Research Articles (Horticulture)

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    Optimization of gum arabic and starch-based edible coatings with lemongrass oil using response surface methodology for improving postharvest quality of whole “wonderful” pomegranate fruit
    (MDPI, 2021-04-12) Kawhena, Tatenda Gift; Opara, Umezuruike Linus; Fawole, Olaniyi Amos
    The effects of edible coatings based on gum arabic (GA) (0.5–1.5%), maize starch (MS) (0.5–1.5%), lemongrass oil (LO) (2–4%), and glycerol (GC) (0.5–1%) developed using response surface methodology (RSM) on “Wonderful” pomegranate fruit were studied. After 42 days of storage (5 1 C, 95 2% RH) and 5 days at ambient temperature (20 0.2 C and 60 10% RH), whole fruit were evaluated for weight loss (%) and pomegranate juice (PJ) for total soluble solids ( Brix), titratable acidity (% Citric acid), and antioxidant capacity. The optimization procedure was done using RSM and the response variables were mainly influenced by the concentrations of MS and GA. The optimized coating consisted of GA (0.5%), MS (0.5%), LO (3%), and GC (1.5%) with desirability of 0.614 (0—minimum and 1—maximum). The predicted values of response variables, for the coating were weight loss (%) = 5.51, TSS ( Brix) = 16.45, TA (% Citric acid) = 1.50, and antioxidant capacity (RSA = 58.13 mM AAE/mL PJ and FRAP = 40.03 mM TE/mL PJ). Therefore, the optimized coating formulation is a potential postharvest treatment for “Wonderful” pomegranate to inhibit weight loss and maintain overall quality during storage and shelf-life.
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    Probabilistic risk-based model for the assessment of Phyllosticta citricarpa-infected citrus fruit and illicit plant material as pathways for pathogen introduction and establishment
    (Elsevier Ltd., 2020) Gottwald, T.R.; Taylor, E.L.; Amorim, L.; Bergamin-Filho, A.; Bassanezi, R.B.; Silva, G.J.; Fogliata, G.; Fourie, P.H.; Graham, J.H.; Hattingh, V.; Kriss, A.B.; Luo, W.; Magarey, R.D.; Schutte, G.C.; Sposito, M.B.
    Citrus Black Spot (CBS), caused by the ascomycete, Phyllosticta citricarpa, is a fruit, foliar, and twig spotting fungal disease affecting the majority of commercial cultivars of citrus. The disease causes cosmetic lesions, may cause fruit drop and P. citricarpa is considered a quarantine pathogen by some countries, impacting domestic and international trade of citrus fruit. Regulatory requirements affecting fruit trade exist even though there is no documented case of disease spread via infected fruit into previously disease-free areas. To clarify the risk of fruit as a potential pathway for the spread of CBS, we developed a quantitative, probabilistic risk assessment model. The model provides an assessment of all steps in the fruit pathway, including production, packinghouse handling, transportation, export-import distribution channels, and consumer endpoints. The model is stochastic and uses Monte Carlo simulation to assess the risk of P. citricarpa moving through all steps in the pathway. We attempted to use all available literature and information to quantitate risk at each point in the potential pathway and by sequentially linking all steps to determine the overall quantitative risk. In addition, we assessed climatological effects on incidence of diseased fruit at production sites and on fungal reproduction and infection, as well as criteria for establishment at endpoints. We examined ten case studies between exporting and importing locations/countries. Model results indicated fruit to be an epidemiologically insignificant means for CBS spread, even between producing countries where CBS occurs and CBS-free importing countries with disease-conducive climates. We created a second model to examine the introduction of infected plant material from countries where CBS occurs. This model demonstrated significant probability of introduction via such infected material. However, pathogen establishment and disease development was still restricted only to areas with conducive climatological conditions. We created a tool to quantitatively explore the viability of various potential pathways via combinations of CBS-present production sites and corresponding pathway endpoints, including environments conducive and non-conducive to CBS. The tool is provided to aid decision makers on phytosanitary risk relative to international trade of citrus fruit.
