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Blast and rust forecast

An early warning system set to deliver wheat disease predictions directly to farmers’ phones is being piloted in Bangladesh and Nepal by interdisciplinary researchers.

Experts in crop disease, meteorology and computer science are crunching data from multiple countries to formulate models that anticipate the spread of the wheat rust and blast diseases in order to warn farmers of likely outbreaks, providing time for pre-emptive measures, said Dave Hodson, a principal scientist with the International Maize and Wheat Improvement Center (CIMMYT) coordinating the pilot project.

Around 50,000 smallholder farmers are expected to receive improved disease warnings and appropriate management advisories through the one-year proof-of-concept project, as part of the UK Aid-funded Asia Regional Resilience to a Changing Climate (ARRCC) program.

Early action is critical to prevent crop diseases becoming endemic. The speed at which wind-dispersed fungal wheat diseases are spreading through Asia poses a constant threat to sustainable wheat production of the 130 million tons produced in the region each year.

“Wheat rust and blast are caused by fungal pathogens, and like many fungi, they spread from plant to plant — and field to field — in tiny particles called spores,” said Hodson. “Disease strain mutations can overcome resistant varieties, leaving farmers few choices but to rely on expensive and environmentally-damaging fungicides to prevent crop loss.”

“The early warning system combines climate data and epidemiology models to predict how spores will spread through the air and identifies environmental conditions where healthy crops are at risk of infection. This allows for more targeted and optimal use of fungicides.”

The system was first developed in Ethiopia. It uses weather information from the Met Office, the UK’s national meteorological service, along with field and mobile phone surveillance data and disease spread modeling from the University of Cambridge, to construct and deploy a near real-time early warning system.

CIMMYT consultant Madan Bhatta conducts field surveys using Open Data Kit (ODK) in the mid-hills of Nepal. (Photo: D. Hodson/CIMMYT)
CIMMYT consultant Madan Bhatta conducts field surveys using Open Data Kit (ODK) in the mid-hills of Nepal. (Photo: D. Hodson/CIMMYT)

Initial efforts focused on adapting the wheat stripe and stem rust model from Ethiopia to Bangladesh and Nepal have been successful, with field surveillance data appearing to align with the weather-driven disease early warnings, but further analysis is ongoing, said Hodson.

“In the current wheat season we are in the process of comparing our disease forecasting models with on-the-ground survey results in both countries,” the wheat expert said.

“Next season, after getting validation from national partners, we will pilot getting our predictions to farmers through text-based messaging systems.”

CIMMYT’s strong partnerships with governmental extension systems and farmer associations across South Asia are being utilized to develop efficient pathways to get disease predictions to farmers, said Tim Krupnik, a CIMMYT Senior Scientist based in Bangladesh.

“Partnerships are essential. Working with our colleagues, we can validate and test the deployment of model-derived advisories in real-world extension settings,” Krupnik said. “The forecasting and early warning systems are designed to reduce unnecessary fungicide use, advising it only in the case where outbreaks are expected.”

Local partners are also key for data collection to support and develop future epidemiological modelling, the development of advisory graphics and the dissemination of information, he explained.

The second stage of the project concerns the adaptation of the framework and protocols for wheat blast disease to improve existing wheat blast early warning systems already pioneered in Bangladesh.

Example of weekly stripe rust spore deposition forecast in Nepal. Darker colors represent higher predicted number of spores deposited. The early warning system combines weather information from the Met Office with field and mobile phone surveillance data and disease spread modeling from the University of Cambridge. (Graphic: University of Cambridge and Met Office)
Example of weekly stripe rust spore deposition forecast in Nepal. Darker colors represent higher predicted number of spores deposited. The early warning system combines weather information from the Met Office with field and mobile phone surveillance data and disease spread modeling from the University of Cambridge. (Graphic: University of Cambridge and Met Office)

Strong scientific partnership champions diversity to achieve common goals

The meteorological-driven wheat disease warning system is an example of effective international scientific partnership contributing to the UN Sustainable Development Goals, said Sarah Millington, a scientific manager at Atmospheric Dispersion and Air Quality Group with the Met Office.

“Diverse expertise from the Met Office, the University of Cambridge and CIMMYT shows how combined fundamental research in epidemiology and meteorology modelling with field-based disease observation can produce a system that boosts smallholder farmers’ resilience to major agricultural challenges,” she said.

The atmospheric dispersion modeling was originally developed in response to the Chernobyl disaster and since then has evolved to be able to model the dispersion and deposition of a range of particles and gases, including biological particles such as wheat rust spores.

“The framework together with the underpinning technologies are transferable to forecast fungal disease in other regions and can be readily adapted for other wind-dispersed pests and disease of major agricultural crops,” said Christopher Gilligan, head of the Epidemiology and Modelling Group at the University of Cambridge.

Fungal wheat diseases are an increasing threat to farmer livelihoods in Asia

Wheat leaf rust can be spotted on a wheat plant of a highly susceptible variety in Nepal. The symptoms of wheat rust are dusty, reddish-orange to reddish-brown fruiting bodies that appear on the leaf surface. These lesions produce numerous spores, which are spread by wind and splashing water. (Photo: D Hodson/CIMMYT)
Wheat leaf rust can be spotted on a wheat plant of a highly susceptible variety in Nepal. The symptoms of wheat rust are dusty, reddish-orange to reddish-brown fruiting bodies that appear on the leaf surface. These lesions produce numerous spores, which are spread by wind and splashing water. (Photo: D Hodson/CIMMYT)

While there has been a history of wheat rust disease epidemics in South Asia, new emerging strains and changes to climate pose an increased threat to farmers’ livelihoods. The pathogens that cause rust diseases are continually evolving and changing over time, making them difficult to control.

Stripe rust threatens farmers in Afghanistan, India, Nepal and Pakistan, typically in two out of five seasons, with an estimated 43 million hectares of wheat vulnerable. When weather conditions are conducive and susceptible cultivars are grown, farmers can experience losses exceeding 70%.

Populations of stem rust are building at alarming rates and previously unseen scales in neighboring regions. Stem rust spores can spread across regions on the wind; this also amplifies the threat of incursion into South Asia and the ARRCC program’s target countries, underscoring the very real risk that the disease could reemerge within the subcontinent.

The devastating wheat blast disease, originating in the Americas, suddenly appeared in Bangladesh in 2016, causing wheat crop losses as high as 30% on a large area, and continues to threaten South Asia’s vast wheat lands.

In both cases, quick international responses through CIMMYT, the CGIAR research program on Wheat (WHEAT) and the Borlaug Global Rust Initiative have been able to monitor and characterize the diseases and, especially, to develop and deploy resistant wheat varieties.

The UK aid-funded ARRCC program is led by the Met Office and the World Bank and aims to strengthen weather forecasting systems across Asia. The program is delivering new technologies and innovative approaches to help vulnerable communities use weather warnings and forecasts to better prepare for climate-related shocks.

