Biochemical, hydrological and mechanical behaviors of high food waste content MSW landfill: Preliminary findings from a large-scale experiment.

A large-scale bioreactor experiment lasting for 2years was presented in this paper to investigate the biochemical, hydrological and mechanical behaviors of high food waste content (HFWC) MSW. The experimental cell was 5m in length, 5m in width and 7.5m in depth, filled with unprocessed HFWC-MSWs of 91.3 tons. In the experiment, a surcharge loading of 33.4kPa was applied on waste surface, mature leachate refilling and warm leachate recirculation were performed to improve the degradation process. In this paper, the measurements of leachate quantity, leachate level, leachate biochemistry, gas composition, waste temperature, earth pressure and waste settlement were presented, and the following observations were made: (1) 26.8m3 leachate collected from the 91.3 tons HFWC-MSW within the first two months, being 96% of the total amount collected in one year. (2) The leachate level was 88% of the waste thickness after waste filling in a close system, and reached to over 100% after a surcharge loading of 33.4kPa. (3) The self-weight effective stress of waste was observed to be close to zero under the condition of high leachate mound. Leachate drawdown led to a gain of self-weight effective stress. (4) A rapid development of waste settlement took place within the first two months, with compression strains of 0.38-0.47, being over 95% of the strain recorded in one year. The compression strain tended to increase linearly with an increase of leachate draining rate during that two months.

Calcium effect on the metabolic pathway of phosphorus accumulating organisms in enhanced biological phosphorus removal systems.

Phosphorus accumulating organisms (PAOs) have been found to act as glycogen-accumulating organisms (GAOs) under certain conditions, thus, the deterioration in the performance of enhanced biological phosphorus removal systems is not always attributed to the proliferation of GAOs. In this work, the effects of calcium on the metabolic pathway of PAOs were explored. It was found that when the influent Ca(2+) concentration was elevated, the tendency and extent of extracellular calcium phosphate precipitation increased, and the intracellular inert Ca-bound polyphosphate was synthesized, while the microbial population remained almost unchanged. The changes in the ratios of phosphorus released/acetate uptaken, the glycogen degraded/acetate uptaken and the poly-ß-hydroxyalkanoates synthesized/acetate uptaken during the anaerobic period confirm that, as the influent Ca(2+) concentration was increased, the polyphosphate-accumulating metabolism was partially shifted to the glycogen-accumulating metabolism. At an influent Ca(2+) around 50 mg/L, in addition to the extracellular calcium phosphate precipitation, the intracellular inert Ca-bound polyphosphate synthesis might also be involved in the metabolic change of PAOs. The results of the present work would be beneficial to better understand the biochemical metabolism of PAOs in enhanced biological phosphorus removal systems.

[Discrimination of donkey meat by NIR and chemometrics].

Donkey meat samples (n = 167) from different parts of donkey body (neck, costalia, rump, and tendon), beef (n = 47), pork (n = 51) and mutton (n = 32) samples were used to establish near-infrared reflectance spectroscopy (NIR) classification models in the spectra range of 4,000~12,500 cm(-1). The accuracies of classification models constructed by Mahalanobis distances analysis, soft independent modeling of class analogy (SIMCA) and least squares-support vector machine (LS-SVM), respectively combined with pretreatment of Savitzky-Golay smooth (5, 15 and 25 points) and derivative (first and second), multiplicative scatter correction and standard normal variate, were compared. The optimal models for intact samples were obtained by Mahalanobis distances analysis with the first 11 principal components (PCs) from original spectra as inputs and by LS-SVM with the first 6 PCs as inputs, and correctly classified 100% of calibration set and 98. 96% of prediction set. For minced samples of 7 mm diameter the optimal result was attained by LS-SVM with the first 5 PCs from original spectra as inputs, which gained an accuracy of 100% for calibration and 97.53% for prediction. For minced diameter of 5 mm SIMCA model with the first 8 PCs from original spectra as inputs correctly classified 100% of calibration and prediction. And for minced diameter of 3 mm Mahalanobis distances analysis and SIMCA models both achieved 100% accuracy for calibration and prediction respectively with the first 7 and 9 PCs from original spectra as inputs. And in these models, donkey meat samples were all correctly classified with 100% either in calibration or prediction. The results show that it is feasible that NIR with chemometrics methods is used to discriminate donkey meat from the else meat.

[Nondestructive discrimination of strawberry varieties by NIR and BP-ANN].

Strawberry variety is a main factor that can influence strawberry fruit quality. The use of near-infrared reflectance spectroscopy was explored discriminate among samples of strawberry of different varieties. And the significance of difference among different varieties was analyzed by comparison of the chemical composition of the different varieties samples. The performance of models established using back propagation-artificial neural networks (BP-ANN), least squares-support vector machine and discriminant analysis were evaluated on spectra range of 4545-9090 cm(-1). The optimal model was obtained by BP-ANN with a topology of 12-18-3, which correctly classified 96.68% of calibration set and 97.14% of prediction set. And the 94.95%, 97% and 98.29% classifications were given respectively for "Tianbao" (n=99), "Fengxiang" (n=100) and "Mingxing" (n=117). One-way analysis of variance was made for comparison of the mean values for soluble solids content (SSC), titratable acid (TA), pH value and SSC-TA ratio, and the statistically significant differences were found. Principal component analysis was performed on the four chemical compositions, and obvious clustering tendencies for different varieties were found. These results showed that NIR combined with BP-ANN can discriminate strawberry of different varieties effectively, and the difference in chemical compositions of different varieties strawberry might be a chemical validation for NIR results.