Simulating nitrogen dynamics in sugarcane cropping systems using DSSAT-Canegro

Abstract

Sugarcane is a high-biomass producing crop and often requires substantial amounts of nitrogen (N) fertiliser to achieve optimal yields. Nitrogen fertiliser represents a significant input cost for the sugar industry. This nutrient is highly challenging to manage due to its susceptibility to various kinds of losses following application, for example, leaching and denitrification. In addition to reduced profitability, N losses potentially lead to environmental degradation, for example, through eutrophication of water bodies. As a result of the complexities of N dynamics in sugarcane cropping systems, mechanistic crop models are now more commonly being used to help understand these various N inand outflows, and to inform better management practices. These models first require extensive calibration, testing and validation with measured data in order to gain confidence in their performance, however. In this study, a historical dataset from a fertigation trial conducted in Komatipoort, Mpumalanga, was firstly used to assess the ability of DSSAT-Canegro (with a newly included N subroutine) to simulate cane and sucrose yields as well as aboveground N mass in response to different N fertiliser rates over five consecutive seasons (2003-2007). Cane and sucrose yields, as well as aboveground N mass were adequately simulated in response to various N rates under drip irrigation. In addition to this, cane yield, aboveground N mass and soil water N concentrations were monitored for model testing purposes as part of this study in trials conducted in Pongola (irrigated), Mount Edgecombe (rainfed), and Inanda (rainfed), all in KwaZulu Natal. For the Mount Edgecombe trial, N fertiliser treatments that took soil N levels into account before deciding when to fertilise were included, and the potentially reduced leaching loads were investigated by the model. In most cases, the DSSATCanegro model simulated N dynamics and cane yield adequately under both irrigated and rainfed conditions. The model was also observed to perform well under contrasting environmental conditions, such as during periods of drought versus high rainfall. In a number of cases, significant differences in cane yield between treatments receiving different rates of N were not observed in the measured data, indicating that the crop was able to acquire sufficient N from organic matter mineralisation and fertiliser N from previous seasons applications or the different N rates were all more than the required amount. Based on the potential implications of reduced cane yield following water stress and/or N stress, and unwanted N exports to the environment, it is concluded that DSSAT-Canegro is a useful tool to improve our knowledge of N dynamics in sugarcane ropping systems and to develop best management practices.