Science intro session
•
0 gefällt mir•24 views
An introduction to the ACAI science behind the development of the AKILIMO decision support tools
Melden
Teilen
Melden
Teilen
Downloaden Sie, um offline zu lesen
Empfohlen
A preview of the results from the validation trials of the recommendations for Scheduled Planting and High Starch content for cassavaScheduled Planting and High Starch Content validation results for AKILIMO
Scheduled Planting and High Starch Content validation results for AKILIMOAfrican Cassava Agronomy Initiative
A preview of the results from the validation trials of site-specific fertilizer recommendation in Nigeria and TanzaniaTailored Fertilizer Recommendation validation results for AKILIMO
Tailored Fertilizer Recommendation validation results for AKILIMOAfrican Cassava Agronomy Initiative
Empfohlen
A preview of the results from the validation trials of the recommendations for Scheduled Planting and High Starch content for cassavaScheduled Planting and High Starch Content validation results for AKILIMO
Scheduled Planting and High Starch Content validation results for AKILIMOAfrican Cassava Agronomy Initiative
A preview of the results from the validation trials of site-specific fertilizer recommendation in Nigeria and TanzaniaTailored Fertilizer Recommendation validation results for AKILIMO
Tailored Fertilizer Recommendation validation results for AKILIMOAfrican Cassava Agronomy Initiative
Presentation highlighting the process and progress of developing the Summary of the field activities towards the development of the SP and HS DSTs, focusing on a combined DST recommending the time of planting and/or harvest to optimize root or starch supply (and revenue) to cassava processors, for both processors and cassava growers.
After two years of field experimentation, the database currently holds yield data from 79 SP trials (combinations of location, planting date, harvest age), and close to 4,000 starch measurements across trials from all use cases.
Most important findings in year 2 include (i) cassava root yield is controlled for a large extent to crop age and month of harvest in Nigeria, but in Tanzania, year-to-year variation is much larger, likely related to variation in rainfall across the growing season, (ii) starch concentration is controlled by harvest month in Nigeria and this is largely stable across years likely due to comparability of rainfall across years, but not so in Tanzania, and (iii) results confirm that starch concentration is not affected by fertilizer application or tillage management.
Inconsistent effects across years emphasize the need for better insights in the processes controlling yield and starch concentration through mechanistic models. LINTUL appears not to adequately predict the impact of rainfall during crop growth on dry matter accumulation. LINTUL does not seem to penalize ‘older’ cassava in the growth season, and underestimate growth and starch accumulation of a ‘medium’ cassava during the dry season…
Advances with the DST development; Modelling framework, the Decision Support Tool were presented, along with the ongoing validation exercises, with over 350 trials currently established to evaluate impact of harvest month on yield. First impressions illustrate that farmers have difficulties to anticipate the price variation across the harvest period, which is an important driver for decision making. The exercise is appreciated as it stimulates farmers and extension agents to reflect on the impact of planting date and harvest date on total revenue, which is often thought of as ‘less important’.
Session 2 4 Development of the Scheduled Planting (SP) and High Starch Conten...
Session 2 4 Development of the Scheduled Planting (SP) and High Starch Conten...African Cassava Agronomy Initiative
Presentation highlighting the process and progress of developing the Summary of the field activities towards the development of the BPP DST
The field trials on BPP had initially a 4 factorial structure with three ploughing regimes followed by ridging versus flat soil and planting at two densities (10000 vs. 12500) and fertilizer application versus nil. This was reduced to three factors and a reduction in ploughing intensity. In the first and second year it transpired that weed interference as a consequence of initial soil tillage, was potentially a major cause of root yield variation and this required the integration of weed control as a factor, which happened in year 3. Further, farmers’ reasons for ploughing were not fully understood and may have confounded tillage intensity with soil fertility. The latest version of the BPP DST will require the inclusion of fallow length and vegetation characteristics to better assess the reasons for intensive ploughing and exclude recommendations of such practices in sites of different fallow and land use history.
For 2019 the BPP will form the base for the integration of weed control aspect into ACAI and this will likely improve the BPP DST through appropriate weed control recommendations and fine tune post emergence weed control requirements and measures as a function of previous tillage.
Session 2 3 Development of the Best Planting Practices Decision Support Tool
Session 2 3 Development of the Best Planting Practices Decision Support ToolAfrican Cassava Agronomy Initiative
Cassava intercropping with Sweet potato (CIS) trials aim to evaluate the land equivalent ratio of cassava - sweet potato intercropping systems, and methods to optimize intercropping practices for maximal revenue.
