scholarly journals Machine Learning Speeding Up the Development of Portfolio of New Crop Varieties to Adapt to and Mitigate Climate Change

2021 ◽  
Author(s):  
Abdallah Bari ◽  
Hassan Ouabbou ◽  
abderrazek Jilal ◽  
Hamid Khazaei ◽  
Fred Stoddard ◽  
...  

Climate change poses serious challenges to achieving food security in a time of a need to produce more food to keep up with the worlds increasing demand for food. There is an urgent need to speed up the development of new high yielding varieties with traits of adaptation and mitigation to climate change. Mathematical approaches, including ML approaches, have been used to search for such traits, leading to unprecedented results as some of the traits, including heat traits that have been long sought-for, have been found within a short period of time.

2011 ◽  
Vol 80 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Ole W. Pedersen

AbstractThis article examines the role human rights instruments play when states seek to adopt regulatory initiatives in the name of addressing climate change. The article argues that a series of important restrictions exist. Governments responding to climate change need to take into account existing human rights. This observation is particularly relevant for countries implementing Reduction of Emissions from Deforestation and Degradation (REDD) projects and for countries taking part in Clean Development Mechanism (CDM) projects under the Kyoto Protocol. The article likewise argues that special human rights obligations arise in relation to the risks associated with climate change. These place on states a responsibility to secure risk assessment and risk communication while taking steps to mitigate climate change-associated risks. While the article considers these requirements to constitute an absolute minimum, it is argued that they can offer a way of securing that national governments are accountable when it comes to climate change responses. On the other hand, it will be shown that these human rights restrictions will sometimes have the potential to run counter to the adoption of effective climate change responses.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Charlotte Remteng ◽  
Johnson Nkem ◽  
Linus Mofor ◽  
James Murombedzi

Purpose This paper aims to provide an analysis of gender strategies in the planning, programmes towards the implementation of Africa’s Nationally Determined Contributions (NDCs). It involved the identification and disaggregation of climate risks on women key climate affected sectors (water, energy, agriculture, health, energy). Design/methodology/approach This involves review of vast scholarly and academic research, to establishment of linkages and interlinkages between the risks. A diagnostic analysis was done on the NDCs to understand the orientation of gender considerations in the NDCs of African countries, and then an assessment on emerging opportunities and empowerment of women to address climate change was carried out as an un-detachable component of gender considerations. Findings Poverty, cultural barriers and inequality, climatic risks such as floods, occurrence of infectious diseases and water scarcity create life threatening situations for women as well as their livelihood Analysis on the NDCs (and INDCs) of all African countries show that over 85% of actions reference gender. At the regional level West Africa has the highest gender actions in their NDCs (41%), East Africa 25%, Southern Africa 15%, Central Africa 8% and North Africa 6%. The coping responses of women, their knowledge about the environment and the environmental services they offer, provide great opportunities for them in the climate change scenario which is seldom spoken about. Empowerment of women by providing access to Information, education, training; sensitization on various facets of climate change; the risks, consequences, possible sustainable solutions (Adaptation and mitigation) and their basic rights especially with regards to land and ownership is necessary, and can help reduce the climatic risks they face. Research limitations/implications The limitation of this study was time constraint as the research was done during my fellowship at the United Nations Economic Commission for Africa which was a short period in relation to the fact that the authors were assigned to other duties. Practical implications Though most African countries are making an effort towards gender integration in their NDCs, they need to carry out systematic gender analysis; collecting and using sex-disaggregated data; establishing gender-sensitive benchmarks and indicators; and developing practical tools to support increased attention to gender perspectives. Social implications Climate change is a serious threat to humanity and views from mostly those affected indicates that there is still a big disconnect between the ambitious agendas set by various stakeholders involved (International organizations, governments and regional organizations), and the real grassroots initiatives, actions and programs being implemented in the ground. There is also inarguably increasing evidence that climate change is amplifying gender inequality, the vulnerability of women and children; consequently, a serious barrier to the achievement of the Paris Agreement, UN 2030 Sustainable development goals, the 2063 Africa Union Agenda. Originality/value Though there exist many research papers on climate and gender and also on NDCs, creating a link between gender risks and climate policies, strategies and programs gives the issue of gender and climate change “high importance”. An integrated approach on identifying the risks makes policies coherent.


