Climate-smart crops for Myanmar’s dry regions
A research study in Myanmar seeks to identify crops with the lowest risk options for intensifying dryland cropping systems.
Myanmar (formerly Burma) is one country where vast tracts of rice fields span as far as the eyes can see. The abundance of natural resources and low labor costs favor the agriculture sector, which contributes 45% of the country’s gross domestic product. It comes as no surprise then that this sector is the primary livelihood source to 70% of the country’s population.
However, Myanmar’s agriculture depends highly on monsoon rains. The country’s Central Dry Zone (CDZ) area, which makes up about 13% of the total land area, and contributes 20% and 54% to the country’s total rice and pulse production, respectively, receives the lowest rainfall and is frequently affected by drought events.
Additionally, the mean annual yields of paddy rice, rainfed rice and pulses in Myanmar are severely affected by extreme weather events as well as low rainfall during the El Niño phase (warm phase) of the El Niño Southern Oscillation (ENSO), as what occurred in 2015. Recent analysis on historical crop yields shows that crop yields are higher in La Niña (cold phase) years.
The ENSO is a back-and-forth cycle between El Niño, La Niña, and neutral conditions which result in varying weather conditions in different areas of the globe. Such climatic variations pose a major setback to Myanmar’s agricultural productivity and more broadly, to the food security of this country where the poverty rate is already at 25%.
To address this issue, a project being led by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), funded by the CGIAR Research Program on Climate Change, Agriculture and Food Security in Southeast Asia (CCAFS SEA), seeks to understand and identify a range of promising rice-fallow intensification options to enhance agricultural productivity particularly in the regions of Magway, Pakokku, and Monwya in CDZ.
The project makes use of historical weather records, seasonal climate forecasts (SCF) and crop scenario analyses with crop-soil models to find more optimal farm management decisions. The SCF builds on the 40-year period historical weather data obtained from the Department of Meteorology and Hydrology (DoMH). An analysis by ICRISAT indicates that there are some clear signals in the climate patterns that when combined with local ‘systems’ information and in discussion with farmers, could lead to lower risk pre-season planning and in-season responsive management options. According to Dr Anthony Whitbread, project leader:
It is only when information about historical climate, forecasts, soils, crop response and farmer preference are interpreted together, that decisions relevant to a location and a farming system become reliable.
Based on the initial SCF in 2015 in the three focus regions, the lowest risk options for intensifying dryland cropping systems are: soybean, groundnut and pigeon pea during the rainy season; and short-season grain legumes: black gram, green gram and chickpea in the post-rainy seasons. Cultivation of these crops improves water use and nitrogen use efficiency.
For 2016-2017, ICRISAT plans to develop SCF for the entire CDZ to help farmers’ decisions based on relevant localized climate information in collaboration with Myanmar’s Department of Agriculture and Research (DoAR) and DoMH, and using outputs from the Indian Institute of Tropical Meteorology.
As the ensuing season (2016) is unfolding to be more like a normal rainfall growing season with a higher probability of better rainfall distribution in the months of October to November, there are likely to be good opportunities for post-rainy season crops to enhance productivity and income.
The study has likewise devised an approach using remote sensing and geographical information system (GIS) tools, to map areas with potential for intensifying the rice fallow phase. These rice fallows are areas where pulses or other crops may be planted to improve income, boost soil fertility and mitigate greenhouse gas emissions.
Under the CCAFS program and linked with the on-going pulses program of the Australian Centre for International Agricultural Research (ACIAR) in Myanmar, a Farmers’ Participatory Varietal Selection (FPVS) activity was organized by DoAR scientists. Several varieties of groundnuts, pigeon peas, chickpeas, green gram, black gram, and sorghum were evaluated for suitability in CDZ. The farmers picked Sinpadaytha 11 for groundnut, Monywashwedingar for pigeon pea, and Yezin-6 and Yezin-8 for chickpea. Seed production and distribution of these selected varieties will be conducted in ACIAR project areas.
While the project has had modest results, much remains to be accomplished by intensifying paddy and rainfed rice systems with the introduction of legumes resistant to yellow mosaic virus (YMV), utilizing variable length of growing season available to enhance water and nitrogen use efficiencies.
Dr Su Su Win, DoAR’s director of the Soil Science Department, expressed the need to conduct soil profile characterization in the CDZ area to enable crop modeling and determine suitable crops in terms of their water holding capacities.
Other major concerns include generating location-specific rainfall forecasts for more accurate crop management decisions. Additionally, mechanisms for timely and effective sharing of seasonal climate information to policymakers, stakeholders and farmers need to be thought out to facilitate appropriate cropping decisions and formulate the needed policy support.
This initiative will extend to the Climate-Smart Villages (CSVs) that were established by CCAFS in three focus countries: Vietnam, Cambodia and Laos. The CSV is a village or cluster of villages that are experiencing various climate challenges; hence, climate-smart agriculture interventions will be applied and tested together with the participation of the local community. CSVs are also convergence areas of collaborative research projects between and among local and international partner institutions.
About the author:
Meira Steffanie Andutan
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