The early warning system uses data gathered from the online Rust Tracker tool, with additional fieldwork support from the Cereal Systems Initiative for South Asia (CSISA), funded by USAID and the Bill & Melinda Gates Foundation, both coordinated by CIMMYT.

New publications: Breeders can benefit much more from phenotyping tools

In crop research fields, it is now a common sight to see drones or other high-tech sensing tools collecting high-resolution data on a wide range of traits — from simple measurement of canopy temperature to complex 3D reconstruction of photosynthetic canopies.

This technological approach to collecting precise plant trait information, known as phenotyping, is becoming ubiquitous, but according to experts at the International Maize and Wheat Improvement Center (CIMMYT) and other research institutions, breeders can profit much more from these tools, when used judiciously.

In a new article in the journal Plant Science, CIMMYT researchers outline the different ways in which phenotyping can assist breeding — from large-scale screening to detailed physiological characterization of key traits — and why this methodology is crucial for crop improvement.

“While having been the subject of debate in the past, extra investment for phenotyping is becoming more accepted to capitalize on recent developments in crop genomics and prediction models,” explain the authors.

Their review considers different contexts for phenotyping, including breeding, exploration of genetic resources, parent building and translations research to deliver other new breeding resources, and how these different categories of phenotyping apply to each. Some of the same tools and rules of thumb apply equally well to phenotyping for genetic analysis of complex traits and gene discovery.

The authors make the case for breeders to invest in phenotyping, particularly in light of the imperative to breed crops for warmer and harsher climates. However, wide scale adoption of sophisticated phenotyping methods will only occur if new techniques add efficiency and effectiveness.

In this sense, “breeder-friendly” phenotyping should complement existing breeding approaches by cost-effectively increasing throughput during segregant selection and adding new sources of validated complex traits to crossing blocks. With this in mind, stringent criteria need to be applied before new traits or phenotyping protocols are incorporated into mainstream breeding pipelines.

Read the full article in Plant Science:
Breeder friendly phenotyping.

A researcher flies a UAV to collect field data at CIMMYT’s experiment station in Ciudad Obregón, Mexico. (Photo: Alfonso Cortés/CIMMYT)
A researcher flies a UAV to collect field data at CIMMYT’s experiment station in Ciudad Obregón, Mexico. (Photo: Alfonso Cortés/CIMMYT)

See more recent publications from CIMMYT researchers:

  1. Genome-wide association study to identify genomic regions influencing spontaneous fertility in maize haploids. 2019. Chaikam, V., Gowda, M., Nair, S.K., Melchinger, A.E., Prasanna, B.M. In: Euphytica v. 215, no. 8, art. 138.
  2. Adapting irrigated and rainfed wheat to climate change in semi-arid environments: management, breeding options and land use change. 2019. Hernandez-Ochoa, I.M., Pequeno, D.N.L., Reynolds, M.P., Md Ali Babar, Sonder, K., Molero, A., Hoogenboom, G., Robertson, R., Gerber, S., Rowland, D.L., Fraisse, C.W., Asseng, S. In: European Journal of Agronomy.
  3. Integrating genomic resources to present full gene and putative promoter capture probe sets for bread wheat. 2019. Gardiner, L.J., Brabbs, T., Akhunova, A., Jordan, K., Budak, H., Richmond, T., Sukhwinder-Singh, Catchpole, L., Akhunov, E., Hall, A.J.W. In: GigaScience v. 8, no. 4, art. giz018.
  4. Rethinking technological change in smallholder agriculture. 2019. Glover, D., Sumberg, J., Ton, G., Andersson, J.A., Badstue, L.B. In: Outlook on Agriculture v. 48, no. 3, p. 169-180.
  5. Food security and agriculture in the Western Highlands of Guatemala. 2019. Lopez-Ridaura, S., Barba‐Escoto, L., Reyna, C., Hellin, J. J., Gerard, B., Wijk, M.T. van. In: Food Security v. 11, no. 4, p. 817-833.
  6. Agronomic, economic, and environmental performance of nitrogen rates and source in Bangladesh’s coastal rice agroecosystems. 2019. Shah-Al Emran, Krupnik, T.J., Kumar, V., Ali, M.Y., Pittelkow, C. M. In: Field Crops Research v. 241, art. 107567.
  7. Highlights of special issue on “Wheat Genetics and Breeding”. 2019. He Zhonghu, Zhendong Zhao, Cheng Shun-He In: Frontiers of Agricultural Science and Engineering v. 6, no. 3, p. 207-209.
  8. Progress in breeding for resistance to Ug99 and other races of the stem rust fungus in CIMMYT wheat germplasm. 2019. Bhavani, S., Hodson, D.P., Huerta-Espino, J., Randhawa, M.S., Singh, R.P. In: Frontiers of Agricultural Science and Engineering v. 6, no. 3, p. 210-224.
  9. China-CIMMYT collaboration enhances wheat improvement in China. 2019. He Zhonghu, Xianchun Xia, Yong Zhang, Zhang Yan, Yonggui Xiao, Xinmin Chen, Li Simin, Yuanfeng Hao, Rasheed, A, Zhiyong Xin, Zhuang Qiaosheng, Ennian Yang, Zheru Fan, Yan Jun, Singh, R.P., Braun, H.J. In: Frontiers of Agricultural Science and Engineering v. 6. No. 3, p. 233-239.
  10. International Winter Wheat Improvement Program: history, activities, impact and future. 2019. Morgounov, A.I., Ozdemir, F., Keser, M., Akin, B., Payne, T.S., Braun, H.J. In: Frontiers of Agricultural Science and Engineering v. 6, no. 3, p. 240-250.
  11. Genetic improvement of wheat grain quality at CIMMYT. 2019. Guzman, C., Ammar, K., Velu, G., Singh, R.P. In: Frontiers of Agricultural Science and Engineering v. 6, no. 3, p. 265-272.
  12. Comments on special issue on “Wheat Genetics and Breeding”. 2019. He Zhonghu, Liu Xu In: Frontiers of Agricultural Science and Engineering, v. 6. No. 3, p. 309.
  13. Spectral reflectance indices as proxies for yield potential and heat stress tolerance in spring wheat: heritability estimates and marker-trait associations. 2019. Caiyun Liu, Pinto Espinosa, F., Cossani, C.M., Sukumaran, S., Reynolds, M.P. In: Frontiers of Agricultural Science and Engineering, v. 6, no. 3, p. 296-308.
  14. Beetle and maize yield response to plant residue application and manual weeding under two tillage systems in northern Zimbabwe. 2019. Mashavakure, N., Mashingaidze, A.B., Musundire, R., Gandiwa, E., Thierfelder, C., Muposhi, V.K. In: Applied Soil Ecology v. 144, p. 139-146.
  15. Optimizing dry-matter partitioning for increased spike growth, grain number and harvest index in spring wheat. 2019. Rivera Amado, A.C., Trujillo, E., Molero, G., Reynolds, M.P., Sylvester Bradley, R., Foulkes, M.J. In: Field Crops Research v. 240, p. 154-167.
  16. Small businesses, potentially large impacts: the role of fertilizer traders as agricultural extension agents in Bangladesh. 2019. Mottaleb, K.A., Rahut, D.B., Erenstein, O. In: Journal of Agribusiness in Developing and Emerging Economies v. 9, no. 2, p. 109-124.
  17. Heterogeneous seed access and information exposure: implications for the adoption of drought-tolerant maize varieties in Uganda. 2019. Simtowe, F.P., Marenya, P. P., Amondo, E., Regasa, M.W., Rahut, D.B., Erenstein, O. In: Agricultural and Food Economics v. 7. No. 1, art. 15.
  18. Hyperspectral reflectance-derived relationship matrices for genomic prediction of grain yield in wheat. 2019. Krause, M., Gonzalez-Perez, L., Crossa, J., Perez-Rodriguez, P., Montesinos-Lopez, O.A., Singh, R.P., Dreisigacker, S., Poland, J.A., Rutkoski, J., Sorrells, M.E., Gore, M.A., Mondal, S. In: G3: Genes, Genomes, Genetics v.9, no. 4, p. 1231-1247.
  19. Unravelling the complex genetics of karnal bunt (Tilletia indica) resistance in common wheat (Triticum aestivum) by genetic linkage and genome-wide association analyses. 2019. Emebiri, L.C., Sukhwinder-Singh, Tan, M.K., Singh, P.K., Fuentes Dávila, G., Ogbonnaya, F.C. In: G3: Genes, Genomes, Genetics v. 9, no. 5, p. 1437-1447.
  20. Healthy foods as proxy for functional foods: consumers’ awareness, perception, and demand for natural functional foods in Pakistan. 2019. Ali, A., Rahut, D.B. In: International Journal of Food Science v. 2019, art. 6390650.
  21. Northern Himalayan region of Pakistan with cold and wet climate favors a high prevalence of wheat powdery mildew. 2019. Khan, M.R., Imtiaz, M., Farhatullah, Ahmad, S., Sajid Ali.In: Sarhad Journal of Agriculture v. 35, no. 1, p. 187-193.
  22. Resistance to insect pests in wheat—rye and Aegilops speltoides Tausch translocation and substitution lines. 2019. Crespo-Herrera, L.A., Singh, R.P., Sabraoui, A., Moustapha El Bouhssini In: Euphytica v. 215, no. 7, art.123.
  23. Productivity and production risk effects of adopting drought-tolerant maize varieties in Zambia. 2019. Amondo, E., Simtowe, F.P., Rahut, D.B., Erenstein, O. In: International Journal of Climate Change Strategies and Management v. 11, no. 4, p. 570-591.
  24. Review: new sensors and data-driven approaches—A path to next generation phenomics. 2019. Roitsch, T., Cabrera-Bosquet, L., Fournier, A., Ghamkhar, K., Jiménez-Berni, J., Pinto Espinosa, F., Ober, E.S. In: Plant Science v. 282 p. 2-10.
  25. Accountability mechanisms in international climate change financing. 2019. Basak, R., van der Werf, E. In: International Environmental Agreements: Politics, Law and Economics v. 19, no. 3, p. 297-313.
  26. Enhancing the rate of genetic gain in public-sector plant breeding programs: lessons from the breeder’s equation. 2019. Cobb, J.N., Juma, R.U., Biswas, P.S., Arbelaez, J.D., Rutkoski, J., Atlin, G.N., Hagen, T., Quinn, M., Eng Hwa Ng. In: Theoretical and Applied Genetics v. 132, no. 3, p. 627-645.

