Varieties with diverse maturity class,
Striga and drought-tolerant maize varieties
Soil fertility management technologies
Good agronomic practices e.g. planting dates
Yam has the advantage of utilizing the nutrient reserve accumulated when the soil is rested. Limited knowledge exists on the nutrient uptake patterns of the D. rotundata grown under field conditions. This study examined the effect of fertilizer application on growth pattern and yield of yam.
Maize grain yield is greatly constrained by the parasitic weed, Striga hermonthica. Levels of infestation are often so high that
maize can suffer total yield loss and farmers usually abandon severely infested fields.
Remote sensing –Beyond images
Mexico 14-15 December 2013
The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
How can ‘Yield gap analysis’ be useful :Global yield gap atlas (gyga)ICRISAT
The Global Yield Gap Atlas provides important information on the capacities of various countries to be self-sufficient in staple food crop production now and in the future. So far the Atlas has been populated for 24 countries for five major staple crops (maize, wheat, rice, sorghum and millet) and analyses for 25 additional countries is in progress.
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Session: ICTs/Mobile Apps for Management and Use of Agricultural Data
on 7 Nov 2013
ICT4Ag, Kiali, Rwanda
Yam has the advantage of utilizing the nutrient reserve accumulated when the soil is rested. Limited knowledge exists on the nutrient uptake patterns of the D. rotundata grown under field conditions. This study examined the effect of fertilizer application on growth pattern and yield of yam.
Maize grain yield is greatly constrained by the parasitic weed, Striga hermonthica. Levels of infestation are often so high that
maize can suffer total yield loss and farmers usually abandon severely infested fields.
Remote sensing –Beyond images
Mexico 14-15 December 2013
The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
How can ‘Yield gap analysis’ be useful :Global yield gap atlas (gyga)ICRISAT
The Global Yield Gap Atlas provides important information on the capacities of various countries to be self-sufficient in staple food crop production now and in the future. So far the Atlas has been populated for 24 countries for five major staple crops (maize, wheat, rice, sorghum and millet) and analyses for 25 additional countries is in progress.
Presentation by Eskender Beza, João Vasco Silva, Pytrik Reidsma, Martin Herold, Lammert Kooistra, Laboratory of Geo-Information Science and Remote Sensing and Plant Production System (PPS)
Session: ICTs/Mobile Apps for Management and Use of Agricultural Data
on 7 Nov 2013
ICT4Ag, Kiali, Rwanda
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this project seeks to calibrate and evaluate the Agricultural Production Systems Simulator(APSIM) model for simulating the response of two maize cultivars(2009 EVDT and IWDC2) to applied nitrogen.
Precision agriculture (PA) / Satellite farming (SF) or Site specific crop management (SSCM) is based on: observing, measuring and responding to inter and intra-field variability in crops. Learn More.
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The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
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Assessment of wheat yield gap in Central AsiaExternalEvents
Within the context of increasing global population, food demands and climate change, a yield assessment was conducted by ICARDA of wheat production both under rainfed and irrigation conditions in Kazakhstan, Kyrgyzstan, Tajikistan and Uzbekistan. The research included the identification of the causes of yield gaps as well as the development of management options to reduce these gaps.
Precision Farming helps findout nutrient and micro nutrient deficiency in minute areas of soils and enables application of nutrients/micro nutrients in the soil where deficiency exists. This saves money and helps soil improvement.
Oral presentation made at the 19th European Association for Potato Research (EAPR) Conference held in Brussels on 7-11 July 2014. It is about a Potato Yield Gap Analysis study for Sub Saharan Africa through Participatory Modeling being conducted by the International Potato Center (CIP).
this project seeks to calibrate and evaluate the Agricultural Production Systems Simulator(APSIM) model for simulating the response of two maize cultivars(2009 EVDT and IWDC2) to applied nitrogen.
Precision agriculture (PA) / Satellite farming (SF) or Site specific crop management (SSCM) is based on: observing, measuring and responding to inter and intra-field variability in crops. Learn More.
Trends and Determinants of Cereal Productivity: Econometric ANalysis of Natio...essp2
Ethiopian Development Research Institute (EDRI) and International Food Policy Research Institute (IFPRI), Seventh International Conference on Ethiopian Economy, June 24, 2010
Bangladesh though a LDC have generated national database on Land and Soil Resources which is mainly used for agricultural development planning and farmers service. SOLARIS and OFRS are two systems dealing with the NR database to generate output needed by academicians, researchers, extentionists and farmers
Precision Agriculture: a concise introduction Joseph Dwumoh
The presentation supplies a brief introduction to what precision agriculture is, what drives its adoption, and what challenges the acceptance of the technologies involved.
