New research reveals path to sustainable rice farming in Myanmar

Biochar Editorial Office, Shenyang Agricultural University

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Nitrogen use for improved profitability and sustainability of rice production in central Myanmar

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Credit: Xia Liang, Ian R. Willett, Arjun Pandey, Helen Suter, Gayathri Mekala, So Pyay Thar, Yunrui Li, Baobao Pan, Wenyan Xie & Deli Chen

Scientists have identified practical fertilizer strategies that can help rice farmers in Myanmar boost their profits, protect the environment, and improve food security. Recent research, led by an international team including experts from the University of Melbourne and local partners, provides new recommendations for nitrogen fertilizer use, aiming for a balance between high yields and low environmental costs.

Myanmar is one of Southeast Asia’s largest rice producers, yet struggles with low productivity, financial challenges, and food insecurity. Most local farmers rely on traditional practices, facing obstacles such as limited access to fertilizer, poor infrastructure, and high input costs. The country’s rice fields, vital for local diets and rural livelihoods, are especially sensitive to nitrogen management – the key factor influencing crop growth, environmental health, and farmer income.

Research showed that while rice yields respond modestly to added nitrogen in the monsoon season, dramatic improvements can be achieved through strategic fertilizer use in irrigated dry-season rice. In dry months, crops benefit from higher solar radiation, allowing yields to increase from 4 to 8 tons per hectare with optimized nitrogen inputs. Applying the right amount of fertilizer helps farmers achieve better profits and higher harvests, particularly when irrigation is available.

Yet, using too much nitrogen fertilizer can backfire. Excess inputs not only fail to increase yields but also harm the bacteria and natural processes that keep rice paddies fertile. The runoff of nitrogen-rich water threatens surrounding ecosystems, adding to pollution and greenhouse gas emissions.

The team conducted economic and environmental analyses to pinpoint both “economically optimal” and “ecologically optimal” nitrogen rates. During the monsoon season, the best economic results came from applying around 83 kilograms of nitrogen per hectare, providing a net economic benefit of nearly $617 per hectare. For irrigated dry-season rice, the optimal economic rate was higher, about 202 kilograms per hectare, which brought a $661 per hectare benefit. However, when accounting for the social and ecological costs of pollution and environmental damage, lower nitrogen application rates yielded far greater long-term gains.

By adopting the ecologically optimal nitrogen rates, 66 kilograms per hectare in the monsoon, and 48 kilograms per hectare in the dry season, farmers could reduce pollution and save money, with only a small drop in yield. The researchers estimated that this adjustment could avoid annual environmental costs of up to $368 per hectare, a substantial benefit compared with current practices. These findings offer authorities and farmers a new path to sustainability, where minor yield sacrifices translate into major gains for community health and future generations.

Farmer engagement also played a central role in the project. Surveys and focus groups revealed a strong preference for learning and decision-making through discussion, peer support, and social media such as Facebook. Instead of relying solely on top-down instructions or one-off mobile apps, farmers valued participatory platforms that allow for experience sharing and real-time advice. To support broader adoption of better fertilizer practices, the research team recommends expanding demonstration plots, interactive online forums, and tailored content delivered via popular digital platforms.

Policy-makers in Myanmar have taken note of the findings. New digital resources, databases, and agricultural extension websites are being built to help farmers and suppliers track fertilizer quality and crop management information. This integrated approach, emphasizing economics, ecology, and farmer participation, could transform rice production not just in Myanmar, but across similar regions in Southeast Asia.

The full research article, funded by Australian and Chinese agricultural research agencies, is published in Nitrogen Cycling, Volume 1, 2025.

 

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Journal Reference: Liang X, Willett IR, Pandey A, Suter H, Mekala G, et al. 2025. Nitrogen use for improved profitability and sustainability of rice production in central Myanmar. Nitrogen Cycling 1: e009  

https://www.maxapress.com/article/doi/10.48130/nc-0025-0009  

 

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About Nitrogen Cycling:
Nitrogen Cycling is a multidisciplinary platform for communicating advances in fundamental and applied research on the nitrogen cycle. It is dedicated to serving as an innovative, efficient, and professional platform for researchers in the field of nitrogen cycling worldwide to deliver findings from this rapidly expanding field of science.

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DOI

10.48130/nc-0025-0009 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Nitrogen use for improved profitability and sustainability of rice production in central Myanmar

Article Publication Date

11-Nov-2025

Missed the live session? Watch the recording now!

Biochar Editorial Office, Shenyang Agricultural University

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Fossil-Free Graphite from Biomass for Greener Process Industries

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Credit: Weihong Yang

The insightful Carbon Research Webinar, "Fossil-Free Graphite from Biomass for Greener Process Industries," is now available on-demand on YouTube!