The CIS trials (2018) have been set up in Zanzibar in 8 clusters in Zanzibar. The study ascertains recommended plant densities and appropriate timing of introducing sweet potato as associated crop. Findings confirm that (i) cassava-sweet potato intercropping systems have LERs exceeding 1, and that (ii) farmers’ practice, with simultaneous planting of both crops at reduced densities of 10,000 sweet potato vines per hectare is optimal. Further yield increases can be achieved through fertilizer application, and the relative cost and revenue from both crops should be considered in decision-making on intercropping cassava.
Cassava intercrop maize (CIM) recommends intensification options in cassava-maize intercropping systems. A comparison of our recommendation with the best performing plot at an individual site showed that for 31% of the farms (where maize was already harvested) this advice was correct and 9% would have lost money due to the investment in fertilizer. The tool proved to be conservative, often not recommending investment in fertilizer where this would have increased revenue.
For the DST version of 2019, we will improve on the indicators for maize and review with our partners whether the value cost ratio should be less conservative, or its level be set by farmers. Increasing the true positive rate (correctly recommend investment when this is profitable) comes along with increases in false positives (recommending investment in fertilizer when not profitable).
Session 2 2 Development of the Best Intercropping Practices Decision Support ...
Session 2 2 Development of the Best Intercropping Practices Decision Support ...African Cassava Agronomy Initiative
This presentation highlighted the process of developing and progress made in the development of the FR and FB DST.
The site-specific fertilizer recommendation (FR) tool is built to provide an optimized and profitable site-specific fertilizer recommendations for cassava growers. The tool considers the location, soil fertility, weather condition, available fertilizers in the area, prices for fertilizer and cassava root, planned planting and harvest dates and the investment capacity of the farmers.
The nutrient omission trials (NOT) in Nigeria and Tanzania conducted by ACAI, in collaboration with the national research and development partners, show a large variation in nutrient responses indicating the need for site-specific fertilizer recommendation. ACAI is developing a crosscutting system using machine learning techniques coupled with process based crop models, LINTUL and QUEFTS, and economic optimizer algorithms to provide the site-specific recommendations. ACAI is transforming available big data like GIS layers from SoilGrids and weather data from CHIRPS and NASA to useful information that can be used to model the relationship between apparent soil nutrient supply and soil properties. Effort has also been made to identify a generic soil fertility indicator that can be easily obtained from farmers and is useful covariate to improve the accuracy of apparent soil nutrient supply predictions.
The next steps in the FR tool development include, validating the FR tool both functionally, checking if the recommendations outperform the current practices in the field and architecturally, checking user friendliness and if the tool satisfies the needs of development partners to dissemination strategy.
Session 2 1 Development of the Site Specific Fertilizer Recommendation (FR) a...
Session 2 1 Development of the Site Specific Fertilizer Recommendation (FR) a...African Cassava Agronomy Initiative
This is a presentation that outlined the ACAI project’s progress, the process of DSTs development and the status of the project and an overview of activities for the last three years of ACAI
Summary of the project - The African Cassava Agronomy Initiative aims at delivering agronomic technologies that improve cassava root yield and quality, and cassava supply to the processing sector, engaging 120,000 farming households through effective partnerships with development partners in Nigeria and Tanzania, supported by the National Agricultural Research Systems, and in collaboration with strategic research institutes. The project consists of six use cases, identified by development partners, and has developed decision support tools, supplying tailored or site-specific recommendations on fertilizer use, fertilizer blend formulations, tillage practices, intercropping and scheduled planting and harvest and high starch content.
The knowledge needed to develop these decision support tools is generated by applying the principles of “Agronomy at Scale”, combining field trials to test and develop best agronomic interventions, modelling to build prediction models, GIS and spatial modelling to extrapolate recommendations across the target intervention area, development of DSTs to supply recommendations through a practical field tool, and extension activities to scale the use of the tools within partner networks.
The implementation progress per six work streams: (i) strategic agronomy research and crop modelling, (ii) geospatial analysis and data management, (iii) DST development, (iv) facilitation of use of the DSTs, (v) Capacity development of national research institutions, (vi) Project governance, management, coordination, and M&E.
Session 1 1 acai overview and progress with project implementation
Session 1 1 acai overview and progress with project implementationAfrican Cassava Agronomy Initiative
Weitere ähnliche Inhalte
Mehr von African Cassava Agronomy Initiative
Presentation highlighting the process and progress of developing the Summary of the field activities towards the development of the SP and HS DSTs, focusing on a combined DST recommending the time of planting and/or harvest to optimize root or starch supply (and revenue) to cassava processors, for both processors and cassava growers.
After two years of field experimentation, the database currently holds yield data from 79 SP trials (combinations of location, planting date, harvest age), and close to 4,000 starch measurements across trials from all use cases.
