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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.

ATER stress is one of the most important abiotic stresses that …….....may limit agriculture production worldwide. This work was carried out on mango trees (Mangifera indica L.) to study the effect of exposure to different levels of drought stress (65, 75, 85 and 100 % of full irrigation requirements), in addition, to evaluating the role of using some plant growth promoting rhizobacteria (PGRP); such as Azospirillum and Azotobacter, in alleviating drought-induced changes. Physiological and biochemical changes were determined in mango leaves after two seasons of different treatments. Results indicated that membrane stability, photosynthetic pigments and insoluble sugar contents were significantly decreased with increasing drought levels, while electrolyte leakage, soluble sugars, total carbohydrates and proline content were sharply increased compared to control. Lipid peroxidation level and the activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) enzymes showed progressive increases with drought levels. Application of biofertilizers may be effective in alleviating the adverse effect of water stress. Bio-fertilizers caused marked increase in photosy nthetic pigments and carbohydrate contents and a decrease in proline content compared to control. Keywords: Drought, Water stress, PGPR, Mangifera indica,Chlorophyll, Antioxidant enzymes, Proline.Abbreviations: PGRP, plant growth promoting rhizobacteria; ROS, reactive oxygen species; SOD, superoxide dismutase; POD, peroxidase; CAT, catalase; EL, Electrolyte leakage; M SI, membrane stability index; DW, dry weight; FM , fresh mass; M DA, M alondialdehyde; S, Azospirillum; B, Azotobacter.Countries in arid and semi-arid regions suffer from water shortage for agriculture usage. Water stress affects plant growth and productivity as it causes various physiological and biochemical changes including hormonal and nutritional imbalance, ion toxicity, desiccation, abscission, senescence and susceptibility to diseases (Nadeem et al., 2014). Also, drought can lead to pigment degradation (Hendry et al., 1987) causing irreversible damage to the photosynthetic apparatus (Clarke et al., 1996). R.R. KHALIL et al. Egypt. J. Bot., Vol. 56, No. 2 (2016) 472On the other hand, water stress can cause rapid damage to plant cells membrane due to an uncontrolled enhancement of reactive oxygen species (ROS) (Moussa and Abdel-Aziz, 2008). Excess accumulation of ROS may initiate destructive oxidative processes such as lipid peroxidation and ch lorophyll bleaching as well as oxidation of proteins, deoxyribonucleic acid and carbohydrates (Ashraf, 2009). The degree of damage caused by ROS depends on the balance between the production of ROS and its removal by efficient antioxidant scavenging system which includes nonenzymic and enzymic antioxidants (Azooz et al., 2009). The enzymic antioxidants include superoxide dismutase (SOD), catalase (CAT), guaiacol peroxidase and enzymes of ascorbateglutahione (AsA-GSH) cycle such as ascorbate peroxidase, monodehydroascorbate redu...