This insightful discussion with Prof. Weihong Yang of KTH Royal Institute of Technology took place on Monday, August 11, 2025. In case you couldn't join us live, you can now catch the full session on-demand, where Prof. Yang explores innovative strategies for replacing fossil-based materials with sustainable, bio-based graphite.

He provides key insights into:

• Converting bioprecursors into fossil-free graphite.

• Its critical applications in lithium-ion batteries and other electrochemical systems.

• A comprehensive techno-economic assessment and life cycle analysis (LCA).

Don't miss this opportunity to learn from a leading expert. Watch the full recording at the link below!

https://youtu.be/CSOm5QI3kx4?si=-vADPe_2QGdMfkpi

 

What we learned from a decade-long genome cohort study of 100,000 Japanese individuals

Tohoku University

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Dispensing DNA solution into a 96-well plate using a liquid handling robot. 

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Credit: ©Tohoku University Tohoku Medical Megabank Organization

At a time when large-scale human genome analysis was not yet common, the Tohoku Medical Megabank Organization (ToMMo) launched its genome cohort study. After ten years of operating this ambitious project, they are sharing key insights regarding the techniques required to analyze, manage, maintain, and update a genomic database of 100,000 people. For researchers around the world, the knowledge gained from this study is a valuable resource to advance genome research, and the research findings derived from it can help build the foundation for genetic-based personalized healthcare.

The findings were published in JMA Journal on October 3, 2025.

Starting in 2013, ToMMo completed whole genome sequencing for 100,000 Japanese individuals. Whole genome sequencing is the process of reading the entirety of the DNA sequence - the building blocks of life that make up who we are. However, conducting in-depth analysis at such a large scale is a major undertaking with many technical and operational limitations that serve as a huge challenge. Even today, only a few countries have conducted genome sequencing at this scale.

"Maintaining high accuracy and consistent quality required careful planning, optimized equipment, and developing innovative new techniques," explains Fumiki Katsuoka, first author of the paper.

This paper shared insights gained over ten years in operating whole genome sequencing, managing quality, and building data infrastructure.

In the early phase, they developed a method named qMiSeq in which small-scale sequencing analyses were performed for each group of samples (typically 96 samples), and the optimal sequencing conditions were determined based on the obtained data volume. After the introduction of high-throughput sequencers, they established a protocol named iDeal, which divides the sequencing of each group into multiple runs to equalize data yield. Both approaches are based on simple concepts, yet they are extremely effective methods.

"As large-scale genome sequencing is becoming more common, we want to share everything we learned during these ten years," remarks first author Fumiki Katsuoka. "We are very proud that some of the unique techniques we developed are now used by other institutions."

Transparency is an important aspect of their project, as frequency and summary data from ToMMo's 100,000 genome project are freely available on jMorp and widely used by researchers worldwide, whereas individual-level genome data are accessible under appropriate conditions following an application-based review process.

As more researchers are expected to conduct large-scale genome analyses, it is predicted that more healthcare providers will use the data to offer innovative medical solutions. The insights from this study will serve as a valuable resource for the genomics community in Japan and around the world, contributing to the advancement of genomic medicine and personalized prevention.

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Journal

JMA Journal

DOI

10.31662/jmaj.2025-0159 

Article Title

Advancements in Whole Genome Sequencing Protocols: A Decade of In-House Operations and Quality Controls at the Tohoku Medical Megabank

Overview of Genome and Multi-omics Analysis in the Tohoku Medical Megabank Project. As illustrated, various types of samples have been collected along with data on participants' health, lifestyle, and medical history. TMM: Tohoku Medical Megabank. 

Credit

©Katsuoka et al.

 

Anthropogenic changes threaten survival of Eastern Himalayan birds

Indian Institute of Science (IISc)

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A Chestnut-headed Tesia being ringed by trained field staff

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Credit: Akshay Bharadwaj

Insectivorous birds found in the understorey of the Eastern Himalayas are under threat due to habitat degradation, a new study from the Indian Institute of Science (IISc) has found.

Researchers at the Centre for Ecological Sciences (CES) studied how changes in forest microclimates after selective logging influence the survival of wild bird populations in the Eaglenest Wildlife Sanctuary, Arunachal Pradesh, over 10 years (2011-2021).

The team tagged birds with lightweight aluminium rings and revisited the same sites annually to track their survival and changes in body mass. They paired this dataset with temperature-humidity loggers placed in both primary and logged forests, to estimate how understorey insectivorous birds – those that live below the canopy – adapt to microclimatic changes. “Using these long-term data sets, we can better understand why some species survive after logging while others decline strongly,” says Akshay Bharadwaj, a former Master of Science student at CES and corresponding author of the study.