Most important findings in year 2 include (i) cassava root yield is controlled for a large extent to crop age and month of harvest in Nigeria, but in Tanzania, year-to-year variation is much larger, likely related to variation in rainfall across the growing season, (ii) starch concentration is controlled by harvest month in Nigeria and this is largely stable across years likely due to comparability of rainfall across years, but not so in Tanzania, and (iii) results confirm that starch concentration is not affected by fertilizer application or tillage management.
Inconsistent effects across years emphasize the need for better insights in the processes controlling yield and starch concentration through mechanistic models. LINTUL appears not to adequately predict the impact of rainfall during crop growth on dry matter accumulation. LINTUL does not seem to penalize ‘older’ cassava in the growth season, and underestimate growth and starch accumulation of a ‘medium’ cassava during the dry season…
Advances with the DST development; Modelling framework, the Decision Support Tool were presented, along with the ongoing validation exercises, with over 350 trials currently established to evaluate impact of harvest month on yield. First impressions illustrate that farmers have difficulties to anticipate the price variation across the harvest period, which is an important driver for decision making. The exercise is appreciated as it stimulates farmers and extension agents to reflect on the impact of planting date and harvest date on total revenue, which is often thought of as ‘less important’.
Session 2 4 Development of the Scheduled Planting (SP) and High Starch Conten...
Session 2 4 Development of the Scheduled Planting (SP) and High Starch Conten...African Cassava Agronomy Initiative
Presentation highlighting the process and progress of developing the Summary of the field activities towards the development of the BPP DST
The field trials on BPP had initially a 4 factorial structure with three ploughing regimes followed by ridging versus flat soil and planting at two densities (10000 vs. 12500) and fertilizer application versus nil. This was reduced to three factors and a reduction in ploughing intensity. In the first and second year it transpired that weed interference as a consequence of initial soil tillage, was potentially a major cause of root yield variation and this required the integration of weed control as a factor, which happened in year 3. Further, farmers’ reasons for ploughing were not fully understood and may have confounded tillage intensity with soil fertility. The latest version of the BPP DST will require the inclusion of fallow length and vegetation characteristics to better assess the reasons for intensive ploughing and exclude recommendations of such practices in sites of different fallow and land use history.
For 2019 the BPP will form the base for the integration of weed control aspect into ACAI and this will likely improve the BPP DST through appropriate weed control recommendations and fine tune post emergence weed control requirements and measures as a function of previous tillage.
Session 2 3 Development of the Best Planting Practices Decision Support Tool
Session 2 3 Development of the Best Planting Practices Decision Support ToolAfrican Cassava Agronomy Initiative
Cassava intercropping with Sweet potato (CIS) trials aim to evaluate the land equivalent ratio of cassava - sweet potato intercropping systems, and methods to optimize intercropping practices for maximal revenue.
The CIS trials (2018) have been set up in Zanzibar in 8 clusters in Zanzibar. The study ascertains recommended plant densities and appropriate timing of introducing sweet potato as associated crop. Findings confirm that (i) cassava-sweet potato intercropping systems have LERs exceeding 1, and that (ii) farmers’ practice, with simultaneous planting of both crops at reduced densities of 10,000 sweet potato vines per hectare is optimal. Further yield increases can be achieved through fertilizer application, and the relative cost and revenue from both crops should be considered in decision-making on intercropping cassava.
Cassava intercrop maize (CIM) recommends intensification options in cassava-maize intercropping systems. A comparison of our recommendation with the best performing plot at an individual site showed that for 31% of the farms (where maize was already harvested) this advice was correct and 9% would have lost money due to the investment in fertilizer. The tool proved to be conservative, often not recommending investment in fertilizer where this would have increased revenue.
For the DST version of 2019, we will improve on the indicators for maize and review with our partners whether the value cost ratio should be less conservative, or its level be set by farmers. Increasing the true positive rate (correctly recommend investment when this is profitable) comes along with increases in false positives (recommending investment in fertilizer when not profitable).
Session 2 2 Development of the Best Intercropping Practices Decision Support ...
Session 2 2 Development of the Best Intercropping Practices Decision Support ...African Cassava Agronomy Initiative
This presentation highlighted the process of developing and progress made in the development of the FR and FB DST.
The site-specific fertilizer recommendation (FR) tool is built to provide an optimized and profitable site-specific fertilizer recommendations for cassava growers. The tool considers the location, soil fertility, weather condition, available fertilizers in the area, prices for fertilizer and cassava root, planned planting and harvest dates and the investment capacity of the farmers.
The nutrient omission trials (NOT) in Nigeria and Tanzania conducted by ACAI, in collaboration with the national research and development partners, show a large variation in nutrient responses indicating the need for site-specific fertilizer recommendation. ACAI is developing a crosscutting system using machine learning techniques coupled with process based crop models, LINTUL and QUEFTS, and economic optimizer algorithms to provide the site-specific recommendations. ACAI is transforming available big data like GIS layers from SoilGrids and weather data from CHIRPS and NASA to useful information that can be used to model the relationship between apparent soil nutrient supply and soil properties. Effort has also been made to identify a generic soil fertility indicator that can be easily obtained from farmers and is useful covariate to improve the accuracy of apparent soil nutrient supply predictions.
