Browsing by Author "Anastasiadi, Maria"
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Item Open Access Application of spectroscopic and multispectral imaging technologies on the assessment of ready-to-eat pineapple quality: A performance evaluation study of machine learning models generated from two commercial data analytics tools(Elsevier, 2020-06-03) Manthou, Evanthia; Lago, Sergio-Llaneza; Dagres, Evaggelos; Lianou, Alexandra; Tsakanikas, Panagiοtis; Panagou, Efstathios Z.; Anastasiadi, Maria; Mohareb, Fady; Nychas, George-John E.Recently, rapid, non-invasive analytical methods relying on vibrational spectroscopy and hyper/multispectral imaging, are increasingly gaining popularity in food science. Although such instruments offer a promising alternative to the conventional methods, the analysis of generated data demands complex multidisciplinary approaches based on data analytics tools utilization. Therefore, the objective of this work was to (i) assess the predictive power of different analytical platforms (sensors) coupled with machine learning algorithms in evaluating quality of ready-to-eat (RTE) pineapple (Ananas comosus) and (ii) explore the potentials of The Unscrambler software and the online machine-learning ranking platform, SorfML, in developing the predictive models required by such instruments to assess quality indices. Pineapple samples were stored at 4, 8, 12 °C and dynamic temperatures and were subjected to microbiological (total mesophilic microbial populations, TVC) and sensory analysis (colour, odour, texture) with parallel acquisition of spectral data. Fourier-transform infrared, fluorescence (FLUO) and visible sensors, as well as Videometer instrument were used. For TVC, almost all the combinations of sensors and Partial-least squares regression (PLSR) algorithm from both analytics tools reached values of root mean square error of prediction (RMSE) up to 0.63 log CFU/g, as well as the highest coefficient of determination values (R2). Moreover, Linear Support Vector Machine (SVM Linear) combined with each one of the sensors reached similar performance. For odour, FLUO sensor achieved the highest overall performance, when combined with Partial-least squares discriminant analysis (PLSDA) in both platforms with accuracy close to 85%, but also with values of sensitivity and specificity above 85%. The SVM Linear and MSI combination also achieved similar performance. On the other hand, all models developed for colour and texture showed poor prediction performance. Overall, the use of both analytics tools, resulted in similar trends concerning the feasibility of the different analytical platforms and algorithms on quality evaluation of RTE pineapple.Item Open Access Biochemical profile of heritage and modern apple cultivars and application of machine learning methods to predict usage, age, and harvest season(American Chemical Society, 2017-06-02) Anastasiadi, Maria; Mohareb, Fady R.; Redfern, Sally P.; Berry, Mark; Simmonds, Monique; Terry, Leon A.The present study represents the first major attempt to characterise the biochemical profile in different tissues of a large selection of apple cultivars sourced from the UK’s National Fruit Collection comprising dessert, ornamental, cider and culinary apples. Furthermore, advanced Machine Learning methods were applied with the objective to identify whether the phenolic and sugar composition of an apple cultivar could be used as a biomarker fingerprint to differentiate between heritage and mainstream commercial cultivars as well as govern the separation among primary usage groups and harvest season. Prediction accuracy > 90% was achieved with Random Forest for all three models. The results highlighted the extraordinary phytochemical potency and unique profile of some heritage, cider and ornamental apple cultivars, especially in comparison to more mainstream apple cultivars. Therefore, these findings could guide future cultivar selection on the basis of health-promoting phytochemical content.Item Open Access Data underpinning "Biochemical Profile of Heritage and Modern Apple Cultivars and Application of Machine Learning Methods to Predict Usage, Age, and Harvest Season"(Cranfield University, 2017-06-05 09:32) Anastasiadi, Maria; Terry, Leon; Redfern, Sally; Mohareb, Fady; Berry, MarkThis dataset contains the quantitative data used for statistical analysis and predictive modelling in the paper entitled "Biochemical Profile of Heritage and Modern Apple Cultivars and Application of Machine Learning Methods to Predict Usage, Age, and Harvest Season". Specifically it contains concentration of phenolic compounds per Fresh weight in the whole apples as well as sugars and organic acids. In addition the phenolic content of individual tissues (peel, flesh, seeds) is uploaded.Item Open Access Data underpinning "Seasonal and Temporal Changes during Storage Affect Quality Attributes of Green Asparagus"(Cranfield University, 2019-09-19 18:33) Anastasiadi, Maria; Collings, Emma; Terry, Leon; Shivembe, Allan; Qian, BinghuaThis dataset contains the data used for statistical analysis and predictive modelling in the paper entitled "Seasonal and Temporal Changes during Storage Affect Quality Attributes of Green Asparagus". Specifically it contains physiological and biochemical changes in