Overall, the team found that logged forests are consistently hotter and drier during the day and colder at night – in comparison to primary forests – exposing birds to stressful fluctuations due to loss of the forest canopy. These conditions, the scientists say, could intensify with climate change, especially in the Eastern Himalayas where bird species are thermal specialists – uniquely adapted to stable climates.

Their findings reveal that these birds, which utilise very different primary and logged forest microclimatic niches, are most adversely affected in a logged forest – they experience a decline in body mass, and steep declines in long-term survival. “Species that can still find microclimates in logged forests similar to their original forest homes are surviving after selective logging. It is those which can’t match their old conditions that face steep declines,” adds Bharadwaj.

“Being in the field studying these fascinating animals is always a thrill. We work in a relatively remote part of Arunachal Pradesh, collecting field data under sometimes challenging field conditions – rain, leeches, and elephants,” says co-author Umesh Srinivasan, Assistant Professor at CES.

Based on their findings, the researchers suggest that conservation strategies should prioritise preserving primary forest across elevational gradients. “In degraded areas, we can consider microclimatic remediation, such as creating shade covers or supplementing water sources to mimic original microhabitats to support vulnerable species,” explains Bharadwaj. “The impacts of forest degradation will impact food chains that are part of larger ecosystem processes.” A drop in the number of insectivorous birds can lead to an increase in insect numbers, which in turn can affect ecological stability, he adds.

The study highlights the significance of understanding why certain species of birds are declining after logging, and how microclimatic niches in disturbed habitats influence population dynamics. “Long-term datasets are crucial for this, and we are continuing to collect these data to try and plan effective conservation measures for these bird species,” explains Srinivasan. “As the climate warms, the persistence of microhabitats will be crucial for many species to remain resilient to climate impacts.”

  

The study site at Eaglenest Wildlife Sanctuary in Arunachal Pradesh, India

Credit

Ritobroto Chanda

Journal

Journal of Applied Ecology

DOI

10.1111/1365-2664.70192 

Article Title

Microclimatic niche shifts predict long-term survival and body mass declines in a warmer and more degraded world

Article Publication Date

11-Nov-2025

 

A novel approach to predicting Arctic sea-ice extent

Institute of Atmospheric Physics, Chinese Academy of Sciences

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Overall architecture of September Pan-Arctic SIE prediction models based on the SWR and LSTM methods

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Credit: Baoqiang Tian

Under the influence of global warming, the Arctic is transitioning from a state dominated by multi-year thick ice to a "New Arctic" characterized predominantly by first-year thin ice. This younger ice is more fragile and prone to melting, which not only exacerbates the instability of the ice cover but also introduces new challenges for sea-ice prediction. Accurate forecasting of sea ice is of significant value for understanding the climate system and ensuring the safety of Arctic navigation. However, due to the combined influence of atmospheric, oceanic, and other factors, precise prediction remains a key international research focus.

 

Recently, associate professor Baoqiang Tian from the Institute of Atmospheric Physics, Chinese Academy of Sciences, and Professor Ke Fan from Sun Yat-sen University have developed a new real-time prediction method for September Arctic sea-ice extent, based on the interannual increment and stepwise regression approaches. The findings were published in Atmospheric and Oceanic Science Letters under the title "A novel stepwise regression method for predicting September Pan-Arctic sea-ice extent: comparison with long short-term memory neural networks."

 

The study shows that this method, which integrates initial sea-ice conditions with thermodynamic and dynamic processes, selects effective predictors through stepwise regression and incorporates the interannual increment approach, demonstrates high predictive performance for September Pan-Arctic sea-ice extent. Compared with LSTM (long short-term memory) neural networks, the new method exhibits smaller prediction errors and greater stability in independent tests from 2014 to 2022. Its prediction accuracy also surpasses that of the forecasts released by the Sea Ice Outlook. Although LSTM performs well during the training phase, its real-world prediction robustness is inferior to the new method—a limitation potentially attributable to the limited availability of sea-ice data, which may lead to overfitting in complex machine learning models.

 

Professor Ke Fan, corresponding author of the paper, explains that, "Our prediction method not only considers the independence of predictors to avoid overfitting, but also amplifies the prediction signal through the interannual increment approach, thereby enhancing the model's predictive capability."

 

This study offers a new perspective for improving seasonal predictions of Arctic sea ice.

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Journal

Atmospheric and Oceanic Science Letters

DOI

10.1016/j.aosl.2025.100727