The next steps in the FR tool development include, validating the FR tool both functionally, checking if the recommendations outperform the current practices in the field and architecturally, checking user friendliness and if the tool satisfies the needs of development partners to dissemination strategy.
Session 2 1 Development of the Site Specific Fertilizer Recommendation (FR) a...
Session 2 1 Development of the Site Specific Fertilizer Recommendation (FR) a...African Cassava Agronomy Initiative
This is a presentation that outlined the ACAI project’s progress, the process of DSTs development and the status of the project and an overview of activities for the last three years of ACAI
Summary of the project - The African Cassava Agronomy Initiative aims at delivering agronomic technologies that improve cassava root yield and quality, and cassava supply to the processing sector, engaging 120,000 farming households through effective partnerships with development partners in Nigeria and Tanzania, supported by the National Agricultural Research Systems, and in collaboration with strategic research institutes. The project consists of six use cases, identified by development partners, and has developed decision support tools, supplying tailored or site-specific recommendations on fertilizer use, fertilizer blend formulations, tillage practices, intercropping and scheduled planting and harvest and high starch content.
The knowledge needed to develop these decision support tools is generated by applying the principles of “Agronomy at Scale”, combining field trials to test and develop best agronomic interventions, modelling to build prediction models, GIS and spatial modelling to extrapolate recommendations across the target intervention area, development of DSTs to supply recommendations through a practical field tool, and extension activities to scale the use of the tools within partner networks.
The implementation progress per six work streams: (i) strategic agronomy research and crop modelling, (ii) geospatial analysis and data management, (iii) DST development, (iv) facilitation of use of the DSTs, (v) Capacity development of national research institutions, (vi) Project governance, management, coordination, and M&E.
Session 1 1 acai overview and progress with project implementation
Session 1 1 acai overview and progress with project implementationAfrican Cassava Agronomy Initiative
Mehr von African Cassava Agronomy Initiative (20)
Session 1 3 acai_development partners presentation Tanzania
Session 1 3 acai_development partners presentation Tanzania
Session 2 4 Development of the Scheduled Planting (SP) and High Starch Conten...
Session 2 4 Development of the Scheduled Planting (SP) and High Starch Conten...
Session 2 3 Development of the Best Planting Practices Decision Support Tool
Session 2 3 Development of the Best Planting Practices Decision Support Tool
Session 2 2 Development of the Best Intercropping Practices Decision Support ...
Session 2 2 Development of the Best Intercropping Practices Decision Support ...
Session 2 1 Development of the Site Specific Fertilizer Recommendation (FR) a...
Session 2 1 Development of the Site Specific Fertilizer Recommendation (FR) a...
Session 1 2 acai_development partners presentation nigeria
Session 1 2 acai_development partners presentation nigeria
Session 1 1 acai overview and progress with project implementation
Session 1 1 acai overview and progress with project implementation
Kürzlich hochgeladen
Kürzlich hochgeladen (20)
TEST BANK For Radiologic Science for Technologists, 12th Edition by Stewart C...
TEST BANK For Radiologic Science for Technologists, 12th Edition by Stewart C...
Chemical Tests; flame test, positive and negative ions test Edexcel Internati...
Chemical Tests; flame test, positive and negative ions test Edexcel Internati...
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Nightside clouds and disequilibrium chemistry on the hot Jupiter WASP-43b
Nightside clouds and disequilibrium chemistry on the hot Jupiter WASP-43b
Feature-aligned N-BEATS with Sinkhorn divergence (ICLR '24)
Feature-aligned N-BEATS with Sinkhorn divergence (ICLR '24)
Call Girls Alandi Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Alandi Call Me 7737669865 Budget Friendly No Advance Booking
SAMASTIPUR CALL GIRL 7857803690 LOW PRICE ESCORT SERVICE
SAMASTIPUR CALL GIRL 7857803690 LOW PRICE ESCORT SERVICE
FAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
FAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
Pulmonary drug delivery system M.pharm -2nd sem P'ceutics
Pulmonary drug delivery system M.pharm -2nd sem P'ceutics
Science intro session
- 2. • •
- 3. • • • • • •
- 5. V0 (concept) Literature-based V1 (prototype) Experimental data V2 (pilot tool) Validated VF (ready tool) N x validated Start 1st round of validation exercises (NG) Start 1st round of validation exercises (TZ)
- 6. • • • • • •
- 7. • • • • •