asparagus spears from two different cultivars during shelf-life captured over the course of the harvest season, as well as during cold storage and subsequent shelf-life for three different cultivars. Physiological changes include moisture loss, respiration rate, cutting energy, stiffness, objective colour. Biochemical data include individual sugars, ascorbic acid and abscisic acid and its catabolites. Also the data capture spatial differences along the asparagus spears (apical and basal regions).Item Open Access The first comprehensive chemical profiling of Vachellia gummifera (Willd.) Kyal. & Boatwr., a plant with medicinal value(Wiley, 2024-03-19) Kisiriko, Musa; Noleto-Dias, Clarice; Bitchagno, Gabin T. M.; Naboulsi, Imane; Anastasiadi, Maria; Terry, Leon A.; Sobeh, Mansour; Beale, Michael H.; Ward, Jane L.Vachellia gummifera (Willd.) Kyal. & Boatwr. is a medicinal plant endemic to Morocco that has no documented studies on its chemical composition. In this study, the chemical composition of the water/methanol (4 : 1) extracts of air-dried leaf and stem samples of Moroccan V. gummifera was determined using UHPLC-MS and NMR. In total, over 100 metabolites were identified in our study. Pinitol was the major compound in both the leaf and stem extracts, being significantly more abundant in the former. Asparagine and 3-hydroxyheteroendrin were the second most abundant compounds in the stem and leaf extracts, respectively, though both compounds were present in each tissue. The other compounds included flavonoids based on quercetin, and phenolic derivatives. Eucomic acid, only identified in the stems and was the major aromatic compound distinguishing the leaf and stem profiles. Quercetin 3-O-(6′′-O-malonyl)-β-D-glucopyranoside was identified as the major flavonoid in the leaves but was also present in the stems. Other malonylated derivatives that were all flavonol glycosides based on myricetin, kaempferol, and isorhamnetin in addition to quercetin were also identified. This is the first report of eucomic acid and malonylated compounds in Vachellia species. This report provides valuable insights into the chemotaxonomic significance of the Vachellia genus.Item Open Access Genetic and physiological responses to heat stress in Brassica napus(Frontiers, 2022-04-05) Kourani, Mariam; Mohareb, Fady; Rezwan, Faisal I.; Anastasiadi, Maria; Hammond, John P.Given the current rise in global temperatures, heat stress has become a major abiotic challenge affecting the growth and development of various crops and reducing their productivity. Brassica napus, the second largest source of vegetable oil worldwide, experiences a drastic reduction in seed yield and quality in response to heat. This review outlines the latest research that explores the genetic and physiological impact of heat stress on different developmental stages of B. napus with a special attention to the reproductive stages of floral progression, organogenesis, and post flowering. Several studies have shown that extreme temperature fluctuations during these crucial periods have detrimental effects on the plant and often leading to impaired growth and reduced seed production. The underlying mechanisms of heat stress adaptations and associated key regulatory genes are discussed. Furthermore, an overview and the implications of the polyploidy nature of B. napus and the regulatory role of alternative splicing in forming a priming-induced heat-stress memory are presented. New insights into the dynamics of epigenetic modifications during heat stress are discussed. Interestingly, while such studies are scarce in B. napus, opposite trends in expression of key genetic and epigenetic components have been identified in different species and in cultivars within the same species under various abiotic stresses, suggesting a complex role of these genes and their regulation in heat stress tolerance mechanisms. Additionally, omics-based studies are discussed with emphasis on the transcriptome, proteome and metabolome of B. napus, to gain a systems level understanding of how heat stress alters its yield and quality traits. The combination of omics approaches has revealed crucial interactions and regulatory networks taking part in the complex machinery of heat stress tolerance. We identify key knowledge gaps regarding the impact of heat stress on B. napus during its yield determining reproductive stages, where in-depth analysis of this subject is still needed. A deeper knowledge of heat stress response components and mechanisms in tissue specific models would serve as a stepping-stone to gaining insights into the regulation of thermotolerance that takes place in this important crop species and support future breeding of heat tolerant crops.Item Restricted An improved model for the analysis of combined antimicrobials: a replacement for the Chou‐Talalay combination index method(Wiley, 2017-10) Anastasiadi, Maria; Polizzi, Karen; Lambert, Ronald J. W.Aims To rationalise confusion in the literature concerning the analysis of combined antimicrobials, specifically to see if the combination index (CI) method of analysis was as rigorous as claimed. Methods & Results data from previous studies of the inhibition of Staphylococcus aureus by mixed antimicrobials were re-analysed using the CI method and a model which takes