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This study was done to indicate the activity of secondary metabolites of cyanophyta algal extracts for Anabaena Azolla which live in Azolla plant in Egypt and to study the effective of secondary metabolites in An.Azolla extracts (cold water and methanol extracts) to inhibition species of fungi (Fusarium oxysporum, penicillium expansum, Aspergillus niger and candida albicans) also used of HPLC analysis to detected some of active secondary metabolites was done only for methanol extracts also to preliminary statements that used of two extracts of blue green alga Anabaena Azolla. The role of An.Azolla extracts to inhibition growth of these fungi was detected through measured diameter of inhibition zone diameters were, 16.58, 11.42, 11.0 & 11.0 mm in case of Fusarium oxysporum, Penicillium expansum, Aspergillus niger and candida albicans respectively, but aqueous extract give inhibition zone were 18.15, 14.13, 14.0 & 13.0mm respectively. and the results showed these extracts had high correlation ratio and fungi shows high sensitivity to these extract. The mode of mechanism action to inhibition was on fungi cell wall by inhibition active enzymes, excelled treatment for cold water extract. The most important active compounds had been detected in HPLC were phenolic compounds and flavonoids compounds these all compounds detected specially in methanol extract of An .Azolla. The experiment has been conducted under temperature and artificial illumination at growth room of Soilless Culture Laboratory, Sadat city University, Egypt. The results showed that green fodder can be produced in 8 days using hydroponic technique. Trays treated with Azolla gave more green fresh yield (11.8 kg/tray) than untreated ones (7.2 kg/tray). Adding Azolla increased protein content and the percentages of N, P, K by 28.7% and 0.98, 0.82, 0.70 %, respectively, as compared to no addition of Azolla. Zero disease incidences were achieved with treated by Azolla as compared to 26.0 % with those untreated by Azolla. It could be concluded from this study that adding Azolla to hydroponic barley forage production improved green forage yield and its chemical analysis and free from root rot fungi.

The primary issues in collecting biochemical information in a large area using chemical laboratory procedures are low throughput, hard work, time-consuming, and requiring several samples. Thus, real-time and precise estimation of biochemical variables of various fruits using a proximal remote sensing based on spectral reflectance is critical for harvest time, artificial ripening, and food processing, which might be beneficial economically and ecologically. The main goal of this study was to assess the biochemical parameters of banana fruits such as chlorophyll a (Chl a), chlorophyll b (Chl b), respiration rate, total soluble solids (TSS), and firmness using published and newly developed spectral reflectance indices (SRIs), integrated with machine learning modeling (Artificial Neural Networks; ANN and support vector machine regression; SVMR) at different ripening degrees. The results demonstrated that there were evident and significant differences in values of SRIs at different ripening degrees, which may be attributed to the large variations in values of biochemical parameters. The newly developed two-band SRIs are more effective at measuring different biochemical parameters. The SRIs that were extracted from the visible (VIS), near-infrared (NIR), and their combination showed better R2 with biochemical parameters. SRIs combined with ANN and SVMR would be an effective method for estimating five biochemical parameters in the calibration (Cal.) and validation (Val.) datasets with acceptable accuracy. The ANN-TSS-SRI-13 model was built to determine TSS with greater performance expectations (R2 = 1.00 and 0.97 for Cal. and Val., respectively). Furthermore, the model ANN-Firmness-SRI-15 was developed for determining firmness, and it performed better (R2 = 1.00 and 0.98 for Cal. and Val., respectively). In conclusion, this study revealed that SRIs and a combination approach of ANN and SVMR models would be a useful and excellent tool for estimating the biochemical characteristics of banana fruits.

Barley (Hordeum vulgare L.) matures faster and more evenly under a hydroponic system than a conventional soil based system. Supplemented Azolla (Azolla Pinnata) to hydroponic system as an aquatic free floating fern provides protein with all essential amino acid which is required for animal nutrition. So, this investigation aimed to evaluate green fodder production and inhibition of root rot fungi under hydroponic conditions for barley. The experiment has been conducted under temperature and artificial illumination at growth room of Soilless Culture Laboratory, Sadat city University, Egypt. The results showed that green fodder can be produced in 8 days using hydroponic technique. Trays treated with Azolla gave more green fresh yield (11.8 kg/tray) than untreated ones (7.2 kg/tray). Adding Azolla increased of protein, N, P and K content percentages by 28.7, 0.98, 0.82 and 0.70 %, respectively, as compared to no addition of Azolla. There is no disease incidences were achieved with treated by Azolla as compared to 26.0 % with those untreated by Azolla. It could be concluded from this study that adding Azolla to hydroponic barley forage production improved green forage yield and its chemical analysis.