4 resultados para Manure Application

em eResearch Archive - Queensland Department of Agriculture


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The amounts of farm dairy effluent stored in ponds and irrigated to land have steadily increased with the steady growth of New Zealand's dairy industry. About 80% of dairy farms now operate with effluent storage ponds allowing deferred irrigation. These storage and irrigation practices cause emissions of greenhouse gases (GHG) and ammonia. The current knowledge of the processes causing these emissions and the amounts emitted is reviewed here. Methane emissions from ponds are the largest contributor to the total GHG emissions from effluent in managed manure systems in New Zealand. Nitrous oxide emissions from anaerobic ponds are negligible, while ammonia emissions vary widely between different studies, probably because they depend strongly on pH and manure composition. The second-largest contribution to GHG emissions from farm dairy effluent comes from nitrous oxide emissions from land application. Ammonia emissions from land application of effluent in New Zealand were found to be less than those reported elsewhere from the application of slurries. Recent studies have suggested that New Zealand's current GHG inventory method to estimate methane emissions from effluent ponds should be revised. The increasing importance of emissions from ponds, while being a challenge for the inventory, also provides an opportunity to achieve mitigation of emissions due to the confined location of where these emissions occur. © 2015 © 2015 The Royal Society of New Zealand.

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PigBal is a mass balance model that uses pig diet, digestibility and production data to predict the manure solids and nutrients produced by pig herds. It has been widely used for designing piggery effluent treatment systems and sustainable reuse areas at Australian piggeries. More recently, PigBal has also been used to estimate piggery volatile solids production for assessing greenhouse gas emissions for statutory reporting purposes by government, and for evaluating the energy potential from anaerobic digestion of pig effluent. This paper has compared PigBal predictions of manure total, volatile, and fixed solids, and nitrogen (N), phosphorus (P) and potassium (K), with manure production data generated in a replicated trial, which involved collecting manure from pigs housed in metabolic pens. Predictions of total, volatile, and fixed solids and K in the excreted manure were relatively good (combined diet R2 ≥ 0.79, modelling efficiency (EF) ≥ 0.70) whereas predictions of N and P, were generally less accurate (combined diet R2 0.56 and 0.66, EF 0.19 and –0.22, respectively). PigBal generally under-predicted lower N values while over-predicting higher values, and generally over-predicted manure P production for all diets. The most likely causes for this less accurate performance were ammonium-N volatilisation losses between manure excretion and sample analysis, and the inability of PigBal to account for higher rates of P uptake by pigs fed diets containing phytase. The outcomes of this research suggest that there is a need for further investigation and model development to enhance PigBal’s capabilities for more accurately assessing nutrient loads. However, PigBal’s satisfactory performance in predicting solids excretion demonstrates that it is suitable for assessing the methane component of greenhouse gas emission and the energy potential from anaerobic digestion of volatile solids in piggery effluent. The apparent overestimation of N and P excretion may result in conservative nutrient application rates to land and the over-prediction of the nitrous oxide component of greenhouse gas emissions.

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The key to better nutrient efficiency is to simultaneously improve uptake and decrease losses. This study sought to achieve this balance using sorbent additions and manure nutrients (spent poultry litter; SL) compared with results obtained using conventional sources (Conv; urea nitrogen, N; and phosphate–phosphorus; P). Two experiments were conducted. Firstly, a phosphorus pot trial involving two soils (sandy and clay) based on a factorial design (Digitaria eriantha/Pennisetum clandestinum). Subsequently, a factorial N and P field trial was conducted on the clay soil (D. eriantha/Lolium rigidum). In the pot trial, sorbent additions (26.2 g of hydrotalcite [HT] g P− 1) to the Conv treatment deferred P availability (both soils) as did SL in the sandy soil. In this soil, P delivery by the Conv treatments declined rapidly, and began to fall behind the HT and SL treatments. Addition of HT increased post-trial Colwell P. In the field trial low HT-rates (3.75 and 7.5 g of HT g P− 1) plus bentonite, allowed dry matter production and nutrient uptake to match that of Conv treatments, and increased residual mineral-N. The SL treatments performed similarly to (or better than) Conv treatments regarding nutrient uptake. With successive application, HT forms may provide better supply profiles than Conv treatments. Our findings, combined with previous studies, suggest it is possible to use manures and ion-exchangers to match conventional N and P source productivity with lower risk of nutrient losses.

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PigBal is a mass balance model that uses pig diet, digestibility and production data to predict the manure solids and nutrients produced by pig herds. It has been widely used for designing piggery effluent treatment systems and sustainable reuse areas at Australian piggeries. More recently, PigBal has also been used to estimate piggery volatile solids production for assessing greenhouse gas emissions for statutory reporting purposes by government, and for evaluating the energy potential from anaerobic digestion of pig effluent. This paper has compared PigBal predictions of manure total, volatile, and fixed solids, and nitrogen (N), phosphorus (P) and potassium (K), with manure production data generated in a replicated trial, which involved collecting manure from pigs housed in metabolic pens. Predictions of total, volatile, and fixed solids and K in the excreted manure were relatively good (combined diet R2 ≥ 0.79, modelling efficiency (EF) ≥ 0.70) whereas predictions of N and P, were generally less accurate (combined diet R2 0.56 and 0.66, EF 0.19 and -0.22, respectively). PigBal generally under-predicted lower N values while over-predicting higher values, and generally over-predicted manure P production for all diets. The most likely causes for this less accurate performance were ammonium-N volatilisation losses between manure excretion and sample analysis, and the inability of PigBal to account for higher rates of P uptake by pigs fed diets containing phytase. The outcomes of this research suggest that there is a need for further investigation and model development to enhance PigBal's capabilities for more accurately assessing nutrient loads. However, PigBal's satisfactory performance in predicting solids excretion demonstrates that it is suitable for assessing the methane component of greenhouse gas emission and the energy potential from anaerobic digestion of volatile solids in piggery effluent. The apparent overestimation of N and P excretion may result in conservative nutrient application rates to land and the over-prediction of the nitrous oxide component of greenhouse gas emissions. © CSIRO 2016.