Repositorio Nacional

High-resolution mapping of rice fields is crucial for understanding and managing rice cultivation in countries like Bangladesh, particularly in the face of climate change. Rice is a vital crop, cultivated in small scale farms that contributes significantly to the economy and food security in Bangladesh. Accurate mapping can facilitate improved rice production, the development of sustainable agricultural management policies, and formulation of strategies for adapting to climatic risks. To address the need for timely and accurate rice mapping, we developed a framework specifically designed for the diverse environmental conditions in Bangladesh. We utilized Sentinel-1 and Sentinel-2 time-series data to identify transplantation and peak seasons and employed the multi-Otsu automatic thresholding approach to map rice during the peak season (April–May). We also compared the performance of a random forest (RF) classifier with the multi-Otsu approach using two different data combinations: D1, which utilizes data from the transplantation and peak seasons (D1 RF) and D2, which utilizes data from the transplantation to the harvest seasons (D2 RF). Our results demonstrated that the multi-Otsu approach achieved an overall classification accuracy (OCA) ranging from 61.18% to 94.43% across all crop zones. The D2 RF showed the highest mean OCA (92.15%) among the fourteen crop zones, followed by D1 RF (89.47%) and multi-Otsu (85.27%). Although the multi-Otsu approach had relatively lower OCA, it proved effective in accurately mapping rice areas prior to harvest, eliminating the need for training samples that can be challenging to obtain during the growing season. In-season rice area maps generated through this framework are crucial for timely decision-making regarding adaptive management in response to climatic stresses and forecasting area-wide productivity. The scalability of our framework across space and time makes it particularly suitable for addressing field data scarcity challenges in countries like Bangladesh and offers the potential for future operationalization.

Synthetic Aperture Radar Random Forest Boro Rice In-Season Maps CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SAR (RADAR) RICE FLOODING CLIMATE CHANGE

Economics of crop residue management

Vijesh Krishna Maxwell Mkondiwa (2023, [Artículo])

More than five billion metric tons of agricultural residues are produced annually worldwide. Despite having multiple uses and significant potential to augment crop and livestock production, a large share of crop residues is burned, especially in Asian countries. This unsustainable practice causes tremendous air pollution and health hazards while restricting soil nutrient recycling. In this review, we examine the economic rationale for unsustainable residue management. The sustainability of residue utilization is determined by several economic factors, such as local demand for and quantity of residue production, development and dissemination of technologies to absorb excess residue, and market and policy instruments to internalize the social costs of residue burning. The intervention strategy to ensure sustainable residue management depends on public awareness of the private and societal costs of open residue burning.

Crop Biomass Residue Burning Environmental Effects CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROPS BIOMASS RESIDUES ENVIRONMENTAL IMPACT CLIMATE CHANGE SMALLHOLDERS TECHNOLOGY ADOPTION

Character association study in maize hybrids developed through integration of rapid cycle genomic selection and doubled haploid technology for heat stress tolerance

Prakash Kuchanur Ayyanagouda Patil Pervez Zaidi vinayan mt (2023, [Artículo])

Multi-Parental Synthetics Rapid Cycle Genomic Selection Phenotypic Correlation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE HEAT STRESS MARKER-ASSISTED SELECTION DOUBLED HAPLOIDS PHENOTYPIC VARIATION CLIMATE CHANGE

Heat-tolerant maize for rainfed hot, dry environments in the lowland tropics: from breeding to improved seed delivery

Pervez Zaidi vinayan mt Sudha Nair Prakash Kuchanur Ayyanagouda Patil Atul Kulkarni Prasanna Boddupalli (2023, [Artículo])

Lowland Tropics CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE DROUGHT HEAT STRESS LOWLAND MAIZE VAPOUR PRESSURE DEFICIT

Review of Nationally Determined Contributions (NCD) of China from the perspective of food systems

Tek Sapkota (2023, [Documento de trabajo])