Crowdsourced data feeds fall armyworm surveillance in Bangladesh

Following the spread of fall armyworm, crowdsourced data is powering a web-based application to help farmers in Bangladesh stay ahead of the crop pest.

The Fall Armyworm Monitor collects population, incidence and severity data, and guides pest management decisions. The web tool relies on information gathered by farmers using smartphones in their fields.

It was developed by the International Maize and Wheat Improvement Center (CIMMYT) in cooperation with Bangladesh’s Department of Agricultural Extension, through the Fighting Back Against Fall Armyworm project, supported by USAID and Michigan State University.

When a foreign caterpillar first munched through Muhammad Hasan Ali’s maize field during the winter 2018-2019 season, he was stumped as to what it was or how to manage it. All he knew was his harvest and the investment he made in growing his crop was at risk.

“I’d never seen this type of insect in previous seasons, but I soon learned from government extension workers it was the fall armyworm,” explained Hasan Ali, a farmer from rural Chuadanga, in western Bangladesh. When poorly managed, fall armyworm can significantly reduce maize productivity.

Hasan Ali asked to join a training program, where he learned how to identify, monitor and control the spread of the invasive and voracious crop pest. The training, mainly tailored to extension staff, was facilitated by CIMMYT and Bangladesh’s Department of Agricultural Extension.

Participants of the Fighting Back Against Fall Armyworm trainings learning to collect field data through the Fall Armyworm Monitor web app in a farmer's field in Chauadanga, Bangladesh. (Photo: Uttam Kumar/CIMMYT)
Participants of the Fighting Back Against Fall Armyworm trainings learning to collect field data through the Fall Armyworm Monitor web app in a farmer’s field in Chauadanga, Bangladesh. (Photo: Uttam Kumar/CIMMYT)
Participants of the Fighting Back Against Fall Armyworm trainings learning to collect field data through the Fall Armyworm Monitor web app in a farmer's field in Chauadanga, Bangladesh. (Photo: Uttam Kumar/CIMMYT)
Participants of the Fighting Back Against Fall Armyworm trainings learning to collect field data through the Fall Armyworm Monitor web app in a farmer’s field in Chauadanga, Bangladesh. (Photo: Uttam Kumar/CIMMYT)
Participants and instructors of the Fighting Back Against Fall Armyworm trainings participate in a field session to work with the Fall Armyworm Monitor web app in Chauadanga, Bangladesh. (Photo: Uttam Kumar/CIMMYT)
Participants and instructors of the Fighting Back Against Fall Armyworm trainings participate in a field session to work with the Fall Armyworm Monitor web app in Chauadanga, Bangladesh. (Photo: Uttam Kumar/CIMMYT)

Equipped to fight the pest

Extension staff and farmers gained valuable insights into different methods of control, including management of small and large patches of insect attack.

“I learned to identify fall armyworms in my field — and how to use hand picking methods and appropriate application of insecticide for control,” said Hasan Ali.

Farmers also learned how to set up pheromone traps to monitor pest populations and to use smartphones to make data-driven integrated pest management decisions using a cloud-based monitoring platform.

