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This study tested the anti-hyperlipidemic, hypoglycemic, hepatoprotective, and anti-inflammatory effects of whole pearl millet grain powder (MPG) and its ethanol extract (MPGethaolE) in obese rats fed a high-fat diet. The rats were divided into eight groups based on the treatments they received: control, high fat diet (HFD), HFD + MGE (25 mg/Kg), HFD + MPGethaolE (50 mg/Kg), HFD + MPGethaolE (100 mg/Kg), HFD + MPG (10%), HFD + MPG (20%), and HFD + MPG (30%). The final body weight, visceral, epididymal fat pads, and the liver weight were significantly decreased, in a dose-dependent manner, in HFD fed rats that were co-administered either the MPG powder or MPGethaolE. In the same line, serum levels of triglycerides (TGs), cholesterol (CHOL), and low-density lipoprotein-cholesterol (LDL-c), as well as fasting glucose, insulin, HOMA-IR, and serum levels of lipopolysaccharides (LPS), interleukine-6 (IL-6), interleukine-10 (IL-10), C-reactive protein (CRP), tumor necrosis factor (TNF-α), and adiponectin were progressively decreased while serum levels of high-density lipoproteins (HDL-c) were significantly increased when increasing the doses of both treatments. In conclusion, both the raw powder and ethanolic extract of MP have a comparative dose-dependent anti-obesity, hypoglycemic, hypolipidemic, anti-inflammatory, and anti-steatotic in HFD-fed rats.

Abstract Carotenoids are important isoprenoids produced in the plastids of photosynthetic organisms that play key roles in photoprotection and antioxidative processes. β-Carotene is generated from lycopene by lycopene β-cyclase (LCYB). Previously, we demonstrated that the introduction of the Daucus carota (carrot) DcLCYB1 gene into tobacco (cv. Xanthi) resulted in increased levels of abscisic acid (ABA) and especially gibberellins (GAs), resulting in increased plant yield. In order to understand this phenomenon prior to exporting this genetic strategy to crops, we generated tobacco (Nicotiana tabacum cv. Petit Havana) mutants that exhibited a wide range of LCYB expression. Transplastomic plants expressing DcLCYB1 at high levels showed a wild-type-like growth, even though their pigment content was increased and their leaf GA1 content was reduced. RNA interference (RNAi) NtLCYB lines showed different reductions in NtLCYB transcript abundance, correlating with reduced pigment content and plant variegation. Photosynthesis (leaf absorptance, Fv/Fm, and light-saturated capacity of linear electron transport) and plant growth were impaired. Remarkably, drastic changes in phytohormone content also occurred in the RNAi lines. However, external application of phytohormones was not sufficient to rescue these phenotypes, suggesting that altered photosynthetic efficiency might be another important factor explaining their reduced biomass. These results show that LCYB expression influences plant biomass by different mechanisms and suggests thresholds for LCYB expression levels that might be beneficial or detrimental for plant growth.

The impact of climate change on biodiversity has been the subject of numerous research in recent years. The multiple elements of climate change are expected to affect all levels of biodiversity, including microorganisms. The common worldwide fungus Fusarium oxysporum colonizes plant roots as well as soil and several other substrates. It causes predominant vascular wilt disease in different strategic crops such as banana, tomato, palm, and even cotton, thereby leading to severe losses. So, a robust maximum entropy algorithm was implemented in the well-known modeling program Maxent to forecast the current and future global distribution of F. oxysporum under two representative concentration pathways (RCPs 2.6 and 8.5) for 2050 and 2070. The Maxent model was calibrated using 1885 occurrence points. The resulting models were fit with AUC and TSS values equal to 0.9 (±0.001) and 0.7, respectively. Increasing temperatures due to global warming caused differences in habitat suitability between the current and future distributions of F. oxysporum, especially in Europe. The most effective parameter of this fungus distribution was the annual mean temperature (Bio 1); the two-dimensional niche analysis indicated that the fungus has a wide precipitation range because it can live in both dry and rainy habitats as well as a range of temperatures in which it can live to certain limits. The predicted shifts should act as an alarm sign for decision makers, particularly in countries that depend on such staple crops harmed by the fungus.

Given crude oil prices and their environmental impacts, the use of sustainable renewable alternative energies such as biofuels is rapidly progressing in numerous countries. Among biofuels, bioethanol is a renewable and clean fuel that can be obtained from the fermentation of several raw agricultural materials, including date fruit. However, the low product yield, mainly due to the low-grade nutrient content, limits its use as a promising alternative biofuel. This current study investigated bioethanol production from date by-products in Saudi Arabia and examined the impact of calcium and nitrogen sources added at different concentrations (0 to 1 g/L) on the productivity and ethanol concentration using Saccharomyces cerevisiae. Yeast extracts and ammonium chloride (NH4Cl) were tested as nitrogen sources for bioethanol fermentation from date juice. Calcium chloride (CaCl2) and calcium carbonate (CaCO3) were evaluated as calcium sources for the same purpose mentioned above. The results showed that both calcium and nitrogen sources improved ethanol production efficiencies. The addition of calcium sources such as CaCl2 at 0.4 g/L resulted in maximum ethanol concentration (41.5 ± 0.85 g/L) and the highest productivity of 0.511 g/L/h. Thus, an increase of 31.3% compared to the control sample was acquired. Ammonium chloride was found to be the best nitrogen supplement among them. Indeed, supplementing the fermentation medium with 1 g/L NH4Cl gave an optimal ethanol concentration and productivity, reaching more than 65 g/L and 0.83 g/L/h, respectively. This is an increase of 106.6%. The functional group of ethanol (C2H5OH) for all the elaborated samples was confirmed by Fourier-transform infrared spectroscopy (FTIR) and NMR analyses. Moreover, the results confirmed the high quality and purity of the bioethanol products. Thus, the “Khodhari” date variety of low market value is a privileged substrate for industrial bioethanol production. For this reason, a proposed flow diagram of a designed plant for bioethanol industrialization is provided and detailed.

