Background: There is a growing interest in the green synthesis of silver nanoparticles (AgNPs) using plant extract because the technique is cost effective, eco-friendly and environmentally benign. This is phasing out the use of toxic and hazardous chemical earlier reported. Tithonia diversifolia is a wild sunflower that grows widely in the western part of Nigeria with a proven medicinal benefit. However, several studies carried out have left doubts on the basic operational parameters needed for the green synthesis of AgNPs. The objective of this work was to carry out green synthesis of AgNPs using T. diversifolia extract via an eco-friendly route through optimization of various operational parameters, characterization, and antimicrobial studies. Method: Green synthesis of TD-AgNPs was done via bottom-up approach through wet chemistry technique using environmentally benign T. diversifolia plant extract as both reducing and stabilizing agent. Phytochemical Screening of the TD plant extract was carried out. Experimental optimization of various operational parameters—reaction time, concentration, volume ratio, and temperature was investigated. TD-AgNPs were characterized by UV–Vis spectroscopy, FTIR Spectroscopy, SEM/energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and transmission electron microscopy (TEM). Antimicrobial studies against multi drug resistant microorganisms (MDRM) were studied using the agar well diffusion method. Results: This study reveals the importance of various operational parameters in the synthesis of TD-AgNPs. Excellent surface plasmon resonance peaks (SPR) were obtained at optimum experimental factors of 90 min reaction time under room temperature at 0.001M concentration with the volume ratio of 1:9 (TD extract:Ag ion solution). The synthesis was monitored using UV–Vis and maximum wavelength obtained at 430 nm was due to SPR. The morphology and elemental constituents obtained by TEM, SEM, and EDX results revealed a spherical shape of AgNPs with prominent peak of Ag at 3.0 kV in EDX spectrum. The crystallinity nature was confirmed by XRD studies. FTIR analysis proved presence of biomolecules functioning as reducing, stabilizing, and capping agents. These biomolecules were confirmed to be flavonoid, triterpenes, and saponin from phytochemical screening. The antimicrobial studies of TD-AgNPs were tested against MDRM—Escherichia coli, Salmonella typhi, Salmonella enterica, and Bacillus subtilis. Discussion: The variation of reaction time, temperature, concentration, and volume ratio played substantive and fundamental roles in the synthesis of TD-AgNPs. A good dispersion of small spherical size between 10 and 26 nm was confirmed by TEM and SEM. A dual action mechanism of anti-microbial effects was provided by TD-AgNPs which are bactericidal and membrane-disruption. Based on the antimicrobial activity, the synthesized TD-AgNPs could find good application in medicine, pharmaceutical, biotechnology, and food science.

In this study, drying characteristics, kinetic modelling, energy and exergy analyses of a convective hot air dryer are presented for water yam. The drying experiments were carried out at temperature levels of 50, 60, and 70°C and slice thicknesses of 3, 6, and 9 mm. The effects of drying variables on the drying rate (DR), moisture diffusivity (D_eff), activation energy (E_a), energy utilization (EU), energy utilization ratio (EUR), exergy loss (EX_L), exergy efficiency (EX_eff), improvement potential (IP), and exergetic sustainability index (ESI) were investigated. The results showed that increasing air temperature increased the DR, D_eff, EU, EUR, EX_L, EX_eff, IP, and ESI, while increasing the slice thickness increased D_eff and E_a, but decreased the DR. The highest D_eff and E_a values were 4.2 × 10⁻⁸ m²/s, and 53 KJ/mol, respectively. EU and EUR varied from 10 to 150 J/s and 0.39 to 0.79, respectively. EX_L and EX_eff varied between 2 and 12.5 J/s and 58 to 75 %, respectively. Midilli’s model had the best performance in predicting the moisture ratio of water yam with coefficient of determination (R² = 0.9998), root mean square error (RMSE = 0.0049), and sum of square error (SSE = 0.0023).

A central composite rotatable design with four independent variables viz. blend ratio (broken rice flour and cowpea flour): 90:10–70:30, moisture content (10–18% wet basis), barrel temperature (110–150 °C), and screw speed (280–360 rpm) were varied in the development of ready-to-eat snacks using a twin extruder for a broken rice–cowpea product. The effects of the independent variables on specific mechanical energy, water absorption index, water solubility index, total color, hardness, bulk density, expansion ratio, and overall acceptability of the extruded snack were investigated using regression analysis. The results showed that the physical qualities of the ready-to-eat snacks were significantly affected by the extrusion parameters (i.e., blend ratio, barrel temperature, moisture content, and screw speed). From the findings, it was observed that screw speed and moisture contents affected hardness, while water absorption index was affected by all the extrusion parameters. However, the water solubility index and overall acceptance were majorly affected by the moisture content; extrudate produced with barrel ratio of 85:15, 12% moisture content, barrel temperature of 140 °C, and screw speed of 300 rpm was the most acceptable, at 6.73 on a 9 point hedonic scales. The blend ratio and barrel temperature influenced the expansion. Furthermore, the combination of cowpea and broken rice to produce nutritious ready-to-eat snacks has high acceptability and is a promising panacea for food security.

The deficit irrigation strategy is a well-known approach to optimize crop water use through the estimation of crop water use efficiency (CWUE). However, studies that comprehensively reported the prediction of crop evapotranspiration (ET_c) and CWUE under deficit irrigation for improved water resources planning are scarce. The objective of the study is to predict seasonal ET_c and CWUE of maize using multiple linear regression (MLR) and artificial neural network (ANN) models under two scenarios, i.e., (1) when only climatic parameters are considered and (2) when combining crop parameter(s) with climatic data in amended soil. Three consecutive field experimentations were carried out with biochar applied at rates of 0, 3, 6, 10 and 20 t/ha, while inorganic fertilizer was applied at rates of 0 and 300 Kg/ha, under three water regimes: 100% Full Irrigation Treatment (FIT), 80% and 60% FIT. Seasonal ET_c was determined using the soil water balance method, while growth data were monitored weekly. The CWUE under each treatment was also estimated and modelled. The MLR and ANN models were developed, and their evaluations showed that the ANN model was satisfactory for the predictions of both ET_c and CWUE under all soil water conditions and scenarios. However, the MLR model without crop data was poor in predicting CWUE under extreme soil water conditions (60% FIT). The coefficient of determination (R²) increased from 0.03 to 0.67, while root mean-square error (RMSE) decreased from 4.07 to 1.98 mm after the inclusion of crop data. The model evaluation suggests that using a simple model such as MLR, crop water productivity could be accurately predicted under different soil and water management conditions.

Climate change is a global phenomenon with multifarious unique regional consequences. Contemporary studies have established Climate change as a product of anthropogenic activities. Studies have linked extreme weather events, heat waves, increase pollution, crop failure as some of the many discernable effects of climate change. Hence, the spatial temporal effects of Climate change are of concern to policy makers, researchers, innovators and the entire public to develop veritable mitigation strategies. This paper examines climate change in Nigeria as a case study; the research adopted desk research method to collect secondary data from literature about hazards caused by climate change and potential adaptation strategies in Nigeria. The findings revealed that a potential environmental hazard caused by climate change in Nigeria includes that of biological, chemical, physical, mechanical and psycho-social. Moreover, this review further showed adaptation technologies that can be used in adapting and mitigating climate change in Nigeria.