Crowdsourced information on the movement of fall armyworm is essential for effectively monitoring its spread and is a pivotal step in its management, said CIMMYT Senior Scientist and Systems Agronomist Timothy Krupnik.

“Farmers in top maize growing regions are working with extension officers to monitor traps and report findings weekly by entering data into smartphones,” Krupnik said.

Pheromones are natural compounds emitted by female moths to attract males for mating. Synthetic compounds that mimic natural fall armyworm pheromones are placed in traps to lure and capture male moths, after which extension agents count moths, enter, and upload data in their districts. At the time of writing, 649 staff from the Department of Agricultural Extension are reporting weekly moth count and pest damage data.

“Pest management practices are best when they are data-driven,” Krupnik explained. “Having information on the geographical location, plant growth stage and severity of infestation provides an informed base from which appropriate decisions can be made, with the ultimate goal of reducing pesticide misuse.”

“We are also excited as the data are open-access, and we are working to share them with FAO and other partners crucial in fall armyworm response,” he added.

The Fall Armyworm Monitor gives moth count and other data at the division, district and upazilla levels. (Photo: CIMMYT)
The Fall Armyworm Monitor gives moth count and other data at the division, district and upazilla levels. (Photo: CIMMYT)

Data for better decisions

“The website hosts real-time data and depicts them graphically and in maps depending on user’s preferences. This information — which was core to the training extension agents participated in — is key for integrated pest management strategies,” explained Mutasim Billah, CIMMYT Data Specialist and the lead developer of the application.

“The department of extension services have employed 253 officers to visit fields with handheld smart devices in 25 districts to upload data,” said Billah. “The online tool stores data entries in its server and calculates the aggregated value for division, district and sub-district level on a weekly basis, and shows the estimated values through charts and in tabular format.”

The Fall Armyworm Monitor has become an essential tool for government officials to aid farmers in managing the pest which so far has been successful, said Bijoy Krishna Halder, additional Deputy Director of Plant Protection with the Bangladesh government.

“CIMMYT’s web portal is a very efficient way to collect data from the field. Anyone can access the page to see the overall condition of infestation across the country,”said Krishna Halder. “I check the portal every week about the fall armyworm condition and now it shows that the infestation is low with the overall field conditions good.”

The pest native to the Americas has become a global menace as it has spread attacking crops through Africa, and Asia, threatening the food and economic security of smallholder farmers.

Visit the Bangladesh Fall Armyworm Monitor.

The Fall Armyworm Monitor was created as part of the new Fighting Back Against Fall Armyworm in Bangladesh project is aligned with Michigan State University’s Borlaug Higher Education for Agricultural Research and Development (BHEARD) program, which supports the long-term training of agricultural researchers in USAID’s Feed the Future priority countries.

Breeder friendly phenotyping

In crop research fields, drones and other high-tech sensing tools are now a common sight. They collect high-resolution data on a wide range of traits — from simple measurement of canopy temperature to complex 3D reconstruction of photosynthetic canopies.

This technological approach to collecting precise plant trait information, known as phenotyping, is becoming ubiquitous. According to experts at the International Maize and Wheat Improvement Center (CIMMYT) and other research institutions, breeders can profit much more from these tools, when used judiciously.

Examples of different classes and applications of breeder friendly phenotyping. (Image: M. Reynolds et al.)
Examples of different classes and applications of breeder friendly phenotyping. (Image: M. Reynolds et al.)

In a new article in the journal Plant Science, CIMMYT Wheat Physiologist Matthew Reynolds and colleagues explain the different ways that phenotyping can assist breeding — from simple to use, “handy” approaches for large scale screening, to detailed physiological characterization of key traits to identify new parental sources — and why this methodology is crucial for crop improvement. The authors make the case for breeders to invest in phenotyping, particularly in light of the imperative to breed crops for warmer and harsher climates.

Read the full article: 
Breeder friendly phenotyping.

This article was originally published on WHEAT.

Cover photo: Remote sensing specialist Francisco Pinto operates a UAV at CIMMYT’s research station in Ciudad Obregón, in Mexico’s Sonora state.

Development of the Enterprise Breeding System well underway

Members of the Enterprise Breeding System advisory committee listen to a presentation from Tom Hagen. (Photo: Alfonso Cortés/CIMMYT)
Members of the Enterprise Breeding System advisory committee listen to a presentation from Tom Hagen. (Photo: Alfonso Cortés/CIMMYT)

Members of the Enterprise Breeding System (EBS) advisory committee met on January 17-18, 2019, to review progress on the development of a full-spectrum breeding data management software.

CGIAR plant breeders currently rely on a suite of different software projects to make use of the data that is crucial to developing better varieties. Developed under the CGIAR Excellence in Breeding Platform (EiB), the EBS aims to provide a single solution that links data across new and existing applications so that the entire breeding data workflow — from experiment creation to analytics — can be accessed from a single user-friendly dashboard.

Development of the system is well underway, with the goal of providing a “minimum viable implementation” to pilot users at the International Maize and Wheat Improvement Center (CIMMYT) and the International Rice Research Institute (IRRI) in 2020. More advanced functions, institutions and crops will be added to the EBS over the next three years.

Working between breeders and developers to ensure needs are translated into software functions, the EBS team has trained CIMMYT staff and consultants as requirements analysts, five of whom presented to members of the EBS advisory committee the meeting on progress in the five “domains” of breeding software functions.

Sharing bits and bytes

Rosemary Shresthra introduced experiment creation, where users can quickly select the type of experiment they wish to run and automatically set up all the steps needed to complete it in the EBS.

Kate Dreher took the attendees through field implementation, where it is possible to map fields in the system and connect them to a range of plot data collection tools developed by external projects.

Ricardo León outlined the germplasm management component of the system, where the seed inventory is kept, and new entries made after trials are harvested to go on to the next stage.

Pedro Medeiros explained how an analytics request manager will allow EBS users to push their data to different analytics tools that support decision-making and, ultimately, their ability to deliver better varieties that meet farmers’ needs.

Finally, Star Gao, a breeding informatics specialist for the Genomic and Open-Source Breeding Informatics Initiative (GOBii), showed how users will be able to request phytosanitary, genotypic and quality analysis of samples from their trials through the EBS system. The system will provide an overview of the status of all samples submitted for analysis with different service providers, in addition to the ability to connect with various databases.

“We can do all this because all information in the EBS is treated the same way, from experiment creation through implementation,” said EBS coordinator Tom Hagen in summary.

The EBS advisory group, which includes user representatives from CIMMYT and IRRI breeding teams alongside EiB staff, ended the day by discussing and prioritizing new functions that could be added to the EBS over the next three years.

New mobile technology to help farmers improve yields and stabilize incomes

An international team of scientists is working with farmers in the Yaqui Valley, in Mexico’s Sonora state, to develop and test a new mobile technology that aims to improve wheat and sugarcane productivity by helping farmers manage factors that cause the yield gap between crop potential and actual field performance.

