This study was executed to investigate the potential of agar-agar, a nontoxic and non-degradable gelling agent, as a promising coating agent to improve and protect banana fruit against fungal postharvest diseases i.e., crown, finger, neck and flower end rots which are caused by fungal isolates of Colletotrichum musae and Fusarium moniliforme. Coated-ba-nana fruit samples with different concentrations of agar-agar suspension particularly at 2.0 g · l−1 exhibited a significant reduction in incidence and severity of postharvest diseases compared to untreated fruit. Banana fruits dipped in agar suspension at 2.0 g · l−1 for 5, 10 and 15 min showed significant reduction in disease incidence and severity. Moreover, application of agar suspension as a coating agent at 2.0 g · l−1 significantly decreased weight loss (%), firmness loss (%), and soluble solid concentration of banana fruit for 15 days at 25 ± 2°C. Scanning electron microscopy observation confirmed that the fruit coated with agar colloid at 2.0 g · l−1 had significantly fewer cracks and showed smoother surfaces than untreated fruit. This explains the quality improvement in agar-coated fruit compared to uncoated fruit. Overall, agar colloid, a safe coating agent, could be used to protect banana fruit against postharvest rot diseases and extend fruit storage life during ripening and storage.
This work was carried out during two successive seasons (2016 and 2017) on cucumber fruits from a plastic greenhouse and from open field cultivation in El Gharbeia and El Giza Governorates, Egypt. Isolation trials from spoilage fruit samples of plastic greenhouse cultivation recorded high frequency of Alternaria tenusinium, Fusarium spp. and Pleospora alli. The most common fungi of rotten cucumber fruits from an open field were Galactomyces spp. and Fusarium spp. Pathogenicity tests proved that, Fusarium solani from El-Gharbeia followed by A. tenusinium from El-Giza were the most frequent isolates responsible for rot of cucumber fruits from plastic greenhouse cultivation. Moreover, the most frequent isolates causing postharvest disease of cucumber fruits of the open field were Galactomyces candidium from El-Giza followed by Geotrichum sp. and F. fujikuroi from El-Gharbeia Governorates, respectively. This is the first report of several fungi causing postharvest fruit rot disease of cucumber i.e., G. candidium, Geotrichum sp., A. tenusinium, P. alli and Fusarium spp. (F. fujikuroi, F. verticiolides, F. solani, F. geraminearium and Fusarium incarnatum). Fungal isolates were identified according to cultural, morphological and molecular characterization based on sequencing of internal transcribed spacer1 (ITS1). All the ITS nucleotide sequences of fungi were applied and conserved in GenBank.
Rockburst is a common engineering geological hazard. In order to evaluate rockburst liability in kimberlite at an underground diamond mine, a method combining generalized regression neural networks (GRNN) and fruit fly optimization algorithm (FOA) is employed. Based on two fundamental premises of rockburst occurrence, depth, σθ, σc, σt, B1, B2, SCF, Wet are determined as indicators of rockburst, which are also input vectors of GRNN model. 132 groups of data obtained from rockburst cases from all over the world are chosen as training samples to train the GRNN model; FOA is used to seek the optimal parameter σ that generates the most accurate GRNN model. The trained GRNN model is adopted to evaluate burst liability in kimberlite pipes. The same eight rockburst indicators are acquired from lab tests, mine site and FEM model as test sample features. Evaluation results made by GRNN can be confirmed by a rockburst case at this mine. GRNN do not require any prior knowledge about the nature of the relationship between the input and output variables and avoid analyzing the mechanism of rockburst, which has a bright prospect for engineering rockburst potential evaluation.