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    Classification learning of latent bruise damage to apples using shortwave infrared hyperspectral imaging
    (MDPI, 2021-07-22) Nturambirwe, Jean Frederic Isingizwe; Perold, Willem Jacobus; Opara, Umezuruike Linus
    Bruise damage is a very commonly occurring defect in apple fruit which facilitates disease occurrence and spread, leads to fruit deterioration and can greatly contribute to postharvest loss. The detection of bruises at their earliest stage of development can be advantageous for screening purposes. An experiment to induce soft bruises in Golden Delicious apples was conducted by applying impact energy at different levels, which allowed to investigate the detectability of bruises at their latent stage. The existence of bruises that were rather invisible to the naked eye and to a digital camera was proven by reconstruction of hyperspectral images of bruised apples, based on effective wavelengths and data dimensionality reduced hyperspectrograms. Machine learning classifiers, namely ensemble subspace discriminant (ESD), k-nearest neighbors (KNN), support vector machine (SVM) and linear discriminant analysis (LDA) were used to build models for detecting bruises at their latent stage, to study the influence of time after bruise occurrence on detection performance and to model quantitative aspects of bruises (severity), spanning from latent to visible bruises. Over all classifiers, detection models had a higher performance than quantitative ones. Given its highest speed in prediction and high classification performance, SVM was rated most recommendable for detection tasks. However, ESD models had the highest classification accuracy in quantitative (>85%) models and were found to be relatively better suited for such a multiple category classification problem than the rest.
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    Fatty acid composition, bioactive phytochemicals, antioxidant properties and oxidative stability of edible fruit seed oil : effect of preharvest and processing factors
    (Elsevier, 2020-09) Kaseke, Tafadzwa; Opara, Umezuruike Linus; Fawole, Olaniyi Amos
    Fruit seed is a by-product of fruit processing into juice and other products. Despite being treated as waste, fruit seed contains oil with health benefits comparable or even higher than the conventional seed oil from field crops. In addition to essential fatty acids, the fruit seed oil is a rich source of bioactive compounds such as tocopherols, carotenoids, flavonoids, phenolic acids and phytosterols, which have been implicated in the prevention of chronic and degenerative diseases such as cancer, diabetes and cardiovascular diseases. The emerging potential of fruit seed oil application in food and nutraceuticals has prompted researchers to study the effect of preharvest and processing factors on the seed oil quality with respect to nutritional qualities, antioxidant compounds and properties. Herein, the effect of cultivar, fruit-growing region, seeds pretreatment, seeds drying and seed oil extraction on tocopherols, polyphenols, phytosterols, carotenoids, fatty acids, antioxidant activity and oxidative stability of the fruit seed oil is critically discussed. Understanding the influence of these factors on seed oil bioactive phytochemicals, nutritional qualities and antioxidant properties is critical not only for genetically improving the oilseeds plants with desired characteristics, but also in seed oil processing and value addition. Therefore, preharvest and processing factors are essential considerations when determining the application of fruit seed oil.
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    Water use of Prosopis juliflora and its impacts on catchment water budget and rural livelihoods in Afar Region, Ethiopia
    (Nature, 2021) Shiferaw, Hailu; Alamirew, Tena; Dzikiti, Sebinasi; Bewket, Woldeamlak; Zeleke, Gete; Schaffner, Urs
    Dense impenetrable thickets of invasive trees and shrubs compete with other water users and thus disrupt ecosystem functioning and services. This study assessed water use by the evergreen Prosopis juliflora, one of the dominant invasive tree species in semi-arid and arid ecosystems in the tropical regions of Eastern Africa. The objectives of the study were to (1) analyze the seasonal water use patterns of P. juliflora in various locations in Afar Region, Ethiopia, (2) up-scale the water use from individual tree transpiration and stand evapotranspiration (ET) to the entire invaded area, and 3) estimate the monetary value of water lost due to the invasion. The sap flow rates of individual P. juliflora trees were measured using the heat ratio method while stand ET was quantified using the eddy covariance method. Transpiration by individual trees ranged from 1–36 L/day, with an average of 7 L of water per tree per day. The daily average transpiration of a Prosopis tree was about 3.4 (± 0.5) mm and the daily average ET of a dense Prosopis stand was about 3.7 (± 1.6) mm. Using a fractional cover map of P. juliflora (over an area of 1.18 million ha), water use of P. juliflora in Afar Region was estimated to be approximately 3.1–3.3 billion m3/yr. This volume of water would be sufficient to irrigate about 460,000 ha of cotton or 330,000 ha of sugar cane, the main crops in the area, which would generate an estimated net benefit of approximately US$ 320 million and US$ 470 million per growing season from cotton and sugarcane, respectively. Hence, P. juliflora invasion in the Afar Region has serious impacts on water availability and on the provision of other ecosystem services and ultimately on rural livelihoods.