Scientists have been developing and testing a smartphone app where farmers can record their farming activities — including sowing date, crop type and irrigation — and receive local, precise crop management advice in return.

This project is a private-public partnership known as Mexican COMPASS, or Mexican Crop Observation, Management & Production Analysis Services System.

Research has shown that proper timing of irrigation is more important to yields than total water amounts. Earlier planting times have also been shown to improve wheat yields. Having optimum dates for both activities could help farmers improve yields and stabilize their incomes.

COMPASS smartphone app interface. (Photo: Saravana Gurusamy/Rezatec)
COMPASS smartphone app interface. (Photo: Saravana Gurusamy/Rezatec)

The COMPASS smartphone app uses earth observation satellite data and in-situ field data captured by farmers to provide information such as optimum sowing date and irrigation scheduling.

“Sowing and irrigation timing are well known drivers of yield potential in that region — these are two features of the app we’re about to validate during this next season,” explained Francelino Rodrigues, Precision Agriculture Scientist at the International Maize and Wheat Improvement Center (CIMMYT).

Sound data

Technological innovation for crop productivity is needed now more than ever with threats to food security increasing and natural resources becoming scarcer. Farmers are under increasing pressure to produce more with less, which means greater precision is needed in their agricultural practices.

The Yaqui Valley, Mexico’s biggest wheat producing area, is located in the semi-arid Sonoran Desert in the northern part of Mexico. Water security is a serious challenge and farmers must be very precise in their irrigation management.

The Mexican COMPASS consortium, which is made up of the geospatial data analytics company Rezatec, the University of Nottingham, Booker Tate, CIMMYT and the Colegio de Postgraduados (COLPOS) in Mexico, evolved as a way to help Mexican farmers improve their water use efficiency.

“Yaqui Valley farmers are very experienced farmers, however they can also benefit by using an app that is designed locally to inform and record their decisions,” Rodrigues explained.

The smartphone app will also allow farmers to record and schedule their crop management practices and will give them access to weekly time-series Normalized Difference Vegetation Index (NDVI) maps, that will allow farmers to view their fields at any time from any location.

“All of this information is provided for free! That’s the exciting part of the project. The business model was designed so that farmers will not need to pay for access to the app and its features, in exchange for providing their crop field data. It’s a win-win situation,” said Rodrigues.

CIMMYT research assistant Lorena Gonzalez (center) helps local farmers try out the new COMPASS app during the workshop in Ciudad Obregon, Sonora state, Mexico. (Photo: Alison Doody/CIMMYT)
CIMMYT research assistant Lorena Gonzalez (center) helps local farmers try out the new COMPASS app during the workshop in Ciudad Obregon, Sonora state, Mexico. (Photo: Alison Doody/CIMMYT)

Farmer-centered design

The app is now in the validation stage and COMPASS partners are inviting farmers to test the technology on their own farms. A workshop on October 21 in Ciudad Obregon provided farmers with hands-on training for the app and allowed them to give their feedback.

Over 100 farmers attended the workshop, which featured presentations from Saravana Gurusamy, project manager at Rezatec, Iván Ortíz-Monasterio, principal scientist at CIMMYT, and representatives from local farmer groups Asociación de Organismos de Agricultores del Sur de Sonora (AOASS) and Distrito de Riego del Río Yaqui (DRRYAQUI). The workshop featured a step-by-step demonstration of the app and practical exercises for farmers to test it out for themselves.

“We need technology nowadays because we have to deal with many factors. The profit we get for wheat is getting smaller and smaller each year, so we have to be very productive. I hope that this app can help me to produce a better crop,” said one local wheat farmer who attended the workshop.

User feedback has played a key role in the development of the app. COMPASS interviewed dozens of farmers to see what design worked for them.

“Initially we came up with a really complicated design. However, when we gave it to farmers, they didn’t know how to use it,” explained Rezatec project manager, Saravana Gurusamy. The team went back to the drawing board and with the feedback they received from farmers, came up with a simple design that any farmer, regardless of their experience with technology or digital literacy, could use.

A farmer who attended the workshop talks about his experience and the potential benefits of the app. See full video on YouTube.

Sitting down with Gurusamy after the workshop, he outlined his vision for the future of the app.

“My vision is to see all the farmers in Sonora, working in wheat using the app. The first step is to prove the technology here, then roll it out to all of Mexico and eventually internationally.”

Mexican COMPASS is a four year project funded by the UK Space Agency’s International Partnership Programme (IPP-UKSA) and the CGIAR Research Program on Wheat (WHEAT). It is a collaboration between Rezatec, the University of Nottingham and Booker Tate in the UK, and the International Maize and Wheat Improvement Center (CIMMYT) and the Colegio de Postgraduados (COLPOS) in Mexico.

First steps taken to unify breeding software

Participants of the EBS DevOps Hackathon stand for a group photo at CIMMYT's global headquarters in Texcoco, Mexico. (Photo: Eleusis Llanderal Arango/CIMMYT)
Participants of the EBS DevOps Hackathon stand for a group photo at CIMMYT’s global headquarters in Texcoco, Mexico. (Photo: Eleusis Llanderal Arango/CIMMYT)

From October 21 to November 1, 2019, software developers and administrators from several breeding software projects met at the global headquarters of the International Maize and Wheat Improvement Center (CIMMYT) in Mexico to work on delivering an integrated solution to crop breeders.

Efforts to improve crop breeding for lower- and middle-income countries involves delivering better varieties to farmers faster and for less cost. These efforts rely on a mastery of data and technology throughout the breeding process.

To realize this potential, the CGIAR Excellence in Breeding Platform (EiB) is developing an Enterprise Breeding System (EBS) as a single solution for breeders. EBS will integrate the disparate software projects developed by different institutions over the years. This will free breeders from the onerous task of managing their data through different apps and allow them to rapidly optimize their breeding schemes based on sound data and advanced analytics.

“None of us can do everything,” said Tom Hagen, CIMMYT-EiB breeding software product manager, “so what breeding programs are experiencing is in fact fragmented IT. How do we come together as IT experts to create a system through our collective efforts?”

For the EBS to succeed, it is essential that the system is both low-cost and easy to deploy. “The cost of the operating environment is absolutely key,” said Jens Riis-Jacobson, international systems and IT director at CIMMYT. “We are trying to serve developing country institutions that have very little hard currency to pay for breeding program operations.”

Stacked software

During the hackathon, twelve experts from software projects across CGIAR and public sector institutions used a technology called Docker to automatically stack the latest versions of their applications into a single configuration file. This file can be loaded into any operating environment in less than four minutes — whether it be a laptop, local server or in the cloud. Quickly loading the complete system into a cloud environment means EBS can eventually be available as a one-click, Software-as-a-Service solution. This means that institutions will not need sophisticated IT infrastructure or support staff to maintain the software.