account of differences in the concentration exponents of individual antimicrobials. Conclusions The Chou-Talalay combination index method for the analysis of combined antimicrobials was found to be valid only in the specific cases where concentration exponents were equal. In these cases the CI method was found to be a function of the residuals of fitting the additive model to the observed data. Where concentration exponents were not equal the CI method was invalid, whereas the additive model took these differences into account. Significance and Impact of Study The CI method can be replaced wholly by the additive model described. The model allows simple regression to be used to analyse whole data sets and provides simple graphical output.Item Open Access Modelling the effect of combined antimicrobials: A base model for multiple-hurdles(Elsevier, 2017-04-14) Anastasiadi, Maria; Lambert, R. J.Combining antimicrobials to reduce microbial growth and to combat the potential impact of antimicrobial resistance is an important subject both in foods and in pharmaceutics. Modelling of combined treatments designed to reduce or eliminate microbial contamination in foods (microbiological predictive modelling) has become commonplace. Two main reference models are used to analyse mixtures: the Bliss Independence and the Loewe reference models (LRM). By using optical density to analyse the growth of Aeromonas hydrophila, Cronobacter sakazakii and Escherichia coli in combined NaCl/NaCl (a mock combination experiment) and combined NaCl/KCl experiments, previous models for combined antimicrobials in foods, based on the Bliss approach, were shown to be inconsistent and that models based on the LRM more applicable. The LRM was shown, however, to be valid only in the specific cases where the concentration exponents of all components in a mixture were identical. This is assured for a mock combination experiment but not for a true mixture. This, essentially, invalidates the LRM as a general reference model. A new model, based on the LRM but allowing for mixed exponents, was used to analyse the combined inhibition data, and concluded that the NaCl/KCl system gave the additive effect expected from literature studies. This study suggests the need to revise current models used to analyse combined effects.Item Open Access Phenolics from medicinal and aromatic plants: characterisation and potential as biostimulants and bioprotectants(MDPI, 2021-10-20) Kisiriko, Musa; Anastasiadi, Maria; Terry, Leon A.; Yasri, Abdelaziz; Beale, Michael Henry; Ward, Jane LouiseBiostimulants and bioprotectants are derived from natural sources and can enhance crop growth and protect crops from pests and pathogens, respectively. They have attracted much attention in the past few decades and contribute to a more sustainable and eco-friendly agricultural system. Despite not having been explored extensively, plant extracts and their component secondary metabolites, including phenolic compounds have been shown to have biostimulant effects on plants, including enhancement of growth attributes and yield, as well as bioprotectant effects, including antimicrobial, insecticidal, herbicidal and nematicidal effects. Medicinal and aromatic plants are widely distributed all over the world and are abundant sources of phenolic compounds. This paper reviews the characterisation of phenolic compounds and extracts from medicinal and aromatic plants, including a brief overview of their extraction, phytochemical screening and methods of analysis. The second part of the review highlights the potential for use of phenolic compounds and extracts as biostimulants and bioprotectants in agriculture as well as some of the challenges related to their use.Item Open Access Physiological and hormone data for the paper entitled 'Transcriptome and phytohormone changes associated with ethylene-induced onion bulb dormancy'(Cranfield University, 2020-06-15 17:29) del carmen Alamar Gavidia, Maria; Terry, Leon; Anastasiadi, Maria; Thompson, Andrew; Mohareb, Fady; G.N. Turnbull, Colin; M. Lopez-Cobollo, Rosa; H. Bennett: mhbennett@imperial.ac.uk, MarkUnderlying data for this onion bulb dormancy paper which includes: respiration rate, sprout elongation and sprout incidence; abscisic acid (ABA) and ABA-metabolites concentration; cytokinins concentration; and differentially expressed genes for ABA, ethylene and cytokinins pathways.Item Open Access Seasonal and temporal changes during storage affect quality attributes of green asparagus(Elsevier, 2019-09-18) Anastasiadi, Maria; Collings, Emma R.; Shivembe, Allan; Qian, Binghua; Terry, Leon A.Asparagus is a perennial crop with a short UK harvest season. Methods to extend the storage life of asparagus have proven difficult. To gain insight into the physiological (viz. colour, respiration rate, cutting energy, and stiffness measured using laser Doppler vibrometry), and biochemical (viz. sugars, ascorbic acid, and abscisic acid and its catabolites) changes throughout the UK season, two cultivars were harvested weekly and stored under shelf life conditions (7 °C). Results were compared to spears (plus one additional cultivar) cold stored (1 °C) for three weeks followed by one week of shelf life. Concentrations of sugar, abscisic acid (ABA) and catabolites at harvest were subject to