Adel M. Ghoneim

Exposure of banana plants, one of the most important tropical and subtropical plants, to low temperatures causes a severe drop in productivity, as they are sensitive to cold and do not have a strong defense system against chilling. Therefore, this study aimed to improve the growth and resistance to cold stress of banana plants using foliar treatments of chitosan nanoparticles (CH-NPs). CH-NPs produced by nanotechnology have been used to enhance tolerance and plant growth under different abiotic stresses, e.g., salinity and drought; however, there is little information available about their effects on banana plants under cold stress. In this study, banana plants were sprayed with four concentrations of CH-NPs—i.e., 0, 100, 200, and 400 mg L−1 of deionized water—and a group that had not been cold stressed or undergone CH-NP treatment was used as control. Banana plants (Musa acuminata var. Baxi) were grown in a growth chamber and exposed to cold stress (5 °C for 72 h). Foliar application of CH-NPs caused significant increases (p < 0.05) in most of the growth parameters and in the nutrient content of the banana plants. Spraying banana plants with CH-NPs (400 mg L−1) increased the fresh and dry weights by 14 and 41%, respectively, compared to the control. A positive correlation was found between the foliar application of CH-NPs, on the one hand, and photosynthesis pigments and antioxidant enzyme activities on the other. Spraying banana plants with CH-NPs decreased malondialdehyde (MDA) and reactive oxygen species (ROS), i.e., hydrogen peroxide (H2O2), hydroxyl radicals (•OH), and superoxide anions (O2•−). CH-NPs (400 mg L−1) decreased MDA, H2O2, •OH, and O2•− by 33, 33, 40, and 48%, respectively, compared to the unsprayed plants. We hypothesize that CH-NPs increase the efficiency of banana plants in the face of cold stress by reducing the accumulation of reactive oxygen species and, in consequence, the degree of oxidative stress. The accumulation of osmoprotectants (soluble carbohydrates, proline, and amino acids) contributed to enhancing the cold stress tolerance in the banana plants. Foliar application of CH-NPs can be used as a sustainable and economically feasible approach to achieving cold stress tolerance.

Abstract. The discharge of untreated waste water in Zefta drain and drain no. 5 is becoming a problem for many farmers in the El-Mahla El-Kobra area, Egypt. The discharged water contains high levels of contaminants considered hazardous to the ecosystem. Some plants, soil, water, and sediment samples were collected from the El-Mahla El-Kobra area to evaluate the contamination by heavy metals. The results showed that the heavy metals, pH, sodium adsorption ratio (SAR), biochemical oxygen demand (BOD), and chemical oxygen demand (COD) in the water of Zefta drain and drain no. 5 exceeded permissible limits for irrigation. In rice and maize shoots grown in soils irrigated by contaminated water from Zefta drain and drain no. 5, the bioaccumulation factors for Cd, Pb, Zn, Cu, and Mn were higher than 1.0. The heavy metals content of irrigated soils from Zefta drain and drain no. 5 exceeded the upper limit of background heavy metals. In this study, the mean contaminant factor values of the drain no. 5 sediments revealed that Zn, Mn, Cu, Cd, Pb, and Ni > 6, indicating very high contamination. The bioaccumulation coefficient values of Cynodon dactylon, Phragmites australis, and Typha domingensis aquatic plants growing in Zefta drain are high. These species can be considered as hyperaccumulators for the decontamination of contaminated water.

Abstract Application of appropriate level of nitrogen fertilization is a major objective to increase nitrogen use efficiency by rice varieties. Field experiments were conducted during 2016 and 2017 growing seasons to evaluate the efficiency of varying nitrogen fertilizer rates on growth and yield parameters, along with nitrogen use efficiency of some newly released rice varieties (Sakha 108) and some promising lines GZ9399-4-1-1-3-2-2, GZ10101- 5-1-1-1 and GZ10154-3-1-1-1. Five nitrogen levels (i.e. 0, 55, 110, 165 and 220 kg N ha-1) were used. The results from both growing seasons indicated that, Sakha 108 recorded the highest grain yield while GZ10154 and GZ10101 recorded the lowest grain yields. A linear increase in grain yield was observed with continuous rate increase of nitrogen from 0 to 220 kg ha-1, while 220 kg N ha-1 treatment showed maximum grain yield followed by 165 kg N ha-1, with control as minimum. Agronomic nitrogen use efficiency (AE) for studied rice genotypes varied significantly, and ranged from 3.63 to 32.9 and from 2.72 to 34.12 kg grain yield produced per kg of nitrogen applied in 2016 and 2017 respectively. Across N levels, GZ9399 recorded the highest values of AE for the nitrogen fertilizer rate of 165 kg N ha-1 in both seasons.

Monitoring and managing water quality parameters (WQPs) in water bodies (e.g., lakes) on a large scale using sampling-point techniques is tedious, laborious, and not highly representative. Hyperspectral and data-driven technology have provided a potentially valuable tool for the precise measurement of WQPs. Therefore, the objective of this work was to integrate WQPs, derived spectral reflectance indices (published spectral reflectance indices (PSRIs)), newly two-band spectral reflectance indices (NSRIs-2b) and newly three-band spectral indices (NSRIs-3b), and artificial neural networks (ANNs) for estimating WQPs in Lake Qaroun. Shipboard cruises were conducted to collect surface water samples at 16 different sites throughout Lake Qaroun throughout a two-year study (2018 and 2019). Different WQPs, such as total nitrogen (TN), ammonium (NH4+), orthophosphate (PO43−), and chemical oxygen demand (COD), were evaluated for aquatic use. The results showed that the highest determination coefficients were recorded with the NSRIs-3b, followed by the NSRIs-2b, and then followed by the PSRIs, which produced lower R2 with all tested WQPs. The majority of NSRIs-3bs demonstrated strong significant relationships with three WQPs (TN, NH4+, and PO43−) with (R2 = 0.70 to 0.77), and a moderate relationship with COD (R2 = 0.52 to 0.64). The SRIs integrated with ANNs would be an efficient tool for estimating the investigated four WQPs in both calibration and validation datasets with acceptable accuracy. For examples, the five features of the SRIs involved in this model are of great significance for predicting TN. Its outputs showed high R2 values of 0.92 and 0.84 for calibration and validation, respectively. The ANN-PO43−VI-17 was the highest accuracy model for predicting PO43− with R2 = 0.98 and 0.89 for calibration and validation, respectively. In conclusion, this research study demonstrated that NSRIs-3b, alongside a combined approach of ANNs models and SRIs, would be an effective tool for assessing WQPs of Lake Qaroun.