Browsing by Author "Opara, Umezuruike Linus"

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    Investigating the involvement of ABA, ABA catabolites and cytokinins in the susceptibility of ‘Nules Clementine’ mandarin to rind breakdown disorder
    (Wiley, 2019-02-14) Magwaza, Lembe Samukelo; Alamar, M. Carmen; Tesfay, Samson Zeray; Mditshwa, Asandas; Opara, Umezuruike Linus; Terry, Leon A.
    Abstract BACKGROUND Nules Clementine’ mandarin was used to investigate the potential involvement of endogenous plant hormones in mediating the citrus fruit susceptibility to rind breakdown disorder (RBD). The effect of light exposure (viz. canopy position and bagging treatments) on the endogenous concentration of ABA, 7’hydroxy‐abscisic acid (7‐OH‐ABA), ABA‐glucose ester (ABA‐GE) and dihydrophaseic acid (DPA), and t‐zeatin was tested using four preharvest treatments: outside, outside bagged, inside and inside bagged. Phytohormones concentration was evaluated during 9 weeks of postharvest storage at 8 °C. RESULTS The shaded fruit inside the canopy had the highest RBD score (0.88) at the end of postharvest storage, while sun‐exposed fruit had the lowest score (0.12). Before storage, ABA concentration was lowest (462.8 μg kg‐1) for inside fruit, and highest in outside bagged fruit (680.5 μg kg‐1). Although ABA concentration suddenly increased from the third week, reaching a maximum concentration of 580 μg kg‐1 at week 6 in fruit from inside position, it generally reduced 1.6‐fold ranging from 240.52 to 480.65 μg kg‐1 throughout storage. The increase of 7‐OH‐ABA was more prominent in fruit from inside canopy. Overall, the concentration of ABA‐GE increased 3‐fold with storage time. DPA concentration of bagged fruit from inside canopy position was significantly higher compared to outside fruit. The lower ABA‐GE and higher DPA concentration in inside bagged fruit throughout storage also coincided with higher RBD. CONCLUSION The strong positive correlations between 7‐OH‐ABA, DPA and RBD incidence demonstrated that these ABA catabolites could be used as biomarkers for fruit susceptibility to the disorder.
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    Plants as an alternative to the use of chemicals for crop protection against biotic threats: trends and future perspectives
    (Springer , 2024-12) Aremu, Adeyemi Oladapo; Omogbene, Temitope Olorunyomi; Fadiji, Tobi; Lawal, Ibraheem Oduola; Opara, Umezuruike Linus; Fawole, Olaniyi Amos
    This review entails a critical appraisal on the potential of plants as alternatives to synthetic chemicals for crop protection, aligning with the global shift towards green-based approaches in agriculture. Utilising a defined set of inclusion and exclusion criteria, 235 papers were extracted from Scopus. These articles were analyzed to address specific research questions related to plant-based biocontrol methods. Approximately 25% of the literature was published in journals such as "Industrial Crops and Products", "Journal of Agricultural and Food Chemistry", "Pest Management Science", and "Frontiers in Microbiology". Thematic analysis identified core focus areas, including the chemical properties of antifungal agents, bioactive compounds, environmental protection, and the use of fungicides. Italy and China emerged as countries with the most represented authors, while China, India, and USA led in scientific production, corresponding authors' publications, and citation impact. We identified 91 plant species from 28 families, notably from the Lamiaceae, with strong potential as biocontrol agents. The most promising plants were Platycladus orientalis (L.) Franco, Mentha piperita L., Foeniculum vulgare L., Coriandrum sativum L., and Allium ascalonicium L. This study offers valuable insights and practical applications in the field of plant-based biocontrol, thereby underscoring the relevance and efficacy of green-based approaches in contemporary agricultural practices. There is an increasing scientific interest in sustainable crop protection strategies and the potential of plant-based biocontrol agents in addressing biotic stresses in crops. Overall, this review contributes to the understanding of plant-based biocontrol for crop protection, providing a foundation for further research and application in sustainable agriculture.
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    Prediction of ‘Nules Clementine’ mandarin susceptibility to rind breakdown disorder using Vis/NIR spectroscopy
    (Elsevier, 2012-07-15) Magwaza, Lembe Samukelo; Opara, Umezuruike Linus; Terry, Leon A.; Landahl, Sandra; Cronje, Paul J.; Nieuwoudt, Helene; Mouazen, Abdul Mounem; Saeys, Wouter; Nicolai, Bart M.
    The use of diffuse reflectance visible and near infrared (Vis/NIR) spectroscopy was explored as a non-destructive technique to predict ‘Nules Clementine’ mandarin fruit susceptibility to rind breakdown (RBD) disorder by detecting rind physico-chemical properties of 80 intact fruit harvested from different canopy positions. Vis/NIR spectra were obtained using a LabSpec® spectrophotometer. Reference physico-chemical data of the fruit were obtained after 8 weeks of storage at 8 °C using conventional methods and included RBD, hue angle, colour index, mass loss, rind dry matter, as well as carbohydrates (sucrose, glucose, fructose, total carbohydrates), and total phenolic acid concentrations. Principal component analysis (PCA) was applied to analyse spectral data to identify clusters in the PCA score plots and outliers. Partial least squares (PLS) regression was applied to spectral data after PCA to develop prediction models for each quality attribute. The spectra were subjected to a test set validation by dividing the data into calibration (n = 48) and test validation (n = 32) sets. An extra set of 40 fruit harvested from a different part of the orchard was used for external validation. PLS-discriminant analysis (PLS-DA) models were developed to sort fruit based on canopy position and RBD susceptibility. Fruit position within the canopy had a significant influence on rind biochemical properties. Outside fruit had higher rind carbohydrates, phenolic acids and dry matter content and lower RBD index than inside fruit. The data distribution in the PCA and PLS-DA models displayed four clusters that could easily be identified. These clusters allowed distinction between fruit from different preharvest treatments. NIR calibration and validation results demonstrated that colour index, dry matter, total carbohydrates and mass loss were predicted with significant accuracy, with residual predictive deviation (RPD) for prediction of 3.83, 3.58, 3.15 and 2.61, respectively. The good correlation between spectral information and carbohydrate content demonstrated the potential of Vis/NIR as a non-destructive tool to predict fruit susceptibility to RBD.