Introduction to line and hybrid development

Yoseph Beyene (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA INBRED LINES HYBRIDS MAIZE GERMPLASM

TELA Project: An update

Yoseph Beyene (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE HYBRIDS PEST INSECTS RESEARCH

High spatial resolution seasonal crop yield forecasting for heterogeneous maize environments in Oromia, Ethiopia

Kindie Tesfaye Vakhtang Shelia Pierre C. Sibiry Traore Dawit Solomon Gerrit Hoogenboom (2023, [Artículo])

Seasonal climate variability determines crop productivity in Ethiopia, where rainfed smallholder farming systems dominate in the agriculture production. Under such conditions, a functional and granular spatial yield forecasting system could provide risk management options for farmers and agricultural and policy experts, leading to greater economic and social benefits under highly variable environmental conditions. Yet, there are currently only a few forecasting systems to support early decision making for smallholder agriculture in developing countries such as Ethiopia. To address this challenge, a study was conducted to evaluate a seasonal crop yield forecast methodology implemented in the CCAFS Regional Agricultural Forecasting Toolbox (CRAFT). CRAFT is a software platform that can run pre-installed crop models and use the Climate Predictability Tool (CPT) to produce probabilistic crop yield forecasts with various lead times. Here we present data inputs, model calibration, evaluation, and yield forecast results, as well as limitations and assumptions made during forecasting maize yield. Simulations were conducted on a 0.083° or ∼ 10 km resolution grid using spatially variable soil, weather, maize hybrids, and crop management data as inputs for the Cropping System Model (CSM) of the Decision Support System for Agrotechnology Transfer (DSSAT). CRAFT combines gridded crop simulations and a multivariate statistical model to integrate the seasonal climate forecast for the crop yield forecasting. A statistical model was trained using 29 years (1991–2019) data on the Nino-3.4 Sea surface temperature anomalies (SSTA) as gridded predictors field and simulated maize yields as the predictand. After model calibration the regional aggregated hindcast simulation from 2015 to 2019 performed well (RMSE = 164 kg/ha). The yield forecasts in both the absolute and relative to the normal yield values were conducted for the 2020 season using different predictor fields and lead times from a grid cell to the national level. Yield forecast uncertainties were presented in terms of cumulative probability distributions. With reliable data and rigorous calibration, the study successfully demonstrated CRAFT's ability and applicability in forecasting maize yield for smallholder farming systems. Future studies should re-evaluate and address the importance of the size of agricultural areas while comparing aggregated simulated yields with yield data collected from a fraction of the target area.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP MODELLING DECISION SUPPORT SYSTEMS FORECASTING MAIZE

Combination of linkage and association mapping with genomic prediction to infer QTL regions associated with gray leaf spot and northern corn leaf blight resistance in tropical maize

David Berger Yoseph Beyene Collins Juma Suresh L.M. Manje Gowda (2023, [Artículo])

Gray Leaf Spot Northern Corn Leaf Blight CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE LEAF SPOTS QUANTITATIVE TRAIT LOCI ASSOCIATION MAPPING GENOME-WIDE ASSOCIATION STUDIES

Spatiotemporal analysis of rainfall and temperature variability and trends for climate resilient maize farming system in major agroecology zones of northwest Ethiopia

Kindie Tesfaye Dereje Ademe Enyew Adgo (2023, [Artículo])

Spatiotemporal studies of the annual and seasonal climate variability and trend on an agroecological spatial scale for establishing a climate-resilient maize farming system have not yet been conducted in Ethiopia. The study was carried out in three major agroecological zones in northwest Ethiopia using climate data from 1987 to 2018. The coefficient of variation (CV), precipitation concertation index (PCI), and rainfall anomaly index (RAI) were used to analyze the variability of rainfall. The Mann-Kendall test and Sen’s slope estimator were also applied to estimate trends and slopes of changes in rainfall and temperature. High-significance warming trends in the maximum and minimum temperatures were shown in the highland and lowland agroecology zones, respectively. Rainfall has also demonstrated a maximum declining trend throughout the keremt season in the highland agroecology zone. However, rainfall distribution has become more unpredictable in the Bega and Belg seasons. Climate-resilient maize agronomic activities have been determined by analyzing the onset and cessation dates and the length of the growth period (LGP). The rainy season begins between May 8 and June 3 and finishes between October 26 and November 16. The length of the growth period (LGP) during the rainy season ranges from 94 to 229 days.