China is the largest emitter of greenhouse gases (GHG) and one of the countries most affected by climate change. China's food systems are a major contributor to climate change: in 2018, China's food systems emitted 1.09 billion tons of carbondioxide equivalent (CO2eq) GHGs, accounting for 8.2% of total national GHG emissions and 2% of global emissions. According to the Third National Communication (TNC) Report, in 2010, GHG emissions from energy, industrial processes, agriculture, and waste accounted for 78.6%, 12.3%, 7.9%, and 1.2% of total emissions, respectively, (excluding emissions from land use, land-use change and forestry (LULUCF). Total GHG emissions from the waste sector in 2010 were 132 Mt CO2 eq, with municipal solid waste landfills accounting for 56 Mt. The average temperature in China has risen by 1.1°C over the last century (1908–2007), while nationally averaged precipitation amounts have increased significantly over the last 50 years. The sea level and sea surface temperature have risen by 90 mm and 0.9°C respectively in the last 30 years. A regional climate model predicted an annual mean temperature increase of 1.3–2.1°C by 2020 (2.3–3.3°C by 2050), while another model predicted a 1–1.6°C temperature increase and a 3.3–3.7 percent increase in precipitation between 2011 and 2020, depending on the emissions scenario. By 2030, sea level rise along coastal areas could be 0.01–0.16 meters, increasing the likelihood of flooding and intensified storm surges and causing the degradation of wetlands, mangroves, and coral reefs. Addressing climate change is a common human cause, and China places a high value on combating climate change. Climate change has been incorporated into national economic and social development plans, with equal emphasis on mitigation and adaptation to climate change, including an updated Nationally Determined Contribution (NDC) in 2021. The following overarching targets are included in China's updated NDC: • Peaking carbon dioxide emissions “before 2030” and achieving carbon neutrality before 2060. • Lowering carbon intensity by “over 65%” by 2030 from the 2005 level. • Increasing forest stock volume by around 6 billion cubic meters in 2030 from the 2005 level. The targets have come from several commitments made at various events, while China has explained very well the process adopted to produce its third national communication report. An examination of China's NDC reveals that it has failed to establish quantifiable and measurable targets in the agricultural sectors. According to the analysis of the breakdown of food systems and their inclusion in the NDC, the majority of food system activities are poorly mentioned. China's interventions or ambitions in this sector have received very little attention. The adaptation component is mentioned in the NDC, but is not found to be sector-specific or comprehensive. A few studies have rated the Chinese NDC as insufficient, one of the reasons being its failure to list the breakdown of each sector's clear pathway to achieving its goals. China's NDC lacks quantified data on food system sub-sectors. Climate Action Trackers' "Insufficient" rating indicates that China's domestic target for 2030 requires significant improvements to be consistent with the Paris Agreement's target of 1.5°C temperature limit. Some efforts are being made: for example, scientists from the Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences (IEDA-CAAS) have developed methods for calculating GHG emissions from livestock and poultry farmers that have been published as an industrial standard by the Ministry of Agriculture and Rural Affairs, PRC (Prof Hongmin Dong, personal communication) but this still needs to be consolidated and linked to China’s NDC. The updated Nationally Determined Contributions fall short of quantifiable targets in agriculture and food systems as a whole, necessitating clear pathways. China's NDC is found to be heavily focused on a few sectors, including energy, transportation, and urban-rural development. The agricultural sectors' and food systems' targets are vague, and China's agrifood system has a large carbon footprint. As a result, China should focus on managing the food system (production, processing, transportation, and food waste management) to reduce carbon emissions. Furthermore, China should take additional measures to make its climate actions more comprehensive, quantifiable, and measurable, such as setting ambitious and clear targets for the agriculture sector, including activity-specific GHG-reduction pathways; prioritizing food waste and loss reduction and management; promoting sustainable livestock production and low carbon diets; reducing chemical pollution; minimizing the use of fossil fuel in the agri-system and focusing on developing green jobs, technological advancement and promoting climate-smart agriculture; promoting indigenous practices and locally led adaptation; restoring degraded agricultural soils and enhancing cooperation and private partnership. China should also prepare detailed NDC implementation plans including actions and the GHG reduction from conditional targets.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GREENHOUSE GAS EMISSIONS CLIMATE CHANGE FOOD SYSTEMS LAND USE CHANGE AGRICULTURE POLICIES DATA ANALYSIS FOOD WASTES

