report is the union of some of the work and analyses carried out at the Laboratory of Dra. Laura Tositti, Bologna University. It is based on the analyses of Particulate Matter, one of the main atmospheric pollutants which is able to cause serious health and environmental problems. Specifically, the sampling of analysed filters has been done at Sierra Nevada, south of Spain, within the Spanish research project FRESA. This sampling station has the characteristic of being next to North Africa at a high altitude (2550 m a.s.l.). Because of this, Particulate Matter collected in these filters often includes Saharan Dust that comes from North Africa transported by the wind. This kind of Particulate Matter has a specific chemical and physical composition. It is made mostly of coarse particulate and its colour tends to be reddish because of its content in iron oxides such as hematite. The aim of this report is to use a series of basic and widely available spectroscopic techniques to analyse these filters in order to characterise in detail the properties and composition of airborne particulate matter. Then the idea was to develop a quantitative analytical approach from spectroscopic techniques usually applied only in a qualitative way according to an approach partly experimental and partly chemometric recently introduced at Dra. Tositti’s lab. Portions of a series of 19 weekly filters from Sierra Nevada were analysed in triplicate. Experimental procedures and data analyses will be separated in 5 parts each. These parts are the 4 analyses of the filters that has been done: Homogeneity test, UV-VIS Diffuse Reflectance Spectroscopy (UV-VIS DRS), Fourier Transform Infrared Spectroscopy with attenuated total reflection (FT-IR ATR), and Chemiluminescence using a Luminol-based test for the detection of ROS (Reactive Oxygen Species). Moreover, a parallel work of this thesis was the design and optimization of the resuspension system, a special assembly that was set up to produce solid calibration standards on filters in order to quantify chemical compounds on the filters, (especially hematite). This work therefore enabled the acquisition of several properties of these environmental samples, i.e. the filters weight and their homogeneity, spectroscopic signal of hematite and colour information, and IR bands that mostly explain the quartz and hematite composition, along with others, and finally, chemiluminescence maximum peak. All the data obtained in this thesis work was finally subjected to Spearman correlation analysis extending my dataset to data previously obtained at Bologna lab such as Ion Chromatography as well as meteorological data during the sampling period. A high correlation was found between hematite, PM10, reddish colour of filters, and the IR absorption band, while chemiluminescence seems to be correlated with acetate and calcium catio

UV-Vis and CIELAB Based Chemometric Characterization of Manihot esculenta Carotenoid Contents

Vitamin A deficiency is a prevalent health problem in many areas of the world, where cassava genotypes with high pro-vitamin A content have been identified as a strategy to address this issue. In this study, we found a positive correlation between the color of the root pulp and the total carotenoid contents and, importantly, showed how CIELAB color measurements can be used as a non-destructive and fast technique to quantify the amount of carotenoids in cassava root samples, as opposed to traditional methods. We trained several machine learning models using UV-visible spectrophotometry data, CIELAB data and a low-level data fusion of the two. Best performance models were obtained for the total carotenoids contents calculated using the UV-visible dataset as input, with R2 values above 90 %. Using CIELAB and fusion data, values around 60 % and above 90 % were found. Importantly, these results demonstrated how data fusion can lead to a better model performance for prediction when comparing to the use of a single data source. Considering all these findings, the use of colorimetric data associated with UV-visible and HPLC data through statistical and machine learning methods is a reliable way of predicting the content of total carotenoids in cassava root samples

Technological innovations for improving cassava production in sub-Saharan Africa

Open Access Journal; Published online: 21 Jan 2021Cassava is crucial for food security of millions of people in sub-Saharan Africa. The crop has great potential to contribute to African development and is increasing its income-earning potential for small-scale farmers and related value chains on the continent. Therefore, it is critical to increase cassava production, as well as its quality attributes. Technological innovations offer great potential to drive this envisioned change. This paper highlights genomic tools and resources available in cassava. The paper also provides a glimpse of how these resources have been used to screen and understand the pattern of cassava genetic diversity on the continent. Here, we reviewed the approaches currently used for phenotyping cassava traits, highlighting the methodologies used to link genotypic and phenotypic information, dissect the genetics architecture of key cassava traits, and identify quantitative trait loci/markers significantly associated with those traits. Additionally, we examined how knowledge acquired is utilized to contribute to crop improvement. We explored major approaches applied in the field of molecular breeding for cassava, their promises, and limitations. We also examined the role of national agricultural research systems as key partners for sustainable cassava production

In-line UV-Visible process analytical technology for optimisation of continuous manufacture of piroxicam products using hot melt extrusion - a quality by design approach