Lipid-producing microorganisms, said to be oleaginous have been recognized since several years. We had investigated the effects of medium components and culturing situations on cell growth and lipid accumulation of oleaginous yeasts which were analytically examined so as to enhance lipid yield for biodiesel production.The main objective of this study was to explore oleaginous yeast, Yarrowia lipolytica isolated from soil and optimization of culture conditions and medium components to obtained better quality microbial oil for biodiesel production.Fifty yeast strains were isolated from soil from different regions of Lahore and eleven of them were selected for oil production. The isolated yeast colonies were screened to further check their lipid producing capabilities by the qualitative analysis. Five yeast strains were designated as oleaginous because they produced more than 16% of oil based on their biomass. To estimate the total lipid content of yeast cells, the extraction of lipids was done by performing the procedure proposed by Bligh and Dyer. The transesterification of yeast oils was performed by using different methods. There were three different strategies customized to transesterifying microbial oil using base catalyzed transesterification, acid catalyzed transesterification and enzyme-based transesterification. After completion of transesterification, sample was used for fatty acid methyl esters (FAMEs) were analyzed by gas-chromatograph with ionization detector type MS.The isolate IIB-10 identified as Yarrowia lipolytica produced maximum amount of lipids i.e. 22.8%. More amount of biomass was obtained when cane molasses was utilized as carbon source where it produced 29.4 g/L of biomass while sucrose and lactose were not utilized by IIB-10 and no biomass was obtained. Similarly, meat extracts showed best results when it was used as nitrogen source because it resulted in 35.8 g/L biomass of Yarrowia lipolytica IIB-10. The culturing conditions like size of inoculum, effect of pH and time of incubation were also studied. The 10% of inoculum size produced 25.4 g/L biomass at 120 h incubation time, while the pH 7 was the optimum pH at which 24.8 g/L biomass was produced by Yarrowia lipolytica IIB-10. GC-MS analysis showed that biodiesel produced by transesterification contained similar fatty acids as found in vegetable oil for this reason it is widely accepted feedstock for biodiesel production.The analysis of fatty acids methyl esters showed the similar composition of microbial oil as in vegetable oils and high amount of methyl esters were obtained after transesterification. Therefore, potentially oleaginous yeast could be used to generate a large amount of lipids for biodiesel production that will be the better substitute of petroleum-based diesel and will also control the environmental pollution.

Mismanagement of crop straw and coal gas residue threatens the atmosphere and the economy. Nevertheless, thermal-pyrolysis is an option for management that turns bio-waste into biochar; its viability and adoption by the public as soil amendments is dependent on the agronomic and environmental values compared between biochar and the raw materials. We undertook a 60-day short-term analysis to assess the impact of various wastes and biochars, as well as inorganic nutrients (N), on carbon dioxide (CO2) fluxes, soil enzyme activities, soil fertility status, and microbial activities. There were eight treatments of soil amendments: without an amendment (CK), Nutrients (N), straw + nutrients (S+N), straw biochar + nutrients (SB+N), coal gas residue + nutrients (C+N), coal gas residue biochar + nutrients (CB+N), straw + straw biochar + nutrients (S+SB+N) and coal gas residue waste + coal gas residue biochar + nutrients (C+ CB +N). The results indicated that soil EC, pH, nitrate N (NO3 -- N), SOC, TN and available K were significantly (p < 0.05) increased coal gas residue biochar and combined with coal fly ash as compared to maize straw biochar and combined with maize straw and N treatments. The higher concentrations of soil MBC and MBN activities were increased in the maize straw application, while higher soil enzyme activity such as, invertase, urease and catalase were enhanced in the coal fly ash derived biochar treatments. The higher cumulative CO2 emissions were recorded in the combined applications of maize straw and its biochar as well as coal gas residue and its biochar treatment. Our study concludes, that maize straw and coal fly ash wastes were converted into biochar product could be a feasible substitute way of discarding, since land amendment and decreased CO2 fluxes and positive changes in soil microbial, and chemical properties, and can be confirmed under long-term conditions for reduction of economical and environment issues.

Crop yield prediction is one of the most challenging tasks in agriculture. It is considered to play an important role and be an essential step in decision-making processes. The goal of crop prediction is to establish food availability for the coming years, using different input variables associated with the crop yield domain. This paper aims to predict the yield of five of the Gulf countries’ crops: wheat, dates, watermelon, potatoes, and maize (corn). Five independent variables were used to develop a prediction model, namely year, rainfall, pesticide, temperature changes, and nitrogen (N) fertilizer; all these variables are calculated by year. Moreover, this research relied on one of the most widely used machine learning models in the field of crop yield prediction, which is the neural network model. The neural network model is used because it can predict complex relationships between independent and dependent variables. To evaluate the performance of the prediction models, different statistical evaluation metrics are adopted, including mean square error (MSE), root-mean-square error (RMSE), mean bias error (MBE), Pearson’s correlation coefficient, and the determination coefficient. The results showed that all Gulf countries are affected mainly by four independent variables: year, temperature changes, pesticides, and nitrogen (N) per year. Moreover, the average of the best crop yield prediction results for the Gulf countries showed that the RMSE and R2 are 0.114 and 0.93, respectively. This provides initial evidence regarding the capability of the neural network model in crop yield prediction.