Redesigning crop varieties to win the race between climate change and food security

Kevin Pixley Jill Cairns Santiago Lopez-Ridaura Chris Ojiewo Baloua Nébié Godfrey Asea Biswanath Das Benoit Joseph Batieno Clare Mukankusi Sarah Hearne Kanwarpal Dhugga Sieglinde Snapp Ernesto Adair Zepeda Villarreal (2023, [Artículo])

Crop Breeding Expert Survey CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CROPPING SYSTEMS FOOD SECURITY CROPS

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

Tek Sapkota (2023, [Documento de trabajo])

Agriculture is one of the fundamental pillars of the 2022–2027 Bottom-up Economic Transformation Plan of the Government of Kenya for tackling complex domestic and global challenges. Kenya's food system is crucial for climate change mitigation and adaptation. Kenya has prioritized aspects of agriculture, food, and land use as critical sectors for reducing emissions towards achieving Vision 2030's transformation to a low-carbon, climate-resilient development pathway. Kenya's updated NDC, as well as supporting mitigation and adaptation technical analysis reports and other policy documents, has identified an ambitious set of agroecological transformative measures to promote climate-smart agriculture, regenerative approaches, and nature-positive solutions. Kenya is committed to implementing and updating its National Climate Change Action Plans (NCCAPs) to present and achieve the greenhouse gas (GHG) emission reduction targets and resilience outcomes that it has identified.

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

Challenging the climate change effects on agriculture: need business unusual

ML JAT (2021, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE FOOD SYSTEMS CONSERVATION AGRICULTURE SUSTAINABILITY INNOVATION

CCAFS Outcome Synthesis Report:

Mathieu Ouédraogo John Recha Maren Radeny Paresh Shirsath Peter Läderach Osana Bonilla-Findji (2021, [Documento de trabajo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE-SMART AGRICULTURE INVESTMENT FARMING SYSTEMS CLIMATE CHANGE

Nitrogen fertilizer application alters the root endophyte bacterial microbiome in maize plants, but not in the stem or rhizosphere soil

Alejandra Miranda Carrazco Yendi Navarro-Noya Bram Govaerts Nele Verhulst Luc Dendooven (2022, [Artículo])

Plant-associated microorganisms that affect plant development, their composition, and their functionality are determined by the host, soil conditions, and agricultural practices. How agricultural practices affect the rhizosphere microbiome has been well studied, but less is known about how they might affect plant endophytes. In this study, the metagenomic DNA from the rhizosphere and endophyte communities of root and stem of maize plants was extracted and sequenced with the “diversity arrays technology sequencing,” while the bacterial community and functionality (organized by subsystems from general to specific functions) were investigated in crops cultivated with or without tillage and with or without N fertilizer application. Tillage had a small significant effect on the bacterial community in the rhizosphere, but N fertilizer had a highly significant effect on the roots, but not on the rhizosphere or stem. The relative abundance of many bacterial species was significantly different in the roots and stem of fertilized maize plants, but not in the unfertilized ones. The abundance of N cycle genes was affected by N fertilization application, most accentuated in the roots. How these changes in bacterial composition and N genes composition might affect plant development or crop yields has still to be unraveled.

Bacterial Community Structure DArT-Seq Bacterial Community Functionality Genes Involved in N Cycling CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL PRACTICES MAIZE RHIZOSPHERE STEMS NITROGEN FERTILIZERS

Genome-wide association study presents insights into the genetic architecture of drought tolerance in maize seedlings under field water-deficit conditions

Ao Zhang (2023, [Artículo])

Erratic Rainfall Adverse Impacts Traditional Breeding Genome-Wide Association Study Field Drought CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DROUGHT TOLERANCE MAIZE SEEDLING STAGE SINGLE NUCLEOTIDE POLYMORPHISM

Genome-wide association study and genomic prediction on plant architecture traits in sweet corn and waxy corn

XUECAI ZHANG Ao Zhang (2023, [Artículo])

Genome-Wide Association Study Genomic Prediction Ear Height Tassel Branch Number Waxy Corn CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOMICS PLANT HEIGHT SWEET CORN WAXY MAIZE

Identification and validation of a key genomic region on chromosome 6 for resistance to Fusarium stalk rot in tropical maize

Zerka Rashid Shilpee Sharma Sudha Nair (2022, [Artículo])

Genome-Wide Association Study Fusarium Stalk Rot CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FUSARIUM MAIZE DISEASE RESISTANCE QUANTITATIVE TRAIT LOCI MAPPING

Automated in-season rice crop mapping using Sentinel time-series data and Google Earth Engine: A case study in climate-risk prone Bangladesh

Mustafa Kamal Timothy Joseph Krupnik (2024, [Artículo])

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

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