Welcome to the Remote Sensing – Beyond Images WorkshopCIMMYT
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Agronomy and crop-livestock interaction activities in Ghana 2019/20 africa-rising
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Many ways to support street children.pptxSERUDS INDIA
By raising awareness, providing support, advocating for change, and offering assistance to children in need, individuals can play a crucial role in improving the lives of street children and helping them realize their full potential
Donate Us
https://serudsindia.org/how-individuals-can-support-street-children-in-india/
#donatefororphan, #donateforhomelesschildren, #childeducation, #ngochildeducation, #donateforeducation, #donationforchildeducation, #sponsorforpoorchild, #sponsororphanage #sponsororphanchild, #donation, #education, #charity, #educationforchild, #seruds, #kurnool, #joyhome
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Recordings are on YouTube and the company website.
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By raising awareness, providing support, advocating for change, and offering assistance to children in need, individuals can play a crucial role in improving the lives of street children and helping them realize their full potential
Donate Us
https://serudsindia.org/how-individuals-can-support-street-children-in-india/
#donatefororphan, #donateforhomelesschildren, #childeducation, #ngochildeducation, #donateforeducation, #donationforchildeducation, #sponsorforpoorchild, #sponsororphanage #sponsororphanchild, #donation, #education, #charity, #educationforchild, #seruds, #kurnool, #joyhome
This session provides a comprehensive overview of the latest updates to the Uniform Administrative Requirements, Cost Principles, and Audit Requirements for Federal Awards (commonly known as the Uniform Guidance) outlined in the 2 CFR 200.
With a focus on the 2024 revisions issued by the Office of Management and Budget (OMB), participants will gain insight into the key changes affecting federal grant recipients. The session will delve into critical regulatory updates, providing attendees with the knowledge and tools necessary to navigate and comply with the evolving landscape of federal grant management.
Learning Objectives:
- Understand the rationale behind the 2024 updates to the Uniform Guidance outlined in 2 CFR 200, and their implications for federal grant recipients.
- Identify the key changes and revisions introduced by the Office of Management and Budget (OMB) in the 2024 edition of 2 CFR 200.
- Gain proficiency in applying the updated regulations to ensure compliance with federal grant requirements and avoid potential audit findings.
- Develop strategies for effectively implementing the new guidelines within the grant management processes of their respective organizations, fostering efficiency and accountability in federal grant administration.
Simulating response of drought-tolerant maize varieties to planting dates in contrasting Agro-ecologies of Nigeria Savannas
1. www.iita.org I www.cgiar.org
Simulating response of drought-tolerant
maize varieties to planting dates in
contrasting Agro-ecologies of Nigeria
Savannas
By
Abdullahi I. Tofa1,2
, A. Y. Kamara1
, U. F. Chiezey2
, B. A.
Babaji2
1
International Institute of Tropical Agriculture, Kano State,
2
Ahmadu Bello University, P.M.B. 1045, Zaria, Kaduna State
21st
Annual Symposium IARSAF
2. www.iita.org I www.cgiar.org
Introduction
• Maize production in Nigeria
has increased nearly ten-fold
between1961 and 2013
• Average yield level was less
than 2.0 t/ha compared to 9.5
t/ha USA and the world
average of 5.5 t/ha
• The increased production is
mainly due to increase in
cultivated land
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
0
2000
4000
6000
8000
10000
12000
Area (000 ha)
Production (000 t)
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
Maizeyield(kg/ha)
0
500
1000
1500
2000
2500
3. www.iita.org I www.cgiar.org
Introduction cont…
• Maize yields in Nigeria are
low due to a myriad of
reasons including:
– poor soil fertility
– moisture stress
– pests and diseases
– inappropriate agronomic
practices
Resultedto ahugegapbetween
attainableyieldandwhat is
obtainedbysmallholderfarmers
4. www.iita.org I www.cgiar.org
Opportunities to increase
productivity of maize in the Nigeria
Savannas Varieties with diverse maturity class,
Striga and drought-tolerant maize varieties
Soil fertility management technologies
Good agronomic practices e.g. planting dates
• Planting too early may result in crop failure due to drought and, in turn, planting too late might
reduce valuable growing time and crop yield.
• Optimum planting date allows crops to best utilized moisture, nutrients and solar radiation.
