Dataset Information

Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops.

ABSTRACT: Sugarcane production relies on the application of large amounts of nitrogen (N) fertilizer. However, application of N in excess of crop needs can lead to loss of N to the environment, which can negatively impact ecosystems. This is of particular concern in Australia where the majority of sugarcane is grown within catchments that drain directly into the World Heritage listed Great Barrier Reef Marine Park. Multiple factors that impact crop yield and N inputs of sugarcane production systems can affect N use efficiency (NUE), yet the efficacy many of these factors have not been examined in detail. We undertook an extensive simulation analysis of NUE in Australian sugarcane production systems to investigate (1) the impacts of climate on factors determining NUE, (2) the range and drivers of NUE, and (3) regional variation in sugarcane N requirements. We found that the interactions between climate, soils, and management produced a wide range of simulated NUE, ranging from ?0.3 Mg cane (kg N)-1, where yields were low (i.e., <50 Mg ha-1) and N inputs were high, to >5 Mg cane (kg N)-1 in plant crops where yields were high and N inputs low. Of the management practices simulated (N fertilizer rate, timing, and splitting; fallow management; tillage intensity; and in-field traffic management), the only practice that significantly influenced NUE in ratoon crops was N fertilizer application rate. N rate also influenced NUE in plant crops together with the management of the preceding fallow. In addition, there is regional variation in N fertilizer requirement that could make N fertilizer recommendations more specific. While our results show that complex interrelationships exist between climate, crop growth, N fertilizer rates and N losses to the environment, they highlight the priority that should be placed on optimizing N application rate and fallow management to improve NUE in Australian sugarcane production systems. New initiatives in seasonal climate forecasting, decisions support systems and enhanced efficiency fertilizers have potential for making N fertilizer management more site specific, an action that should facilitate increased NUE.

SUBMITTER: Thorburn PJ

PROVIDER: S-EPMC5591824 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops.

Thorburn Peter J PJ Biggs Jody S JS Palmer Jeda J Meier Elizabeth A EA Verburg Kirsten K Skocaj Danielle M DM

Frontiers in plant science 20170905

Sugarcane production relies on the application of large amounts of nitrogen (N) fertilizer. However, application of N in excess of crop needs can lead to loss of N to the environment, which can negatively impact ecosystems. This is of particular concern in Australia where the majority of sugarcane is grown within catchments that drain directly into the World Heritage listed Great Barrier Reef Marine Park. Multiple factors that impact crop yield and N inputs of sugarcane production systems can af ...[more]

PMID: 28928756

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Project description:The warming of world climate systems is driving interest in the mitigation of greenhouse gas (GHG) emissions. In the agricultural sector, practices that mitigate GHG emissions include those that (1) reduce emissions [e.g., those that reduce nitrous oxide (N2O) emissions by avoiding excess nitrogen (N) fertilizer application], and (2) increase soil organic carbon (SOC) stocks (e.g., by retaining instead of burning crop residues). Sugarcane is a globally important crop that can have substantial inputs of N fertilizer and which produces large amounts of crop residues ('trash'). Management of N fertilizer and trash affects soil carbon and nitrogen cycling, and hence GHG emissions. Trash has historically been burned at harvest, but increasingly is being retained on the soil surface as a 'trash blanket' in many countries. The potential for trash retention to alter N fertilizer requirements and sequester SOC was investigated in this study. The APSIM model was calibrated with data from field and laboratory studies of trash decomposition in the wet tropics of northern Australia. APSIM was then validated against four independent data sets, before simulating location × soil × fertilizer × trash management scenarios. Soil carbon increased in trash blanketed soils relative to SOC in soils with burnt trash. However, further increases in SOC for the study region may be limited because the SOC in trash blanketed soils could be approaching equilibrium; future GHG mitigation efforts in this region should therefore focus on N fertilizer management. Simulated N fertilizer rates were able to be reduced from conventional rates regardless of trash management, because of low yield potential in the wet tropics. For crops subjected to continuous trash blanketing, there was substantial immobilization of N in decomposing trash so conventional N fertilizer rates were required for up to 24 years after trash blanketing commenced. After this period, there was potential to reduce N fertilizer rates for crops when trash was retained (?20 kg N ha(-1) per plant or ratoon crop) while maintaining ?95% of maximum yields. While these savings in N fertilizer use were modest at the field scale, they were potentially important when aggregated at the regional level.

Project description:Soil CO2 emissions are regarded as one of the largest flows of the global carbon cycle and small changes in their magnitude can have a large effect on the CO2 concentration in the atmosphere. Thus, a better understanding of this attribute would enable the identification of promoters and the development of strategies to mitigate the risks of climate change. Therefore, our study aimed at using data mining techniques to predict the soil CO2 emission induced by crop management in sugarcane areas in Brazil. To do so, we used different variable selection methods (correlation, chi-square, wrapper) and classification (Decision tree, Bayesian models, neural networks, support vector machine, bagging with logistic regression), and finally we tested the efficiency of different approaches through the Receiver Operating Characteristic (ROC) curve. The original dataset consisted of 19 variables (18 independent variables and one dependent (or response) variable). The association between cover crop and minimum tillage are effective strategies to promote the mitigation of soil CO2 emissions, in which the average CO2 emissions are 63 kg ha-1 day-1. The variables soil moisture, soil temperature (Ts), rainfall, pH, and organic carbon were most frequently selected for soil CO2 emission classification using different methods for attribute selection. According to the results of the ROC curve, the best approaches for soil CO2 emission classification were the following: (I)-the Multilayer Perceptron classifier with attribute selection through the wrapper method, that presented rate of false positive of 13,50%, true positive of 94,20% area under the curve (AUC) of 89,90% (II)-the Bagging classifier with logistic regression with attribute selection through the Chi-square method, that presented rate of false positive of 13,50%, true positive of 94,20% AUC of 89,90%. However, the (I) approach stands out in relation to (II) for its higher positive class accuracy (high CO2 emission) and lower computational cost.

Dataset Information

Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops.

Publications

Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops.

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