Behind the scenes, different applications are replicated in a single software solution, the Enterprise Breeding System. (Photo: CIMMYT)
Behind the scenes, different applications are replicated in a single software solution, the Enterprise Breeding System. (Photo: CIMMYT)

“If everything goes as planned, the end users won’t know that we exist,” said Peter Selby, coordinator of the Breeding API (BrAPI) project, an online collective working on a common language for breeding applications to communicate with each other. Updates to individual apps will be automatically loaded, tested and pushed out to users.

As well as the benefits to breeders, this automated deployment pipeline should also result in better software. “We have too little time for development because we spend too much time in deployment and testing,” said Riis-Jacobson.

A cross-institution DevOps culture

Though important technical obstacles were overcome, the cultural aspect was perhaps the most significant outcome of the hackathon. The participants found that they shared the same goals, language and were able to define the common operating environment for their apps to work together in.

“It’s really important to keep the collaboration open,” said Roy Petrie, DevOps engineer at the Genomic and Open-Source Breeding Informatics Initiative (GOBii) based at the Boyce Thompson Institute, Cornell University. “Having a communications platform was the first thing.”

In the future, this could mean that teams synchronize their development timeline to consistently release updates with new versions of the EBS, suggested Franjel Consolacion, systems admin at CIMMYT.

“They are the next generation,” remarked Hagen. “This is the first time that this has happened in CGIAR informatics and it validated a key aspect of our strategy: that we can work together to assemble parts of a system and then deploy it as needed to different institutions.”

By early 2020, selected CIMMYT and International Rice Research Institute (IRRI) breeding teams will have access to a “minimal viable implementation” of the EBS, in which they can conduct all basic breeding tasks through a simple user interface. More functionality, breeding programs and crops from other institutions including national agricultural research programs will be added in phases over three years.

New tools guide interventions against acid soils in Africa using lime

Researchers visit maize fields in Ethiopia's Wondo Genet Agricultural Research Center. (Photo: Peter Lowe/CIMMYT)
Researchers visit maize fields in Ethiopia’s Wondo Genet Agricultural Research Center. (Photo: Peter Lowe/CIMMYT)

One major reason why maize productivity in sub-Saharan Africa is very low is poor soil health. Soil acidity is often mentioned because of its impact on crop yields and the extent of acid soils in the region. A recent soil mapping exercise, conducted by the Ethiopian Soil Information System (EthioSIS) under the administration of the Ethiopian Agricultural Transformation Agency (ATA), estimated that 43% of arable lands were affected by acid soils and that 3.6 million people, about 10% of the total rural population, live in areas with acidic soils.

Very acid soils — those with a pH below 5.5, roughly one hundred times more acidic than neutral soils — are associated with certain toxicities, like aluminum and iron excess, and some nutrient deficiencies. Soil acidity pushes soil nutrients out of reach of the plant, leading to stunting of root system and plant. As a result, the plant becomes also less tolerant to drought.

Soil acidification depends on soil nature, agroecology and farming systems. It happens through natural leaching of CO2 after rainfall and excess application of nitrogenous fertilizer or organic matter, for instance.

As a result, soil acidity significantly affects maize yields. In Ethiopia, studies have revealed substantial impacts on crop productivity related to acid soils and the importance of acid soil management for Ethiopia’s food security. The Ethiopian Institute of Agricultural Research (EIAR) estimated that soil acidity on wheat production alone costed the country over 9 billion Ethiopian Birr, about $300 million per year.

Acidic soils in the limelight

Preliminary analysis led by the International Food Policy Research Institute (IFPRI) suggests that yields of major cereal crops, such as wheat and barley, could increase by 20 to 40% with the application of lime in acidic areas of the country.

While these preliminary results are significant, we need to know more about local farmers’ experience with acidic soil and their mitigation strategies. Such impact assessments are however typically determined at either the national or experimental plot level and do not map where mitigating against acid soils would be the most profitable.

To improve acid soils, farmers may apply lime on their fields to raise the pH, a practice known as liming. How much lime to apply will depend on the crop, soil type but also on the quality of lime available. Liming has multiple beneficial effects like improving nitrogen fixation of legume nodules, boosting yields of legume crops.

But liming has a cost. It can quickly become a very bulky affair as we need to apply 3 to 4 tons per hectare for sandy soils and up to 8 tons per hectare for clay and humifere soils.

Furthermore, existing lime markets are quite limited or even non-existent in many areas, even those where acidic soils are prevalent. Developing supply chains from scratch is difficult and costly. Understanding the costs and potential returns to such investments is important. There are many questions to ask at different levels, from the farm and farming system to the lime supply chain. What are the available lime sources — calcitic, dolomite or blend — and lime quality? Where are the lime processing units and how could you assess the transport cost to the farms? What could be the crop yield response depending on the lime application?

User-friendly and scalable dashboard

IFPRI, in collaboration with EIAR, the International Maize and Wheat Improvement Center (CIMMYT) and the German aid agency GIZ, developed a pilot in Ethiopia’s Amhara region to help better target lime interventions for a greater impact. Amhara region was chosen because of the importance of acid soils, and access to extensive soil data.

Combination of several spatial datasets on soil quality, agroecological, weather, long-term agronomic trials and crop modelling tools enabled to generate at scale, georeferenced estimates of crop yield responses for different lime applications. Calibration of this spatial model for wheat estimated a yield increase of approximately 30% increasing the pH from 5.5 to 6.5, which is relatively consistent with general research data and expert opinion.

Mapped estimates of the grain prices and the delivered costs of lime, based on the location of the lime crushers in the region and transport costs, enables then to map out the spatial profitability of lime operations.

Initial calculations revealed a great variability of lime costs at the farmgate, with transportation representing at least half of total lime costs. It showed also that farmers often do not use the most cost-effective combination of inputs to tackle soil acidity.

Another possible application is to determine maize growing areas where lime benefits outweigh the costs, which would be ideal sites for demonstrating to farmers the positive impact lime applications could have to their livelihoods.

This Amhara lime dashboard prototype demonstrated its scalability. A national dashboard is currently being developed, which includes lime sources GPS location, grain prices and district-level soil quality mapping. This approach is tested also in Tanzania.

CIMMYT and its partners plan to package such tool in a user-friendly open-access web version that can be rapidly updated and customized depending on the area of intervention, for instance integrating a new lime source, and applied for different crops, and across the Eastern African region. Such dashboards will help development organizations and government make better informed decisions regarding lime investments.

UN-sponsored report acknowledges CIMMYT’s use of data and technologies to promote sustainable farming in Latin America

Surveyors in Mexico collect data from farmers. (Photo: CIMMYT)
Surveyors in Mexico collect data from farmers. (Photo: CIMMYT)

CIMMYT’s projects in Latin America feature in a new report that aims to help countries use data to design public policies and projects that help achieve the Sustainable Development Goals (SDGs) by 2030.

