Intensifying rice-fallow systems in Southeast and South Asia with grain legumes and/or dry season crops: analysis using field experiment and simulation
von Elsa Rakhmi Dewi
Datum der mündl. Prüfung:2016-07-06
Betreuer:Prof. Dr. Anthony Whitbread
Gutachter:Prof. Dr. Klaus Dittert
Gutachter:Prof. Dr. Reimund Roetter
EnglischIn most Southeast and South Asia countries, lowland rice is particularly grown as a single crop at the wet season, followed by dry season crops or fallow at dry season and characterized under rainfed condition. The inclusion of dry season crops such as legumes into rice based cropping system has contributed to improve soil structure and nutrition, providing the basis for rice yield enhancement. In addition, dry season crops require less water in comparison to rice and are therefore better options for additional income. The success of the dry season crops generally rely on climatic conditions prevailing during crop establishment stage and various management practices. Since rainfed lowland rice highly depends on the reliability and amount of rainfall, the growth of the subsequent crops can be restricted due to low and erratic rainfall, as a result they rely on residual moisture from the wet season crop. Besides, undesirable climatic condition such as droughts and floods can lead to increased risk of crop losses. The poor performance of dry season crop is also influenced by limited inputs and management as well as limited research and extension advice. As a consequence, the crops receive low inputs and management level along with the adverse soil moisture and soil structure conditions which contribute to the low yields. To meet the yield of dry season crops, the crop establishment has to be improved and residual soil water during the period after rice crop has to be maintained. The success of crop establishment can be achieved by rapid germination, which relies on the content of soil water and the contact between seed and soil. An approach is also required to improve understanding of the impact of climatic variation, which allows farmers to respond to climatic variability and possible future climate change. In regions with high rainfall, farmers are mostly postponing planting or providing surface drainage in order to avoid waterlogging. The correct planting time of crops and the availability of subsoil water are related to climatic conditions, which determine the success of the crops. Since planting time is important for the success of dry season crops, the planting window is therefore narrow and will be defined by interaction between the crop growth and environmental condition. Many studies showed that management system such as planting time adjustment, water management, and tillage can be used to maximize dry season production, nevertheless they are time consuming and expensive. Simulation studies could therefore be useful to interpret the interaction between soil, crops, management options and weather in rice cropping system. Modeling is able to explain the correlation among the components of complex systems, give more insight into processes and verify the consequences of management as well as explore the potential for modification. The application of appropriates model to simulate rainfed lowland rice cropping systems is a challenge, especially related to climate variability. The Agricultural Production Systems Simulator (APSIM) cropping systems model, which has been developed by Agricultural Production System Research Unit in Australia, has the ability to simulate diverse cropping systems, rotation and environmental dynamics. Information on how to intensify rice-fallow systems in Southeast Asia is limited. Therefore, the main objective of this study was to intensify and analyse rice-fallow systems in Southeast (Indonesia and Thailand) and South (IGP India, Tamil Nadu and Bangladesh) Asia with grain legumes/dry season crops, using field experiment and simulation (chapter I). The second chapter examines the effective use of climate forecast information, farmers’ knowledge and ability in understanding and predicting the response of agricultural systems to climate variability in Jakenan, Central Java Indonesia and was based on face to face interviews with smallholder farmers, using a semi-structured questionnaire that consists of open and closed questions. The interview was conducted in four villages (Ngastorejo, Tlogorejo, Bungasrejo and Sendangsoko) in Jakenan sub-district and a total of 100 farmers were selected randomly based on the list of farmers available in each village. The findings revealed characteristics of the respondents, factors that affect farmers in using climate forecast information in lowland rice-based cropping system, and farmers’ perception on climate variability and change. About 80% of respondents in Jakenan indicated rice-rice-mungbean as their main cropping pattern. Selection of cropping pattern is mostly based on water availability. To meet crop water requirements, farmers usually apply supplemental irrigation over rice growing season. Looking