Stomatal and Non-stomatal Effects of Salinity on Photosynthesis in Faba Beans (Vicia faba L.)

The effect of salinity (40 and 80 meq/1 NaCl) on stomatal conductance, chlorophyll content, ultrastructural damage and photosynthetic performance of six cultivars of faba beans ( Vicia faba L.) from different agroclimatic regions were investigated. Low levels of salinity (40 meq/1 NaCl) increased chlorophyll content in some cultivars but did not lead to simultaneous increase in photosynthesis (P). Increased salinity levels (80 meq/1 NaCl) decreased chlorophyll content and stomatal conductance. Ultrastructural damage was observed in sensitive cultivars even at low salinity levels. Based on the parameters investigated, there was no concrete evidence to suggest that the physiological processes of cultivars from arid and semi-arid regions are less affected under saline conditions as compared to cultivars from temperate regions. The results suggested increased salinity affects P not only due to its effect on stomatal closure but also due to other non-stomatal effects like ultrastructural damage and decrease in chlorophyll content below a threshold level.     

Effects of elevation and season on nutrient composition of leaves and green pods of Moringa stenopetala and Moringa oleifera

The baobab tree (Adansonia digitata L.) is of large socioeconomic importance. However, domesticated plant material of baobab is rarely available to African farmers, and very limited pre-breeding knowledge is available. To evaluate genetic differentiation between geographical origins we compared vigor and leaf morphology of trees from 17 West African and 13 East African provenances of baobab. Seedlings were grown and evaluated in a common garden test at Bamako, Mali. Germination was assessed and growth measured 3 and 12?months after germination. Leaf morphology (leaf length, leaflet number, petiole length and diameter and leaflet border) were assessed after 12?months. Significant differences between the provenances were observed for both growth rate and leaf morphology. West African provenances in general grew faster than East African provenances, but leaf characters did not reveal a particular geographic structure, and the correlations between geographic distances and multivariate Mahalanobis distances were not significant. The correlations between leaf morphological traits and climatic data were in general low at the provenance level. However, the number of leaflets was significantly higher for provenances from drier areas. Two years increment at a field site also varied significantly between the provenances, where West African provenances confirmed their tendency to higher growth rate. Still, trees are young and results regarding both growth data and leaf characteristics should be confirmed when the trees are closer to maturity.     

Water Quality Monitoring Using Remote Sensing and an Artificial Neural Network

In remotely located watersheds or large waterbodies, monitoring water quality parameters is often not feasible because of high costs and site inaccessibility. A cost-effective remote sensing-based methodology was developed to predict water quality parameters over a large and logistically difficult area. Landsat spectral data were used as a proxy, and a neural network model was developed to quantify water quality parameters, namely chlorophyll-a, turbidity, and phosphorus before and after ecosystem restoration and during the wet and dry seasons. The results demonstrate that the developed neural network model provided an excellent relationship between the observed and simulated water quality parameters. These correlated for a specific region in the greater Florida Everglades at R ²?>?0.95 in 1998?C1999 and in 2009?C2010 (dry and wet seasons). Moreover, the root mean square error values for phosphorus, turbidity, and chlorophyll-a were below 0.03?mg?L^?1, 0.5 NTU, and 0.17?mg?m^?3, respectively, at the neural network training and validation phases. Using the developed methodology, the trends for temporal and spatial dynamics of the selected water quality parameters were investigated. In addition, the amounts of phosphorus and chlorophyll-a stored in the water column were calculated demonstrating the usefulness of this methodology to predict water quality parameters in complex ecosystems.     

Reservoir sedimentation and its mitigating strategies: a case study of Angereb reservoir (NW Ethiopia)

Purpose  

The Angereb dam in northwestern Ethiopia was commissioned in 1997 to serve as a domestic water supply for 25 years. However, its sustainability is being threatened by rapid sedimentation. The overall objective of this study was to understand reservoir sedimentation in this tropical highland watershed and to propose its mitigating strategies that would contribute to the improved planning and management of reservoirs in similar regions.     

Increased number of large non‐atretic follicles and co‐dominance effects account for high litter sizes in Bonga sheep

To understand the ovarian basis for prolificacy of Bonga sheep, a total of 31 ewes were selected based on litter size (LS) records and divided into two groups: High Prolificacy (HP) (n = 20) with LS ≥ 2 and Low Prolificacy (LP) (n = 11) with LS = 1. At a synchronized estrus, follicular dynamics were determined using transrectal ultrasonography. Plasma estradiol concentrations were also monitored. In total 27 ewes were observed in estrus being 9/11 LP (82%) and 18/20 HP (90%). On the day of estrus (day 0), the mean number of large follicles was higher (p < .05) in HP (1.78 ± 0.19) than in LP (1.0 ± 0.28) ewes. Prior to estrus, more (p < .05) medium follicles were visible for HP compared to LP ewes. Plasma estradiol concentrations were higher in HP compared to LP ewes (18.91 ± 0.41 vs. 14.51 ± 0.65 pg/ml; p < .05) and similarly was ovulation number (2.3 ± 0.15 vs. 1.28 ± 0. 14; p < .05). Higher ovulation rates and litter size in Bonga sheep are evidenced by the previous presence of more large follicles and the existence of co‐dominance effects as most likely medium follicles are selected to ovulate.     

