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Mobile phone applications (apps) designed to assist smallholder farmers improve decision‐making have been revolutionizing the agriculture sector. These apps offer solutions to farmer information needs by providing weather information, crop market trends, pest and disease damage identification, and advice on pesticide and fertilizer use. They also facilitate interaction with fellow farmers, extension workers and other stakeholders in the value chain who are interested in information exchange. Much previous research has investigated the contribution of mobile apps to agricultural production. This study explored the agricultural mobile apps available in Myanmar, analyzed factors affecting their use and assessed the potential for farm‐based decision support. Our findings indicate that when introducing mobile‐based tools, focus should be given to younger, more educated farmers growing more specialized crops. The main constraints to adopt agricultural apps are lack of access to smartphone and/or internet (63%) and lack of digital knowledge (20%). However, smallholder farmers in Myanmar were optimistic and positive toward agricultural apps for effective utilization. We also found that majority of the surveyed farmers were familiar with information received through Facebook groups. Incorporating useful information and functions from an agricultural mobile app to a Facebook Page could have a more useful and sustainable impact. [ABSTRACT FROM AUTHOR]

Agriculture in low latitude countries such as Sri Lanka is already operating at the maximum temperature limits for crop growth and faces increased production risk from expected climate change. Sri Lanka is a developing country with limited economic and technological capacity to develop adaptation strategies; hence more vu lnerable to climate change than developed countries. Coconut (Cocos nucifera L) is a rain fed perennial crop important in Sri Lankan culture, food consumption and the economy. It is the second most important food in the Sri Lankan diet after rice. Several studies have examined the impact of climate change on Sri Lankan agriculture, but none were conducted to simulate the impact of future climate change and future adaptation strategies on coconut production, or to calculate the economic welfare effects for different stakeholders in the coconut value chain. In this paper we report the development of an economic model of the coconut value chain that allows prediction of welfare impacts, and a quantitative representation of coconut yield that allows prediction of the impact of changing climatic conditions. The average outcome of 16 climate models was used to generate future climatic conditions, with two future climatic scenarios for 2020, 2030 and 2050 considered for three production regions. The most important yield estimate was a yield decline of more than 10 percent in the wet climatic zone due to the expected increase of maximum temperature. Without extra adaptation measures this is predicted to result in a loss to the industry of 4,795 Rs. Million annually by 2020, which is nearly 4.7 percent of the total value of the industry at equilibrium prices and quantities. The negative impact of climate change has the potential to be reduced with the implementation of additional adaptation practices. However, the cost effectiveness of these practices needs to be considered. Wider adoption of fertilizer application at specific times and moisture conservation practices are estimated to be economically beneficial. [ABSTRACT FROM AUTHOR]

Decision Support Tools (DSTs) in agriculture have been widely developed but have not been well accepted by smallholder farmers. One reason for the limited use is that the tools do not account for the complexity of heterogeneous smallholder farming systems. Identifying farm typologies has facilitated technology transfer to target groups of farmers. Accounting for heterogeneity in farm systems can help in designing and deploying DSTs to address farmer needs. Typology analysis was applied to a 600-household survey dataset to identify different farm system types. Qualitative participatory research was used to assess the potential deployment of DSTs for fertilizer management. Six types of farm systems were identified with distinct characteristics in the study area of central Myanmar. Participatory research through focus group discussions with 34 participants from the six different farm types validated the farm typologies and found that farmers from one type considered that DSTs could be useful in gaining more information and knowledge. An important finding was that DSTs providing prescriptive advice were inconsistent with what many farmers want. Farmers indicated that discussion groups are a preferred learning-based approach rather than a prescriptive tool. Farmers preferred video clips and infographics integrated into existing familiar digital platforms. This study identifies heterogeneity within a large farm sample and develops a deeper understanding of fertilizer decisions as well as knowledge and intentions related to the use of DSTs or apps via follow-up focus group discussions. Incorporating a participatory research framework with typology identification can have a beneficial role in direct interactions with smallholders that may increase their acceptability of DSTs. This study has generated valuable information about farmer types and serves as a starting point for developing a framework for discussion support systems that may better relate to the needs of farmers. [ABSTRACT FROM AUTHOR]

Agriculture in Myanmar has substantial development potential given the abundance of land, water, and labor resources in the country. Despite this, agricultural productivity in Myanmar is low and farm incomes are amongst the lowest in Asia. The underperformance of crops and low yield is widely reported to be due to low fertilizer use by smallholders. This study investigated the perceptions of smallholders about fertilizer use for cereal crops by considering their motives and decision making. We reported results of a 600 smallholders' survey and tested whether the reportedly low fertilizer use by smallholders is generally true for central Myanmar. We compared the fertilizer application timing against recommended "good management practices". Among the surveyed rice farmers, the average fertilizer applied was much higher than previously reported national average fertilizer rates while the majority of the surveyed maize farmers were found to be applying less than the national recommended rates. With respect to timing, nearly half of the surveyed smallholders were not applying nitrogen at the estimated panicle initiation stage, which is often crucial to increase yield, and the majority (82%) of smallholders were applying phosphorus throughout the growth stages, when earlier applications are desirable. Smallholders may be able to reduce the cost of labor by reducing the number of P applications and avoiding late applications. [ABSTRACT FROM AUTHOR]

Shifts in rainfall and rising temperatures due to climate change pose a formidable challenge to the sustainability of broadacre crop yields in Western and South-Eastern Australia. Output from18 Global Climate Models (GCMs) for the Special Report on Emission Scenarios (SRES) A2 scenario was statistically downscaled to four contrasting locations. For the first time in these regions, bias corrected statistically downscaled climate data were employed to drive the Agricultural Production Systems Simulator (APSIM) crop model that integrates the effects of soil, crop phenotype, and management options for a quantitative comparison of crop yields and phenology under an historical and a plausible projected climate. The dynamic APSIM simulation model explore the implications of climate change across multiple locations and multiple time periods (1961–2010, 2030, 2060 and 2090) for multiple key crops (wheat, barley, lupin, canola, field pea) grown in three different types of soil. On average, the ensemble of downscaled GCM projections show a decrease in rainfall in the future at the four locations considered, with increased variability at two locations. At all locations and for five crops, future changes in both crop biomass and grain yield are strongly associated with changes in rainfall (P = 0.05 to P = 0.001). The overall rainfall amount is critical in determining yields but, equally, higher future temperatures can contribute to reducing crop productivity primarily due to advanced crop phenology. For example, for wheat cropping at Hamilton (a higher rainfall site), there is a significant advancement in median flowering date for 2030, 2060, and 2090 of 10, 18, and 29 days respectively with a significant 0.50% grain yield changes for each percentage change in rainfall compared to significant 0.90% grain yield changes in Cunderdin (a lower rainfall site). At all sites except Hamilton, the change in crop grain yield is significantly correlated (P = 0.001) with the percentage change in the future rainfall and the impact increased progressively from higher rainfall to lower rainfall sites. However, the magnitude of the change in crop phenology and yield were not significantly different between soil types. These results help to define regions of concern and their relative importance in the coming years. In this future climate the negative consequences for crop yields and advancement of phenology relative to baseline are not uniform across crops and locations. Of the crops studied – wheat, barley, lupin, canola and field pea – field pea is the most sensitive to the projected future climate changes, and the ensemble median changes in field pea yield range from a decrease of 12% to a decrease of 45%, depending on location. These results highlight the importance of research and policy to support strategies for adapting to climate change, such as advances in agronomy, soil moisture conservation, seasonal climate forecasting and breeding new crop varieties. [ABSTRACT FROM AUTHOR]