at current climate variability and change, the use of climate forecast is important to improve crop production and to cope with climate risk. According to the survey about 70% of respondents have knowledge of climate forecast and use it for planting time determination. Adjusting sowing time and selection of appropriate crop varieties has become their main strategy in coping with climate variability. Farmers’ adoption level however was low considering climate risk management especially coping with El Nino events. In the third chapter, the opportunity of legumes performance at various sowing times, residue treatments, soil types and plant available water at four sites in Central Java, Indonesia is presented. The performance of the model for growing legumes under different agro-climatic conditions in rainfed lowland rice system is also evaluated. Results from long-term scenario analysis showed that late sowing at 70 mm of plant available water is crucial factors for greater yields of mungbean across all four sites. Across the four sites, different sowing time and plant available water had effect on mungbean yields. Delay sowing at 70 mm of plant available water in dry season will ensure better establishment because soil is not very wet and well-structured and drained so that the emergence and root growth is not inhibited, resulting greater yields. The site with adequate rainfall at the end of dry season should be able to grow mungbean effectively. To grow mungbean successfully in rainfed lowland rice-based cropping system, we should consider rainfall, soil water at sowing and sowing time. The fourth chapter discusses the long-term potential of intensified rice/or fallows in relation to historical climate data and the opportunity and riskiness of legumes within rainfed lowland rice-based cropping system in northeast Thailand. Model evaluation indicated fairly well results for rice phenology, grain yield and biomass. The model was able to predict grain yield and biomass with RMSEn in % of the observed mean was 30 and 18, respectively and a good model efficiency (EF) of 0.65 and 0.79, respectively for the given treatment applications and inter-annual climate variations. The model however was unlikely to capture the dynamic of cowpea grain yield. Further investigation is required to use APSIM model using different legume species. The long-term simulation evaluated the opportunity and performance of cowpea sown before and after rice in rainfed lowland rice-based cropping system in northeast Thailand. Results indicated that cowpea sown before or after rice cropping was influenced by rainfall, soil water at sowing and sowing date. Sowing cowpea in the dry season close to the onset of the rainy season will allow for reliable crop establishment and root growth as the soil surface is adequately moist. Whereas sowing cowpea in the dry season shortly after rice harvests allows suitable soil conditions to allow roots to penetrate and explore the subsoil water, contributing towards good crop establishment and growth. The ability of the model to simulate such a system can provide useful information for farmers and be used to simulate the benefits and risks of using different legumes species. The last chapter presents the capability of the APSIM-ORYZA in simulating diverse rice-based cropping system over a range of management practices and agro-climatic conditions in South Asia (IGP India, Tamil Nadu and Bangladesh). The validation model was able to predict grain energy yield (GEY), which represent system productivity, with RMSEn of 8% and EF of 0.94 for the given diverse crop sequences, rice establishments, residue treatments and agro-climatic conditions. The long-term scenario analysis demonstrated the beneficial of the intensification options with non-rice crops and direct-seeded rice. The rice-wheat-mungbean system showed the high GEY and was simply adapted at all study sites. The lowest and riskiest system productivity (Karnal and Patna: the rice-fallow-rice; Aduthurai: the rice-wheat-cowpea; Gazipur: the rice-maize system) showed higher probability of climatic risk. Selection of option improving productivity in rice-based cropping system is strongly affected by climate conditions such as rainfall and minimum daily temperature. Regardless crop sequence, the GEY of system with direct-seeded rice was relatively higher than transplanted rice, indicating that direct-seeded rice can be advantageous as transplanted rice. The success of direct-seeded rice in this study was possibly due to suitable rice varieties and sufficient water during rice growing season. Further investigation is needed to identify effect of changes in irrigation availability and to evaluate the performance of the systems using diverse short duration varieties of main or legume crops. Evaluation of the effect of residue retention is also required, particularly for long period of time using more data on residue.
Keywords: Intensification; Rice-based cropping system; Legumes; Dry season crops; Simulation; APSIM; Southeast and South Asia