Variation in growth potential between hybrid clones of <Emphasis Type="Italic">Eucalyptus</Emphasis> trees in eastern South Africa

Growth of commercial forestry is highly dependent on the availability of fast-growing planting materials. Consequently, the efficient utilization of fast-growing plantations can greatly impact productivity. The objectives of this study were to evaluate variations in the growth potential of two clones and to estimate the average stem radial growth advantage of a fast-growing clone using data obtained from Sappi landholdings in eastern South Africa and a mixed modelling approach that permits the incorporation of covariance structure into the statistical model. During the first 2 years of growth, the stem radius of nine trees each of two clones was measured using dendrometer attached to the tree. A second-degree fractional polynomial model was chosen to show the functional relationship between stem radius and tree age. Growth of the two hybrid clones differed significantly. The Eucalyptus grandis × Eucalyptus urophylla clone grew faster than the E. grandis × camaldulensis clone, indicating better genetic potential for rapid growth and yield. This study can be considered as starting point to further compare the potential for rapid growth of several hybrid clones using the longitudinal data modelling approach.     

Suspended sediment load prediction of river systems: An artificial neural network approach

Information on suspended sediment load is crucial to water management and environmental protection. Suspended sediment loads for three major rivers (Mississippi, Missouri and Rio Grande) in USA are estimated using artificial neural network (ANN) modeling approach. A multilayer perceptron (MLP) ANN with an error back propagation algorithm, using historical daily and weekly hydroclimatological data (precipitation P_(t), current discharge Q_(t), antecedent discharge Q_(t−1), and antecedent sediment load SL_(t−1)), is used to predict the suspended sediment load SL_(t) at the selected monitoring stations. Performance of ANN was evaluated using different combinations of input data sets, length of record for training, and temporal resolution (daily and weekly data). Results from ANN model were compared with results from multiple linear regressions (MLR), multiple non-linear regression (MNLR) and Autoregressive integrated moving average (ARIMA) using correlation coefficient (R), mean absolute percent error (MAPE) and model efficiency (E). Comparison of training period length was also made (4, 3 and 2 years of training and 1, 2 and 3 years of testing, respectively). The model efficiency (E) and R² values were slightly higher for the 4 years of training and 1 year of testing (4 * 1) for Mississippi River, indifferent for Missouri and slightly lower for Rio Grande River. Daily simulations using Input 1 (P_(t), Q_(t), Q_(t−1), SL_(t−1)) and three years of training and two years of testing (3 * 2) performed better (R² and E of 0.85 and 0.72, respectively) than the simulation with two years of training and three years of testing (2 * 3) (R² and E of 0.64 and 0.46, respectively). ANN predicted daily values using Input 1 and 3 * 2 architecture for Missouri (R² = 0.97) and Mississippi (R² = 0.96) were better than those of Rio Grande (R² = 0.65). Daily predictions were better compared to weekly predictions for all three rivers due to higher correlation within daily than weekly data. ANN predictions for most simulations were superior compared to predictions using MLR, MNLR and ARIMA. The modeling approach presented in this paper can be potentially used to reduce the frequency of costly operations for sediment measurement where hydrological data is readily available.     

Effect of long-term heat exposure on peripheral concentrations of heat shock protein 70 (Hsp70) and hormones in laying hens with different genotypes

1. The effect of long-term, moderate heat stress (30 to 32 degrees C) on heat shock protein 70 (Hsp70) concentration in mononuclear blood cells and plasma concentrations of 3,5,3'-triiodothyronine (T3) and corticosterone in laying hens was investigated. 2. Three groups of 48 hens each (Ethopian line [Angete Melata, Na], New Hampshire [NH], F1 cross [Na x NH]) were divided into an experimental group (24 each) and a control group (24 each, ambient temperature 18 to 20 degrees C), respectively. All hens were kept in individual cages up to an age of 68 weeks and performance data were recorded. 3. Blood samples were taken from the wing vein of 12 hens from each group at weeks 22, 38, 51 and 65 (12 hens x 3 lines x 2 treatments). Mononuclear blood cells were isolated and Hsp70 concentrations were determined by Western Blot analysis with a monoclonal anti-Hsp70 antibody. T3 and corticosterone were measured with commercially available ELISA and RIA kits, respectively. 4. The moderate heat stress caused significantly increased Hsp70 levels compared with the control groups in weeks 51 and 65. However, the responses of the lines were not uniform at different ages. 5. In contrast, T3 levels were significantly decreased in stressed birds regardless of line and age. There was no effect of treatment and line on corticosterone levels during the experimental period. 6. Our results indicate that Hsp70 and T3 levels are affected by mild heat stress applied over a long period but are both involved in independent mechanisms of acquisition of thermotolerance. Further investigations are necessary to clarify whether the observed differences in Hsp70 response between the genotypes are indicators for differences in thermotolerance.