seasonal variation, directly affecting storage potential. A generalised linear model with stepwise feature selection was applied to select the most important parameters for the prediction of total sugars and phaseic acid (PA). More favourable growing conditions at harvest increased sugars and lowered ABA content and catabolites, which coincided with better maintenance of spear quality during storage; including maintaining textural characteristics. Storage time had a negative impact on spear texture and sugar content, with cutting energy increasing and stiffness decreasing both during cold storage and subsequent shelf life. A partial shift in sugar biosynthesis occurred during shelf life increasing sucrose concentrations. Results suggest that the temporal flux in ABA and catabolites, and individual sugars could be used to model storage potential of asparagus spears.Item Open Access Transcriptome and phytohormone changes associated with ethylene-induced onion bulb dormancy(Elsevier, 2020-06-15) Alamar, M. Carmen; Anastasiadi, Maria; Lopez-Cobollo, Rosa M.; Bennett, Mark H.; Thompson, Andrew J.; Turnbull, Colin G. N.; Mohareb, Fady; Terry, Leon A.Control of dormancy and sprouting in onion bulbs is commercially important for postharvest management. Although ethylene application is sometimes used to extend dormancy, the underlying mechanisms regulating dormancy transition remain unclear. Since the sprout leaves emerge from the bulb baseplate, we used this tissue to assess the impact of ethylene treatment and storage time on the hormone profile and the transcriptome. Reads from 30 libraries were assembled and annotated, with 94,840 unigenes retained after filtering. The de novo transcriptome assembly was of high quality and continuity (N50: 1809 bp, GC content: 36.21 %), and was used to analyse differential expression and Gene Onotologies. Across two years, applied ethylene resulted in delayed dormancy break and reduced post-dormancy sprout vigour. Ethylene supplementation enhanced endogenous ethylene production and caused a transient climacteric-like increase in respiration. Significant changes in hormone and associated transcript profiles occurred through storage and in response to ethylene. In particular, abscisic acid (ABA) and its metabolite phaseic acid (PA) increased under ethylene during the longer dormancy period; however, cytokinin increases observed during storage appeared largely independent of ethylene treatment. Several hormone-related transcripts showed differential expression over time and/or in response to ethylene. Expression of ethylene biosynthesis (ACO), receptor (EIN4) and transcription factor (EIL3) genes were modified by ethylene, as were ABA biosynthesis genes such NCED, and cytokinin biosynthesis genes such as LOG and CKX. We conclude that ethylene substantially modifies expression of genes in several phytohormone pathways, and some of these changes may underlie the dormancy-extending effects of exogenous ethylene.Item Open Access Underpinning data "A comprehensive study of factors affecting postharvest disorder development in celery ".(Cranfield University, 2020-10-14 12:47) Anastasiadi, Maria; Falagan Sama, Natalia; Rossi, Simone; Terry, LeonThis dataset contains the data used for statistical analysis in the paper entitled "A comprehensive study of factors affecting postharvest disorder development in celery". Specifically it contains physiological and biochemical changes affecting quality, during shelf-life in celery plants from three different horticultural maturity stages and harvested in different seasons from Spain and the UK. Part of the samples were subjected to different postharvest treatments: 1-MCP application for 24 h followed by cold storage storage under continuous air, continuous ethylene application, and continuous air application (control). In addition, this dataset contain data recording the physiological and biochemical changes occurring during shelf-life in celery plants grown under deficit irrigation and harvested at different horticultural maturity stages. Physiological changes recorded include, respiration rate, objective colour, dry matter changes, browning development and pithiness development. Biochemical data include individual sugars, abscisic acid and its catabolites and chlorogenic acid. Also the data capture spatial differences along the celery plants (apical and basal regions).Item Open Access Underpinning data 'Investigating the role of abscisic acid and its catabolites on senescence processes in green asparagus under controlled atmosphere (CA) storage regimes'(Cranfield University, 2022-03-25 10:47) Anastasiadi, Maria; Collings, Emma; Terry, LeonThis dataset contains the data used for statistical analysis and predictive modelling in the paper entitled "Revisiting CA Protocols and Their Effect on Hormonal Flux in Asparagus". Specifically it contains physiological and biochemical changes in asparagus spears from three different cultivars during cold storage under different CA and DCA regimes and subsequent shelf-life. Physiological changes include moisture loss, respiration rate, cutting energy, objective colour. Biochemical data include individual sugars, abscisic acid and its catabolites. Also the data capture spatial differences along the asparagus spears (apical and basal regions).