The Counting on The World to Act report was released on September 23, 2019, by the Sustainable Development Solutions Network (SDSN) and the Thematic Research Network on Data and Statistics (TReNDS) during the 74th session of the United Nations General Assembly (UNGA 74) in New York City.

The report describes CIMMYT’s data management systems and tools as examples of “frontier technologies” for data gathering, management and analysis that effectively contribute to sustainable farming in Colombia, Guatemala and Mexico.

“As part of the data revolution, efficiencies are being derived from lower-tech approaches such as using citizen-generated data and smartphones to speed up existing survey-based approaches,” reads the introduction to CIMMYT’s sidebar story in Chapter 4, Incentives for Innovation.

The MasAgro Electronic Log that field technicians use to monitor crop cycles and management practices, and the AgroTutor application that offers farmers more specific and timely recommendations are some of the new affordable tools for data management that CIMMYT is successfully implementing in Latin America.

Read the full report on the TReNDS website.

Read more about MasAgro’s work for sustainable farming in Latin America here.

CIMMYT research at the forefront of the digital revolution in African agriculture

At the African Green Revolution Forum 2019, global and African leaders come together to develop actionable plans that will move African agriculture forward. This year, the forum is taking place in Ghana on the week of September 3, 2019, under the theme “Grow digital: Leveraging digital transformation to drive sustainable food systems in Africa.” Participants will explore the practical application of the emerging elements of the digital era such as big data, blockchain, digital IDs, drones, machine learning, robotics, and sensors.

CIMMYT’s work in this area is showcased in a new leaflet entitled “Data-driven solutions for Africa: Using smart tools to combat climate change.” The leaflet highlights innovations such as crowdsourced crop disease tracking and response systems in Ethiopia, low-cost imaging tools to speed up the development of hardier varieties, and combining geospatial data with crop models to predict climate change and deliver personalized recommendations to farmers.

A new publication highlights the diverse ways in which CIMMYT's research is propelling the digital transformation of agriculture in Africa.
A new publication highlights the diverse ways in which CIMMYT’s research is propelling the digital transformation of agriculture in Africa.

Speaking at the conference attended by 2,000 delegates and high-level dignitaries, CIMMYT Director General Martin Kropff will give the keynote remarks during the session “Digital innovations to strengthen resilience for smallholders in African food systems” on September 3. This panel discussion will focus on how the data revolution can support African smallholder farmers to adapt quickly challenges like recurrent droughts or emerging pests, including the invasive fall armyworm. The Global Resilience Partnership (GRP), the Food and Agriculture Organization of the United Nations (FAO), CABI, and the Minister of Agriculture of Burkina Faso will be among the other panelists in the session.

The same day, CIMMYT will also participate to an important “Agronomy at scale through data for good” panel discussion with speakers from the Bill & Melinda Gates Foundation, research organizations and private companies. The session will highlight how digital agriculture could help deliver better targeted, site-specific agronomic advice to small farmers.

During the forum, the CIMMYT delegation will seek collaborations in other important drivers of change like gender transformation of food systems and smallholder mechanization.

They will join public sector leaders, researchers, agri-preneurs, business leaders and farmers in outlining how to leverage the growth in digital technologies to transform food systems and agricultural livelihoods in Africa.

New platform rapidly diagnoses wheat rust

“Knowing which strain you have is critical information that can be incorporated into early warning systems and results in more effective control of disease outbreaks in farmer’s fields” said Dr. Dave Hodson, a rust pathologist at CIMMYT in Ethiopia and co-author of the paper “MARPLE, a point-of-care, strain-level disease diagnostics and surveillance tool for complex fungal pathogens.” Read more here.

Using the MARPLE kit to diagnose wheat rust in Ethiopia

MARPLE (Mobile and Real-time PLant disEase) Diagnostics is a revolutionary mobile lab developed by a team from the John Innes Centre (JIC), the International Maize and Wheat Improvement Center (CIMMYT) and the Ethiopian Institute of Agricultural Research (EIAR). It uses nanopore sequence technology to rapidly diagnose and monitor wheat rust in farmers’ fields.

Designed to be used without constant electricity and in varying temperatures, the suitcase-sized lab allows researchers to identify wheat rust to strain level in just 48 hours — something that used to take months using other tools.

The MARPLE team was recognized as Innovator of the Year for international impact in 2019 by the UK Biotechnology and Biological Sciences Research Council (BBSRC).

A new video from the John Innes Centre shows how the MARPLE Diagnostics kit will allow Ethiopia to quickly identify wheat rust strains, instead of sending samples to labs abroad.

How the data revolution could help design better agronomic investments

Profitability under different fertilization recommendation scenarios in Ethiopia and Tanzania, measured in U.S. dollars per hectare.
Profitability under different fertilization recommendation scenarios in Ethiopia and Tanzania, measured in U.S. dollars per hectare.

What fertilizer application will give me the best returns? What maize crop variety should I use?

Each farmer faces constraints related to weather uncertainty, soil fertility management challenges, or access to finance and markets. To improve their yields and incomes, African smallholder farmers need agronomic advice adapted to their specific circumstances. The challenge is even greater in sub-Saharan Africa, where agricultural production landscapes are highly diverse. Yet traditional agronomic research was not designed to fit with complex agroecological regions and farming systems. Compounding the problem, research organizations often have limited resources to develop the necessary experiments to generate farm- and site-specific agronomic advice at scale.

“Agronomic research is traditionally not equipped to consider spatial or socio-economic diversity among the millions of farmers it targets,” said Sebastian Palmas, data scientist at the International Maize and Wheat Improvement Center (CIMMYT) in Nairobi, Kenya.

Palmas presented some of the learnings of the Taking Maize Agronomy to Scale in Africa (TAMASA) project during a science seminar called “A spatial ex ante framework for guiding agronomic investments in sub-Saharan Africa on March, 4, 2019.

The project, funded by the Bill & Melinda Gates Foundation, has used data to improve the way agronomic research for development is done. Researchers working on the TAMASA project addressed this challenge by using available geospatial information and other big data resources, along with new data science tools such as machine learning and Microsoft’s AI for Earth. They were able to produce and package information that can help farmers, research institutions and governments take better decisions on what agronomic practices and investments will give them the best returns.

By adapting the Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model to the conditions of small farmers in TAMASA target countries (Ethiopia, Nigeria and Tanzania), using different layers of information, CIMMYT and its partners have developed a versatile geospatial tool for evaluating crop yield responses to fertilizer applications in different areas of a given country. Because calculations integrate spatial variation of fertilizer and grain prices, the tool evaluates the profitability — a key factor influencing farmers’ fertilizer usage — for each location. The project team can generate maps that show, for instance, the estimated agronomic and economic returns to different fertilizer application scenarios.

