scholarly journals Effects of Increasing Nitrogen Content on Process Stability and Reactor Performance in Anaerobic Digestion

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1139 ◽  
Author(s):  
Ievgeniia Morozova ◽  
Nadiia Nikulina ◽  
Hans Oechsner ◽  
Johannes Krümpel ◽  
Andreas Lemmer
Keyword(s):  
Anaerobic Digestion ◽  
Conversion Efficiency ◽  
Stable Process ◽  
Process Stability ◽  
Reactor Performance ◽  
High Nitrogen ◽  
Fresh Matter ◽  
Feeding Regime ◽  
N Concentration ◽  
Feeding Regimes

The aim of this study was to analyse the effect of different nitrogen increase rates in feedstock on the process stability and conversion efficiency in anaerobic digestion (AD). The research was conducted in continuously stirred tank reactors (CSTR), initially filled with two different inocula: inocula #1 with low and #2 with high nitrogen (N) concentrations. Three N feeding regimes were investigated: the “0-increase” feeding regime with a constant N amount in feeding and the regimes “0.25-increase” and “0.5-increase” where the N concentrations in feedstock were raised by 0.25 and 0.5 g·kg−1, respectively, related to fresh matter (FM) every second week. The N concentration inside the reactors increased according to the feeding regimes. The levels of inhibition (Inhibition) in specific methane yields (SMY), related to the conversion efficiency of the substrates, were quantified. At the N concentration in digestate of 10.82 ± 0.52 g·kg−1 FM measured in the reactors with inoculum #2 and “0.5-increase” feeding regime, the level of inhibition was equal to 38.99% ± 14.99%. The results show that high nitrogen increase rates in feeding regime are negatively related to the efficiency of the AD process, even if low volatile fatty acid (VFA) concentrations indicate a stable process.

Bioconversion of Dried Leaves from Algerian Date Palm (Phoenix dactylifera L.) to Biogas by Anaerobic Digestion

2019 ◽  
Vol 41 ◽  
pp. 131-144
Author(s):  
Mohammed Djaafri ◽  
Slimane Kalloum ◽  
Ahmed Elamine Soulimani ◽  
Mostefa Khelafi
Keyword(s):  
Anaerobic Digestion ◽  
Date Palm ◽  
Biogas Production ◽  
Stable Process ◽  
Production Capacity ◽  
Oxygen Demand ◽  
Phoenix Dactylifera ◽  
Total Alkalinity ◽  
Process Stability ◽  
Biogas Yield

This work aimed to study anaerobic digestion of a new substrate made from the waste of Algerian date palm (Phoenix dactyliferaL.) in order to evaluate its biogas production capacity. The lignocellulosic component biodegradability and the process stability were also tested. Two reactors were launched with the same concentration of 20g total solid (TS)/L. A physical pre-treatment (grinding) of dried leaves lowered the substrate size below 2 mm. The theoretical methane yield (499 - 538 mL CH4/g of Volatile Solids (VS)) indicated a high substrate methanogen potential. The tested methane and biogas yield reached 130±6 mL CH4/gVS and 197±6 mL/g VS respectively. The biodegradability through the volatiles solid reduction was 29%. The total alkalinity (TA) value increased from the beginning to the end, due to the substrate nature which gave a high buffering capacity of the medium. During the stable process, a higher Chemical Oxygen Demand (COD) removal was reached with a value of 77.58%. The majority of the biogas yield was generated during the same period, which confirmed that the anaerobic digestion process stability is indispensable. Finally, this study was an opportunity to better exploit local by-products for the bioenergy production.

scholarly journals Video surveillance methods to evaluate individual feeding response in rainbow trout (Oncorhynchus mykiss, Walbaum)—implications for feeding regime optimisation

2021 ◽  
Author(s):  
Philip Niclas Just ◽  
Bernd Köllner ◽  
Matthew James Slater
Keyword(s):  
Rainbow Trout ◽  
Oncorhynchus Mykiss ◽  
Video Surveillance ◽  
Average Weight ◽  
Short Term ◽  
Feeding Regime ◽  
Daily Feeding ◽  
Juvenile Rainbow Trout ◽  
Feeding Regimes ◽  
The Impact

