Research Articles

This study modeled and optimized energy consumption and greenhouse gas emissions (GHGE) for watermelon (Citrullus lanatus L.) production in Adana, Turkey. Artificial Neural Networks (ANN) and Multi-Objective Genetic Algorithms (MOGA) were employed for the analysis. The findings revealed that chemical fertilizers accounted for the largest share of energy use (77.0%), followed by diesel fuel (8.4%), with a total energy consumption of 50,100 MJ ha⁻¹. The ANN 10-8-2 architecture provided the most accurate performance (R²). Using the MOGA method, optimum values ​​were determined for minimum total GHGE and maximum watermelon production. The highest amount of production with minimum energy usage was approximately 10,900 MJ ha^-1. The GHGE of the best production were calculated as approximately 282 kg CO₂_eq ha^-1. The GHGE reduction potential using MOGA was calculated as 903 kg CO₂_eq ha^-1. Furthermore, the highest reduction in GHGE occurred in nitrogen fertilizer by 52.0%. The results also indicated that the highest amount of production with minimum energy usage is approximately 10,900 MJ ha^-1. The GHGE of the best production were calculated as approximately 282 kg CO₂_eq ha^-1. The GHGE reduction potential using MOGA was calculated as 903 kg CO₂_eq ha^-1. Furthermore, the highest reduction in GHGE occurred in nitrogen fertilizer by 52.0%.

Effects of acid and enzymatic hydrolysis, as well as starch content, were compared relative to the amounts of reducing sugars obtained from rice polish. The growth of yeast on various sugar profiles obtained from both hydrolysis was evaluated. The effect of pretreatments of different H₂SO₄ concentrations (1 to 5%) was examined at different incubation periods (1 to 3 h). The impacts of 1% H₂SO₄ and H₃PO₄ on rice polish were also studied, and the reducing sugar release was measured using the DNS assay. For enzymatic hydrolysis, a fungus with high starch-degrading ability was isolated from soil and tentatively identified as Aspergillus niger. The efficiency of amylase produced by A. niger via submerged fermentation was determined at various residence times (48 to 120 h), with reducing sugar release measured by a substrate-based assay and enzyme activity by a product-based assay. Finally, the yeast growth was assessed on hydrolysates from both methods. Proximate analysis revealed 79.5% starch, 35.2% sugar, and 8.5% nitrogen in rice polish. Maximum reducing sugar (19.2 mg/mL) was obtained after pretreatment with 2% H₂SO₄ after 1.0 h, and H₂SO₄ yield (1.08 g/L) outperformed H₃PO₄ (0.59 g/L). Moreover, the substrate-based assay showed optimal starch conversion at 72 h (10.6 µmol/min), and the product-based assay showed maximum enzyme activity after 72 h (409 µmol/min). The evaluation of yeast growth revealed that enzymatic hydrolysis produced more reducing sugars (8.68 mg/mL) compared to acid hydrolysis (6.61 mg/mL), highlighting its potential for ethanol production.