Continuous manufacture (CM) and process analytical technology (PAT) have been proposed as innovative solutions for the pharmaceutical industry to decrease costs and prevent shortages of medicines in the market. This concept implies that raw materials are continuously fed and processed in a sequence of unit operations while being monitored by non-destructive analytical techniques. Furthermore, this strategy provides flexibility as products can be diverted in response to process deviations. The work carried out in this thesis concerns the use of Hot-Melt Extrusion (HME) as a continuous process system with in-line UV-Vis spectroscopy to develop and manufacture piroxicam (PRX) amorphous dispersions (ASD) with enhanced solubility. Solubility parameters of the drug and polymers were calculated using group contribution methods to select a carrier miscible with PRX. The Just-Breitkreutz total solubility parameter value for PRX is (δ = 21 MPa1/2) and for Vinyl pyrrolidone – vinyl acetate copolymer (PVPVA) it is (δ = 19.71 MPa1/2). The small difference (Δδ < 7 MPa1/2) between PRX and PVPVA solubility parameters (Δδ = 1.30 MPa1/2) indicated those would be miscible, therefore PVPVA was selected as the ASD carrier to be evaluated experimentally. The Flory-Huggins thermodynamic model and differential scanning calorimetry (DSC) melt depression data were applied to build a phase diagram of PRX and PVPVA mixtures. The phase diagram estimated that 8-24% PRX processed with PVPVA around 140 °C would form a metastable amorphous mixture. The phase diagram results were validated using extrusion experiments. Samples containing 15-20 % of PRX with PVPVA yielded amorphous mixtures whereas samples with concentration ≥ 25 % PRX produced unstable dispersions that resulted in phase separation. Design of experiments (DoE), multivariate analysis (MVA) and Process Analytical Technology (PAT) were used to investigate the impact of die temperature, screw speed, solid feed rate and PRX % on the ASD extrudates. Statistical models built from in-line UV-Vis responses (L*, b*, a*) revealed interactions between PRX% and die temperature, feed rate and screw speed. The design space (DS) of the process included PRX 0.1) and colour changes (L* -9). In-line UV-Vis spectroscopy provides a powerful tool to monitor quality of extrusion products in real-time. A quantitative method based in-line UV-Vis absorbance and partial-least square model to predict the PRX % in PVPVA during HME was proposed using analytical quality by design principles (AQbD) and accuracy profile approach. The accuracy profile showed that In-line UV-Vis could predict PRX % within the trueness and precision acceptance limits (±5 %) for all PRX levels analysed (10.58-18.46 %). Additionally, the quick response and simplicity of in-line UV-Vis responses enabled a machine learning Nelder-Mead (NM) algorithm to converge to screw speed (7.81 g/min) and feed rate (354.44 rpm) settings that matched L* (93.07) and b* (83.00) targets. The optimised PRX dispersions with 16 % PRX were formulated as immediate-release tablets. The analysis of the Hausner ratio (1.11), angle of response (37-40 °) and compressibility index showed that the ASDs have excellent flow, thus are good candidates for direct compression (DC) process. The tabletability plot demonstrated that ASDs achieved considerable low tensile strength (TS) at high force (TS ~ 1.5 at 160 MPa). A mixture design experiment determined optimal combinations of fillers (Avicel® PH 102, Pearlitol® SD 200) and the disintegrant (Ac-Di-Sol®), whereas a classical design evaluated compaction pressure, speed and lubrication effects on tablet critical quality attributes (CQAs). The mixture design determined a minimum Avicel® PH 102 threshold of 27 % to achieve TS > 1.7MPa at 120 MPa, while the process experiment excluded lubricant % and compression speed effects in TS and SF. Formulations with 30-50 % Avicel® PH 102, 15-30 % Pearlitol® SD 200, 3-5 % Ac-Di-Sol® manufactured between 120-180 MPa resulted in tensile strength > 1.7 MPa, solid fraction ≈ 0.85, ejection pressure < 3 MPa, friability < 0.5 %, disintegration time < 300 s and 80 % PRX released within 30 min of the in-vitro dissolution test, confirming the formulation design space and compression pressure predicted effects. This work demonstrated the role of in-line UV-Vis spectroscopy in optimisation and monitoring the extrusion of amorphous PRX. The PAT detected the PRX saturation limit, previously predicted by Flory-Huggins thermodynamic modelling. The L* and b* were successfully implemented as targets of the NM algorithm to optimise screw speed and feed rate. Finally, a new tablet dosage form was developed based on the optimised extruded amorphous PRX and PVPVA