Climate Trends Spatiotemporal Analysis Agroecology Zone CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGROECOLOGY CLIMATE CLIMATE VARIABILITY MAIZE

Use of remote sensing for linkage mapping and genomic prediction for common rust resistance in maize

Alexander Loladze Francelino Rodrigues Cesar Petroli Felix San Vicente Garcia Bruno Gerard Osval Antonio Montesinos-Lopez Jose Crossa Johannes Martini (2024, [Artículo])

Common Rust Rp1 Locus CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUSTS REMOTE SENSING VEGETATION INDEX MAIZE CHROMOSOME MAPPING

Targeted nitrogen management to increase cereal production while reducing nitrogen consumption in India

Tek Sapkota Sieglinde Snapp (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CEREAL PRODUCTS PRODUCTION SYSTEMS CEREALS NITROGEN RICE WHEAT MAIZE

Simulación del rendimiento de maíz (Zea mays L.) en el norte de Sinaloa usando el modelo Aquacrop

Simulation of corn (Zea mays L.) yield in northern Sinaloa using the Aquacrop model

HILARIO FLORES GALLARDO WALDO OJEDA BUSTAMANTE Hector Flores Magdaleno ENRIQUE MEJIA SAENZ (2013, [Artículo])

La intensificación de la variabilidad climática ha generado incertidumbre en los volúmenes de agua disponible en varias zonas de riego de México, ocasionan inestabilidad en la productividad del cultivo de maíz (Zea mays L.). Los modelos calibrados de simulación biológica son una herramienta computacional viable para estudiar el comportamiento de los cultivos en condiciones climáticas y escenarios de manejo agronómico e hídrico diferentes. En la presente investigación se calibró y validó el modelo AquaCrop para simular el desarrollo del cultivo de maíz en el norte de Sinaloa, México, con tres condiciones de disponibilidad hídrica: riego total (RT) y riego deficitario (80 % y 60 % respecto a RT).

Cultivos alimenticios Maíz Simulación INGENIERÍA Y TECNOLOGÍA

Can I speak to the manager? The gender dynamics of decision-making in Kenyan maize plots

Rachel Voss Zachary Gitonga Jason Donovan Mariana Garcia-Medina Pauline Muindi (2023, [Artículo])

Gender and social inclusion efforts in agricultural development are focused on making uptake of agricultural technologies more equitable. Yet research looking at how gender relations influence technology uptake often assumes that men and women within a household make farm management decisions as individuals. Relatively little is understood about the dynamics of agricultural decision-making within dual-adult households where individuals’ management choices are likely influenced by others in the household. This study used vignettes to examine decision-making related to maize plot management in 698 dual-adult households in rural Kenya. The results indicated a high degree of joint management of maize plots (55%), although some management decisions—notably those related to purchased inputs—were slightly more likely to be controlled by men, while other decisions—including those related to hiring of labor and maize end uses—were more likely to be made by women. The prevalence of joint decision-making underscores the importance of ensuring that both men’s and women’s priorities and needs are reflected in design and marketing of interventions to support maize production, including those related to seed systems, farmer capacity building, and input delivery.

Intrahousehold Jointness CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENDER HOUSEHOLDS MAIZE SEED SYSTEMS DECISION MAKING

Innovative approaches to integrating gender into conventional maize breeding: lessons from the Seed Production Technology for Africa project

Rachel Voss Jill Cairns Michael Olsen Esnath Tatenda Hamadziripi (2023, [Artículo])

The integration of gender concerns in crop breeding programs aims to improve the suitability and appeal of new varieties to both women and men, in response to concerns about unequal adoption of improved seed. However, few conventional breeding programs have sought to center social inclusion concerns. This community case study documents efforts to integrate gender into the maize-focused Seed Production Technology for Africa (SPTA) project using innovation history analysis drawing on project documents and the authors’ experiences. These efforts included deliberate exploration of potential gendered impacts of project technologies and innovations in the project’s approach to variety evaluation, culminating in the use of decentralized on-farm trials using the tricot approach. Through this case study, we illustrate the power of active and respectful collaborations between breeders and social scientists, spurred by donor mandates to address gender and social inclusion. Gender integration in this case was further facilitated by open-minded project leaders and allocation of funding for gender research. SPTA proved to be fertile ground for experimentation and interdisciplinary collaboration around gender and maize breeding, and has provided proof of concept for larger breeding projects seeking to integrate gender considerations.

Crop Breeding On-Farm Trials Tricot CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENDER CROPS BREEDING ON-FARM RESEARCH SOCIAL INCLUSION CITIZEN SCIENCE MAIZE