AbstractPrecisely analysing and optimising feeding regimes is central to salmonid growth performance and delivery of special diets. The current study developed novel video surveillance methods and analysis techniques to assess individual feed intake and minimum pellet intake (MPI) in individually identified juvenile rainbow trout, Oncorhynchus mykiss. Three trials were conducted to test the impact of short-term starvation (N=112 [16 tanks, 7 fish per tank], average weight=27.1±3.4g, age= 119 days), portion numbers per feeding (N=105 [15 tanks, 7 fish per tank], average weight=22.8±2.1g, age= 99 days) and varied numbers of daily feeding events (N=84 [12 tanks, 7 fish per tank], average weight=32.4±3.3g, age= 133 days). All trails were carried out in a recirculating aquaculture system with 20 tanks held at 15 ± 0.5°C. All individuals were code-tagged and high quality video images were taken and analysed to identify all feeding interactions. Individual trout feeding activity under different feeding regimes could be precisely analysed with the video methods developed. Moving from one to two daily feeding events doubled pellet intake per fish from 27.4 ± 5.8 to 52.8 ± 11.5 pellets. Pellet intake (58.8 ± 24.2 pellets) did not increase at three daily feeding events but became more variable across fish. MPI nearly doubled to 30 pellets in fish receiving two daily feeding events (MPI30: chi-squared = 8.74, df = 2, p = 0.01). Short-term starvation had no influence on intake (28 ± 8 pellets/fish) or MPI. Increasing portion number from one (27.8 ± 7.4 pellets fish−1) to two (31.1 ± 7.4 pellets fish−1) or more did not significantly increase the number of ingested pellets. Adjusting the feeding regime by increasing daily feeding events to two, possibly combined with multiple portions, can increase pellet intake and reduce the heteroscedasticity of pellet intake. The methods presented in this study are viable for analysing feeding regimes for juvenile rainbow trout and controlled feedstock/supplement delivery. Implications for analyses with other species and for vaccination optimisation are discussed.

The impact of restricted rationing upon growth, food conversion efficiency and body composition of rainbow trout

1995 ◽  
Vol 31 (10) ◽  
pp. 219-223 ◽  
Author(s):  
M. Tomec ◽  
Z. Teskeredžic ◽  
E. Teskeredžic ◽  
M. Hacmanjek ◽  
E. McLean
Keyword(s):  
Body Composition ◽  
Rainbow Trout ◽  
Conversion Efficiency ◽  
Food Conversion ◽  
Lipid Levels ◽  
Feed Conversion ◽  
Body Lipid ◽  
Rainbow Trout Oncorhynchus Mykiss ◽  
Feeding Regimes ◽  
The Impact

Juvenile rainbow trout, Oncorhynchus mykiss, maintained under commercial conditions, were subjected to four different feeding regimes. Duplicate groups of fish were fed to satiation 3 times/d for either 7, 3, 2 or 1 d/wk over a 10 wk period. At the end of the trial, evaluations were made of group growth performance, body composition, and feed conversion efficiency (FCE). At the end of the experiment, no differences were discerned between fish fed either daily or 3 times/wk with respect to growth, FCE or body composition. Animals placed upon the two lowest rations were significantly smaller (P<0.05) than those fed daily and exhibited decreased condition factors and body lipid levels (P<0.05) and increased moisture content (P<0.05). Food conversion was least efficient in those fish provided the largest ration.

scholarly journals Application of Various Machine Learning Models for Process Stability of Bio-Electrochemical Anaerobic Digestion

Processes ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 158
Author(s):  
Ain Cheon ◽  
Jwakyung Sung ◽  
Hangbae Jun ◽  
Heewon Jang ◽  
Minji Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Anaerobic Digestion ◽  
Prediction Accuracy ◽  
Input Data ◽  
Process Stability ◽  
Operational Parameters ◽  
Monitoring Parameter ◽  
Efficient Prediction ◽  
Single Input ◽  
Machine Learning Models

The application of a machine learning (ML) model to bio-electrochemical anaerobic digestion (BEAD) is a future-oriented approach for improving process stability by predicting performances that have nonlinear relationships with various operational parameters. Five ML models, which included tree-, regression-, and neural network-based algorithms, were applied to predict the methane yield in BEAD reactor. The results showed that various 1-step ahead ML models, which utilized prior data of BEAD performances, could enhance prediction accuracy. In addition, 1-step ahead with retraining algorithm could improve prediction accuracy by 37.3% compared with the conventional multi-step ahead algorithm. The improvement was particularly noteworthy in tree- and regression-based ML models. Moreover, 1-step ahead with retraining algorithm showed high potential of achieving efficient prediction using pH as a single input data, which is plausibly an easier monitoring parameter compared with the other parameters required in bioprocess models.