The TAMASA team plans to publish the code and user-friendly interface of this new geospatial assessment tool later this year. (Photo: CIMMYT)
The TAMASA team plans to publish the code and user-friendly interface of this new geospatial assessment tool later this year. (Photo: CIMMYT)

Making profits grow

These tools could potentially help national fertilizer subsidy programs be more targeted and impactful, like the ambitious Ethiopia’s Fertilizer Blending initiative which distributes up to 250,000 tons of fertilizer annually. Initial calculations showed that, by optimizing diammonium phosphate (DAP) and urea application, the profitability per hectare could improve by 14 percent on average, compared to the current fertilizer recommendations.

Such an approach could generate farm-specific advice at scale and boost farmers’ incomes. It could also provide insights on many different issues, like estimating market demand for a new fertilizer blend, or the estimated quantity of additional fertilizer required to bring about a targeted maize yield increase.

Future extensions of the framework may incorporate varietal differences in nutrient management responses, and thus enable seed companies to use the framework to predict where a new maize hybrid would perform best. Similarly, crop breeders could adapt this ex ante assessment tool to weigh the pros and cons of a specific trait and the potential impact for farmers.

The TAMASA team plans to publish the code and user-friendly interface of this new geospatial assessment tool later this year.

The Molecular Maize Atlas encourages genetic diversity

Maize ears from CIMMYT's collection, showing a wide variety of colors and shapes. CIMMYT's germplasm bank contains about 28,000 unique samples of cultivated maize and its wild relatives, teosinte and Tripsacum. These include about 26,000 samples of farmer landraces — traditional, locally-adapted varieties that are rich in diversity. The bank both conserves this diversity and makes it available as a resource for breeding. (Photo: Xochiquetzal Fonseca/CIMMYT)
Maize ears from CIMMYT’s collection, showing a wide variety of colors and shapes. CIMMYT’s germplasm bank contains about 28,000 unique samples of cultivated maize and its wild relatives, teosinte and Tripsacum. These include about 26,000 samples of farmer landraces — traditional, locally-adapted varieties that are rich in diversity. The bank both conserves this diversity and makes it available as a resource for breeding. (Photo: Xochiquetzal Fonseca/CIMMYT)

Imagine walking through a grocery store, doing your weekly shopping. Everything seems normal, but as you pick up a can, there’s no label. There’s nothing to tell you what the product is, and now you can’t reliably choose anything to eat this week.

Now switch gears and imagine a germplasm bank. Without the right labeling on these different varieties, it’s difficult to tell what’s new and what’s already been discovered when working on new research projects.

That’s where the Molecular Maize Atlas steps into play.

About nine years ago, the International Maize and Wheat Improvement Center (CIMMYT) started an initiative called the Seeds of Discovery (SeeD). This initiative facilitates easier access to and use of maize and wheat genetic resources.

SeeD achieves impact through five main components: genotyping, phenotyping, software tools, pre-breeding and capacity building.

“One of the aims of Seeds of Discovery was to best characterize germplasm,” says Sarah Hearne, a molecular geneticist and maize lead of SeeD. “At CIMMYT, our international germplasm bank holds in trust one of the largest and most diverse publicly available maize collections in the world.”

However, Hearne says this germplasm bank used to look like a grocery store without any labels or without labels that would allow someone to select a can of value. To combat this, SeeD decided to work on a labeling process for the germplasm bank: the Molecular Maize Atlas.

The Molecular Maize Atlas is an information platform that brings genotypic data resources and associated tools together. This genotypic data provides unifying information across landraces and acts as a common backbone, which other valuable information, like phenotypic data, can be added to.

Read the full article on SeedWorld.

Digital imaging tools make maize breeding much more efficient

Mainassara Zaman-Allah conducts a demonstration of the use of unmanned aerial vehicles (UAV) at the Chiredzi research station in Zimbabwe.
Mainassara Zaman-Allah conducts a demonstration of the use of unmanned aerial vehicles (UAV) at the Chiredzi research station in Zimbabwe.

To keep up with growing maize demand, breeders aim at optimizing annual yield gain under various stress conditions, like drought or low fertility soils. To that end, they identify the genetic merit of each individual plant, so they can select the best ones for breeding.

To improve that process, researchers at the International Maize and Wheat Improvement Center (CIMMYT) are looking at cost-effective ways to assess a larger number of maize plants and to collect more accurate data related to key plant characteristics. Plant phenotyping looks at the interaction between the genetic make-up of a plant with the environment, which produces certain characteristics or traits. In maize, for example, this may manifest in different leaf angles or ear heights.

Recent innovations in digital imagery and sensors save money and time in the collection of data related to phenotyping. These technologies, known as high-throughput phenotyping platforms, replace lengthy paper-based visual observations of crop trials.

Authors of a recent review study on high-throughput phenotyping tools observe that obtaining accurate and inexpensive estimates of genetic value of individuals is central to breeding. Mainassara Zaman-Allah, an abiotic stress phenotyping specialist at CIMMYT in Zimbabwe and one of the co-authors, emphasizes the importance of improving existing tools and developing new ones. “Plant breeding is a continuously evolving field where new tools and methods are used to develop new varieties more precisely and rapidly, sometimes at reduced financial resources than before,” he said. “All this happens to improve efficiency in breeding, in order to address the need for faster genetic gain and reduction of the cost of breeding.”

“Under the Stress Tolerant Maize for Africa (STMA) project, we are working on implementing the use of drone-based sensing, among other breeding innovations, to reduce time and cost of phenotyping, so that the development of new varieties costs less,’’ said Zaman-Allah. “The use of drones cuts time and cost of data collection by 25 to 75 percent  compared to conventional methods, because it enables to collect data on several traits simultaneously — for example canopy senescence and plant count,” he explained.

Another great innovation developed under this CIMMYT project is what Zaman-Allah calls the ear analyzer. This low-cost digital imaging app allows to collect maize ear and kernel trait data 90 percent faster. This implies higher productivity and rigor, as more time is dedicated to data analysis rather than time spent on data collection. Using digital image processing, the ear analyzer gives simultaneous data of more than eight traits, including ear size and number, kernel number, size and weight.

Measuring maize attributes such as ear size, kernel number and kernel weight is becoming faster and simpler through digital imaging technologies.
Measuring maize attributes such as ear size, kernel number and kernel weight is becoming faster and simpler through digital imaging technologies.

Some national agricultural research systems and NGOs have adopted this digital imagery tool to better assess maize yields in farmers’ fields. For instance, CIMMYT and GOAL have used this tool to assess the extent of fall armyworm impact on maize crops yield in eastern Zimbabwe.

Scientists are exploring the use of different sensors for phenotyping, such as Red, Green and Blue (RGB) digital imaging or Light Detection and Ranging (LIDAR) devices. Infrared thermal and spectral cameras could lead to further progress towards faster maize breeding.

Such sensors can help collect numerous proxy data relating to important plant physiological traits or the plant environment, like plant height and architecture, soil moisture and root characteristics. This data can be used to assess the maize crop yield potential and stress tolerance.

Such breeding innovations are also making maize research more responsive to climate change and emerging pests and diseases.