Agroecology can promote climate change adaptation outcomes without compromising yield in smallholder systems

Sieglinde Snapp Yodit Kebede Eva Wollenberg (2023, [Artículo])

A critical question is whether agroecology can promote climate change mitigation and adaptation outcomes without compromising food security. We assessed the outcomes of smallholder agricultural systems and practices in low- and middle-income countries (LMICs) against 35 mitigation, adaptation, and yield indicators by reviewing 50 articles with 77 cases of agroecological treatments relative to a baseline of conventional practices. Crop yields were higher for 63% of cases reporting yields. Crop diversity, income diversity, net income, reduced income variability, nutrient regulation, and reduced pest infestation, indicators of adaptative capacity, were associated with 70% or more of cases. Limited information on climate change mitigation, such as greenhouse gas emissions and carbon sequestration impacts, was available. Overall, the evidence indicates that use of organic nutrient sources, diversifying systems with legumes and integrated pest management lead to climate change adaptation in multiple contexts. Landscape mosaics, biological control (e.g., enhancement of beneficial organisms) and field sanitation measures do not yet have sufficient evidence based on this review. Widespread adoption of agroecological practices and system transformations shows promise to contribute to climate change services and food security in LMICs. Gaps in adaptation and mitigation strategies and areas for policy and research interventions are finally discussed.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CROPS FOOD SUPPLY GAS EMISSIONS GREENHOUSE GASES FARMING SYSTEMS AGROECOLOGY FOOD SECURITY LESS FAVOURED AREAS SMALLHOLDERS YIELDS NUTRIENTS BIOLOGICAL PEST CONTROL CARBON SEQUESTRATION LEGUMES

Calibrated multi-model ensemble seasonal prediction of Bangladesh summer monsoon rainfall

Nachiketa Acharya Carlo Montes Timothy Joseph Krupnik (2023, [Artículo])

Bangladesh summer monsoon rainfall (BSMR), typically from June through September (JJAS), represents the main source of water for multiple sectors. However, its high spatial and interannual variability makes the seasonal prediction of BSMR crucial for building resilience to natural disasters and for food security in a climate-risk-prone country. This study describes the development and implementation of an objective system for the seasonal forecasting of BSMR, recently adopted by the Bangladesh Meteorological Department (BMD). The approach is based on the use of a calibrated multi-model ensemble (CMME) of seven state-of-the-art general circulation models (GCMs) from the North American Multi-Model Ensemble project. The lead-1 (initial conditions of May for forecasting JJAS total rainfall) hindcasts (spanning 1982–2010) and forecasts (spanning 2011–2018) of seasonal total rainfall for the JJAS season from these seven GCMs were used. A canonical correlation analysis (CCA) regression is used to calibrate the raw GCMs outputs against observations, which are then combined with equal weight to generate final CMME predictions. Results show, compared to individual calibrated GCMs and uncalibrated MME, that the CCA-based calibration generates significant improvements over individual raw GCM in terms of the magnitude of systematic errors, Spearman's correlation coefficients, and generalised discrimination scores over most of Bangladesh areas, especially in the northern part of the country. Since October 2019, the BMD has been issuing real-time seasonal rainfall forecasts using this new forecast system.

Multi-Model Ensemble Seasonal Forecasting CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE SERVICES FORECASTING MONSOONS

Sistemas agroalimentarios sustentables: aumento de rentabilidad con uso eficiente de insumos y preservación del medio ambiente

Jelle Van Loon (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRIFOOD SYSTEMS SUSTAINABLE INTENSIFICATION COVID-19 CONFLICTS CLIMATE CHANGE