A critical review of conventional and emerging methods for improving process stability in thermophilic anaerobic digestion

2020 ◽  
Vol 54 ◽  
pp. 72-84 ◽  
Author(s):  
John Ryue ◽  
Long Lin ◽  
Farokh Laqa Kakar ◽  
Elsayed Elbeshbishy ◽  
Abdullah Al-Mamun ◽  
...  
Keyword(s):  
Anaerobic Digestion ◽  
Critical Review ◽  
Process Stability ◽  
Thermophilic Anaerobic Digestion

scholarly journals Estimating Nitrogen and Chlorophyll Status of Romaine Lettuce Using SPAD and at LEAF Readings

2019 ◽  
Vol 47 (3) ◽  
Author(s):  
Rodrigo Omar MENDOZA-TAFOLLA ◽  
Porfirio JUAREZ-LOPEZ ◽  
Ronald-Ernesto ONTIVEROS-CAPURATA ◽  
Manuel SANDOVAL-VILLA ◽  
Iran ALIA-TEJACAL ◽  
...  
Keyword(s):  
Linear Correlation ◽  
Crop Production ◽  
Chlorophyll Concentration ◽  
Production Cycle ◽  
Digital Object Identifier ◽  
Romaine Lettuce ◽  
Fresh Matter ◽  
Nitrogen Levels ◽  
N Concentration

Nitrogen (N) is an essential nutrient for plant growth and development and is especially important in the production of high quality leafy green vegetables. In this experiment, leaf N concentration, chlorophyll concentration (Chl) and weight above fresh matter (AFM) of romaine lettuce (Lactuca sativa L. var. longifolia) were estimated by correlations between in situ SPAD and atLEAF readings. Lettuce was grown in high tunnels during 42 days and was irrigated at five nitrogen levels: 0, 4, 8, 12 and 16 mEq·L-1 of NO3-, based on the Steiner nutrient solution. The N concentration, Chl concentration and AFM were determined in the laboratory, while SPAD and atLEAF readings were measured in situ weekly. SPAD readings had high, positive and significant linear correlations with N (R2 = 0.90), Chl (R2 = 0.97) and AFM (R2 = 0.98); atLEAF readings had a similar linear correlation with N (R2 = 0.91), Chl (R2 = 0.92) and AFM (R2 = 0.97). Besides, SPAD and atLEAF readings had high, positive, and significant linear correlation (R2 = 0.96). Thus, SPAD and atLEAF meters can be used to non-destructively and accurately estimate the N status of lettuce, in a reliable and quick manner during the crop production cycle. In addition, atLEAF is currently more affordable than SPAD.   ********* In press - Online First. Article has been peer reviewed, accepted for publication and published online without pagination. It will receive pagination when the issue will be ready for publishing as a complete number (Volume 47, Issue 3, 2019). The article is searchable and citable by Digital Object Identifier (DOI). DOI link will become active after the article will be included in the complete issue. *********

scholarly journals Industrially Finished Calves: A Water Footprint-Profitability Paradox

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2565 ◽  
Author(s):  
Frikkie Maré ◽  
Henry Jordaan
Keyword(s):  
South African ◽  
Conversion Rate ◽  
Water Footprint ◽  
Feeding Period ◽  
Feed Conversion ◽  
Feeding Regime ◽  
Cattle Breeds ◽  
Feeding Regimes ◽  
Feed Conversion Rate ◽  
South African Rand

The feed conversion rate is one of the most important determinants of the water footprint (WF) of beef and is known to vary between different cattle breeds. The objective of this study was to estimate the WF of industrially finished calves of seven different cattle breeds on two different feeding regimes: normal pre-determined feeding period (NPFP) and profit-maximising feeding period (PMFP). Data were collected by finishing 35 calves of each of the seven breeds in a feedlot. Green, blue and grey WFs were estimated for the different feeding regimes, and a feedlot simulation provided the effect of the different feeding regimes on the water footprint, financial margin and the water footprint per rand of margin. The results indicated that the water footprint differed notably between breeds on the same feeding regime, as well as between the feeding regimes. While the PMFP had a 1% higher water footprint per year in a typical feedlot than the NPFP, the financial margin was 33% more, resulting in a 24% decrease in the water footprint per South African rand of margin. The contributions of green, blue and grey water to the total WF were 91.5%, 2.5% and 6%, respectively, irrespective of breed or feeding regime.

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