2020 ◽  
Vol 14 (1) ◽  
pp. 28-37
Author(s):  
Ayana Angassa Abdeta ◽  
Summer Mabula

This paper presents perception of farmers in terms of adaptation and mitigation to climate change in Kgalagadi-North District. The study used qualitative survey method and results are derived from purposively selected interviews using semi-structured questionnaire. The research focused on participants who were aged 50 years and above. Data were summarized and analysed qualitatively using descriptive statistics. Farmers’ perceptions showed that frequent wildfire was major cause of climate change. Farmers further mentioned that they were affected by irregular rainfall, increased temperature and recurrent droughts. The findings confirmed that milk production and number of calves per cows were in declining trend over the last 30 years. The results showed increased trends in donkeys’ population signifying importance of donkeys in farmer’s herd as adaptation strategy. The results revealed that livestock diversification, making use of migratory approach in search of pasture and water, and sale of livestock before onset of drought are key adaptation strategies developed by farmers. The results also displayed that farmers mainly used to practice different strategies such as saving food and seeds, use of drought tolerant crops, diversifying crop varieties and changing of planting dates to overcome the irregularity of rainfall. Results revealed that farmers mostly used to pray for rains and involve in environmental management for adaptation and mitigating. It seems that adaptation and mitigation measures employed by farmers helped them to enhance resilience and reduce vulnerability. We suggest that farmers’ experience for adaptation and mitigation to climate change plays a crucial role in scientific research and sustainable development.


Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.


2019 ◽  
Vol 11 (4) ◽  
pp. 1235-1249 ◽  
Author(s):  
A. Mentzafou ◽  
A. Conides ◽  
E. Dimitriou

Abstract Coastal ecosystems are linked to socio-economic development, but simultaneously, are particularly vulnerable to anthropogenic climate change and sea level rise (SLR). Within this scope, detailed topographic data resources of Spercheios River and Maliakos Gulf coastal area in Greece, combined with information concerning the economic value of the most important sectors of the area (wetland services, land property, infrastructure, income) were employed, so as to examine the impacts of three SLR scenarios, compiled based on the most recent regional projections reviewed. Based on the results, in the case of 0.3 m, 0.6 m and 1.0 m SLR, the terrestrial zone to be lost was estimated to be 6.2 km2, 18.9 km2 and 31.1 km2, respectively. For each scenario examined, wetlands comprise 68%, 41% and 39% of the total area lost, respectively, reflecting their sensitivity to even small SLR. The total economic impact of SLR was estimated to be 75.4 × 106 €, 161.7 × 106 € and 510.7 × 106 € for each scenario, respectively (3.5%, 7.5% and 23.7% of the gross domestic product of the area), 19%, 17% and 8% of which can be attributed to wetland loss. The consequences of SLR to the ecosystem services provided are indisputable, while adaptation and mitigation planning is required.


2019 ◽  
Vol 20 (5) ◽  
pp. 540-550 ◽  
Author(s):  
Jiu-Xin Tan ◽  
Hao Lv ◽  
Fang Wang ◽  
Fu-Ying Dao ◽  
Wei Chen ◽  
...  

Enzymes are proteins that act as biological catalysts to speed up cellular biochemical processes. According to their main Enzyme Commission (EC) numbers, enzymes are divided into six categories: EC-1: oxidoreductase; EC-2: transferase; EC-3: hydrolase; EC-4: lyase; EC-5: isomerase and EC-6: synthetase. Different enzymes have different biological functions and acting objects. Therefore, knowing which family an enzyme belongs to can help infer its catalytic mechanism and provide information about the relevant biological function. With the large amount of protein sequences influxing into databanks in the post-genomics age, the annotation of the family for an enzyme is very important. Since the experimental methods are cost ineffective, bioinformatics tool will be a great help for accurately classifying the family of the enzymes. In this review, we summarized the application of machine learning methods in the prediction of enzyme family from different aspects. We hope that this review will provide insights and inspirations for the researches on enzyme family classification.


Author(s):  
Sarah Blodgett Bermeo

This chapter introduces the role of development as a self-interested policy pursued by industrialized states in an increasingly connected world. As such, it is differentiated from traditional geopolitical accounts of interactions between industrialized and developing states as well as from assertions that the increased focus on development stems from altruistic motivations. The concept of targeted development—pursuing development abroad when and where it serves the interests of the policymaking states—is introduced and defined. The issue areas covered in the book—foreign aid, trade agreements between industrialized and developing countries, and finance for climate change adaptation and mitigation—are introduced. The preference for bilateral, rather than multilateral, action is discussed.


2020 ◽  
Vol 12 (20) ◽  
pp. 8369
Author(s):  
Mohammad Rahimi

In this Opinion, the importance of public awareness to design solutions to mitigate climate change issues is highlighted. A large-scale acknowledgment of the climate change consequences has great potential to build social momentum. Momentum, in turn, builds motivation and demand, which can be leveraged to develop a multi-scale strategy to tackle the issue. The pursuit of public awareness is a valuable addition to the scientific approach to addressing climate change issues. The Opinion is concluded by providing strategies on how to effectively raise public awareness on climate change-related topics through an integrated, well-connected network of mavens (e.g., scientists) and connectors (e.g., social media influencers).


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