5. www.iita.org I www.cgiar.org
Problem of deployment of maize production
technologies
Reports on the performance of these technologies are largely
site specific
To assess the performance of these technologies on large scale
could require time and expensive experiments
Dominant soils Rainfall distribution Length of growing season
6. www.iita.org I www.cgiar.org
Opportunities for Use of Cropping
System Models to deploy Crop
technologies CSMs like CERES-Maize present opportunity for extrapolating
short-duration field experimental results to other years and other
locations.
Simulate crop growth, development and yield for specific cultivars
based on the effects of weather, soil characteristics and crop
management practices.
Multi-locational evaluation and assessment of the adaptation of a
new cultivar to a region and climate.
Support the decision making process for cropping system
management and agricultural policy
7. www.iita.org I www.cgiar.org
Objectives of the study
• To evaluate the ability of the model in simulating yield of maize
under varying planting dates in contrasting environments.
8. www.iita.org I www.cgiar.org
Model Calibration and
ValidationCalibration
• Involves the modification of some model parameters such that
data simulated by the error-free model fit the observed data.
• Non-compliance may arise from sampling errors as well as from
incomplete knowledge of the system.
Validation
• Involves the confirmation that the calibrated model closely
represents the real situation
• The most commonly used statistics for model validation are
RMSE and d-index:
9. www.iita.org I www.cgiar.org
Datasets for Model Calibration
& Evaluation
2 field studies were conducted during the 2015 and 2016 wet
seasons at Zaria and Iburu, Nigeria to calibrate and validate
CERES-maize model in DSSAT.
• Selected maize varieties: SAMMAZ 15 and SAMMAZ 16.
• Seasonal weather records: daily rainfall, Tmax, Tmin, SRAD
from 2015 and 2016 used to create weather files.
• Soil profile data for the 2 locations
• Top soil analysis physical and chemical properties data.
• Management practices: planting date, fertilization, weeding, etc
• Experimental data: yields, TDM e.t.c.
10. www.iita.org I www.cgiar.org
Cultivar Genetic coefficients
`
Coefficient Description SAMMAZ
15
SAMMAZ
16
P1 (O
C day-1
)
Thermal time from seedling emergence to the
end of juvenile phase. 283.0 300.0
P2 (day)
Delay in development for each hour that day-
length is above 12.5 hours. 0.678 0.640
P5 (O
C day-1
)
Thermal time from silking to time of
physiological maturity. 845.8 851.1
G2 (grains ear-1
)
Maximum kernel number per
plant. 750.3 668.1
G3 (mg day-1
)
Kernel growth rate during linear grain filling
stage under optimum conditions. 6.54 6.58
PHINT (O
C day-1
)
Thermal time between successive leaf tip
appearance. 44.00 41.51
Cultivar Statistics Anthesis day
(DAP)
Physiological
maturity day
(DAP)
Grain yield
(kg /ha)
Tops weight
(kg /ha)
Harvest
index
SAMMAZ 15 D-Index 0.89 0.87 0.99 0.98 0.84
RMSE 0.50 1.22 66.3 533.4 0.02
SAMMAZ 16 D-Index 0.94 0.94 0.99 0.97 0.90
RMSE 0.71 1.22 68.3 542.9 0.01
Results
Statistical indicators
GCs allow the model to
predict differences among
different cultivars when
planted in the same
environment
vegetative, reproductive and
developmental growth
processes are sensitive to both
temperature and photoperiod
In most cases, each cultivar
has a unique photothermal
requirement to achieve each
of the developmental stages.
Cultivar specific parameters
are therefore used to define
the sensitivity of each cultivar
to day length or night length.
13. www.iita.org I www.cgiar.org
Model application to predict
maize response to planting dates
in three agro-ecological zones
• The seasonal analysis tool of DSSAT Version 4.7
• Model runs using 25 years of historical weather (1990 – 2014) data
for each location.
• Soil profile data for the 3 locations
• 9 Planting dates with 10 days intervals beginning on early June (10)
until late August (29)
20. www.iita.org I www.cgiar.org
Conclusion
CERES–maize model was found to be a useful decision-support tool for maize
researchers in the Savanna regions of Nigeria.
The model predicted that early-June, mid and late August planting decreases mean
grain yield in the 3 agro-ecologies most especially in SS.
In SS, the best planting date was mid-June delaying planting beyond mid-June
consistently decreases grain yield.
In NGS and SGS, the best planting windows is from late-June to mid- July.
Mean grain yield was generally higher in NGS for both varieties.
SAMMAZ 15 the drought tolerant variety generally produced higher grain yield
across the three agro-ecological zones especially with delay plantings.